Many problems in financial world are being modeled by means of differential equation. These problems are time dependent, highly nonlinear, stochastic and heavily depend on the previous history of time. A variety of financial products exists in the market, such as forwards, futures, swaps and options. Our main focus in this thesis is to use the numerical analysis tools to solve some option pricing problems. Depending upon the inter-relationship of the financial derivatives, the dimension of the associated problem increases drastically and hence conventional methods (for example, the finite difference methods or finite element methods) for solving them do not provide satisfactory results. To resolve this issue, we use a special class of numerical methods, namely, the mesh free methods. These methods are often better suited to cope with changes in the geometry of the domain of interest than classical discretization techniques. In this thesis, we apply these methods to solve problems that price standard and non-standard options. We then extend the proposed approach to solve Heston' volatility model. The methods in each of these cases are analyzed for stability and thorough comparative numerical results are provided.

A robust computational framework is presented for the risk-neutral valuation of capital guarantees written on discretely-reallocated portfolios following the Constant Proportion Portfolio Insurance (CPPI) strategy. Aiming to address the (arguably more realistic) cases where analytical results are unavailable, this framework accommodates risky-asset jumps, volatility surfaces, borrowing restrictions, nonuniform reallocation schedules and autonomous CPPI floor trajectories. The two-asset state space representation developed herein facilitates visualising the CPPI strategy, which in turn provides insight into grid design and interpolation. It is demonstrated that given a deterministic process for the risk-free rate, the pricing problem can be cast as solving cascading systems of 1D partial integro-differential equations (PIDEs). This formulation’s stability and monotonicity are studied. In addition to making more sense financially, the limited borrowing variant of the CPPI strategy is found to be better suited than the classical (unlimited borrowing) counterpart for bounded-domain calculations. Consequently, it is demonstrated how the unlimited borrowing problem can be approximated by imposing an artificial borrowing limit. For implementation validation, analytical solutions to special cases are derived. Numerical tests are presented to demonstrate the versatility of this framework.

Many problems in financial world are being modeled by means of differential equation. These problems are time dependent, highly nonlinear, stochastic and heavily depend on the previous history of time. A variety of financial products exists in the market, such as forwards, futures, swaps and options. Our main focus in this thesis is to use the numerical analysis tools to solve some option pricing problems. Depending upon the inter-relationship of the financial derivatives, the dimension of the associated problem increases drastically and hence conventional methods (for example, the finite difference methods or finite element methods) for solving them do not provide satisfactory results. To resolve this issue, we use a special class of numerical methods, namely, the mesh free methods. These methods are often better suited to cope with changes in the geometry of the domain of interest than classical discretization techniques. In this thesis, we apply these methods to solve problems that price standard and non-standard options. We then extend the proposed approach to solve Heston' volatility model. The methods in each of these cases are analyzed for stability and thorough comparative numerical results are provided.

A robust computational framework is presented for the risk-neutral valuation of capital guarantees written on discretely-reallocated portfolios following the Constant Proportion Portfolio Insurance (CPPI) strategy. Aiming to address the (arguably more realistic) cases where analytical results are unavailable, this framework accommodates risky-asset jumps, volatility surfaces, borrowing restrictions, nonuniform reallocation schedules and autonomous CPPI floor trajectories. The two-asset state space representation developed herein facilitates visualising the CPPI strategy, which in turn provides insight into grid design and interpolation. It is demonstrated that given a deterministic process for the risk-free rate, the pricing problem can be cast as solving cascading systems of 1D partial integro-differential equations (PIDEs). This formulation’s stability and monotonicity are studied. In addition to making more sense financially, the limited borrowing variant of the CPPI strategy is found to be better suited than the classical (unlimited borrowing) counterpart for bounded-domain calculations. Consequently, it is demonstrated how the unlimited borrowing problem can be approximated by imposing an artificial borrowing limit. For implementation validation, analytical solutions to special cases are derived. Numerical tests are presented to demonstrate the versatility of this framework.

No mercado financeiro, a precificação de contratos complexos muitas vezes apoia-se em técnicas de simulação numérica. Estes métodos de precificação geralmente apresentam baixo desempenho devido ao grande custo computacional envolvido, o que dificulta a análise e a tomada de decisão por parte do trader. O objetivo deste trabalho é apresentar uma ferramenta de alto desempenho para a precificação de instrumentos financeiros baseados em simulações numéricas. A proposta é construir uma calculadora eficiente para a precificação de opções multivariadas baseada no método de Monte Carlo, utilizando a plataforma CUDA de programação paralela. Serão apresentados os conceitos matemáticos que embasam a precificação risco-neutra, tanto no contexto univariado quanto no multivariado. Após isso entraremos em detalhes sobre a implementação da simulação Monte Carlo e a arquitetura envolvida na plataforma CUDA. No final, apresentaremos os resultados obtidos comparando o tempo de execução dos algoritmos. / In the financial market, the pricing of complex contracts often relies on numerical simulation techniques. These pricing methods generally present poor performance due to the large computational cost involved, which makes it difficult for the trader to analyze and make decisions. The objective of this work is to present a high performance tool for the pricing of financial instruments based on numerical simulations. The proposal is to present an efficient calculator for the pricing of multivariate options based on the Monte Carlo method, using the parallel programming CUDA platform. The mathematical concepts underlying risk-neutral pricing, both in the univariate and in the multivariate context, will be presented. After this we will detail the implementation of the Monte Carlo simulation and the architecture involved in the CUDA platform. At the end, we will present the results obtained comparing the execution time of the algorithms.

Philosophiae Doctor - PhD / Many problems in financial world are being modeled by means of differential equation. These problems are time dependent, highly nonlinear, stochastic and heavily depend on the previous history of time. A variety of financial products exists in the market, such as forwards, futures, swaps and options. Our main focus in this thesis is to use the numerical analysis tools to solve some option pricing problems. Depending upon the inter-relationship of the financial derivatives, the dimension of the associated problem increases drastically and hence conventional methods (for example, the finite difference methods or finite element methods) for solving them do not provide satisfactory results. To resolve this issue, we use a special class of numerical methods, namely, the mesh free methods. These methods are often better suited to cope with changes in the geometry of the domain of interest than classical discretization techniques. In this thesis, we apply these methods to solve problems that price standard and non-standard options. We then extend the proposed approach to solve Heston' volatility model. The methods in each of these cases are analyzed for stability and thorough comparative numerical results are provided. / South Africa

Doctor Scientiae - DSc / Robust Spectral Methods for Solving Option Pricing Problems by Edson Pindza PhD thesis, Department of Mathematics and Applied Mathematics, Faculty of Natural Sciences, University of the Western Cape Ever since the invention of the classical Black-Scholes formula to price the financial derivatives, a number of mathematical models have been proposed by numerous researchers in this direction. Many of these models are in general very complex, thus closed form analytical solutions are rarely obtainable. In view of this, we present a class of efficient spectral methods to numerically solve several mathematical models of pricing options. We begin with solving European options. Then we move to solve their American counterparts which involve a free boundary and therefore normally difficult to price by other conventional numerical methods. We obtain very promising results for the above two types of options and therefore we extend this approach to solve some more difficult problems for pricing options, viz., jump-diffusion models and local volatility models. The numerical methods involve solving partial differential equations, partial integro-differential equations and associated complementary problems which are used to model the financial derivatives. In order to retain their exponential accuracy, we discuss the necessary modification of the spectral methods. Finally, we present several comparative numerical results showing the superiority of our spectral methods.

Philosophiae Doctor - PhD / Many problems in financial world are being modeled by means of differential equation. These problems are time dependent, highly nonlinear, stochastic and heavily depend on the previous history of time. A variety of financial products exists in the market, such as forwards, futures, swaps and options. Our main focus in this thesis is to use the numerical analysis tools to solve some option pricing problems. Depending upon the inter-relationship of the financial derivatives, the dimension of the associated problem increases drastically and hence conventional methods (for example, the finite difference methods or finite element methods) for solving them do not provide satisfactory results. To resolve this issue, we use a special class of numerical methods, namely, the mesh free methods. These methods are often better suited to cope with changes in the geometry of the domain of interest than classical discretization techniques. In this thesis, we apply these methods to solve problems that price standard and non-standard options. We then extend the proposed approach to solve Heston's volatility model. The methods in each of these cases are analyzed for stability and thorough comparative numerical results are provided.

論文摘要 Reiner（1992）說明投資人對他國投資股票時，除了關心外國股價風險外，也關切匯率變動的風險，所以他提出了匯率連動選擇權，來規避匯率風險。另外，對於規避股價風險方面，Bouaziz, Briys and Crouhy（1994；以下簡稱BBC（1994））為了防止商品受人為操縱或其他原因而產生不合理的股價風險，提出遠期生效亞洲選擇權。以及Gray及Whaley（1999）提出了重設型賣權，它不但具有一般賣權的基本特徵，也能使投資人於購買股票時，同時買進一個重設型賣權。它不但可規避股價下跌的風險，在股價上升時，因賣權的重設使得保險的底值（Floor）向上提昇而鎖住股價上漲的資本利得。 本論文分別結合上述兩種選擇權的特徵（規避匯率風險與股價風險）而設計出兩種新金融商品，分別是：「匯率連動遠期生效亞洲選擇權」與「匯率連動重設型賣權」。它們的優點為：（1）可提供投資人同時對外國股價風險及匯率風險進行避險。（2）同時，評價模型的簡單化（類似Black-Scholes模型）以及避險操作的簡易性，使發行券商（或銀行）可獲得風險控管，因此可降低避險損失，提昇利潤。

本論文推導違約風險下四種新奇選擇權的評價模型及其避險比率，依序為數據選擇權、寬它選擇權、互換選擇權，極值選擇權。並比較無違約風險與違約風險下的評價模型之差異。假若違約風險不存在時，違約風險下各種類型選擇權的評價模型皆會縮減成為無違約風險下所對應的評價模型。避險比率亦為如此。數值範例則印證違約風險下選擇權的價值較無違約風險選擇權的價值低。本論文完成目前尚無任何學術研究於違約風險下四種新奇選擇權的評價模型及避險比率。這是一個重要貢獻。 關鍵詞：違約風險、新奇選擇權、數據選擇權、寬它選擇權、互換選擇權、極值選擇權。 / This paper presents the analytic pricing formula and the hedging ratio of four kinds of exotic options with correlated credit risk. They are Digital options, Quanto Options, Exchange Options and Extreme-value Options, respectively. Furthermore, compare the discrepancy of the models under the condition whether the default risk exists. Finding that if there is no default risk, all models that we derive will reduce to the corresponding models with no default risks, and so do the hedging ratio. Numerical examples certify that the value of the vulnerable options will be lower than that of the ordinary options. All above that finished has not been done by existing researches and it is a chief contribution in this paper. Keywords: Exotic Options, Credit Risk, Digital Options, Quanto Options, Exchange Options, Extreme-value Options, Default Risk.