ETDs

This collection includes most of the ASU Theses and Dissertations from 2011 to present. ASU Theses and Dissertations are available in downloadable PDF format; however, a small percentage of items are under embargo. Information about the dissertations/theses includes degree information, committee members, an abstract, supporting data or media.

In addition to the electronic theses found in the ASU Digital Repository, ASU Theses and Dissertations can be found in the ASU Library Catalog.

Dissertations and Theses granted by Arizona State University are archived and made available through a joint effort of the ASU Graduate College and the ASU Libraries. For more information or questions about this collection contact or visit the Digital Repository ETD Library Guide or contact the ASU Graduate College at gradformat@asu.edu.

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IVC与CVC对科技型创业企业上市及上市后的影响差异分析

Description随着科创板、注册制出台，企业间的竞争逐步从资源型竞争转向科技和技术的竞争，大量有知识、有文化、有理想、有技术的人才涌入社会，给科技发展、技术创新在政策、市场和人才层面提供了支撑、机遇和源动力，科技型创新企业大量涌现，形成趋势性上升行业。科技型创业企业多冠以“规模小、技术密集、高成长、高风险”的标签，在融资过程中困难重重，这些特点与风险投资（VC）“高风险、高回报”的特质不谋而合，VC机构还能给被投企业提供人才、信息、商业模式、政策法律咨询等增值服务，助力企业发展。引入VC走上市路径成为诸多科技型创业企业最优选择。 近些年VC行业在我国得到迅猛发展，IVC和CVC已成了助推我国科技型创业企业发展的主力军。由于IVC和CVC的组织架构、投资期限、资金来源、投资目标、投资经验、管理层薪资结构等方面存在着很大的不同。不同的投资模式势必会对被投企业的经营活动产生不同影响，本文基于总资产单位产出和投入为经济学逻辑，针对相关变量提出假设。 本文对我国中小板和创业板2013年以前上市的七个高新技术行业（5G通信、大数据、人工智能、软件服务、生物制药、新材料、医疗器械）共123家，以上市为起点的6年企业数据为基础。以IVC和CVC为自变量，以上市司龄、企业规模、行业控制、分红占净利润比为控制变量，以V/A、E/A、K/A和E/R为因变量，对IVC和CVC投入的科技型创业企业分别进行描述性统计、相关性分析和回归分析，验证IVC和CVC对被投企业的市场维度（V/A）、财务维度（E/A、E/R）、创新维度（K/A）的影响。试图从企业的角度出发，理清企业与VC的关系，为二级市场投资者提供一个投资决策视角。
ContributorsZhang, Mingpeng (Author) / Shen, Wei (Thesis advisor) / Jiang, Zhan (Thesis advisor) / Hu, Jie (Committee member) / Arizona State University (Publisher)
Created2021
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An Empirical Study on the Accuracy of Analysts' Long-term Earnings Forecast

Description
With the continuous development of the Chinese capital market over the past thirty years, the securities analyst industry has experienced a process of transformation from a reckless period to a golden time. One of the most important signals is that securities analysts are increasingly conducting research report providing long-term earnings…

With the continuous development of the Chinese capital market over the past thirty years, the securities analyst industry has experienced a process of transformation from a reckless period to a golden time. One of the most important signals is that securities analysts are increasingly conducting research report providing long-term earnings forecasts for the company. However, current research on analysts is limited to their short-term forecasting behavior, and there is little on analysts' long-term earnings forecasts. Therefore, this article takes the research on analysts' long-term forecast reports issued by analysts on A-share listed companies, and conducts an empirical study on the analysts' forecasts accuracy and its influencing factors. First, the author combed the research literature related to analyst forecasts and selected variables from three dimensions, including company characteristics (financial indicators and non-financial indicators), analyst characteristics and affiliated institution characteristics; secondly, considering the high-dimensionality of the influencing factors, this paper uses the method of combining machine learning and traditional regression to conduct empirical research; finally, the research tested the heterogeneity of influencing factors from two perspectives, including time and industry.The results of this article show that the long-term profit forecasts of analysts in China have advantages over traditional statistical models. More than 60% of analysts provide profit forecasts that are better than statistical models. Afterwards, when examining the factors that affected the accuracy of analysts’ forecasts, it found that although analyst and institutional characteristics affected analysts’ predictions to a certain extent, company characteristics are the most important variables among them all. As the time goes by, the influence of non-financial factors on forecast accuracy gradually decreasing, but analyst characteristics continue to strengthen. In addition, cyclical industries are more difficult to predict than companies in non-cyclical industries, and the difficulty of prediction will not be reduced with the analyst efforts. This research can help analysts optimizing their forecasting behavior and prompts investors to understand analysts' reports more deeply, which makes them using analyst forecast data to make investment decisions in a rationally ways, and it can also help to promote the securities pricing efficiency and development of Chinese capital market.
ContributorsRao, Gang (Author) / Shen, Wei (Thesis advisor) / Yan, Hong (Thesis advisor) / Hu, Jie (Committee member) / Arizona State University (Publisher)
Created2024