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作 者:高扬[1] 赵昆 王耀君 GAO Yang;ZHAO Kun;WANG Yaojun(School of Economics and Management,Beijing University of Technology,Beijing 100124,China;College of Information and Electrical Engineering,China Agricultural University,Beijing 100083,China)
机构地区:[1]北京工业大学经济与管理学院,北京100124 [2]中国农业大学信息与电气工程学院,北京100083
出 处:《运筹与管理》2023年第7期156-161,共6页Operations Research and Management Science
基 金:国家自然科学基金面上项目(72171005)~~。
摘 要:股价泡沫严重影响资本市场健康运行,而投资者情绪和市场流动性是影响泡沫膨胀和破灭的重要因素。为探究二者对股价泡沫的作用机制,本文选取上证行业指数,通过动态因子分析法,将百度指数等网络社交媒体数据与换手率等传统情绪代理变量相结合,构建多个行业的投资者情绪指标。随后基于广义右尾单位根(Generalized Sup-ADF,GSADF)检验法,检测了不同行业的泡沫,并运用面板Logit模型和中介效应检验方法,进一步分析了投资者情绪、流动性与行业股价泡沫之间的关系。实证分析及稳健性检验结果均表明,投资情绪与流动性对股价泡沫的存在性具有显著的正向作用,投资者情绪可以通过促进流动性的提升,导致股价泡沫产生的可能性的进一步提高。研究结论对于防范股价泡沫风险具有重要启示,为监管者对加强市场情绪监管提供相关理论依据。Stock price bubbles seriously affect the healthy operation of capital markets.Recently,with the development of behavioral finance and other financial theories,many studies have explored the causes of stock price bubbles from the perspective of investor behavior and market microstructure.Behavioral finance theory believes that investor sentiment plays an essential role in affecting the price of financial assets.Investors tend to be influenced by emotions to change their investment behavior,which to a certain extent,drives the speed and extent of stock price fluctuations and thus generates stock market bubbles.Moreover,market microstructure theory holds that stock liquidity,as a critical measure of market quality,will directly affect the speed and cost of market transactions,eventually acting on stock price fluctuations and leading to stock price bubbles.Therefore,investigating the relationship between investor sentiment,stock liquidity,and stock price bubbles can help maintain the stable development of our financial markets.To explore the mechanisms of both investor sentiment and liquidity on stock price bubbles,we select nine Shanghai Stock Exchange(SSE)industry indices,including Energy,Materials,Industrials,Discretionary Consumption,Staples Consumption,Pharmaceutical,Information Technology,Telecom,and Utilities.Then based on dynamic factor analysis,this study constructs investor sentiment indicators by combining online social media data,such as the Baidu index,with traditional sentiment proxy variables,such as turnover rate.Subsequently,the bubbles in different industries are detected based on the Generalized Sup-ADF(GSADF)test.The GSDAF test results show that bubbles are detected in all nine industry indices,and the original hypothesis of the existence of unit root is rejected at the 1%significance level except for the Energy industry.Specifically,the highest number of bubbles is four in the Staples consumption sector,the second highest is three in the Industrials industry,and two bubbles exist in the Pharmaceu
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