Although volatility clustering has a long history as a salient empirical regularity
characterizing high-frequency speculative prices, it was not until recently that applied …

Diffusion models for volatility have been used to price options while ARCH models
predominate in descriptive studies of asset volatility. This paper compares a discrete‐time …

We study the properties of the quasi-maximum likelihood estimator (QMLE) and related test
statistics in dynamic models that jointly parameterize conditional means and conditional …

ARCH models often impute a lot of persistence to stock volatility and yet give relatively poor
forecasts. One explanation is that extremely large shocks, such as the October 1987 crash …

We study the correlation of monthly excess returns for seven major countries over the period
1960-90. We find that the international covariance and correlation matrices are unstable …

We explore mixed data sampling (henceforth MIDAS) regression models. The regressions
involve time series data sampled at different frequencies. Volatility and related processes …

A new class of fractionally integrated GARCH and EGARCH models for characterizing
financial market volatility is discussed. Monte Carlo simulations illustrate the reliability of …

This paper takes a new look at the predictability of stock market returns with risk measures.
We find a significant positive relation between average stock variance (largely idiosyncratic) …

This paper studies the intertemporal relation between the conditional mean and the
conditional variance of the aggregate stock market return. We introduce a new estimator that …

Six different commodities are examined using daily data over two futures contract periods.
Cash and futures prices for all six commodities are found to be well described as …