UrmaBlume

We find the signal to be profitable and that it comes in plenty of time to correlate with other indicators and then execute the trade. The markets turn for only one reason - a change in the balance/imbalance in the order flow. This indicator is designed to find short bursts of intense (usually automated) trade while certain other indicators indicate buying or selling intensity.

This work has nothing to do with Elliott Wave/GET. GET is based solely on price, this particular indicator does not use price in any form as any part of its calculation.

Yes to all three, it is reset everday at midnight PST.

Blowfish, What an interesting analogy. At least part of what we do is exactly what you describe. Some of our technologies look to find high intensity, auto-executed, market activity and other bits and pieces work to execute trades in a timely enough fashion to take advantage of the information. cheers

Whether or not there is distortion depends on how you read the data. While it is true that in trade station contsant volume bars don't always carry a constant number of contracts you can still read the upticks and downticks within the bar to determine the total order flow.

Both harmonic charts have been reposted, thank you for noticing. As to the infinity of space outside the box - the good news is that there are paths that will help to parse or limit this infinity of space. The bad news is that there are false paths and no matter which path you choose, you must walk it alone. Some say that as a rule the most difficult path will most often be best. cheers

Blowfish, Thanks for the kind words and the rational discussion. In these posts I am trying to walk the fine line between stimulating the conversation, providing clues to new concepts and methods and not p*ssing off my partners by giving away the farm. In reply to your first paragraph: 1) In the futures market the market depth means almost nothing. Size is almost never posted - It waits 2) Those who either want to disquise their trade or create liquidity do so by placing, according to a certain algorithm, orders on both sides of the market. In the old days they used to say "sell a little to buy a lot." Sometimes a quick burst of selling will trigger other selling and maybe even some stops which adds tremendously to buy liquidity. Without regard to whatever trading concept, market or indicator, there is a very small, in number, set of size traders that, not necessarily in concert, set local bottoms and tops. Without some knowledge of where they are active and what they are doing puts other, smaller, intra-session traders at a huge disadvantage and no MACD, RSI, CCI, BollingerBands, etc, buschwa will overcome that disadvantage. I am not saying that knowledge of this activity is the only way to trade successfully or that one can not profit without it. I am saying that most know nothing of when or where this activity occurs and that they would have a better chance at success if they did.

Here it is again -

Nite session spikes in trade intensity are very useful in determining commercial intent. During the nite session there is so little retail trade that when the commercials get active it is very obvious, as in the graph below, and often serves as a key reference point during the next day's trade. The spike show below happened about four hours ago, times are PST.

In other posts I have mentioned that we are a small private group of traders, poker players and programmers. The we is us. In answer to your question - Our indicator of trade intensity is designed to spot size automated execution by commercial trade. Tick charts only show transactions and not size and volume charts have all the same volume. We break time down into milliseconds and then measure x trade over a constant unit of time. When these spikes occur they really stand out as you can see in the graph below. This spike happened a little under 4 hours ago. These spikes during the nite session are especially indicative of commercial intent.

While we do it a bit differently the base concept is close.

Thank You, I am glad you like our HUD. We find it very useful. We favor indicators that measure buying and selling strengths as opposed to indicators calculated solely on the basis of price inputs. The RSI indiator is just a smoothed ratio of price change over time. The Balance of Trade indicator shows the balance, or more importantly, the imbalance between buying and selling in the current order flow. RSI only measures past price changes. It is not past changes in price that motivate future prices, it is only a change in the balance of trade that will change the direction of price. An imbalance of buy orders usually preceedes a price move up and vice versa. Thanks for your interest and your kind words. cheers

Thanks for the kind words. There are many different ways to calculate accumulation/distribution/moneyflow, this is ours. We are a small group of private traders and none of our technology is for sale. We do however engage in conversations about the concepts behind our work such as the posts here.

One would think that new, original content would be of value to the forum as it might attract subscribers which would increase your ad revenues. My posts sell nothing and promote no one and certainly, in concept, go beyond the normal discussion on this board concerning dated, off-the-shelf, price based indicators. As to the other question, market delta is about volume on the bid and asked which is entirely different our work and I am unaware of the other product. At any rate what I have discussed is certainly new in concept to this board and some have found it useful. On the other hand, you as moderator, have the duty to ban objectionable persons and posts from the community. You don't know me, know my enviornment, or my motives. There is not the slightest indication that I am out to sell anything to anybody. I think all of your rat and snake oil buschwa is petty, personal, unfounded and, uh, oh yes, unprofessional.

I am trying to stimulate thought and conversation beyond market conventional wisdom. While I am indeed proud of our work my purpose in these postings is to demonstrate the value of thinking outside the box. None of this technologiy is for sale or lease and we have no plans to take any of this to the market. Many years ago a couple of guys on the CBOT shared what was then beyond conventional thinking and technology and those teachings formed the basis of our work today. I thought I would try to return the favor and share some of our concepts and technologies with the 1% of the trading community that will dare to "go beyond." How will all of this will help you to trade the market? I don't know. For some there is nothing that can help them trade the market and for others all it takes is the slightest clue. What I have tried to do here is to share and to learn. My thoughts are that I have shared new and useful concepts and technologies that subscribers to this board would have no other way to access. You are a moderator - if you don't approve of the material I post or my motives for posting it, please just cancel my membership on this board.

As price consolidates the question is always, how will it break from the consolidation? The answer is that the Net New Trade or net buying and selling during the consolidation will usually tell the story. The graph below represent trade on 12/16/2008 in the hours before and immediately after a Fed announcement. The bottom graph is our calculation of Net New Trade and is reset at midnight PST. Primarily we use this to determine the net longs or shorts for the session but it also is a very good measure of intra-session net accumulation/distribution. Notice that in the hours before the announcement (which came just after 1100 PST) price was completely flat and traded whithin narrow and well defined boundaries. During that same 4 hour period before 1100 Net New Trade demonstraded steady accumulation. This is a further demonstration of how different measures of buying and selling power do a better job of predicting price than price base indicators such as CCI, MA, EMA, Stochastics, RSI, Bollinger Bands...... While the chart below shows almost a whole session the same indications are present in micro intra-session time frames for all of these indicators.

We have developed an algorithm that uses constant volume structures to produce what we call our Harmonic of Trade Flow. In the bottom secion of the graph the red solid line represents selling power and the blue line represents buying power. The Blue crosses indicate that the buyer is in charge and the red indicates the seller. The lines and crosses in the bottom graph are our calculation of recent buying and selling volumes smoothed by a zero phase Jurik Adaptive Moving Average. The graph below shows 4 very clear signals in just over an hour in the S&P. Please not that the crosses in the bottom graph most often change color before price changes direction. The bottom graph is calculated using different volume inputs only. This confirms that indicators with price as their only input have a natural lag and that it is buying and selling that motivates price. Our experience tells us that the best indicators of price usually don't have price as any part of their calculation.

Eiger, Thank you for the kind words. We are a small group of private traders, programmers and poker players. We are pround of the work we do. As to your questions "how these traders know where to trigger their high volume trades?" - Most of this high intensity is triggered in 1 of 2 ways - 1) a certain level of premium is present in either the options or the futures and a barrage of basket trades or other premium arbitrage trades are triggered and 2) Buy and sell prices generated by artificially intelligent and genetically optimized trading models are met by the market and the trade is executed in miliseconds. Often it is not required that one seek "pools of liquidity" as, to a certain extent, there are very fast automated routines that both disguise size trade and at the same time stimulate activity and trade flow. Further as to the question of liquidity, besides the automated trading/execution routines, we use certain applications such as the Heads-Up display shown below. This app is further described in separate post but beside measuring the power of surges and buying and selling, it helps to spot places where size is more easily executed.

Here is a screenshot of a Market HUD. While this software is in private use and not available for sale or lease, it does demonstrate some of the power available by combining processed data feeds. This application shows the market's very vital signs and completley demonstrates and reports the surges of buying and selling that propel intra-session price surges. A refreshing look at something besides the same old bar charts. There are many, smart, successful traders who know that technical innovation is often a pre-cursor to trading success. The purpose of this post is to illuminate by the presentation of new concepts and technologies and to stimulate a conversation that could lead to innovation of technique rather than a contiuous re-hash of the sameO, sameO. The top line shows longer term trader commitment so far that session as well as current trade flow as measured by contracts per minute. The red, yellow and green bars are buy/sell signals in 11 different time frames and a are constantly changing throughout the session. Blue bars on the left show the percentage of time of day normalized volume in 6 different time frames. The pie charts demonstrate the buying and selling during the most recent blocks of trade and are constantly pulsing with surges of buying and selling power. The price ladder in the middle shows current and recent prices. The red and green bars on the right show time of session normalized trader commitment over 6 time frames. The balance of trade is shown on the bottom left and price on the bottom right.

Hlm, Tick charts are NOT useful in the analysis of trade flow becasue they treat all transactions equally. In a tick chart, each transaction is treated as a single tick regardless of size and I assure you that a 1000 contract trade in the S&P has a bigger affect on price than a 1 lot. As to zero or near zero latency data feed and automated execution, they are the standard for many technically astute commercial traders. Most of the work we do requires automated execution. For the technically astute, the charts make it obvious that you trade the spikes. The special information presented is completely described in the text as the intensity of trade by special size traders. I know of not other way to demonstrate this information and have never seen it demonstrated before, have you? Most all retail trade uses indicators that have price as their only input - adaptive moving averages, exponential moving averages, RSI, Stochastic, Bollinger Bands, CCI etc. Regardless of time frame or combination of time frames these indicators have no chance of ever defining trade or leading it as they are based on price which responds to trade flow. Price is motivated by trade not price itself. The indicator I posted does not use price in any way and defines trade by the very secretive traders whose trade alone is enough to motivate/propel price and the non-retail traders I know find that very useful indeed. Another purpose is to try and elevate the discussion beyond the triteness and futility of discussions about the utility of trade based on the consideration of multi-time frames of price based indicators. Be assured that most successful commercial trade is not based on a few parameter changes on off the shelf indicators but is based on processes that have never been discussed or even mentioned on this forum. The intensity of trade indicator I demonstrated here is such an indicator and I know of no forum, book or discussion that has ever mentioned it before. I created this indicator and am proud of its basis and utility and don't mind sharing my work. You seem to have a big history of many very short, mostly content free posts that offer nothing new and contribute very little. Where is something new and useful that you have created that you are willing to share?

Price is motivated by volume, not time. The granularity of an optimal data vessel is determined by units of trade and not units of time. While I do believe that a 1 second bar chart would indeed reflect much of this same information, much would be lost by having any measure of time as the structure constant rather than units of trade. In the emini S&P, which until very recently has traded an average of something over 2m contracts during the session, we demonstrate this data in a 25 contract bar which generates something just short of 100,000 bars per session. A 1 second chart would only generate 24,300 during the standard 405 minute day session and their rate of presentation would be constant rather than accelerating and and slowing down consistant with the rate of trade at the moment. Time as a constant with regard to this kind of processing fails to report many very pertinent facts with regard to the balance and flow of trade and money in any market. A very compelling demonstration of this fact is accomplished by our Buy/Sell Volume Harmonic which I will present in a future post.

In most markets and certainly in the equity index futures markets there is a small set of very big traders whose entries into the market often have an immediate and very tradeable impact on price. These traders go to great lengths to disquise their trade - they have automated routines to send a series of small transactions to the market at intervals close to 1000th of a second. Because many of these traders operate from price based models they must get their execution within a very narrow price/time range which means they must execute as much of the volume they want as fast as they can while price is in that range. This results in a huge spike in what we call the intensity of trade. To calulate the indicator shown below you must have a very expensive and almost zero latency data feed and be able to measure time in 1000ths of a second. The calculation of the indicator is merely so much volume over so little time. The charts shown are in TradeStation. While TradeStation by itself doesn't have the ability to get nearly as granular with time the are dll's etc that can enable that most able platform for this work. This software is NOT for sale or lease. To trade this indicator at optimal levels requires automated execution. These plainly visable spikes in short term trade intensity occur between 12 and 30 times per session in the S&P. Notice the time axis on the bottom of this first chart - the whole chart is a look inside 1 minute of trade. This chart shows a similar spike in the intensity of trade The same spikes happen at tops - this trade was good for 5 points in only 3 minutes - a great days trade in only 3 minutes

The need for speed November 3rd 2008 Irene Aldridge, quantitative portfolio manager and managing partner at Able Alpha Trading in New York, looks at what defines a good high-frequency system One out of every two money management job vacancies listed in October 2008 on the finance recruiting site eFinancialCareers.com was a search mandate for "high-frequency trading" professionals. A rush for a specific job category in the middle of the worst crisis since the Great Depression is unusual, particularly when most companies are enacting hiring freezes. The reason for the hiring spree in the high-frequency field is simple: high-frequency trading is capable of generating money in all market conditions, whether a crisis or business as usual. High-frequency trading is a new discipline among buy-side money managers. The main innovation is more frequent turnover of capital in response to changing market conditions. High-frequency environments are characterised by lower average gain per trade and a higher number of trades. While traditional money managers hold their trading positions for weeks or months at a time, high-frequency money managers typically execute multiple trades each day with few, if any, positions carried overnight. The absence of overnight positions is important for two reasons: 1) the continuing globalisation of capital markets extends most of the trading activity to 24-hour cycles, and with the current volatility, overnight positions are particularly risky; and 2) overnight positions taken out on margin have to be paid for at the interest rate referred to as an 'overnight carry rate', which is usually slightly above Libor. But with volatility in Libor and hyperinflation around the corner, overnight positions become increasingly expensive, and so unprofitable for many money managers. While high-frequency trading enables the same strategy to be used across a wide range of financial securities, developing these trading strategies presents new challenges for money managers. The first fundamental challenge of high-frequency trading is the large volumes of intraday data. Most prudent money managers require at least two years of back-testing of the trading system to consider putting money behind it. Credible systems usually require four or more years of data to fully examine potential pitfalls, and dealing with this volume of numbers can be overbearing for most. Another issue is that signals must be precise enough to work in fast-moving markets, where gains could quickly turn to losses if the signals are misaligned. Speed of execution is critical to high-frequency trading. Traditional phone-in orders are not sustainable within the high-frequency framework. The only reliable way to achieve the required speed and precision is computer automation of order generation and execution. Programming high-frequency computer systems requires advanced skills in software development. Run-time mistakes can be costly and human supervision of trading in production remains essential to ensure the system is running within pre-specified risk boundaries. Discretion embedded in human supervision, however, should be limited to one decision only: whether or not the system is performing within pre-specified bounds and, if it is not, whether it is the right time to pull the plug. What defines a good high-frequency system? As with any money management activity, the first metric to consider is the Sharpe ratio. For trading systems with no overnight positions, the Sharpe ratio equals the mean of returns divided by the standard deviation of returns. An annualised Sharpe ratio of 4, after all transaction costs, is becoming a de-facto benchmark for a solid, stable system in the industry. A system with a lower Sharpe might be profitable for short periods of time, but is statistically subject to blow-ups. An annualised Sharpe ratio of 4 corresponds to a daily Sharpe ratio of 0.25. That is, daily standard deviation can be at most four times the average daily return. So, if the system or manager you are considering employing produces 0.1% per day on average, the maximum daily standard deviation of the returns should ideally fall under 0.4%. What this means in turn is that 68% of all daily returns should fall within one standard deviation from the mean, and 95% of all daily returns should fall within two standard deviations from the mean. In our example, 68% of all daily returns should fall within the -0.3% to 0.5% range, and 95% of all daily returns should fall between -0.7% and 0.9%. The second consideration is sensitivity to latency. Many fast-moving markets are sensitive to timely execution. So a thorough understanding of what costs are involved when execution is delayed is a critical factor in understanding viability of a high-frequency trading system. Other traditional metrics apply as well. A prospective investor in a high-frequency system should ask the system's manager questions about the maximum drawdown (a maximum peak-to-trough loss), betas (sensitivity to Standard & Poor's 500 and other macroeconomic indicators), value at risk (the loss potential at 95% probability level) and Sortino ratio (return over T-bills divided by average underperformance) among others. The manager's answers will not only indicate the stability of the system, but also reveal the manager's knowledge of, and attitude towards, risk management practices. Overall, high-frequency trading is a difficult but profitable endeavour that can generate stable profits in various market conditions. Solid footing in both theory and practice of finance and computer science are the normal pre-requisites for successful implementation of high-frequency environments. And while past performance is never a guarantee of future returns, solid investment management metrics delivered on auditable returns net of transaction costs are likely to give investors a good indication of the high-frequency manager's abilities

Below is the EL Code for an EL user function that will calculate a slightly better AMA but still not as good as the JMA from Jurik. The first bit of code is for the function itself and the second is for a indicator that will plot 2 smoothed lines of the mid point of the price bar. the User Function: Inputs: Price( NumericSeries ), Length( NumericSimple ); CSmoothX = XAverage( 2 * XAverage( Price, Length / 2 ) - XAverage( Price, Length ), SquareRoot( Length ) ); The 2 Line indicator, this is the code that calls the function and plots the 2 smoothed lines of the mid point of the bar: Inputs: FastCSmoothXL(3), SlowCSmoothXL(6); Vars: FastCSmoothX(0), SlowCSmoothX(0), PriceMP(0); PriceMP = (H + L) * .5; FastCSmoothX = CSmoothX(PriceMP, FastCSmoothXL); SlowCSmoothX = CSmoothX(PriceMP, SlowCSmoothXL); If FastCSmoothX >= SlowCSmoothX then Begin Plot1(FastCSmoothX, "Fast", Blue); Plot2(SlowCSmoothX, "Slow", Blue); End; If FastCSmoothX < SlowCSmoothX then Begin Plot1(FastCSmoothX, "Fast", Red); Plot2(SlowCSmoothX, "Slow", Red); End;

The phase setting will help with over shoot. Also the JMA package comes with a MACD function which has inputs for both speed and phase for 2 JMAs. I use this MACD line along with a JMA of that same line which is, of course, the difference between the 2 unseen lines of the MACD.