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European Equity Pairs Trading

Last Updated on 10 February, 2024 by Rejaul Karim

In their exploration of European equity pairs trading, Michael E. Lucey and Don P. Walshe unravel the intricacies influenced by data frequency on risk and return dynamics. Published in 2012, the research scrutinizes daily, weekly, and monthly European share price data from 1998 to 2007.

Utilizing a straightforward trading rule based on volatility between normalized historical prices for paired stocks, the authors unveil annualized raw returns of up to 15%, with a pronounced impact observed at the weekly data frequency. Bootstrap analysis underscores the strategy’s skill-driven nature rather than mere luck, while insignificant beta coefficients underscore its market-neutral essence.

Notably, the strategy’s resilience to reversal factors distinguishes pairs trading from conventional mean reversion strategies, marking a paradigm shift in the understanding of equity pairs trading dynamics.

Abstract Of Paper

This article examines an equity pairs trading strategy using daily, weekly and monthly European share price data over the period 1998–2007. The authors shows that when stocks are matched into pairs with minimum distance between normalised historical prices, a simple trading rule based on volatility between these prices yields annualised raw returns of up to 15% for the weekly data frequency. Bootstrap results suggest returns from the strategy are attributable to skill rather than luck, while insignificant beta coefficients provide evidence that this is a market neutral strategy. Resistance of the strategy’s returns to reversal factors suggest pairs trading is fundamentally different to previously documented reversal strategies based on concepts such as mean reversion.

Original paper – Download PDF

Here you can download the PDF and original paper of European Equity Pairs Trading: The Effect of Data Frequency on Risk and Return.

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Author

Michael E. Lucey
Durham Business School

Don P. Walshe
University College Cork

Conclusion

In conclusion, our exploration of European equity pairs trading across varying data frequencies presents a nuanced perspective on risk and return dynamics.

Utilizing daily, weekly, and monthly share price data from 1998 to 2007, we reveal that a straightforward trading rule based on volatility between normalized historical prices can yield substantial annualized raw returns, reaching up to 15% for the weekly frequency. Bootstrap results fortify the notion that these returns stem from skill rather than chance, emphasizing the strategy’s robustness. Notably, insignificant beta coefficients underscore the market-neutral nature of this approach.

The strategy’s resilience to reversal factors further distinguishes pairs trading, highlighting its distinctive characteristics in comparison to previously documented strategies.

Related Reading:

Is Daily Pairs Trading of ETF-Stocks Profitable?

The Profitability of Pairs Trading Strategies: Distance, Cointegration, and Copula Methods

FAQ

– What are the key findings regarding returns in the European equity pairs trading strategy?

The study demonstrates that a straightforward trading rule based on volatility between normalized historical prices for paired stocks yields annualized raw returns of up to 15%, particularly at the weekly data frequency. The findings suggest that this pairs trading strategy exhibits resilience and skill-driven performance, showcasing its effectiveness in the European equity landscape during the period 1998–2007.

– How does the strategy’s market-neutral essence contribute to its success?

The pairs trading strategy, as revealed in the research, is inherently market-neutral, as indicated by insignificant beta coefficients. This emphasizes that the strategy’s success is not dependent on overall market movements but rather on the skillful implementation of the trading rule. The market-neutral essence contributes to the strategy’s robustness and distinguishes it from other approaches.

– What sets European equity pairs trading apart from conventional mean reversion strategies?

The research highlights a paradigm shift in understanding equity pairs trading dynamics, particularly in comparison to conventional mean reversion strategies. The strategy’s resilience to reversal factors sets it apart, showcasing fundamental differences from previously documented strategies relying on concepts such as mean reversion. This distinction marks European equity pairs trading as a unique and effective approach in the financial landscape.

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