Stochastic Methods in Economics and Finance - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Stochastic Methods in Economics and Finance write by A.G. Malliaris. This book was released on 1982. Stochastic Methods in Economics and Finance available in PDF, EPUB and Kindle. 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
Stochastic Methods in Economics and Finance - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Stochastic Methods in Economics and Finance write by C.J. Bliss. This book was released on 1984. Stochastic Methods in Economics and Finance available in PDF, EPUB and Kindle.
Stochastic Modeling in Economics and Finance
Stochastic Modeling in Economics and Finance - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Stochastic Modeling in Economics and Finance write by Jitka Dupacova. This book was released on 2005-12-30. Stochastic Modeling in Economics and Finance available in PDF, EPUB and Kindle. 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
Mathematical Modeling in Economics and Finance: Probability, Stochastic Processes, and Differential Equations - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Mathematical Modeling in Economics and Finance: Probability, Stochastic Processes, and Differential Equations write by Steven R. Dunbar. This book was released on 2019-04-03. Mathematical Modeling in Economics and Finance: Probability, Stochastic Processes, and Differential Equations available in PDF, EPUB and Kindle. 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
Applications of Stochastic Optimal Control to Economics and Finance - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Applications of Stochastic Optimal Control to Economics and Finance write by Salvatore Federico. This book was released on 2020-06-23. Applications of Stochastic Optimal Control to Economics and Finance available in PDF, EPUB and Kindle. 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.
