Volatility timing and portfolio selection: How best to forecast volatility
AbstractWithin the context of volatility timing and portfolio selection this paper considers how best to estimate a volatility model. Two issues are dealt with, namely the frequency of data used to construct volatility estimates, and the loss function used to estimate the parameters of a volatility model. We find support for the use of intraday data for estimating volatility which is consistent with earlier research. We also find that the choice of loss function is important and show that a simple mean squared error loss, overall provides the best forecasts of volatility upon which to form optimal portfolios.
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Bibliographic InfoPaper provided by National Centre for Econometric Research in its series NCER Working Paper Series with number 76.
Length: 14 pages
Date of creation: 12 Oct 2011
Date of revision:
Volatility; volatility timing; utility; portfolio allocation; realized volatility;
Find related papers by JEL classification:
- C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models &bull Diffusion Processes
- G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
- G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation
This paper has been announced in the following NEP Reports:
- NEP-ALL-2012-02-20 (All new papers)
- NEP-ECM-2012-02-20 (Econometrics)
- NEP-FOR-2012-02-20 (Forecasting)
- NEP-RMG-2012-02-20 (Risk Management)
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