The bootstrap method works by repeatedly computing a metric on random samples drawn from the backtest’s returns. Then, the metric is computed on each random sample, and the average is taken. By doing this on thousands of random samples, we obtain a more robust and accurate estimate of the metric. So this is to see that whether our amazing backtesting result is just obtained by luck. In Monte Carlo simulation, if we simulate equity paths, being lucky means we get the equity curve with the highest return at the end. However, in real trading, the probability of picking this lucky equity curve is very low.
He joined J.P. Morgan AI Research as Managing Director in Jan 2019
who else is here after their backtest returns 7.377e+21% apr
“Don’t forward test”
can anyone please tell me what the last gentleman to ask a question, was talking about.Thank you.
some people use other ways to make their backtest more robust, like bootstrapping
trades and (Inaudible). Do you use this technique in practice?
The bootstrap method works by repeatedly computing a metric on random samples drawn from the backtest’s returns. Then, the metric is computed on each random sample, and the average is taken. By doing this on thousands of random samples, we obtain a more robust and accurate estimate of the metric. So this is to see that whether our amazing backtesting result is just obtained by luck. In Monte Carlo simulation, if we simulate equity paths, being lucky means we get the equity curve with the highest return at the end. However, in real trading, the probability of picking this lucky equity curve is very low.
His book is $35 for 148 pages on Amazon. So, counter to claims to the contrary, it's not cheap.
jonesr227 a book should be judged by its content not its pages
He says it's $5 in the video though.
Nice