s in it, you must lower yourposition size when the volatility drastically rises. Very few peo-ple follow this guideline and it is a major reason why cata-strophic loses occur.
5. When multiple signals occur, a larger than normal position sizeshould be considered. For example, a Connors VIX Reversalcombined with a TRIN Thrust increases the likelihood that themarket will follow through for the next few days.
These guidelines are a good place to begin to build your moneymanagement strategies. If you desire a more in-depth academicview on the subject, read The Mathematics of Money Management byRalph Vince. It is filled with solid statistical advice.CHAPTER 3 0
HOW SUPERIOR |INDIVIDUALS BECOME
aeeeee eee newt eee eo eee eee eee oooh ee
T would like to conclude this book with a look at the role that practice,experience, and psychology play in leading one to become a superiortrader. Through the use of a study done on elite musicians, chess players,and athletes published in 1993, we will correlate these findings to ourown profession.
One of the subjects I have always been fascinated by is how and whyindividuals achieve greatness in their fields. Why does one individualdominate a sport, an industry, or an art, while the masses fail? Does ge-netics predetermine greatness or is it some other factor that allows indi-viduals to become leaders in their field?
I recently finished reading a book by Howard Gardner entitled Extraordi-nary Minds. In the bibliography, he refers to a study published in Psycho-logical Review in 1993. The study, “The Role of Deliberate Practice in theAcquisition of Expert Performance,” looked at whether “great” musi-cians, chess players, and athletes were genetically predisposed to achievegreatness (physiological) or whether greatness came as a result of exter-nal factors such as practice. (Of course, since I am a trader, I ask thequestion from this perspective—“are great traders born or can they bedeveloped?”)
 
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The study’s findings overwhelmingly showed that there was absolutelyno basis to the argument that genetics is the sole determinant in predict-ing success. In fact, genetics played at best a very minor role in differenti-ating between those who were “great” in their field versus those whowere merely “good.” The number one factor in determining whether or notone reached the highest levels in their field was the amount of time these indi-viduals spent on “deliberate practice.” Deliberate practice is defined as theamount of time one spends in attempting to improve their performance.Simply performing the act is not deliberate practice; deliberately attempt-ing to push oneself further is.
Drs. Ericksson, Krampe, and Tesch-Roemer found that those whoachieved greatness in their fields spent anywhere from 30 minutes to 2hours more per day on deliberate practice than those who were only“good” in their field. The authors go on to say that 30 to 120 minutes ofextra practice does not seem like much until one begins adding up thedifference over a period of time. For example, they cite numerous studiesthat show that it is virtually impossible to reach the: pinnacle in one’s fieldwithout at least 10 years of concentrated effort. Therefore, the 30 to 120 min-utes each day the “future greats” spend on improving themselves worksout to be many thousands of hours of extra practice over a 10-year period!
I suspect that had the authors looked at the most successful traders, theirfindings would be the same. Buying blackbox systems, trading crazymethodologies, or listening to gurus who claim they can tell you wherethe Dow will be three years from now will never bring you into the ranksof the trading elite. Simply put, 10 years of deliberate practice and hardwork is the only sure recipe for success! 
CHAPTER 3 1
FINAL THOUGHTS
I am writing these final pages after four friends read, proofed, and cri-tiqued the galleys. These individuals all trade. Two are private traderswhose main source of income is derived from the markets, one is a CTA,and the fourth is not only a professional trader, but he also possesses aPh.D. in mathematical statistics. Each is as different as night and day andI have a great deal of respect for their insights.
Their response to the trading methods was very good. I would expectthat, for each is a trading strategies junkie, just as I am. More importantly,these four very different gentlemen saw something that was bigger thanthe strategies. They each saw my point of first needing to understandmarket dynamics before creating a trading methodology. They saw thingssuch as the principle of volatility reverting to its mean and when it isextremely low you trade breakout strategies and when it is extremelyhigh, you trade strategies to exploit price implosion. They saw that mar-kets are made up of human beings and human beings are irrational. TheOptions on Stock Splits strategy exploits this, but bigger picture, thesetypes of irrational occurrences will be with us long after the stock splitstrategy fades away. Each, in their own way, was fascinated by the VictorNiederhoffer saga, not because they liked to see someone get hurt, butbecause, like me, they saw a piece of themselves in him. Each realized
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that without a proper understanding and respect for volatility, it couldjust as easily have happened to them.
The majority of readers will finish this book and tell themselves they nowhave 30 plus more strategies to trade the markets. This is fine, and it isthe main reason they bought the book. A small handful, though, will seedeeper and realize that markets have inherent features. They will go onin the future and trade methodologies that best exploit these features. Ifyou are part of this small group, congratulations. I strongly suspect youwill become a far better trader than most.APPENDIX
While the following formula for historical volatility may be of use to a mathema-tician, you should ideally have a software program calculate this for you.
HISTORICAL VOLATILITY BENCHMARK CALCULATION
Historical volatility (HVG) calculates the volatility of the underlying se-curity log-normally following the assumptions of most standard optionpricing models. The N-day price volatility as of.a specific date is the un-biased standard deviation of the “N” minus one most recent logarithmicdaily returns times the annualization factor, expressed as a percentage.(Logarithmic daily retum is the log of one day’s price divided by theprior day’s price. This is algebraically the same as the difference of thelogs of the individual prices.) For example:
10/882 10/782 10/692 105492price: 81.76 82.87 83.43 83.35natural log: 4.403788 «4.417273 «4.424007 «4.423048
 
difference: ~.01348 ~0.00673 000959unbiased std. dev.: 007227times sqrt (260): -116536times 100%: 11.65% (same as HVG)
 
 
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