Tharp's Expectancy

[Paul Altman <paulha@xxxxxxxxxxxxx>]

Would one of you mathematicians kindly take a moment and explain to me why 
we'd require that a system demonstrate positive expected return 
historically, before we'd put any money on it?

I'm specifically looking at Tharp's definition of expectancy, where he 
states:  (p.148)  "Expectancy is a way of comparing trading systems while 
factoring out the effects of time, position sizing, and the fact that one 
is trading various instruments that have different prices."

Using _his_ definition, I think I can imagine a negative expectancy game 
that would make money, since you could conceivably have a position sizing 
algorithm that would "know" when to enormously increase your bet size on 
winning trades, even if those winning %'s were very small.

Obviously, all things being equal, I guess you'd want a higher expectancy 
rather than a lower one.  But why would you insist it be positive?  If I'm 
reading him correctly, he's saying that you don't want to play a negative 
expectancy at all.   With his definition removing position sizing as an 
input to the expectancy formula, I don't fully understand his reasoning.

      Paul