Mosaics of Predictability

Lin Cong, Guanhao Feng (), Jingyu He and Yuanzhi Wang

No 35158, NBER Working Papers from National Bureau of Economic Research, Inc

Abstract: We argue that return predictability is a latent, asset-specific, and state-dependent characteristic. We develop an interpretable Panel Tree that endogenously partitions the U.S. equity panel into out-of-sample and persistent “mosaic” patterns, and estimate cluster-specific forecasting models. Predictability concentrates in stocks with large earnings surprises, high earnings–price ratios, and low trading volume. It is countercyclical, stronger when market dividend yields are high and liquidity is low. Accounting for predictability heterogeneity, which conventional models ignore, improves forecasts and yields portfolios with out-of-sample Sharpe ratios around 2. Across 50 years of data, the mosaic map shows where signals arise and where noise dominates.

JEL-codes: C38 C53 C55 G12 (search for similar items in EconPapers)
Date: 2026-04
Note: AP
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