Risk Management and Simulation
Product details
- ISBN 9780367379889
- Weight: 816g
- Dimensions: 156 x 234mm
- Publication Date: 23 Sep 2019
- Publisher: Taylor & Francis Ltd
- Publication City/Country: GB
- Product Form: Paperback
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The challenges of the current financial environment have revealed the need for a new generation of professionals who combine training in traditional finance disciplines with an understanding of sophisticated quantitative and analytical tools. Risk Management and Simulation shows how simulation modeling and analysis can help you solve risk management problems related to market, credit, operational, business, and strategic risk. Simulation models and methodologies offer an effective way to address many of these problems and are easy for finance professionals to understand and use. Drawing on the author’s extensive teaching experience, this accessible book walks you through the concepts, models, and computational techniques.
How Simulation Models Can Help You Manage Risk More Effectively
Organized into four parts, the book begins with the concepts and framework for risk management. It then introduces the modeling and computational techniques for solving risk management problems, from model development, verification, and validation to designing simulation experiments and conducting appropriate output analysis. The third part of the book delves into specific issues of risk management in a range of risk types. These include market risk, equity risk, interest rate risk, commodity risk, currency risk, credit risk, liquidity risk, and strategic, business, and operational risks. The author also examines insurance as a mechanism for risk management and risk transfer. The final part of the book explores advanced concepts and techniques. The book contains extensive review questions and detailed quantitative or computational exercises in all chapters. Use of MATLAB® mathematical software is encouraged and suggestions for MATLAB functions are provided throughout.
Learn Step by Step, from Basic Concepts to More Complex Models
Packed with applied examples and exercises,
Aparna Gupta is an associate professor of quantitative finance, director of the Financial Engineering and Risk Analytics Program, and co-director of the Center for Financial Studies in the Lally School of Management at Rensselaer Polytechnic Institute. She is also an associate professor of industrial and systems engineering in the School of Engineering. Her research interest is in addressing issues in risk management at the individual and the institutional levels. She conducts US National Science Foundation funded research in financial innovation for risk management. Dr. Gupta earned her doctorate from Stanford University and her B.Sc. and M.Sc. degrees in Mathematics from the Indian Institute of Technology, Kanpur.
