Mark Brown

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About Oddball Systems

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

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

This month’s 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:  

“It'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 “always in” the market (later we’ll 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 

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

Portfolio Simulation Settings 

1. Starting equity is $250,000.
2. Risk a maximum of 1% of total account equity per trade (stop-based Risk %) to calculate the number of contracts.
3. 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’s 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’s point, and the portfolio’s 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’s 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 “character” 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. 

Strategy Summary

LEGEND: Net Profit – Profit at end of test period, less commission · Exposure – The area of the equity curve exposed to long or short positions, as opposed to cash · Profit Factor – Gross Profit divided by Gross Loss · Payoff Ratio – Average Profit of Winning Trades divided by Average Loss of Losing Trades · Recovery Factor – Net Profit divided by Max Drawdown · Max DD% - Largest percentage decline in Equity · Longest Flat Days – Longest period, in days, the system is between two Equity highs · No. Trades – Number of trades generated by the system · Win/Loss% - The percentage of trades that were profitable · Avg. Profit – The average profit for all trades · Avg. Hold Time – The average holding period for all trades · Avg. Profit (Winners) – The average profit for winning trades · Avg. Hold Time (Winners) – The average holding time for winning trades · Avg. Loss (Losers) – The average loss for losing trades · Avg. Hold Time (Losers) – The average holding time for losing trades · Max Consec.. Win/Loss – The maximum number of consecutive winning and losing trades 

Periodic Returns

LEGEND: Avg. Return – The average percentage for the period · Sharpe Ratio – Average return divided by standard deviation of returns (annualized) · Best Return – Best return for the period · Worst Return – Worst return for the period · % Profitable Periods – The percentage of periods that were profitable · Max Consec.. Profitable – The largest number of consecutive profitable periods · Max Consec. Unprofitable – The largest number of consecutive unprofitable periods. 

Sample Trade

Notice how the bands expand with the increased volatility.

Equity Curve 1%

The equity curve with the 1% money management rule applied.

Equity Curve 2%

The equity curve with the 2% money management rule applied.

Drawdown

The underwater equity curve of the system when applying the 1% equity risk money management rule.

This systems 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)

MetaStock code:

To create the system test, open the tester under the Tools menu. Select new test and enter the following formulas in for the specific orders.

Enter Long:
ama:=If(Cum(1)=5,Ref(C,-1)+(Pwr((Abs((C-Ref(C,-4))
/Sum(Abs(ROC(C,1,$)),4)))*((2/3)-(2/31))+(2/31),2))*
(C-Ref(C,-1)),PREV+(Pwr((Abs((C-Ref(C,-4))
/Sum(Abs(ROC(C,1,$)),4)))*((2/3)-(2/31))+(2/31),2))*(C-PREV));
C>BBandTop(ama,38,S,3)

Close Long:
ama:=If(Cum(1)=5,Ref(C,-1)+(Pwr((Abs((C-Ref(C,-4))
/Sum(Abs(ROC(C,1,$)),4)))*((2/3)-(2/31))+(2/31),2))*
(C-Ref(C,-1)),PREV+(Pwr((Abs((C-Ref(C,-4))
/Sum(Abs(ROC(C,1,$)),4)))*((2/3)-(2/31))+(2/31),2))*(C-PREV));
C<BBandBot(ama,38,S,3)

Enter Short:
ama:=If(Cum(1)=5,Ref(C,-1)+(Pwr((Abs((C-Ref(C,-4))
/Sum(Abs(ROC(C,1,$)),4)))*((2/3)-(2/31))+(2/31),2))*
(C-Ref(C,-1)),PREV+(Pwr((Abs((C-Ref(C,-4))
/Sum(Abs(ROC(C,1,$)),4)))*((2/3)-(2/31))+(2/31),2))*(C-PREV));
C<BBandBot(ama,38,S,3)

Close Short:
ama:=If(Cum(1)=5,Ref(C,-1)+(Pwr((Abs((C-Ref(C,-4))
/Sum(Abs(ROC(C,1,$)),4)))*((2/3)-(2/31))+(2/31),2))*
(C-Ref(C,-1)),PREV+(Pwr((Abs((C-Ref(C,-4))
/Sum(Abs(ROC(C,1,$)),4)))*((2/3)-(2/31))+(2/31),2))*(C-PREV));
C>BBandTop(ama,38,S,3)

inputs:BBLength(38),BBStdDev(3),
BBHPrice(ADAPTIVE(H,10)),BBLPrice(ADAPTIVE(L,10));

vars:BBH(0),BBL(0);

BBH=BollingerBand(BBHPrice,BBLength,BBStdDev);
BBL=BollingerBand(BBLPrice,BBLength,-BBStdDev);

if c >bbh then buy;
if c<bbl then sell;

{
P.S. The adaptive function part is Perry Kaufmans:
}
inputs:price(numericseries),period(numericsimple);

vars: noise(0),signal(0),dif(0),efratio(0),
       smooth(1),fastend(.666),slowend(.0645),am(0);

{CALCULATE EFFICIENCY RATIO}
dif=@AbsValue(price - price[1]);
if(currentbar <= period) then am =price;
if(currentbar > period)then begin
        signal = @AbsValue(price - price[period]);
        noise = @summation(dif,period);
        efratio = signal/noise;
        smooth = @Power(efratio*(fastend - slowend) + slowend,2);

{ADAPTIVE MOVING AVERAGE}
       am = am[1] + smooth*(price - am[1]);
     Adaptive=am;
        end;

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).

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.

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

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

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