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On the economic benefit of utility based estimation of a volatility model

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Author Info
Adam Clements () (QUT)
Annastiina Silvennoinen () (QUT)

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Abstract

Forecasts of asset return volatility are necessary for many financial applications, including portfolio allocation. Traditionally, the parameters of econometric models used to generate volatility forecasts are estimated in a statistical setting and subsequently used in an economic setting such as portfolio allocation. Differences in the criteria under which the model is estimated and applied may inhibit reduce the overall economic benefit of a model in the context of portfolio allocation. This paper investigates the economic benefit of direct utility based estimation of the parameters of a volatility model and allows for practical issues such as transactions costs to be incorporated within the estimation scheme. In doing so, we compare the benefits stemming from various estimators of historical volatility in the context of portfolio allocation. It is found that maximal utility based estimation, taking into account transactions costs, of a simple volatility model is preferred on the basis of greater realized utility. Estimation of models using historical daily returns is preferred over historical realized volatility.

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Publisher Info
Paper provided by National Centre for Econometric Research in its series NCER Working Paper Series with number 44.

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Length: 17 pages
Date of creation: 21 Jul 2009
Date of revision:
Handle: RePEc:qut:auncer:2009_57

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Related research
Keywords: Volatility; utility; portfolio allocation; realized volatility; MIDAS;

Find related papers by JEL classification:
C10 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General - - - General
C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions
G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting

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This page was last updated on 2009-11-25.


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