RichardCox

One of the things that attracts newcomers to technical analysis is the wide variety of indicators that can be used to assess price data in a more objective way. What most people don’t know is that the logic behind many of the most commonly used indicators is relatively similar. This should not be a total surprise because, in some cases, collections of indicators have been created by the same person (J. Welles Wilder would be a primary example). It is, however, possible to make small alterations to these indicators and change the number and type of signals that are received. To take this approach even further, it is possible to plot multiple readings of the same indicator and use the comparative results as a basis for trading decisions. When exiting a trade, market conditions will never be what they were when the trade was opened. At the same time, psychological factors will often cause to hold onto trades too long (usually when markets are working against a trade), or to exit too quickly (once small gains are finally seen). Both of these scenarios have clear drawbacks and can quickly lead to substantial losses. Indicators can help traders avoid some of these situations because these tools arm you with information that describes when a trending move has reached completion and is ready to reverse. For these reasons, it is preferable to wait for technical signals to materialize before pulling the trigger to close a trade, rather than relying on emotional reactions to do the same. Using the MACD to Measure Trends One of the most common indicator tools used by traders is the Moving Average Convergence Divergence (MACD), as it helps to enhance the probabilities in determining the lengths of trending moves. But which parameters should be plotted on the charts? The default settings in trading stations will generally call for the following: The MACD Line subtracts a 12-day EMA from a 26-day EMA. The Signal Line is a 9-day EMA of the MACD Line itself, and acts as a “signal” for trades (identifies potential turning points). Finally, the MACD Histogram is plotted, and shows as either “positive” or “negative.” The Histogram is positive if the MACD rises above the Signal Line. The Histogram is negative if the MACD falls below the Signal Line. These elements can be seen in the charted example. The job of the MACD indicator is to help traders establish trades and then hold those positions until the current move has run its course. This is important because traders will typically spend much more time on their trade entry decisions than they do with their trade exit decisions. While it is a good idea to spend time with your entries, it is ultimately your exits that will determine your level of profit or loss. Tools like the MACD are designed to maximize your strategic decisions and fine tune your exit levels within the larger trend. Understanding the Signals The MACD sends signals to traders in a few different ways. As the name suggests, the indicator focuses on the convergence and divergence seen between the two moving averages. Convergence is found when the moving averages move close together. Divergence is seen when the moving farther apart. The Signal Line is simply an average of the MACD Line. Because of this, the Signal Line will lag behind the MACD Line. When the MACD Line crosses above the signal line, positive momentum is expected and buy positions should be initiated. When the MACD Line crosses below the signal line, negative momentum is expected and sell positions should be initiated. Illustrated examples can be seen in the second chart. In addition to this, buy signals are generated when the MACD Line crosses above the histogram. When the MACD Line crosses back below the histogram, momentum is negative and this is a signal to sell an asset. These signals help traders to know whether or not a specific price move has enough momentum to warrant a new position. As always, multiple signals (such as a Signal Line crossover, combined with a Histogram crossover), add to the validity of any potential positions. Doubling the Indicator for Exits Once you have a firm understanding of how the indicator works, we can change some of the parameters to work off of the traditional way position exits are constructed. In most cases, traders will use the same logic for entering MACD positions as what was seen when the trade idea was initiated (for example, a Signal Line or Histogram crossover). Unfortunately, this will create many scenarios where the trader will exit a position before the entire move is complete. So, while the MACD is helpful in these areas, there are still ways to improve and capture a larger portion of each move. This can be done by adding an additional plotted MACD. The reasoning here is that the faster MACD (which is more sensitive to price changes) can be used to generate signals for position entries (as this helps you spot developing or changing trends). The slower MACD (which is less sensitive to price changes) can then be added to your charts. To do this, you will need to change the parameters when making the addition (as it would make no sense to again use the default settings). The initial MACD would show the difference between the 12-day and 26-day moving averages. For the slower MACD, we can raise this to show the difference between the 19-day and 39-day moving averages. The Signal Line can be kept constant as a 9-day average of the MACD. The signals generated by this additional MACD plot can be used for exiting positions. So, for example, if we are in a long position, and the second MACD plot shows a negative cross of the Signal Line and/or a cross below the Histogram, the position can be closed on the expectation that the initial bull trend is reaching its end. The parameters for second MACD can be entered fairly easily using the “properties” area in your trading station. Once this is done, you will notice both MACD readings serve different ends. The faster MACD is useful in that it is key for allowing us to spot new trends in their early phases. This indicator is less useful for trade exits, however, because it will often lead many traders to exit their positions before most of the trending move has completed. When we add a slower MACD to our charts, fewer signals are generated. In addition to this, the slower MACD will give you an idea of the broader picture. So when counter trend signals are generated in the slower MACD plot (for example, a sell signal in an uptrend or a buy signal in a downtrend) if becomes a better idea to exit the position and capture your profits before they are given back. Conclusion Indicator tools are an excellent way of viewing price action in more objective ways. In many cases, however, these indicators can lead us to exit positions well before the full trend moves unfold, and this can lead to large reductions in profits. But when we double up on our indicators (and extend the time periods for their measurements), we can get a broader picture of when trends are actually coming to an end. For the MACD, its creator (Gerald Appel) actually recommended that traders use multiple plots of the indicator but this is rarely something that most traders today would even consider.

In part one of this article, we looked at key elements of the backtesting process and discussed some of the differences between “in-sample” and “out-of-sample” data. We also looked at some of the complexities and procedures involved when optimizing strategies so that traders can use these methods to settle on an approach to technical analysis that is likely to result in long-term profitability. It is important to read the first part of the article, as there are some basic steps in the process that must be first understood before moving on to the final steps. In the next sections, we will look at correlation as a critical component of the total process. Defining Correlation In this context, correlation refers to the performance similarities that can be found when comparing a technical analysis strategy that is applied to more than one data set. The results from correlation measurements will allow traders to spot broad trends and evaluate the performance of a given strategy over your chosen test period. When strong correlations can be found between results generated from all data sets (in-sample data and out-of-sample data), there is an enhanced probability the system will generate positive results when used in the following steps (forward testing and in live trading). There will be cases where a system is found to be curve-fit to perform strongly with one of your data sets but these situations fail to meet the requirement threshold to make it to the next phase of the testing process. When these situations are seen, it is likely that the system is over-optimized and much less likely to generate long-term gains when applied to live trading conditions. High levels of correlation mean that the system is ready for the next step, which requires further out-of-sample data testing. This data will form the basis for the next part of the process, which is forward testing. System Rules when Forward Testing Forward testing might sound overly complicated for traders new to the process. But forward testing is simple paper trading (trades are placed with a demo account using “virtual” money). With an additional set of out-of-sample data, forward testing gives traders new information with which to test a strategy that has already performed well (and shown strong correlation) in historical back tests. Forward testing simulates the live trading environment and gives us a better idea of how a strategy will work when real trades are placed. This is an important step of the process because there has been no optimization in the same way there was with historical price data. Optimization at this phase of the process would be impossible because there is no way to know where prices will travel next. This is also why it is important to place these trades with a demo account first, before moving on to live trading with real funds. The results (profits and losses) of each forward testing trade will be recorded, so it is vital that the rules of your system are rigorously followed. Any changes made (with respect to the rules of the system) will cloud the data and make it difficult to accurately assess the viability of the system in achieving consistent profitability. Making Valid Assessments When forward testing, it might become tempting to cherry-pick some trades that might look especially attractive and neglect others. There might be instances where your system send a trading signal but you look at the situation and avoid the trade because you believe it is unlikely you would actually take the position with a real account. But what is important to remember here is that you are not testing your skills as a trader, you are testing the viability of your proposed system. If the rules of your system send a signal to execute a trade, that is the trade that should be placed. This is the only way to properly evaluate your strategy. So, while the term “forward testing” might seem as though we are attempting to predict the future, the fact is that we are really only backtesting with live data, rather than historical price data. Because of this, the same standard apply when we look to assess the performance of a proposed system. We are looking for trading results (profits vs. losses) to show consistent profitability through all phases of the testing. This includes in-sample data, out-of-sample data, and forward tested data (or live data). You will also need to see strong correlations in all phases of your testing. When this is found, you will know you have a trading system that holds up even in situations that were not optimized. This means you have found a system that is likely to perform well in active markets (with real funds). Conclusion Backtesting a strategy can give traders some highly valuable information when looking for new ways to approach the markets. Most of the latest trading platforms enable traders to conduct these tests, and here we looked at some of the key elements required when we evaluate regular trading programs. There are many critics of backtesting, as people will often argue that historical price data does little to tell us how markets will behave in the future. While there is some validity to these arguments, we do have ways of dividing up historical data to increase the probability that our assessments are accurate. When we make our determinations using in-sample and out-of-sample data, traders have an efficient (and relatively easy) way of evaluating the potential success rate of a technical analysis strategy. These strategies can also be optimized (in the hope of improving on potential profit performance) but it is important to retest your approach on multiple data sets in order to prevent your trading profits from becoming a “self-fulfilling prophecy” that might not work under live trading conditions. As a final step, traders should implement out-of-sample forward testing, as this puts your strategy up against a new set of price activity and provides another layer of protection against potential losses. Once these steps are completed, you are ready to start actively trading with real money. So, while the general process cannot guarantee your next trades will be profitable, it does increase your chances of success when compared to systems that have received no backtesting. Ideally, you will be looking for strong profit performance and high levels of correlation between all data samples, as this creates the best scenario for systems later used in live markets.

Technical analysis traders looking to find and implement new trading strategies will often look to backtesting as a means for assessing the general efficacy of a given method (or series of parameters). Relying solely on these results is a mistake, however, as backtesting results have only a limited ability to determine the profitability of any system when used in live markets. To be sure, backtesting can offer traders some valuable information in terms of the potential success or failure present in any trading strategy. But it should be remembered that these results will often be misleading and should be thought of as just one element of the overall evaluation process. Other elements to consider can be found in forward testing and out-of-sample testing, which can help to achieve a better understanding of which markets work best with certain trading strategies. It is important to analyze these results before real money is put at risk in a trade, as this can help to avoid haphazard methods that lack depth. When these three assessment methods (backtesting, forward testing, and out-of-sample testing) are conducted, good correlation is the best indication of a trading system’s viability. Here (and in part 2 to this article), we will look at some of the key elements of that correlation so that backtesting methods can be refined for live market trades. Basics of Backtesting At its core, backtesting is the practice of applying trading systems through historical price fluctuations in order to monitor its level of success or failure over a given time period. Technical analysis strategies can be tested relatively quickly in this fashion without risking real money. Any trading strategy can be tested, from the most basic ideas to the most complex. One example of a simple tested strategy would be to look at moving average crossovers as a basis for trading positions. More complicated tests would involve a larger number of inputs and triggers. Any trading system that can be quantified is suitable for backtesting. Some computer programming ability can be helpful, especially in cases where less common trading platforms are used, or a wider variety of variables will be tested. For example, better knowledge in these areas will enable traders to change the commonly used inputs (the moving average periods themselves). Here, a trader might then be able to test a large number of moving average periods and determine which variables have the best success rates over time. Strategy Optimization Some of the more commonly used trading platforms will enable traders to use “optimization” features during the process. This feature allows traders to input a range of variable (such as a range of moving averages). The computer then looks at the number of successful trades for each input and will determine which period has the highest rate of profitability. Multi-variable optimization can be used for strategies with more than one input variable. In the moving average example, this would mean that the trader would input a range for two moving averages and then the software would be able to identify which combination works best. For example, crossover strategies using a 100-period average and a 55-period moving average might lead to more successful trades than a 100-period moving average and a 50-period moving average. The main benefit of this feature is there there will be some cases where an unprofitable strategy can undergo a few simple tweaks (or “optimizations”), and be transformed into a profitable strategy. It should be remembered, however, that this “profitability” will be in past terms. This does not necessarily mean that this same success rate will be seen in the future in live markets. Curve-fitting uses optimization analytics to identify scenarios with the largest number of successful trades and the best potential for profits. Problems can arise here, however, as methods are “optimized” for the specific data set being analyzed. Since that same price history will not be seen again, many of these systems will become unreliable in the future. So, while backtests and optimization procedures can offer some interesting benefits when looking to develop and assess a trading strategy, the results should not be viewed in isolation. The next part of the process is to test the same strategy against historical price data that was not used in the original tests. Using Out-of-Sample Price Data Once you have a strategy you want to test, it is important to section off historical periods for the testing process. The first set of data is used to test and later optimize the original strategy. This initial data set becomes the “in-sample” data. The other time periods that have been sectioned-off (and not yet tested) now make up the “out-of-sample” data set. It is important to make these differentiations (separating the time periods) because this is the only way to test your original idea on new historical price activity. Initially, your optimization process “custom-designed” its inputs based on a specific set of price action. In order for the strategy to be considered valid, it must be used successfully in new scenarios that were in no way influenced by the optimization process. While this does not remove all of the potential problems in the backtesting process, it does create a greater likelihood that your trading strategy will work in live markets if it is successful in more than one historical time period. The in-sample data is the key component for testing your original strategy, finding its weak points and then optimizing the process to enhance the number of profitable trades. Since this is such a critical component of the original test, traders will usually devote a larger period of time to the in-sample data set. Once the system has been optimized, the system must then be applied to the smaller out-of-sample price data. An added benefit of this approach is that traders can compare the results between the two data sets. When similar performances are seen, there is a better chance for profitability when using the same system with a real trading account. Conclusion Backtesting can allow traders to find, develop, and optimize a technical analysis trading strategy based on the price activity markets have experienced in the past. While this information does have a good deal of value, it is not enough to simply take these backtesting results at face value and expect the success to continue when applied to live markets. For this reason, backtesting is always conducted using a demo account, as additional refinements will be needed before real funds are put at risk. It should also be understood that true backtesting analysis is a multistep procedure that divides price data into different (but necessary segments) In the next sections of this article, we will look at correlation and forward testing as the next key components of the process.

Technical analysts rely on price activity because it is perhaps the clearest indication of trader sentiment and market positioning. Of course, there is an incredible variety of ways to approach technical analysis. But, generally speaking, technical traders will attempt to be as objective as possible when reading price action. This approach will allow you to remove your personal biases and go far in removing some of the unnecessary ideas that can cloud your analysis. One way of removing your biases and remaining objective is to use indicators and oscillators to filter the price data. Indicators and oscillators can help traders to view how price is behaving relatively to the larger trend, and to identify areas where extreme movements have become over-extended. This goes far in determining whether or not a specific trade idea has a high probability of success. One of the most common tools in this area is the Stochastic Momentum Index, which allow traders to spot potential turning points in price activity. This type of analysis is critical when looking to determine where prices are trading within the broader context, and where prices are likely to move next. Not Simply Overbought vs. Oversold Price Action As an Oscillator, the Stochastic Momentum Index is usually implemented as a means to finding overbought and oversold market conditions. The main advantage here is that these readings are relatively easy to identify and understand. But there is more to oscillators than simple overbought and oversold readings, and it is usually not recommended to base trade on these readings by themselves. Here, we will look at some of the critical characteristics of the Stochastic Momentum Index so that traders can understand the signals this oscillator sends. This will help those looking to increase the probability of success when these signals are used as part of a bigger trading plan. The Stochastic Momentum Index (SMI) was brought to the attention of markets by William Blau in the early 1990s. Blau’s intention was for the index to help clarify the signals that are sent from the traditional stochastic oscillator, as the SMI makes it easier to see where the closing price of a given period falls in relation to the midpoint of the most recent price low and price high. This helps the indicator send signals to the trader which offer greater perspective in terms of market context. This is important because once we know where closing prices rest (relative to recent ranges or trends), it becomes easier to identify potential turning points (or at least to understand whether or not the current price move has further to travel). Armed with the additional knowledge of historical price ranges, potential changes in trend can be found high a higher level of accuracy. Trading with the SMI When using the SMI for price analysis, it quickly becomes clear that the SMI is faster than the tool used for traditional stochastics, and this can make things more prone to mistakes if the oscillator is not read correctly. As with any charting tool, there will be default settings, but these can be slowed by increasing the number of periods used in calculating the SMI. When looking to start placing trades with the indicator, there are three common approaches. These different methods make the SMI a flexible tool that can be used in a number of different market environments. Overbought / Oversold SMI Readings The most commonly used method for finding trade signals with the SMI comes with the ability to spot instances where the reading crosses into overbought or oversold territory. In many cases, it will be difficult to spot clear levels of support or resistance (to create a workable range). If this is not visible, trading off of simple overbought and oversold readings can be a dangerous prospect. One of the most common phrases in the trading markets is that markets can trend (and remain irrational) longer than you can remain solvent. This can make it difficult to take contrarian positions against the dominant trend (even if prices have sent oscillator readings into overbought or oversold territory). When we look at the SMI to determine these levels, the generally accepted parameters are +/- 40 on the reading. But it is generally a good idea to make sure that a workable range is in place before taking positions based on these readings. The added technical price parameters will result in higher probability trades as long as these signals are in agreement. Crossing the Signal Line in the SMI Another approach is to use the SMI signal line and wait for crossovers in the reading. These signals tend to have a lower probability of success, so it is more important to have additional signals in place before committing to trades. For example, an upward cross of the signal line (indicating prices are starting to turn up from oversold territory) should be accompanied by price levels bouncing off of a clear level of historical support. The combination of these factors will help filter out crossovers that have a lower probability of success (accurate price forecasting). Another way to improve on the probabilities for this strategy is to add a neutral zone to the indicator, using +/- 15 as the key levels. In these areas, signal line crossovers should be disregarded, as price levels are not in “overextended territory.” When this is the case it is less likely that prices are near a major turning point, and this removes some of the added incentive to move into new positions. Examples of SMI crossovers can be seen in the first attached chart, but it should be remembered that crossovers occurring in the middle of the oscillator field will usually be filtered out. SMI Divergences The last major method for using the SMI readings to your advantage can be found with divergences, which show areas where the price action itself is moving in an opposing direction (diverging) from the readings seen on the indicator. Technical divergences can happen on both the buy and sell sides of your price charts but they are not very common. This essentially means that they will send stronger signals when they actually are sent but there will not be as many trading opportunities when looking to implement this strategy. The second chart example shows instance of divergences. For buy positions, a bullish divergence is seen when the oscillator is moving higher as prices are making new lows. Buy positions can be taken here because the oscillator is not confirming the price action, and this generally leads to rallies seen later. An added advantage of trading off of bullish divergences is that traders are able to buy in at extremely low levels before uptrends begin. This means you can get the best price before any bull runs are seen. Conversely, bearish divergences occur when prices are making new highs as the oscillator reading is starting to head lower. The same advantages can be found in bearish divergences, as traders are able to sell into rallies (and get the most expensive price possible) before the major declines are seen later. Confirmation of these signals can be found when major areas of support are broken (for bearish positions), or when major areas of resistance are broken (after bullish divergences are seen). Conclusion The SMI oscillator is a valuable and flexible tool that can be used in many different types of trading. If you are using crossovers, divergences or overbought and oversold readings in your positions, the oscillator can present traders with some great signals that can be used to generate new position ideas. As always, it is a good idea to find a couple of agreeing signals and then to trade in the direction of those signals, as this helps to improve on overall probabilities and creates fewer losing trades.

Investors that find themselves falling in the more traditional category of fundamental analysis often have many criticisms for those regularly implementing technical chart analysis as a basis for trades. Generally speaking, these criticisms suggest that charts “have little to do” with the economic drivers influencing market valuations or that previous price action has nothing to do with where valuations will travel next. In essence, these investors will argue that past performance is not an indication of future market activity. In order for an assessment like this to be accurate, there must be an idea that technical analysis involves only lagging indicators. But is this entirely true? When we look at the available charting tools that are available in the commonly used trading stations, a variety of different options can be seen. Specifically, these tools will often be divided into “lagging” indicators and leading “indicators,” and the fact that there are different types of trading tools goes far to dispel some of the misconceptions that are commonly held with respect to technical chart analysis. Here, we will look at some of the differences that can be found in these two types of indicators so that traders have a better understanding of the functions in many of the commonly used trading applications. Know Your Indicators It’s important to understand the strengths and weaknesses of any indicator before using it in any real money trade. One of the most common mistakes new traders make is to start placing indicators on their charts without having a real understanding of the calculations behind the indicator or the way it is best used in analysis. Some might say that a full understanding of these indicators is unnecessary: Buy if prices fall into “oversold” territory, or Sell if prices reach “overbought” territory. Unfortunately, trading is not this simple. If technical analysis was this easy, everyone could be a profitable trader. Even further, we could simply set software applications to find these signals and walk away as billionaires. The reality is that trading takes more work than this, and we will need to do a good deal of homework before we can make our indicators work for us in consistent and repeatable ways. Not knowing the (usually simple) formulas behind your indicators is not an acceptable practice - and it will negatively influence your trading results. Without this, it will be much more difficult to understand the true application behind each type of indicator. But before you delve into the specifics of your chosen indicator, you must first understand the types of indicators that are available. The two mains types of indicators are leading and lagging indicators. Lagging indicators alert traders to situations that trends have started and that it is time to pay attention to developments that have already become apparent. Leading indicators aim to signal trend changes before they develop. This might seem to suggest that leading indicators will lead to instant riches but the fact is that the signals generated are not always accurate. Traders using leading indicators will, in many cases, encounter “head fakes” and erroneous breakouts. Trades taken on these inaccurate signals eat into the advantages created by the leading nature of these indicators. But this does not mean that they can not be used to generate consistently profitable signals over the longer term. Oscillators: Leading Indicators When using common trading platforms (such as MetaTrader), one of the main indicator options is the Oscillator. Oscillators are objects that mark two points and move back and forth between those points (always falling inside those points). When the oscillator reaches an extreme area within this 2-point range, buy and sell signals are generated. When seen near the midpoint of this range, the signal is neutral and no trade should be taken. Common examples of indicators include the Relative Strength Index (RSI), Stochastics, or Parabolic SAR. All these indicators help traders identify reversal spaces, as the prior trend reaches completion and prices are preparing to make a forceful move in the opposite direction. In the first chart, we can see examples of buy and sell signals for all three indicators. As we can see from the first chart, price activity causes all three oscillators to move back and forth between buy and sell signals, creating opportunities in both directions. This chart, of course, represents an ideal example, where all indicators are in agreement with one another. For example, the RSI might show a screaming buy while the Parabolic SAR is showing a sell signal. In these cases, it is better to simply step aside and stay out of the market. Additionally, this is a good reason why traders should not use too many indicators on their charts as this will greatly reduce the number of viable signals that become present during your daily routines. Another point to remember is that all leading calculators do not use the same calculations and formulas. The RSI bases its signals on the changing levels in succeeding closing prices. Stochastics uses the highs and lows of price ranges over the time frame shown on your chart, relying much less on successive time periods. Parabolic SAR is has probably the most unique calculations of the bunch, and this can complicate trading signals when combined with other indicators. From this, it should be clear that not all leading indicators are created equal, and traders should practice with a few options before committing to any one choice. Momentum Indicators: Lagging Indicators The second major category is the “lagging indicator,” which includes tools like Exponential Moving Averages and the MACD indicator. These tools are commonly used to spot trends that are starting or are already in place. The downside to using these indicators is that (since the trend is already in place) your entry signals will come later. This means less profit as a smaller portion of the overall move is captured. The upside to lagging indicators is that they send fewer false signals, which will generally mean that you are stopped out for a loss on fewer occasions. In the second chart example, moving average crossovers are seen in conjunction with buy and sell signals sent by the MACD indicator. In all of these cases, the indicators were sent signals (using their accompanying formulas) and then the indicators themselves produces signals shortly afterwards. Here, traders using these signals would have missed some portion of the initial move but the validity of the signals sent would have had a better chance of eventual success. Conclusion: Learn about Your Indicators and Play from Their Strengths Traders have different types of indicators at their disposal, and this is helpful when looking for tools that fit your individual trading style. Leading indicators sent trading signals before new trends or reversals develop. Lagging indicators use available market information to send trading signals that have a slightly higher chance of being accurate (avoiding false breakouts but missing a portion of the early move). It is up to you too decide which approach best matches your risk tolerance and trading approach. It is possible that some tools will work better in some environments than it will in others, and this is an added reason why traders should practice their routines with a variety of indicators before committing real money to positions.

One aspect of technical analysis trading that can be especially confusing for newcomers is the dual notion that it is a better idea to trade with the trend (not against it), while at the same time “buying low and selling high.” Of course, anyone with a proper understanding of these two trading practices can tell you that these two concepts are fundamentally at odds with one another: If you are trading in an uptrend you have - by definition - already missed the lows and therefore cannot buy into them. The reverse would be true for traders looking to sell downtrends. So, it would seem that there is no way to do both, and that traders must find one strategy that works best for their temperament, abilities, and time availability. But is that entirely true? Is there no way to find a happy medium and play off of some of the strengths of both of these time-tested market maxims? Here, we will look at some ways to approach trend trading in a manner that allows us to - at least to some extent - buy when prices are cheap, and sell when they have become expensive. Specifically, this means finding lower highs (for short sells) and higher lows (for long positions) within the larger trend. Of course, these strategies will by no means completely fix the inherent problem. It will still be impossibly to “buy low and sell high” in the direction of a trend. But when we look at prices from this perspective, we can start to arrive at a happy medium that plays to the strengths of both strategies. The Importance of Trade Entries Experienced traders will always tell you that finding the proper trade entry requires patience, and in some cases you will be forced to completely miss a trade if prices never extend to your desired level. Here, we are going to look at the way prices behave when lower peaks are seen (in a downtrend), and the way they behave when higher troughs are seen (in an uptrend). The first case is an opportunity for sell positions while the second is an opportunity for buy positions. It is important to wait for these structures to complete before establishing trade entries because, without this, it is much easier to find yourself trying to “catch a falling knife” and lose in a buy position, or sell into a rally before it has completed. Establish the Dominant Trend The first step in the process is to establish the dominant trend. This is important because it will give you context and help you to gain an understanding of which direction your trade will be follow (buys in uptrends, sells in downtrend). There are many different ways to do this but perhaps the simplest and clearest way is to find uptrend or downtrend channels (parallel channels). These structures are relatively easy to spot, and examples of both types can be found in the attached graphics. Standard definitions or these channel will generally say that uptrend channels are marked by higher lows and higher highs, while downtrend channels are marked by lower highs and lower lows. Finding trading opportunities within these trends will require us to the “anti-areas” within these trending moves in order to get a better price and come closer to “buying low and selling high” in the direction of the larger trend. Examples for Long and Short Positions Next, we will use the trend example to spot areas where new longs can be established. The green arrows show areas where prices have dropped to support, given reversal signals (such as a doji candlestick pattern), and then resume the initial upward direction. Traders spotting the fact that prices have become cheaper without breaking the trend would be able to establish positions at lower levels (relatively speaking), and then capitalize on the upward move seen later. Similar logic can be used when selling into downtrends. In these cases, traders are looking for rallies that do not violate the dominant downtrend, yet still give traders an opportunities to sell at preferable levels. Spotting Valid Turning Points Of course, there is not foolproof way of knowing these areas are valid turning points. There will be instances where traders spot a higher low, only to establish a new long position and then to watch prices fall lower once again. So, it is not enough to simply identify areas where higher lows and lower highs can be visually determined. Luckily, there is a wide variety of other tools that can be used to help confirm the validity of a turning point. Some common examples include candlestick reversal patterns, (such as shooting stars, doji, or hammers), indicators (such as the RSI or MACD), or Pivot Points (which show areas where price moves are likely to become overextended). Fibonacci support and resistance levels can also be used within these trends and can help traders to find new levels for trade entries. When using these types of tools, there is a better chance that traders can avoid buying an asset that will start to fall or sell an asset that will continue to rise. This is an important element of the entire process because even though this is trend trading, it can also be viewed as contrarian trading on smaller time frames. Because of this, it is also important to use multiple charting periods in order to get a price perspective that is both wider and smaller at the same time. Stop Losses and Profit Targets When looking for areas to place stop losses and profit targets, the channel trendlines themselves can be particularly helpful. For example, in an uptrend, stop losses can be placed below the rising trendline (support trendline). The reason here is that and downside violation of these areas would invalidate the uptrend channel and remove the initial logic behind the trade. For downtrends, the stop loss would be placed above the descending (resistance) trendline. Conversely, profit targets would take the other side of things. In an uptrend, traders would look to capture profits once prices rise to the descending trendline (as this area is likely to act as resistance). In a downtrend, traders would look to capture profits once prices fall to the ascending (support) trendline (as this area is likely to act as support). Other technical tools (such as indicators or Pivot Points) can also be used to identify turns in price but it is important to watch the channel activity itself as this is the central basis for the logic behind the trade. Conclusion: Buying Low and Selling High Offers Chance to Improve on Entries in Trends Using price channel activity can offer traders a way of playing on seemingly oppositional market maxims. Those looking to rely on the idea that the “trend is your friend” can buy higher lows in uptrends in order to get improved price entries (when compared to strategies like breakouts). Combining these strategies will allow traders to buy low and sell high, while playing off of the dominant underlying momentum that is present in trends. These strategies are relatively easy to spot on a price chart, so these approaches to price activity can be used by traders of all experience levels.

It is not uncommon for new traders to view the forex markets with a certain level of mystique. This is largely because of the wide variety of trading approaches that can be implemented at any given time. If we compare forex trading to riding a bicycle, some similarities emerge. Learning to ride a bike requires skill, patience, balance, the proper equipment, and the ability to accurately assess your surroundings. It wouldn’t be a good idea to practice riding on a street with speedy traffic, and the same attitudes and rules should be applied to the forex markets as well. When we are able to combine solid analysis with effective practices, it becomes easier to increase success rates. Like many things with substantial potential for rewards, successful trading requires both talent and hard work. Here, we look at some ways to combine the advantages of your natural talents with your strategic approach to put you on course to develop methods that will improve success in all trading markets. Understanding the Value of Patient Preparation Before any trades are placed, it is important to understand the value patience and preparation can add to any strategy. This requires an assessment of your trading goals and personal strengths. Nobody can make these judgements better than you can, and this is not something that you can learn by reading textbooks on the subject. When applying these strengths and goals to your trading plan, it is generally a good first step to decide on a time frame that will typically be used for your trades. Time frames can be altered, of course, but it is a good idea to choose a time frame that is best suited for your temperament and level of time availability. Traders that typically use 5-minute charts, for example, tend to be uncomfortable holding positions overnight, as these trades carry certain types of added risk. Conversely, traders that use weekly charts tend to be willing to hold positions even through periods where prices might be working against the trade. Traders using shorter time frames will generally have to spend more time during the day monitoring their computer screens - looking for new opportunities and closing positions once the market is ready to change. Traders using longer time frames might spend more time doing research, for example using the weekend to look for new opportunities and then arriving at a game plan for the coming week. Using a Consistent Methodology Once you are able to settle on a general time frame, it is important to look for a methodology that you will be able to implement with consistency. For example, some traders to identify ranges and then buy when prices fall toward support and sell when prices rise back toward resistance. Some traders prefer to wait for breakouts and then trade in the direction of the underlying momentum. Others wait for indicator readings to send certain signals or for significant price patterns to develop. Once you settle on a system that matches your strengths, it is often a good idea to test your ideas to see if the strategy works over a long period of time. If backtesting results show that your system generates reliable signals in more than 50% of your positions, you will be able to gain an edge and improve on the results of most of your competition. It is also important to test a few different strategies and then settle on the one that best matches your temperament and generates positive outcomes on a consistent basis. Use a variety of different forex pairs for your assessments and look at multiple time frames in order to get a broader perspective on the success or failure of your preferred methods. Develop a Trader's Mindset Having a go-to time frame and a solid strategy is great, but these can only have a limited impact if the trader using these techniques fails to exhibit a consistent mindset. A successful mindset comes with an adherence to four key areas: Discipline, Patience, Manageable Expectations, and Market Objectivity. Once you settle on a system, you must exercise the patience to wait for situations where all of your trading requirements are met. If your system requires prices to reach a certain area, and that area is never reached, no trades should be placed. It is time to look for opportunities in other areas. If you miss a train, you don't run after the train, you simply wait for the next one to arrive. In the forex markets another opportunity will present itself. The ability to wait for the next opportunity also requires discipline, and a willingness to obey your strategic rules. Discipline is also required in order to place trades and open or close a position when it is necessary. This becomes even more important when dealing with stop losses. Market objectivity comes in when traders must detach their biases and emotions and rely on the strengths of a trading system. Traders must also create manageable expectations that are realistic. It is unreasonable to take a $500 trading account and expect to make $1,000 on each trade. There will be instances where a market will more more than you expect (and generate substantial profits) but if you expect this to happen all the time, you are setting yourself up for disappointment. Don’t Focus on Too Many Markets at Once Many new traders feel the need to be in a position all the time and monitor an unmanageable number of forex pairs at once. While it is true that the use more more forex pairs will generate more trading opportunities, this is a practice that is largely unnecessary. Its generally a better idea to limit yourself to a smaller number of markets, and then to have a better understanding of how those markets operate. Some currency pairs will behave differently in different market environments, so it is also a good idea to have a pairs that exhibit different types of moves so that you will have a trade to make when conditions change. There is no system that will create successful trades 100% of the time. Even in cases where a system is accurate 65% of the time, you will still see periods of loss (the other 35% of the time). Because of this, overall profitability is really an exercise in risk management and trading execution. It is important to cut your losses and accept defeat in a trade in order to prevent further losses from accumulating. Look to trade in areas where prices are likely to move in your chosen direction right out of the gate. This is especially true for traders using shorter time frames. In some cases, you will need to try a position two or three times in order to see prices move in your direction right off the bat. This requires a high level of discipline and patience, but when it is done correctly, you will be able to trail your stops and stay in the trade until the move has run its course. There are many different ways to approach the forex markets in a coherent fashion, and these key steps are vital when developing a strategy that works over time. No matter your preference for time frames or strategy, these steps must be considered before putting your money at risk in potentially volatile markets.

One of the main reasons chart analysts use historical price behavior to gauge general momentum and market sentiment. The advantage of this type of analysis is that these patterns in sentiment and momentum can be assessed in real time, whereas fundamental analysis will often require traders to wait for market moving events and then make trading decisions directly afterwards. Trading tools like the Ichimoku indicator enable traders to to identify areas where conservative trade entries can be placed once the broader price direction is determined. Not all indicators will work for all traders (either stylistically or even in terms of individual personalities). But it is important to try out a few different indicators in order to avoid getting pigeon-holed and miss the potential opportunities that might be found when other indicators are used. Different indicators will work better in different market environments so technical traders should at least test multiple options in order to determine what works best. The Ichimoku indicator is one of the lesser discussed indicators, so here we will look at some of the situations where the indicator should be used and where it should not be used to gain a better understanding of the situations where Ichimoku is most advantageous. Maintain a Varied “Toolbox” Your trading platform and charting software should really be viewed in the same way a toolbox would be used by a carpenter. You will rarely find a carpenter that has only one tool at his disposal. Additionally, it pays to remember the old phrase than when your only tool is a hammer, every problem starts to look like a nail. The financial markets are widely diverse and dynamic, and anyone with any experience trading these markets will tell you that no one tool or strategy will work in all situations. For example, trending markets will not exhibit the same patterns are markets that are range-bound, so it is essential to have a broader “toolbox” when actively establishing positions. Avoid Ranges with Ichimoku For the Ichimoku indicator, most of its applications are best suited for trending markets. Feel to take a look at the section’s previous article discussing this environment to get a better sense of the characteristics displayed when trends are in place. When the Ichimoku indicator is used in range-bound markets, you are more likely to get a sell signal near the bottom of the range (the buy zone), or a buy signal near the top of the range (a sell zone). Since there is a smaller chance for true agreement in the signals, the indicator is not compatible with these market scenarios. Of course, it is not possible to force a trend when one does not exist, so placing trades here with the wrong tools can leave to some highly frustrating results. Watching for Trends Given the “back and forth” signals that would be seen with Ichimoku during ranges, it starts to become clear that higher probability signals can be sent when higher highs and lows are visible (during an uptrend) or when lower highs and lows can be easily spotted (during a downtrend). When the 9 & 26 period Ichimoku averages are used for the trigger and base lines smaller market moves (during ranges) will not occur at price points that are advantageous for trades. So, when looking for trends in conjunction with Ichimoku, the indicator reading itself can be extremely helpful. For example, prices breaking above or below the Ichimoku cloud can give excellent indications of where prices are likely to extend. In the charted example, we can see sell signals with prices falling below the cloud and extending a large distance before support levels are seen. In a bullish scenario the situation in this chart would be reversed. It should also be remembered that in cases where the cloud is not clearly above or below the levels seen in previous months, it is generally a better idea to stay away from trades and wait for better opportunities. Trading Rules for Ichimoku Analysis Now that we understand when Ichimoku analysis works and when it is not worth your time and effort, we need to establish some rules for how trades can be structured when using the indicator. Since the initial chart example present a sell trade, we will set the rules for buy positions. These rules can then be reversed when looking to establish sell positions. Before entering into buy positions, the following criteria should be seen: Price activity is holding above the Ichimoku cloud The trigger line is seen higher than the base line, os is starting to at least show a bullish cross More conservative traders will want to wait to make sure the lagging line is holding above the price activity seen 26 periods previously The Kumo is above the price action and is showing an upward trajectory Price levels for entries are not more than 300 points from the base line (because there is likely to be some volatility back to the line if extended moves are seen). Once these conditions are met, high probability trading entries can be found when moving in the direction of the wider trend. As long as prices hold above the cloud and move below the base line, it is important to watch out for times when prices might cross back above the base line with increasing strength. Base line crossovers tend to be a good indication that the wider trend is resuming and this can be key for assessing how trades are likely to unfold. When looking to set stop losses, traders can use the technical support created by the cloud itself (in conjunction with pivot points or other support indicator) and then set stop losses below the cloud (for long positions). Profit targets can be determined using your risk to reward ratio and then based off of the risk exposure taken with the stop loss. Conclusion: Consider Using the Ichimoku Indicator and Remember its Best Price Environments The Ichimoku indicator can be a strong technical indicator to use when looking to expand on your trading “toolbox.” But it is important that (as with all indicators) there are certain situations where the indicator will best perform. For the Ichimoku, this tends to be in trending environments, rather than in range bound price activity. This helps to reduce the number of bad signals and use your trading time in more efficient ways. Certain criteria should be met for both buy and sell positions, and, in this respect, the Ichimoku has more rules than some of the other commonly used indicators. Luckily, the indicator is extremely visual in nature and once the different lines are understood, you will only need a quick glance at your chart in order to find new trading opportunities.

The charts are used to illustrate the point. If you are interested in backtesting results, maybe you should post some.

Don't worry about that. Feel free to post a link, I'm sure a lot of us will take a look.

Once we start to look at technical price analysis from an academic perspective, it can be difficult to remember some of the foundational aspects of the practice that got us started in the first place. The idea of what makes a trend creates a basis for most of the more “advanced” technical analysis techniques that follow. So, it is surprising that so many active forex traders dismiss trend analysis as overly simplistic and only worthy of limited attention. But the simplicity of any price analysis method is not something that should be immediately disregarded as a negative, and trend analysis is something that should be used by traders of all experience levels. The ability to understand what makes a trend can bail a trader out of a strategy that is imperfect and help prevent the excessive losses that can break a trading account. “The Trend is Your Friend” The most commonly used phrase in technical analysis is “the trend is your friend.” Whether your strategy agrees with it or not, the phrase has stood the test of time because it does form the building blocks for the way most people view price activity. There are many traders that use trends as an opportunity to work in reverse (using contrarian strategies), but even when thats the case, you will still need to have an understanding of how trends are defined in order to know what you are working against. Here, we will look at some of the benefits of trend-based strategies so that investors can use these ideas (for or against) when establishing new positions. Trends and Imperfect Strategies There will be many cases where an alternating strategy will fail against an uptrend or downtrend. When markets are bullish the majority of the price momentum is set in a clear direction and this is the main argument trend traders will use to base their positions. Trading in the direction of the majority of the market’s momentum allows you to focus on other aspects of your strategy (such as stop loss levels and profit targets). This also allows you an added advantage when using a strategy that is less than perfect. When trend trading, the timing of your exact entry isn’t as important (when compared to contrarian or swing strategies). Of course, this does not mean that trend trading will result in gains in all cases. But when using these methods, you will gain some protection against the inherent flaw seen in any strategy and the exact time of exits and entries becomes less critical because most of the market is already on your side. In recent months, one of the stronger trend instances have been seen in the JPY pairs (as carry trades become more popular). The activity in these pairs has shown significant rebounds from long term lows, essentially suggesting that a new uptrend is in place. Combining Trend Moves with Indicators Once your underlying trend direction is identified (higher lows and higher highs vs. lower lows and lower highs), some of the less commonly used indicators can be added as a way of getting an edge on the rest of the trend trading market (where traders tend to focus on many of the same charting tools). One example of a less commonly used (yet effective) market indicator is the Commodity Channel Index (CCI). Helping remove some of the difficulty of timing entries in a trend, the CCI is an oscillator used to determine the strength or weakness in cyclical trends. The CCI helps traders identify price activity that has reached extreme points (become overbought or oversold) by quantifying the relationship between prices, moving averages, and deviations that are typically seen relative to the moving average. In the attached chart, we can see that rallies are expected once the indicator falls below -100, whereas declines are expected after the reading rises above +100. The CCI cannot guarantee 100% success even used in conjunction with a forceful trend. But when, for example, a strong uptrend is in place, buyers are more likely to enter the market when prices have become oversold relative to their near term averages. One of the biggest problems seen when trend trading is the fact that it is difficult to “buy low and sell high.” Looking for oversold activity is one way of combating this problem as it gives you an opportunity to capitalize on short term reversals within the larger trend. When strong trends are seen, you will usually have multiple opportunities to enter and re-enter, and using the CCI is one way to find these opportunities. Choosing Your Markets If trends make up the majority of market price activity, we will need to take some trading opportunities while dismissing others. The main focus, at all times, should be in finding which price trend will allow you capture the most pips at any given time. If you are looking to implement a contrarian strategy, the argument can be made that there is greater opportunity in a reversal (became the previous trend made prices too expensive or cheap). But this is only the case when a trend has actually reached its end. When you align yourself with the direction of the trend (and choose your markets based on underlying strength), your positions are exposed to larger pip potential and reduced possibilities for losses. Conclusion: Turn the Odds in Your Favor Until Reversals are Seen When looking at trend-trading strategies, there are several advantages that allow traders to turn the odds in their favor and to protect against the flaws that are inevitably present in any trading system. As long as a trend is in place, there is an enhanced potential for gains as most of the market is in agreement with the positions you will be taking. The first step is to identify the main trend direction and, in many cases, this will not be immediately apparent. But when this is the case, it is better to look for other opportunities, as much more money can be made after the most obvious trending moves are seen. The forex market has an impressive selection of available currency pairs to trade (even when using some of the smaller brokers), so there are always alternative options when your chosen pair is not expressing clear trend activity. For this reason, it is important to filter your signals in ways that allow you to only focus on those pairs with the strongest trends (and the best potential for gains). For positions that are already open, it is important to watch for counter-trend reversal signals to either stop out the position or to take profits. At some stage, even the strongest trends will come to an end as uptrends turn into downtrends and vice versa. The best indication of these changes when an uptrend fails to proceed with higher highs and higher lows (momentum stalls too early when attempting new highs, or support levels break). In a downtrend, this would mean prices fails to proceed with lower highs and lower lows (downside momentum stalls too early when attempting to push to new lows, or resistance levels break). Other than this, trading rules can be altered but the central goal is to find the most obvious examples of a trend before any trades are placed.

Traders that are focused solely on price analysis tend to make arguments suggesting that fundamental or economic factors can be largely ignored in favor of pure chart analysis. Typically, these arguments rest on the idea that all of this information is already contained in the price itself and that studying this data is an extraneous activity. For these reasons, there tends to be a rather large disconnect between traders that use technical and fundamental analysis, as well as chartists and those that pay special attention to news events. But completely disregarding fundamental factors and significant market news events is a dangerous practice for a variety of reasons. At best, this will limit the number of trading possibilities you can identify. At worst, this can leave you unnecessarily exposed to risk when major fundamental events are about to occur. The forex market is always moving and traders are always reacting to the latest news and developments, and pushing market prices in the appropriate directions. There is very little downside in at least knowing when significant news events are about to occur and exercising the ability to bridge the gap between technical and fundamental analysis and make your trading strategies more comprehensive and complete. Maintain an Awareness of Session Changes During the businessweek, trades are being placed virtually every second. But even with a 24-hour market, it should be remembered that certain locational sessions dominate certain hours, and new is typically generated when these sessions are starting. For those looking to base trades after news events, the times can be great for creating technically-based trading opportunities. Traders that are aware of these occurrences will have an edge over those that are oblivious to these factors. To be sure, there are some market events that will have a greater impact than others, and major news events will not occur every day. Specifically, this edge comes from added foresight and the ability to better manage risk before markets become especially volatile (a common reaction after major news is released). In addition to this, trade directions can be identified in their earliest stages as the initial drivers of market momentum can be pinpointed with extreme accuracy. News events will often be the reason trends change, so for those looking to implement contrarian strategies (buying low and selling high), it is important to be able to isolate areas where these changes might occur. Trading probabilities can be increased this way and overall returns can be improved when watching these factors. Since news events and economic data tends to be released at the beginning of each session, it is important to have an idea of when these sessions begin and end. The Asian session starts the week, and runs everyday from 11pm to 8am GMT. The European session runs from 7am to 4pm GMT. The North American session runs from Noon to 8pm GMT. Volatility typically slows in between these sessions, and this favors range-bound strategies. Once liquidity re-enters the market, volatility starts to pick up again, and this is especially true when a particularly important news event comes. In these situations, breakout strategies become more efficient as markets determining the main trend of the day. Judging the Importance of the Day’s News For technical traders, perhaps the most difficult task will be to determine the relative importance of a given piece of news or economic release. The main problem here is that there are no hard and fast rules for understanding which events will be market moving on which days. There will be times when inflation is a central issue for a particular currency pair, while at other times growth data might be a bigger price driver for that same pair. Because of this, it is important to have a strong sense of which data the market is watching at any given time. Generally speaking, interest rate decisions and employment data tends to have a significant impact on price activity. This is because higher interest rates increase the total return that is gained or lost when holding a certain position. For example, the Australian dollar has relatively high interest rates, while the Japanese yen has long been associated with low interest rates. Long positions in the AUD/JPY generate interest rate yield while short positions in the same pair require interest costs to be paid. If the Australian central bank made the decision to raise interest rates, it would be a bullish event for pairs like the AUD/JPY. So, when an interest rate decision is scheduled for a specific country, it is a good idea to watch price action and base trading decisions on the eventual outcome. Price volatility will often increase when interest rate decisions are made, a scenario that tends to benefit breakout strategies. Basing Trading Strategies on Expected Volatility Once we are able to identify high importance news events, we need to settle on a strategy to trade off of the expected changes. Generally speaking, price volatility will come to a near halt before major economic releases. This is because traders are not as willing to commit to positions before the economic results are known. This is usually a wise approach, as it helps to prevent traders from getting stopped out if the position initially taken does not agree with the data release or news event. It doesn’t make much sense to get into a bullish position when there is a 50/50 probability that the economic data will have a bearish effect on your chosen currency pair. Since its usually a good idea to wait for the event risk to pass before establishing positions, let’s take a look at an example of how prices might perform prior to an interest rate decision. In the charted example, the USD/JPY is showing a low volatility downtrend prior to an interest rate decision from the Bank of Japan. Those in positions before this decision were clearly taking on unnecessary risk, given that the outcome was still unknown. Once the scheduled decision was released, the outcome was highly bullish for the USD/JPY pair, and this is later reflected in the upside price volatility. When looking to place trades in this situation, buy orders could have been established just above short term resistance levels, while sell orders could simultaneously be placed below short term support levels. This is because news events tend to favor breakout strategies as new trends develop. Stop losses can be kept relatively tight in these cases because significant follow-through is almost always expected. Staying current on geopolitical news and economic data releases can be helpful for both short and long term traders, and can help to reduce some of the risk associated with trades that are placed before major changes in volatility are expected. The biggest challenge is to know which market events will have the biggest impact on prices, and in which pairs will be most influenced by the releases. Technical traders can still use their skills for these trades, as breakout strategies tend to work well once these situations are seen.

Losing money is a necessary part of learning to trade in the forex markets. It is important to remember this, because there is essentially no trader that can claim to win 90-100% of his trades and still be taken seriously by his peers. Since losing trades are an inevitability, it is unfair to define all losing trades as mistakes - because this simply is not the case. A better approach is to define trading mistakes as the events that are actually under our control and work out in the wrong direction. As long as we keep position sizes to manageable levels and spot true mistakes early (when mistakes are actually made), we can avoid substantial damage to a trading account and correct errors so that we can continue improving and moving forward toward your trading goals. Analyzing Seemingly Chaotic Markets When looking to trade and analyze markets that appear chaotic on the surface, it is easy to become frustrated when looking at how price activity unfolds in real-time. This creates some differences when looking at price activity from an historical perspective (which, in hindsight, is much easier). In most cases, new traders will look for ways to improve their methods and build on their strategies using defined trading markets and a specific set of rules on which to base positions. But for most of these early traders, a majority of these positions might turn out to lose money. If you place 10 real money trades and then 6 of those trades lose money, most new traders might say that 6 mistakes have been made - but this is not always the case. For example, let’s assume that we use classic RSI readings and support and resistance levels to generate trading ideas. The classic trading signal might be seen if the RSI indicator falls below the 30 reading and starts to turn back in the upward direction (indicating oversold price activity). When this signal is seen as prices fall to a clearly defined support level, long positions can be taken on the expectation that prices will rise further in the future. Unsuccessful Trades vs. Trading Mistakes In some cases, ideas like this will be successful and generate gains. In other cases, markets will continue through oversold territory and stop out your position for a loss. In the second scenario, did the trader make a mistake? The clear answer is “no,” because all of the original trading rules were in place before the position was established. Once all of these factors are in place, we have no control over what happens next in the market. Using our original definition, connecting true trading mistakes to factors and elements we can actually control, these types of situations cannot be considered mistakes. These are simply unsuccessful trades. When we look at historical price activity, it is much easier to spot the situations where trading rules unfolded in a successful fashion. In real-time, however, those situations can only be judged in terms of probability. There are key differences here. Market scenarios that do not fall in line with the initial probabilities must be categorized correctly, because assigning the word “mistake” to setups that are normally successful might prevent us from using those strategies again in the future. This can reduce the occurrence of winning trades and limit overall gains as well. Elements of Trading Mistakes One way that traders can help their strategies and continue improving is to deconstruct the rules that make up their trading systems. Breaking those rules now becomes the only trading mistake we can make. If, for example, we set leverage limits to create 2-3% account risk at any given moment, a trading mistake could be seen if we enter into a position that creates the possibility for a 5% loss at any given time. In the RSI trading example above, a mistake might be seen if we were chasing markets and established positions before the RSI indicator actually fell below 30 and started to rise again. Whether your trading system is simple or complicated, remaining loyal to your pre-established rules is a vital prerequisite for success, and can help give you a leg-up over the competition. No trader knows where prices will actually be at the end of the day, so it doesn’t make sense to describe inaccurate price forecasting as a “mistake.” Instead, mistakes are directed at behaviors, and not in the end result of any individual trade. An alternate viewpoint can be seen in traders that operate with no plan at all. In this case, we might actually say that any trading decision is a mistake. When traders with no game plan are able to execute a successful trade, should these be considered successful behaviors? Luck of the draw does not create a successful traders, because repeating these same behaviors will not result in consistent profitability over time. In order to have consistent success, you will need to have a clear set of trading rules so that you can enter into positions when the opportunity arises. Analysis vs. Control Both technical and fundamental analysis can help us to take advantage of changes in price and market valuations - but this does not mean these analysis methods give us control over the markets. Of course, there are behaviors that can be followed which can improve the chances of profitability and minimize the damage seen when markets move in an unexpected direction. But the validity of these behaviors should be judged on performance over time, rather than in individual situations. Building on the strength of certain analysis methods, setting clear parameters for risk and reward will depend heavily on your ability to implement conservative position sizing. When looking at all of the possible mistakes, failures here mark one of the worst. If this area is not working out for you, this is the first place to focus your attention. There are special apps and calculators that can help with these problems (helping you set percentage risk parameters that will automatically calculate profit targets and stop losses). Other areas to watch are the time of day you trade, methods for trading during active or subdued markets, and how much capital to trade at any given time. Ultimately, you should make time to reassess your trading rules to see if there are inconsistencies for certain market environments. When you watch your progress in these ways, you can minimize your trading mistakes and show consistent improvement toward your trading goals.

When most potential traders start to research the forex markets, most of the common explanations describe foreign exchange as the “largest and most liquid market in the world,” and then go on to cite number of transactions that are made on a daily or weekly basis. In many cases, these articles will also compare the forex to the number of regular transactions that are seen in the stock or bond markets, and, of course, these numbers equal the proverbial “drop in the ocean” when compared alongside one another. But despite the frequency with which these facts are printed, traders will usually disregard liquidity as an important factor when trades are placed. This type of activity is surprising, especially when these areas are disregarded by technical analysts or charting traders. Liquidity is one of the central issues to consider when determining the likelihood that a certain level of support or resistance will hold and continue to remain valid. To be sure, liquidity in the forex market can be confusing to new and old traders alike. Since the forex market is so large, it can be difficult to determine liquidity levels with a high degree of accuracy. But there are still trends that can be identified, and certain market behaviors that are repeatedly seen during certain time of the year. Periods of economic data release also exhibit certain characteristics in terms of market liquidity, so it does make sense to have an understanding of how these factors will influence prices when levels trading. Liquidity vs. Volatility It should be understood that liquidity is measured in terms of the active number of buyers and sellers that are available for transactions in a market at any given time. If I am trying to sell an asset at $100 and there are no available buyers at that price, markets will gap to the next available price. If I am able to find a willing buyer at $100, we can complete the transaction and there will be no gaps in the market price. In this second hypothetical, we are seeing the effects of a transaction in a market with higher liquidity levels. For active traders, this will generally mean that these markets will experience reductions in volatility. In some cases, however, markets can be both volatile and liquid at the same time, but this is usually the result of external factors (such as major news headlines or significant market data). But the strong liquidity levels that are present in the forex market should be viewed as a strong positive when compared to other reforms of trading. The $4 trillion in daily transactions will generally ensure that you are able to get in and out of the markets at the price you want, and will also help trading probabilities in regions of clearly defined support and resistance (since there is a reduced likelihood for false breaks). Examples of Price Extremes If we think back to the Credit Crisis of 2008, we can remember that anyone trying to sell a home missed the benefits of market liquidity. Credit and available cash was much more difficult to come by, and this prevented some home sales from completing, as the negative impacts snowballed. What about a case where a stock trader finds himself on the wrong side of the market (shorting) as the news is reporting that the company is being bought at a premium during afterhours trading? In both of these cases, individuals found themselves in a situation where they could not “exit a trade” at the desired time and price because of the low level liquidity conditions in that were seen in the market environment. While these extremes are not seen to the same extent in the forex markets, there was still major declines in forex market volatility in 2008, and many major price gaps were seen. It should also be noted that the majority of the volatile activity in 2008 was in the downward direction (for stocks and high yielding currencies), and this is no coincidence. In the attached chart, we can see the 2008 price activity in the EUR/USD. Price gaps generally accompany market uncertainty, so, for certain asset classes, this is a very bearish scenario. This is another way changes in market liquidity can give traders an indication of where asset prices are likely to head next. Signs of Significant Liquidity Changes Since changes in liquidity can have a major influence on trades and trading decisions (giving validity to price levels, and helping determine potential direction), it is important to have an idea of when these changes are likely to occur. A market that is highly liquid might also be referred to as a “deep” or “smooth” market, and this is because the number of active traders is “deep” and overall price activity is usually “smooth.” Some currency pairs have greater liquidity than others. The most commonly traded pairs (such as EUR/USD, USD/JPY, and GBP/USD) will have might higher liquidity levels (and more stable price action), than pairs like EUR/HUF, USD/NOK, or USD/MXN. When managing risks (setting stop losses) liquid markets offer better protection levels. This is because the enhanced volatility that is usually seen after a major break (typical areas for stop placement) can lead to price gaps and more substantial losses. For this reason, some traders stick to liquid markets (commonly traded pairs), traded during stable times (not after data releases or during periods of extreme uncertainty). Spotting Times of Declining Liquidity Since forex is a 24 hour market, there is no added element of session closing (such as what is seen with stock exchanges), but there are still many situations where declines in liquidity can lead to dangerous price gaps. If, for example, a major interest rate announcement or high-interest news event might jar market expectations. In other cases, prices might see gaps as forex market open initially during the Monday Asia session (Sunday night in North America). Price gaps are much less common in forex markets (some studies suggest that 0.5% of forex price activity occurs during a gap), and there are some times during the day that bring reduced liquidity (such as session changes), and these times will be especially important for scalpers and others using short term strategies (which generally require tight stop losses). Asian session hours tend to be less active (favoring range bound strategies), while the London and US sessions tend to be more active (prone to large percentile moves and breakouts), but this activity tends to taper off during the afternoon periods in both areas. Additionally, market periods tend to slow during the Summer months and mid-month periods, while the end of the month will often see activity spikes as a larger number of investors square positions. Conclusion: Stay On Top of Market Liquidity and Its Impact on Prices Most traders tend to disregard the impact of liquidity and the related impact that this can have on price action. When dealing with less liquid currency pairs (or times when markets are holding off from establishing positions), markets are prone to see larger price moves - and these price moves tend to favor certain types of strategies. For these reasons it is important to have a handle on liquidity and its implications, as this can lead to positioning processes that are more streamlined and efficient based on what markets are likely to encounter going forward.

In a market that is as large as the forex, building an edge and maintaining that edge can seem like a daunting task. New traders often find themselves in situations where the first few trades go well, leverage is then maximized in anticipation of huge gains, and then a string of losers destroys the trading account beyond repair. This is an experience that has been had by most (if not all) experienced traders, and this can be a costly but valuable lesson on the road to a successful trading career. One of the things that should be understood first is that the behaviors described above represent the exact opposite of trading consistency, and consistency is what you will need (more than anything else) to develop a successful trading career. Playing to Your Strengths One commonly cited trading fact that might not seem apparent in the early stages is that aiming toward consistency is more important than aiming toward the 100% perfect trading system. Traders that are able to develop a system that plays to their strengths, time availability, and investment goals are the ones that will be able to gain an edge on the rest of the market. This is because playing to your strengths will make consistency easier to achieve, and this is where your focus should be - rather than in looking to try to capture every pip out of every market move. Finding the “perfect trading system” or capturing 100% of every market moves are unrealistic pursuits. What is possible is looking internally to see which styles and approaches work best for your investment profile and then to apply those methods using strict rules that can be regularly followed and repeated on a consistent basis. Imagine someone approached Kobe Bryant and suggested that he suppress his love of basketball and the natural talent he has developed playing the sport because he could make more money playing baseball. In hindsight, most people would say choosing baseball (and ignoring his natural impulses) would have been an unwise choice. This analogy can be applied to trading in the various occasions we see new traders persuaded to use advertised investment systems that promise great gains but do nothing to take the personality profile of the trader into consideration. But when traders use automated systems, those traders will have no way of understanding the risks involved with the systems and when losses do occur, traders will usually scrap the system entirely and waste a good deal of time and money on something that yielded no real advantages (intellectual or financial). Forgetting the “Perfect Strategy” Another common characteristic of new traders can be seen when looking for the “holy grail” or the “perfect” trading strategy. But the unfortunate reality that what works well for one trader is not necessarily got to “rain profits” for another trader. But the fact that there is no “perfect” system should be viewed as a positive - because now you can stop looking. Instead, you should be looking for the system that is perfect for you. It is your mindset and personality that is the most important component of any trading system, so you can save your time, energy, and sanity spent looking for a Holy Grail system that just doesn’t exist. In place of this, you should be looking for a trading system that allows you to spot high probability setups with consistency. Repeatability over time is the ultimate goal, rather than a system that can be followed blindly and applied to any trading style. Consistency Over “Perfection” When attaching your personality to your regular trading system, you should only rely on indicators that you can fully understand and are comfortable reading. The formulas before most of the commonly used indicators are relatively simple to understand, and there are many helpful articles on this site that can guide you in the right direction. It never makes sense to use an indicator if you do not understand how its calculations are made, and you are comfortable with the way it displays signals. Money management techniques are also a central issue here, as some traders are willing to take on more risk than others. Are you an aggressive trader or a conservative trader? In all cases, you money management system must be one that will allow you to remain cool, calm, and collected under even the most volatile market conditions. For the most part, indicators are used to give exit and entry signals, as these tools will provide price action signals that are relatively easy to spot and understand. Not all indicators look (or behave) the same, however, so it is important to choose indicators that move in ways that work well with your natural reactions. Indicators work along with your money management system in ways that cannot be duplicated by another trader. The combination of all of these factors will create your unique niche, and allow you to develop your edge over the market in the longer term. Looking at Hypothetical Reactions To exemplify this, we can look at two hypothetical examples in a long term uptrend. Let’s assume that the uptrend ran for 500 pips, and that the “beginner’s mindset” will be deemed as a failure if all of those pips are not captured in a long position. In some cases, it might be possible to capture all of these pips, but when using a system that is consistent and repeatable, this will not be the case in the vast majority of trading situations. A repeatable system that promises to capture 100% of a trading move simply does not exist, and thus it is unrealistic to have expectations like this. More often, the beginner trader will wait too long to exit a position and a corrective downward move will be seen (forcing the trader to give back some portion of the original gains). This unfortunate occurrence is all too common and comes as the result of the beginner's mindset focused on finding the perfect system. Instead, the experienced trader’s focus is elsewhere: for example, on identifying trades with strong risk to reward ratios. For the experienced traders, the proverbial “holy grail” comes with high probability trading setups that can be regularly identified with simplicity and consistency. These long term scenarios (a large number of trades) is far more important than any individual trade. In the hypothetical long term uptrend example above, the experienced trader would exit the position once risk to reward ratios are satisfied and the trend has started to reach an exhaustion point. Conclusion: Focus on Consistency, Not Perfection It is natural for traders to want to squeeze every possible pip out of a market move, but the unfortunate reality is that in trading it is simply not possible to hit the “bullseye” on every shot. Because of this, experienced traders avoid this practice altogether and instead choose to focus on systems that match the personality of the individual and can be repeated with high levels of consistency. With this, it becomes clear that trading takes work, and that there is not Holy Grail trading system that can be applied to everyone. Instead, the best approach is to look for trading opportunities that match your personal requirements for high probability scenarios using indicator setups that are easy to use and understand. Of course, losses will be seen but the main goal here is to find systems that generate profits over the long run, not in single instances.

The Ichimoku Kinko Hyo is technical indicator used in price analysis which helps traders to gauge changes in momentum and to stop potential areas of support and resistance. The indicator itself is made up of 5 individual lines, called the Kijun-Sen, Tenkan-Sen, Chickou Span, Senkou Span A, and Senkou Span B. The main purpose of the Ichimoku Kinko Hyo is to allow traders to quickly identify trend direction, underlying momentum and potential turning points (support and resistance) in future price action. One thing that separates Ichimoku analysis from most other forms of price assessment is that it can be used as a stand alone tool (without signals from other indicators). The word "Ichimoku" is Japanese and loosely translates to "one look" or “at a glance,” and this is highly important for understanding what exactly the indicator aims to accomplish. While the visual appearance of the indicator looks complicated when first introduced, most of the mystery is quickly cleared up once each of the 5 lines are understood. The Ichimoku indicator is meant to give traders the ability to quickly assess key elements at work in the market, literally with a single glance at your price charts. Once we have a basic understanding of the Ichimoku indicator, we can start to look at some specifics for managing trades. Here, we will look at one of the most critical elements of position management: identifying profit targets. Managing Parameters with a Diverse Trading System Ichimoku offers a very diverse trend following trading system which can aid traders in finding places to enter and exit positions, and these will generally be found as trends are changing course. When trades are proceeding in a favorable (profitable) direction, it is important to have a good idea of when to close the position so that those initial profits are not given back if prices show a sharp reversal. The profit targets that are outlined at the beginning of any trade need to show certain relationships with the potential for risks (risk to reward ratio), and this area is specifically defined by the level used for stop loss placement. Generally, traders need to see a risk to reward ratio of at least 2:1 (or 3:1) before considering that trade as being financially viable. Ichimoku is great for determining areas for stop losses but when looking for levels for profit exits, traders can use price pivots as a way of determining when positions should be closed. When developing an Ichimoku strategy for exiting profitable trades, it is important to look for ways that allow you to capture as much of a trending move as possible. It should also always be remembered that exit strategies are not static and can be altered as the trade progresses. One useful way to alter trades in these ways can be to use methods of scaling, which essentially means that the position is exited in parts (and not all at once). For example, if we are in a forex trade that is three lots in size, we might choose to close one of those lots while leaving the other two lots to run further. This method allows traders to capture small profits while still maintaining exposure to the original position. Adding Pivot Points When dealing with Ichimoku strategies, Pivot Points can be added to buy (for example, prices breaking above the cloud) and sell signals (prices breaking below the cloud). In the first pictured example, we can see a situation where a strong buy signal is being generated: Price activity is seen rising above the Ichimoku cloud, the Chikou Span is seen above the cloud, and the Tenkan crossover underneath the Kijun line in a space that is above the cloud: Now that we have an example of a buy signal, we need to know how to manage the position as it runs into profitable territory. Here, it should be remembered that Pivot Points are measured using the high, low and close of the previously charted period. The numbers associated with the Pivot Point are calculated by adding the high, low, and close, and dividing this number by three. Support and resistance levels that are created using these points are based on variations of these 3 levels, and these areas can be used for exiting buy positions (resistance) and for sell positions (support). Pivot Points do not need to be calculated manually, as this is a common feature of most regularly used trading stations. Combining Signals While there are many Ichimoku traders that use the indicator by itself, there is nothing to say that other signals cannot be added and used for determining the best time to exit profitable positions. After adding Pivot Points to the Ichimoku chart, trader can look for prices to move to the next important support level (for short positions), or resistance level (for long positions). Traders can then opt to scale out of positions (taking partial profits) and move stop losses on the remaining exposure to the break even point. This ensures a profitable trade that still has the opportunity to run further if the favorable trend movements continue. Alternatively, positions can be closed entirely, removing the risk of giving back previously accumulated gains. When looking to add Pivot Points to your charts, there might be a few different options, but the most commonly used measurement is the “Classic” Pivot Points (many traders view these as being most reliable). As a strategy measure, many traders will use monthly Pivots for trades made using daily charting time frames. These wider time frame Pivots tend to have better results as they are more commonly viewed. In the second attached graphic, we can see the setup for a sell position, with the stop loss placed just above the top of the cloud (a significant point of technical resistance, the breach of which would suggest a bullish trend change). On the chart, this resistance level is marked in green. The basis for the bearish bias can be seen in the price as it breaks below the cloud along with the failure seen in the Ichimoku lagging line (shown in the yellow circle). In order for the trade to be acceptable, we will need to see a profit target at least two times the pip value of the distance between the entry point and the stop loss. In this chart example, the profit target is placed in the low 0.8000s, at a Pivot support level in the path of the larger trend. This is shown with the second (lower) red line. Notice, however, that an initial profit target can be found at the first Pivot support (the first red line). This area can be used to scale out of some of the bearish position (at a profit) and to move the stop loss for the remainder of the position to break even. Trade Summary: Rules for Setup and Management First, prices should be seen below the Ichimoku cloud The trigger line (shown in black) crosses below the Ichimoku base line (shown in blue) The lagging line drops below the price Future price cloud shows trend direction (downward for bearish trades, upward for bullish trades) Pivot support levels used as bearish profit targets, Pivot resistance levels are used for bullish profit targets Consider scaling when using multiple Pivot Points

Tradingpsychologie, a recent book from German author Norman Welz, was received with a good amount of favor both for its theory and application but most of the book is centered on the appropriate trading psychology. Whether you agree with his opinions or not, Welz does offer a good deal of experience and some insights that are relatively unique when compared to most of the available materials on market psychology. The central trust of the book is that traders must develop the right mindset before profitable trades can be made on a consistent and long term basis. Welz makes the attempt to separate his ideas from most of the literature currently available on the topic but stressing the idea that applied trading psychology is the only useful information on the subject, and this will likely be viewed as refreshing for active traders not interested in theory as much as they are in the daily trading routine. It is widely understood that successful trading requires discipline and a prudent approach, but the actual acceptance of this idea in practice is something totally different, so it is not enough to simply understand these concepts without actively implementing them when trades are placed and managed. Emotional Security in Trading Welz starts his assessment of the proper mindset for active traders with the emotional perspective, essentially suggesting that human being are in constant need of security (in all aspects of life). This presents some problems because anytime a position is open, traders are completely exposed to monetary losses (the exact opposite of security), so there are very few businesses that are less well-suited to personalities that are not prepared for these factors. Welz argues that there are not many professions that experience psychological and emotional responses that reflect many aspects of our personalities that we otherwise might rather forget. For Welz, the financial markets become inseparable from our own psyches and egos, and in the end there is no difference between financial performance (profits), and personal self-worth. Because of this, attaining the right trading mindset is a vital but complicated task but, at the same time, it is difficult to divorce our minds from from the external factors (both financial and psychological). It can take time and patience to separate your mind from its old habits, but at the same time it is these habits that are creating a large number of trading mistakes in the first place so it is essential that these elements at least be identified when assessing a daily trading routine. Looking broadly, our trading psychology is informed by our personal histories, our friends, family, education, and media (social and otherwise). So, as we actually construct a daily trading routine, all of these factors will play a role in the regular patterns we exhibit, and some of these traits will inevitably be less than optimal for maximizing profit results. Separating the Objective from the Subjective When dealing with the approaches that are espoused by Welz and similar theorists focused on the psychological aspects of trading, it is important to understand the differences that are seen with the objective and subjective. The subjective, of course, measures our beliefs, “assessments,” and “gut feelings,” while the objective is the true market reality. While total objectivity is never completely attainable, it is important to understand the role of the brain within the larger trading environment. In the Welz view, traders cannot divorce themselves from psychology, and it is this psychology (brain function) that allows us to to make assessments about potential risks and to recognize underlying shifts in trend and price momentum. When all of these factors are taken into consideration, it becomes clear that mental fortitude is a requirement for success when trading the financial markets. According to Welz, 95% of all trading activity is subconscious and the behaviors that take place in the past are likely to repeat themselves. Since most traders wind up placing losing positions, it starts to become apparent that most of these behaviors are repeated and this is what leads to compounding losses. As a foundational basis for these assertions, Welz discusses an academic survey of traders that were given a trading strategy with high quality backtesting results for 19 of the previous 20 years. After one year of trading this system, all but one of these traders were unable to produce consistently successful results, and the conclusion made was that psychological behaviors were preventing this accurate system from being used correctly. From this study, Welz concludes that success and failure are completely dependent on logical and emotional functions in the brain, and that this is true to such a large extent that even traders with excellent trading systems can have difficulties if negative (and repeated) behaviors are not removed from our daily trading routines. The Tendency to Ignore Psychology When looking at the reasons traders often ignore psychology, Welz cites the fact that more traders are male, and less likely to consider psychology as an important factor in daily routines. Welz suggests that men tend to think that success depends on remaining rational, remaining informed with the dynamics of the market, and compiling experience in decision making. Welz responds to this by suggesting that experience, rationality,and compiled information fail to create success in trading if the brain is not programmed appropriately. When looking to program the brain in an “appropriate” fashion, Welz advises traders to actually use hypnosis to uncover critical aspects of the unconscious. In this state, traders are encouraged to anchor the required competences in the subconscious, in order to remove certain elements of fear and other logic obstacles. Welz suggest that only after this has been achieved will traders be able to engage in the appropriate behaviors, motivations and energies. According to Welz, each trader has different mental barriers and logical obstacles that must be removed in order to trade profitably on a consistent basis. The Welz Trading Discipline For Welz, proper trading discipline comes with the ability to modify behaviors toward a specific goal and to overcome the logical barriers that have prevented you from attaining those goals in the past. To overcome this resistance, traders must integrate knowledge of the markets with a trader’s brain and mental capabilities. Traditional skills are, of course, highly important, but traders must be able to prevent those skills from being overshadowed by inappropriate mental patterns and behaviors. All of this means that successful trading involves some degree of personal modification, so while the idea of actual hypnosis might seem extreme to some, Welz argues that anyone unwilling to take steps to truly change their frame of mind should not put money at risk in the trading markets. If traders focus solely on the logic in charts and price trends, other aspects of the process might be missed and traders might have no way of dealing with the array of emotions that comes with the process of market trading. This, in a nutshell, is the thrust of the arguments in the Welz book. Anyone Can Develop the Trader’s Midset Ultimately, Welz believes that anyone can become a successful trader as long as these common elements of fear and lack of emotional sense can be controlled. This does take some time and effort, as well as a good grip on the realities of the market. Of course, nothing can replace market knowledge and experience in the ways of price activity, but without the complete package, even the best systems can lead to failing results. Welz also discusses the importance of having realistic expectations (you will not become wealthy overnight), because if this were the case, everybody would be a trader. All too often, the importance of psychology in the trader’s mindset is neglected, so it is essential to analyze our own personality traits and look to remove entrenched behavior patterns that prevent trades from reaching their potential.

It can be said that technical analysis in the forex markets is essentially an exercise in framing price activity. Strong skills in this area can help traders to identify exit and entry levels that enhance profitability probabilities, and these framing techniques use historical price activity to determine the possibility of reversal or extension in a given price movement. While these techniques are incapable of predicting the future price of an asset, they can aid in forming expectations in whether or not prices have additional room to extend, or are more likely to reverse. In most cases, traders are looking for indications that one of these scenarios is in place before establishing new positions (or looking to close established positions). Of course, there is a wide variety of methods technical analysts can use to frame price activity, so it is important to test out a few of these approaches in order to determine which feels most comfortable for you. When studying charts, in many situations, it will look as though market values are completely dictated by momentum (or some other force of nature), and that prices can only reverse once this momentum has reached an extreme. Price framing techniques can be one of the best methods for determining when this momentum has reached its extreme points, and when there is an increased likelihood that these formations will result in a bounce or price failure, appropriate entry and exit levels can be identified. When using price channels for these strategies, there are a few different formats that can be applied, and so traders only familiar with the traditional format should take a look at some of the other options to see which format is most suitable. Here, we will look at 3 common approaches to price channel analysis: Trend Line Channels, median-line analysis with Andrew’s Pitchfork Channels, and Donchian Channels. Trend Line Channels Price channels can accomplish different things when traders are attempting to pinpoint continuations in developed trends, or reversals back into an established ranges. Its important to understand the basics, so first we will look at Trend Line Channels. Because of the simplicity involved, some traders might overlook this method of analysis but the fact is that Trend Line Channels can be a highly effective, and can be a very good place to start when traders have limited technical analysis experience. Trend Line Channels are easy to identify and understand, and these can be used in both range bound and trending markets. The central elements are dual trend lines, connecting points of support and resistance, and these channels can come in uptrends, downtrends, and range bound markets. The central visual should be familiar, in the first attachment is an example of an uptrend channel. As a general rule, prices should reach both the upper (resistance) trend line, and the lower (support) line at least two times. Preferably you will see three separate tests, and more is definitely better (improves on the validity of the channel). In rising Trend Line Channels, market momentum is positive and prices are making higher highs along with higher lows. This generally leads to buy entries at channel lows and possible sell exits near the top of the channel. Sell entries are generally not advised in these cases (at channel tops), as the majority of the market momentum is in the upward direction. In declining Trend Line Channels, market momentum is negative and prices are making lower highs along with lower lows. This generally leads to sell entries at channel highs and possible buy exits near the top of the channel. Buy entries are generally not advised in these cases (at channel bottoms), as the majority of the market momentum is in the downward direction. Looking for Price Extremes with Donchian Channels Donchian Channels were created by Richard Donchian in the 1980s, and these studies have had a massive impact on the way markets view channel activity on historical price charts. The main themes center on areas of buying strength and the differences seen in the areas of selling weakness. Donchian Channels are used as a breakout strategy with a high probability outcome, which located areas where prices have surpassed significant highs or lows over a given time frame (which can be individually selected). Donchian Channels tend to give the best signals during market environments with strong trends, weaker results tend to be seen during sideways ranges. The Donchian Channel system looks for trend-following breakouts, and the signals are based on the following criteria: Prices closing above the Donchian Channel produce buy signals (and indicate areas to close shorts) Prices closing below the Donchian Channel produce sell signals (and indicate areas to close longs) Trading with Donchian Channels produces relatively few signals but in high probability systems, formations tend to have improved accuracy. In the second attachment, we can see a visual of how Donchian Channels look on a price chart. Watching the Median Line with the Andrews Pitchfork Andrews Pitchfork methods tend to fall into the “advanced” category of trading but once we understand the locations trading signals are generated, the tool becomes much easier to use. On the whole, the Andrews Pitchfork system is based on the idea that market values revert to the mean on averaged time frames and divergences from the indicator’s median line will continue until price trends reverse. The main benefit of the Andrews Pitchfork is that it allows for tight stop losses and conservative profit targets. The overall construction of the Andrews Pitchfork is built on market pivots. Three channel lines are drawn (which looks like a pitchfork). A “buy” signal is seen when prices start from the mid point, rise to the upper trend line, and then fall to the lower trend line. The first profit target is the median line, the second profit target is the upper trend line. Stop losses can be placed just below the lower trend line, but the eventual profit target is seen at the upper trend line. A “sell” signal is seen when prices start from the mid point, fall to the lower trend line, and then rise to the upper trend line. Sell entries can be taken here. The first profit target is the median line, the second profit target is the lower trend line. Stop losses can be placed just below the upper trend line. In Andrews Pitchfork analysis most of the arguments rest on the fact that prices gravitate toward the midline 80% of the time when markets are trending. In strongly trending markets, traders tend to target the opposing trendline (for profit targets), and stops can be placed outside the Pitchfork, sometimes using the Average True Range to define extreme areas. Conclusion: Consider All Trend Channel Strategies It is important to remember that trend line strategies can be a highly effective method for determining exit and entry points for chart based trades. In many cases stop losses can be kept tight, which is very helpful in improving risk to reward ratios. Here, we looked at three different formats and traders can choose from the traditional Trend Line Channel, the Donchian Channel and the Andrews Pitchfork, as one of these methods of likely to aid in your individual approach to technical analysis.

The Elder-Ray Index is a price chart indicator introduced by Alexander Elder which calculates levels of buying and selling pressure over a given time frame. The indicator combines two unique elements, which Elder calls the "bull power" and "bear power" indicators. The aim of these various elements is to enable traders to identify the position of current prices, relative to a pre-determined EMA. The calculation for the indicator is as follows: Bull Power Indicator = Period High - (X-Period EMA) Bear Power Indicator = Period Low - (X-Period EMA) When using the Elder-Ray Index, chartist traders can use price divergences in conjunction with the Bull and Bear Power Indicators when establishing positions. For long positions, traders will watch for times when the Bear Power indicator falls below zero and is starting to rise, while the Bull Power indicator reaches a peak that is higher than its previous peak. Conversely, for short positions, traders will watch for times when the Bull Power indicator rises above zero and is starting to fall, while the Bear Power indicator reaches a trough that is lower than its previous trough. Traders can also look at the slope of the EMA as an additional feature, as this helps to confirm the direction of the dominant trend. Themes Behind the Indicator Alexander Elder is a newer contributor to the field of technical analysis and his arguments tend to rely on the behavior of moving averages and the differences between the highs and lows that accompany those averages. When looking specifically at the Elder-Ray Indicator, we can see a tool that is linked inextricably to the calculations of oscillators which are typically used to find areas where market prices are likely to turn. These turning points tend to come after markets reach the emotional and psychological extremes in bullish and bearish waves, and since these extreme price points are generally unable to sustain themselves for very long, these situations tend to present excellent opportunities for contrarian trading strategies. In these cases, the potential for reversal far outweighs the potential for extended continuation, so probabilities tend to side with those implementing a contrarian trading strategy. When bullish exuberance unfolds and greedy investors late to the party enter into a position, experienced investors start to look for shorting opportunities. When the market is tanking, and fear has taken control of the market majority, experienced traders look for areas to start buying. The Elder-Ray Indicator has labels for these areas, and this is where the Bull Power and Bear Power elements come into the picture. Interpretations Using the Indicator Next, we look at the various ways traders can interpret the component parts of the Elder-Ray Indicator. The first point to remember is that price action represents the consensus opinion on the appropriate value for an asset at a given time. In technical analysis, Moving Averages are used to express that same consensus over an extended time frame. The EMA that is most commonly used with the Elder-Ray Indicator is a 13-period average. When traders interpret the EMA, the most important factor is the slope. When the slope is rising, the market consensus is showing a bullish reaction to external events. When the slope is falling, the market consensus is showing a bearish reaction to external events. Based on this, the Elder-Ray system trades can be placed using a confirmed EMA slope signal but when prices show extreme extensions, reversals are imminent. This means that the highs of the day represent the maximum “power” of the bulls, while the lows of the day represent of the maximum power of the bearish traders. Using the Elder-Ray system, traders can assess the difference between the period high and the EMA to determine the Bullish “Power” in place at that moment. This measurement is essentially the extent to which bulls have been able to move prices above the longer term consensus value (the Moving Average). Bullish “power” increases when external developments strengthen, and then weaken when those factors weaken. Conversely, Bear “power” will be measured in the reverse fashion and will show the ability of bears to put pressure on prices and move values below the longer term valuation (the moving average). The distance between these elements will widen when bearish market sentiment weakens, and narrow when conditions improve. Bearish Power is, by definition, negative, so if traders do see an instance where this turns positive, Bullish Power has assumed control. Trading Signals with the Elder-Ray Indicator When using the Elder-Ray Indicator, there are some necessary conditions that must be in place before any buy or sell positions are initiated. When looking to make the decision to buy or sell an asset, the Elder-Ray system sets parameters (shown in the first chart graphic): For buy conditions, the EMA will show an uptrend slope and the Bear Power indicator will be in negative territory but rising. These are the minimum requirements for buy positions but additional confirmation can be found in cases where the Bull Power indicator forms a peak that is higher than its previous peak. In the best case scenario, all of these conditions will be present as the Bear Power indicator is showing its upward movement along with a bullish divergence. Looking at the opposing scenario (shown in the second chart graphic), sell signals are generated when prices reach a new high while the Bull Power indicator forms a lower peak (when compared to the rally seen previously). The EMA will show that the trend is down as the Bull Power indicator is still in positive territory and falling. Additional confirmation can be found when the latest trough in the Bear Power indicator is lower than the previous troughs and the Bull Power indicator starts to drop after a bearish divergence. Similar to instances for buy positions, the highest probability sell signals come when divergences are seen between the Power signal and the actual price activity. Exiting Positions The Elder-Ray Indicator is also useful for knowing when to close an open position. For example, when looking to cover a short position, traders should note instances where the Bear Power Indicator shows changes in the strength or weakness of bearish momentum. If prices are making new lows as the Bear Power Indicator is making new lows, an extended downtrend should be expected. In other cases, the Bear Power Indicator might show a trough that is more shallow than the previous trough and if prices are seen making new lows, a Bullish divergence would be present. For those short the asset, it would be a good time to exit the position, as prices are likely to reverse in the upward direction. Divergences can be used for long positions as well, and trades would be closed after Bearish divergences are identified. Conclusion: Look for Divergences When Using the Elder-Ray Indicator For traders using the Elder-Ray Indicator, the highest probability trading opportunities can be found when divergences are present when looking at price action and the Bull/Bear Power Indicators. The central strength of the Elder-Ray signals can be found when these additional divergence elements are identified but as we can see from the chart graphics, the minimum requirements for trades do not include these divergences. When placing these additional requirements for trades, fewer signals will be generated but the signals that are seen will have an increased probability in accurately forecasting prices.

In the next part of this article, we will look at ways to fine-tune these harmonic trades and discuss a newly discovered harmonic pattern many traders might not have seen previously. Creating Tight Trading Parameters One of the main benefits of the harmonic trading patterns is that the create incredibly tight trading zones that pinpoint reversals down to a very small number of pips. This allows traders to set stop losses and trade entries that are extremely fine-tuned with the PRZ. This area is referred to as a “zone,” and not a level, however, because the reversal point is actually not an exact price. This is because there are two relevant measurements that produce slightly different results. First, we have the retracement (or extension) of move XA which gives us one number at the D point. Second, we have the extension of price move BC which gives us a slightly different D point. The space between these two D points forms the Potential Reversal Zone, and this area is used as the basis for both trade entries and stop losses. It should also be noted that price move BC can have varying lengths of extension, and this can produce different results for the PRZ. Because of this, it is important to be aware of the fact that price move BC, so traders should watch the length of price move BC to get a better sense of what is actually going to happen in the PRZ. Watching Price Move BC When all the projected price moves meet the criteria for harmonic patterns, positions can be established anywhere within the PRZ. In some cases, the PRZ will be larger (for example when using longer term time frames), and when this happens, traders should watch the price action to see if price move BC shows a longer extension, as this can change the overall structure and create different entry points. When placing a stop loss, the order can be set outside of the widest possible extension of the price move BC. For example, if we are watching a developing crab pattern, this would should be seen at the 3.618 measurement. If prices reverse within this measurement, stop losses can be placed above/below this Fibonacci level, as you would need to see an additional extension later in order to invalidate the pattern. If the pattern does become invalid, the position should be closed but the total risk will be relatively minimal when compared to other types of trading patterns. Profit Targets and Stop Losses Another strategy method to consider is to wait for prices to hit the extreme calculation levels in the PRZ and then to show signs of retreat from that area (helping to validate the price point). Once this activity is seen, there is a greater likelihood that the stop loss (placed outside the PRZ) will not be hit and so this helps to increase the probability for a successful trade. Harmonic patterns often develop during times of high market volatility, so you do not want to set yourself up in a position where prices are showing an extreme move and run right through the PRZ. When looking at profit targets, traders can use support and resistance levels that can be found inside the pattern. Many traders look at the B point when looking for an initial profit target, as a majority of the market is influenced to change positions after the original pattern unfolds. Finding profit targets with harmonic patterns is a much more proactive process than what is seen when trading other types of patterns. It is important to watch how prices react when coming back to the price points within the pattern. Another strategy is to watch for shorter term patterns that might conflict with your original position. For example, if you are in a long position based on a bullish Bat pattern on a daily chart, there might be an instance where you see a bearish Crab unfold on the hourly charts. This is essentially an indication that now might be a good time to close the position, as prices have likely traveled as far as they will go with respect to your original trade. It is very common to see multiple patterns inhabit the same space on a chart, so it is important that these occurrences not be ignored, as this can be a very good indication that there is indecision in the market. The Shark Pattern Next, we will look at one of the newest harmonic patterns - the Shark pattern, which was discovered by Scott Carney in 2011. Visually, the pattern structure can be seen in the first attachment. Those with some experience with harmonic relationships might notice that the Shark pattern is a building 5-0 structure which is traded from the C point, with a target at the D point. The D point price target is not shown in these graphics but this level can be calculated using the confluence in price moves AB=CD and the 50% Fib level from the BC price move. In addition to these trading signals in the Shark, subsequent trading signals can be found as well, and these will allow traders to build further on the position strategy. These signals come from the 3 subsequent patterns that can emerge after the Shark formation is initiated. The first can be seen as the Shark leads to the 5-0 structure. The next attachment shows this structure’s visual elements. With the pattern, it is easy to see how the Shark can ultimately unfold, becoming the 5-0 pattern but at the same time it should be remembered that not all 5-0 patterns start with a Shark pattern. From the graphic, we can also see how the initial profit target in the Shark comes at the D point in the 5-0 structure. As the 5-0 develops, traders can enter into positions at the D point (in the opposite direction of the trade taken with the initial Shark signal). Another element to watch is the fact that price move BCD in the 5-0 structure will, in many cases, become the price move XAB in a later Crab or Bat pattern. Key measurements here can be seen with the B point showing at the 50% Fib of price move XA, as these are components of both the Crab and Bat patterns. Given this information, traders should look for developing Crab or Bat patterns, and once the C point can be identified, traders can position themselves with a trade based on a Bat Action Magnet Move (BAMM), which is based on the Bat harmonic structure. These trades allow for positions to be established at the price level from the B point, targeting the D point of the next developing pattern. Generally, BAMM trades are taken only when the signal is inline with the dominant trend (BAMM trades are not contrarian). But even in cases where the BAMM trade is not taken, the final position can be taken if a Crab or Bat pattern later forms. So, as you can see, the Shark pattern can be highly useful for initiating a series of four possible trades, as long as the Fibonacci calculations meet the measurement requirements. Conclusion: Using Harmonic Patterns to Trade Extreme Market Moves Harmonic trading offers a great deal of precision for traders looking for reversal points in extreme market moves. Perhaps the primary benefits of these reversal points is that they are confined within a very tight area (the PRZ), and this allows traders to set small stop losses and limit risk. Harmonic trading is more mathematical and less subjective than most other approaches in technical analysis but it can take time to see stable patterns emerge. Here, we looked at the traditional harmonic patterns, and a new entry into the harmonic world with the Shark pattern. Many of these patterns have similarities and can change from one structure to another, so traders should closely watch their charts when dealing with these patterns - especially on the smaller time frames.

Harmonic patterns build on simple geometric chart patterns with the use of the Fibonacci sequence and the retracement and projection percentages that are typically associated with these numbers. Technical traders that use these patterns are looking for potential turning points after extreme trending moves are seen. But harmonic patterns are somewhat unique in that this trading approach looks to predict price movements, rather than to simply describe them. For this reasons, harmonic patterns show some differences when compared to trend trading or the identification of overbought and oversold conditions. Many common trading methods involve simple reactions to market conditions, rather than actually attempting to predict (and project) what will happen next for the price of an asset. Here, we will look at some of the ways harmonic patterns are actively used in forex markets, and learn about some of the ways the “Divine Ratio” is actually put to use. Looking for Repeating Price Patterns Harmonic trading looks for patterns in price activity and positions are initiated based on the idea that certain types of patterns repeat themselves over time. The foundations of these patterns come from the 0.618 (or 1.618) ratio and its complementary Fibonacci ratios, which can be found in common retracement and projection analysis. The logic behind these applied ratios comes from the idea that the 0.618 ratio is common throughout nature and the universe and can even be found in structures that were made by human beings (unintentionally). The prevalence of this ratio suggests that these measurements will apply to the financial markets as well, as these markets are a small part of a universal whole. In identifying price patterns of differing lengths and magnitudes, traders can use Fibonacci ratios to plot potential turning points. It is in these areas that actual trades are taken. The “Father” of the harmonic trading approach is considered to be H.M. Gartley but his foundational work did not actually use Fibonacci ratios in his analysis. In later years, Scott Carney has done major work to develop this form of analysis and many of the price patterns currently used are attributed to Carney. Difficulties When Trading with Harmonics The textbook structures for harmonic patterns are very precise, and require prices to unfold in movements of a set magnitude in order to signal a reversal point and trigger an actual trade. There will be many instances where traders might see a pattern that resembles one of the harmonic structures but if the Fibonacci measurements do not align with the predetermined requirements for the pattern, the structure is not valid. This essentially means that the shape itself is not enough (as it might be with a head and shoulders or flag pattern), to actually generate a trading signal. At the same time, however, this can be viewed as a positive as it takes out an element of subjectivity and can enhance the validity (and eventual accuracy) of the trading signals that are sent. Structures Within Structures One of the accepted strengths of harmonic patterns is that they give traders an indication of how long impulsive waves will last, in addition to the price points where the moves will occur. But the major trading difficulties are seen when the reversal area fails to catch prices and they continue in their original direction. This possibility always exists, and this is dangerous because harmonic patterns pick up extreme moves where price gaps can easily be seen. In this way, it can be more difficult to control risk when dealing with these patterns (despite the limited stop losses that are typically used). Another factor to consider is that patterns can (and often will) exist inside other patterns. Multiple (smaller) price waves can be seen within a single (larger price wave), and this can go far to complicate and confuse the analysis. This can occur because of the fractal nature of harmonic analysis. Larger time frames tend to be viewed as being more reliable but it is preferable to see all of the available signals move in agreement. It is also possible to see non-harmonic patterns inside the harmonic area and these patterns might show conflicting signals. But in cases where these patterns do agree (such as a reverse head and shoulders, and a bullish Crab pattern), this can offer an added level of validity to the signal. The 4 Main Pattern Structures At this stage, there are many harmonic patterns that can be traded but, generally speaking, there are four structures are are most common. The most well-known patterns are the Gartley, the Bat, the Crab, and the Butterfly. The first of these was the Gartley, originally introduced on the book Profits in the Stock Market. This original pattern dealt with simple fractions, rather than Fibonacci levels but it was on this pattern that all the later patterns were modeled. As we can see in the first attachment, Fibonacci ratios were later added to the Gartley pattern. In bullish cases, the pattern tends to be seen at the beginning of an uptrend, with the downside corrective moves reaching completion at point D. This D Point is the 0.786 correction of the XA price move, and is the 1.27 (or 1.618) Fibonacci extension of the BC price move. This D Point is also referred to as the PRZ, or potential reversal zone. Buy positions can be established in this area, with stop losses slightly below the D Point. Bearish examples would be the mirror image of this scenario. The Butterfly Pattern The butterfly pattern is a variation from the Gartley in that it looks for reversals at new lows for bullish patterns and new highs for bearish patterns. Similarities are seen, however, at the D Point, which is still the reversal point. Fibonacci measurements of the D Point must show extension of BC equal to 1.618 or 2.618. This will be seen with the extension of XA equal to 1.27 or 1.618. The D Point is again the entry point, with stops taken just below this area (the PRZ) for bullish trades. The opposite would be true for bearish trades. The Bat Pattern The bat pattern is close in resemblance to the Gartley, but uses different Fibonacci measurements. The B Point in the Bat uses a smaller retracement of the move XA, equal to either 0.382 or 0.50 (not 0.618). The Fibonacci extension of the move from BC to D must be at least 1.618 but can extend as far as 2.618. This places the D Point at a 0.886 retracement of the initial XA price move. This area is the PRZ, where positions are established. The Crab Pattern Of all the harmonic patterns, the Crab pattern is the pattern that posts the best back testing results and is thought to be most accurate in price forecasting. The PRZ for these patterns is also the smallest of the group, which means that loss potential is more limited. Similar to the Butterfly, the Crab pattern identifies reversal point at a new low (bullish turns) or at a new high (bearish turns). For example, with a bullish Crab, we will see the B Point retrace a maximum of 0.618 of the move XA. The Fibonacci extension of the price move BC to the D Point is the largest of the group, as this ranges between 2.24 and 3.618. The PRZ at the D Point is an extension of 1.618 of the price move XA. Entries made at the D Point have the smallest PRZ, and the smallest stop loss levels. In the next part of this article, we will look at ways to fine-tune these trades and discuss a newly discovered harmonic pattern many traders might not have seen previously.

A common mistake made by many technical analysis traders is failing to watch the ways various assets interact and perform under different market conditions. Some assets show incredibly high correlations (moving in a similar fashion at similar times), while others are inversely correlated to a near-perfect degree. This information can be highly valuable for traders because the price behavior forecasts that are required to make successful trades can be tailored (at least in part) based on the activity that has already been seen in related assets. Historically, one of the best examples of highly correlated assets can be found in the stock market and in the carry trade, which pairs high interest currencies with low interest currencies. The strategy requires traders to buy a high yielding currency, using a low yielding currency as the funding asset. In these trades, investors can gain the dual benefit of favorable currency moves and the interest that is captured for as long as the trade is held. Common examples of carry trades include AUD/JPY and NZD/JPY but the currency pairs that are used in these cases will depend on the prevailing interest rate levels at the moment. The Japanese Yen has offered extremely low interest rates for a long period of time, and because of this, the JPY tends to be the “go-to currency” for those looking to position themselves using this trading method. Asset Performance During Periods of Market Stability Now that we understand how the carry trade works, it is important to understand which environments provide the best opportunities to make gains using this strategy. To do this,we can look at opposing market scenarios. In the first case, imagine that price activity is rapidly changing because of widespread economic uncertainty. A good example of this would be the 2008 Credit Crisis, or the 1999 tech bubble in stock markets. In these cases, price activity was highly volatile and this tends to be unfavorable environments for both stocks and carry trades. A quick look at chart activity during these periods will show extreme bearish declines, as investors looked to pull their money out of riskier assets and find protections in safe havens. Now imagine a second scenario, where price volatility is more subdued, and market fundamentals are showing more stable and predictable data releases. Excellent examples of this could be seen during the market rallies of the 1990s and in 2007. In these cases, the general stability of the financial world allows investors to take on additional risk (in order to increase the chance of enhanced gains). During periods like this, both stock markets and carry trades tend to perform well. Applying this Behavior to Trading The use of technical analysis is essentially an expectation that what has happened in the past is likely to happen again in the future. With this in mind, trades can be taken based on the market environment that is currently in place and on the ways these different assets have performed with respect to one another. For example, stock markets are now approaching their highest levels in 5 years, which leads many traders to look at stocks as overbought and in danger of a downside reversal. This trading bias can be applied to highly correlated currency pairs (such as the AUD/JPY), and major breaks of support will then be viewed by many as being more credible, creating a better chance of significant follow-through. Hypothetically, the opposite scenario (a large scale bear market in stocks) would be viewed by many as a buying opportunity in currencies like the AUD/JPY if upside breaks of resistance were seen. This bullish bias would be based on the idea that a heavily correlated asset (the stock market) is oversold and is ready for an upside correction. A Look at the Historical Correlations In the attached graphic, we can see the historical correlations between one of the most popular carry trade currencies (the AUD/JPY) and the most commonly traded stock index (the S&P 500). When looking at correlation tables, a reading of 1 indicates perfect asset correlation (prices of both assets move in “lockstep” 100% of the time). A reading of 0 indicates both assets have no correlation (move randomly with respect to one another), and a reading of -1 means that both assets show perfect negative correlation (move in opposing directions 100% of the time). Looking at the correlation chart, we can see that the AUD/JPY and S&P 500 show a reading close to 1 for most of the charted time period. Over the 6-year period, there are only three brief intervals where this correlation breaks down into “random” territory and, on the whole, this suggests a highly reliable relationship that can be used as additional information when trades are placed. Of course it should be remembered that these relationships can change. If, for example, Australia decided to drop interest rates to 0%, the AUD/JPY would no longer qualify as a carry trade (and the correlation relationship would no longer apply). For this reason, it is unwise to base trades solely on these types of correlations. A more prudent approach is to use these relationships in conjunction with other forms of technical analysis in order to improve probabilities for gains. The main point to remember is that correlation tables that show asset relationships closer to 1 (or even -1 for opposing trades), tend to provide the most reliable signals. Using Inverse Correlations A final point to remember is that we are not limited to assets with positive correlations when structuring trades. If fact, negative correlations can be equally valuable as long as we understand what this relationship suggests. For example, Gold is typically though as as a safe haven asset, with a negatively correlated relationship with JPY carry trades. In these cases, technical events that are bullish for Gold should be viewed as bearish for carry trades (such as the AUD/JPY or NZD/JPY). In a hypothetical trading situation, occurrences like oversold conditions for Gold would actually suggest future selling pressure for carry trades, as a bullish correction in Gold would become more likely. Conversely, overbought conditions in Gold would suggest that pairs like the GBP/JPY are likely to experience a rally going forward. Conclusion: Understand the Relationships between Different Asset Classes Currency correlations provide traders with valuable information that all types of strategies can utilize. Calculations like correlations tend to be used more by fundamental traders but it is important for technical charting traders to understand these developments as well. Anything that can turn the odds in your favor when placing a trade should be used and acted upon, and the performance of correlated (or even negatively correlated) assets can signal some key ways trends are likely to develop in the future.

Hi clmac, there will be trading setups with Fractals in a future article. I will post a link in this thread.

Before his death, Benoit Mandelbrot was one of the most celebrated mathematicians in the world, and most of his work was based on the belief that the wider view of price behavior in financial markets is primitive and in need of large revisions. Mandelbrot's work sought to update these “medieval” views of market behavior so that economists could update the ways asset price changes are understood on a fundamental level. Mandelbrot's legacy as one of the main contributors to the field of technical analysis is firmly established but there are still some traders that view Mandelbrot's work as being disconnected from the real workings of asset markets. Here, we will look at some of Mandelbrot's main contributions to the study of price behavior. The work started roughly 50 years ago and involved the creation of a new type of mathematics. Rather than focusing on accounting or simple geometry, Mandelbrot equations dealt with mathematical shapes rough and complex, rather than smooth and simplistic. Additionally, the pattern repetition that Mandelbrot found was largely uncommon and unexpected relative to most of the similarly focused work that had come before him. Mandelbrot's equations would later be referred to as Fractals and the wider applications for these equations have been seen in environments that are far-removed from the world of finance (being used to describe clouds and coastal formations, to forecast the ways rocks and metals will wear over time, and to generate computer graphics programs. Mandelbrot’s Approach to Finance Markets Focusing on how Mandelbrot's work relates to a financial context, specific examples can be seen in the ways Mandelbrot criticized a large majority of his colleagues attempted to predict the changes in price activity. Mandelbrot’s initial assertions were that market participants should be looking to describe market behavior before attempting to forecast or predict it. While this might sound disappointing to some looking for the “holy grail” of price forecasting, for Mandelbrot, this was an essential step in the process because accurate predictions would be impossible without first having accurate descriptions of what exactly is happening in market environments. Mandelbrot’s Critiques of Prevailing Ideas Since Mandelbrot largely disagreed with most of the price forecasting approaches around him,it should be noted that Mandelbrot's main contention was with the idea that price activity is determined by dual opposing positions (the decision to either push prices higher, or to drive them lower). This idea he saw as an overly simplistic view of market activity, reducing asset valuations to nothing more than the toss of a coin: Heads, markets buy and push prices higher, Tails, markets sell and drive prices lower. Before Mandelbrot, this idea reigned as an explanation of how prices remain generally supported: Buyers and Sellers constantly bump into each other and keep prices suspended with real valuation changes occurring slowly. Mandelbrot argued, however, that this view does not adequately account for the occurrence of major swings in market volatility. Imagine a stock that falls from $50 to 5 cents. Surely, for Mandelbrot, these suspension ideas (and the binary Coin Toss view) contain some inefficiencies and cannot be relied upon to forecast all possible price outcomes. According to Mandelbrot, large increases in price activity should never happen when viewing markets in a binary, suspension fashion. But, of course, we know that these situations occur all the time and Mandelbrot main focus was to explain why this is the case. Changing the Prevailing Approach One of Mandelbrot’s suggestions was to modify the binary (Coin Toss) suspension model to that the equations matched the real world occurrences. When looking at the financial markets, this modification meant applying Fractals because of the ways they can plot and describe the rough and seemingly unlevel nature of price activity. Uneven changes in price activity (or any observable environment) will make it difficult to formulate equations, and for Mandelbrot, this is the reason simple geometry proved insufficient when describing these environments. This is the reason Mandelbrot’s work with Fractal geometry became a primary focus. With this form of mathematics, he felt he could write equations that mirrored market behavior but he still found himself confronting problems with the ability to forecast future price behavior (especially in cases where major swings in price were seen). While many of Mandelbrot’s critics agreed with the idea that traditional statistics were insufficient when looking to forecast wild variations in price, some contended that when looking at longer time frames the market actually does smooth out in ways less rough than Mandelbrot was suggesting. This debate led many to favor Mandelbrot’s models over short time frames, while preferring to use more traditional models as durational periods are extended. Theories Gauging Market Performance In his 1982 book The Fractal Geometry of Nature, Mandelbrot looked more broadly, attempting to find evidence continual reappearance of fractals within the universe, and this is the work that ultimately granted him the notoriety he would later receive. The appearance of Fractals in many of the patterns we encounter in daily life (in clouds, plants, geographical formations), can be described by Mandelbrot’s mathematics. This gained him attention from practitioners of Chaos Theory and computer graphics visionaries and both of these fields would later draw largely from Mandelbrot’s Fractals equations. Mandelbrot’s equations for price forecasting evolved later in his life. The changing approach to price analysis allowed for new ways to measuring market performance, and in modeling the drastic price swings with a greater level of precision. Mandelbrot's formulas are now viewed as a means for measuring and assessing the broader climate seen in the market over a given period. For Mandelbrot’s theories, consequences must be tested a large number of times and show high levels of accuracy in order to be applicable to asset trading. Mandelbrot's central contention is that Coin Tossing approaches are overly simplistic and almost suggest that the trading outcome of one day is equal to those seen on every other day. Anyone with any real experience in the markets knows that this just isn’t the case. Trading with Mandelbrot’s theories typically involves looking at the number of price changes and then isolating the number of important trading days to small intervals. For Mandelbrot, it is this significant minority that is the important period, and the other trading days can be avoided altogether - as the ability to forecast movements is less likely to result in substantial gains. A Summary of Mandelbrot’s Fractals Benoit Mandelbrot’s Fractal theory has been studied for decades and is based on the idea that financial markets (and science as a whole) is based on our sensations. Most of these sensations are commonly understood: When we see something, we recognize this as the sensation of optics. When we hear something, we recognize this as the sensation of acoustics. When temperatures rise, we develop theories to explain the sensation of heat. For Mandelbrot, one of the most fundamental sensations can be described as “roughness.” Imagine primitive man agitated by roughness in the same way that humans become agitated by heat. Roughness was difficult for primitive man to overcome, and this, for Mandelbrot required the use of Fractal geometry to remedy. Mandelbrot argues that the ability to measure the non-basic sensations (such as Roughness) came relatively recently. These advances came with ability to make accurate physical measurements, as we essentially turn sensations into abstract numbers and equations. The patterns that mark Fractals repeat in a similar fashion, and with this repetition Mandelbrot suggests that we can gain an accurate description of “rough” and irregular constructions - like a cloud formation, coastline, plant structure - or the financial markets. For Mandelbrot, it is this description that is the first step to efficient price forecasting.

When new traders are exposed to the technical chart aspects of the trading markets, one of the earliest terms that is typically confronted is “Fibonacci.” While some of us remember this name from mathematics lessons in elementary school, it can still be confusing to understand why this term is so commonly applied to the analysis of price activity. Even further, there are many chart technicians that would argue Fibonacci has no connection to the market and should not be used when forecasting asset values. In a later article we will look at why some of the skeptics make these arguments. But first, we will outline some of the ways practitioners apply Fibonacci tools, as it is undeniable that these calculations are some of the most commonly used measurements when traders are looking for potential turning points within trends. Relationships Between the Large and the Small Fibonacci analysis is based on a unique mathematical ratio that is used both inside and outside the financial markets to describe many of the proportional relationships that are found in elemental aspects of nature. These relationships range from the smallest bodies found in the universe to the largest bodies found in the universe and practitioners of Fibonacci analysis argue that the ubiquity of these relational occurrences is a testament to its validity when looking to forecast price activity. Assuming this is true, what better analysis could there be than to judge financial markets by the same rules that apply to much larger aspects of the universe? If nature uses proportional relationships to maintain a wider balance, then the financial markets would inevitably be forced to follow these sames rules. Here, we will look at some of the ways Fibonacci measurements are used and briefly explain how the denominations are calculated. The Math Behind the Fibonacci Sequence Many are familiar with the Fibonacci sequence, which a succession of numbers discovered in the 12th century, with each term equal to the sum of the previous two terms (1, 1, 2, 3, 5, 8, 13, 21, 34, etc.). The “Golden Ratio” is then derived from this sequence, with the quotient of neighboring terms in the sequence showing what even skeptics consider to be a surprising proportional relationship. This proportion is 1.618 (with 0.618 the inverse proportion going in the opposite direction), and this relationship is sometimes called the Divine Portion, PHI or the Golden Mean. As we can see from the lofty terminology, it is clear that many practitioners of Fibonacci analysis see deep meanings in these numerical relationships. And many would argue that the consistent presence of this same numerical relationship within nature (for example, in the arc of a nautilus shell or in the sectional lengths of a dolphin’s body) is reason enough to believe this analysis has valid applications for the financial markets as well. Applications in Technical Chart Analysis Practitioners of Fibonacci analysis love to give examples of the Golden Ratio in nature. One of the favorites is to measure the length from your shoulder to your fingertips and divide that number by the distance between the elbow and the ends of your fingers, which should equal the Golden Ratio. In price analysis, this mathematical base is used to identify the differences between separate impulsive wave movements. This information is then used to mark potential turning points as price trends reach the end of a cycle. In these ways, traders take natural phenomenon and apply it to the financial markets when making trading forecasts. Fibonacci Studies as They Appear on Charts On a chart, Fibonacci ratios are typically visible as three percentages (38.2%, 50% and 61.8%). There are variations here, however, with many traders adding additional percentages (such as 23.6%, 78.6% or 161.8%). These variations can be constructed in many different ways. The four most common Fibonacci studies when used in the financial markets can be found in Retracements, Fans, Arcs, and Time Zones - all of which are derived from Fibonacci calculations. Fibonacci Retracements The most common study (and the one used by most new traders) is the Fibonacci retracement, which uses horizontal lines (calculated in conjunction with the previously mentioned percentages) to mark potential turning points within trends (regions of support and resistance). To determine the percentage levels, we take a significant price move (which is clearly defined on a chart). The starting point is marked by the first horizontal line and given the percentage description of 100% (as a price retracement back to this area would be a full retracement). At this point, we can see many variations but most Fib charts will then show additional horizontal lines at the 61.8%, 50%, 38.2% and 0% (which is the end of the previous impulsive move. In an uptrend, the structure looks like the first attached picture. In a downtrend, the image would be reversed. Price points like those in points C, D, and E would be expected to act as support, pushing prices higher in a turning point after a small corrective downtrend. In a downtrend, these points would expected to act as resistance. As you can see, the “turning point” areas are based on calculations made using the Fibonacci sequence and its accompanying implications. Fibonacci Arcs The next commonly used chart tool is the Fibonacci arc, where we again find a major price movement (with a clearly defined high and low). Three circular lines (concentric), using the 38.2%, 50% and 61.8% reference points. In a way similar to Fib Retracements, these circular lines also mark areas of expected support and resistance regions. In some cases, traders use these areas as ways of determining where ranges will develop. This is most easily understood with a visual example. The second attached picture shows how Fibonacci Arcs are used. Fibonacci Fans The next chart application is the Fibonacci Fan, which uses diagonal lines. Again, we find a significant price high and low, and an invisible diagonal line is drawn toward the price point on the right (this can be the high or the low). Diagonal lines are then plotted based on the 38.2%, 50% and 61.8% measured calculations. These diagonal lines mark regions of potential support and resistance. The third attached graphic is a visual example of this. Fibonacci Time Zones The last (and probably least common) Fibonacci study is the Time Zone, which is plotted using vertical lines. These Time Zones are created to divide charts into vertical segments, which are spaced in intervals that correspond to Fibonacci calculations. Similar to the other studies, these lines mark areas where significant price changes are expected to occur. The fourth chart graphic is a visual example of this. Conclusion: Basing Market Forecasts on Natural Phenomenon While there are many technical traders that are skeptical of the validity of Fibonacci studies in forecasting asset price movements, it is undeniable that these studies are a major feature of the markets and one of the most commonly used methods to trading. In some cases traders will even use these studies in conjunction with one another (looking for intersection points in the combined studies). It is rare for traders to use Fibonacci alone when trading but there are many practitioners using these measurements as the foundational basis when opening new positions. Not all market participants are convinced, however, and will instead argue that these price points are arbitrary levels that have nothing to do with future value directions. Some of these disagreements will be address in a later article.