Abstract

I propose a regime-switching generalization of instrumented principal components analysis (IPCA) that yields new insights about the relation between characteristics, factor loadings, and expected stock returns. Using a two-regime specification, I find evidence of a high-volatility regime in which individual stocks have high conditional expected returns. This contrasts sharply with the pattern of bull and bear regimes that is obtained by analyzing only market returns. Although exact factor pricing can be rejected, characteristics are more strongly related to priced covariances in the high-volatility regime. Furthermore, regime-switching predictability makes a substantial incremental contribution to the out-of-sample explanatory power of IPCA estimates.

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