Roulette, with a paltry 1/37, or 2.7% edge, makes casinos serious profit over time, financial trading sits on very similar ground. Having a statistical edge does not necessarily result with positive expectancy, though it definitely helps. This calls for an empirical test.
Empirical analysis
Forecast Model- Multilayer Perceptron Neural Network
Input/Predictive Variables- Various commodity and Dow Jones indexes
Output/Dependent Variable- Next Day Return of the S&P500 Index (Next Day Open price – Next Day closing price)
Training Period- from Jan. 2002 to Jan 2005
Test Period- from Jan 2005 to Aug. 2009
Focused only on next-day direction, the predicted values offered a winning rate of just about 54%. Keep in mind this stands quite superior to the roulette casino edge. Then out of curiosity, I wanted to see how hypothetical trades off these forecasts would have resulted, basically buying/shorting at the open and liquidating positions at the NYSE close. Virtual trading equity starts at 1, or 100%, and would compound daily, winning or losing. See chart below.
I know- it’s pretty cool, 400% plus return in roughly 4.5 years. It also appeared that the mid 2007 volatility jump pushed performance up tremendously. This brings the thought that maybe with volatility based position size adjustments; return over time could become smoother and even higher. Imagine what a higher hit rate could achieve…
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