互联网金融特征、投资者情绪与互联网理财产品回报
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摘要
互联网金融投资者情绪(IFIS)和互联网理财产品回报的互动关系是亟待解决的问题,本文基于互联网金融投资者情绪对互联网理财产品市场回报独特的影响机制,创新性地分别采用四个类股市指标表征IFIS的直接作用、六个反映互联网金融特征的指标表征其间接作用,协同构建互联网金融投资者情绪指数。应用从2014年1月到2017年12月的Wind数据库和网贷之家数据库的月度数据进行实证分析,结果表明:IFIS与互联网理财产品回报之间呈负向关系,并且IFIS造成的系统性风险独立于宏观经济与其他互联网理财产品市场系统性风险,会额外通过互联网理财产品价格波动影响预期收益,得到风险补偿,这与基于股市投资者情绪的研究结果一致。IFIS对互联网理财产品回报呈现单向因果关系。还有一个有趣的发现是,与国内外股市投资者情绪相关研究的结论相反,IFIS与由类比IPO数量而采用的新增平台数量呈负向关系,这可以通过互联网理财产品市场阶段性监管政策得到解释。本文结论稳健,为研究互联网金融、互联网理财产品市场以及互联网金融投资者行为提供一个新工具。
Internet financial products market is booming, but also brings high risks. In particular, the market may be greatly affected by behavioral factors such as internet financial investor sentiment, due to the participation of a large number of individual investors. The interaction between internet financial investor sentiment and the return of Internet financial products is an urgent problem for both financial regulators and academic researchers. However, the existing research on investor sentiment mainly focuses on traditional security markets(Baker & Wurgler, 2006; Huang et al., 2015; Benhabib et al., 2016; Aboody et al., 2018), while there is a lack of research on investor sentiment in new financial sectors.Different from the influencing mechanism of investor sentiment on stock returns, internet financial investor sentiment may not only directly affect the returns of internet financial products, but also have indirect impacts through financial intermediary platform. Thererfore, in this paper, we apply four stock-comparable indicators(turnover-rate, newly added platform, volume, and net inflow of funds) and six innovative indicators that reflect internet financial characteristics(newly added problematic platform, numbers of investors, the proportion in internet financial products, total individual investment, internet finance index, and net loan popularity index). In empirical tests, this paper applies monthly data mainly collected from Wind database and Net Loan database(www.wdzj.com) during January 2014 and December 2017. In the process of index construction, taking into account the impact of macroeconomic cycle changes on the internet financial investor sentiment, we have removed relevant macroeconomic variables to better measure the irrational behavior of investors. Then, through principal component analysis, this paper has synthesized the numerous indicators introduced above and generate a time series of internet financial investor sentiment index. Given the index, this paper also verifies the effectiveness of internet financial investor sentiment index by various methods and finally investigate the relationship between the internet financial investor sentiment and the returns of internet financial products. All results have been checked by using robustness tests.This paper contributes to the literature of the internet finance and the investor sentiment in four perspectives. First, our ten internet finance-related indicators compose the most comprehensive indicator system for internet financial investor sentiment. Second, this study is the first to expand the investor sentiment theory to the internet financial product market. The third, this paper finds that internet financial investor sentiment has a negative relationship with the return of internet financial products. It proves that internet financial investor sentiment is a significant factor affecting the return of internet financial products, which has extra explanation power beyond the macroeconomic variable(i.e. M2). Fourth, based on the interactive research results of Granger causality test, the internet financial investor sentiment has a one-way causal effect on the return of internet financial products.There is also another interesting finding. This paper demonstrates that the relationship between each indicator and the final index is in line with theoretical inference, except the numbers of newly added platforms(NAP). NAP is constructed following the number of IPOs in stock markets. It is negatively correlated with the internet financial investor sentiment, which is different from the positive relationship between the number of IPOs and the investor sentiment in stock market(Benhabib et al., 2016; Aboody et al., 2018; He et al., 2017;Yao et al., 2018). This interesting discovery is also reasonably explained by comparing the three development stages of the internet financial product market. This finding also points out the difference between the internet financial product market and the traditional securities market, and confirms the research significance of this paper.
Internet financial products market is booming, but also brings high risks. In particular, the market may be greatly affected by behavioral factors such as internet financial investor sentiment, due to the participation of a large number of individual investors. The interaction between internet financial investor sentiment and the return of Internet financial products is an urgent problem for both financial regulators and academic researchers. However, the existing research on investor sentiment mainly focuses on traditional security markets(Baker & Wurgler, 2006; Huang et al., 2015; Benhabib et al., 2016; Aboody et al., 2018), while there is a lack of research on investor sentiment in new financial sectors.Different from the influencing mechanism of investor sentiment on stock returns, internet financial investor sentiment may not only directly affect the returns of internet financial products, but also have indirect impacts through financial intermediary platform. Thererfore, in this paper, we apply four stock-comparable indicators(turnover-rate, newly added platform, volume, and net inflow of funds) and six innovative indicators that reflect internet financial characteristics(newly added problematic platform, numbers of investors, the proportion in internet financial products, total individual investment, internet finance index, and net loan popularity index). In empirical tests, this paper applies monthly data mainly collected from Wind database and Net Loan database(www.wdzj.com) during January 2014 and December 2017. In the process of index construction, taking into account the impact of macroeconomic cycle changes on the internet financial investor sentiment, we have removed relevant macroeconomic variables to better measure the irrational behavior of investors. Then, through principal component analysis, this paper has synthesized the numerous indicators introduced above and generate a time series of internet financial investor sentiment index. Given the index, this paper also verifies the effectiveness of internet financial investor sentiment index by various methods and finally investigate the relationship between the internet financial investor sentiment and the returns of internet financial products. All results have been checked by using robustness tests.This paper contributes to the literature of the internet finance and the investor sentiment in four perspectives. First, our ten internet finance-related indicators compose the most comprehensive indicator system for internet financial investor sentiment. Second, this study is the first to expand the investor sentiment theory to the internet financial product market. The third, this paper finds that internet financial investor sentiment has a negative relationship with the return of internet financial products. It proves that internet financial investor sentiment is a significant factor affecting the return of internet financial products, which has extra explanation power beyond the macroeconomic variable(i.e. M2). Fourth, based on the interactive research results of Granger causality test, the internet financial investor sentiment has a one-way causal effect on the return of internet financial products.There is also another interesting finding. This paper demonstrates that the relationship between each indicator and the final index is in line with theoretical inference, except the numbers of newly added platforms(NAP). NAP is constructed following the number of IPOs in stock markets. It is negatively correlated with the internet financial investor sentiment, which is different from the positive relationship between the number of IPOs and the investor sentiment in stock market(Benhabib et al., 2016; Aboody et al., 2018; He et al., 2017;Yao et al., 2018). This interesting discovery is also reasonably explained by comparing the three development stages of the internet financial product market. This finding also points out the difference between the internet financial product market and the traditional securities market, and confirms the research significance of this paper.
引文
部慧、 解峥、李佳鸿、吴俊杰,2018:《基于股评的投资者情绪对股票市场的影响》,《管理科学学报》第4期。
陈国进、张贻军、刘淳,2010:《机构投资者是股市暴涨暴跌的助推器吗?——来自上海A股市场的经验证据》,《金融研究》第11期。
冯博、叶绮文、陈冬宇,2017:《P2P网络借贷研究进展及中国问题研究展望》,《管理科学学报》第4期。
韩金晓、张丽,2018:《中国股票市场短期反转效应的流动性供给解释——机构投资者退出的角度》,《管理世界》第5期。
贺志芳、文凤华、黄创霞、杨晓光、郑石明,2017:《投资者情绪与时变风险补偿系数》,《管理科学学报》第12期。
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李广子、唐国正、刘力,2011:《股票名称与股票价格非理性联动——中国A股市场的研究》,《管理世界》第1期。
李克穆,2016:《互联网金融的创新与风险》,《管理世界》第2期。
刘翱、童泽平、邓旭东、刘克,2017:《基于改进TOPSIS法的P2P网贷平台运营效率评价》,《系统科学与数学》第7期。
刘京军,2018:《货币市场基金的市场集中度影响了其风险承担吗?》,《金融研究》第7期。
刘维奇、刘新新,2014:《个人和机构投资者情绪与股票收益——基于上证A股市场的研究》,《管理科学学报》第3期。
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王靖一、黄益平,2018:《金融科技媒体情绪的刻画与对网贷市场的影响》,《经济学(季刊)》第4期。
王美今、孙建军,2004:《中国股市收益,收益波动与投资者情绪》,《经济研究》第10期。
王馨,2015:《互联网金融助解“长尾”小微企业融资难问题研究》,《金融研究》第9期。
汪昌云、武佳薇,2015:《媒体语气、投资者情绪与IPO定价》,《金融研究》第9期。
文凤华、肖金利、黄创霞、陈晓红、杨晓光,2014:《投资者情绪特征对股票价格行为的影响研究》,《管理科学学报》第3期。
吴悠悠,2015:《我国互联网金融:问题、前景和建议》,《管理世界》第4期。
伍燕然、韩立岩,2007:《不完全理性、投资者情绪与封闭式基金之谜》,《经济研究》第3期。
许海川、周炜星,2018,《情绪指数与市场收益:纳入中国波指(iVIX)的分析》,《管理科学学报》第1期。
姚尧之、王坚强、刘志峰,2018:《混频投资者情绪与股票价格行为》,《管理科学学报》第2期。
易志高、茅宁,2009:《中国股市投资者情绪测量研究:CICSI的构建》,《金融研究》第11期。
战明华、张成瑞、沈娟,2018:《互联网金融发展与货币政策的银行信贷渠道传导》,《经济研究》第4期。
张皓星、黄益平,2018:《情绪、违约率与反向挤兑——来自某互金企业的证据》,《经济学(季刊)》第4期。
张强、杨淑娥,2009:《噪音交易、投资者情绪波动与股票收益》,《系统工程理论与实践》第3期。
张文、崔杨波、姜祎盼,2018:《基于SVM～(K-Means)的非均衡P2P网贷平台风险预测研究》,《系统科学与数学》第3期。
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(1)由于中国互联网理财产品市场以2013年为发展元年,数据统计均从2013年后期到2014年初开始,且主要为月度数据,甚至部分为年度数据。本文样本一共有48组,在后文中实证研究的每一步OLS回归时均对所得残差进行了Jarque-Bera(JB)检验,结果表明,所有残差均呈正态分布,即本文的样本容量符合实证检验的要求。
(2)本文选取的网贷之家互联网理财平台(www.wdzj.com),是目前中国网络借贷行业最大、最权威的第三方资讯平台,并曾为上海市政府对行业调研提供咨询参考,同时网贷之家数据库也被发表在核心期刊的文章(刘翱等,2017;张文等,2018)引用数据,从这政府和学术的层面上来说,本文选取的网贷之家数据库都受到认可,数据具有可靠性。
(3)样条插值法可能会对实验结果的准确性造成影响,另外选择互联网理财的比例与个人可投资总额可能存在相关性问题。因此本文在第四节特设稳定性检验,在构建过程剔除“个人可投资总额”以及“选择互联网理财的比例”两个指标,结果显示本文的结论均稳健。
(4)文献中普遍采用IS(investor sentiment)来简称投资者情绪,本文结合互联网金融特性,简称为IFIS(internet financial investor sentiment)。本文将第一期基于当期指标以及一阶滞后项得到的投资者情绪指标时间序列称为IFIS0。后续会有剔除宏观因子后的基于主成分1(IFIS1)、主成分2(IFIS2)以及最终综合主成分加权(IFIS)三项投资者情绪指标时间序列。其中IFIS为本文最终采用的基于互联网特征的投资者情绪指数。
(5)本文实证过程中处理滞后阶数据,故后文中的实证结果均基于自2014年3月至2017年12月的样本数据。
(6)网贷之家《年终盘点:从无到有细数网贷监管的三个阶段》,http://www.wdzj.com/zhuanlan/licai/6-3336-1.htm1。
(7)卢纹岱和朱红兵(2015)取累计贡献率大于80%来确定取前k个成分作为研究问题的主成分,而Baker & Wurgle(2006)仅取了方差解释度为49%的第一主成分。
陈国进、张贻军、刘淳,2010:《机构投资者是股市暴涨暴跌的助推器吗?——来自上海A股市场的经验证据》,《金融研究》第11期。
冯博、叶绮文、陈冬宇,2017:《P2P网络借贷研究进展及中国问题研究展望》,《管理科学学报》第4期。
韩金晓、张丽,2018:《中国股票市场短期反转效应的流动性供给解释——机构投资者退出的角度》,《管理世界》第5期。
贺志芳、文凤华、黄创霞、杨晓光、郑石明,2017:《投资者情绪与时变风险补偿系数》,《管理科学学报》第12期。
黄德龙、文风华、杨晓光,2009:《投资者情绪指数及中国股市的实证》,《系统科学与数学》第1期。
李广子、唐国正、刘力,2011:《股票名称与股票价格非理性联动——中国A股市场的研究》,《管理世界》第1期。
李克穆,2016:《互联网金融的创新与风险》,《管理世界》第2期。
刘翱、童泽平、邓旭东、刘克,2017:《基于改进TOPSIS法的P2P网贷平台运营效率评价》,《系统科学与数学》第7期。
刘京军,2018:《货币市场基金的市场集中度影响了其风险承担吗?》,《金融研究》第7期。
刘维奇、刘新新,2014:《个人和机构投资者情绪与股票收益——基于上证A股市场的研究》,《管理科学学报》第3期。
鲁训法、黎建强,2012:《中国股市指数与投资者情绪指数的相互关系》,《系统工程理论与实践》第3期。
王靖一、黄益平,2018:《金融科技媒体情绪的刻画与对网贷市场的影响》,《经济学(季刊)》第4期。
王美今、孙建军,2004:《中国股市收益,收益波动与投资者情绪》,《经济研究》第10期。
王馨,2015:《互联网金融助解“长尾”小微企业融资难问题研究》,《金融研究》第9期。
汪昌云、武佳薇,2015:《媒体语气、投资者情绪与IPO定价》,《金融研究》第9期。
文凤华、肖金利、黄创霞、陈晓红、杨晓光,2014:《投资者情绪特征对股票价格行为的影响研究》,《管理科学学报》第3期。
吴悠悠,2015:《我国互联网金融:问题、前景和建议》,《管理世界》第4期。
伍燕然、韩立岩,2007:《不完全理性、投资者情绪与封闭式基金之谜》,《经济研究》第3期。
许海川、周炜星,2018,《情绪指数与市场收益:纳入中国波指(iVIX)的分析》,《管理科学学报》第1期。
姚尧之、王坚强、刘志峰,2018:《混频投资者情绪与股票价格行为》,《管理科学学报》第2期。
易志高、茅宁,2009:《中国股市投资者情绪测量研究:CICSI的构建》,《金融研究》第11期。
战明华、张成瑞、沈娟,2018:《互联网金融发展与货币政策的银行信贷渠道传导》,《经济研究》第4期。
张皓星、黄益平,2018:《情绪、违约率与反向挤兑——来自某互金企业的证据》,《经济学(季刊)》第4期。
张强、杨淑娥,2009:《噪音交易、投资者情绪波动与股票收益》,《系统工程理论与实践》第3期。
张文、崔杨波、姜祎盼,2018:《基于SVM～(K-Means)的非均衡P2P网贷平台风险预测研究》,《系统科学与数学》第3期。
Aboody,D.,O.Even-Tov,R.Lehavy,and B.Trueman,2018,“Overnight Returns and Firm-specific Investor Sentiment”,Journal of Financial and Quantitative Analysis,53(2),485—505.
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(1)由于中国互联网理财产品市场以2013年为发展元年,数据统计均从2013年后期到2014年初开始,且主要为月度数据,甚至部分为年度数据。本文样本一共有48组,在后文中实证研究的每一步OLS回归时均对所得残差进行了Jarque-Bera(JB)检验,结果表明,所有残差均呈正态分布,即本文的样本容量符合实证检验的要求。
(2)本文选取的网贷之家互联网理财平台(www.wdzj.com),是目前中国网络借贷行业最大、最权威的第三方资讯平台,并曾为上海市政府对行业调研提供咨询参考,同时网贷之家数据库也被发表在核心期刊的文章(刘翱等,2017;张文等,2018)引用数据,从这政府和学术的层面上来说,本文选取的网贷之家数据库都受到认可,数据具有可靠性。
(3)样条插值法可能会对实验结果的准确性造成影响,另外选择互联网理财的比例与个人可投资总额可能存在相关性问题。因此本文在第四节特设稳定性检验,在构建过程剔除“个人可投资总额”以及“选择互联网理财的比例”两个指标,结果显示本文的结论均稳健。
(4)文献中普遍采用IS(investor sentiment)来简称投资者情绪,本文结合互联网金融特性,简称为IFIS(internet financial investor sentiment)。本文将第一期基于当期指标以及一阶滞后项得到的投资者情绪指标时间序列称为IFIS0。后续会有剔除宏观因子后的基于主成分1(IFIS1)、主成分2(IFIS2)以及最终综合主成分加权(IFIS)三项投资者情绪指标时间序列。其中IFIS为本文最终采用的基于互联网特征的投资者情绪指数。
(5)本文实证过程中处理滞后阶数据,故后文中的实证结果均基于自2014年3月至2017年12月的样本数据。
(6)网贷之家《年终盘点:从无到有细数网贷监管的三个阶段》,http://www.wdzj.com/zhuanlan/licai/6-3336-1.htm1。
(7)卢纹岱和朱红兵(2015)取累计贡献率大于80%来确定取前k个成分作为研究问题的主成分,而Baker & Wurgle(2006)仅取了方差解释度为49%的第一主成分。
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