Adaptive Asset Allocation

Butler, Philbrick and Gordillo, who run a quantitative asset management firm, argue for a systematic allocation approach that adjusts holdings in response to observed returns and risk rather than holding fixed weights.

The critique of the conventional approach comes first. They argue that the standard sixty-forty portfolio and the strategic allocation framework depend on long-run return assumptions that cannot be estimated reliably, that they ignore observable changes in risk and correlation, and that the historical record supporting them covers a period of falling interest rates that will not repeat. They also argue that market-capitalisation weighting concentrates a portfolio in whatever has already risen.

Their method combines three elements applied to a universe of asset classes accessed through liquid instruments. Momentum selects the assets with the strongest recent returns, on the empirical finding that relative performance persists over intermediate horizons. Volatility estimation sizes positions so that each contributes comparable risk, since volatility is far more predictable than return. Correlation estimation adjusts the combination so the portfolio's total risk is minimised for the assets selected. The whole is rebalanced periodically.

They support this with backtests over long periods showing higher risk-adjusted returns and smaller drawdowns than static allocation.

The method's components are each supported in the academic literature: momentum, the low volatility effect and the predictability of volatility and correlation relative to returns. The combination's backtested performance depends on parameter choices made after seeing the data, which is the standard problem, and the authors' out-of-sample record since publication is where the evidence actually lies. Transaction costs and tax treatment matter more for this approach than for static allocation, and the book treats them lightly.