I finished my third live trading system about a year ago and have been trading it with some success for the past six months. However, when I first starting designing and testing it I was still learning the ropes and as such, I ignored in-sample and out-of-sample data periods. So in essence, the system was tested over the entire data set available. Iíve just read Howard Bandyís Quantitative Trading Systems and as a result Iíve lost the nerve to trade my current system. To be honest, I was using discretion to pick between trades and sometimes ignoring trades if they looked too volatile anyway so perhaps my confidence in the code wasnít 100% in the first place. My question however, is this: are there situations where itís acceptable to not have in and out-of sample periods.
I canít see how the system Iím trading can be curve-fit and I was hoping somebody could enlighten me. I say this because of the following:
- The entry code is relatively simple; there are no complex functions or indicators used and there are relatively few actual entry conditions
- The system produces a large number of trades (about 400 a year, 4,000 over the last ten)
- The holding period is about 2 weeks per trade
- It returns a (genuine, I think) 35% per year and is VERY realistic (overly harsh slippage on entry and exit, accurately modeled brokerage, very restrictive volume and liquidity filters, no forward looking etc)
- The equity curve is consistent in slope over the past decade, with no major draw downs (11% ish max DD) or volatility (this is partly due to the large number of trades; I can limit position sizes and risk and I think this has a major effect on the overall DD)
I donít see how it can be dangerous to trade this system and Iíd like other peopleís opinions (especially yours Mr Bandy if possible). I understand I can wait six months and walk-forward test or perhaps alter the conditions a bit and see if thereís a major change in results, but Iím more interested in the theory of it. If something produces a consistent profit over a sufficiently large number of trades and your equity curve is smooth, I donít see how it can be curve fit.
To me it seems like if the frequency of trades is high enough over an extended period of time, there wouldnít be a single static piece of code that would fit that data set well enough to produce consistent performance.
Am I wrong?
By the way, I definitely recommend the book. Nice to see somebody apply some analytical rigor to an industry/genre that seems to be full of people spouting unfounded BS.
Any comments appreciated.