Hao Ma (SFI): How to Use Price Disparity to Estimate Investor Sentiment
Huang Engineering 305
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How to Use Price Disparity to Estimate Investor Sentiment
Hao Ma (Swiss Finance Institute)
This paper shows how to identify and estimate investor sentiment. By exploiting the price disparity of dual-listed stocks, we show how to exactly identify stock-specific market-wide investor sentiment based on the Noise Trader Theory. We then conduct structural estimation via Deep Learning to estimate the Chinese investor sentiment as a general function of firm-level characteristics. This novel model-free sentiment indicator extends our understanding of what and how characteristics drive the sentiment dynamics. We further use this framework to extract the sentiment component of each stock in the Chinese stock market and test on a wide range of behavioral theories.
Hao Ma is a Ph.D. Candidate at the Swiss Finance Institute and The University of Lugano. His research interest lies in the intersection of asset pricing, financial econometrics, and machine learning. His work mostly focuses on combining econometrics with machine learning to solve big data problems in empirical asset pricing. He also shares an interest in understanding how differently AI adoption affects the economy compared with previous waves of technological innovation.