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About Mark Brown

About Mark Brown

Since 1987 Brown has acted as and independent consultant to various institutional commodity traders and entities on a fee basis. He is a licensed vendor of the Market Profile Indicator for the Chicago Board of Trade. Mr. Brown is also the creator of the published Oddball Systems. His works have been disclosed in books, magazines and various forms of electronic media as well through speaking engagements.

Sophisticated systems elegantly programmed yet simplistic and not beyond the comprehension of ordinary human logic. Developed using proprietary custom analysis software and hardware created to deep data mine for the highest probability reoccurring market anomalies. The human intellect is capable of understanding the results of deep data mining market research. However it would be impossible for a human mind to ever discover or conceive these replicating anomalies from observation alone.

Expertise in computer modeling and exhaustive knowledge distinguishes the typical empirical derived system from a deep data mined model. Quantitative computer analysis combined with data cleansing allows the true nature of the subject market to be revealed. Enormous financial commitment is required with no guarantee that replicable, let alone tradable market anomalies can be found or exploited. Yet to date there have been no liquid markets which have not yielded profitable models in multitude.

Myths abound that mechanical systems require continual adjustment to adapt to varying market conditions. Properly designed trading models will enjoy many years if not decades of continual profitability. Again this is what separates empirically designed models from superior data mined modeling. Much of the success of discovery can be directly attributed to acquiring the knowledge to properly filter data. This technique alone can be credited with a noteworthy percentage of the profits derived from this method of modeling.

Experience and capital commitment play a large role in the longevity of modeling. These types of models are the direct results of countless man-hours and millions of dollars spent in research spanning well over a decade. Yet all that effort could have easily been wasted had the development process not been pursued with a feverish tenacity as it is to this day. Great discovery's sometimes come about when researchers stand aside and let the process reveal the truth of its final analysis. Data mining and complex analysis are difficult enough without tainting the whole process with human preconception and emotions. Thus human intervention has proven to be the least desirable tool in the modeling research inventory.

Thank You, Mark Brown

Mark Brown continued

With the advent of micro-computers in the late 1970's, Mr. Brown determined that they could be of benefit to him in his commodity trading and began a prolific career as a computer programmer and researcher developing scores of original trading models and methodologies at that time. The vast majority of this extensive research and development was conducted utilizing privately owned super computers and proprietary programming languages.

Since 1997, Mr. Brown has acted as an independent consultant to various institutional commodity traders and entities on a fee or partnership basis. In July 1997, Mr. Brown was registered under the Commodity Exchange Act as a Commodity Trading Advisor until October 1998. In May 1998, Mr. Brown was a principal for Computer Investment Research, Inc., in which he was an independent consultant until August 2001.

He was also a principal for Futures Programs, Inc. from August 2000 until April 2001 serving as an independent consultant. Presently, Mr. Brown was a NFA registered principal of Cabrio Capital Management, LLC, Brown & Parker and Odd Dog Systems, Inc. He is a licensed vendor of the Market Profile Indicator for the Chicago Board of Trade.

Historical Past

Mr. Brown has been involved with Real Estate development and finance, both commercial and residential for over twenty years. He has owned his own real estate office and construction companies. While his family's business focused on real estate and construction; during this twenty- year time span he also traded commodity markets as a hobby. With the advent of micro-computers in the late 1970's, Mr. Brown found computers to be useful in performing job cost estimating for his family's construction projects.

Mr. Brown has always been an electronics hobbyist, so he quickly taught himself to program in various computer languages. Early on, he had the idea that computers could be used to assist in trading the commodity markets. There were no products available at the time to do this task; so Mr. Brown set out to program his own. He began programming and developing his own trading models and methodologies at that time. After accomplishing this, Mr. Brown has been continually active in programming fully mechanical computerized trading systems.

Mr. Brown transitioned from using computers in construction estimating, into a full time career performing computer programming. Since 1987, Mr. Brown has acted as an independent consultant to various institutional commodity and equity traders on a fee basis. In the late 80's Mr. Brown took a position with Smith Barney, Dallas Texas as a automated trading system developer for Stan Finney. Mr. Brown's proprietary system development at Smith Barney were for the sole benefit of Mr. Finney and his other associated trading company's such as Regal Asset Management, Rainbow Trading Group etc. In the mid 90's Mr. Finney opened his own broker dealer (SpyGlass Trading) of ABN AMRO an international bank.

Mr. Brown held various positions while under the employment of Mr. Finney. Trader of proprietary accounts and manager of information services were but a few of the primary responsibilities. After the transition from Smith Barney to SpyGlass Trading, Mr. Brown also became a contract technical trading consultant for Regal Asset Mgt. of which Mr. Finney is a principle. Mr. Brown also received compensation for consulting services from Rainbow Trading Group another company owned by Mr. Finney. All the while under Mr. Finney's employment Mr. Brown received generous amounts of experimental trading capital as well as computer equipment and software. Of the services used by Mr. Brown on Mr. Finney's behalf was the Ned Davis program called The Technalyzer of which less than 10 are licensed world wide to selected institutional money managers. Mr. Browns primary responsibilities were to exhaustively develop, test and implement automated trading systems.

Recent Past

Mark Brown was registered under the Commodity Exchange Act as a principle of Computer Investment Research, Inc. ("CIR"), a Texas corporation. Since March 1997, Mr. Brown was registered under the Commodity Exchange Act as a principle of CIR. CIR was registered under the Commodity Exchange Act as a commodity trading advisor. Mr. Brown worked on a full time basis to develop and refine the company's proprietary computer trading models.

CIR does not direct any client accounts; instead, CIR leases its trading programs to selected persons who exercise their own discretion regarding which trades, if any, to implement and the size of such positions, among other considerations. As a result, the trading programs implemented by the Advisor for and on behalf of its clients are a unique application of the programs that it leases from CIR.

One such company that leases trading programs from CIR is Hargrave Financial Group Inc. (HFG), a Texas corporation that became registered under the Commodity Exchange Act as a commodity trading advisor and commodity pool operator in April 1998. The firm was also a member of the National Futures Association.

In 1999 CIR and Masterpiece Software joined forces and created TraderWare Corporation, an internet based trading and analytical software package.

In 1997 Mr. Brown was granted a license to be a software vendor of the Market Profile Indicator for the Chicago Board of Trade (CBOT).

The Oddball System

The following is an excerpt. For the complete article, see the December 2000 issue of Active Trader magazine.

Trading the momentum of market breadth

One of the best ways to keep track of the market true dynamics is to monitor its advancing and declining issues. Here a strategy that uses the momentum of advancing issues to time short-term trades.

By Mark Brown

The S&P tracking stock (SPY) and the S&P 500 futures contract probably are among the most difficult markets to trade. Statistics would most likely show the futures contract toward the top of a group of markets responsible for the quickest depletion of customer trading accounts.

Most short-term traders trade the S&P 500 markets using timeframes ranging from a single tick up to one hour. When trading in these shorter timeframes, it easy to become disoriented and lose track of the true market dynamics.

One tool many traders use to track nternalmarket strength is a breadth indicator such as the advance-decline line (the running total of advancing NYSE stocks minus the declining stocks). The changes in the number of advancing or declining issues can offer a glimpse of market dynamics not immediately revealed by price action. For example, even if the market is rising, a declining advance-decline line may indicate these gains are being fueled by a progressively smaller number of stocks, in which case a correction or reversal may be imminent.

While breadth indicators are commonly used to gauge longer-term directional strength, intraday analysis of advancing or declining issues can be used to develop shorter-term trading strategies. Here, wel look at how measuring the momentum of advancing NYSE stocks on an hourly basis can be used to time trades.

Breadth of fresh air

It is well-known that the combined directional bias of the NYSE advancing, declining and unchanged issues lists are helpful in determining the overall direction of the S&P 500 index and S&P futures. Traditionally, studies have been based on either a combination of the advancing and declining issues (such as the advance-decline line described previously), or the advancing, declining and unchanged issues.

However, research suggests that you can gain the same benefit (and simplify your analysis in the process) by using only the advancing issues statistics. And just as many short-term traders use price momentum in their trading decisions, the readthmomentum can be used to trigger trades. In fact, the momentum of the advancing issues provides enough information to develop a profitable trading strategy that allows you to bypass the actual market prices.

One simple trading model based on this approach is the ddball S&P system,which uses hourly readings from the NYSE advancing issues list. This timing model is based on the theory that in the short-term the S&P futures (and even the actual S&P index) and the market breadth may deviate from time to time, but they will nonetheless align themselves when large moves are made.

The original purpose behind this strategy was to use advancing/declining/unchanged numbers to identify high-volatility situations that showed the highest likelihood of having a directional bias. However, research and testing showed it was sufficient to use the advancing issues alone not just as a filter, but also as a stand-alone trading strategy. In addition, as mentioned earlier, using only the advancing issues numbers makes the approach less complicated. As a very basic trading approach, this strategy also functions as an excellent benchmark against which to compare other systems.

Measuring momentum

The strategy is based on calculating the rate of change (ROC) of the hourly advancing issues number. ROC, which is an oscillator-type indicator, is the difference (or alternately, the ratio) between the current price and the price n periods in the past. For example, the five-day ROC would be the difference between today price and the price five days ago. On an hourly chart, the five-period ROC would be the difference between the current price and the price five bars (hours) ago. (For a more thorough discussion of the ROC indicator, see ndicator Insight: Momentum and rate of change,Active Trader, October, p. 82). Because there are seven hours in the trading day, a seven-period ROC of the advancing issues number was used in this strategy.

One way to construct an oscillator-based system is to trigger trades when the indicator crosses above and below the eroline (the median line that represents neutral momentum, when the current price is the same as the price n periods ago). But a better alternative is to use two separate indicator levels, or zones one to initiate long trades and another to initiate all short trades.

A good initial setting is to set the buy level to 3 percent, and the sell level to 1 percent. That is, you buy as soon as the rate of change of the advancing issues is 3 percent higher than it was seven periods ago and sell as soon as it falls below 1 percent higher than it was seven periods ago. (See trategy snapshot,below, for the precise formula for the indicator.) This means the system will always be in the market, either with a long or short position.

The indicator settings used here were selected to keep the strategy as straightforward and simple as possible for testing. Traders may, of course, experiment with other indicator settings to see if they produce better results. Similarly, a different oscillator-type indicator could be substituted for the ROC. The underlying system logic and trading approach would remain the same.

In short, the oddball S&P system works as follows:

f the rate of change of the advancing issues is greater than the buy trigger level, buy the market.

f the rate of change of the advancing issues is less than the sell trigger level, sell the market.

Every hour, on the hour

Because this system recalculates every hour on the hour, up to and including the close of the stock market at 4 p.m. EST, you will not be able to use the last reading of the day if you are trading the S&P 500 tracking stock (SPY). However, if you are trading the S&P futures, you will still be able to enter a trade based on the last reading because the futures market continues trading until 4:15 p.m. EST.

For either market, this also means that you will have to wait for the first reading at 10 a.m. EST to trade in the morning. But this is actually advantageous, because as so many professional traders point out, you should avoid trading immediately after the open because of the directionless volatility that often occurs before the market finds its direction and pace for the day.

This kind of trading strategy is strengthened by the fact that it is easy to monitor and execute, and it is based on one primary input. The one-hour timeframe was selected because it is outside of the typical short-term trader time horizon, and also because consistency is a key factor when implementing a mechanical model. It is easy to check your trades each hour on the hour, or to program your laptop, mobile phone or handheld computer to do so for you.

Also, only using one data point per hour also enhances the reliability of the model. Why? Because when you view an intraday chart and observe a bad price print it will most likely be the high or the low of the given bar. By eliminating all data points but the close, you also reduce the possibility of errors.

Another Oddball System

This system was originally developed by Mark Brown
(www.markbrown.com) in 1997

Compiled by Volker Knapp and Dion Kurczek
of Wealth-Lab (www.wealth-lab.com)

Market: Futures

System Concept

The following is an excerpt. For the complete article, see the May 2004 issue of Active Trader magazine.

This month May '04 article is a reality check on a futures system that was published on a public forum in 1997 by Mark Brown, a well-known personality in the trading system industry. According to his statement he had traded it (or similar systems) for many years and has since moved on to other system trading styles. In his introductory comment for this system he made the following interesting statement:

t's as much a mind game as anything and if you want to make money let your mind go blank and trust the system, the system can be intuitive or computerized or any blend thereof. But defined and cast in stone it must be." Mark Brown Oct.1 1997

According to the method, we create a 38 bar, 3 standard deviation Upper Bollinger Band of the 10 bar Adaptive Moving Average of high prices, and a corresponding Lower Band of low prices. The Adaptive Moving Average is taken from Perry Kaufmann, whose Adaptive Moving Average (AMA) automatically increases the speed of the moving average as market volatility increases.

The entry and exit rules are rather straightforward. When the closing price crosses above the upper band we go long, and below the lower band we go short. Since the published methodology defines only the entry and exit rules, we have added our own position sizing rules, which are summarized below. As the system is trend-following in nature and is lways inthe market (later wel see that this is not the precisely the case due to the effect of our self-imposed position sizing rules), it is expected to work best in trending, non-correlated markets and is therefore ideal for our Active Trader magazine sample portfolio. Figure 1 shows an sample trade.

Entry and Exit Rules

Construct Bollinger Bands based on a 10 bar Adaptive Moving Average of highs and lows.
Go long and cover a short position on the next bar open when closing price crosses above the top band.
Go short and sell a long position on the next bar open when closing price prices crosses below the bottom band.

Portfolio Simulation Settings

Starting equity is $250,000.
Risk a maximum of 1% of total account equity per trade (stop-based Risk %) to calculate the number of contracts.
Deduct $10 slippage/commission per contract (entry and exit).

Test Data

The system was tested on the Active Trader Standard Futures Portfolio, which contains the following 20 futures: DAX30 (AX), Corn (C), Crude Oil (CL), German Bund (DT), Euro Dollar (ED), Euro Forex (FX), Gold (GC), Copper (HG), Japanese Yen (JY), Coffee (KC), Live Cattle (LC), Live Hogs (LH), NASDAQ100 (ND), Natural Gas (NG), Soybeans (S), Sugar (SB), Silver (SI), S&P 500 (SP) and T-Notes 10 year (TA). For this article we used Ratio Adjusted data from Pinnacle Data Corp.

Test Period: June 1997 until August 2003 (out of sample data)

Money Management

Often money management is also referred to as position sizing, portfolio allocation and so on. Proper money management defines two important and related rules: position sizing and the bet sizing. Bet sizing defines which percentage of the portfolio total equity the trader is willing to risk (to bet). The position size calculates how many contracts the trader should open on any given trade expecting the worst outcome (stop loss triggered). The number of contracts is calculated using a basis price, the stop loss level, the contract point, and the portfolio total equity. The basis price is the price at which the market closes prior to putting on a new position.

Using an example of a commodity with a point value of $250, assume that the entry signal goes long at a basis price of $100 and the stop loss on that date is shown to be at $90. We calculate our dollar risk by multiplying $250 by $10 ($100 - $90). Consequently, if we were stopped out on the purchase of one contract, we would lose $2,500. Now, if our portfolio total equity on the date before entering into the position was at $320,000, and we do not want to risk more than one percent of our total equity ($3,200), we would be allowed to buy one contract since the integer part of the quotient $3,200/$2,500 is 1. Had total equity been below $250,000, we would not be able to take this position since the dollar risk would exceed the 1% equity risk that we are willing to assume. This position sizing method keeps us out of risky trades that have potential to ruin our account, and in the same way, it keeps us from entering other markets entirely since the risk is too high during specific trading periods. In Figure 2 we show the result of the system when risking one percent of the total portfolio equity per trade.

System Results

With $250,000 of starting capital, the system achieved an overall profit of 129.99% in approximately six years and accomplished an average annual return of 13.78 percent, with the worst year being a loss of 13.20 percent in 2003. The same year had the largest drawdown of 26.01 percent. Out of 251 trades, only 31.08 percent were winners. Nevertheless, the average profit per trade was $1,294.76. Over our testing period, trading from either side, long or short, was profitable and complementary as you can quickly observe by the thin red and black lines (equity curves attributable to short and long trades, respectively) in Figure 2, the portfolio equity curve. Even thou this is essentially a stop and reverse (SAR) system, we can see a rather moderate exposure of 33.79% which would give us some room to increase risk.

Effect of Money Management

To demonstrate the effect of money management on overall system performance, we now double the risk per trade to two percent of total portfolio equity. Looking at the same system with the increased risk, Figure 3 illustrates an equity curve with much greater volatility accompanied by higher draw downs (45% compared to the earlier 26%) and even less profit (42% compared to the earlier 129%). Exposure climbs to over 37%, and the number of trades reduces to 237 due to the fact that at certain periods insufficient equity existed to assume the 2% programmed risk.

Conclusion

Given that the system was published free of charge and we have not changed any parameters, it shows a rather good result. We did not make any market selection as it was not stated for which market it was created. Many commercial systems are often optimized for certain markets. On the other hand, there is no guaranty that the market haracter will stay the next ten years as it was the last ten years. Diversification and sound money management is the key to success as many hedge fund managers are proving year after year. The more markets you can trade, the more likely you will catch the big trend that those systems require to be profitable. The pure fact that this trading system was offered gratis does not make it a better or worse than others. Each trader should fully evaluate and research any system before risking real money.

International Communications for Management Conference

Evaluating and Profiting from: TRADING TECHNOLOGY - Marriott East Side, New York, NY - August 18, 19, 1998

Panel Discussion
Exploring the future of electronic trading

Analyzing emerging technologies
Defining new technology capabilities
Evaluation the future needs of your organization
Assenting the compatibility of current technology with future technologies

Mark Brown

Director of System Development
Computer Investment Research, Inc.

CSI Technical Journal - December 1998, Volume XIV, Number 12

What Mark Brown is Saying About Perpetual Contract Data

Perpetual Contracts [data] are used for a variety of reasons, some explanation follows. When a future contract nears expiration it becomes more volatile. That volatility causes many systems to initiate trades that would have otherwise not been engaged. If the real market is to be traded, surely then it would exist somewhere in between the current contract and next one out.

Given that, I would suggest you think about this: Various researchers build models using back adjusted contracts and other methods. Most all models work best on that type of data. However when you understand why they work better you may want to re-examine the way a model is built. If you have a model that follows price action rather employs the most statically consistent cyclical method. Consider the following proposal that a good model instead trades a markets historical 70 to 90 percentile personality. The very price moves that other models concentrate on are the very moves I dismiss as an anomaly.

Mark Brown

Trading Chicago Style: Insights and Strategies of Today Top Traders

Chicago's hottest traders reveal their Midas-touch secrets. In Trading Chicago Style, futures trading stars explain how they reached the pinnacle of Chicago's rough-and-tumble, lightning-fast commodities markets. Packed with winning tips, strategies, and methods, this book delivers closely guarded advice and genuine secrets that were - until now - not available anywhere else. Each chapter features trading techniques of one of today's market wizards, along with computer techniques and off-floor methods. Traders from every major Chicago exchange - Chicago Mercantile Exchange, Chicago Board of Trade, Chicago Board of Exchange, and Chicago Stock Exchange - are included.

Mark Brown, Dallas based money manager and system trader. Mark has had access to resources few traders or analysts will ever have. He knows from practical experience what works, what does not, and why.

Neal Weintraub

A True Story : The Pursuit of The Holy Grail

The X-Files Project began with the agreement of two parties to culminate all their research and ideas, for the purpose of financial gain by trading the markets. Both entities agreed to pursue with all resources the elusive, dependable and consistently profitable, fully automated trading system. There were no cost spared during the project, a very large research fund was set aside to insure the projects completion. In spite of these preparations, funds ran low so additional funds were sought and secured from two sources. One of the sources is no longer associated with the project, having exhausted their available funds. The other party is now a client of the original projects founders.

The project ended two years beyond the estimated time of completion, and at a staggering cost five times the estimated initial proforma. All available and most non-available trading methodologies were extensively researched. The extent of pursuing some of the technology, at times bordered upon criminal espionage. Extensive computer testing as well as real money accounts were used to determine the fact from fiction. Through out the ordeal, many outside sources were employed to work on various pieces of the project, none however having the whole, nor the complete concept. This was done not just for the obvious security reasons but also because this ensured the results of their part of the project was not tainted by some preconceptions.

If one item were to be singled out as the most detrimental to the project, it would have to be that there were preconceived ideas of what a successful trading system should look like. The computer was assumed to be in error, time and time again no matter how successful the per trade profit looked. This assumption of error was perpetuated by the resistance to investigate what the results were showing. The computer modeling did not look and behave as was anticipated by the research team. Following in the footsteps of one of the early pioneers of computer testing and trading. It was realized that the project was closer to completion, than what had been previously thought.

The project completion was being held up because the team refused to allow the computer model to trade the methodology that it found most profitable. In spite of what the research team thought, one area was left not completely researched. That area was the research team themselves ability to allow a computer to do the actual trading. In other words the team needed to ensure that they were profit motivated and not motivated by the need to be traders. Thus the intervention of the pioneer mentioned earlier. He having been in the very same situation years ago when developing his computer model, was gracious enough to share the road map for the human part of the systems evolution.

The main element that was provided to the team was the experience that once you have a methodology that works, you have to let the system do its job. It must become the trader and you a servant of it. After this is accomplished trading actually becomes a rather mundane experience.

What has taken years of research and at one time consumed the space of a large warehouse, has now been reduced to approximately one page of code for use with Omega Research TradeStation. For the participants of the project the road to recovery is at hand. It will take some time to recoup the expenses of the developmental cost. There were many who fell by the wayside during the process and that is just a natural order occurrence. However the monumental task that has been accomplished is now realized to be fact not fiction. During the work, at some time the consensus was that an answer would not be found. However with feverish tenacity the developmental process was pursued. The consensus now is that the answers were always out there somewhere, waiting to be implemented by those willing to take the risk and work hard enough for it.

- The End For Now -
- Thanks to the participants knowingly or not. -

- People -
- Rick Parkhurst - Miles Casad - Bruce Collins - Stan Finney - Ed Courson - Ellery Scott - Rick Saidenberg - Peter Aan - Mike Conner - Jim Steadman - Tom Richter - Jean Coats - R.L. Mc Alister - Linda Satterfield - Robert Strittmatter - Brian Shiell - Scott Shiell -

- Products -
- Cray Research - Omega Research - The Math Works - Ned Davis Research -

- Company's -
- Smith Barney - First Texas Futures - First American Discount - Advance Futures and Options Group - Moss Capital Management -

- Universities -
- The University of Arizona - Department of Astro Physics -

- Dedication -
- A Dedication to those Involved in The X-Files Project -
- Rick Parkhurst...... We Thank You...... Mark Brown -
- Copywright1997 Mark Brown Trading Systems. -
- Project Is Now Completely Self Funded -

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