Looking through the leader board I noticed that max draw-down of all the entries is zero. How important is this as a measure of a good algorithm?
This backtest I made the other night produces 17553% returns between 2013-15, I wondered how effectively measures such as sharpe, beta and volatility can judge algorithms when the past returns seem so good?
Finally, I wondered what the highest% returns you guys can get (in the same 2year period) for fun.
Hi Edward,
The reason this algorithm has such huge returns is because it borrows and invests about 50x its capital base, so it's leveraged to the hilt. That kind of leverage is unrealistic in the equities market, but the backtesting engine assumes the user manages the margin/leverage accounting and allows you to borrow as much as you please.
Your code is actually correct as written, the reason the borrowing occurred is because orders were being placed when there were already open orders that had not filled yet due the slippage model used. I added a line to check for open orders, and recorded your leverage, that seems to fix the issue.
The various metrics like Sharpe and drawdown are pretty important, they give you an idea of how consistent a strategy is. For example, imagine you could borrow infinite capital and you invested in your algorithm above, there was a drawdown of 271% at one point, that would be pretty gut wrenching to experience in a real trading scenario.
Thanks for sharing!
best,
David
Hi Edward,
Before the last leaderboard update I made a quick code change that inadvertently resulted in all the max drawdown being equal to 0%. I'm fixing that tonight to be the same calculation as was prior to this.
Thanks for your understanding,
Justin
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