ENGLISH

Essential Mathematics for Market Risk Management

By Simon Hubbert(auth.)

Book information

Year
2011
ISBN
9781119979524, 9781118467213
DOI
10.1002/9781118467213
Language
english
Format
PDF
Filesize
3 MB (3016588 bytes)
Pages
327\327
Orientation
yes
Scanned
yes
Time added
2013-08-01 04:00:00

Description

Everything you need to know in order to manage risk effectively within your organizationYou cannot afford to ignore the explosion in mathematical finance in your quest to remain competitive. This exciting branch of mathematics has very direct practical implications: when a new model is tested and implemented it can have an immediate impact on the financial environment. With risk management top of the agenda for many organizations, this book is essential reading for getting to grips with the mathematical story behind the subject of financial risk management. It will take you on a journey?from the early ideas of risk quantification up to today's sophisticated models and approaches to business risk management. To help you investigate the most up-to-date, pioneering developments in modern risk management, the book presents statistical theories and shows you how to put statistical tools into action to investigate areas such as the design of mathematical models for financial volatility or calculating the value at risk for an investment portfolio. Respected academic author Simon Hubbert is the youngest director of a financial engineering program in the U.K. He brings his industry experience to his practical approach to risk analysisCaptures the essential mathematical tools needed to explore many common risk management problemsWebsite with model simulations and source code enables you to put models of risk management into practicePlunges into the world of high-risk finance and examines the crucial relationship between the risk and the potential reward of holding a portfolio of risky financial assetsThis book is your one-stop-shop for effective risk management.Content: Chapter 1 Introduction (pages 1–9): Chapter 2 Applied Linear Algebra for Risk Managers (pages 11–25): Chapter 3 Probability Theory for Risk Managers (pages 27–41): Chapter 4 Optimization Tools (pages 43–61): Chapter 5 Portfolio Theory I (pages 63–75): Chapter 6 Portfolio Theory II (pages 77–89): Chapter 7 The Capital Asset Pricing Model (CAPM) (pages 91–99): Chapter 8 Risk Factor Modelling (pages 101–116): Chapter 9 The Value at Risk Concept (pages 117–129): Chapter 10 Value at Risk under a Normal Distribution (pages 131–135): Chapter 11 Advanced Probability Theory for Risk Managers (pages 137–149): Chapter 12 A Survey of Useful Distribution Functions (pages 151–167): Chapter 13 A Crash Course on Financial Derivatives (pages 169–184): Chapter 14 Non?linear Value at Risk (pages 185–195): Chapter 15 Time Series Analysis (pages 197–205): Chapter 16 Maximum Likelihood Estimation (pages 207–216): Chapter 17 The Delta Method for Statistical Estimates (pages 217–225): Chapter 18 Hypothesis Testing (pages 227–239): Chapter 19 Statistical Properties of Financial Losses (pages 241–254): Chapter 20 Modelling Volatility (pages 255–270): Chapter 21 Extreme Value Theory (pages 271–289): Chapter 22 Simulation Models (pages 291–307): Chapter 23 Alternative Approaches to VaR (pages 309–317): Chapter 24 Backtesting (pages 319–325):

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