# Selecting stock pairs for pairs trading while incorporating lead-lag   relationship

**Authors:** Kartikay Gupta, Niladri Chatterjee

arXiv: 1906.05057 · 2020-06-24

## TL;DR

This paper introduces a new distance measure that incorporates lead-lag relationships to improve stock pairs selection for pairs trading, demonstrating enhanced profitability in experiments with Indian and American markets.

## Contribution

A novel distance measure that accounts for lead-lag effects and their variation over time, improving pairs trading strategies.

## Key findings

- Proposed measure outperforms existing methods in profit generation.
- Combining the new measure with SSD yields the best trading results.
- Experiments conducted on Indian and American stock datasets validate effectiveness.

## Abstract

Pairs Trading is carried out in the financial market to earn huge profits from known equilibrium relation between pairs of stock. In financial markets, seldom it is seen that stock pairs are correlated at particular lead or lag. This lead-lag relationship has been empirically studied in various financial markets. Earlier research works have suggested various measures for identifying the best pairs for pairs trading, but they do not consider this lead-lag effect. The present study proposes a new distance measure which incorporates the lead-lag relationship between the stocks while selecting the best pairs for pairs trading. Further, the lead-lag value between the stocks is allowed to vary continuously over time. The proposed measures importance has been show-cased through experimentation on two different datasets, one corresponding to Indian companies and another corresponding to American companies. When the proposed measure is clubbed with SSD measure, i.e., when pairs are identified through optimising both these measures, then the selected pairs consistently generate the best profit, as compared to all other measures. Finally, possible generalisation and extension of the proposed distance measure have been discussed.

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Source: https://tomesphere.com/paper/1906.05057