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Stochastic Spread Pairs Trading in Indian Commodities

Article arXiv papers · Author: Dhruv Mahajan et al.
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Summary

This study tests a pairs strategy on spot prices for 17 Indian commodities across energy, metals, and agriculture from 2010 through 2018. It uses Johansen cointegration tests on the training sample to select long-run related commodity pairs, then models each selected pair’s logarithmic spread with a single-factor stochastic approach.

The model parameters are estimated with differential evolution, while trading-rule parameters are tuned by backtesting on the training period and carried into the later test period. Twelve pairs were selected from 136 candidates, and the reported test-period Sharpe ratios exceeded 1.4 for all selected pairs. The findings are limited by the stated assumption that training-period cointegration persists into the test period; the document does not describe transaction costs or other implementation frictions.

Key ideas

  • Johansen cointegration tests identify candidate pairs among commodity spot prices.
  • The strategy models cointegrated pairs through their logarithmic spreads.
  • Differential evolution estimates the stochastic model parameters.
  • Trading rules are optimized on training data and applied to a later test period.
  • All selected pairs are reported to have test-period Sharpe ratios above 1.4.

Tags

CommoditiesPairs tradingMean reversionBacktestingStatistics
Full text
# Stochastic Spread Pairs Trading in the Indian Commodity Market


# Stochastic Spread Pairs Trading in the Indian Commodity Market









In this study, we applied a stochastic spread pairs trading strategy on the Indian commodity market. The complete set of commodities were taken whose spot price was available for the period of January 1st 2010 to December 31st 2018 including energy, metals and the agricultural commodity sector. Spot data was taken from the MCX pooled spot prices for 17 commodities. The data was split into training period (January 1st 2010 to 14th March 2017) and testing period(15th Match 2017 to 31st December 2018). The splitting was done using a 80:20 split.Johanssen Cointegration tests were done on training data for pairs of commodities to check for long-run relationship and the cointegrated commodities were selected for formation of the trading process. We found a total of 12 cointegrated pairs out of 136 possible pairs. Cointegration was assumed for the testing period. A single-factor stochastic trading approach was applied on the logarithmic spread of the cointegrated pairs for both the training and testing period.The parameters of stochastic spread model were estimated using differential evolution algorithm. Also parameters for the trading rule were optimized by backtesting on the training period and assumed for the testing period. The results show a sharpe ratio of above 1.4 for all the commodity cointegrated pairs in the backtesing period.

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This summary was written by Stratmill's research agent from the original; it is not a copy of the source.