Nowadays, financial derivatives play an increasingly important role in the global financial system, and options are popular structural financial derivatives, which attract much attention from academia and the industry. China Financial Futures Exchange (CFFEX) initiated the CSI 1000 index future and CSI 1000 index option in the Chinese market on July 22, 2022, which indicates a trend of acceleration in financial innovations in China’s financial market. This dissertation focuses on the volatility models in option pricing and modern numerical procedures that approximate option prices. In this dissertation, different stochastic volatility models, for example, the Black–Scholes model and the Heston stochastic volatility model, are introduced and applied to price in not only European options but also exotic options, which possess complicated payoff structures. Moreover, a comprehensive empirical analysis is conducted to demonstrate these option pricing algorithms based on the recent data of CSI 1000 index options in the Chinese market. / Business Administration/Finance

Doctor of Philosophy / Department of Mathematics / Alexander G. Ramm / A new method, the Dynamical Systems Method (DSM), justified recently, is applied to solving ill-conditioned linear algebraic system (ICLAS). The DSM gives a new approach to solving a wide class of ill-posed problems. In Chapter 1 a new iterative scheme for solving ICLAS is proposed. This iterative scheme is based on the DSM solution. An a posteriori stopping rules for the proposed method is justified. We also gives an a posteriori stopping rule for a modified iterative scheme developed in A.G.Ramm, JMAA,330 (2007),1338-1346, and proves convergence of the solution obtained by the iterative scheme. In Chapter 2 we give a convergence analysis of the following iterative scheme: u[subscript]n[superscript]delta=q u[subscript](n-1)[superscript]delta+(1-q)T[subscript](a[subscript]n)[superscript](-1) K[superscript]*f[subscript]delta, u[subscript]0[superscript]delta=0, where T:=K[superscript]* K, T[subscript]a :=T+aI, q in the interval (0,1),\quad a[subscript]n := alpha[subscript]0 q[superscript]n, alpha_0>0, with finite-dimensional approximations of T and K[superscript]* for solving stably Fredholm integral equations of the first kind with noisy data. In Chapter 3 a new method for inverting the Laplace transform from the real axis is formulated. This method is based on a quadrature formula. We assume that the unknown function f(t) is continuous with (known) compact support. An adaptive iterative method and an adaptive stopping rule, which yield the convergence of the approximate solution to f(t), are proposed in this chapter.

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