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Herd Behavior in Venture Capital Market: Evidence from China

Ruijun Zhang (), Xiaotong Yang (), Nian Li () and Muhammad Asif Khan ()
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Ruijun Zhang: School of Business, Renmin University of China, Beijing 100872, China
Xiaotong Yang: School of Business, Renmin University of China, Beijing 100872, China
Nian Li: School of Economics and Management, Yanshan University, Qinhuangdao 066004, China
Muhammad Asif Khan: Department of Commerce, Faculty of Management Sciences, University of Kotli, Azad Jammu and Kashmir, Kotli 11100, Pakistan

Mathematics, 2021, vol. 9, issue 13, 1-18

Abstract: This paper aims to empirically analyze the herd behavior in the VC market in the context of China, including the existence, causes and consequences of herding among venture capitalists. For our empirical analysis, we first construct a herding measure and confirm the existence of herd behavior in the Chinese VC market. Then, we perform OLS/logit regression to examine the causes and consequences of herding among venture capitalists. Our results suggest that herd behavior in the venture capital market are driven by positive signals of essential information and a higher degree of information uncertainty. However, we find no evidence of the influence of feedback trading signals on herding among venture capitalists. Further analysis suggests that a better external information environment would help weaken the herding among venture capitalists, while their reputation concerns might amplify the herding effect. Finally, we examine the economic consequence of the herding and find that the herd behavior of venture capitalists would have an adverse effect on their exit performance. In addition to the enrichment and development of herding theory, our study also provides an essential theoretical frame and policy implications for the steady growth of the venture capital market in emerging economies.

Keywords: venture capital; venture capitalist; herd behavior (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2021
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