@Jamie, Yeah, python is a bit of a brain bender coming from VBA (Excel?) But there are some code jocks here who are able to assist on the tough questions.

In general and in no particular order:

• Use an agnostic security selection technique rather than a fixed security set. Set Universe, or the fundamental filters or at least use the base 10 ETFs so that you are not introducing much of a selection bias into your results.
  
• Use all the data available. If your strategy cannot survive 2011, 2008 (or 2002 if Q only had the data) then it's basically a no go from the start.
  
• Introduce risk reduction to your strategy: stops, size reduction, hedges, regime filters can all help you reduce drawdowns. Better to be out than follow the pack into a hole.
  
• Creative index following works for pension funds running 100's of billions but you'll need more than that to deliver a viable strategy.
  
• Metrics for performance have been bandied about lately but Sharpe > 1, DD < 10%, annual RoR > 10% are general minimums for attracting money (all estimates).
  
• Work in as accurate as possible slippage + commissions.
  
• And I recommend creating a model strategy that exhibits much of the above -- but with limited or a simplistic entry model -- and keeping it evolving with new techniques you discover. Then you can use it as your own model for trying out new entry (and exit and risk) variations.
  

Thanks for the input--and yes, its VBA in excel. I agree with your points and i'll keep tinkering with this one. I may also try and leverage scipy and some of the other stats modules. The algo did not perform well during the 2009 bottom and i need a way to prevent that draw down.. I haven't added any stop losses to the model but i need to consider one.

Thanks!