Modelling the implied volatility surface based on Shanghai 50ETF options |
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| Affiliation: | 1. Clark University, Worcester, MA 01610, United States;2. Prairie View A&M University, Prairie View, TX 77446, United States;3. University of Nebraska-Lincoln, Lincoln, NE 68588, United States;1. Department of Mathematics, Kunsan National University, Kunsan 54150, Republic of Korea;2. Department of Mathematics, Yonsei University, Seoul 120-749, Republic of Korea |
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| Abstract: | We develop a dynamic factor model to forecast the implied volatility surface (IVS) of Shanghai Stock Exchange 50ETF options. Based on the assumption that dynamic change in IVS is mean-reverting and Markovian, we use a state space model to capture the dynamics of IVS, and set the latent factors to be the Ornstein–Uhlenbeck processes. We obtain the optimal estimations of parameters using the Kalman filter algorithm. Empirical results show that our model performs better than the traditional IVS model in terms of fitting ability and prediction performance. |
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| Keywords: | Dynamic factor model Implied volatility surface Kalman filter Ornstein–Uhlenbeck process |
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