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Author: Dessislava A. Pachamanova Publisher: John Wiley & Sons ISBN: 0470882123 Category : Business & Economics Languages : en Pages : 786
Book Description
An introduction to the theory and practice of financial simulation and optimization In recent years, there has been a notable increase in the use of simulation and optimization methods in the financial industry. Applications include portfolio allocation, risk management, pricing, and capital budgeting under uncertainty. This accessible guide provides an introduction to the simulation and optimization techniques most widely used in finance, while at the same time offering background on the financial concepts in these applications. In addition, it clarifies difficult concepts in traditional models of uncertainty in finance, and teaches you how to build models with software. It does this by reviewing current simulation and optimization methodology-along with available software-and proceeds with portfolio risk management, modeling of random processes, pricing of financial derivatives, and real options applications. Contains a unique combination of finance theory and rigorous mathematical modeling emphasizing a hands-on approach through implementation with software Highlights not only classical applications, but also more recent developments, such as pricing of mortgage-backed securities Includes models and code in both spreadsheet-based software (@RISK, Solver, Evolver, VBA) and mathematical modeling software (MATLAB) Filled with in-depth insights and practical advice, Simulation and Optimization Modeling in Finance offers essential guidance on some of the most important topics in financial management.
Author: Dessislava A. Pachamanova Publisher: John Wiley & Sons ISBN: 0470882123 Category : Business & Economics Languages : en Pages : 786
Book Description
An introduction to the theory and practice of financial simulation and optimization In recent years, there has been a notable increase in the use of simulation and optimization methods in the financial industry. Applications include portfolio allocation, risk management, pricing, and capital budgeting under uncertainty. This accessible guide provides an introduction to the simulation and optimization techniques most widely used in finance, while at the same time offering background on the financial concepts in these applications. In addition, it clarifies difficult concepts in traditional models of uncertainty in finance, and teaches you how to build models with software. It does this by reviewing current simulation and optimization methodology-along with available software-and proceeds with portfolio risk management, modeling of random processes, pricing of financial derivatives, and real options applications. Contains a unique combination of finance theory and rigorous mathematical modeling emphasizing a hands-on approach through implementation with software Highlights not only classical applications, but also more recent developments, such as pricing of mortgage-backed securities Includes models and code in both spreadsheet-based software (@RISK, Solver, Evolver, VBA) and mathematical modeling software (MATLAB) Filled with in-depth insights and practical advice, Simulation and Optimization Modeling in Finance offers essential guidance on some of the most important topics in financial management.
Author: Manfred Gilli Publisher: Academic Press ISBN: 0128150653 Category : Languages : en Pages : 638
Book Description
Computationally-intensive tools play an increasingly important role in financial decisions. Many financial problems-ranging from asset allocation to risk management and from option pricing to model calibration-can be efficiently handled using modern computational techniques. Numerical Methods and Optimization in Finance presents such computational techniques, with an emphasis on simulation and optimization, particularly so-called heuristics. This book treats quantitative analysis as an essentially computational discipline in which applications are put into software form and tested empirically. This revised edition includes two new chapters, a self-contained tutorial on implementing and using heuristics, and an explanation of software used for testing portfolio-selection models. Postgraduate students, researchers in programs on quantitative and computational finance, and practitioners in banks and other financial companies can benefit from this second edition of Numerical Methods and Optimization in Finance. Introduces numerical methods to readers with economics backgrounds Emphasizes core simulation and optimization problems Includes MATLAB and R code for all applications, with sample code in the text and freely available for download
Author: Bruce D. Craven Publisher: Springer Science & Business Media ISBN: 0387242805 Category : Business & Economics Languages : en Pages : 161
Book Description
Some recent developments in the mathematics of optimization, including the concepts of invexity and quasimax, have not yet been applied to models of economic growth, and to finance and investment. Their applications to these areas are shown in this book.
Author: Alexandrova-Kabadjova, Biliana Publisher: IGI Global ISBN: 1466620129 Category : Business & Economics Languages : en Pages : 378
Book Description
Simulation has become a tool difficult to substitute in many scientific areas like manufacturing, medicine, telecommunications, games, etc. Finance is one of such areas where simulation is a commonly used tool; for example, we can find Monte Carlo simulation in many financial applications like market risk analysis, portfolio optimization, credit risk related applications, etc. Simulation in Computational Finance and Economics: Tools and Emerging Applications presents a thorough collection of works, covering several rich and highly productive areas of research including Risk Management, Agent-Based Simulation, and Payment Methods and Systems, topics that have found new motivations after the strong recession experienced in the last few years. Despite the fact that simulation is widely accepted as a prominent tool, dealing with a simulation-based project requires specific management abilities of the researchers. Economic researchers will find an excellent reference to introduce them to the computational simulation models. The works presented in this book can be used as an inspiration for economic researchers interested in creating their own computational models in their respective fields.
Author: Michael C Fu Publisher: Springer ISBN: 1493913840 Category : Business & Economics Languages : en Pages : 387
Book Description
The Handbook of Simulation Optimization presents an overview of the state of the art of simulation optimization, providing a survey of the most well-established approaches for optimizing stochastic simulation models and a sampling of recent research advances in theory and methodology. Leading contributors cover such topics as discrete optimization via simulation, ranking and selection, efficient simulation budget allocation, random search methods, response surface methodology, stochastic gradient estimation, stochastic approximation, sample average approximation, stochastic constraints, variance reduction techniques, model-based stochastic search methods and Markov decision processes. This single volume should serve as a reference for those already in the field and as a means for those new to the field for understanding and applying the main approaches. The intended audience includes researchers, practitioners and graduate students in the business/engineering fields of operations research, management science, operations management and stochastic control, as well as in economics/finance and computer science.
Author: Denis Belomestny Publisher: Springer ISBN: 1137033517 Category : Business & Economics Languages : en Pages : 364
Book Description
This is an advanced guide to optimal stopping and control, focusing on advanced Monte Carlo simulation and its application to finance. Written for quantitative finance practitioners and researchers in academia, the book looks at the classical simulation based algorithms before introducing some of the new, cutting edge approaches under development.
Author: Hui Wang Publisher: CRC Press ISBN: 1439858241 Category : Business & Economics Languages : en Pages : 294
Book Description
Developed from the author’s course on Monte Carlo simulation at Brown University, Monte Carlo Simulation with Applications to Finance provides a self-contained introduction to Monte Carlo methods in financial engineering. It is suitable for advanced undergraduate and graduate students taking a one-semester course or for practitioners in the financial industry. The author first presents the necessary mathematical tools for simulation, arbitrary free option pricing, and the basic implementation of Monte Carlo schemes. He then describes variance reduction techniques, including control variates, stratification, conditioning, importance sampling, and cross-entropy. The text concludes with stochastic calculus and the simulation of diffusion processes. Only requiring some familiarity with probability and statistics, the book keeps much of the mathematics at an informal level and avoids technical measure-theoretic jargon to provide a practical understanding of the basics. It includes a large number of examples as well as MATLAB® coding exercises that are designed in a progressive manner so that no prior experience with MATLAB is needed.
Author: Patrick L. Anderson Publisher: CRC Press ISBN: 0203494652 Category : Mathematics Languages : en Pages : 499
Book Description
This book takes recent theoretical advances in Finance and Economics and shows how they can be implemented in the real world. It presents tactics for using mathematical and simulation models to solve complex tasks of forecasting income, valuing businesses, predicting retail sales, and evaluating markets and tax and regulatory problems. Busine
Author: Ciro D'Apice Publisher: SIAM ISBN: 0898717000 Category : Mathematics Languages : en Pages : 209
Book Description
This book offers a state-of-the-art introduction to the mathematical theory of supply chain networks, focusing on those described by partial differential equations. The authors discuss modeling of complex supply networks as well as their mathematical theory, explore modeling, simulation, and optimization of some of the discussed models, and present analytical and numerical results on optimization problems. Real-world examples are given to demonstrate the applicability of the presented approaches. Graduate students and researchers who are interested in the theory of supply chain networks described by partial differential equations will find this book useful. It can also be used in advanced graduate-level courses on modeling of physical phenomena as well as introductory courses on supply chain theory.
Author: Dessislava A. Pachamanova
Author: Dessislava A. Pachamanova
Author: Manfred Gilli
Author: Wayne L. Winston
Author: Bruce D. Craven
Author: Alexandrova-Kabadjova, Biliana
Author: Michael C Fu
Author: Denis Belomestny
Author: Hui Wang
Author: Patrick L. Anderson
Author: Ciro D'Apice