A conditional factor model for real estate investment trusts returns

Abstract We find that a small set of latent systematic factors identified using the Instrumented Principal Component Analysis model explains a substantial share of the cross‐section of US real estate investment trust (REIT) returns. These factors deliver markedly smaller pricing errors than standard REIT and equity factor models, both in‐sample and out‐of‐sample. We also find that REIT characteristics—size, leverage, dividend yield, momentum, and property‐type indicators—are the primary determinants of factor exposures. Evidence from correlation analysis suggests that the latent factors reflect aggregate risk, financing conditions, liquidity/visibility, sector rotation between property types, and a time‐varying dividend‐income premium. Together, these findings point to a unified and economically interpretable factor structure for REITs.