Abstract

Pairs trading that is built on ’Relative-Value Arbitrage Rule’ is a popular short-term speculation strategy enabling traders to make profits from temporary mispricing of close substitutes. This paper aims at investigating the profit potentials of pairs trading in a new finance area – on cryptocurrencies market. The empirical design builds upon four well-known approaches to implement pairs trading, namely: correlation analysis, distance approach, stochastic return differential approach, and cointegration analysis, that use monthly closing prices of leading cryptocoins over the period January 1, 2018, – December 31, 2019. Additionally, the paper executes a simulation exercise that compares long-short strategy with long-only portfolio strategy in terms of payoffs and risks. The study finds an inverse relationship between the correlation coefficient and distance between different pairs of cryptocurrencies, which is a prerequisite to determine the potentially market-neutral profits through pairs trading. In addition, pairs trading simulations produce quite substantive evidence on the continuing profitability of pairs trading. In other words, long-short portfolio strategies, producing positive cumulative returns in most subsample periods, consistently outperform conservative long-only portfolio strategies in the cryptocurrency market. The profitability of pairs trading thus adds empirical challenge to the market efficiency of the cryptocurrency market. However, other aspects like spectral correlations and implied volatility might also be significant in determining the profit potentials of pairs trading.

Highlights

  • Contemporary valuation models often characterize portfolio optimizations as a function of price correlations in asset markets (Fabozzi et al, 2013)

  • The results reveal that cointegration coefficient, as a proxy to the optimal allocation ratio for pairs trading in crypto markets is significant in producing profits with fewer amounts of risks

  • The simulation exercise compares the payoffs and risks of the statistical arbitrage technique of pairs trading with the long-only portfolio strategy in cryptocoins markets

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Summary

Introduction

Contemporary valuation models often characterize portfolio optimizations as a function of price correlations in asset markets (Fabozzi et al, 2013). Modern portfolio theory tracing back to Markowitz (1952) suggests that investors can potentially maximize returns while even minimizing risks through selecting complementary assets with low price correlations. Financial assets like stocks show very close correlations during significant volatility, and their relations appear to be low under normal market conditions (Cao et al, 2013).

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