On the economic benefit of utility based estimation of a volatility model
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.
|Date of creation:||21 Jul 2009|
|Date of revision:|
|Contact details of provider:|| Phone: 07 3138 5066|
Fax: 07 3138 1500
Web page: http://www.ncer.edu.au
More information through EDIRC
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Bollerslev, Tim, 1986.
"Generalized autoregressive conditional heteroskedasticity,"
Journal of Econometrics,
Elsevier, vol. 31(3), pages 307-327, April.
- Tim Bollerslev, 1986. "Generalized autoregressive conditional heteroskedasticity," EERI Research Paper Series EERI RP 1986/01, Economics and Econometrics Research Institute (EERI), Brussels.
- Andersen T. G & Bollerslev T. & Diebold F. X & Labys P., 2001. "The Distribution of Realized Exchange Rate Volatility," Journal of the American Statistical Association, American Statistical Association, vol. 96, pages 42-55, March.
- Patton, Andrew J., 2011.
"Volatility forecast comparison using imperfect volatility proxies,"
Journal of Econometrics,
Elsevier, vol. 160(1), pages 246-256, January.
- Andrew Patton, 2006. "Volatility Forecast Comparison using Imperfect Volatility Proxies," Research Paper Series 175, Quantitative Finance Research Centre, University of Technology, Sydney.
- Kenneth D. West & Hali J. Edison & Dongchul Cho, 1993.
"A utility based comparison of some models of exchange rate volatility,"
International Finance Discussion Papers
441, Board of Governors of the Federal Reserve System (U.S.).
- West, Kenneth D. & Edison, Hali J. & Cho, Dongchul, 1993. "A utility-based comparison of some models of exchange rate volatility," Journal of International Economics, Elsevier, vol. 35(1-2), pages 23-45, August.
- Kenneth D. West & Hali J. Edison & Dongchul Cho, 1992. "A Utility Based Comparison of Some Models of Exchange Rate Volatility," NBER Technical Working Papers 0128, National Bureau of Economic Research, Inc.
- Ser-Huang Poon & Clive W.J. Granger, 2003. "Forecasting Volatility in Financial Markets: A Review," Journal of Economic Literature, American Economic Association, vol. 41(2), pages 478-539, June.
- Torben G. Andersen & Tim Bollerslev & Francis X. Diebold & Paul Labys, 2003.
"Modeling and Forecasting Realized Volatility,"
Econometric Society, vol. 71(2), pages 579-625, March.
- Torben G. Andersen & Tim Bollerslev & Francis X. Diebold & Paul Labys, 2001. "Modeling and Forecasting Realized Volatility," Center for Financial Institutions Working Papers 01-01, Wharton School Center for Financial Institutions, University of Pennsylvania.
- Anderson, Torben G. & Bollerslev, Tim & Diebold, Francis X. & Labys, Paul, 2002. "Modeling and Forecasting Realized Volatility," Working Papers 02-12, Duke University, Department of Economics.
- Torben G. Andersen & Tim Bollerslev & Francis X. Diebold & Paul Labys, 2001. "Modeling and Forecasting Realized Volatility," NBER Working Papers 8160, National Bureau of Economic Research, Inc.
- Engle, Robert & Colacito, Riccardo, 2006. "Testing and Valuing Dynamic Correlations for Asset Allocation," Journal of Business & Economic Statistics, American Statistical Association, vol. 24, pages 238-253, April.
- Spyros Skouras, 2001.
"Decisionmetrics: A Decision-Based Approach to Econometric Modeling,"
01-11-064, Santa Fe Institute.
- Skouras, Spyros, 2007. "Decisionmetrics: A decision-based approach to econometric modelling," Journal of Econometrics, Elsevier, vol. 137(2), pages 414-440, April.
- Jeff Fleming, 2001. "The Economic Value of Volatility Timing," Journal of Finance, American Finance Association, vol. 56(1), pages 329-352, 02.
- Engle, Robert F, 1982. "Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation," Econometrica, Econometric Society, vol. 50(4), pages 987-1007, July.
- Fleming, Jeff & Kirby, Chris & Ostdiek, Barbara, 2003. "The economic value of volatility timing using "realized" volatility," Journal of Financial Economics, Elsevier, vol. 67(3), pages 473-509, March.
When requesting a correction, please mention this item's handle: RePEc:qut:auncer:2009_57. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (School of Economics and Finance)
If references are entirely missing, you can add them using this form.