Improving volatility prediction and option valuation using VIX information: A volatility spillover GARCH model |
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| Authors: | Zhiyuan Pan Yudong Wang Li Liu Qing Wang |
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| Affiliation: | 1. Institute of Chinese Financial Studies, Southwestern University of Finance and Economics, Chengdu, China;2. School of Economics and Management, Nanjing University of Science and Technology, Nanjing, China;3. School of Finance, Nanjing Audit University, Nanjing, China;4. Institute of Chinese Financial Studies, Southwestern University of Finance and Economics, Chengdu, China Collaborative Innovation Center of Financial Security, Chengdu, China |
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| Abstract: | We develop a new generalized autoregressive conditional heteroskedasticity (GARCH) model that accounts for the information spillover between two markets. This model is used to detect the usefulness of the CBOE volatility index (VIX) for improving the performance of volatility forecasting and option pricing. We find the significant ability of VIX to predict stock volatility both in-sample and out-of-sample. VIX information also helps to greatly reduce the option pricing error. The proposed volatility spillover GARCH model performs better than the related approaches proposed by Kanniainen et al. (2014, J Bank Finance, 43, pp. 200-211) and P. Christoffersen et al. (2014, J Financ Quant Anal, 49, pp. 663–697). |
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| Keywords: | G12 option valuation VIX volatility forecasting volatility spillover |
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