Stochastic Methods in Economics and Finance
Title | Stochastic Methods in Economics and Finance PDF eBook |
Author | A.G. Malliaris |
Publisher | North Holland |
Pages | 332 |
Release | 1982 |
Genre | Business & Economics |
ISBN |
Theory and application of a variety of mathematical techniques in economics are presented in this volume. Topics discussed include: martingale methods, stochastic processes, optimal stopping, the modeling of uncertainty using a Wiener process, Itô's Lemma as a tool of stochastic calculus, and basic facts about stochastic differential equations. The notion of stochastic ability and the methods of stochastic control are discussed, and their use in economic theory and finance is illustrated with numerous applications. The applications covered include: futures, pricing, job search, stochastic capital theory, stochastic economic growth, the rational expectations hypothesis, a stochastic macroeconomic model, competitive firm under price uncertainty, the Black-Scholes option pricing theory, optimum consumption and portfolio rules, demand for index bonds, term structure of interest rates, the market risk adjustment in project valuation, demand for cash balances and an asset pricing model.
Stochastic Methods in Economics and Finance
Title | Stochastic Methods in Economics and Finance PDF eBook |
Author | C.J. Bliss |
Publisher | |
Pages | 303 |
Release | 1984 |
Genre | |
ISBN |
Stochastic Modeling in Economics and Finance
Title | Stochastic Modeling in Economics and Finance PDF eBook |
Author | Jitka Dupacova |
Publisher | Springer Science & Business Media |
Pages | 394 |
Release | 2005-12-30 |
Genre | Mathematics |
ISBN | 0306481677 |
In Part I, the fundamentals of financial thinking and elementary mathematical methods of finance are presented. The method of presentation is simple enough to bridge the elements of financial arithmetic and complex models of financial math developed in the later parts. It covers characteristics of cash flows, yield curves, and valuation of securities. Part II is devoted to the allocation of funds and risk management: classics (Markowitz theory of portfolio), capital asset pricing model, arbitrage pricing theory, asset & liability management, value at risk. The method explanation takes into account the computational aspects. Part III explains modeling aspects of multistage stochastic programming on a relatively accessible level. It includes a survey of existing software, links to parametric, multiobjective and dynamic programming, and to probability and statistics. It focuses on scenario-based problems with the problems of scenario generation and output analysis discussed in detail and illustrated within a case study.
Mathematical Modeling in Economics and Finance: Probability, Stochastic Processes, and Differential Equations
Title | Mathematical Modeling in Economics and Finance: Probability, Stochastic Processes, and Differential Equations PDF eBook |
Author | Steven R. Dunbar |
Publisher | American Mathematical Soc. |
Pages | 232 |
Release | 2019-04-03 |
Genre | Economics |
ISBN | 1470448394 |
Mathematical Modeling in Economics and Finance is designed as a textbook for an upper-division course on modeling in the economic sciences. The emphasis throughout is on the modeling process including post-modeling analysis and criticism. It is a textbook on modeling that happens to focus on financial instruments for the management of economic risk. The book combines a study of mathematical modeling with exposure to the tools of probability theory, difference and differential equations, numerical simulation, data analysis, and mathematical analysis. Students taking a course from Mathematical Modeling in Economics and Finance will come to understand some basic stochastic processes and the solutions to stochastic differential equations. They will understand how to use those tools to model the management of financial risk. They will gain a deep appreciation for the modeling process and learn methods of testing and evaluation driven by data. The reader of this book will be successfully positioned for an entry-level position in the financial services industry or for beginning graduate study in finance, economics, or actuarial science. The exposition in Mathematical Modeling in Economics and Finance is crystal clear and very student-friendly. The many exercises are extremely well designed. Steven Dunbar is Professor Emeritus of Mathematics at the University of Nebraska and he has won both university-wide and MAA prizes for extraordinary teaching. Dunbar served as Director of the MAA's American Mathematics Competitions from 2004 until 2015. His ability to communicate mathematics is on full display in this approachable, innovative text.
Applications of Stochastic Optimal Control to Economics and Finance
Title | Applications of Stochastic Optimal Control to Economics and Finance PDF eBook |
Author | Salvatore Federico |
Publisher | |
Pages | 206 |
Release | 2020-06-23 |
Genre | |
ISBN | 9783039360581 |
In a world dominated by uncertainty, modeling and understanding the optimal behavior of agents is of the utmost importance. Many problems in economics, finance, and actuarial science naturally require decision makers to undertake choices in stochastic environments. Examples include optimal individual consumption and retirement choices, optimal management of portfolios and risk, hedging, optimal timing issues in pricing American options, and investment decisions. Stochastic control theory provides the methods and results to tackle all such problems. This book is a collection of the papers published in the Special Issue "Applications of Stochastic Optimal Control to Economics and Finance", which appeared in the open access journal Risks in 2019. It contains seven peer-reviewed papers dealing with stochastic control models motivated by important questions in economics and finance. Each model is rigorously mathematically funded and treated, and the numerical methods are employed to derive the optimal solution. The topics of the book's chapters range from optimal public debt management to optimal reinsurance, real options in energy markets, and optimal portfolio choice in partial and complete information settings. From a mathematical point of view, techniques and arguments of dynamic programming theory, filtering theory, optimal stopping, one-dimensional diffusions and multi-dimensional jump processes are used.
Stochastic Optimization Models in Finance
Title | Stochastic Optimization Models in Finance PDF eBook |
Author | William T. Ziemba |
Publisher | World Scientific |
Pages | 756 |
Release | 2006 |
Genre | Business & Economics |
ISBN | 981256800X |
A reprint of one of the classic volumes on portfolio theory and investment, this book has been used by the leading professors at universities such as Stanford, Berkeley, and Carnegie-Mellon. It contains five parts, each with a review of the literature and about 150 pages of computational and review exercises and further in-depth, challenging problems.Frequently referenced and highly usable, the material remains as fresh and relevant for a portfolio theory course as ever.
Stochastic Processes, Finance And Control: A Festschrift In Honor Of Robert J Elliott
Title | Stochastic Processes, Finance And Control: A Festschrift In Honor Of Robert J Elliott PDF eBook |
Author | Samuel N Cohen |
Publisher | World Scientific |
Pages | 605 |
Release | 2012-08-10 |
Genre | Mathematics |
ISBN | 9814483915 |
This book consists of a series of new, peer-reviewed papers in stochastic processes, analysis, filtering and control, with particular emphasis on mathematical finance, actuarial science and engineering. Paper contributors include colleagues, collaborators and former students of Robert Elliott, many of whom are world-leading experts and have made fundamental and significant contributions to these areas.This book provides new important insights and results by eminent researchers in the considered areas, which will be of interest to researchers and practitioners. The topics considered will be diverse in applications, and will provide contemporary approaches to the problems considered. The areas considered are rapidly evolving. This volume will contribute to their development, and present the current state-of-the-art stochastic processes, analysis, filtering and control.Contributing authors include: H Albrecher, T Bielecki, F Dufour, M Jeanblanc, I Karatzas, H-H Kuo, A Melnikov, E Platen, G Yin, Q Zhang, C Chiarella, W Fleming, D Madan, R Mamon, J Yan, V Krishnamurthy.