Business-Cycle-Conditioned Multi-Asset Portfolio Optimization: A Comparative Risk–Return Assessment of Sharpe, Sortino, and Omega Methods

Abstract

Heightened macroeconomic volatility and repeated shifts in growth, inflation, and interest-rate regimes have increased the importance of portfolio strategies that adapt asset allocation to changing business-cycle conditions while balancing return and risk. Previous research shows that asset-class performance varies across the business cycle and that risk-adjusted rankings depend on the selected measure, yet relatively limited evidence compares Sharpe-, Sortino-, and Omega-based optimization within one consistent multi-asset, phase-conditioned framework. This study assesses whether conditioning a tradable multi-asset portfolio on business-cycle phases improves its return–risk profile and identifies which of the three optimization methods performs most favorably during expansion, slowdown, recession, and recovery relative to equal-weighted and cycle-agnostic alternatives. The analysis covers 242 monthly observations from November 2004 to February 2025 for exchange-traded instruments representing United States equities, developed-market equities, investment-grade bonds, listed real estate, and gold, while the Organisation for Economic Co-operation and Development Composite Leading Indicator identifies 74 expansion, 62 slowdown, 54 recovery, and 52 recession months. Long-only portfolios were optimized separately for each phase in Microsoft Excel Solver by maximizing the Sharpe, Sortino, and Omega ratios and were assessed using mean monthly return, total standard deviation, target downside deviation, downside standard deviation, and correlation structure. During slowdown, Omega optimization generated the highest monthly return of 0.47% versus 0.26% for equal weighting, while Sharpe optimization produced the lowest total standard deviation of 1.62%; during recession, equal weighting returned −0.49% per month, whereas all optimized portfolios earned approximately 0.46%, and Omega reduced total standard deviation to 2.16%. Recovery produced the strongest performance, with Omega yielding 2.13% per month compared with 1.52% for equal weighting, whereas in expansion Sharpe optimization achieved the highest return of 1.64% compared with 1.19%, while Omega delivered the lowest target downside deviation of 0.99% and downside standard deviation of 0.42%. Over the full sample, Sortino optimization produced the highest cycle-agnostic return of 0.88% per month, while the phase-conditioned highest-return strategy yielded an arithmetic aggregate of 289.44% compared with 212.96%, a difference of 76.48 percentage points that should not be interpreted as compounded wealth performance. The findings indicate the potential relevance of business-cycle information for strategic asset allocation and portfolio risk management, while future research should test these phase-dependent patterns out of sample, incorporate transaction costs and turnover constraints, and compare alternative optimization approaches across broader asset classes.