Series: Wiley Finance
Hardcover: 576 pages
Publisher: Wiley; 1 edition (October 12, 2015)
Language: English
ISBN-10: 1119135516
ISBN-13: 978-1119135517
Product Dimensions: 7.5 x 1.8 x 10.3 inches
Shipping Weight: 2.6 pounds (View shipping rates and policies)
Average Customer Review: 5.0 out of 5 stars See all reviews (1 customer review)
Best Sellers Rank: #1,224,481 in Books (See Top 100 in Books) #103 in Books > Business & Money > Finance > Financial Risk Management #1666 in Books > Business & Money > Finance > Corporate Finance #8183 in Books > Textbooks > Business & Finance > Economics
This book covers a wide range of topics, including different risk sources and modern risk management approaches. As a graduate student majoring in applied mathematics with a focus of risk management, what I am looking for is a handbook that has clear mathematical expressions as well as good interpretations of how those risk issues arose. This book can serve both of my purposes.At the beginning of each chapter, the authors present a good background review by telling stories about what happened in the history. They incorporate their views which help you understand what caused the troubles in the past and why practitioners and regulators are paying more attention to some specific risk issues. This is one thing I eagerly want to know because I need to know if I have an appetite for that topic and should spend more time on it.Instead of showing lengthy documentations of the regulations, the authors use some simple examples that are easy to understand but still mathematically precise. With those examples, not only can I get a better view of the whole picture but also each single detail. If you also need a floating bar, like I do, trying to understand some regulations not written in a plain language, this book for sure will help you out there.In the case of mathematical modelling, one thing I definitely want to avoid is something mathematically correct but practically useless. This book provides good guidance on that. It answers questions like the followings. What is the convention in the industry? Why people prefer one model to another? What is the proper use case for a model? What kind of improvements can people still make?
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