Quasi Monte Carlo Methods In Finance With Application To Optimal Asset Allocation
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Quasi Monte Carlo Methods In Finance With Application To Optimal Asset Allocation
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Author : Mario Rometsch
language : en
Publisher: diplom.de
Release Date : 2014-04-11
Quasi Monte Carlo Methods In Finance With Application To Optimal Asset Allocation written by Mario Rometsch and has been published by diplom.de this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-04-11 with Mathematics categories.
Inhaltsangabe:Introduction: Portfolio optimization is a widely studied problem in finance. The common question is, how a small investor should invest his wealth in the market to attain certain goals, like a desired payoff or some insurance against unwished events. The starting point for the mathematical treatment of this is the work of Harry Markowitz in the 1950s. His idea was to set up a relation between the mean return of a portfolio and its variance. In his terminology, an efficient portfolio has minimal variance of return among others with the same mean rate of return. Furthermore, if linear combinations of efficient portfolios and a riskless asset are allowed, this leads to the market portfolio, so that a linear combination of the risk-free asset and the market portfolio dominates any other portfolio in the mean-variance sense. Later, this theory was extended resulting in the CAPM, or capital asset pricing model, which was independently introduced by Treynor, Sharpe, Lintner and Mossin in the 1960s. In this model, every risky asset has a mean rate of return that exceeds the risk-free rate by a specific risk premium, which depends on a certain attribute of the asset, namely its _. The so-called _ in turn is the covariance of the asset return normalized by the variance of the market portfolio. The problem of the CAPM is its static nature, investments are made once and then the state of the model changes. Due to this and other simplifications, this model was and is often not found to be realistic. An impact to this research field were the two papers of Robert Merton in 1969 and 1971. He applied the theory of Ito calculus and stochastic optimal control and solved the corresponding Hamilton-Jacobi-Bellman equation. For his multiperiod model, he assumed constant coefficients and an investor with power utility. Extending the mean-variance analysis, he found that a long-term investor would prefer a portfolio that includes hedging components to protect against fluctuations in the market. Again this approach was generalized by numerous researchers and results in the problem of solving a nonlinear partial differential equation. The next milestone in this series is the work by Cox and Huang from 1989, where they solve for Optimal Consumption and Portfolio Policies when Asset Prices Follow a Diffusion Process . They apply the martingale technique to get rid of the nonlinear PDE and rather solve a linear PDE. This, with several refinements, is [...]
Quasi Monte Carlo Methods In Finance
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Author : Mario Rometsch
language : en
Publisher: Diplomica Verlag
Release Date : 2008
Quasi Monte Carlo Methods In Finance written by Mario Rometsch and has been published by Diplomica Verlag this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008 with Asset allocation categories.
Portfolio optimization is a widely studied problem in finance dating back to the work of Merton from the 1960s. While many approaches rely on dynamic programming, some recent contributions use martingale techniques to determine the optimal portfolio allocation. Using the latter approach, we follow a journal article from 2003 and show how optimal portfolio weights can be represented in terms of conditional expectations of the state variables and their Malliavin derivatives. In contrast to other approaches, where Monte Carlo methods are used to compute the weights, here the simulation is carried out using Quasi-Monte Carlo methods in order to improve the efficiency. Despite some previous work on Quasi-Monte Carlo simulation of stochastic differential equations, we find them to dominate plain Monte Carlo methods. However, the theoretical optimal order of convergence is not achieved. With the help of some recent results concerning Monte-Carlo error estimation and backed by some computer experiments on a simple model with explicit solution, we provide a first guess, what could be a way around this difficulties. The book is organized as follows. In the first chapter we provide some general introduction to Quasi-Monte Carlo methods and show at hand of a simple example how these methods can be used to accelerate the plain Monte Carlo sampling approach. In the second part we provide a thourough introduction to Malliavin Calculus and derive some important calculation rules that will be necessary in the third chapter. Right there we will focus on portfolio optimization and and follow a recent journal article of Detemple, Garcia and Rindisbacher from there rather general market model to the optimal portfolio formula. Finally, in the last part we will implement this optimal portfolio by means of a simple model with explicit solution where we find that also their the Quasi-Monte Carlo approach dominates the Monte Carlo method in terms of efficiency and accuracy.
Monte Carlo Methods In Financial Engineering
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Author : Paul Glasserman
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-03-09
Monte Carlo Methods In Financial Engineering written by Paul Glasserman and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-03-09 with Mathematics categories.
Monte Carlo simulation has become an essential tool in the pricing of derivative securities and in risk management. These applications have, in turn, stimulated research into new Monte Carlo methods and renewed interest in some older techniques. 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. It divides roughly into three parts. 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. The next part describes techniques for improving simulation accuracy and efficiency. The final third of the book addresses special topics: estimating price sensitivities, valuing American options, and measuring market risk and credit risk in financial portfolios. The most important prerequisite is familiarity with the mathematical tools used to specify and analyze continuous-time models in finance, in particular the key ideas of stochastic calculus. Prior exposure to the basic principles of option pricing is useful but not essential. The book is aimed at graduate students in financial engineering, researchers in Monte Carlo simulation, and practitioners implementing models in industry. Mathematical Reviews, 2004: "... this book is very comprehensive, up-to-date and useful tool for those who are interested in implementing Monte Carlo methods in a financial context."
Monte Carlo Simulation And Finance
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Author : Don L. McLeish
language : en
Publisher: John Wiley & Sons
Release Date : 2011-09-13
Monte Carlo Simulation And Finance written by Don L. McLeish and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-09-13 with Business & Economics categories.
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. This state-of-the-art book on Monte Carlo simulation methods is ideal for finance professionals and students. Order your copy today.
Monte Carlo And Quasi Monte Carlo Methods 2002
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Author : Harald Niederreiter
language : en
Publisher: Springer Science & Business Media
Release Date : 2011-06-28
Monte Carlo And Quasi Monte Carlo Methods 2002 written by Harald Niederreiter and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-06-28 with Mathematics categories.
This book represents the refereed proceedings of the Fifth International Conference on Monte Carlo and Quasi-Monte Carlo Methods in Scientific Computing which was held at the National University of Singapore in the year 2002. An important feature are invited surveys of the state of the art in key areas such as multidimensional numerical integration, low-discrepancy point sets, computational complexity, finance, and other applications of Monte Carlo and quasi-Monte Carlo methods. These proceedings also include carefully selected contributed papers on all aspects of Monte Carlo and quasi-Monte Carlo methods. The reader will be informed about current research in this very active area.
Numerical Probability
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Author : Gilles Pagès
language : en
Publisher: Springer
Release Date : 2018-07-31
Numerical Probability written by Gilles Pagès and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-07-31 with Mathematics categories.
This textbook provides a self-contained introduction to numerical methods in probability with a focus on applications to finance. Topics covered include the Monte Carlo simulation (including simulation of random variables, variance reduction, quasi-Monte Carlo simulation, and more recent developments such as the multilevel paradigm), stochastic optimization and approximation, discretization schemes of stochastic differential equations, as well as optimal quantization methods. The author further presents detailed applications to numerical aspects of pricing and hedging of financial derivatives, risk measures (such as value-at-risk and conditional value-at-risk), implicitation of parameters, and calibration. Aimed at graduate students and advanced undergraduate students, this book contains useful examples and over 150 exercises, making it suitable for self-study.
Monte Carlo Methods And Models In Finance And Insurance
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Author : Ralf Korn
language : en
Publisher: CRC Press
Release Date : 2010-02-26
Monte Carlo Methods And Models In Finance And Insurance written by Ralf Korn and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-02-26 with Business & Economics categories.
Offering a unique balance between applications and calculations, Monte Carlo Methods and Models in Finance and Insurance incorporates the application background of finance and insurance with the theory and applications of Monte Carlo methods. It presents recent methods and algorithms, including the multilevel Monte Carlo method, the statistical Rom
Monte Carlo And Quasi Monte Carlo Methods 2012
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Author : Josef Dick
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-12-05
Monte Carlo And Quasi Monte Carlo Methods 2012 written by Josef Dick and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-12-05 with Mathematics categories.
This book represents the refereed proceedings of the Tenth International Conference on Monte Carlo and Quasi-Monte Carlo Methods in Scientific Computing that was held at the University of New South Wales (Australia) in February 2012. These biennial conferences are major events for Monte Carlo and the premiere event for quasi-Monte Carlo research. The proceedings include articles based on invited lectures as well as carefully selected contributed papers on all theoretical aspects and applications of Monte Carlo and quasi-Monte Carlo methods. The reader will be provided with information on latest developments in these very active areas. The book is an excellent reference for theoreticians and practitioners interested in solving high-dimensional computational problems arising, in particular, in finance, statistics and computer graphics.
Monte Carlo And Quasi Monte Carlo Methods 2000
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Author : Kai-Tai Fang
language : en
Publisher: Springer Science & Business Media
Release Date : 2011-06-28
Monte Carlo And Quasi Monte Carlo Methods 2000 written by Kai-Tai Fang and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-06-28 with Mathematics categories.
This book represents the refereed proceedings of the Fourth International Conference on Monte Carlo and Quasi-Monte Carlo Methods in Scientific Computing which was held at Hong Kong Baptist University in 2000. An important feature are invited surveys of the state-of-the-art in key areas such as multidimensional numerical integration, low-discrepancy point sets, random number generation, and applications of Monte Carlo and quasi-Monte Carlo methods. These proceedings include also carefully selected contributed papers on all aspects of Monte Carlo and quasi-Monte Carlo methods. The reader will be informed about current research in this very active field.
Advances In Modeling And Simulation
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Author : Zdravko Botev
language : en
Publisher: Springer Nature
Release Date : 2022-11-30
Advances In Modeling And Simulation written by Zdravko Botev and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-11-30 with Mathematics categories.
This book celebrates the career of Pierre L’Ecuyer on the occasion of his 70th birthday. Pierre has made significant contributions to the fields of simulation, modeling, and operations research over the last 40 years. This book contains 20 chapters written by collaborators and experts in the field who, by sharing their latest results, want to recognize the lasting impact of Pierre’s work in their research area. The breadth of the topics covered reflects the remarkable versatility of Pierre's contributions, from deep theoretical results to practical and industry-ready applications. The Festschrift features article from the domains of Monte Carlo and quasi-Monte Carlo methods, Markov chains, sampling and low discrepancy sequences, simulation, rare events, graphics, finance, machine learning, stochastic processes, and tractability.