Pair trading: Clustering based on principal component analysis

• Author(s): Cardoso, Rafael Govin
• Date: 2015
• Persistent ID: http://hdl.handle.net/10362/15355
• Origin: Repositório Institucional da UNL
• Subject(s): Pair trading; Clustering; Principal component analysis; Emerging markets
• Document Type: Master thesis
• Language: English
• Advisor(s): Lameira, Pedro
• Contributor(s): RUN

Description

This study focuses on the implementation of several pair trading strategies across three emerging markets, with the objective of comparing the results obtained from the different strategies and assessing if pair trading benefits from a more volatile environment. The results show that, indeed, there are higher potential profits arising from emerging markets. However, the higher excess return will be partially offset by higher transaction costs, which will be a determinant factor to the profitability of pair trading strategies. Also, a new clustering approach based on the Principal Component Analysis was tested as an alternative to the more standard clustering by Industry Groups. The new clustering approach delivers promising results, consistently reducing volatility to a greater extent than the Industry Group approach, with no significant harm to the excess returns.

UNL - NSBE