# Mean-Reverting Portfolio Design with Budget Constraint

## TL;DR

This paper introduces a novel approach for designing mean-reverting portfolios under budget constraints, optimizing mean-reversion strength and outperforming traditional methods in profit generation.

## Contribution

It formulates a general mean-reverting portfolio design problem with budget constraints and proposes efficient algorithms for its solution.

## Key findings

- Proposed methods outperform traditional portfolio design techniques.
- Numerical results show consistent profits on synthetic and market data.
- The approach effectively balances mean-reversion strength and variance.

## Abstract

This paper considers the mean-reverting portfolio design problem arising from statistical arbitrage in the financial markets. We first propose a general problem formulation aimed at finding a portfolio of underlying component assets by optimizing a mean-reversion criterion characterizing the mean-reversion strength, taking into consideration the variance of the portfolio and an investment budget constraint. Then several specific problems are considered based on the general formulation, and efficient algorithms are proposed. Numerical results on both synthetic and market data show that our proposed mean-reverting portfolio design methods can generate consistent profits and outperform the traditional design methods and the benchmark methods in the literature.