T2W Trading Community

• Your strategy must be repetitive and consistent. You will be unable to define system parameters with any accuracy if you are doing something different every time you trade. (If you are a prodigy who can make a fortune trading your gut instincts, I congratulate you and you certainly will not need any help from me. For the rest of us, we need to define one or more favourable strategies and repeat them consistently whenever we get the opportunity.)
• You need to know what your probability of winning is, whenever you place a trade. (Knowing the probability of winning, you automatically know the probability of losing.) This can be a difficult statistic to get a handle on in real life. Tossing a coin is easy; obviously the Probability of Winning = 50%. But with a market strategy, the probability will not be intuitively obvious, so you will have to figure out a way of measuring it. You can only measure it on the basis of historical information and there is no guarantee that your estimate will be correct in the future. You can have greater confidence that your estimate is correct if it is derived from a logical trading strategy based on your knowledge of the ways markets work.
• You need to know the size of your average winning trade and the size of your average losing trade. Depending on your strategy, this may be well defined, or you may need to figure out a way to estimate it from historical data (again with the caveat that history does not necessarily repeat itself).
• Based on these numbers, your Expectancy must be positive. Expectancy can be worked out from the following formula:
• Expectancy = (Probability of Winning x Average Win) - (Probability of Loss x Average Loss)
• In the die throwing example I used before: Probability of a Win = 2/3; Probability of a Loss = 1/3; the Average Win and Average Loss are both $100.
• Therefore Expectancy = 2/3 x 100 - 1/3 x 100 = 66.66 - 33.33 = 33.33.
• Remember, this means that over time you will earn an average of $33.33 every time you play the game.
• You know that statistics gleaned from small samples are of little value, and also that strategies with a good expectancy are almost certain to have bad runs of several losses in succession. Such runs are simply random fluctuations in a series of results which will revert to the statistical norms in the long run.
• Because bad runs are to be expected, you must anticipate them when determining the amount of capital needed to play the game.
• An important part of any strategy is the opportunity to profit provided. A good strategy which provides few opportunities may well be a lot less profitable than a mediocre strategy which provides a lot of opportunities.

Think about the casino owner, or your local bookmaker. They do not berate themselves if one of their clients has a big win. They do not change their entire business plan if they have a few unprofitable days. They do not tinker with the rules of their games after a few losses. They know the odds are in their favour, and in the long run their profits are assured.

If you can really internalize the simple concepts in this article, not just read and understand them, your attitude to futures trading will be much more realistic. You will expect strings of losses to occur at times. You won't get down on yourself because you have made a wrong bet on something that is, after all, basically unknowable.

You understand that if you act consistently over time, and take care to employ sufficient capital to ride out bad runs, then you will be profitable in the long run providing your strategy has a profitable expectation.

To win at the trading game you need a strategy with a positive expectancy. The system parameters that determine expectancy are the Probability of Winning, the size of the Average Win and the size of the Average Loss.

You apply this strategy consistently, without variation, as often as possible. The positive expectancy asserts itself in the long run and profits accrue, although there will be bad runs which cause short term losses.

When you look at examples like tossing a coin or rolling a die, it is easy to see what the Probability of Winning is, but in real trading situations it is far from obvious. The only way of determining system parameters is by estimating them from samples of market action.

The usual way of doing this is by obtaining historical data and back-testing your strategy to see how it performed in the past, or by paper trading the strategy for a test period. In either case, your objective is to get reliable estimates of the system parameters.

There are some important caveats to emphasize:

• Small samples provide unreliable estimates of system parameters! Your test period should include a minimum of 20 trades, and preferably 50 or more.
• A strategy may not work in all market conditions. If you back-test your strategy in different periods when market conditions vary (bull market, bear market, sideways market), your parameter estimates are more reliable.
• The greatest trap of all is curve fitting.
• This occurs when you define rules in your strategy to optimize results obtained in a test period. If you look at any particular set of historical data, you can often specify trading rules which produce magnificent results applied over that period. (If only we could trade in the past, we would all be wealthy.)
• Curve fitted strategies can usually be recognized by their complexity and large number of rules and exceptions.
• Curve fitting is a very natural thing to do, so it is vital that you are on guard against it. The problem is that markets are infinitely variable, and a strategy optimized on data from one time period is most unlikely to perform well in other periods.
• The other problem with curve fitting is that the sample estimates of system parameters are no longer accurate, since they have been deliberately optimized.
• The best way of avoiding curve fitting is to define a strategy based on a trading idea (I will look at some of these in future articles). A strategy based on an idea of how markets work, or other traders react to certain events, can be developed independent of past data. If you then back-test that strategy, the results will not be curve fitted.
• But if, as a result of observations you make during the test period, you decide to make adjustments to the strategy, that is the time to beware. Any change you make must have a logical trading rationale - otherwise you will be falling into the curve fitting trap.

Consider a soybean futures strategy traded at the Chicago Board of Trade (CBOT). The strategy is based on the simple idea of trading price breakouts which occur during the first 30 minutes of the trading day. If no breakout occurs, there is no trade for the day. Otherwise the market is entered with a Buy or Sell order in the direction of the price breakout.

(A price breakout occurs when the price moves out of a previously established trading range.)

The target profit for the trade is determined from the chart pattern forming the trade setup, and the stop loss is set at an equal amount. In other words, the amount risked is equal to the potential profit in this strategy. If neither the profit target not the stop loss are reached during the trading day, the position is closed at the end of the session.