Realized stochastic volatility with leverage and long memory

Seminar Series in Management Science and Quantitative Economics

We develop a discrete-time stochastic volatility option pricing model, which exploits the information contained in high-frequency data. The Realized Volatility (RV) is used as a proxy of the unobservable log-returns volatility. We model its dynamics by a simple but effective (pseudo) long-memory process, the Leverage Heterogeneous Auto-Regressive Gamma (HARGL) process. Both the discrete-time sp...

Ten Things We Should Know About Time Series

Time series data affect many aspects of our lives. This paper highlights ten things we should all know about time series, namely: a good working knowledge of econometrics and statistics, an awareness of measurement errors, testing for zero frequency, seasonal and periodic unit roots, analysing fractionally integrated and long memory processes, estimating VARFIMA models, using and interpreting c...

Estimating the Leverage Parameter of Continuous-time Stochastic Volatility Models Using High Frequency S&P 500 and VIX*

* The authors are most grateful to two referees for helpful comments and suggestions. Abstract This paper proposes a new method for estimating continuous-time stochastic volatility (SV) models for the S&P 500 stock index process using intraday high-frequency observations of both the S&P 500 index and the Chicago Board of Exchange (CBOE) implied (or expected) volatility index (VIX). Intraday hig...

Common Non-linearities in Multiple Series of Stock Market Volatility Common Non-linearities in Multiple Series of Stock Market Volatility *

Decreases in stock market returns often lead to higher increases in volatility than increases in returns of the same magnitude, and it is common to incorporate these so-called leverage effects in GARCH and stochastic volatility models. Recent research has also found it useful to account for leverage in models of realized volatility, as well as in models of the continuous and jump components of ...

A note on the properties of power-transformed returns in long-memory stochastic volatility models with leverage effect