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With Simulation and Optimization in Finance and itscompanion Web site, authors Dessislava Pachamanova and FrankFabozzi explain the application of these tools for both financialprofessionals and academics in this field.
Divided into five comprehensive parts, this reliable guideprovides an accessible introduction to the simulation andoptimization techniques most widely used in finance, while offeringfundamental background information on the financial conceptssurrounding these techniques.
In addition, the authors use simulation and optimization as ameans to clarify difficult concepts in traditional risk models infinance, and explain how to build financial models with certainsoftware. They review current simulation and optimizationmethodologies—along with the available software—andproceed with portfolio risk management, modeling of randomprocesses, pricing of financial derivatives, and capital budgetingapplications.
Designed for practitioners and students, this book:
Contains a unique combination of finance theory and rigorousmathematical modeling emphasizing a hands-on approach throughimplementation with software
Highlights both classical applications and more recentdevelopments such as pricing of mortgage-backed securities
Includes models and code in both spreadsheet-based software(@RISK, Solver, and VBA) and mathematical modeling software(MATLAB)
Incorporates a companion Web site containing ancillarymaterials, including the models and code used in the book,appendices with introductions to the software, and practicesections
And much more
Filled with in-depth insights and practical advice,Simulation and Optimization in Finance offers essentialguidance on some of the most important topics in financialmanagement.
This practical guide is divided into five informative parts:
Part I, Fundamental Concepts, provides insights on the mostimportant issues in finance, simulation, optimization, andoptimization under uncertainty
Part II, Portfolio Optimization and Risk Measures, reviews thetheory and practice of equity and fixed income portfoliomanagement, from classical frameworks to recent advances in thetheory of risk measurement
Part III, Asset Pricing Models, discusses classical static anddynamic models for asset pricing, such as factor models anddifferent types of random walks
Part IV, Derivative Pricing and Use, introduces important typesof financial derivatives, shows how their value can be determinedby simulation, and discusses how derivatives can be employed forportfolio risk management and return enhancement purposes
Part V, Capital Budgeting Decisions, reviews capital budgetingdecision models, including real options, and discusses applicationsof simulation and optimization in capital budgeting underuncertainty
Supplemented with models and code in both spreadsheet-basedsoftware (@RISK, Solver, and VBA) and mathematical modelingsoftware (MATLAB), Simulation and Optimization in Finance is awell-rounded guide to a dynamic discipline.