Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 20 of 70 for “"Mathematical Finance"”.
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Level Crossing Times in Mathematical Finance
<p>Level crossing times and their applications in finance are of importance, given certain threshold levels that represent the "desirable" or "sell" values of a stock. In this thesis, we make use of Wald's lemmas and various deep results from renewal theory, in the context of finance, in modelling …
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The use of implied methodologies in mathematical finance
… the uses of implied methodologies in the area of Mathematical Finance. The existing literature broadly separates the ways that implied methodologies can be exploited in to two different categories; for purposes of recovery of the market sentiment and for consistent pricing of exotic and …
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Polynomial Multi-Curve Models And Extensions In Mathematical Finance
This thesis is organized into three chapters: In the first chapter, we introduce the changes that have occurred in the fixed-income market due to the credit crisis in 2007–2008. We then discuss the impact of this crisis on the pre-crisis relation between zero-coupon bonds and forward rate …
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Enlargement of Filtration, Backward Stochastic Differential Equations and Optimal Stopping Problems
… useful tool in stochastic optimal control and mathematical finance, the usefulness in the latter being that the solutions provide simultaneous calculation of derivative prices and their corresponding hedging strategies. Enlargement of filtration has a very intuitive application to BSDEs in a …
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The Symbol of a Markov Semimartingale
… of how our methods work for processes used in mathematical finance.
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Strongly Asymptotically Optimal Methods for the Pathwise Global Approximation of Stochastic Differential Equations with Coefficients of Super-linear Growth
… with the Heston–3/2–model originating from mathematical finance.
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Closing the memory gap in stochastic functional differential equations
… whose coefficients have linear growth. In mathematical finance, an option pricing formula with full finite memory is obtained through convergence of stock dynamics with memory gap to stock dynamics with full finite memory.
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Stochastic modelling of financial markets with differential information
Many of the fundamental results in mathematical finance are based on the assumption that all traders have access to exactly the same information, usually assumed to be the filtration generated by the history of stock prices or the history of the underlying Brownian motion. In the last fifteen years …
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The required ansatz to construct Lie point transformations and the symmetries of a first-order stochastic differential equation
… are of much use, for instance, in the field of mathematical finance whereby its use has shown the relationship between call options and their non-deterministic underlying stock prices. Wiener processes must be considered in finding an approximation of these integrals. Acclimatization of Sophus …
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Convergence in incomplete market models
… from nonstandard analysis in the context of mathematical finance is given as well as a brief introduction to mean-variance hedging and variance-optimal pricing.
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Optimal Stopping Problems with A Random Time Horizon
… of American contingent claim pricing problem in mathematical finance. We give a self-contained overview of the theory, including the complete proofs of existence and uniqueness theorems for the optimal stopping time in finite-time formulation. These theorems are developed with the goal of …
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Numerical approximation and parametric statistical inference of stochastic differential equations, with applications to finance
… modelling the dynamics of key state variables in mathematical finance such as instantaneous short rates of interest, share prices, and volatility processes. The appropriate application of SDEs requires reliable methods of generating sample paths from the equations, e.g. for use in Monte Carlo …
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Constructive approaches to quasi-Monte Carlo methods for multiple integration
… multiple integrals in hundreds of dimensions in mathematical finance, and were significantly more efficient than Monte Carlo methods. To understand the apparent success of quasi-Monte Carlo methods for multiple integration, one popular approach is to study worst-case error bounds in weighted …
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TOPICS IN STOCHASTICS AND STATISTICS: SHOCK CREATION AND DISSOLUTION FOR STABLE AND LINNIK CONSERVATION LAWS AND TARGET STUDENT RECRUITMENT USING PREDICTIVE MODELING
… including, for example, in application to mathematical finance and dislocation dynamics. Moreover, it has evolved into a vital and important part of the theory of conservation laws. It is known from recent work that the solutions of the fractal conservation laws exhibit shocks for bounded, …
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Information and generative deep learning with applications to medical time-series
… time-series monitoring (e.g. climate science, mathematical finance, signal processing). In the first half of this thesis, I focused firstly on information and causal influence in time- series data and then on flexible time-series modelling and hierarchical model comparison using Bayesian …
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On two utility maximization problems
… two expected utility maximization problems from mathematical finance. The first project (Chapter 2) deals with a single-agent utility maximization under constraints on intertemporal consumption; the second project (Chapter 3) studies Nash equilibria in an N-player game of utility maximization …
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Application of Lie symmetries to Solving Partial Differential Equations associated with the Mathematics of Finance
… for mathematicians working in the area of mathematical finance. Adopting their approach of deducing prices of contingent claim via solving the associated PDE models, we apply the algorithmic quantitative theory of Lie, the Lie symmetry analysis, to derive and solve the models associated …
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Calibrating the Hurst Parameter for Rough Volatility Models with Application in the South African Market
It is known that accurate and efficient calibration of any fractional stochastic volatility model is important for trading and risk management purposes. Under the rough Heston model proposed by El Euch et al. (2019), the Hurst parameter governs the roughness of the volatility process. This …
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