Assume I have a trading system that I'm evaluating over a three-year period. The returns are 25%, -40% and 25%. Empirically, I can see that this system loses because at the end of three years, I have less than when I started.
Wikipedia defines expected return
as follows:
E(R)= Sum: probability (in scenario i) * the return (in scenario i)
If we insert our values into this formula, we get the following:
E(R) = (.33 * .25) + (.33 * -.40) + (.33 * .25) = .033
So a positive expected return for a system that loses every time, no matter if you re-arrange the order of the returns.
What's wrong here?
To further explain how the game works, consider an initial start value of 100. What can you expect at the end of the game? There are no re-investments, no withdrawls, no dividends, no broker fees nor SEC fees. It is a simple game. Here is some R code to illustrate the game.
first <- c(.25, .25, -.4)
second <- c(-.4, .25, .25)
third <- c(.25, -.4, .25)
Pass any of the above sequence of returns into this function:
game <- function(x){
start <- 100
for(i in 1:NROW(x))
start <- start + start*x[i]
return(start)
}
NOTE: I asked a similar question on quantexchange, but I'm interested here in the math behind the expected return equation.