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How is the filter Q1500US built?

I want to build a filter AllTimeHigh(window_length) to filter/scan stocks which is/are all time high. I think I could do similarly as the Q1500US. Where can I find the code?

2 responses

Hi Thomas,

The underlying code for the Q1500 and Q500 universes is not available, but this community post offers a great explanation fo how these universes are constructed. You can create similar universes using the make_us_equity_universe and default_us_equity_universe_mask.

One note on your AllTimeHigh filter idea is that it would require you to load the entire history of pricing data, which would quickly result in memory issues. Also, this would require the window_length to increase as the simulation progresses and pipeline definitions cannot be updated on runtime.

One solution would be to instead check if the security is at an all-time-high over a sliding window.

I hope this helps.

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A really AllTimeHigh Filter is not yet built. But I've created a fator for doing similar. Since I use the 'pd.rolling_max' and 'pd.rolling_min', (the so-called sliding window?) it doesn't take much time. See attached algo.

Maybe someone else has a better idea?

Clone Algorithm
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Backtest from to with initial capital
Total Returns
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Alpha
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Beta
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Sharpe
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Sortino
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Max Drawdown
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Benchmark Returns
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Volatility
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Returns 1 Month 3 Month 6 Month 12 Month
Alpha 1 Month 3 Month 6 Month 12 Month
Beta 1 Month 3 Month 6 Month 12 Month
Sharpe 1 Month 3 Month 6 Month 12 Month
Sortino 1 Month 3 Month 6 Month 12 Month
Volatility 1 Month 3 Month 6 Month 12 Month
Max Drawdown 1 Month 3 Month 6 Month 12 Month
# Backtest ID: 5a0edcf2d41799450387f40a
There was a runtime error.