A01=Alexander J. McNeil
A01=Paul Embrechts
A01=Rudiger Frey
Age Group_Uncategorized
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Author_Alexander J. McNeil
Author_Paul Embrechts
Author_Rudiger Frey
Autocorrelation
automatic-update
Autoregressive conditional heteroskedasticity
Autoregressive-moving-average model
Balance sheet
Calculation
Capital requirement
Cash flow
Category1=Non-Fiction
Category=KFF
Category=KJMV1
Coherent risk measure
Comonotonicity
Confidence interval
COP=United States
Correlation and dependence
Correlogram
Covariance matrix
Credit derivative
Credit rating
Credit risk
Credit spread (options)
Delivery_Delivery within 10-20 working days
Elliptical distribution
eq_bestseller
eq_business-finance-law
eq_isMigrated=2
eq_nobargain
eq_non-fiction
Estimation
Estimator
Extreme value theory
Fair value
Financial crisis
Financial institution
Geometric Brownian motion
Historical simulation (finance)
Inference
Insurance
Interest rate
Joint probability distribution
Language_English
Likelihood function
Likelihood-ratio test
Marginal distribution
Markov chain
Mathematical finance
Maxima and minima
Measurement
Mixture distribution
Mixture model
Monte Carlo method
Multivariate Model
Multivariate normal distribution
Normal distribution
Obligor
PA=Available
Parameter
Payment
Price_€50 to €100
Pricing
Principal component analysis
Probability
PS=Active
Quantile
Quantity
Rank correlation
Risk management
Risk-neutral measure
Securitization
Shortfall
softlaunch
Special case
Stochastic process
Stylized fact
Tail dependence
Theorem
Threshold model
Time series
Trading Book
Tranche
Valuation (finance)
Variance
Volatility clustering
Yield curve
Zero-coupon bond
Product details
- ISBN 9780691166278
- Weight: 1633g
- Dimensions: 178 x 254mm
- Publication Date: 26 May 2015
- Publisher: Princeton University Press
- Publication City/Country: US
- Product Form: Hardback
- Language: English
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This book provides the most comprehensive treatment of the theoretical concepts and modelling techniques of quantitative risk management. Whether you are a financial risk analyst, actuary, regulator or student of quantitative finance, Quantitative Risk Management gives you the practical tools you need to solve real-world problems. Describing the latest advances in the field, Quantitative Risk Management covers the methods for market, credit and operational risk modelling. It places standard industry approaches on a more formal footing and explores key concepts such as loss distributions, risk measures and risk aggregation and allocation principles. The book's methodology draws on diverse quantitative disciplines, from mathematical finance and statistics to econometrics and actuarial mathematics. A primary theme throughout is the need to satisfactorily address extreme outcomes and the dependence of key risk drivers. Proven in the classroom, the book also covers advanced topics like credit derivatives.
* Fully revised and expanded to reflect developments in the field since the financial crisis* Features shorter chapters to facilitate teaching and learning* Provides enhanced coverage of Solvency II and insurance risk management and extended treatment of credit risk, including counterparty credit risk and CDO pricing* Includes a new chapter on market risk and new material on risk measures and risk aggregation
Alexander J. McNeil is professor of actuarial mathematics and statistics at Heriot-Watt University in Edinburgh. Rudiger Frey is professor of mathematics and finance at the Vienna University of Economics and Business. Paul Embrechts is professor of mathematics at the Swiss Federal Institute of Technology in Zurich.
