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@article{200138,
        author = {Pranjala G. Kolapwar and Jaishri M. Waghmar and Manisha S. Mahindrakar},
        title = {Dual Spread Confirmation Framework for Robust Pairs Trading},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {12},
        number = {12},
        pages = {970-975},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=200138},
        abstract = {Pairs trading is a widely adopted statistical arbitrage strategy that relies on the mean-reverting behavior of correlated asset pairs. However, traditional approaches based on a single spread—either static or dynamic—often suffer from noise, unstable signals, and excessive trading frequency. This paper proposes a Dual Spread Confirmation Framework (DSCF) that integrates both long-term (static) and short-term (dynamic) spread representations to enhance signal reliability. The proposed framework generates trading signals only when both spreads simultaneously indicate significant deviation, thereby filtering out spurious market movements. Empirical analysis on equity pairs demonstrates that the DSCF approach delivers improved risk-adjusted performance compared to conventional methods. Additionally, the proposed model effectively reduces maximum drawdown and trading frequency, indicating enhanced stability and robustness. The results highlight that incorporating a dual confirmation mechanism can mitigate noise in dynamic models while preserving adaptability. This study establishes DSCF as a simple yet effective enhancement to traditional pairs trading strategies, with strong potential for practical financial applications.},
        keywords = {Pairs Trading, Statistical Arbitrage, Dual Spread, Signal Confirmation, Rolling Regression, Risk Management},
        month = {May},
        }