Some risk ideas:
- Downside Volatility (Volatility of negative returns).
- Max overall historical drawdown- to help assess potential downside volatility. Max monthly or quarterly negative return could be insightful too.
- Average bid/ask spread of stocks in simulation. The lower the better. Generally a model that performs the same but with higher liquidity should be more desirable
Remove Sharpe:
Flawed metric as upside volatility is not necessarily a risk.
If you want a substitute then downside deviation relative to the universe or benchmark can be chosen.
How is the risk score calculated?
“Risk Scores range from 1 to 5, with 1 being the least risky. The model's Risk Score reflects the combined impact of three criteria:
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three month volatility (lower is better)
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three month maximum drawdown (lower is better)
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number of positions (higher is better)
The scoring of each criteria and the overall score is done on a relative basis: the values are sorted then assigned a percentile depending on the order (not the magnitude).
(i) Since scoring is done on a relative basis, using only three months for statistics like volatility was enough to correctly classify models.”
Thoughts:
Is it just three months of performance for the stats or is it over a longer period with 3-month samples? If it is just three months total then:
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three month volatility (lower is better) (should be at least a year or more and use downside volatility. Ideally it could be over the entire live period, but it should be more than 3 months)
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three month maximum drawdown (lower is better) (Should be over a longer timespan too)
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number of positions (higher is better) agreed, but perhaps should only penalize under a specific number of stocks say 50 or 100 without extreme reward for say a 500 stock model. In other words, cap the score if a model has a high enough number.