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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.
Monte Carlo simulation: Drawing a large number of pseudo-random uniform variables from the interval [0,1] at one time, or once at many different times, and assigning values less than or equal to 0.50 as heads and greater than 0.50 as tails, is a Monte Carlo simulation of the behavior of repeatedly tossing a coin.
In mathematical finance, a Monte Carlo option model uses Monte Carlo methods [Notes 1] to calculate the value of an option with multiple sources of uncertainty or with complicated features. [1] The first application to option pricing was by Phelim Boyle in 1977 (for European options ).
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Monte Carlo: methodologies and applications for pricing and risk management. Risk. ISBN 1-899332-91-X. Paul Glasserman (2003). Monte Carlo methods in financial engineering. Springer-Verlag. ISBN 0-387-00451-3. Peter Jaeckel (2002). Monte Carlo methods in finance. John Wiley and Sons. ISBN 0-471-49741-X. Don L. McLeish (2005).
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In mathematics, he has made important contributions to the field of Sobol sequences; while in Mathematical Finance, he has been influential in the development of Monte Carlo methods in finance, and has also contributed, to the LIBOR market model, and volatility modelling. [1] Jäckel received his D. Phil. in Physics from Oxford University in ...