Model-Driven Statistical Arbitrage on LETF Option Markets

Quantitative Finance, Vol. 19, No. 11, 2019, 1817–1837

41 Pages Posted: 17 Nov 2020

See all articles by Sergey Nasekin

Sergey Nasekin

Humboldt University of Berlin - Center for Applied Statistics and Economics (CASE)

Wolfgang Karl Härdle

Blockchain Research Center Humboldt-Universität zu Berlin; Charles University; National Yang Ming Chiao Tung University; Asian Competitiveness Institute

Date Written: 2019

Abstract

In this paper, we study the statistical properties of the moneyness scaling transformation by Leung and Sircar (2015). This transformation adjusts the moneyness coordinate of the implied volatility smile in an attempt to remove the discrepancy between the IV smiles for levered and unlevered ETF options. We construct bootstrap uniform confidence bands which indicate that the implied volatility smiles are statistically different after moneyness scaling has been performed. An empirical application shows that there are trading opportunities possible on the LETF market. A statistical arbitrage type strategy based on a dynamic semi-parametric factor model is presented. This strategy presents a statistical decision algorithm which generates trade recommendations based on comparison of model and observed LETF implied volatility surface. It is shown to generate positive returns with a high probability. Extensive econometric analysis of LETF implied volatility process is performed including out-of-sample forecasting based on a semi-parametric factor model and uniform confidence bands’ study. It provides new insights into the latent dynamics of the implied volatility surface. We also incorporate Heston stochastic volatility into the moneyness scaling method for better tractability of the model.

Keywords: exchange-traded funds, options, implied volatilities, moneyness scaling, bootstrap, dynamic factor models, trading strategies

JEL Classification: C00, C14, C50

Suggested Citation

Nasekin, Sergey and Härdle, Wolfgang Karl, Model-Driven Statistical Arbitrage on LETF Option Markets (2019). Quantitative Finance, Vol. 19, No. 11, 2019, 1817–1837, Available at SSRN: https://ssrn.com/abstract=3702188 or http://dx.doi.org/10.2139/ssrn.3702188

Sergey Nasekin (Contact Author)

Humboldt University of Berlin - Center for Applied Statistics and Economics (CASE) ( email )

Spandauer Strasse 1
Berlin, D-10178
Germany

Wolfgang Karl Härdle

Blockchain Research Center Humboldt-Universität zu Berlin ( email )

Unter den Linden 6
Berlin, D-10099
Germany

Charles University ( email )

Celetná 13
Dept Math Physics
Praha 1, 116 36
Czech Republic

National Yang Ming Chiao Tung University ( email )

No. 1001, Daxue Rd. East Dist.
Hsinchu City 300093
Taiwan

Asian Competitiveness Institute ( email )

Singapore

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