A multi-factor market-neutral investment strategy for New York Stock Exchange equities

ArXiv ID: 2412.12350 “View on arXiv”

Authors: Unknown

Abstract

This report presents a systematic market-neutral, multi-factor investment strategy for New York Stock Exchange equities with the objective of delivering steady returns while minimizing correlation with the market. A robust feature set is integrated combining momentum-based indicators, fundamental factors, and analyst recommendations. Using various statistical tests for feature selection, the strategy identifies key drivers of equity performance and ranks stocks to build a balanced portfolio of long and short positions. Portfolio construction methods, including equally weighted, risk parity, and minimum variance beta-neutral approaches, were evaluated through rigorous backtesting. Risk parity demonstrated superior performance with a higher Sharpe ratio, lower beta, and smaller maximum drawdown compared to the Standard and Poor’s 500 index. Risk parity’s market neutrality, combined with its ability to maintain steady returns and mitigate large drawdowns, makes it a suitable approach for managing significant capital in equity markets.

Keywords: Market-Neutral Strategy, Multi-Factor Model, Risk Parity, Equity Portfolio, Beta-Neutral

Complexity vs Empirical Score

  • Math Complexity: 6.0/10
  • Empirical Rigor: 8.5/10
  • Quadrant: Holy Grail
  • Why: The paper applies advanced statistical methods (Lasso regression, multivariate regression) and mathematical formulations for feature engineering (e.g., trended momentum via linear regression), but is heavily grounded in real-world implementation with detailed data sourcing, Point-in-Time constraints, and rigorous multi-period backtesting.
  flowchart TD
    A["Research Goal:<br>Create a market-neutral, multi-factor<br>NYE equity strategy"] --> B["Input: Feature Set<br>Momentum, Fundamental, Analyst"]
    B --> C["Computational Process:<br>Statistical Feature Selection"]
    C --> D["Computational Process:<br>Portfolio Construction & Backtesting<br>Equally Weighted, Risk Parity, Min Variance"]
    D --> E["Key Outcome:<br>Risk Parity Outperforms<br>Higher Sharpe, Lower Beta, Low Drawdown"]