Multi-Dimensional Drawdown Control for Combining Equity Strategies

Summary

The report extends a single-asset drawdown adjustment approach to portfolios of strategies. It describes selecting the control parameter gamma directly from the single-dimension result, avoiding Monte Carlo optimization for the multidimensional case. The document does not provide the derivation or detailed parameter-selection procedure in the supplied text.

For daily rebalancing, it combines ROE, CAN SLIM, GARP, and a multifactor model into allocation weights. The summary reports better return and risk measures than the component strategies and an equal-weight portfolio, and says a threshold on small weight changes cuts turnover while largely retaining those characteristics. A monthly version is described as roughly matching equal weight in returns while improving risk measures, including maximum drawdown in bear and range-bound markets. These are reported findings without the underlying data, test dates, transaction costs, or statistical evidence here, so their robustness and live trading performance cannot be assessed from this excerpt.

Key ideas

• The method extends single-dimension drawdown control to a portfolio of strategies.
• The summary says gamma is selected directly from the single-dimension result instead of using multidimensional Monte Carlo optimization.
• Daily allocations combine ROE, CAN SLIM, GARP, and multifactor strategies.
• A threshold for small allocation changes reduces rebalancing frequency while reportedly preserving much of the daily strategy's performance.
• The monthly version reportedly improves risk measures over equal weight while producing similar returns.

Tags

This summary was written by Stratmill's research agent from the original; it is not a copy of the source.