Great initial results! Personally I’m getting suspicious when a simple model produces very high sharpes for long periods of time. Performance statistics usually change when you eliminate all data snooping and implement transaction costs.
From my experience the trading costs could be devastating for the model performance. I would suggest using an approximation in % per trade. Also, i am not sure what kind of backtesting procedure you use. Do you test the performance on the training set? In that case data snooping is introduced with risk of overfitting.

you’ll find the equity curve here: http://twitpic.com/w9mqc

Best,
Frank

Could you please make a chart which includes the massive market crunch at early 2000, when the IT bubble burst? I.e. 1990-2008 straight, without splitting it in two 10-year pieces. It would be interesting to see the behaviour.

No problem — obviously your first priorities should be elsewhere, as they are. I will happily take “light” twitter updates over none!

Thanks for all your posts this year. Best wishes for a great 2010. I hope it will be a prosperous year for all of us, and that your efforts with the new model will be very successful!

no, it doesn’t. But until the end of February I’ll be busy moving into a new home and always short of time during the regular session, so respective twiter updates unfortunately will be light. Sorry for any inconvenience caused.

Best,
Frank

Does this mean you will no longer be making your traditional “trading the odds” type posts?

I would really miss those….

the model is currently checking for a potentially long setup first, means if conditons x,y,z …are triggered, and is going short in the event NO buy setup is triggered. The latter is not optimal, because I’m going for the right end of the distribution (means the odds favor a greater move on the upside, see percentage-wise participation in the Top 10% Moves), while filtering out those occurrences where there is only a small (or no) edge on the upside.

It would be better to filter those occurrences as well where no buy setup is triggered if there is any edge on the short side, and if not, then simply take no position at all and stay in cash on the respective session (it doesn’t make sense to go long or short if no edge is provided). But currently the model is NOT optimized for the short side, means it will take a short position (no questions asked) if no buy setup is triggered.

The proprietary indicator is very similar to the RSI(2), but quantifying intermedium-term overbought/oversold conditions based on high/low/close data (similar to the ATR Average True Range). At the moment it’s difficult to quantify is’t impact on the model’s performance percentage-wise (but I’ll go into more detail over the course of the next couple of weeks).

Best,
Frank

Also just curious but how much of an effect does your proprietary indicators maximize results?