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

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Title: Decoupling the short- and long-term behavior of stochastic volatility
Authors: Bennedsen, M
Lunde, A
Pakkanen, MS
Item Type: Journal Article
Abstract: We introduce a new class of continuous-time models of the stochastic volatility of asset prices. The models can simultaneously incorporate roughness and slowly decaying autocorrelations, including proper long memory, which are two stylized facts often found in volatility data. 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. Applying the models to realized volatility measures covering a vast panel of assets, we find evidence consistent with the hypothesis that time series of realized measures of volatility are both rough and very persistent. Lastly, we illustrate the utility of the models in 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.
Issue Date: 30-Jan-2021
Date of Acceptance: 3-Dec-2020
URI: http://hdl.handle.net/10044/1/85479
DOI: 10.1093/jjfinec/nbaa049
ISSN: 1479-8409
Publisher: Oxford University Press (OUP)
Journal / Book Title: Journal of Financial Econometrics
Copyright Statement: © The Author(s) 2021. Published by Oxford University Press. All rights reserved. For permissions, please email: journals.permissions@oup.com. This is a pre-copy-editing, author-produced version of an article accepted for publication in Journal of Financial Econometrics following peer review. The definitive publisher-authenticated version is available online at: https://academic.oup.com/jfec/advance-article/doi/10.1093/jjfinec/nbaa049/6124197
Sponsor/Funder: Academy of Finland
Funder's Grant Number: 258042
Keywords: Social Sciences
Business, Finance
Economics
Business & Economics
Brownian semistationary process
forecasting
high-frequency data
long memory
persistence
rough volatility
stochastic volatility
REALIZED VOLATILITY
FRACTAL DIMENSION
SPOT VOLATILITY
MEMORY
PRICES
MODELS
q-fin.ST
q-fin.ST
q-fin.MF
60G10, 60G15, 60G17, 60G22, 62M09, 62M10, 91G70
Econometrics
1403 Econometrics
1502 Banking, Finance and Investment
Publication Status: Published online
Embargo Date: 2023-01-29
Online Publication Date: 2021-01-30
Appears in Collections:Financial Mathematics
Mathematics
Faculty of Natural Sciences