Ideally, a good performance measure should show high performance when the return on capital is high, when the equity/return curve increases linearly over time, and when loss periods (if any) are not clustered.
In the sentence above, Andrew Clark describes just exactly what all of us are looking for in designing, testing, and evaluating our trading systems.
Sorry for the lack of updates on the Melba Toast System. I've been very busy with other projects. But, haven't stopped dreaming up ways to capture the congestion. Here are just a few ideas that I will test as soon as I get the time:
- What if you count the number of weeks a stock closes above its mean and number of weeks closed below its mean? If the ratio of above to below is close to 1 then does that suggest a congestion range-bound area in the time series?
- Should we look for these congestion areas within a certain percentage from their all-time high? Or all-time low? Or both? Or maybe all-time high is too limited and we just need to look for a certain percentage from their 5-year high and low.
- Could using a stock's beta help identify congestion areas? Does the congestion area exhibit less beta than the market? Speaking of beta...has anyone ever attempted to create an indicator out of beta? Basically, the number of stocks with a beta above 1? If so, please share.
Well, that's it from here...where I'm looking forward to seeing Ricky Bobby on the big screen! Ha ha!
Later Trades,
MT
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