Abstract
The Chinese stock market incurs huge illiquidity costs. Liquidity has different aspects but literature rarely measures it from an aggregate perspective. To capture liquidity along various dimensions and more consistently, we propose an aggregate liquidity premium with a partial least squares approach by aggregating information on 12 liquidity-related firm characteristics in the Chinese stock market. The aggregate liquidity predictor generates significantly higher expected stock returns than individual characteristics, remains robust to different information aggregation methods, and reflects the multidimensional feature of liquidity. Behavioral mispricing theory helps explain the aggregate liquidity premium because illiquidity limits arbitrage to correct mispricing. As liquidity is important and traditional factor models limitedly explain it, we develop a new-factor model to capture the aggregate liquidity premium. The aggregate liquidity premium in China indicates that policymakers should improve market liquidity.
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