Document Type thesis Author Name Krykova, Inna URN etd-0113104-140925 Title Evaluating of path-dependent securities with low discrepancy methods Degree MS Department Mathematical Sciences Advisors Domokos Vermes, Advisor Keywords variance-reduction techniques Quasi- Monte Carlo path-dependent securities low-discrepancy methods Date of Presentation/Defense 2003-12-23 Availability unrestricted
The objective of this thesis is the implementation of Monte Carlo and quasi-Monte Carlo methods for the valuation of financial derivatives. Advantages and disadvantages of each method are stated based on both the literature and on independent computational experiments by the author. Various methods to generate pseudo-random and quasi-random sequences are implemented in a computationally uniform way to enable objective comparisons.
Code is developed in VBA and C++, with the C++ code converted to a COM object to make it callable from Microsoft Excel and Matlab. From the simulated random sequences Brownian motion paths are built using various constructions and variance-reduction techniques including Brownian Bridge and Latin hypercube. The power and efficiency of the methods is compared on four financial securities pricing problems: European options, Asian options, barrier options and mortgage-backed securities. In this paper a detailed step-by-step algorithm is given for each method (construction of pseudo- and quasi-random sequences, Brownian motion paths for some stochastic processes, variance- and dimension- reduction techniques, evaluation of some financial securities using different variance-reduction techniques etc).
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