A factor that people keep expressing for what constitutes a good strategy is that the strategy should show consistent profits over the backtest period (i.e. $100/day over 10 days instead of $1000 on one day and flat the rest).
In other words, the profit curve should be "smooth" and, ideally, steep. Unfortunately, there's no easy way to optimize for this in the current implementation. I propose that we could measure these factors by performing a linear regression across the set of trades for a given strategy and measuring the standard deviation of the trades from the resultant line-of-best-fit. A strategy that has a steep, positive line-of-best-fit, as well as a low standard deviation would be an ideal candidate for trading because it would have been highly profitable over the entire backtest period. The downside of incorporating this sort of calculation into the optimizer is that it would add a lot of overhead into an already CPU- intensive process. However, it could also provide a lot of insight into what constitutes a good strategy. Thoughts? --~--~---------~--~----~------------~-------~--~----~ You received this message because you are subscribed to the Google Groups "JBookTrader" group. To post to this group, send email to [email protected] To unsubscribe from this group, send email to [EMAIL PROTECTED] For more options, visit this group at http://groups.google.com/group/jbooktrader?hl=en -~----------~----~----~----~------~----~------~--~---
