Artikel

Option-implied information: What’s the vol surface got to do with it?

We find that option-implied information such as forward-looking variance, skewness and the variance risk premium are sensitive to the way the volatility surface is constructed. For some state-of-the-art volatility surfaces, the differences are economically surprisingly large and lead to systematic biases, especially for out-of-the-money put options. Estimates for risk-neutral variance differ across volatility surfaces by more than 10% on average, leading to variance risk premium estimates that differ by 60% on average. The variations are even larger for risk-neutral skewness. To overcome this problem, we propose a volatility surface that is built with a one-dimensional kernel regression. We assess its statistical accuracy relative to existing state-of-the-art parametric, semi- and non-parametric volatility surfaces by means of leave-one-out cross-validation, including the volatility surface of OptionMetrics. Based on 14 years of end-of-day and intraday S&P 500 and Euro Stoxx 50 option data we conclude that the proposed one-dimensional kernel regression represents option market information more accurately than existing approaches of the literature.

Sprache
Englisch

Erschienen in
Journal: Review of Derivatives Research ; ISSN: 1573-7144 ; Volume: 23 ; Year: 2020 ; Issue: 3 ; Pages: 323-355 ; New York, NY: Springer US

Klassifikation
Wirtschaft
Contingent Pricing; Futures Pricing; option pricing
Financial Forecasting and Simulation
Semiparametric and Nonparametric Methods: General
Thema
Option-implied
Risk-neutral variance
Risk-neutral density
Tail risk
Option standardization
Interpolation

Ereignis
Geistige Schöpfung
(wer)
Ulrich, Maxim
Walther, Simon
Ereignis
Veröffentlichung
(wer)
Springer US
(wo)
New York, NY
(wann)
2020

DOI
doi:10.1007/s11147-020-09166-0
Letzte Aktualisierung
10.03.2025, 11:45 MEZ

Datenpartner

Dieses Objekt wird bereitgestellt von:
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.

Objekttyp

  • Artikel

Beteiligte

  • Ulrich, Maxim
  • Walther, Simon
  • Springer US

Entstanden

  • 2020

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