本文關鍵詞： 分位數(shù)回歸 Granger因果檢驗 網(wǎng)絡情緒 股市收益 微博數(shù)據(jù)　出處：《管理科學》2017年03期 　論文類型：期刊論文

【摘要】：行為金融學理論認為,股票市場的價格變動除受宏觀基本因素影響外,還在很大程度上受眾多個體投資者或噪音交易者行為左右。中國股票市場擁有龐大的個人投資者群體,且股民群體與網(wǎng)民群體之間具有高度耦合性,使用網(wǎng)絡情緒等信息能夠探索中國股市收益變動基本規(guī)律。為揭示個體投資者行為對股市收益的影響,以個體投資者情緒為視角,以網(wǎng)絡環(huán)境中個體投資者的情緒信息為切入點,檢驗投資者情緒與股市收益的關聯(lián)關系,評估網(wǎng)絡情緒信息價值。使用中文文本情感分析方法,從新浪微博文本中提取出網(wǎng)絡情緒時間序列;分別運用均值Granger因果和分位數(shù)Granger因果檢驗方法,探討網(wǎng)絡情緒波動與股市收益之間是否存在因果關系;將股票市場發(fā)展階段進行細致劃分,研究不同市場階段下網(wǎng)絡情緒波動與股市收益之間的因果關系。對滬深300指數(shù)收益進行實證研究,結果表明,盡管在均值框架下網(wǎng)絡情緒波動與股市收益之間因果關系并不明顯,但基于分位數(shù)Granger因果分析卻發(fā)現(xiàn)兩者在極端分位點區(qū)間處存在廣泛且顯著的因果關系。數(shù)據(jù)顯示,在40個因果關系檢驗中,分位數(shù)Granger因果檢驗的因果關系發(fā)現(xiàn)了23個顯著的因果關系,發(fā)現(xiàn)率為57.5%,遠高于均值Granger因果檢驗的7.5%。此外,股市收益受到網(wǎng)絡情緒波動影響的程度和方式在不同市場階段下有所不同。研究結果具有一定的理論意義和應用價值。在一些特定分位點區(qū)間網(wǎng)絡情緒波動對股市收益存在顯著因果關系影響,這為在特定條件下股市收益的可預測性提供了佐證。網(wǎng)絡情緒能夠預測股市收益的尾部(上尾或下尾)行為特征,可以為金融風險防范提供決策參考。研究結果為股票市場的定價、收益預測和波動率估計等相關研究提供了新的研究思路,也為網(wǎng)絡情緒信息使用提供了新的方向。
[Abstract]:The theory of behavioral finance holds that the price change of stock market is not only influenced by macroscopic basic factors. The Chinese stock market has a large group of individual investors, and there is a high degree of coupling between the investors and Internet users. In order to reveal the influence of individual investors' behavior on stock market returns, we can explore the basic rules of stock market returns by using information such as online sentiment. Based on the emotional information of individual investors in the network environment, this paper examines the relationship between investor sentiment and stock market returns, and evaluates the value of online emotional information. The online emotional time series is extracted from the text of Sina Weibo. Using the mean Granger causality test and the quantile Granger causality test, the paper discusses whether there is a causal relationship between the network emotion fluctuation and the stock market return. The development stage of stock market is divided into two parts, and the causality between the network emotion fluctuation and the stock market return is studied in different market stages. The empirical research on the Shanghai and Shenzhen 300 index returns shows that. Although the causal relationship between online emotional volatility and stock market returns is not obvious under the mean value framework. However, based on the quantile Granger causality analysis, we found that there was a wide and significant causal relationship between the two in the extreme locus interval. The data showed that there were 40 causality tests. In the quantile Granger causality test, 23 significant causal relationships were found, and the discovery rate was 57.5, which was much higher than that of the mean Granger causality test. The degree and mode of the stock market income affected by the network emotion fluctuation are different in different market stages. The research results have certain theoretical significance and application value. There is a significant causal relationship between market returns. This provides evidence for the predictability of stock market returns under certain conditions. Internet emotions can predict the tail (upper tail or lower tail) behavior characteristics of stock market returns. The research results provide a new approach for the stock market pricing, income forecasting and volatility estimation. It also provides a new direction for the use of network emotional information.
【作者單位】： 合肥工業(yè)大學管理學院;合肥工業(yè)大學過程優(yōu)化與智能決策教育部重點實驗室;
【基金】：國家自然科學基金(71671056) 國家社會科學基金(15BJY008) 教育部人文社會科學研究規(guī)劃基金(14YJA790015)~~
【分類號】：C912.6;C913.4;F832.51
【正文快照】： 為揭示個體投資者行為對股市收益的影響,以個體投資者情緒為視角,以網(wǎng)絡環(huán)境中個體投資者的情緒信息為切入點,檢驗投資者情緒與股市收益的關聯(lián)關系,評估網(wǎng)絡情緒信息價值。使用中文文本情感分析方法,從新浪微博文本中提取出網(wǎng)絡情緒時間序列;分別運用均值Granger因果和分位數(shù)G

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