Analysis reveals strong performance of pairs trading strategies using Renko and Kagi charts, suggesting effective statistical arbitrage potential.
This paper investigates the profitability and robustness of pairs trading strategies based on non-parametric technical chart constructions—Renko and Kagi—across the U.S. and Chinese equity markets. Within a market-neutral, mean-reversion framework, the study examines strategy performance under varying market regimes, including the Global Financial Crisis (GFC) and the COVID-19 period. Using historical data from indices such as the S&P 500 and the CSI series, pairs are selected via statistical patterns in Renko and Kagi charts. Robustness checks consider varying trading horizons, the number of pairs, and transaction costs. Results show that both chart based strategies generate significant excess returns and exhibit strong Sharpe ratios before costs. While trading frictions reduce profitability, Renko-based strategies remain resilient, especially during crises. The findings highlight that adaptive and non-parametric charting methods can effectively capture transient mispricings and provide viable alternatives for statistical arbitrage in turbulent markets.
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Yufei Sun (2025) studied this question.
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