Anticipating Correlations
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€74.99
A01=Robert Engle
Accuracy and precision
Author_Robert Engle
Autocorrelation
Autoregressive conditional heteroskedasticity
Basis Point
Bayesian
Bias of an estimator
Capital asset pricing model
Category=GPQD
Category=KJMV1
Conditional variance
Copula (probability theory)
Correlation and dependence
Covariance matrix
Credit risk
Cross product
Data set
Default Rate
Determinant
Dividend
Dummy variable (statistics)
Economics
eq_bestseller
eq_business-finance-law
eq_isMigrated=1
eq_isMigrated=2
eq_nobargain
eq_non-fiction
Equity Market
Estimation
Estimator
Expected value
Exponential smoothing
Extreme value theory
Factor analysis
Fat-tailed distribution
Forecasting
Hedge fund
High-yield debt
Implied volatility
Inference
Interest rate
Joint probability distribution
Least squares
Likelihood function
Likelihood-ratio test
Long run and short run
Marginal distribution
Market capitalization
Maximum likelihood estimation
Mean absolute error
Monotonic function
Moving-average model
Multivariate Model
Multivariate normal distribution
Normal distribution
Ordinary least squares
Parameter
Pearson product-moment correlation coefficient
Portfolio optimization
Probability
Probability of default
Quantile
Random variable
Risk management
Risk premium
Skewness
Standard deviation
Stationary distribution
Stochastic volatility
T-statistic
Tail dependence
Time series
Tranche
Unit root
Valuation (finance)
Variable (mathematics)
Variance
Weighted arithmetic mean
Product details
- ISBN 9780691116419
- Weight: 397g
- Dimensions: 152 x 235mm
- Publication Date: 08 Feb 2009
- Publisher: Princeton University Press
- Publication City/Country: US
- Product Form: Hardback
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Financial markets respond to information virtually instantaneously. Each new piece of information influences the prices of assets and their correlations with each other, and as the system rapidly changes, so too do correlation forecasts. This fast-evolving environment presents econometricians with the challenge of forecasting dynamic correlations, which are essential inputs to risk measurement, portfolio allocation, derivative pricing, and many other critical financial activities. In Anticipating Correlations, Nobel Prize-winning economist Robert Engle introduces an important new method for estimating correlations for large systems of assets: Dynamic Conditional Correlation (DCC). Engle demonstrates the role of correlations in financial decision making, and addresses the economic underpinnings and theoretical properties of correlations and their relation to other measures of dependence. He compares DCC with other correlation estimators such as historical correlation, exponential smoothing, and multivariate GARCH, and he presents a range of important applications of DCC. Engle presents the asymmetric model and illustrates it using a multicountry equity and bond return model.
He introduces the new FACTOR DCC model that blends factor models with the DCC to produce a model with the best features of both, and illustrates it using an array of U.S. large-cap equities. Engle shows how overinvestment in collateralized debt obligations, or CDOs, lies at the heart of the subprime mortgage crisis--and how the correlation models in this book could have foreseen the risks. A technical chapter of econometric results also is included. Based on the Econometric and Tinbergen Institutes Lectures, Anticipating Correlations puts powerful new forecasting tools into the hands of researchers, financial analysts, risk managers, derivative quants, and graduate students.
Robert Engle is the Michael Armellino Professor in the Management of Financial Services at New York University's Leonard N. Stern School of Business. His books include "Cointegration, Causality, and Forecasting". He was awarded the 2003 Nobel Prize in economics.
