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Designing Efficient Pair-Trading Strategies Using Cointegration for the Indian Stock Market

arXiv 2211.07080 ↗First posted 14 Nov 2022q-fin.PM cs.LGcited by 4

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Abstract (arXiv)

A pair-trading strategy is an approach that utilizes the fluctuations between prices of a pair of stocks in a short-term time frame, while in the long-term the pair may exhibit a strong association and co-movement pattern. When the prices of the stocks exhibit significant divergence, the shares of the stock that gains in price are sold (a short strategy) while the shares of the other stock whose price falls are bought (a long strategy). This paper presents a cointegration-based approach that identifies stocks listed in the five sectors of the National Stock Exchange (NSE) of India for designing efficient pair-trading portfolios. Based on the stock prices from Jan 1, 2018, to Dec 31, 2020, the cointegrated stocks are identified and the pairs are formed. The pair-trading portfolios are evaluated on their annual returns for the year 2021. The results show that the pairs of stocks from the auto and the realty sectors, in general, yielded the highest returns among the five sectors studied in the work. However, two among the five pairs from the information technology (IT) sector are found to have yielded negative returns.

Key facts. Cited by 4 papers in the map (data through 7 Oct 2026). Builds on 4 of its 15 references that are in the map. First posted on arXiv 14 Nov 2022.

Builds on

4 of 15 references.

References · 4

  1. 2019A Robust Predictive Model for Stock Price Prediction Using Deep Learning and Natural Language Processingcited by 23
  2. 2020A Time Series Analysis-Based Stock Price Prediction Using Machine Learning and Deep Learning Modelscited by 18
  3. 2021Stock Portfolio Optimization Using a Deep Learning LSTM Modelcited by 9
  4. 2022Robust Portfolio Design and Stock Price Prediction Using an Optimized LSTM Modelcited by 6

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Citing papers per year: 2023: 3; 2024: 1.

4 papers.

  1. 2023A Comparative Analysis of Portfolio Optimization Using Mean-Variance, Hierarchical Risk Parity, and Reinforcement Learning Approaches on the Indian Stock Marketcited by 0
  2. 2023Portfolio Optimization: A Comparative Studycited by 0
  3. 2023Performance Evaluation of Equal-Weight Portfolio and Optimum Risk Portfolio on Indian Stockscited by 0
  4. 2024Exploring Sectoral Profitability in the Indian Stock Market Using Deep Learningcited by 0