In this paper we deal with quantile hedging of derivatives in the stochastic volatility (SV) models. We assume that temporary volatility of the stock prices is AR(1) process (autoregressive process of order 1). Then we formulate the problem of maximizing the expected success coefficient regarded that the cost of the hedging is limited. We describe how to solve this problem using dynamical programming method. Then we show empirical results for Polish stock market and compare the quality of the quantile hedging with the hedging based on Black-Scholes model
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