An Empirical Study of Volatility Regimes in a Multifactor Equity Portfolio

Abstract

This paper presents an empirical analysis of a rules-based multifactor equity portfolio and examines how its performance varies across market volatility regimes. The portfolio is constructed from a fixed universe of 50 large-cap U.S. equities and employs a cross-sectional ranking methodology based on valuation, profitability, growth, and risk signals, with momentum used only as a secondary tie-breaker. The strategy is rebalanced monthly and is evaluated relative to the SPDR S&P 500 ETF (SPY) using both gross and net-of-transaction-cost returns. Market volatility regimes are identified using the CBOE Volatility Index (VIX). Low- and high-volatility regimes are defined as the bottom and top terciles of a rolling three-month (63 trading day average of daily VIX levels. Portfolio performance is summarized using annualized return, annualized volatility, Sharpe ratio, and information ratio versus SPY. Results indicate pronounced regime dependence: risk-adjusted and benchmark-relative performance is strongest in low-volatility regimes, while elevated-volatility regimes exhibit substantially higher return variability and weaker benchmark-relative outcomes. This analysis is intended as an empirical research note and a methodological prototype rather than a production trading framework.