I'm a complete newbie so please be kind.
Evidence-Based Technical Analysis: Applying the Scientific Method and Statistical Inference to Trading Signals by David Aronson
And I'm struggling to understand the following excerpt:
ER = [p (long) × avg. daily return] − [p (short) × avg. daily return]
For example, if the position biases were 60 percent long and 40 percent short, the expected return is zero.
0 = [0.60) × 0] − [0.40 × 0] Position Bias: 60 percent long, 40 percent short
If, on the other hand, a rule does have predictive power, its expected return on detrended data will be greater than zero. This positive return reflects the fact that the rule’s long and short positions are intelligent rather than random.
I fail to see how its possible for this equation to ever produce a result greater than zero if the detrended market data mandates the avg. daily return to be 0.