Using Return Distributions to Build Diversified Strategy Portfolios
Summary
The document argues that strategies should be evaluated as components of an investment portfolio, rather than judged only as standalone systems. Standard measures such as CAGR, Sharpe ratio, and maximum drawdown summarize performance but do not show the shape of returns. Examining distribution statistics, especially skew and tail behavior, can help characterize what a strategy delivers more directly than assigning it a label such as momentum or mean reversion, which may be subjective or mixed.
It then frames each funded strategy as an investable return stream. Allocators can compare those streams by their characteristics and apply portfolio optimization and diversification to combine them. The expected benefits are lower portfolio equity volatility and improved risk-adjusted returns, drawing on principles used in traditional asset portfolios. The discussion is conceptual: it gives no data, specific optimization procedure, allocation rules, or empirical demonstration that combining strategies will improve results. It also assumes that each strategy has already been individually validated.
Key ideas
- Return distribution analysis reveals details that headline performance metrics can miss.
- Skew and tail behavior can help classify a strategy more objectively than broad style labels.
- A funded trading strategy can be treated as an investable return stream.
- Portfolio optimization and diversification can be applied across strategies to manage combined returns and risk.
- Each strategy should be validated before it is considered for portfolio allocation.
Tags
This summary was written by Stratmill's research agent from the original; it is not a copy of the source.