jswanson

In this article I will create a trend filter (also known as market mode filter or regime filter) that is adaptable to volatility and utilizes some of the basic principles of hysteresis to reduce false signals (whipsaws). As you may know I often will use the 200-period simple moving average (200-SMA) to determine when a market is within a bull or bear mode on a daily chart. When price closes above our 200-SMA we are in a bull market. Likewise, when price is below our 200-SMA we are in a bear market. Naturally, such rules will create some false signals. By the end of this article you will have a market mode filter that can be used in your system development that produces better results than a standard 200-SMA filter. To build our better market trend filter we will use the following concepts: Hysteresis Price proxy HYSTERESIS BASICS When building trading systems many of the decisions have a binary outcome. For example, the market is bearish or bullish. You take the trade or you don’t. Introducing a “gray area” is not always considered. In this article I’m going to introduce a concept called Hysteresis and how it can be applied to our trading. The common analogy to help understand the concept of Hysteresis is to imagine how a thermostat works. Let’s say we are living in a cool weather climate and we are using a thermostat to keep the temperature of a room at 70 degrees F (critical threshold). When the temperature falls below our critical threshold the heaters turn on and begin blowing warm air into the room. Taking this literally as soon as the temperature moves to 69.9 our heater kicks on and begins blowing warm air into the room driving the temperature up. Once the temperature reaches 70.0 our heaters turn off. In a short time the room begins to cool and our heaters must turn on again. What we have is a system that is constantly turning off and on to keep the temperature at 70 degrees. This is inefficient as it produces a lot of wear on the mechanical components and wastes fuel. As you might have guessed, hysteresis is a way to correct this issue. More in just a moment. The purpose of this article is to improve our market mode filter. Below is the result of buying the S&P cash index when price closes above the 200-SMA and selling when price closes below the 200-SMA. This is similar to our thermostat example. Instead of turning on the furnace to heat a room we are going to open a new position when a critical threshold (200-SMA) is crossed. In order to keep things simple, there is no shorting. For all the examples in this article, $50 is deducted from each trade to account for both slippage and commissions. SMA_Line = Average( Close, 200 ); If ( Close > SMA_Line ) then Buy next bar at market; If ( Close < SMA_Line ) then Sell next bar at market; Going back to our thermostat example, how do we fix the problem of the furnace turning on and tuning off so many times? How do we reduce the number of signals? Let’s create a zone around our ideal temperature of 70 degrees. This zone will turn on the heaters when the temperature reaches 69 degrees and turn off when the temperature reaches 71 degrees. Our ideal temperature is in the middle of a band with the upper band at 71 and the lower band at 69. The lower band is when we turn on the furnace and the upper band is when we turn off the furnace. The zone in the middle is our hysteresis. In our thermostat example we are reducing “whipsaws” or false signals, by providing hysteresis around our ideal temperature of 70 degrees. Let’s use the concept of hysteresis to attempt to remove some of these false signals. But like our ideal temperature we want an upper band and a lower band to designate our “lines in the sand” where we take action. There are many ways to create these bands. For simplicity let’s create the bands from the price extremes for each bar. That is, for our upper band we will use the 200-SMA of the daily highs and for the lower band we will use the 200-SMA of the daily lows. This band floats around our ideal point which is the 200-SMA. Both the upper and lower bands vary based upon the recent past. In short, our system has memory and adjusts to expanding or contracting volatility. The EasyLanguage code for our new system look something like this: SMA_Line = Average( Close, 200 ); UpperBand = Average( High, 200 ); LowerBand = Average( Low, 200 ); If ( Close crosses over UpperBand ) then Buy next bar at market; If ( Close crosses under LowerBand ) then Sell next bar at market; Here are the results with using our new bands as trigger points. Looking at the chart above we can see an improvement in all important aspects of the system’s key performance. Most notably, the Band Cross column shows a reduced number of trades and increased the accuracy of the system. This suggests we eliminated unprofitable trades. Just what we want to see. Below is an example of a trade entry example. Notice the trade is opened when our daily bar closes above the upper band. The thick blue line is our 200-SMA. PRICE PROXY A price proxy is nothing more than using the result of a price-based indicator instead of price directly. This is often done to smooth price. There are many ways to smooth price. I won’t get into them here. Such a topic is great for another article. For now, we can smooth our daily price by using fast period exponential moving average (EMA). Let’s pick a 5-day EMA (5-EMA). Each day we compute the 5-EMA and it’s this value that must be above or below our trigger thresholds. By using the EMA as a proxy for our price we are attempting to remove some of the noise in our system. Let’s see how this effects our performance. SMA_Line = Average( Close, 200 ); UpperBand = Average( High, 200 ); LowerBand = Average( Low, 200 ); PriceProxy = XAverage( Close, 5 ); If ( PriceProxy crosses over UpperBand ) then Buy next bar at market; If ( PriceProxy crosses under LowerBand ) then Sell next bar at market; Looking at the graph above we once again see a solid improvement in our system’s performance. We continue to reduce the number of losing trades. Our profit per trade has jumped from $7.15 to $23.17. That’s over a 300% increase. Below is an example of a trade entry example. Notice the trade is opened when our price proxy (yellow line) crosses over the upper band. The above code is a simple trading system designed to show you the benefit of our “better” trend filter. If we want to use this in a trading system it would be ideal to create a function from this code that would pass back if we are in a bear or bull trend. However, the programming aspect of such a task is really beyond the scope of this article. However, below is a quick example of setting two boolean variables (in EasyLanguage) that could be used as trend flags: BullMarket = PriceProxy > UpperBand; BearMarket = PriceProxy <= LowerBand; In this article we have created a dynamic trend filter that smooths price by using a simple EMA as price proxy, it adapts to market volatility and utilizes hysteresis principles. With just a few lines of code we dramatically reduced the number of false signals thus, increasing the profitability of the trading system. This type of filter can be effective in building the trading system for ETFs, futures and forex on daily bars.

Looks great! Stops can be tricky. I have often found trailing or ATR stops simply do not work. A hard stop based on a fixed dollar amount may work. Timed stops are also worth trying. Here are some articles that you might find interesting. EasyLanguage code is available as well. What's Wrong with ATR Stops? This article talks about how ATR stops may not works well because ATR values can vary greatly often causing huge losses. The author then proposes using the square root of the ATR value to generate a compressed stop value that may perform better. A Flexible Trailing Stop Function This is a rather complex function/indicator you can add to test various stops on your system.

I agree with this 100%. There are times when a stop will really hurt you. Yet, I never trade with out them.

This is all educational material I post here on Traders Laboratory. It's the very research I use to trade the markets. You don't have to believe it or accept it. Read it and if you don't have anything constructive to say or don't find it useful - then so be it. The system posted in this thread is not a complete trading system. If you read the article you would have understood this. It's a launching pad or a study. A person interested in creating his/her own system can use this or the can ignore it. But as it stands, it's not a complete system. I do trade a system that is a modified version of what I posted. I also trade other systems. You're right, I don't have to sell anything. However, I enjoy running a business. I've been running some type of business since I was in high school. My goal in life is to have multiple streams of income. It's called diversification and living my life the way I want to. Have a great weekend.

Sorry, but not familiar with Metastock otherwise I would be happy to convert it. Maybe there someone else on this forum that can do this?

Here is the 2-period RSI system on the S&P Cash index going back to 1992. Trading a fixed lot of 100 shares.

The two-period RSI has worked wonders over the past 10 years on the ES and the numbers show it. But thanks for your opinion.

I trade futures, so there is minimal over night risk since the market is actively trading and my stop can get hit without fear of a large gap the next day. Furthermore, my studies have also demonstrated there is a long bias on the overnight session. Many people fear holding over night. Such thinking is common wisdom, but holding overnight can be very beneficial. There is a weekend risk since the market is not open. I picked $1,000 from a backtest study. I wanted a stop simply because most people don't trade without a stop. I trade a very similar RSI system with a $500 stop. If you are not going to trade with a stop, options may be a good idea.

We all know there are no magic indicators but there is an indicator that certainly acted like magic over the past 10 years or so. What indicator is it? Our reliable RSI. In this article we are going to look at two trading systems that were first talked about in the book, ”Short Term Trading Strategies That Work” by Larry Connors and Ceasar Alvarez. It has been well established in various articles on the web that a 2-peirod RSI on the daily chart of the stock index markets has been a fantastic tool for finding entry points. Sharp price drops in the S&P E-Mini futures during bullish markets have historically (since the year 2000) been followed by reversals. These reversals can often be detected by using the standard RSI indicator with a period value of two. Place this indicator on a daily chart and look for points when the indicator falls below five, for example. These extreme low points are buying opportunities. RSI(2) SYSTEM We can turn this into a simple strategy to test the effectiveness of the RSI(2) indicator on the E-mini S&P. In short, we wish to go long on the S&P when it experiences a pullback in a bull market. We can use a 200-day simple moving average to determine when we are in a bull trend and using a 2-period RSI to locate high probability entry points. We can then exit when price closes above a 5-day simple moving average. The rules are clear and simple: Price must be above its 200-day moving average. Buy on close when cumulative RSI(2) is below 5. Exit when price closes above the 5-day moving average. Use a $1000 catastrophic stop loss. The system backtest was performed from September 1997 through March 2012. A total of $50 for commissions and slippage was deducted per round trip. Below is a chart of what this system would look like along with the system results. RSI(2) SYSTEM RESULTS Net Profit: $17,163 Percent Winners: 67% No. Trades: 64 Ave Trade: $268.16 Max Drawdown: -$5,075 Profit Factor: 1.90 These results are great considering we have such a simple system. This demonstrates the power the RSI(2) indicator has had now for well over a decade. Just with this concept alone you can develop several trading systems. For now, let’s see if we can we improve upon these results. ACCUMULATED RSI(2) STRATEGY Larry Conners adds a slight twist to the RSI(2) trading system by creating an accumulated RSI value. Instead of a single calculation we will be computing a running daily total of the 2-period RSI. In this case, we are going to use the total of the 2-period RSI for the past three days. When you keep an accumulated value of the RSI(2) you smooth out the values. Below is a chart comparing the standard 2-period RSI indicator with an accumulated 2-period RSI indicator. You can see how much smoother our new indicator is. This is done to reduce the number of trades in hopes of capturing the quality trades. In short, it’s an attempt to improve the efficiency of our original trading system. The rules are: Price must be above its 200-day moving average. Buy on close when cumulative RSI(2) of the past three days is below 45. Exit when RSI(2) of the close of current day is above 65. Use a $1000 catastrophic stop loss. ACCUMULATED RSI(2) SYSTEM RESULTS Net Profit: $17,412 Percent Winners: 67% No. Trades: 52 Ave Trade: $334.86 Max Drawdown: -$4,850 Profit Factor: 2.02 Conclusions So which one is better? The accumulated strategy worked as intended. It increased the efficiency of the standard RSI(2) trading system by reducing the number of trades, yet produced about the same amount of net profit. As a bonus, the drawdown was even slightly smaller. While both systems do a fantastic job, the accumulation strategy may do a slightly better job. The Accumulated RSI(2) strategy will work well on the mini Dow as well as the two ETFs, DIA and SPY. Download The EasyLanguage code is available below as a free download. There is also a TradeStation workspace. Please note, the trading concept and the code as provided is not a complete trading system. It is simply a demonstration of a robust entry method that can be used as a core of a trading system. So, for those of you who are interested in building your own trading systems this concept may be a great starting point. DOWNLOAD HERE

It's true! I'm a blood-sucking vendor. I'm also a cold hearted speculator. So be warned!

Experience, I guess. When you have an extreme value on RSI(2) it's really easy for it to pop in the other direction. Thus, I was simply looking for a price action move that had a little more strength behind it. By adjusting the lookback to 5 price has to work a little harder in my direction before trigging an exit. Of course, there are probably several other exists that may work better. Exits are always a prime candidate to test and test again.

The system only holds trades for a few days, max. With such a short hold time I would think deep in the money options would be a great way to trade this. Thus, you would have your downside risk controlled and have plenty of leverage for the ride up. However, this is just my guess. I don't trade options. I also agree combining the different Connors methods would be interesting.

Would you like to see a timing method that is 75% correct and consistently pulls money from the S&P 500 market since 1997? The following trading strategy is called the VIX Stretch Strategy and was found in a book called “Short Term Trading Strategies That Work” by Larry Connors and Ceasar Alvarez. The concept is executed on a daily chart of the S&P E-mini futures market and the rules are very simple. Price must be above its 200-day moving average VIX must be stretched 5% or more above its 10-day moving average for 3 or more days Exit when 2-period RSI crosses over 65 Simple yes, but also powerful. A 200-day simple moving average (SMA) acts as a simple market environment filter by dividing the market into two major mode: bullish and bearish. Since the strategy only goes long, trades are initiated if the closing price is above the 200-day SMA filter. The next rule utilizes the VIX which is a measure of the implied volatility of the S&P 500 index options. This is sometimes called the fear index. Why? You will see this index climb dramatically when the market sharply falls and market participants become fearful. Thus, spikes in the VIX index are often associated with steep or dramatic market selling. Since we are looking for a market downturn to open a long trade when we are within a longer term bullish trend, we use the VIX index to gauge the market downturn. Buying the dips within an overall bull market is a classic trading setup. It’s also interesting to note we are not simply using price action to gauge a market downturn. By using VIX to gauge the level of the market downturn we are measuring the increasing volatility seen in the S&P 500 index option prices. Thus we are not measuring a pullback in price directly, but indirectly. The final rule is our exit rule which uses a 2-period RSI. Upon the close of the daily bar the RSI is calculated and if this value is above 65 we exit at the close. I coded these rules in EasyLanguage to see how well they would perform. It did rather well. The results below are from 1997 through March 2011. $20 for slippage and commissions was deducted per round trip. The code I used to generate the results is available at the bottom of this post. Is this a complete trading system? Please note the code used to generate these results has no stops! Most people would consider this a complete violation of the rules. I myself would not trade without stops. So a catastrophic hard stop may be added. In closing this timing strategy is a great seed idea for building a complete trading system. With a little creativity I’m sure you could turn this into a great system. DOWNLOAD Please note, the trading concept and the code as it is provided is not a complete trading system. It is simply a demonstration of a robust entry method that can be used as a core of a trading system. So, for those of you who are interested in building your own trading systems this concept may be a great starting point. The EasyLanguage code (text file) can be downloaded here.

Keep in mind there are times you can trade without stops. If you have a strategy based upon a short-term move in the index ETFs, don't buy the security. Buy options. Options have a catastrophic stop built in. You know your risk when you open your position. Again, not having a stop does not mean you don't control risk. It depends on what or how you are trading.

Hey I don't mind. Feel free to post away...

It actually trades on a five minute bar but takes it's signals from a daily chart. So, I don't have a daily chart.

Are you using the RSI(2) indicator on the same timeframe as you trade it? The system I've currently built uses the RSI on a daily chart and manages the trade on a 5-minute. It only trades on average once per month. I'm looking at in increasing the number of trades and would be interested in how you utilize it. Do you have any of the stats on your system? My general experience has been the currency markets tend to exhibit a bit more trending behavior instead of mean reverting. But, I've not looked at it much lately.

The system does not trade often. About once a month. The chart is 11 year period through 2011.

Yes, I believe I was inspired by Larry on the concept. The blue equity curve above, is from a system that trades with RSI(2) as a key indicator. But there is more behind it as well. You're probably right about 180 being an ideal period. However, I always avoid picking the best values. I would rather keep the 200. I'll have to look at the Euro with such a strategy.

The charts above are not strategies. They are market studies designed to highlight market characteristics. Sorry if I did not make this clear. The intent of this thread is to show the mean-reverting characteristic of the S&P E-mini futures market. This may be helpful to those who wish to trade or design a trading system. It's a starting point. As for designing a system around this mean reverting concept, I have done this as well. The chart below is a custom trading system written in EasyLanguage that trades the S&P E-mini futures market with a $500 stop per contract. Trades are entered at the close of the day session and monitored on a 5-minute bar.

Emotionally it's a lot easier to buy on strength than to buy into weakness. Buying into a falling market feels unnatural. Your instincts warn that price may continue to fall resulting in lost capital. On the other hand buying when the market makes new highs feels more natural. Price is moving in your direction and the sky is the limit! However, what feels natural or easy is often the opposite of what you should be doing. In this post I'm going to compare these two different trading strategies on the S&P E-mini futures market and see which one produces better results. I created two simple trading systems in EasyLanguage. Both systems will go long only. Both systems will utilize a 200-day simple moving average (SMA) for an environment filter. Long trades will only be opened if the closing price is above the 200-day SMA. All open positions are closed at the end of the 5th day. No commissions or slippage will be deducted for these tests. The tests were all executed on the S&P E-mini futures market between September 1997 and September 2011. BUY NEW HIGHS First let's create a system that goes long if price creates a new three day high. In other words, when price creates a short term breakout on the up side, we will open our long position. This will represent our buying into strength test. Below is the equity curve. The system is profitable, but we have an ugly looking equity curve with deep drawdown. BUY PULLBACKS Instead of going long on a new three day high, we are going to go long after three consecutive lower closes. This system will represent our buying into weakness test. The equity curve below depicts this system. What a difference! This equity graph looks great all the way until the recent market volatility that hit during the summer of 2011. Our last trade produced a large loss at the very end of our equity curve. Remember, both of these trading systems have no stops. The point is clear. Buying into weakness outperforms buying into strength for the S&P.

This is a continuation from my previous post where I explore the number of ticks the Euro currency future closes from its intraday low. In the original post I looked at a 5-year period starting on January 30, 2012. That post looked at each day. In this post I want to introduce a 200-sma filter to break the market into two modes: bullish and bearish. My question is: does the market mode impact the number of ticks available? LONG TRADES All Trades Regardless of Market Mode: 66 ticks Trades Taken Only When Price Above 200-SMA (Bull Market): 64 ticks Trades Taken Only When Price Below 200-SMA (Bear Market): 70 ticks According to these initial findings, going long when price is trading BELOW the 200 day simple moving average might provide more tick potential. Granted it's small. In reality, the median tick value does not change much. SHORT TRADES All Trades Regardless of Market Mode: 63 ticks Trades Taken Only When Price Above 200-SMA (Bull Market): 82 ticks Trades Taken Only When Price Below 200-SMA (Bear Market): 53 ticks According to these initial findings, gong short when price is ABOVE the 200-day simple moving average might provide more tick potential. Strangely, the optimal median ticks available are when 1) shorting a bull market and 2) going long during a bear market. Counterintuitive, but thats what the numbers say at this time. I still want to explore if there are particular times during day when a low/high are established.

Some markets exhibit trending behavior while others do not. I was wondering what would be a good way to determine if a given market exhibits trending behavior. One simple method to accomplish this is to build a simple trend following strategy and test how well it performs on the S&P vs other markets. This simple trending strategy consists of a single 50-period simple moving average (SMA) on a daily chart. To keep things simple, the system only takes long signals. It opens a new trade when price crosses above the moving average and closes that position when a daily bar closes below the SMA. I'm not attempting to create a trading system per se, but creating an indicator that measures a market's trending characteristics. Daily Bars - No Commissions - No Slippage Buy close of bar when Close > SMA(50) Sell close of bar when Close < SMA(50) Below is the equity graph created with this system on the S&P E-mini futures market from September 1997 to September 2011. As you can see the equity curve remains in negative territory and produces an overall losing strategy. We can now run the same strategy on the Euro currency futures. Below is the equity graph on the Euro from May 2001 to September 2011. Notice anything different? The equity curve is climbing higher and higher. By creating a simple trend following system that utilizes a 50-period moving average, I can demonstrate that the S&P E-mini (ES) futures market can be unfavorable to trend following systems. The trending characteristic of the S&P E-mini is not very strong. On the other hand the Euro currency futures shows much stronger trending characteristics. In short you can use this knowledge to help develop trading systems. A trend following system on the S&P daily bar may be a lot more difficult to develop than a trend following system on the Euro. An interesting thought is, has the S&P always acted this way? Was there ever a time when the S&P was a trending market? The answer comes below in the form of an equity graph with our trading system applied to the S&P cash index all the way back to 1960. The Market Changed After The Year 2000 A different story is seen from 1960 through 2000. During those times the market exhibited a trending characteristic that could be exploited with a trend following trading system. It could also be exploited by investors utilizing a buy and hold mentality. Decades of this trending characteristic has conditioned millions of people to faithfully follow buy and hold. It did well for a long time, and the rewards of that strategy came to be expected. Looking at the graph above, each green dot is a new equity high. That tall equity peek occurred around the year 2000 is when the dot com bubble burst. Since that event the S&P market has lost much of its once trending characteristics and this trading system has created no new equity high. You can bet that at some point in the future, this trending characteristic will return. But until that day, the S&P remains a difficult environment for trend following systems.

Wouldn't it be great to have an indicator to help tell you when we are in a major bull or bear market? Imagine if you had a clear signal to exit the market on January 18, 2008 before the major market crash. Then the same indicator told you when to get back into the markets on August 18, 2009. Such an indicator would have also gotten you out of the market during the dot-com crash on October 27, 2000. Well, this indicator I'm going to talk about does just that. Below you will also find the EasyLanguage code for this indicator. This major trend indicator was inspired by an article entitled "Combining RSI with RSI" by Peter Konner and it appears in the January 2011 issue of Technical Analysis of Stocks and Commodities. HOW IT WORKS We are going to start with a well known indicator: the Relative Strength Indicator (RSI). The premise we're looking at is how to identify major bull market and bear market phases. In his article, Peter does this by simply using an RSI indicator on a weekly chart. Peter noticed that during bull markets the RSI rarely goes below the value 40. Likewise during a bear market the RSI rarely rises above the value of 60. Thus you can determine the beginning and ending on bull and bear markets when the RSI crosses these critical levels. For example, during the bear financial crisis of 2008 the weekly RSI indicator did not rise above 60 until August of 2009. This signaled the start of a new bull trend. The next bear trend will be signaled when the weekly RSI falls below 40. With these simple rules you are able to determine bull and bear markets with a surprising amount of accuracy giving the S&P futures market. MODIFYING RSI I personally found the RSI signal a little choppy. See the indicator within the picture. I decided to make two modifications to help smooth the raw RSI signal. First, the input into the RSI indicator I changed from the closing price to the average of the high, low and close. I then take this RSI signal and pass it through a 3-period exponential moving average function. The results look like this: RSI_Mod = RSI( (c+h+l)/3, RSI_Period ); Signal = Xaverage( RSI_Mod, 3 ); Below this post the paintbar indicator and the strategy are available for download. They're both very simple and use the standard RSI indicator. The RSI uses a length of 16 and is applied on the weekly chart. I also smooth the RSI value by using an exponential moving average of the last three reads. ENTRY AND EXIT DATES Using this indicator we come up with the following turning points for major bull and bear markets for the US indices. The blowup of the dot-com bubble happened in 2000 and we got out in October 27, 2000.The indicator then tells us to go long on June 13, 2003. We then ride this all the way up to the financial crisis getting out of the market on January 18, 2008. Then on August 18, 2009 we go long. HOW CAN THIS INDICATOR HELP YOU? Looking at these dates we see that they are fairly accurate in capturing the major bull and bear cycles of the US stock indices. How can this be used in your trading? Well perhaps you can use this as a basis of a long-term swing strategy. Maybe this is an indicator to let you know when to liquidate your long positions in your 401(k) and other retirement accounts. Or perhaps if you are a discretionary trader you can use this to focus on trades in the primary direction of the market. Anyway I thought it was an interesting and novel way at looking at the RSI indicator. I hope you find it useful in your trading. DOWNLOAD You can download the EasyLanguage code here. RSI_WEEKLY_TREND.ELD RSI_Weekly_Trend_Strategy.txt Weekly_RSI.tsw

I've become interested in this potential edge of capturing points off the daily low (Green Rat) so I began to create some studies. I hope the RumpledOne does not mind me posting within his thread. I think my post is relevant and my help others when exploring this type of trade setup. First, I don't trade forex but I do trade Euro futures. So, the following numbers are based on this futures contract. I want to answer the question, How Many Points Does Price Close Above The Low? The Low-To-Close (LTC) observation is the price difference between the closing price and the low of a single daily candle. The first thing I want to explore is how many ticks are available between the low and the close? To do this I created an EasyLanguage strategy that computes this value for each candle and places them within an Excel spreadsheet. Within Excel I can compute the median ticks for each day and generate a histogram showing the distribution of ticks. The histogram will be broken into “bins” that represent a 15 tick range. Bin number one will contain the number of days that had a Low-To-Close count of 0 through 14 ticks. Bucket number two will contain all days that had a Low-To-Close count between 15 through 29 ticks. The bins are arranged from left to right on the x-axis of the graphs. The bins look something like this: Bin #1 00 – 14 ticks Bin #2 14 – 29 ticks Bin #3 30 – 44 ticks Bin #4 45 – 59 ticks . . . The days in our study will be from 08/08/2008 to 01/27/2011. ALL DAYS This study produces 1,061 days with a median LTC value of 66 ticks. This value translates into $825. That's a lot of ticks that can be captured! Below is the distribution curve which shows a nice smooth graph which peeks at bin number 3 which is 30-44 ticks. The curve smoothly tapers off into a nice tail as the bin numbers climb. In the end it sure looks like there might be potential here. The trading concept would be to open a long position near the intraday low and closing that trade at the median LTC value or at the end-of-day. In my next study I want to see if there are any particular times during the day where a low is most often put-in.