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Validation of volatility models

Magdon-Ismail, Malik and Abu-Mostafa, Yaser S. (1998) Validation of volatility models. Journal of Forecasting, 17 (5-6). pp. 349-368. ISSN 0277-6693. https://resolver.caltech.edu/CaltechAUTHORS:20170408-150548267

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Abstract

In forecasting a financial time series, the mean prediction can be validated by direct comparison with the value of the series. However, the volatility or variance can only be validated by indirect means such as the likelihood function. Systematic errors in volatility prediction have an ‘economic value’ since volatility is a tradable quantity (e.g. in options and other derivatives) in addition to being a risk measure. We analyse the fidelity of the likelihood function as a means of training (in sample) and validating (out of sample) a volatility model. We report several cases where the likelihood function leads to an erroneous model. We correct for this error by scaling the volatility prediction using a predetermined factor that depends on the number of data points.


Item Type:Article
Related URLs:
URLURL TypeDescription
https://dx.doi.org/10.1002/(SICI)1099-131X(1998090)17:5/6<349::AID-FOR701>3.0.CO;2-XDOIArticle
Additional Information:© 1998 John Wiley & Sons, Ltd. We would like to thank Dr Amir Atiya, Joseph Sill and Zehra Cataltepe for helpful discussion.
Subject Keywords:validation; volatility prediction; maximum likelihood
Issue or Number:5-6
Record Number:CaltechAUTHORS:20170408-150548267
Persistent URL:https://resolver.caltech.edu/CaltechAUTHORS:20170408-150548267
Official Citation:Magdon-Ismail, M. and Abu-Mostafa, Y. S. (1998), Validation of volatility models. J. Forecast., 17: 349–368. doi:10.1002/(SICI)1099-131X(1998090)17:5/6<349::AID-FOR701>3.0.CO;2-X
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:76019
Collection:CaltechAUTHORS
Deposited By: 1Science Import
Deposited On:04 May 2017 22:28
Last Modified:03 Oct 2019 16:56

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