Combining Pairs Trading with Black-Litterman Portfolio Optimization

Summary

The paper combines pairs trading with the Black-Litterman framework to construct mean-variance portfolios. Its motivation is that pairs trades may fail to return to equilibrium within the investment horizon, particularly during volatile or distressed markets. Incorporating the strategy into portfolio optimization is presented as a way to manage pair-based views within a broader portfolio construction process.

The abstract reports that the resulting portfolios outperformed the S&P 500 in both normal and extreme market conditions. It describes the approach as scalable and systematic, but the supplied text does not explain how pairs are selected, how Black-Litterman views and uncertainties are set, or how portfolio weights are constrained. It also provides no test period, transaction costs, risk measures, or methodology for defining extreme conditions, so the performance claim cannot be independently assessed from this summary alone.

Key ideas

• The approach integrates pairs trading into Black-Litterman portfolio optimization.
• The resulting portfolio is designed within a mean-variance framework.
• The motivation is that pairs may not revert before the investment horizon ends, especially in stressed markets.
• The abstract reports outperformance over the S&P 500 in normal and extreme conditions.
• The supplied text omits details needed to evaluate pair selection, portfolio construction, and test robustness.

Tags

# Application of Black-Litterman Bayesian in Statistical Arbitrage


# Application of Black-Litterman Bayesian in Statistical Arbitrage









\begin{abstract} In this paper, we integrated the statistical arbitrage strategy, pairs trading, into the Black-Litterman model and constructed efficient mean-variance portfolios. Typically, pairs trading underperforms under volatile or distressed market condition because the selected asset pairs fail to revert to equilibrium within the investment horizon. By enhancing this strategy with the Black-Litterman portfolio optimization, we achieved superior performance compared to the S\&P 500 market index under both normal and extreme market conditions. Furthermore, this research presents an innovative idea of incorporating traditional pairs trading strategies into the portfolio optimization framework in a scalable and systematic manner.

Shown in full with attribution under the source's licence. Licence: abstract CC0

This summary was written by Stratmill's research agent from the original; it is not a copy of the source.