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. Engaging and accessible, this book and its companion Web site provide an introduction to the simulation and optimization techniques most widely used in finance, while, at the same time, offering essential information on the financial concepts surrounding these applications. This practical guide is divided into five informative parts: * Part I, Fundamental Concepts, provides insights on the most important issues in finance, simulation, optimization, and optimization under uncertainty * Part II, Portfolio Optimization and Risk Measures, reviews the theory and practice of equity and fixed income portfolio management, from classical frameworks to recent advances in the theory of risk measurement * Part III, Asset Pricing Models, discusses classical static and dynamic models for asset pricing, such as factor models and different types of random walks * Part IV, Derivative Pricing and Use, introduces important types of financial derivatives, shows how their value can be determined by simulation, and discusses how derivatives can be employed for portfolio risk management and return enhancement purposes * Part V, Capital Budgeting Decisions, reviews capital budgeting decision models, including real options, and discusses applications of simulation and optimization in capital budgeting under uncertainty Supplemented with models and code in both spreadsheet-based software (@RISK, Solver, and VBA) and mathematical modeling software (MATLAB), Simulation and Optimization in Finance is a well-rounded guide to a dynamic discipline.