About Our Pairs Trading Strategy

Overview

In today’s fast-changing financial markets, achieving consistent returns without taking on substantial directional risk is increasingly challenging. Our strategy harnesses statistical techniques to capture temporary mispricings between related stocks. By focusing on the intrinsic relationship between asset pairs, we seek to profit from short-term deviations that eventually revert to long-term equilibrium.

Our Approach

We begin by scanning a broad universe of equities and then narrowing our focus to pairs that exhibit strong historical relationships. Key steps include:

  • Correlation Screening: We select pairs with strong historical price correlation (typically over 0.7) based on daily data over one year.
  • Cointegration Validation: Statistical tests confirm that the selected price series maintain a long-term equilibrium relationship.
  • Dynamic Signal Generation: Our entry and exit signals are derived from the Z-score of the price spread, which adapts to market conditions with volatility adjustments via the VIX index.

Quantitative Methodology

Our method relies on straightforward yet robust quantitative techniques:

  • Log-Price Transformation: \[\text{Log Price}_i = \log(\text{Price}_i)\] This normalization allows us to manage multiplicative effects and volatility.

  • Spread and Z-Score Calculation: The spread is computed as the difference between the log-prices of the paired assets: \[\text{Spread} = \text{Log Price}_A - \text{Log Price}_B\] The Z-score, calculated over a rolling window (typically 20 days), quantifies the deviation of the current spread from its mean: \[Z\text{-score} = \frac{\text{Spread} - \text{Mean(Spread)}}{\text{Std(Spread)}}\]

  • Half-Life Estimation: To understand how quickly the spread returns to its mean, we estimate the half-life using an AR(1) model: \[\text{Half-life} = \frac{-\ln(2)}{\rho}\] where () is the coefficient from the regression of the spread’s change on its lagged value.

  • Volatility Adjustment: By incorporating the VIX index, we adjust our Z-score entry thresholds dynamically so that the strategy is more conservative in volatile markets.

Risk Controls

Risk management is integral to our strategy. Key measures include:

  • Dollar-Neutral Positions: Each trade is structured to maintain a near-neutral market exposure.
  • Stop-Loss Implementation: Positions are exited if adverse movements exceed 5% of the trade’s value.
  • Holding Period Limits: We impose a maximum holding time (typically based on 1.5 times the estimated half-life) to avoid extended exposure.
  • Diversification Across Pairs: Trading multiple, uncorrelated pairs helps mitigate the risk of any single pair underperforming.

Strategy Rationale

The rationale behind our strategy is that even highly correlated stocks can temporarily deviate from their equilibrium due to market inefficiencies, news events, or short-term supply/demand imbalances. By capturing these transient mispricings and applying strict risk controls, we aim to generate steady, low-risk returns independent of overall market direction.

Learn More

To delve deeper into the technical details, please visit our Indicators page where we explain our statistical filters and signal generation methods. For performance metrics and trade execution details, check out our Results page.