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Monte Carlo methods in finance

Monte Carlo methods are used in corporate finance and mathematical finance to value and analyze (complex) instruments, portfolios and investments by simulating the various sources of uncertainty affecting their value, and then determining the distribution of their value over the range of resultant outcomes.[1][2] This is usually done by help of stochastic asset models. The advantage of Monte Carlo methods over other techniques increases as the dimensions (sources of uncertainty) of the problem increase.

Monte Carlo methods were first introduced to finance in 1964 by David B. Hertz through his Harvard Business Review article,[3] discussing their application in Corporate Finance. In 1977, Phelim Boyle pioneered the use of simulation in derivative valuation in his seminal Journal of Financial Economics paper.[4]

This article discusses typical financial problems in which Monte Carlo methods are used. It also touches on the use of so-called "quasi-random" methods such as the use of Sobol sequences.

  1. ^ "Real Options with Monte Carlo Simulation". Archived from the original on 2010-03-18. Retrieved 2010-09-24.
  2. ^ "Monte Carlo Simulation". Palisade Corporation. 2010. Retrieved 2010-09-24.
  3. ^ "Risk Analysis in Capital Investment". Harvard Business Review. Sep 1, 1979. p. 12. Retrieved 2010-09-24.
  4. ^ Boyle, Phelim P. (1977). "Options: A Monte Carlo approach". Journal of Financial Economics. 4 (3). Journal of Financial Economics, Volume (Year): 4 (1977), Issue (Month): 3 (May): 323–338. doi:10.1016/0304-405X(77)90005-8. Retrieved 2010-09-24.

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