Department of Economics and Business Economics

Decoupling the short- and long-term behavior of stochastic volatility

Research output: Working paperResearch

Standard

Decoupling the short- and long-term behavior of stochastic volatility. / Bennedsen, Mikkel; Lunde, Asger; Pakkanen, Mikko.

Aarhus : Institut for Økonomi, Århus Universitet, 2017.

Research output: Working paperResearch

Harvard

Bennedsen, M, Lunde, A & Pakkanen, M 2017 'Decoupling the short- and long-term behavior of stochastic volatility' Institut for Økonomi, Århus Universitet, Aarhus.

APA

Bennedsen, M., Lunde, A., & Pakkanen, M. (2017). Decoupling the short- and long-term behavior of stochastic volatility. Aarhus: Institut for Økonomi, Århus Universitet. CREATES Research Papers, No. 2017-26

CBE

Bennedsen M, Lunde A, Pakkanen M. 2017. Decoupling the short- and long-term behavior of stochastic volatility. Aarhus: Institut for Økonomi, Århus Universitet.

MLA

Bennedsen, Mikkel, Asger Lunde and Mikko Pakkanen Decoupling the short- and long-term behavior of stochastic volatility. Aarhus: Institut for Økonomi, Århus Universitet. (CREATES Research Papers; Journal number 2017-26). 2017., 46 p.

Vancouver

Bennedsen M, Lunde A, Pakkanen M. Decoupling the short- and long-term behavior of stochastic volatility. Aarhus: Institut for Økonomi, Århus Universitet. 2017 Aug 14.

Author

Bennedsen, Mikkel ; Lunde, Asger ; Pakkanen, Mikko. / Decoupling the short- and long-term behavior of stochastic volatility. Aarhus : Institut for Økonomi, Århus Universitet, 2017. (CREATES Research Papers; No. 2017-26).

Bibtex

@techreport{66d5f1873eb9462494ddc32720798081,
title = "Decoupling the short- and long-term behavior of stochastic volatility",
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.",
keywords = "Stochastic volatility, high-frequency data, rough volatility, persistence, long memory, forecasting, Brownian semistationary process",
author = "Mikkel Bennedsen and Asger Lunde and Mikko Pakkanen",
year = "2017",
month = "8",
day = "14",
language = "English",
publisher = "Institut for {\O}konomi, {\AA}rhus Universitet",
type = "WorkingPaper",
institution = "Institut for {\O}konomi, {\AA}rhus Universitet",

}

RIS

TY - UNPB

T1 - Decoupling the short- and long-term behavior of stochastic volatility

AU - Bennedsen, Mikkel

AU - Lunde, Asger

AU - Pakkanen, Mikko

PY - 2017/8/14

Y1 - 2017/8/14

N2 - 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.

AB - 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.

KW - Stochastic volatility, high-frequency data, rough volatility, persistence, long memory, forecasting, Brownian semistationary process

M3 - Working paper

BT - Decoupling the short- and long-term behavior of stochastic volatility

PB - Institut for Økonomi, Århus Universitet

CY - Aarhus

ER -