Asynchronous ADRs: Overnight vs Intraday Returns and Trading Strategies

Studies in Economics & Finance, vol 34, issue 4, pp.580-596, 2017

23 Pages Posted: 25 Oct 2016 Last revised: 12 Nov 2019

See all articles by Tim Leung

Tim Leung

University of Washington - Department of Applied Math

Jamie Kang

Stanford University; Columbia University

Date Written: October 23, 2016

Abstract

American Depositary Receipts (ADRs) are exchange-traded certificates that represent shares of non-U.S. company securities. They are major financial instruments for investing in foreign companies. Focusing on Asian ADRs in the context of asynchronous markets, we present methodologies and results of empirical analysis of their returns. In particular, we dissect their returns into intraday and overnight components with respect to the U.S. market hours. The return difference between the S&P500 index, traded through the SPDR S&P500 ETF (SPY), and each ADR is found to be a mean-reverting time series, and is fitted to an Ornstein-Uhlenbeck process via maximum-likelihood estimation (MLE). Our empirical observations also lead us to develop and backtest pairs trading strategies to exploit the mean-reverting ADR-SPY spreads. We find consistent positive payouts when long position in ADR and short position in SPY are simultaneously executed at selected entry and exit levels.

Keywords: American Depositary Receipts, Pairs Trading, Ornstein-Uhlenbeck process

JEL Classification: C10, G11, G15

Suggested Citation

Leung, Tim and Kang, Jamie, Asynchronous ADRs: Overnight vs Intraday Returns and Trading Strategies (October 23, 2016). Studies in Economics & Finance, vol 34, issue 4, pp.580-596, 2017, Available at SSRN: https://ssrn.com/abstract=2858048

Tim Leung

University of Washington - Department of Applied Math ( email )

Lewis Hall 217
Department of Applied Math
Seattle, WA 98195
United States

HOME PAGE: http://faculty.washington.edu/timleung/

Jamie Kang (Contact Author)

Stanford University ( email )

Stanford, CA 94305
United States

Columbia University ( email )

3022 Broadway
New York, NY 10027
United States

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