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The asymmetric relationship between returns and implied volatility: Evidence from global stock markets
European University of Institute, Italy; IPAG Business Sch, France.
Tilburg University, Netherlands.
University of Manouba, Tunisia; University of Manouba, Tunisia.
Linköping University, Department of Management and Engineering, Economics. Linköping University, Faculty of Arts and Sciences.
2017 (English)In: Journal of Financial Stability, ISSN 1572-3089, E-ISSN 1878-0962, Vol. 30, 156-174 p.Article in journal (Refereed) Published
Abstract [en]

We investigate the asymmetric relationship between returns and implied volatility for 20 developed and emerging international markets. In particular we examine how the sign and size of return innovations affect the expectations of daily changes in volatility. Our empirical findings indicate that the conditional contemporaneous return-volatility relationship varies not only based on the sign of the expected returns but also upon their magnitude, according to recent results from the behavioral finance literature. We find evidence of an asymmetric and reverse return-volatility relationship in many advanced, Asian, LatinAmerican, European and South African markets. We show that the US market displays the highest reaction to price falls, Asian markets present the lowest sensitivity to volatility expectations, while the Euro area is characterized by a homogeneous response both in terms of direction and impact. These results may be safely attributed to cultural and societal characteristics. An extensive quantile regression analysis demonstrates that the detected asymmetric pattern varies particularly across the extreme distribution tails i.e., in the highest/lowest quantile ranges. Indeed, the classical feedback and leverage hypotheses appear not plausible, whilst behavioral theories emerge as the new paradigm in real-world applications. (C) 2017 Elsevier B.V. All rights reserved.

Place, publisher, year, edition, pages
Elsevier, 2017. Vol. 30, 156-174 p.
Keyword [en]
Implied volatility; Quantile regression; Behavioral bias; Predictability
National Category
Economics
Identifiers
URN: urn:nbn:se:liu:diva-141738DOI: 10.1016/j.jfs.2017.05.006ISI: 000410818200011Scopus ID: 2-s2.0-85019682471OAI: oai:DiVA.org:liu-141738DiVA: diva2:1147290
Note

Funding Agencies|EU Horizon research and innovation programme under the MS-C Grant [656136]; Jan Wallanders and the Tom Hedelius Foundation

Available from: 2017-10-05 Created: 2017-10-05 Last updated: 2017-10-10Bibliographically approved

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CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • oxford
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
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