There are two ways to skin a cat...
I know a number of you are still working on this, so I thought I would try a different approach to see what happens. 🙂
As well as using long term backtesting to try and find a formula that will give you the best trades going forward you can also backtest on very short term data and then over-optimize the results to tell you what to do next (the idea is that what happened several years ago isn't relevant but what happened last week/month is). So, for instance, you optimize on January's data to find the best entry price in January, then you use that entry price for February. Then at the end of February you optimize on February and use that entry price for March etc etc. Effectively, you are trying to see if the best entry price for one month has any relationship with the best entry price for the following month.
I've attached a spreadsheet that shows the results of optimizing for each month. The most important worksheet is the Summary sheet. I have split the results into Longs and Shorts. The stop is 50 points from entry. In Column A is the Entry Level (so 70 means 70 points above yesterday's Close). You can see that, for example, the best Long Entry Level for December 2002 was 70 (giving you $107 profit), but if you had used 70 as your Entry Level in January 2003 you would only have made $381, whereas the best entry level in January was at 10 (giving $619 profit). If you then used 10 as your Entry Level for February you would have lost $356. I hope this makes sense. :|
Unfortunately, I couldn't find a relationship between one month and the next. 😢 You can see that months like February and August on the long side produce losses whatever Entry Level you have. The best results come from using 60 on the Long side and -60 on the Short side right throughout the year. But you have no guarantee that these levels will work going forward.