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Topic: Monte Carlo methods in finance

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	Monte Carlo Methods (Site not responding. Last check: 2007-11-06)
		The Monte Carlo method is a numerical method of solving mathematical problems by the simulation of random variables.
		However, because simulation of random variables by hand is a laborious process, the use of the Monte Carlo method as a universal numerical technique became practical only with the advent of computers and high-quality pseudorandom number generators.
		Monte Carlo is one of the most versatile and widly used numerical methods, unbeatable for solving multidimensional problems in composite domains.
	sprng.cs.fsu.edu /montecarlo.html (290 words)

	Monte Carlo methods in finance - Wikipedia, the free encyclopedia
		Monte Carlo methods are ideally suited to evaluating difficult integrals (see also Monte Carlo method).
		The method here can be extended to generate sample paths of several variables, where the normal variables building up the sample paths are appropriately correlated.
		Let us suppose that we wish to obtain the Monte Carlo value of a derivative H, but know the value analytically of a similar derivative I. Then H* = (Value of H according to Monte Carlo) + (Value of I analytically) - (Value of I according to same Monte Carlo paths) is a better estimate.
	en.wikipedia.org /wiki/Monte_Carlo_methods_in_finance (1060 words)

	The World-Wide Web Virtual Library: Random Numbers and Monte Carlo methods
		In a series of papers the research group of J.F. Traub has shown that quasi-Monte Carlo methods using low discrepancy sequences are superior to Monte Carlo methods for the high dimensional integrals arising in mathematical finance.
		Monte Carlo Methods a lecture by Erich Ormand.
		The Molecular Monte Carlo Home Page is meant to serve as an information resource for those who use "random walks" (stochastic methods) to simulate and analyze molecular systems throughout the world.
	random.mat.sbg.ac.at /links/monte.html (1022 words)

	Derivatives Portal
		Monte Carlo methods have been used in the financial community for many years for addressing complex financial calculations.
		Monte Carlo Methods in Finance is an important reference for those working in investment banks, insurance and strategic management consultancy.
		Of particular importance are the many known variance reduction methods, and they are duly covered, not only in their own right, but also with respect to their potential combinations, and in the direct context of realistic applications.
	www.derivativesportal.org /Articles/detail.asp?Id=3028 (371 words)

	Applications of Monte Carlo Methods to Finance & Insurance, 2003
		Monte Carlo methods are useful in solving a wide range of problems, both stochastic and deterministic, that cannot easily be solved using analytic methods.
		The text illustrates the practical application of such methods to real-life problems in finance and insurance by presenting several in-depth case studies, including a model for generating stochastic interest rates and issues having to do with the important concept of value at risk, a measure for assessing the risk and/or performance of assets and/or liabilities.
		Lord is the author or coauthor of numerous papers and contributed chapters, in finance, mathematics, higher education and demography, one of which won a Financial Management Association prize for distinguished applied research.
	www.actexmadriver.com /productdetails.cfm?PC=1055 (577 words)

	Monte Carlo Methods in Finance
		Monte Carlo methods are mentioned briefly in two opening chapters, but the author spends most of those chapters on topics unrelated to the title of the book.
		If you are looking for a solid introduction to Monte Carlo methods (and especially variance reduction), there are better introductions.
		If you are interested in the use of Monte Carlo methods in financial engineering, this book doesn't compare to Glasserman's (2003) excellent treatise.
	www.riskbook.com /titles/jackel_p_(2002).htm (586 words)

	Monte carlo methods in finance
		Many people in these earlier generations were monte carlo methods in financ able to go to school, get an education and work for a single employer for their entire working lives.
		The monte carloo methods in finance most important thing you can do when beginning to build a good credit report is to always pay your bills on time and to never, ever borrow more than you can afford to pay back.
		Peter Taylor is a senior financial analyst at easyfinance4u with an acumen for finance and monte carlo mtehods in finance insurance.
	fincosultant.fcpages.com (6307 words)

	Amazon.com: Monte Carlo Methods in Financial Engineering (Stochastic Modelling and Applied Probability): Books: Paul ... (Site not responding. Last check: 2007-11-06)
		Monte Carlo simulations are extensively used not only in finance but also in network modeling, bioinformatics, radiation therapy planning, physics, and meteorology, to name a few.
		When applying Monte Carlo simulation, the author restricts himself to options that can only be exercised at a finite, fixed set of opportunities, with a discrete Markov chain used to model the underlying process representing the discounted payoff from the exercise of the option at a particular time.
		Monte Carlo simulation then allows the calculation of the transition probabilities and the averaged payoffs, and then these calculations are used to obtain estimates of the approximating value function.
	www.amazon.com /Financial-Engineering-Stochastic-Modelling-Probability/dp/0387004513 (3291 words)

	Monte Carlo Methods in Financial Engineering
		Monte Carlo Methods are among the most broadly applicable and thus most powerful tools for valuing derivatives securities and measuring their risks.
		As computer speeds continue to increase and new research expands the scope and efficiency of these methods, their use is destined to grow.
		It is roughly divided into three parts: the first three chapters concentrate on the basics of Monte Carlo methods; the next three develop ways to improve Monte Carlo methods; and the final four chapters deal with more specialized problems arising, in particular applications of Monte Carlo to financial engineering.
	www.defaultrisk.com /bk_mcmfe.htm (173 words)

	Monte Carlo Methods
		Monte Carlo methods are computational methods used to make simulations of complex systems in physics, finance, biology and other fields.
		The methods involve using random numbers and statistics to determine an unknown quantity.
		On this page, the basic principle behind Monte Carlo methods will be demonstrated with a simple example that most people should be able to understand easily: the approximation of the number π (pi).
	www.idius.net /montecarlo (712 words)

	biblio-cup
		A quantization method for the discretization of bsde's and reflected bsde's.
		A confidence interval for Monte Carlo methods with an application to simulation of obliquely reflecting Brownian motion.
		Monte Carlo evaluation of functionals of stochastic differential equations-variance reduction and numerical examples.
	cermics.enpc.fr /~bl/monte-carlo.html (1401 words)

	Real Options with Monte Carlo Simulation (Site not responding. Last check: 2007-11-06)
		The Monte Carlo method solves a problem by simulating directly the physical process, and is not necessary to write down the differential equations that describe the behavior of the system.
		The name "Monte Carlo" appeared in the World War II times, and sometimes is attributed to the researcher Nicholas Metropolis, inspired in the interest of Stanislaw Ulam, his colleague of Manhattan Project at Los Alamos, in the poker game.
		Monte Carlo simulation is considered a good way to face these problems, but there is the difficult problem to optimize.
	www.puc-rio.br /marco.ind/monte-carlo.html (4270 words)

	Monte Carlo methods, Goodman, Fall 2005
		Monte Carlo is a computational technique with a large and growing range of applications.
		Today, Monte Carlo is having big impacts in biology and genomics, finance, statistics, atmospheric modeling, and in many other areas.
		Finally, many advanced Monte Carlo strategies have parameters that can be optimized to improve the performance of the Monte Carlo algorithm.
	www.math.nyu.edu /faculty/goodman/teaching/MonteCarlo2005/index.html (575 words)

	Monte Carlo & Quasi-Monte Carlo Methods (via CobWeb/3.1 planetlab1.netlab.uky.edu) (Site not responding. Last check: 2007-11-06)
		MCQMC 2004 in France, proceedings published as Monte Carlo and Quasi-Monte Carlo Methods 2004, Table of Contents, eds.
		MCQMC 2002 in Singapore, proceedings published as Monte Carlo and Quasi-Monte Carlo Methods 2002, Table of Contents (PDF), Harald Niederreiter, ed.
		MCQMC 2000 in Hong Kong, proceedings published as Monte Carlo and Quasi-Monte Carlo Methods 2000, Table of Contents (PDF), K. Fang, F. Hickernell and H. Niederreiter, ed.
	www.mcqmc.org.cob-web.org:8888 (195 words)

	GloriaMundi Resource Detail page (Site not responding. Last check: 2007-11-06)
		First- and second-order sensitivities are then used in a Monte Carlo simulations to determine the distribution of the value of the entire portfolion over a short time interval.
		Monte Carlo simulation is widely used in pricing and risk management of complex financial instruments.
		Deterministic simulation methods (quasi-Monte Carlo methods) are superior to Monte Carlo in terms of accuracy and speed.
	www.gloriamundi.org /resultstop10.asp?keyword=monte (1163 words)

	Amazon.co.uk: Monte Carlo Methods in Financial Engineering: v. 53 (Stochastic Modeling and Applied Probability): Books: ... (Site not responding. Last check: 2007-11-06)
		Monte Carlo simulation has become an essential tool in the pricing of derivative securities and in risk management.
		This book develops the use of Monte Carlo methods in finance and it also uses simulation as a vehicle for presenting models and ideas from financial engineering.
		The first part develops the fundamentals of Monte Carlo methods, the foundations of derivatives pricing, and the implementation of several of the most important models used in financial engineering.
	www.amazon.co.uk /Monte-Carlo-Methods-Financial-Engineering/dp/0387004513 (630 words)

	Monte Carlo methods in finance (via CobWeb/3.1 planetlab1.netlab.uky.edu) (Site not responding. Last check: 2007-11-06)
		In the field of financial mathematics, many problems, for instance the problem of finding the arbitrage-free value of a particular derivative security, boil down to the computation of a particular integral.
		Recall from the fundamental theorem of finance that the value of a derivative is equal to the discounted expected value of the derivative payoff where the expectation is taken under the risk-neutral measure
		= (Value of H according to Monte Carlo) + (Value of I analytically) - (Value of I according to same Monte Carlo paths) is a better estimate.
	monte-carlo-methods-in-finance.iqnaut.net.cob-web.org:8888 (978 words)

	Monte Carlo method - Wikipedia, the free encyclopedia
		For many types of problems, its efficiency relative to other numerical methods increases as the dimension of the problem increases.
		Arnaud Doucet, Nando de Freitas and Neil Gordon, Sequential Monte Carlo methods in practice, 2001, ISBN 0-387-95146-6.
		Approximation of π with the Monte Carlo Method
	en.wikipedia.org /wiki/Monte_Carlo_method (1970 words)

	Amazon.com: Monte Carlo Methods in Finance: Books: Peter Jaeckel (Site not responding. Last check: 2007-11-06)
		Monte Carlo, Density of Ali-Mikhail-Haq, Density of Clayton, Density of Frank, Density of Gumbel, John von Neumann, Density of Gaussian, Peter Acklam
		Monte Carlo Methods in Finance by Peter Jaeckel
		This book is pretty good as it covers lots of different areas of Monte Carlo simulation and some of the newer stuffs, such as copulae, etc. The math presentation is brief but to the point as application of the mathematics to Monte Carlo methods is the emphasis.
	www.amazon.com /Monte-Methods-Finance-Peter-Jaeckel/dp/047149741X (1543 words)

	Forums - Monte Carlo Simulation
		10:32 PM Monte Carlo simulation as a tool sounds more elaborate than what it really is. That is not to say that you cannot use it for elaborate analysis.
		11:19 PM Amazon dot com sells a book called "Monte Carlo methods in finance" and another one called "Monte Carlo simulation in finance." Maybe they might be of some benefit.
		Monte Carlo simulation as a tool sounds more elaborate than what it really is. That is not to say that you cannot use it for elaborate analysis.
	www.elitetrader.com /vb/showthread.php?threadid=59758 (459 words)

	Workshops - Centre for Analytical Finance - Indian School of Business (Site not responding. Last check: 2007-11-06)
		The workshop is aimed at financial researchers and analysts, including derivatives desk staff at financial services companies, and anyone else interested in modern computational techniques used in finance.
		The workshop provided analytical insights and technical skills in applied finance that are very important for superior performance but are not usually available from a single source.
		Monte Carlo techniques for portfolio credit risk and credit derivatives.
	www.isb.edu /ISB-CAF/htmls/workshop.htm (457 words)

	marcus evans - events, conferences, summits, training
		Understand the Monte Carlo simulation and speed-up methods such as antithetic and control variates, and sampling from standard processes like GBM and OU processes
		simulation represents the most effective method at present for the valuation of options and risk management of complex derivatives portfolios, but in order to fully grasp the implications of pricing the instruments, a practical workshop is mandatory.
		Webber is a frequent speaker at academic and industry conferences and the author of various publications on aspects of modelling and computational finance.
	www.marcusevans.com /EVENTS/Banking_Finance_TCEventinfo.asp?RecID=11261 (535 words)

	CAF Workshop on Computational Finance - News & Events - Indian School of Business
		A Workshop on Computational Finance was organised by the Centre for Analytical Finance (CAF), ISB, on July 15, 2006.
		It was aimed at financial researchers and analysts, including derivatives desk staff at financial services companies, and anyone else interested in modern computational techniques used in finance.
		The instructors provided analytical insights and technical skills in applied finance that are very important for superior performance, but are not usually available from a single source.
	www.isb.edu /campussbuzz1/CAFWorkshop_ComputationalFinance.html (137 words)

	Selected documents by Peter Jaeckel
		Errata in Monte Carlo methods in finance (John Wiley and Sons, February 2002).
		Fast numerical integration methods for stochastic volatility models in financial markets are discussed.
		This article is about plain vanilla FX option approximations in a cross currency Libor market model with explicit (displaced diffusion) control over the skew of both domestic and foreign interest rates, as well as the spot FX process.
	www.jaeckel.org (470 words)

	Publisher description for Library of Congress control number 2004025812 (Site not responding. Last check: 2007-11-06)
		A state-of-the-art book on Monte Carlo simulation methods for finance professionals and students Monte Carlo methods have been used for decades in physics, engineering, statistics, and other fields.
		Monte Carlo Simulation and Finance explains the nuts and bolts of this essential technique used to value derivatives and other securities.
		Author and educator Don McLeish examines this fundamental process, and discusses important issues, including specialized problems in finance that Monte Carlo and Quasi-Monte Carlo methods can help solve and the different ways Monte Carlo methods can be improved upon.
	www.loc.gov /catdir/description/wiley051/2004025812.html (188 words)

	Monte Carlos And Metropolis
		The algorithm of choice for Monte Carlo analysis of the Ising Model involves repeated, probabilistic updates of individual spins.
		Probability models are common in a variety of areas, ranging from physics and chemistry to sociology and finance.
		There are many, many forms for Monte Carlo calculations depending on the details of the problem at hand.
	oscar.cacr.caltech.edu /Hrothgar/Ising/monte.html (2059 words)

	Finance & Stochastics: An Application of Malliavin Calculus to Monte Carlo Methods in Finance (Site not responding. Last check: 2007-11-06)
		Finance & Stochastics: An Application of Malliavin Calculus to Monte Carlo Methods in Finance
		Our method is compared to the Monte Carlo finite difference approach and turns out to be very efficient in the case of discontinuous payoff functionals.
		Monte Carlo methods, Malliavin calculus, hedge ratios and Greek
	www.math.ethz.ch /~finasto/abstracts/1997/FS-97-125.html (161 words)

	index (Site not responding. Last check: 2007-11-06)
		Monte Carlo and Quasi-Monte Carlo Methods, Mathematical Finance
		Monte Carlo and Quasi-Monte Carlo Methods 1996, Lecture Notes in Statistics, Volume 127, Springer-Verlag, 1997.
		Third International Conference On Monte Carlo and Quasi-Monte Carlo Methods in Scientific Computing, July, 1998, Claremont Graduate University, Claremont, CA.
	www.cs.bsu.edu /homepages/gokten (227 words)

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