The aim of this thesis is the numerical valuation of the solution of the mean-variance hedging problem. The initial capital, the hedging strategy and the associated minimized variance are computed. The time changed Lévy process models the logarithm of a stock price. The stochastic time change is given by an integrated Cox-Ingersoll-Ross (CIR) or an Ornstein- Uhlenbeck (OU) process, respectively. While the initial capital and the hedging strategy are one-dimensional integrals, the variance of the hedging error requires computation of multidimensional integrals. In this context the dimension adaptive quadrature and the quasi monte carlo method (after Faure) will be considered. It turns out, that the initial capital in the CIR and OU cases is similar to the Black-Scholes price. The variance-optimal hedging strategy in the CIR and OU cases differs only slightly from the Black-Scholes delta hedge. While the variance of the Black-Scholes delta hedge error is zero, the variance of the hedging error of the hedging strategy in CIR and OU cases growths with maturity.
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The aim of this thesis is the numerical valuation of the solution of the mean-variance hedging problem. The initial capital, the hedging strategy and the associated minimized variance are computed. The time changed Lévy process models the logarithm of a stock price. The stochastic time change is given by an integrated Cox-Ingersoll-Ross (CIR) or an Ornstein- Uhlenbeck (OU) process, respectively. While the initial capital and the hedging strategy are one-dimensional integrals, the variance of the...
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