Cunfei Liao

• Assistant Professor at Nanjing University of Science and Technology

This paper introduces a weather-related sentiment (mood) index (WSI) for the Chinese stock market based on precipitation and temperature data with the PLS method. We find that the WSI is negatively correlated with the equity market and has strong predictive power that is far greater than that of other market and macroeconomic variables. The predict...

This paper compares the explanations and predictabilities of 35 firm-level characteristics in stock returns between developed and ṆṆemerging stock markets using instrumented principal components analysis (IPCA). In contrast to the weak performance of the global model in each region, the local model performs better with lower mispricing errors at th...

This paper proposes a factor timing strategy with information from 146 characteristic‐based factors and a deep learning approach to capture the nonlinear predictability. The deep learning‐based factor timing strategy generates the highest economic value compared with the unconditional and alternative linear machine learning‐based portfolios and rem...

To explore what kinds of roles foreign investors take in a gradually opening financial market, we propose the abnormal holding value ratio (AHVR) of northbound investors among stocks through China's Stock Connect Mechanism. We find that AHVR positively predicts the expected stock returns and significantly relates to firms' quality‐related fundament...

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-relat...