Efficient Numerical Methods for Stochastic Differential Equations in Computational Finance

  • Juho Happola

Student thesis: Doctoral Thesis


Stochastic Differential Equations (SDE) offer a rich framework to model the probabilistic evolution of the state of a system. Numerical approximation methods are typically needed in evaluating relevant Quantities of Interest arising from such models. In this dissertation, we present novel effective methods for evaluating Quantities of Interest relevant to computational finance when the state of the system is described by an SDE.
Date of AwardSep 19 2017
Original languageEnglish (US)
Awarding Institution
  • Computer, Electrical and Mathematical Sciences and Engineering
SupervisorRaul Tempone (Supervisor)


  • options
  • Stochastic Differential Equations
  • Numerical Methods

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