The successful futures day trader knows that trading is a form of betting. It is a numbers game based on probabilities. The traders task is to adopt a strategy with favourable odds and execute the strategy as perfectly as possible.
To be successful, the trader identifies one or more setups which signal high expectancy trades. The setups are most often related to some kind of chart pattern, or a signal given by one or more technical indicators. I look at some ideas for setups in other articles. For now it is sufficient to understand that a setup should be measurable. It is a clear, unambiguous signal to enter a trade, and each trade should be managed in exactly the same way so that the results of the trade can be accurately determined in a theoretical test situation.
The expectancy of a trade cannot be estimated without testing the strategy. You test by either trying out the strategy on historical data (back-testing), or paper trading the strategy for a period of time. In either case you are unlikely to get a decent estimate unless the sample includes a minimum of 20 trades, preferably more.
You should observe the results for the trades in your test sample and calculate the Probability of Winning - P(W), the Probability of Losing - P(L), the Average Win in dollars - A(W), and the Average Loss in dollars - A(L). Use the following formula to estimate the Expectancy for your strategy:
E = P(W) x A(W) - P(L) x A(L)
For example, you test 50 trades resulting in 30 wins (60%) and 20 losses (40%), with an average win of $300 and average loss of $200.
E = (60% x 300) - (40% x 200) = 180 - 80 = $100
This means that in the long run you expect to make $100 per trade using this strategy.
Many people examine historical data to determine a good trading strategy. After this, you cannot use the same data to estimate Expectancy, because the strategy is optimised for this particular set of data. To estimate Expectancy, back-test data from a different period or run an independent paper trading trial. Ignoring this principle results in curve fitting and you delude yourself into thinking your strategy is better than it really is.
No strategy can be profitable unless it has a positive expectation, but higher expectation does not necessarily lead to higher profit. You must also consider the opportunities to trade generated by your strategy. A strategy averaging 10 trades per day with an Expectancy of $50/trade is better than a strategy providing 2 trades per year with an Expectancy of $1,000/trade.
You can see from the formula that Expectancy is a function of both the Probability of Winning and the Average Win to Average Loss ratio. If you only win 1 in 4 trades, but the average win is $400 versus an average loss of $80.
E = (1/4 x 400) - (3/4 x 80) = 100 - 60 = 40
This is a situation where a strategy with a low probability of winning has a positive Expectancy because wins are much bigger than losses. In contrast, suppose you win 8 out of 10 trades with an average win of $80 and an average loss of $300:
E = (0.8 x 80) - (0.2 x 300) = 56 - 60 = -4
This strategy wins much more often than it loses, but has a negative Expectancy because losses are substantially bigger than wins.
There is no right answer for the balance of these parameters, other than that the Expectancy for your trading strategy must be positive. Often, improving your average win to average loss ratio will decrease the probability of winning, and vice-versa.
However, for a small trader there is an advantage in gaining positive Expectancy by having a high probability of winning. Sticking to a strategy that generates a lot of winners is less strain on the trader!
A positive Expectancy is no guarantee against a run of losses. Indeed, with most strategies it is almost certain that there will be significant strings of losses at some time. However, a positive Expectancy should lead to profits in the long run, providing the trader uses proper money management and can survive losing sequences.
In summary, the trader needs to specify clearly defined strategies which can be traded in a mechanical manner whenever their setup occurs. The strategy should be tested (avoiding the trap of curve fitting) to ensure that it has a positive Expectancy. Thereafter, the trader should execute the strategy at every possible opportunity.
That is how to win.
David Bennett trades US commodity futures from his home on the Gold Coast in Australia. He provides coaching and mentoring services for people wanting to start trading for themselves. Visit http://www.12oclocktrades.com to read more futures trading articles.