Arbeitspapier

Asymmetric connectedness of stocks: How does bad and good volatility spill over the U.S. stock market?

Asymmetries in volatility spillovers are highly relevant to risk valuation and portfolio diversification strategies in financial markets. Yet, the large literature studying information transmission mechanisms ignores the fact that bad and good volatility may spill over at different magnitudes. This paper fills this gap with two contributions. One, we suggest how to quantify asymmetries in volatility spillovers due to bad and good volatility. Two, using high frequency data covering most liquid U.S. stocks in seven sectors, we provide ample evidence of the asymmetric connectedness of stocks. We universally reject the hypothesis of symmetric connectedness at the disaggregate level but in contrast, we document the symmetric transmission of information in an aggregated portfolio. We show that bad and good volatility is transmitted at different magnitudes in different sectors, and the asymmetries sizably change over time. While negative spillovers are often of substantial magnitudes, they do not strictly dominate positive spillovers. We find that the overall intra-market connectedness of U.S. stocks increased substantially with the increased uncertainty of stock market participants during the financial crisis.

Language
Englisch

Bibliographic citation
Series: FinMaP-Working Paper ; No. 13

Classification
Wirtschaft
Methodological Issues: General
Financial Econometrics
International Financial Markets
Subject
volatility
spillovers
semivariance
asymmetric effects
financial markets

Event
Geistige Schöpfung
(who)
Barunik, Jozef
Kočenda, Evžen
Vácha, Lukáš
Event
Veröffentlichung
(who)
Kiel University, FinMaP - Financial Distortions and Macroeconomic Performance
(where)
Kiel
(when)
2014

Handle
Last update
10.03.2025, 11:42 AM CET

Data provider

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ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. If you have any questions about the object, please contact the data provider.

Object type

  • Arbeitspapier

Associated

  • Barunik, Jozef
  • Kočenda, Evžen
  • Vácha, Lukáš
  • Kiel University, FinMaP - Financial Distortions and Macroeconomic Performance

Time of origin

  • 2014

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