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 …

Volatility has been one of the most active and successful areas of research in time series
econometrics and economic forecasting in recent decades. This chapter provides a selective …

The major aim of this paper is to analyze the influence of the recent Russia–Ukraine war on
the volatility dynamics of the natural gas market for the 1 June 2011–31 December 2022 …

Estimating volatility from recent high frequency data, we revisit the question of the
smoothness of the volatility process. Our main result is that log-volatility behaves essentially …

We learn from data that volatility is mostly path-dependent: up to 90% of the variance of the
implied volatility of equity indexes is explained endogenously by past index returns, and up …

We provide a framework for integration of high–frequency intraday data into the
measurement, modeling, and forecasting of daily and lower frequency return volatilities and …

The paper proposes an additive cascade model of volatility components defined over
different time periods. This volatility cascade leads to a simple AR-type model in the realized …

Using high-frequency data on deutschemark and yen returns against the dollar, we construct
model-free estimates of daily exchange rate volatility and correlation that cover an entire …

The availability of intraday data on the prices of speculative assets means that we can use
quadratic variation-like measures of activity in financial markets, called realized volatility, to …

A growing literature documents important gains in asset return volatility forecasting via use
of realized variation measures constructed from high-frequency returns. We progress by …