Computational finance

Computational Finance is a branch of Applied Science that deals with problems of practical interest in finance . [1] Somewhat 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 analyzes . [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 price series . [6]

History

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 requirement is available at the time, so it worked on useful algorithms for approximate solutions. [7]Mathematical finance Began with la même insight, goal diverged by making Simplifying Assumptions to express relationships in a 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 Markowitz Harry, Paul Samuelson and Robert C. Merton ) [10] pioneered the use of computers in arbitrage trading. In academics, sophisticated computer processing is needed by 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” on Wall Street and brought along personal computers . This led to an explosion of both the size and variety of computational finance applications. [12] Many of the new cam from technical signal processingand speech recognition Rather than traditional fields of computational economics like optimization andtime 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 of the Iron Curtain , into finance. These people are known as ” financial engineers ” (“quant” as “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 has become 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 grown dramatically. [1] Moreover, many specialized companies have grown up to supply computational finance software and services. [10]

Applications of Computational Finance

  • Algorithmic trading
  • Quantitative investing
  • High-frequency trading

See also

  • List of finance topics
  • Quantitative analyst
  • List of quantitative analysts
  • Mathematical finance
  • QuantLib
  • Algorithmic trading
  • Master of Computational Finance
  • Financial reinsurance
  • Financial modeling

References

  1. ^ Jump up to:b Rüdiger U. Seydel, Tools for Computational Finance , Springer; 3rd edition (May 11, 2006) 978-3540279235
  2. Jump up^ “Computational Finance and Research Laboratory” . University of Essex . Retrieved 2012-07-21 .
  3. Jump up^ Cornelis A. Los,Computational FinanceScientific World Scientific Co Inc. (December 2000) 978-9810244972
  4. Jump up^ Mario J. Miranda and Paul L. Fackler,Applied Computational Economics and Finance, The MIT Press (September 16, 2002) 978-0262134200
  5. Jump up^ Omur Ugur,Introduction to Computational Finance, Imperial College Press (December 22, 2008) 978-1848161924
  6. Jump up^ Jin-Chuan Duan, Karl Härdle Wolfgang and James E. Gentle (editors),Handbook of Computational Finance, Springer (October 25, 2011) 978-3642172533
  7. Jump up^ Harry M. Markowitz,Portfolio Selection:WileyEfficient Diversification of Investments, second edition (September 3, 1991) 978-1557861085
  8. ^ Jump up to:b Justin Fox, The Myth of the Rational Market: A History of Risk, Reward, and Delusion on Wall Street , HarperBusiness (June 9, 2009) 978-0060598990
  9. Jump up^ 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) 978-0809045990
  10. ^ Jump up to:b Michael Goodkin, The Wrong Answer Faster: The Inside Story of Making the Machine That Trades Trillions , Wiley, (February 21, 2012) 978-1118133408
  11. ^ Jump up to:b Aaron Brown, Red-Blooded Risk: The Secret History of Wall Street , Wiley (October 11, 2011) 978-1118043868
  12. ^ Jump up to:b John F. Ehlers, Rocket Science for Traders , Wiley (July 20, 2001) 978-0471405672
  13. Jump up^ Aaron Brown,The Face of Wall Street Poker, Wiley (March 31, 2006) 978-0470127315
  14. Jump up^ “Center for Computational Finance” . Carnegie Mellon University . Retrieved 2012-07-21 .