Leveraged ETFs with Market Closure and Frictions

50 Pages Posted: 7 Jun 2021

See all articles by Min Dai

Min Dai

The Hong Kong Polytechnic University; National University of Singapore

Steven Kou

Boston University

H. Mete Soner

Princeton University - Department of Operations Research & Financial Engineering (ORFE)

Chen Yang

The Chinese University of Hong Kong (CUHK) - Department of Systems Engineering and Engineering Management

Date Written: May 30, 2021

Abstract

Although leveraged ETFs are popular products for retail investors, how to hedge them poses a great challenge to financial institutions. We develop an optimal rebalancing (hedging) model for leveraged ETFs in a comprehensive setting, including overnight market closure and market frictions. The model allows for an analytical optimal rebalancing strategy. The result extends the principle of “aiming in front of target” introduced by Garleanu and Pedersen (2013) from a constant weight between current and future positions to a time-varying weight, because the rebalancing performance is monitored only at discrete time points but the rebalancing takes place continuously. Empirical findings and implications for the weekend effect, return deviations during multi-day periods, and the intraday trading volume are also presented.

Keywords: daily rebalancing, leveraged ETFs, market closure, frictions

Suggested Citation

Dai, Min and Kou, Steven and Soner, H. Mete and Yang, Chen, Leveraged ETFs with Market Closure and Frictions (May 30, 2021). Available at SSRN: https://ssrn.com/abstract=3856573 or http://dx.doi.org/10.2139/ssrn.3856573

Min Dai

The Hong Kong Polytechnic University ( email )

National University of Singapore ( email )

Singapore

Steven Kou

Boston University ( email )

595 Commonwealth Avenue
Boston, MA 02215
United States
6173583318 (Phone)

H. Mete Soner

Princeton University - Department of Operations Research & Financial Engineering (ORFE) ( email )

Sherrerd Hall, Charlton Street
Princeton, NJ 08544
United States

Chen Yang (Contact Author)

The Chinese University of Hong Kong (CUHK) - Department of Systems Engineering and Engineering Management ( email )

Hong Kong
China

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