AN EMPIRICAL ASSESSMENT OF PAIRS TRADING USING ENSEMBLE Q-LEARNING
Pairs trading and statistical arbitrage in equities, studied by Rayaprolu in 2026 with reinforcement learning. The abstract mentions a Sharpe ratio, alpha, excess returns, an out-of-sample test and transaction costs but not a benchmark, multiple testing or the size of the universe.
“Results demonstrate that the ensemble Q-learning agent delivered an average six-month portfolio return of 105.2% with a Sharpe ratio of 2.08, substantially outperforming both traditional pairs trading benchmarks and major global indices.”
AssetEquitiesindices
StrategyPairs tradingshort-term reversal
TechniqueReinforcement learningBayesian
GeographyGlobalIndia
Also stated: Intraday, Sharpe ratio, Alpha, Excess return, out-of-sample test, costs
Missing from abstract: benchmark, multiple testing, universe
Institutional-grade audit of this strategy.
£5 — Request the audit- Audit of the paper claims accounting for costs, luck, crises, originality, geography, etc.
- Reproduction code integratable into Bloomberg, IBKR, etc.
- Bias-free datasets for backtesting included
- Delivered in 2 working days
The paper's neighbourhoodPairs trading and statistical arbitrage by year
FamilyPairs trading and statistical arbitrage93Momentum and trend following289Factor investing240Machine learning return prediction15318 more · 909
AssetEquities51
The family is counted across the whole universe. Asset, method and authors are counted inside the family.
| Similar papers | citation | same method | same asset | same authors | |
|---|---|---|---|---|---|
| Robust Currency Cointegration using Bayesian Optimization by Lo et al. | 2026 | ||||
| A Regime-Aware, Free-Boundary Framework for Statistical Arbitrage: Kalman-Filtered Synthetic Baskets, EGARCH Volatility, Markov Regime Detection, and Optimal Stopping via Hamilton-Jacobi-Bellman by Bektas | 2026 | ||||
| A Regime-Aware Hybrid Pairs Trading System with Sentiment-Driven Intelligence by Kolapwar et al. | 2026 | ||||
| Signature-Based Optimal Execution for Statistical Arbitrage with Path-Dependent Trading Signals by Morbelli et al. | 2026 | ||||
| Attention Factors for Statistical Arbitrage by Epstein et al. | 2025 |