The economic value of volatility timing using “realized” volatility ☆

By Jeff Fleming, C. Kirby, Barbara Ostdiek. 2003

652 citations recorded by the source corpus.

Subfields: Finance

View Paper: https://www.semanticscholar.org/paper/c54c84c83ffc692e1e038c3e9fc2f984b86359db

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Citations in the corpus

Demystifying Time‐Series Momentum Strategies: Volatility Estimators, Trading Rules and Pairwise Correlations (2020, neutral): “Fleming et al. (2003) investigate the performance and turnover benefits for a mean-variance portfolio from using more efficient estimates of volatility.”
Evaluating Volatility and Correlation Forecasts (2009, neutral): “Applications of volatility forecasts in portfolio decisions are have been widely explored (see [59, 27, 46, 32], amongst others).”
Measuring and modeling systematic risk in factor pricing models using high-frequency data (2003, positive): “Following the recent analysis in Fleming et al. (2001, 2003), the table reports the monthly fees that an investor with a quadratic utility function and constant relative risk aversion equal to c would be willing to pay to switch from the traditional RR 5-year monthly rolling regression-based…”
Market microstructure noise, integrated variance estimators, and the accuracy of asymptotic approximations (2011, methodology): “This section examines the economic bene ts of our nite sample methods by way of a dynamic portfolio allocation experiment in the spirit of Fleming et al. (2001, 2003) and West et al. (1993).”
Modeling and Forecasting Large Realized Covariance Matrices and Portfolio Choice (2017, neutral): “We evaluate the proposed model in terms of its forecasting performance in comparison to benchmark alternatives as well as in terms of its economic value in a conditional mean-variance analysis to assess the value of volatility forecasts to short-horizon investors as in Fleming et al. (2003).”
Realized Volatility: A Review (2008, background): “On the other hand, one might proceed, as in Fleming et al. (2001, 2003), by examining the economic benefits of different volatility measures in a dynamic portfolio allocation experiment (see also Section 5.2 for further discussion).”