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August 24, 2005 � Issue #234 | |
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Feature Article Play a Game You Can Win, By Paul M. King
Trading Tip Don�t Get Caught by a Bad Reward-to-Risk Trade, By D.R. Barton, Jr.
Teleconference Our Friends From "Early To Rise" Accelerate Your Wealth Teleconference Listening In Self-Sabotage Special Report Reports by Van Tharp: Self Sabotage Re-examined, Part One and Two
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Play a Game You Can Win by Paul M King Imagine a simple coin-tossing game where you win whatever you stake if heads comes up, lose what you stake if tails comes up, and you are charged 1% of your stake each turn to play. Can you win money at this game? If you are familiar with the concept of expectancy, then you will probably answer "No" since over many turns the amount won will be equal to the amount lost (assuming the coin is a fair one) and after factoring in the 1% cost of playing you will lose money overall. In fact, there is a way to win this game, and that is to understand that the longer you play, the more you will lose, so the optimum strategy is to bet everything you have on just one toss of the coin; just like Ashley Revell did when he sold everything he owned, took the $135,300 to Las Vegas, and bet it all on �Red� on one spin of the roulette wheel. Mr. Revell was fortunate and he won, but I am not recommending that you bet everything you have on one trade! Obviously risking everything on one trade is not a useful strategy since we want a game we can play for long periods of time to generate a consistent income. So how can we change the game so that we can win? There are three aspects to the game which can be adjusted to increase our chances of winning consistently:
Tipping the chances of a winner is not possible in a fair coin toss game, but it is possible in trading. There are two ways to approach this: identify conditions that are more favorable to your winners and include them in your system definition, or identify circumstances where a loser is more likely and skip those trades. For example, if you notice that most of your winners are entered on days where the overall market has moved in the same direction as your trade, then only enter trades when the overall market is moving in the correct direction. This means that your trade is in the same direction of the overall market, rather than against it. Another example might be that trades that are entered just before major news announcements, like earnings calls, often get stopped out as losers due to increased volatility, so you should skip those trades. There may be many patterns of winners and losers that you can identify for your own systems and careful study of past trades is definitely worthwhile. Note that we do not want to increase our win percentage too significantly (i.e. to greater than 60%) since this would indicate that we have �curve-fitted� our system to historical results that are unlikely to continue into the future. It is also important to note that for some types of trading (i.e. long-term trend following strategies) it may not be possible to have a win percentage that is greater than 50% (and it may be much lower) and that is where the second aspect of improving your system comes into play: the average size of winners versus losers. Increasing the size of the payout so that the winners win more on average than the losers lose depends on the way you handle your stops. Having large winners in relation to losers can make up for a low win percentage, and mean that you will still make money playing the game. One method is to have a trailing stop that moves up as a trade becomes a winner. If you have fixed stops for losing trades that limit losses, but trailing stops for winning ones that allow winners to grow, then you are increasing your chances of your average winner being larger than your average loser. Generally it is better to be strict with losers by having tighter stops that keep losses to a minimum and generous with winners by having stops that allow profits to grow. In any case you want to make losers small and winners large, so never add to a losing trade � that would be doing the opposite of what you want to achieve. Lastly, reducing the costs of trading is probably the simplest change you can make and can mean the difference between winning and losing overall � especially for systems that have lower expectancy. There are many online brokers now that charge 1c per share for equity trades (and comparably low fees for other instrument types) and there is no reason why you should be paying more than this if you are trading electronically. Every trader should do whatever they can to maximize the expectancy of their trading system or method by considering each of the three aspects just described. If we do some, or all, of these things then the amount we win now becomes a factor of how much we stake, and how often we play because we have created a true �edge� where we know that the system we are trading should make money (if traded accurately). Calculating the expectancy of your trading system or method tells you whether you are playing a game you can win, and is a very important piece of information that every trader should know before they risk real money. If the game is rigged against you because your trading methods lose money regardless of how accurately you implement them, how can you ever be a successful trader?
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Trading Tip Don�t Get Caught by a Bad Reward-to-Risk Trade by D. R. Barton, Jr. I�ve been exposed to three incidents of malfeasance recently, and I�m struck by the two similarities: � None of the people thought they�d get caught. � The cheating was done for very modest payoffs (all things are relative, I guess). I�ll talk about the trading episode below, but let me briefly cover the other two. The first is perhaps the most curious. Baseball star Rafael Palmeiro plays just down I-95 from me in Baltimore. With well over 500 home runs and almost 3000 hits to his credit, Mr. Palmeiro was an absolute lock to enter Baseball�s Hall of Fame. He was questioned on steroid use in front of congress before the season started and made a now-famous and vehement denial of ever taking steroids. But in baseball�s tougher testing policy (some say still not tough enough), Mr. Palmeiro tested positive, went through a lengthy internal and private appeal process and then was shown to the world as a guy who, by all facts now available, cheated by using performance enhancing drugs this season. It seems to me that Mr. Palmeiro had very little to gain from using steroids. He was going to get his 3000th hit. He was going to finish out his career in the next year or two as the guy who stood out in Congressional hearings as the most self-assured steroids abstainer. How would taking (or continuing to take, as some sources claim) steroids help him? A few extra home runs this year? A few more hits? The reward-to- risk ratio for this decision certainly looks terrible from here. Unless new evidence surfaces, Mr. Palmiero�s place in the Hall of Fame is in serious doubt. The best possible answer I can imagine is that Mr. Palmeiro thought he wouldn�t get caught. The art and science of selecting screening agents for performance enhancing drugs is very advanced. It is quite possible that the low R-multiple decision was made because the perceived risk of being caught was small. The second incidence of wrongdoing happened in my hometown church (the church I grew up attending). An arsonist struck the church several months ago. That was tragic enough. But then one of the workers who had been hired to assist in the cleaning stole checks from the church office and started cashing them at local banks. The three or four that were cashed were all for less than $175 dollars. Who risks jail for that kind of scratch? Again, all things are relative, and this low R-multiple decision was most likely done out of desperation. Perhaps, the person thought that by keeping the amounts low, he wouldn�t get caught. Now, onto the world of trading. The front page of Tuesday�s, August 23, 2005, Wall Street Journal gave some insight into the trading scandal where a small group of traders made their trades by illegally listening to the internal order flow of four major brokerage firms. This was cheating of the highest order � coordinated, payoffs made, you name it. The scheme was simple: listen to internal discussion of pending large institutional order and then �front run� them. But for the life of me, I can�t see where the payoff was for making such clear-cut violations. It looks like less than a million dollars was made by three traders in 18 months. (Perhaps the SEC could only get positive proof on a relatively small amount of the actual illegal trading.) But even if the figure was doubled or made ten times bigger, this was the amount being made for the firm as proprietary traders (meaning that this isn�t the money the traders themselves were making). Who would risk hard jail time for relatively small amounts of money? The example on the front page of the WSJ listed a trading example that a day trader with $50,000 in their account could pull off. Again, I�m guessing that the amounts were kept small to try to fly under the regulatory radar screen. And so the traders doing it thought they wouldn�t get caught. The lesson for traders and investors is that if something stinks, it�s probably for good reason. Schemes are everywhere and we need to be on guard. But I keep coming back to making decisions based on reward-to-risk ratios. Even an amoral person should be able to do that! We never enter a trade thinking that it�s a loser � that we�ll �get caught�. But we can enter every trade and investment understanding the reward-to-risk ratio (the potential R-multiple) and only take the ones that are decidedly in our favor.
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Quote of the Week "Chains of habit are too light to be felt until they are too heavy to be broken." |
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