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.
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