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Computational finance

Simulation of Brownian Motion sample paths is an important tool in calculating the price of financial instruments under the risk-neutral measure.

Computational finance is a branch of applied computer science that deals with problems of practical interest in finance.[1] Some slightly different definitions are the study of data and algorithms currently used in finance[2] and the mathematics of computer programs that realize financial models or systems.[3]

Computational finance emphasizes practical numerical methods rather than mathematical proofs and focuses on techniques that apply directly to economic analyses.[4] It is an interdisciplinary field between mathematical finance and numerical methods.[5] Two major areas are efficient and accurate computation of fair values of financial securities and the modeling of stochastic time series.[6]

  1. ^ Rüdiger U. Seydel, Tools for Computational Finance, Springer; 3rd edition (May 11, 2006) 978-3540279235
  2. ^ "Computational Finance and Research Laboratory". University of Essex. Archived from the original on 2012-07-12. Retrieved 2012-07-21.
  3. ^ Cornelis A. Los, Computational Finance World Scientific Pub Co Inc (December 2000) ISBN 978-9810244972
  4. ^ Mario J. Miranda and Paul L. Fackler, Applied Computational Economics and Finance, The MIT Press (September 16, 2002) ISBN 978-0262134200
  5. ^ Omur Ugur, Introduction to Computational Finance, Imperial College Press (December 22, 2008) ISBN 978-1848161924
  6. ^ Jin-Chuan Duan, Wolfgang Karl Härdle and James E. Gentle (editors), Handbook of Computational Finance, Springer (October 25, 2011) ISBN 978-3642172533

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