A complete guide to the theory and practice of volatility models in
financial engineering
Volatility has become a hot topic in this era of instant
communications, spawning a great deal of research in empirical
finance and time series econometrics. Providing an overview of the
most recent advances, "Handbook of Volatility Models and Their
Applications" explores key concepts and topics essential for
modeling the volatility of financial time series, both univariate
and multivariate, parametric and non-parametric, high-frequency and
low-frequency.
Featuring contributions from international experts in the field,
the book features numerous examples and applications from
real-world projects and cutting-edge research, showing step by step
how to use various methods accurately and efficiently when
assessing volatility rates. Following a comprehensive introduction
to the topic, readers are provided with three distinct sections
that unify the statistical and practical aspects of volatility:
Autoregressive Conditional Heteroskedasticity and Stochastic
Volatility presents ARCH and stochastic volatility models, with a
focus on recent research topics including mean, volatility, and
skewness spillovers in equity markets
Other Models and Methods presents alternative approaches, such
as multiplicative error models, nonparametric and semi-parametric
models, and copula-based models of (co)volatilities
Realized Volatility explores issues of the measurement of
volatility by realized variances and covariances, guiding readers
on how to successfully model and forecast these measures
"Handbook of Volatility Models and Their Applications" is an
essential reference for academics and practitioners in finance,
business, and econometrics who work with volatility models in their
everyday work. The book also serves as a supplement for courses on
risk management and volatility at the upper-undergraduate and
graduate levels.
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