Update on Trading Research

I came to the conclusion that none of the trading tools I developed are reliable. They can match market behavior for a while and make money, but then the relationship breaks down. In the long run there is no relationship between any of these indicators and returns.

I wrote a back-testing program for Turtle type trend-following models. This allows me to optimize the time periods to use to maximize profits. There is the potential for over-fitting and unstable relationships here too. The answer I think is to regularly re-optimize as the market changes. This re-optimization is easy to do. Given that a wide range of values is profitable in the exercise I did, I don't think there would be a sudden failure. We will see.

In the backtest there were 78 trades with a 48% win rate. But wins were on average 3.45 times larger than losses. The annualized Sharpe ratio is 2.2. Here there is a negative correlation between the initial risk taken (amount of money lost if the stop is triggered) and profits. That means it makes sense to bet bigger when the risk is lower:

I am now trading Bitcoin futures with the optimized algorithm (Long Bitcoin since yesterday). Next step is to see if there are other futures I could trade. Stock index futures aren't more profitable than just going long the index.