Threshold effect in the relationship between investor sentiment and stock market returns: a PSTR specification

This article verifies whether the hypothesis of heterogeneous agent modelling and the behavioural heterogeneity framework can reproduce recent stylized facts regarding stock markets (e.g. the 1987 crash, internet bubble, and subprime crisis). To this end, we investigate the relationship between investor sentiment and stock market returns for the G7 countries from June 1987 to February 2014. We propose an empirical non-linear panel data specification based on the panel switching transition model to capture the investor sentiment-stock return relationship, while enabling investor sentiment to act asymmetrically, non-linearly, and time varyingly according to the market state and investor attitude towards risk. Our findings are twofold. First, we show that the hypotheses of efficiency, rationality, and representative agent do not hold in reproducing stock market dynamics. Second, investor sentiment affects stock returns significantly and non-linearly, but its effects vary with the market conditions. Indeed, the market appears predominated by fundamental investors in the first regime. In the second regime, investor sentiment effect is positively activated, increasing stock returns; however, when their overconfidence sentiment exceeds some threshold, this effect becomes inverse in the third regime for a high threshold level of market confidence and investor over-optimism.     

Stock return autocorrelations and predictability in the Chinese stock market—Evidence from threshold quantile autoregressive models

This paper applies the threshold quantile autoregressive model to study stock return autocorrelations and predictability in the Chinese stock market from 2005 to 2014. The results show that the Shanghai A-share stock index has significant negative autocorrelations in the lower regime and has significant positive autocorrelations in the higher regime. It attributes that Chinese investors overreact and underreact in two different states. These results are similar when we employ individual stocks. Besides, we investigate stock return autocorrelations by different stock characteristics, including liquidity, volatility, market to book ratio and investor sentiment. The results show autocorrelations are significantly large in the middle and higher regimes of market to book ratio and volatility. Psychological biases can result into return autocorrelations by using investor sentiment proxy since autocorrelations are significantly larger in the middle and higher regime of investor sentiment. The empirical results show that predictability exists in the Chinese stock market.     

Stochastic investor sentiment,crowdedness and deviation of asset prices from fundamentals

This study constructs a theoretical model to address how stochastic investor sentiment affects investor's crowdedness, and how stochastic investor sentiment and crowdedness affect asset prices. An asset pricing model incorporating stochastic investor sentiment and crowdedness is developed, which can provide efficient explanations for the deviations of asset prices from fundamentals and the maverick risk of investors. This model indicates that the optimistic (pessimistic) investor sentiment and the long (short) crowdedness caused by optimistic (pessimistic) sentimental investors can push asset price above (below) fundamental value. Also, the sentimental investors who are wrong and alone would take the maverick risk. Our results are consistent with the idea that investor sentiment and investor behavior matter for the asset prices and the deviations of asset prices from fundamentals.     

Investor sentiment and the financial crisis: a sentiment-based portfolio theory perspective

The article proposes a portfolio model subjected to a constraint that captures the investor’s goal, with maximum estimation of expected return that is affected by investor sentiment. And we give a solution of the portfolio model by exploring the geometric features. Furthermore, we discuss the relationship between investor sentiment and the financial crisis by analysing the optimal allocation. The results show that: when investor sentiment is low enough, the investor should reject the investment, this condition leads the depression financial market to prevail, then the financial crisis erupts; when investor sentiment is modest, the financial crisis is difficult to erupt unless the decline of investor sentiment is quick and deep; but there is a special status that the financial crisis is caused by other factors rather than by investor sentiment; and only improving investor sentiment cannot move away from the financial crisis.     

Dynamic sentiment asset pricing model

Conventional wisdom suggests that the equilibrium stock price is not affected by investor sentiment, and the equilibrium price at an early time is higher than the one at a later time. In contrast to this wisdom, we present a dynamic asset pricing model with investor sentiment and we find that investor sentiment has a significant impact on the equilibrium stock price. The equilibrium stock price, which is affected by pessimistic sentiment at time 0, may be lower than the one at time 1. Moreover, consistent with the reality stock market, our model shows that time varying sentiments can lead to various price changes. Finally, the model could offer a partial explanation for the financial anomaly of high volatility.     

Investor sentiment,variance risk premium and delta-hedged gains

Delta-hedged gains are supposed to be negative and represent a volatility risk premium. Using a sample of Standard & Poor 500 index options from 2006 to 2009, this study documents two anomalies that cannot be explained by the volatility risk premium. First, delta-hedged gains are more negative for out-of-money options than for at-the-money options. Second, delta-hedged gains are significantly positive during financial crisis period. We propose a behavioural explanation in which both option prices and stock prices are affected by investor’s sentiment, but pessimistic sentiment has a greater impact on stock market than option market. This asymmetric response to pessimistic mood in turn affects the relative expensiveness of option prices.     

Daily happiness and stock returns: The case of Chinese company listed in the United States

Existing literature exclusively focuses on the association between local investor sentiment and local stock market performance. In this paper, we investigate the contemporaneous and the lead-lag relationship between local daily happiness sentiment extracted from Twitter and stock returns of cross-listed companies, i.e., the Chinese companies listed in the United States. The empirical results show that: 1) by respectively controlling for the firm capitalization, liquidity and volatility, there exists the largest skewness on the Most-happiness subgroup. (2) There exist bi-directional relationships between daily happiness sentiment and market variables, i.e., the stock return, range-based volatility and excess trading volume. (3) There are significantly positive stock returns, higher excess trading volume and higher range-based volatility around the daily happiness sentiment spike days. These findings not only suggest that there exists significant interdependence between online activities and stock market dynamics, but also provide evidence for the existence of “home bias”.     

卖空障碍、投资者情绪与股票价格异象

利用2003年1月至2011年12月我国沪深两市A股上市公司的月度数据,采用月调整组合方式,分别利用双变量T检验法和资本资产定价模型检验中国股票市场中"价格异象"的存在性,利用相关分析法检验了价格异象不属于小公司异象,利用Tobit模型研究个人投资者持股的决定因素,采用主成分分析法构造投资者情绪指数,分析投资者情绪、卖空障碍与价格异象之间的关系。研究结果显示:股票价格越低,个人投资者持股比例越高;投资者情绪和卖空障碍是导致价格异象的主要原因。     

Changes in Investors' Market Attention and Near-Term Stock Market Returns

We use Google Search volume to track changes investors' positive and negative market attention. Our results support the hypothesis that this information reflects investors' optimistic and pessimistic anticipation and can be used to predict near-term future returns. We find that changes in negative search term volume of “market crash” and “bear market” and changes in positive search term volume “market rally” explain near-term stock returns. Changes in investors' attention are partly related to past stock market returns, implying that investors are prone to pay attention to possible price reversals. These measures of market attention are potential gauges of investor sentiment.     

Two centuries of bull and bear market cycles

Very few economic phenomena attract more attention than bull and bear market cycles do, and there is also agreement that bull markets are associated with persistently rising share prices, strong investor interest, and enhanced financial well-being. This paper identifies bull and bear market turning points using a formal turning-point identification procedure and finds that the bull and bear market phases are associated with distinct and persistent mean return shifts. The analysis highlights return evidence that distinguishes bull markets as distinct investment return regimes. The paper also emphasizes the properties of bull markets that can be important to investors, including the persistence of return differences between bull and bear markets as well as interrelationships amongst bull markets and investor interest.     

A nonlinear Granger causality test between stock returns and investor sentiment for Chinese stock market: a wavelet-based approach

In this article, we re-examine the causality between the stock returns and investor sentiment in China. The number of net added accounts is used as a proxy for investor sentiment. To mimic the different investment horizons of market participants, we use the wavelet method to decompose stock returns and investor sentiment into time series with different frequencies. Additionally, we test for nonlinear causal relationships based on Taylor series approximation. Our results indicate that there is a one-directional linear causality from stock returns to investor sentiment on the original series, while there is a strong bi-directional nonlinear causality between stock returns and investor sentiment at different timescales.     

总投资和未来收益率的长期关系及影响机制*——基于贝叶斯估计方法的实证分析

本文利用2000—2015年中国上市公司季度数据,采用贝叶斯估计方法实证研究总投资和未来收益率间的长期关系,并从投资者情绪视角探究了二者间的微观影响机制。实证结果显示：第一,短期内总投资的不断增加导致了未来收益率的下降,并且这种负向作用长期内显著增加;第二,在总投资能预期到现金流冲击的情况下,投资者情绪因素解释了总投资与未来收益率间的负向效应问题。     

Investor sentiment,trading behavior and stock returns

This article examines how investor sentiment and trading behaviour affect asset returns. By analysing the unique stock trading dataset of the Korean market, we find that high investor sentiment induces higher stock market returns. We also find that institutional (individual) trades are positively (negatively) associated with stock returns, suggesting the information superiority (inferiority) of institutional (individual) investors. Investor sentiment generally plays a more important role in explaining stock market returns than investor trading behaviour.     

投资者情绪、股票市场流动性和经济增长

采用2000—2009年的GDP、股票市场流通市值以及交易值的季度数据,从实证角度对此时段的投资者情绪、股票市场流动性和资本化率进行计量分析,通过ADF单位根检验、Johansen协整检验及Granger因果检验研究投资者情绪、股票市场流动性和股票市场发展之间的关系,进而揭示了投资者情绪影响经济增长的途径。结果显示,投资者情绪和股票市场流动性是经济增长的格兰杰原因。     

A Report on the March 2001 Investor Sentiment Survey

Steep declines in the value of publicly traded stocks in the first quarter of 2001 left many market observers speculating whether investor sentiment had undergone a significant and negative change, and whether investors would subsequently flee stocks in favor of less volatile investment options. A survey study of investor expectations and confidence was conducted in late March 2001 to capture investor sentiment and compare it with similar measures taken in surveys conducted in 1998 during a period of rapid market incline. The surprising results are that there are only minor differences in investor sentiment in terms of: (a) confidence in the long and intermediate performance of the stock markets; (b) composition of stocks versus bonds in their portfolios; (c) the intention to buy on the dips; (d) the amount of risk investors plan to undertake. The high level of investor confidence observed in 2001 (in spite of a severe drop in market value) is potentially accounted for by psychological processes that influence investor judgment. These processes include reliance on image-driven affective evaluations of common stocks that contribute to excessive optimism.     

Googling Investor’s Sentiment: Powerful Measure in Conventional and Islamic MENA Financial Markets

ABSTRACT

The objective of this paper is to investigate whether investors' sentiment measured by the Internet search behavior constitutes a valid measure of investor’s sentiment on Islamic and conventional indexes of emerging and frontier financial markets in MENA countries. In fact, we examine the relation between googling investor’s sentiment and monthly Islamic and conventional index returns during the period 2004–2016. Using the Dynamic Conditional Correlation, the BEKK-GARCH and the wavelet coherence models, we confirm that googling investor’s sentiment is a perfect indicator of investor’s sentiment measure. Indeed, we find that this measure has the ability to reflect major events such as subprime financial crisis, oil crisis and Arab spring revolution affecting MENA Islamic and conventional index markets. Our finding indicates that investors can use googling investor’s sentiment as an indicator to predict returns and volatility of emerging and frontier markets since it reflects the behavior and emotions of investors in MENA financial markets.     

Home is Where You Know Your Volatility – Local Investor Sentiment and Stock Market Volatility

Using a new variable to measure investor sentiment we show that the sentiment of German and European investors matters for return volatility in local stock markets. A flexible empirical similarity (ES) approach is used to emulate the dynamics of the volatility process by a time‐varying parameter that is created via the similarity of realized volatility and investor sentiment. Out‐of‐sample results show that the ES model produces significantly better volatility forecasts than various benchmark models for DAX and EUROSTOXX. Regarding other international markets no significant difference between the forecasts can be observed.     

Does mixed-frequency investor sentiment impact stock returns? Based on the empirical study of MIDAS regression model

We examine whether mixed-frequency investor sentiment affects stock returns. In line with recent evidence from China, we find that the aggregate effect and the individual effect of mixed-frequency investor sentiment are statistically significant, and mixed-frequency investor sentiment is more important than the low-frequency one. Moreover, mixed-frequency investor sentiment, which is mixed by high-frequency data, can be more important than the market premium.     

私募股权投资、投资者情绪与科技型企业R&D投入

根据2009-2017年深圳证券交易所科技型上市企业相关面板数据,研究私募股权投资、投资者情绪与企业R&D投入之间的关系。研究发现：存在私募股权投资的科技型企业R&D投资强度更大;投资者情绪在私募股权投资与企业R&D投入之间起中介效应,即存在私募股权投资的科技型企业的投资者情绪更为高涨,高涨的投资者情绪会促使企业加大R&D投入。企业异质性检验发现,不同于国有企业和外资企业,民营企业的投资者情绪在私募股权投资与研发投入中的中介效应更加显著,并且处于不同生命周期的企业,无论是年轻企业还是成熟企业,投资者情绪的中介效应均不显著。将投资者情绪纳入分析框架,深入研究私募股权投资对企业研发活动的影响,对私募股权投资机构、企业、政府等进行科学决策具有重要理论价值和实践意义。     

Where does return and volatility come from? The case of Asian ETFs

We analyze return and volatility of Asian iShares traded in the U.S. The difference in trading schedules between the U.S. and Asia offers a unique market setting that allows us to distinguish various return and volatility sources. We find Asian ETFs have higher overnight volatility than daytime volatility, explained by public information released during each local market's trading session. Local Asian markets also play an important role in determining each Asian ETF return. Nonetheless, returns for these funds are highly correlated with U.S. markets, indicative of the effects of investor sentiment and location of trade. Finally, returns in the U.S. market Granger-cause returns in all six Asian markets are analyzed.