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Computational finance

October 23, 2023

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]

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

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]

History Edit

The birth of computational finance as a discipline can be traced to Harry Markowitz in the early 1950s. Markowitz conceived of the portfolio selection problem as an exercise in mean-variance optimization. This required more computer power than was available at the time, so he worked on useful algorithms for approximate solutions.[7] Mathematical finance began with the same insight, but diverged by making simplifying assumptions to express relations in simple closed forms that did not require sophisticated computer science to evaluate.[8]

In the 1960s, hedge fund managers such as Ed Thorp[9] and Michael Goodkin (working with Harry Markowitz, Paul Samuelson and Robert C. Merton)[10] pioneered the use of computers in arbitrage trading. In academics, sophisticated computer processing was needed by researchers such as Eugene Fama in order to analyze large amounts of financial data in support of the efficient-market hypothesis.[8]

During the 1970s, the main focus of computational finance shifted to options pricing and analyzing mortgage securitizations.[11] In the late 1970s and early 1980s, a group of young quantitative practitioners who became known as "rocket scientists" arrived on Wall Street and brought along personal computers. This led to an explosion of both the amount and variety of computational finance applications.[12] Many of the new techniques came from signal processing and speech recognition rather than traditional fields of computational economics like optimization and time series analysis.[12]

By the end of the 1980s, the winding down of the Cold War brought a large group of displaced physicists and applied mathematicians, many from behind the Iron Curtain, into finance. These people become known as "financial engineers" ("quant" is a term that includes both rocket scientists and financial engineers, as well as quantitative portfolio managers).[13] This led to a second major extension of the range of computational methods used in finance, also a move away from personal computers to mainframes and supercomputers.[11] Around this time computational finance became recognized as a distinct academic subfield. The first degree program in computational finance was offered by Carnegie Mellon University in 1994.[14]

Over the last 20 years, the field of computational finance has expanded into virtually every area of finance, and the demand for practitioners has grown dramatically.[1] Moreover, many specialized companies have grown up to supply computational finance software and services.[10]

Applications of Computational Finance Edit

See also Edit

References Edit

  1. ^ a b Rüdiger U. Seydel, Tools for Computational Finance[permanent dead link], Springer; 3rd edition (May 11, 2006) 978-3540279235
  2. ^ "Computational Finance and Research Laboratory". University of Essex. 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
  7. ^ Harry M. Markowitz, Portfolio Selection: Efficient Diversification of Investments, Wiley, second edition (September 3, 1991) 978-1557861085
  8. ^ a b Justin Fox, The Myth of the Rational Market: A History of Risk, Reward, and Delusion on Wall Street, HarperBusiness (June 9, 2009) ISBN 978-0060598990
  9. ^ William Poundstone, Fortune's Formula: The Untold Story of the Scientific Betting System That Beat the Casinos and Wall Street, Hill and Wang (September 19, 2006) ISBN 978-0809045990
  10. ^ a b Michael Goodkin, The Wrong Answer Faster: The Inside Story of Making the Machine that Trades Trillions, Wiley, (February 21, 2012) ISBN 978-1118133408
  11. ^ a b Aaron Brown, Red-Blooded Risk: The Secret History of Wall Street, Wiley (October 11, 2011) ISBN 978-1118043868
  12. ^ a b John F. Ehlers, Rocket Science for Traders, Wiley (July 20, 2001) ISBN 978-0471405672
  13. ^ Aaron Brown, The Poker Face of Wall Street, Wiley (March 31, 2006) 978-0470127315
  14. ^ "Center for Computational Finance". Carnegie Mellon University. Retrieved 2012-07-21.

External links Edit

  • IEEE Computational Finance and Economics Technical Committee
  • An Introduction to Computational Finance without Agonizing Pain
  • Introduction to Computational Finance, IEEE Computational Intelligence Society Newsletter, August 2004
  • Centre for Computational Finance and Economic Agents (CCFEA)
  • The Journal of Computational Finance

October 23, 2023
computational, finance, branch, applied, computer, science, that, deals, with, problems, practical, interest, finance, some, slightly, different, definitions, study, data, algorithms, currently, used, finance, mathematics, computer, programs, that, realize, fi. 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 Simulation of Brownian Motion sample paths is an important tool in calculating the price of financial instruments under the risk neutral measure 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 Contents 1 History 2 Applications of Computational Finance 3 See also 4 References 5 External linksHistory EditThe birth of computational finance as a discipline can be traced to Harry Markowitz in the early 1950s Markowitz conceived of the portfolio selection problem as an exercise in mean variance optimization This required more computer power than was available at the time so he worked on useful algorithms for approximate solutions 7 Mathematical finance began with the same insight but diverged by making simplifying assumptions to express relations in simple closed forms that did not require sophisticated computer science to evaluate 8 In the 1960s hedge fund managers such as Ed Thorp 9 and Michael Goodkin working with Harry Markowitz Paul Samuelson and Robert C Merton 10 pioneered the use of computers in arbitrage trading In academics sophisticated computer processing was needed by researchers such as Eugene Fama in order to analyze large amounts of financial data in support of the efficient market hypothesis 8 During the 1970s the main focus of computational finance shifted to options pricing and analyzing mortgage securitizations 11 In the late 1970s and early 1980s a group of young quantitative practitioners who became known as rocket scientists arrived on Wall Street and brought along personal computers This led to an explosion of both the amount and variety of computational finance applications 12 Many of the new techniques came from signal processing and speech recognition rather than traditional fields of computational economics like optimization and time series analysis 12 By the end of the 1980s the winding down of the Cold War brought a large group of displaced physicists and applied mathematicians many from behind the Iron Curtain into finance These people become known as financial engineers quant is a term that includes both rocket scientists and financial engineers as well as quantitative portfolio managers 13 This led to a second major extension of the range of computational methods used in finance also a move away from personal computers to mainframes and supercomputers 11 Around this time computational finance became recognized as a distinct academic subfield The first degree program in computational finance was offered by Carnegie Mellon University in 1994 14 Over the last 20 years the field of computational finance has expanded into virtually every area of finance and the demand for practitioners has grown dramatically 1 Moreover many specialized companies have grown up to supply computational finance software and services 10 Applications of Computational Finance EditAlgorithmic trading Quantitative investing High frequency tradingSee also EditOutline of finance Quantitative analyst List of quantitative analysts Mathematical finance Financial engineering QuantLib Master of Computational Finance Master of Quantitative Finance Financial reinsurance Financial modelingReferences Edit a b Rudiger U Seydel Tools for Computational Finance permanent dead link Springer 3rd edition May 11 2006 978 3540279235 Computational Finance and Research Laboratory University of Essex Retrieved 2012 07 21 Cornelis A Los Computational Finance World Scientific Pub Co Inc December 2000 ISBN 978 9810244972 Mario J Miranda and Paul L Fackler Applied Computational Economics and Finance The MIT Press September 16 2002 ISBN 978 0262134200 Omur Ugur Introduction to Computational Finance Imperial College Press December 22 2008 ISBN 978 1848161924 Jin Chuan Duan Wolfgang Karl Hardle and James E Gentle editors Handbook of Computational Finance Springer October 25 2011 ISBN 978 3642172533 Harry M Markowitz Portfolio Selection Efficient Diversification of Investments Wiley second edition September 3 1991 978 1557861085 a b Justin Fox The Myth of the Rational Market A History of Risk Reward and Delusion on Wall Street HarperBusiness June 9 2009 ISBN 978 0060598990 William Poundstone Fortune s Formula The Untold Story of the Scientific Betting System That Beat the Casinos and Wall Street Hill and Wang September 19 2006 ISBN 978 0809045990 a b Michael Goodkin The Wrong Answer Faster The Inside Story of Making the Machine that Trades Trillions Wiley February 21 2012 ISBN 978 1118133408 a b Aaron Brown Red Blooded Risk The Secret History of Wall Street Wiley October 11 2011 ISBN 978 1118043868 a b John F Ehlers Rocket Science for Traders Wiley July 20 2001 ISBN 978 0471405672 Aaron Brown The Poker Face of Wall Street Wiley March 31 2006 978 0470127315 Center for Computational Finance Carnegie Mellon University Retrieved 2012 07 21 External links EditIEEE Computational Finance and Economics Technical Committee An Introduction to Computational Finance without Agonizing Pain Introduction to Computational Finance IEEE Computational Intelligence Society Newsletter August 2004 Numerical Techniques for Options Monte Carlo Simulation of Stochastic Processes Centre for Computational Finance and Economic Agents CCFEA The Journal of Computational Finance Retrieved from https en wikipedia org w index php title Computational finance amp oldid 1152613938, wikipedia, wiki, book, books, library,

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