Volatility timing: How best to forecast portfolio exposures

• How best to forecast portfolio weights in the context of a volatility timing strategy.
• We examine a number of traditional econometric models using intraday data.
• Directly forecast weights constructed from observed volatility.
• Naïve long term moving averages generate equivalent economic value to model forecasts.
• Forecasting weights give stable portfolios of similar economic benet to other models.

This paper investigates how best to forecast optimal portfolio weights in the context of a volatility timing strategy. It measures the economic value of a number of methods for forming optimal portfolios on the basis of realized volatility. These include the traditional econometric approach of forming portfolios from forecasts of the covariance matrix. Both naïve forecasts using simple historical averages, and those generated from econometric models are considered. A novel method, where a time series of optimal portfolio weights are constructed from observed realized volatility and direct forecast is also proposed. A number of naïve forecasts and the approach of directly forecasting portfolio weights show a great deal of merit. Resulting portfolios are of similar economic benefit to a number of competing approaches and are more stable across time. These findings have obvious implications for the manner in which volatility timing is undertaken in a portfolio allocation context.