Characteristic Portfolios, Conditional Quantile Curves, and the Cross-Section of Option Returns

51 Pages Posted: 11 Jun 2021 Last revised: 15 Nov 2021

See all articles by Simon Fritzsch

Simon Fritzsch

University of Leipzig - Faculty of Economics and Management Science

Felix Irresberger

Durham University

Gregor N. F. Weiss

University of Leipzig - Faculty of Economics and Management Science

Date Written: November 14, 2021

Abstract

Portfolio sorts and cross-sectional regressions are standard tools to test the pricing of asset characteristics. We propose the alternative use of non-parametric machine learning methods to estimate quantile curves of the characteristic of interest conditional on a set of controls. Building portfolios based on conditional quantile curves yields characteristic portfolios that should only reflect the priced risk associated with the characteristic and does not require any assumption on the functional form of the characteristic-return relation. We apply our procedure to the pricing of volatility risk in the cross-section of option returns. The Sharpe ratio of the resultant characteristic portfolios are up to 30% higher than those of comparable strategies.

Keywords: Option returns, implied volatility, machine learning, realized volatility, Volatility Risk Premium, volatility mispricing.

JEL Classification: G11,G13,C14,C58,C45

Suggested Citation

Fritzsch, Simon and Irresberger, Felix and Weiss, Gregor N. F., Characteristic Portfolios, Conditional Quantile Curves, and the Cross-Section of Option Returns (November 14, 2021). Available at SSRN: https://ssrn.com/abstract=3864131 or http://dx.doi.org/10.2139/ssrn.3864131

Simon Fritzsch

University of Leipzig - Faculty of Economics and Management Science ( email )

Leipzig, 04109
Germany

Felix Irresberger

Durham University ( email )

Old Elvet
Mill Hill Lane
Durham, Durham DH1 3HP
United Kingdom

Gregor N. F. Weiss (Contact Author)

University of Leipzig - Faculty of Economics and Management Science ( email )

Grimmaische Str. 12
Leipzig, 04109
Germany
+49 341 97 33821 (Phone)
+49 341 97 33829 (Fax)

HOME PAGE: http://www.wifa.uni-leipzig.de/nfdl

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