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Abstract
Long-term investors tilt their portfolios given their views on the evolving investment landscape. In the literature, portfolio tilting is often implemented with methodologies that use investors’ views on point estimates of conditional assets’ expected returns. These conditional return expectations are notoriously difficult to estimate, and using them often results in unstable portfolio weights when existing methodologies are applied. The authors avoid such shortcomings by providing a methodology that incorporates views on the likelihood of economic regimes (e.g., growth and inflation surprises) instead. Using data on equities, bonds, and commodities, the authors show—both in simulation and empirically—that this approach generates stable portfolio weights and outperformance that is minimally affected by forecast errors.
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