Please use this identifier to cite or link to this item:
https://hdl.handle.net/20.500.14279/9612
Title: | Assessing the performance of symmetric and asymmetric implied volatility functions |
Authors: | Andreou, Panayiotis Charalambous, Chris Martzoukos, Spiros H. |
metadata.dc.contributor.other: | Aνδρέου, Παναγιώτης |
Major Field of Science: | Social Sciences |
Field Category: | Economics and Business |
Keywords: | Deterministic volatility functions;Implied volatility forecasting;Model selection;Option pricing;Stochastic volatility |
Issue Date: | 1-Apr-2014 |
Source: | Review of Quantitative Finance and Accounting, 2014, vol. 42, no. 3, pp. 373-397 |
Volume: | 42 |
Issue: | 3 |
Start page: | 373 |
End page: | 397 |
DOI: | 10.1007/s11156-013-0346-z |
Journal: | Review of Quantitative Finance and Accounting |
Abstract: | This study examines several alternative symmetric and asymmetric model specifications of regression-based deterministic volatility models to identify the one that best characterizes the implied volatility functions of S&P 500 Index options in the period 1996-2009. We find that estimating the models with nonlinear least squares, instead of ordinary least squares, always results in lower pricing errors in both in- and out-of-sample comparisons. In-sample, asymmetric models of the moneyness ratio estimated separately on calls and puts provide the overall best performance. However, separating calls from puts violates the put-call-parity and leads to severe model mis-specification problems. Out-of-sample, symmetric models that use the logarithmic transformation of the strike price are the overall best ones. The lowest out-of-sample pricing errors are observed when implied volatility models are estimated consistently to the put-call-parity using the joint data set of out-of-the-money options. The out-of-sample pricing performance of the overall best model is shown to be resilient to extreme market conditions and compares quite favorably with continuous-time option pricing models that admit stochastic volatility and random jump risk factors. |
URI: | https://hdl.handle.net/20.500.14279/9612 |
ISSN: | 15737179 |
DOI: | 10.1007/s11156-013-0346-z |
Rights: | © Springer Nature |
Type: | Article |
Affiliation : | Cyprus University of Technology Durham University University of Cyprus |
Publication Type: | Peer Reviewed |
Appears in Collections: | Άρθρα/Articles |
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