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Handbook of Financial Risk Management: Simulations and Case Studies, by Ngai Hang Chan, Hoi Ying Wong
Free Ebook Handbook of Financial Risk Management: Simulations and Case Studies, by Ngai Hang Chan, Hoi Ying Wong
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An authoritative handbook on risk management techniques and simulations as applied to financial engineering topics, theories, and statistical methodologies
�
The Handbook of Financial Risk Management: Simulations and Case Studies illustrates the prac�tical implementation of simulation techniques in the banking and financial industries through the use of real-world applications.�
Striking a balance between theory and practice, the Handbook of Financial Risk Management: Simulations and Case Studies demonstrates how simulation algorithms can be used to solve practical problems and showcases how accuracy and efficiency in implementing various simulation methods are indispensable tools in risk management. The book provides the reader with an intuitive understanding of financial risk management and deepens insight into those financial products that cannot be priced traditionally. The Handbook of Financial Risk Management also features:
- Examples in each chapter derived from consulting projects, current research, and course instruction
- Topics such as volatility, fixed-income derivatives, LIBOR Market Models, and risk measures
- Over twenty-four recognized simulation models
- Commentary, data sets, and computer subroutines available on a chapter-by-chapter basis
As a complete reference for practitioners, the book is useful in the fields of finance, business, applied statistics, econometrics, and engineering. The Handbook of Financial Risk Management is also an excellent text or supplement for graduate and MBA-level students in courses on financial risk management and simulation.�
- Sales Rank: #1613454 in Books
- Published on: 2013-07-10
- Original language: English
- Number of items: 1
- Dimensions: 9.60" h x 1.10" w x 6.45" l, 1.55 pounds
- Binding: Hardcover
- 432 pages
From the Back Cover
An authoritative handbook on risk management techniques and simulations as applied to financial engineering topics, theories, and statistical methodologies
The Handbook of Financial Risk Management: Simulations and Case Studies illustrates the practical implementation of simulation techniques in the banking and financial industries through the use of real-world applications.
Striking a balance between theory and practice, the Handbook of Financial Risk Management: Simulations and Case Studies demonstrates how simulation algorithms can be used to solve practical problems and showcases how accuracy and efficiency in implementing various simulation methods are indispensable tools in risk management. The book provides the reader with an intuitive understanding of financial risk management and deepens insight into those financial products that cannot be priced traditionally. The Handbook of Financial Risk Management also features:
- Examples in each chapter derived from consulting projects, current research, and course instruction
- Topics such as volatility, fixed-income derivatives, LIBOR Market Models, and risk measures
- Over twenty-four recognized simulation models
- Commentary, data sets, and computer subroutines available on a chapter-by-chapter basis
As a complete reference for practitioners, the book is useful in the fields of finance, business, applied statistics, econometrics, and engineering. The Handbook of Financial Risk Management is also an excellent text or supplement for graduate and MBA-level students in courses on financial risk management and simulation.
About the Author
N. H. CHAN is Choh-Ming Li Chair Professor of Statistics at The Chinese University of Hong Kong and Associate Editor of six journals. Dr. Chan is also the author of Time Series: Applications to Finance with R and S-Plus, Second Edition, published by Wiley.
H. Y. WONG is Associate Professor in the Risk Management Science Program of the Department of Statistics at The Chinese University of Hong Kong. His areas of interest include data analysis, statistical computing, risk management, and stochastic calculus.
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