A simple sizing rule — trade smaller when markets are choppy, larger when they are calm — has produced one of the largest improvements in risk-adjusted return in the systematic literature.
Volatility clusters. High-volatility days tend to follow high-volatility days; calm follows calm. This is one of the most replicated stylised facts in financial econometrics, and it has a powerful practical implication: a strategy that holds a constant notional position is, in risk terms, taking far more risk in volatile regimes than in quiet ones.
The mechanics
Volatility targeting scales position size inversely to recent realised volatility — typically using an exponentially weighted estimator. The portfolio carries roughly constant ex-ante risk over time. The intuition is the same one any sensible discretionary trader uses informally; the discipline of doing it systematically is what differentiates institutional implementations.
Empirical effects
Across equities, futures and credit, volatility targeting tends to compress drawdowns, raise Sharpe ratios modestly, and — most importantly — make returns more behaviourally tolerable. Investors who can stay invested capture the long-run premium; volatility-targeted strategies make staying invested materially easier.
Pitfalls
Estimators that react too slowly miss regime shifts. Estimators that react too quickly produce excessive turnover. A blend of short-window and long-window estimators, with explicit transaction-cost penalties on sizing changes, is the modern best practice.
FAQ
Does volatility targeting reduce returns?
On average, no. It tends to be Sharpe-improving and drawdown-reducing. In strong bull markets it lags constant-notional alternatives, which is the cost of better risk control.