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Volatility and Time Series EconometricsEssays in Honor of Robert Engle$
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Tim Bollerslev, Jeffrey Russell, and Mark Watson

Print publication date: 2010

Print ISBN-13: 9780199549498

Published to Oxford Scholarship Online: May 2010

DOI: 10.1093/acprof:oso/9780199549498.001.0001

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PRINTED FROM OXFORD SCHOLARSHIP ONLINE (oxford.universitypressscholarship.com). (c) Copyright Oxford University Press, 2021. All Rights Reserved. An individual user may print out a PDF of a single chapter of a monograph in OSO for personal use. date: 23 September 2021

Measuring Downside Risk – Realized Semivariance *

Measuring Downside Risk – Realized Semivariance *

Chapter:
(p.117) 7 Measuring Downside Risk – Realized Semivariance*
Source:
Volatility and Time Series Econometrics
Author(s):

Ole E. Barndorff‐Nielsen

Silja Kinnebrock

Neil Shephard (Contributor Webpage)

Publisher:
Oxford University Press
DOI:10.1093/acprof:oso/9780199549498.003.0007

A number of economists have wanted to measure downside risk, the risk of prices falling, just using information based on negative returns. This has been operationalized by quantities such as semivariance, value at risk and expected shortfall, which are typically estimated using daily returns. This chapter introduces a new measure of the variation of asset prices based on high frequency data, called realized semivariance (RS). Its limiting properties are derived, relating it to quadratic variation and, in particular, negative jumps. It is shown that it has some useful properties in empirical work, enriching the standard ARCH models pioneered by Rob Engle over the last 25 years and building on the recent econometric literature on realized volatility.

Keywords:   realized semivariance, ARCH models, downside risk, asset prices, volatility

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