Decoupling the Short- and Long-Term Behavior of Stochastic Volatility
- 2 October 2016
- preprint
- Published by Elsevier BV in SSRN Electronic Journal
Abstract
We study the empirical properties of realized volatility of the E-mini S&P 500 futures contract at various time scales, ranging from a few minutes to one day. Our main finding is that intraday volatility is remarkably rough and persistent. What is more, by further studying daily realized volatility measures of close to two thousand individual US equities, we find that both roughness and persistence appear to be universal properties of volatility. Inspired by the empirical findings, we introduce a new class of continuous-time stochastic volatility models, capable of decoupling roughness (short-term behavior) from long memory and persistence (long-term behavior) in a simple and parsimonious way, which allows us to successfully model volatility at all intraday time scales. Our prime model is based on the so-called Brownian semistationary process and we derive a number of theoretical properties of this process, relevant to volatility modeling. As an illustration of the usefulness our new models, we conduct an extensive forecasting study; we find that the models proposed in this paper outperform a wide array of benchmarks considerably, indicating that it pays off to exploit both roughness and persistence in volatility forecasting.Other Versions
This publication has 43 references indexed in Scilit:
- Intraday Trading Invariance in the E-Mini S&P 500 Futures MarketSSRN Electronic Journal, 2015
- On the short-time behavior of the implied volatility for jump-diffusion models with stochastic volatilityFinance and Stochastics, 2007
- Modeling and Forecasting Realized VolatilityEconometrica, 2003
- The Distribution of Realized Exchange Rate VolatilityJournal of the American Statistical Association, 2001
- The Distribution of Stock Return VolatilityPublished by National Bureau of Economic Research ,2000
- Intraday and interday volatility in the Japanese stock marketJournal of International Financial Markets, Institutions and Money, 2000
- Forecasting financial market volatility: Sample frequency vis-à-vis forecast horizonJournal of Empirical Finance, 1999
- Intraday periodicity and volatility persistence in financial marketsJournal of Empirical Finance, 1997
- Normal Inverse Gaussian Distributions and Stochastic Volatility ModellingScandinavian Journal of Statistics, 1997
- DM-Dollar Volatility: Intraday Activity Patterns, Macroeconomic Announcements, and Longer Run DependenciesPublished by National Bureau of Economic Research ,1996