Asymptotic analyses for trend-stationary pairs trading strategy in high-frequency trading

Conventional pairs trading strategies (PTS) exploit the mean-reverting nature of stock pairs with stationary value processes. This paper elevates PTS by integrating trend-stationary value processes, thereby enhancing profitability and expanding trading opportunities. Our asymptotic analysis reveals that the value process, adjusted for the derived slant asymptote, adheres to a stationary distribution. By capitalizing on price deviations and value trends, the strategy profits by longing undervalued or shorting overvalued processes based on their respective upward or downward slopes. Positions are strategically closed when they revert to the asymptote, thus securing profits and avoiding counterproductive trades against prevailing trends. In this context, conventional stationary-based PTS can be considered a specific instance of our broader approach when the asymptote is non-trended. To refine trade selection, we evaluate the mean-reversion velocity, monitoring the frequency at which the portfolio's value crosses the slant asymptote to exclude high-risk pairs. Empirical evidence underscores our method's superiority over conventional stationary PTS, delivering higher average returns per trade, improved Sharpe ratios, and increased trading opportunities, even amidst the financial uncertainties of the COVID era.