融资融券对股市波动性影响的实证研究——以深证为例

本文主要从实证角度去考察融资融券交易机制对股票市场波动性的影响,并选取我国证券市场过去几年的相关交易数据进行实证研究。在实证中运用Granger因果检验、脉冲响应函数、方差分解等计量经济学方法进行实证验证,得出了如下结论:一是在我国证券市场中,股票指数变动是融券余额变动的Granger原因,融资融券余额变动不是融券余额变动的Granger原因,融资融券并不是造成市场波动的本质原因;二是在我国融资融券额对股票指数变动的影响都不大,融资交易相比融券交易对市场指数变动的解释程更大,并且对市场指数变动影响的持续时间更长。     

融资融券、投资者情绪与市场波动北大核心CSSCISSCI

融资融券是否通过影响投资者情绪,进一步对市场参与主体行为业绩,以及市场整体稳定性产生影响?本文认为,当前融资融券所表现出的"强杠杆、弱风险对冲"特征对投资者情绪起到助长的净效应;进一步,包含融资融券在内的投资者情绪对市场波动性具有加剧效应。从参与者层面,消极型投资者受投资者情绪影响所导致的业绩波动程度大于积极型投资者;在融资融券开展不同时期内,投资者情绪对投资者业绩波动呈现出先抑后扬的表现。从市场整体稳定性层面,本文发现投资者情绪对内地A股市场的加剧波动影响程度最大,而对香港中概股市场及海外(非港)中概股市场1也存在不同程度的情绪传染。     

卖空限制与收益可预测性——A股融资融券制度的证据

基于A股市场融资和融券余额的巨大差距,本文拓展了Hong et al.(2016)的理论模型,在融券端和融资端分别找到了影响股票收益率的变量:融券比率(融券余额/流通市值)和融资回补天数(融资比率/日均换手率)。进一步,本文利用组合价差法和Fama-MacBeth横截面回归法,实证检验了A股市场中融券比率与融资回补天数解释和预测股票收益率的能力。实证结果表明,在存在融券限制条件下,融券比率相比融券回补天数(融券比率/日均换手率)能更好地代表套利者对股票价格高估程度的看法,根据融券比率构建的等权重多空组合能带来月均1.58%的显著收益;而由于融资约束相对较少,融资回补天数相比融资比率(融资余额/流通市值)能更好地代表套利者对股票价格低估程度的看法,根据融资回补天数构建的等权重多空组合能带来月均1.28%的显著收益。实证结果与本文存在融券数量限制下的理论模型相符,且该收益率不能被多因子模型和常规股票特征所解释。     

基于小波CCC-GARCH模型的融资融券交易与证券市场波动率关系研究

以2010年4月2日～2016年7月21日的中国证券市场交易数据为样本,运用小波CCC-GARCH模型,考量融资融券交易对证券市场波动率的影响.结果表明,融资交易行为对证券市场收益率和成交量的波动均有较显著的影响,而融券交易对市场波动率的影响不显著.同时,融资交易行为对市场的影响主要由高频信号所驱动,投资者短期非理性行为或噪音交易对市场波动的影响较大.为促进市场的健康发展,应均衡融资融券业务的发展,培养理性机构投资者,加强投资者风险警示加快融资融券数据库的建设.     

卖空限制与收益可预测性——A股融资融券制度的证据

基于A股市场融资和融券余额的巨大差距,本文拓展了Hong et al.(2016)的理论模型,在融券端和融资端分别找到了影响股票收益率的变量:融券比率(融券余额/流通市值)和融资回补天数(融资比率/日均换手率)。进一步,本文利用组合价差法和Fama-MacBeth横截面回归法,实证检验了A股市场中融券比率与融资回补天数解释和预测股票收益率的能力。实证结果表明,在存在融券限制条件下,融券比率相比融券回补天数(融券比率/日均换手率)能更好地代表套利者对股票价格高估程度的看法,根据融券比率构建的等权重多空组合能带来月均1.58%的显著收益;而由于融资约束相对较少,融资回补天数相比融资比率(融资余额/流通市值)能更好地代表套利者对股票价格低估程度的看法,根据融资回补天数构建的等权重多空组合能带来月均1.28%的显著收益。实证结果与本文存在融券数量限制下的理论模型相符,且该收益率不能被多因子模型和常规股票特征所解释。     

杠杆投资者融资交易行为模式研究——来自A股市场的经验证据

自2010年证监会推出融资融券方案以来,A股市场上融资交易和融资余额都出现了较为显著的增长.目前A股市场上融资余额总量已达到万亿元的水平,对于中国股市的重要性日趋增加.有鉴于此,有必要对杠杆投资者的融资交易行为模式以及其对A股定价机制的影响进行更加深入地研究.本文通过实证研究检验杠杆投资者的融资交易行为模式与市场回报率、流动性等重要指标之间的相关关系.研究发现,滞后股票收益与杠杆投资者的净融资交易额之间存在着显著的正相关关系,说明我国杠杆投资者总体而言是追涨杀跌的趋势追逐者.股票价格下跌对融资交易的影响显著大于股票价格上涨所带来的影响,且这种不对称性在很大程度上是由市场收益而非个股异质性收益所引起的.此外,杠杆投资者的融资交易行为与未来股票周度收益之间存在负相关关系,这种负相关主要是由融资净卖出所引起的.     

融资融券机制对我国股市波动性的影响——基于上证50的实证分析

2010年3月31日,沪深两市正式接受券商的融资融券交易申报.经过4年准备的融资融券交易正式进入市场操作阶段.为了解其是否会影响股市的波动性、如何影响,本文运用VAR模型和Granger检验,基于上证50支首批允许融资融券交易股票437个交易日的数据进行实证分析并得到相关结论.最后本文在短期数据分析的基础上,分析预测了融资融券机制对我国A股市场的长期影响     

融资融券对个股交易变化影响的实证研究

文章运用融资融券155只标的证券的截面数据,实证研究了融资融券对个股交易变化的影响.结果发现,融资融券余额对标的股的个股回报率、交易股数、率都具有较为显著的正向作用,分析了导致这一现象出现的原因,并针对如何充分发挥融资融券价格发现功能,平抑股价过度波动提出了相关政策建议.     

中国股市融资融券标的股票“异质性波动率之谜”研究

本文研究了中国A股市场融资融券标的股票的"异质性波动率之谜",分别在我国融资融券制度推行初期和后期,构建了两阶段的双重差分回归模型,比较融资融券制度的政策效果。实证结果表明,在融资融券制度推行初期,两融标的股票"异质性波动率之谜"现象未能得到有效抑制。融资融券制度推行后期,A股市场融券交易总量快速增长,融资融券标的股票的"异质性波动率之谜"现象相对非融资融券股票得到明显抑制,这一抑制效应对于融券交易活跃的股票更为显著,说明融券交易的活跃程度对于抑制融资融券标的股票"异质性波动率之谜"现象起主要作用。     

分区间的融资融券交易影响股票价格实证分析

目前学界和业界就融资融券交易对股票价格的影响尚未达成共识。文章选取我国证券市场2010年4月至2018年12月的月度融资融券余额数据和沪指300指数数据,分样本区间实证研究了两者的变化规律。结果显示,在部分子样本区间内,融资融券交易推动了沪指300指数的上扬,但在整个样本区间内融券交易卖空机制的作用发挥尚不明显。由此,文章从完善融资融券交易机制和促进资本市场健康稳定发展的角度提出相应的政策建议。     

Investor Sentiment and Stock Returns: Evidence from Turkey

This paper investigates the relation between investor sentiment and stock returns on the Istanbul Stock Exchange, employing vector autoregressive (VAR) analysis and Granger causality tests. The sample period extends from July 1997 to June 2005. In the VAR models, stock portfolio returns and investor sentiment proxies are used as endogenous variables. Two dummy variables accounting for natural and economic crises are used as exogenous variables. The analysis results suggest that, excepting shares of equity issues in aggregate issues, stock portfolio returns seem to affect all investor sentiment proxies, namely closed-end fund discount, mutual fund flows, odd-lot sales-to-purchases ratio, and repo holdings of mutual funds. Investor sentiment does not appear to forecast future stock returns; only the turnover ratio of the stock market seems to have forecasting potential.     

Investor sentiment and return predictability of disagreement

This study examines the influence of investor sentiment on the relationship between disagreement among investors and future stock market returns. We find that the relationship between disagreement and future stock market returns time-varies with the degree of investor sentiment. Higher disagreement among investors’ opinions predicts significantly lower future stock market returns during high-sentiment periods, but it has no significant effect on future stock market returns during low-sentiment periods. Our findings imply that investor sentiment is related to several causes of short-sale impediments suggested in the previous literature on investor sentiment, and that the stock return predictability of disagreement is driven by investor sentiment. We demonstrate that investor sentiment has a significant impact on the stock market return predictability of disagreement through in-sample and out-of-sample analyses. In addition, the profitability of our suggested trading strategy exploiting disagreement and investor sentiment level confirms the economic significance of incorporating investor sentiment into the relationship between disagreement among investors and future stock market returns.     

投资者情绪是导致我国投资者对市场信息出现反应偏差的原因吗：基于贝叶斯分位数回归模型的研究

本文使用贝叶斯分位数回归模型实证分析包含投资者情绪的投资者最优选择模型,结果表明：投资者情绪对于股票收益率存在非线性的正向影响,这是造成投资者对于市场信息出现反应偏差的一个重要原因.同时,市场信息和投资者情绪指标对于我国股票收益率都有着较大的影响作用;当股票出现不同涨跌幅时,市场信息对于股票收益率的影响有着较大的差异性.而考虑了投资者情绪指标之后,投资者对于市场信息的反应偏差明显减小,说明投资者情绪是造成我国投资者对于市场信息出现过度反应和反应不足的重要原因.我国投资者应该树立起良好的投资意识和心态,避免潜在的投资损失.     

Investor Trading Behavior and Sentiment in Futures Markets

This study investigates the effects of investor trading behavior and investor sentiment on futures market return. We find that the spot investor trading behavior, futures investor trading behavior, spot market sentiment, and futures market sentiment all have positive effects on daily futures returns in Chinese financial market. More importantly, we show that the effect of (spot) futures investor trading behavior has better explanatory power than (spot) futures market sentiment on futures returns. Further supporting our results, high investor trading behavior and high investor sentiment strengthen the positive relation between sentiment-returns and behavior-returns.     

Applications of a multivariate Hawkes process to joint modeling of sentiment and market return events

To investigate the complex interactions between market events and investor sentiment, we employ a multivariate Hawkes process to evaluate dynamic effects among four types of distinct events: positive returns, negative returns, positive sentiment, and negative sentiment. Using both intraday S&P 500 return data and Thomson Reuters News sentiment data from 2008 to 2014, we find: (a) self-excitation is strong for all four types of events at 15 min time scale; (b) there is a significant mutual-excitation between positive returns and positive sentiment and negative returns and negative sentiment; (c) decay of return events is almost twice as fast as sentiment events, which means market prices move faster than investor sentiment changes; (d) positive sentiment shocks tend to generate negative price jumps; and (e) the cross-excitation between positive and negative sentiments is stronger than their self-excitation. These findings provide further understanding of investor sentiment and its intricate interactions with market returns.     

Can margin traders predict future stock returns in Japan?

A growing body of literature suggests that investor sentiment affects stock prices both at the firm level and at the market level. This study examines the relationship between investor behavior and stock returns focusing on Japanese margin transactions using weekly data from 1994 to 2003. Margin trading is dominated by individual investors in Japan. In analysis at the firm level, we find a significant cross-sectional relationship between margin buying and stock returns. Both market-level and firm-level analyses show that margin buying traders follow herding behavior. They seem to follow positive feedback trading behavior for small-firm stocks and negative feedback trading behavior for large firm stocks. Our results show that information about margin buying helps predict future stock returns, especially for small-firm stocks at short horizons. The predictive power does not diminish even after controlling for firm size and liquidity.     

Sentiment stocks

To study how investor sentiment at the firm level affects stock returns, we match more than 58 million social media messages in China with listed firms and construct a measure of individual stock sentiment based on the tone of those messages. We document that positive investor sentiment predicts higher stock risk-adjusted returns in the very short term followed by price reversals. This association between stock sentiment and stock returns is not explained by observable stock characteristics, unobservable time-invariant characteristics, market-wide sentiment, overreaction to news, or changing investor attention. Consistent with theories of investor sentiment, we find that the link between sentiment and stock returns is mainly driven by positive sentiment and non-professional investors. Finally, exploiting a unique feature of the Chinese stock market, we are able to isolate the causal effect of sentiment on stock returns from confounding factors.     

Investor Sentiment and the Cross-Section of Stock Returns

We study how investor sentiment affects the cross‐section of stock returns. We predict that a wave of investor sentiment has larger effects on securities whose valuations are highly subjective and difficult to arbitrage. Consistent with this prediction, we find that when beginning‐of‐period proxies for sentiment are low, subsequent returns are relatively high for small stocks, young stocks, high volatility stocks, unprofitable stocks, non‐dividend‐paying stocks, extreme growth stocks, and distressed stocks. When sentiment is high, on the other hand, these categories of stock earn relatively low subsequent returns.     

投资者情绪对市场风险价格影响

本文利用我国证券市场统计数据研究了个体和机构投资者情绪对风险市场价格（MPR）的影响,实证结果证明了市场对波动的反应是异质性的,并且受投资者情绪变化的影响。具体来看,将投资者情绪分解成理性和非理性成分后,非理性乐观情绪的增加将导致MPR明显的下降,但理性情绪的变动不会对MPR有明显的影响。这意味着当市场投资者情绪是由基础价值变化来决定的时候,市场风险价格不会发生变化。进一步的VAR脉冲响应函数分析结果显示,非理性的乐观或悲观情绪并不受理性情绪波动的影响,这意味着非理性情绪不是由基础风险因素决定的。     

Chinese institutional investors’ sentiment

We use daily survey data on Chinese institutional investors’ forecasts to measure investors’ sentiment. Our empirical model uncovers that share prices and investor sentiment do not have a long-run relation; however, in the short-run, the mood of investors follows a positive-feedback process. Hence, institutional investors are optimistic when previous market returns were positive. Contrarily, negative returns trigger a decline in sentiment, which reacts more sensitively to negative than positive returns. Investor sentiment does not predict future market movements—but a drop in confidence increases market volatility and destabilizes exchanges. EGARCH models reveal asymmetric responses in the volatility of investor sentiment; however, Granger causality tests reject volatility-spillovers between returns and sentiment.