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Empirische Analyse des Zusammenhangs zwischen Rendite und impliziter Volatilität am deutschen Aktienmarkt

Author

Listed:
  • Annika Mauer
  • Andreas Nastansky

    (Hochschule für Wirtschaft und Recht (HWR) Berlin)

Abstract

In diesem Beitrag wird empirisch untersucht, ob die zeitliche Entwicklung der Renditen des Deutschen Aktienindex (DAX) und die Zuwächse des Volatilitätsindex VDAX-NEW wechselseitig erklärt und vorhergesagt werden können. Der VDAX-NEW bildet dabei die von den Markteilnehmern erwartete Volatilität des Deutschen Aktienindex DAX ab. Die Ergebnisse zeigen, dass der im nationalen wie internationalen Kontext vielfach dokumentierte asymmetrische negative Zusammenhang zwischen den Renditen bzw. Änderungen der impliziten Volatilitätsindizes und den dazu korrespondierenden Aktienmarktindizes auch am deutschen Markt für den Zeitraum nach der globalen Finanzkrise nachgewiesen werden konnte, wobei der negative Zusammenhang im Falle negativer DAX-Renditen betragsmäßig stärker ausgeprägt ist als bei positiven DAX-Renditen. Hingegen verfügen die zeitverzögerten täglichen DAX-Renditen nur über einen geringen Mehrwert bei der Prognose des VDAX-NEW (und umgekehrt). Die empirischen Resultate sind robust hinsichtlich der Datenperiodizität und lassen sich mit Erkenntnissen aus der Kapitalmarkt- und Behavioral-Finance-Forschung erklären.

Suggested Citation

  • Annika Mauer & Andreas Nastansky, 2025. "Empirische Analyse des Zusammenhangs zwischen Rendite und impliziter Volatilität am deutschen Aktienmarkt," Statistische Diskussionsbeiträge 58, Universität Potsdam, Wirtschafts- und Sozialwissenschaftliche Fakultät.
    • Handle: RePEc:pot:statdp:58
    DOI: 10.25932/publishup-66946
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    References listed on IDEAS

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    More about this item

    Keywords

    implizite Volatilität; Leverage-Effekt; Rendite-Risiko; VDAX-NEW; Volatility-Feedback-Effekt;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)

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