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SVI estimation of the implied volatility by Kalman filter.Burnos, Sergey, Ngow, ChaSing January 2010 (has links)
To understand and model the dynamics of the implied volatility smile is essential for trading, pricing and risk management portfolio. We suggest a linear Kalman filter for updating of the Stochastic Volatility Inspired (SVI) model of the volatility. From a risk management perspective we generate the 1-day ahead forecast of profit and loss (P\&L) of option portfolios. We compare the estimation of the implied volatility using the SVI model with the cubic polynomial model. We find that the SVI Kalman filter has outperformed the others.
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