Publisher Summary The class of stochastic volatility (SV) models has its roots in both,
mathematical finance and financial econometrics. In fact, several variations of SV models …

This chapter reviews the evidence of predictability in US residential and commercial real
estate markets. First, we highlight the main methodologies used in the construction of real …

… Andreou and Ghysels (2002) extend this analysis to sampling returns intradaily, denoted r(i),t
for some intra-day frequency i = 1,...,m, and form data-driven estimates of daily volatility by …

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 …

… easy to introduce as demonstrated by Ghysels et al. (Citation2005… a variation of the
results in Ghysels et al. (Citation2005 … present a variation of the results in Ghysels et al. (Citation2005 …

Many time series are sampled at different frequencies. When we study co-movements between
such series we usually analyze the joint process sampled at a common low frequency. …

This paper evaluates the role of various volatility specifications, such as multiple stochastic
volatility (SV) factors and jump components, in appropriate modeling of equity return …

We revisit the relation between stock market volatility and macroeconomic activity using a
new class of component models that distinguish short-run from long-run movements. We …

We consider various mixed data sampling (MIDAS) regressions to predict volatility. The
regressions differ in the specification of regressors (squared returns, absolute returns, realized …

We use option prices to estimate ex ante higher moments of the underlying individual securities’
risk‐neutral returns distribution. We find that individual securities’ risk‐neutral volatility, …