Hangyuan SHI

Date of Award


Degree Type


Degree Name

Master of Philosophy (MPHIL)


Finance and Insurance

First Advisor

Prof. WONG Man Lai Sonia


Based on a valuable testing venue in China where listed companies are required to disclose corporate site visit records of financial analyst to the public, this study examines whether analysts will learn from visiting analysts' forecasts that contain superior private information. I find that visiting forecasts tend to attract more analysts to issue forecasts in their aftermath than the prior forecasts issued by the same analysts but without conducting corporate site visit (non-visiting forecasts). The following effect is weaker when the visiting forecasts are more informative. In addition, other analysts’ forecasts following the visiting forecasts tend to move closer to the visiting forecasts than the forecasts following the non-visiting forecasts, with the effects being stronger for more informative visiting forecasts. Furthermore, followers experience a greater improvement in their forecast accuracy than the non-followers. This effect is also stronger when the visiting forecasts are more informative. Last but not the least, I find a decline in analyst forecast dispersion, an increase in common information, and an improvement in forecast accuracy in the period subsequent to the issuance of visiting analysts’ forecasts but no such effect for non-visiting forecasts. Collectively, the results suggest that analysts have incentive to learn from the forecasts that contain superior information and such learning activities tend to improve the information environment of the visiting firms.

Recommended Citation

Shi, H. (2016). Will analysts learn from other analysts who possess superior private information? (Master's thesis, Lingnan University, Hong Kong). Retrieved from