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.     

The Impact of U.S. Individual and Institutional Investor Sentiment on Foreign Stock Markets

This study examines the degree to which U.S. individual and institutional investor sentiments are propagated abroad. Previous studies construe investor sentiments as fully irrational; we find contrary evidence that individual and institutional investor sentiments are driven by both rational and irrational factors, with distinct effects on domestic and international stock market returns. The generalized impulse response functions from VAR model estimations show that U.S. institutional investor sentiments have varying degrees of impact on the equity markets of the U.K., Mexico, and Brazil, and no effect on Chile. Specifically, the individual investor sentiment effect is statistically significant only for the U.K market. Not surprisingly, the two classes of investor sentiments have a strong significant effect on the U.S. stock market returns. The response of the U.S. to individual investor sentiments is relatively more erratic, while the response to institutional investor sentiments is smoother. This difference in pattern becomes more visible when we consider the response of the foreign stock markets. We find significant effects of rational sentiments of institutional investors on the U.S., the U.K., Mexico, and Brazil. However, there is an insignificant effect of the irrational sentiments on the same set of countries. A direct implication of our empirical evidence is that it is important for international asset pricing models to consider the role of rational sentiments of institutional and individual investors on developed and emerging markets.     

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.     

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.     

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.     

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.     

Beauty contest,bounded rationality,and sentiment pricing dynamics

We present a dynamic asset pricing model that incorporates investor sentiment, bounded rationality and higher-order expectations to study how these factors affect asset pricing equilibrium. In the model, we utilize a two-period trading market and investors make decisions based on the heterogeneous expectations principle and the “sparsity-based bounded rational” sentiment. We find that bounded rationality results in mispricing and reduces it in next period. Investor sentiment produces more significant effects than private signals, optimistic investor sentiment increases hedging demand, thus causing prices to soar. Higher-order investors are more rational and attentive to the strategies of other participants rather than private signals. This model also derives the dampening effect of higher-order expectations to price volatility and the heterogeneity expectation depicts inconsistent investor behavior in financial markets. In the model, investors' expectations about future price is distorted by their sentiment and bounded rationality, so they obtain a biased mean from the signal extraction.     

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。     

Sentiment asset pricing model with consumption

We present an asset pricing model by incorporating investor sentiment. The sentiment equilibrium price could be decomposed to the rational term and the sentiment term, and the investor sentiment has a systematic and significant impact on the risky asset price. In the model, the sentiment term has a wealth-weighted average structure and the investor's wealth proportion could amplify the sentiment shock on the asset price. The model could offer a partial explanation of some financial anomalies in the stock market: the phenomenon of savings transfer to the stock market, pricing bubble and high volatility.     

The cross-section and time-series effects of individual stock sentiment on stock prices

In this article, we construct an individual stock sentiment index by using the principal component analysis method. We empirically study the cross-section and time-series effects of investor sentiment on the stock prices based on the panel data model with dummy variable. The results indicate that individual stock sentiment has greater impact on small-firm stock prices than big-firm stock prices, which presents obvious cross-section effect. Moreover, individual stock sentiment leads to much sharper ?uctuations of stock prices in the stock market downturn than in the stock market expansion, which shows obvious time-series effect. Specifically, the individual stock sentiment has the greatest impact on small-firm stock prices under the stock market downturn, exerting significant dual asymmetric effect. Our results are helpful to understanding the micro-mechanism of sentiment effect.     

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.     

投资者情绪、股票错误估值与上市公司投资简

以剩余收益估值模型衡量股票错误估值程度,基于公司层面测度投资者情绪,利用非平衡面板数据模型检验投资投资者情绪如何通过证券市场传导到上市公司从而影响其实际投资行为。实证研究发现,投资者情绪主要通过直接的迎合渠道而非间接的股权融资渠道影响上市公司投资行为,且公司投资在迎合渠道上表现出对投资者情绪的“反迎合机制”,此外不同特征的公司其投资对投资者情绪的敏感度存在横截面差异。     

Does investor sentiment dynamically impact stock returns from different investor horizons? Evidence from the US stock market using a multi-scale method

This article uses the investor sentiment index to investigate the Granger causality between investor sentiment and stock returns for the US economy using a multi-scale method. To focus on the local analysis of different investor horizons, bivariate empirical mode decomposition is used to decompose time series of investor sentiment and stock returns at different timescales. We employ the linear and nonlinear integrated Granger causality method to examine the causal relationship of decomposed series on similar timescales. The results indicate both strong bilateral linear and nonlinear causality between longer-term investor sentiment and stock returns. However, there is no strong evidence for correlation of stock returns and investor sentiment on shorter timescales.     

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.     

Investor sentiment and the prediction of stock returns: a quantile regression approach

We employ quantile regression to provide a detailed picture of the stock return forecasting ability of investor sentiment. We find that investor sentiment predicts aggregate stock returns at lower quantiles. However, the forecasting power is lost at upper quantiles. The results are robust after controlling for a comprehensive set of macroeconomic and financial predictors and for characteristic portfolios. We also show that investor sentiment consists mainly of cash flow news and contains little information about discount rate news. The ability to forecast cash flows increases gradually from the lower quantiles to upper quantiles. Our results do not support that the ability of investor sentiment to predict stock returns comes from a rational forecast of future cash flows.     

The importance of fear: investor sentiment and stock market returns

The presence of investor sentiment pushes asset prices away from the equilibrium level justified by underlying fundamentals. While sentiment is not directly observable, identifying appropriate proxies and, quantifying the impact of sentiment on asset prices is an important topic. Asset prices that do not appropriately reflect fundamental values may result in inefficient allocation of capital – impacting portfolio allocation decisions and the cost of capital. Utilizing a number of sentiment proxies, over the period 1990–2015, we demonstrate a strong relationship between investor sentiment and stock returns that is consistent with theoretical explanations of sentiment. We determine that implied volatility index (VIX) is the preferred measure of sentiment in terms of improving model fit and adding explanatory power. Causality tests suggest that investor fear (VIX) drives returns across firm-size and value, and also across industry. We also illustrate that firms that are more subjective to value, or face limits to arbitrage, such as small-cap stocks, or those in the business equipment (technology) or telecoms industry, are most responsive to changes investor sentiment. Finally, we demonstrate that sentiment has a greater influence on market returns during recession, when sentiment is at its lowest ebb, and this is particularly true for those stocks most susceptible to speculative demand.     

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。     

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.     

Overreaction to extreme market events and investor sentiment

This article investigates the role of investor psychology, captured here by investor sentiment index, in driving individual stock price reactions to extreme movements in the broader market. In addition to confirming prior evidence of overreaction, we find much stronger overreaction when investor sentiment is low rather than high. This is consistent with the role of the contrast dimension of an uncommon event, suggested in the psychology literature, over and above the emotion of surprise it brings about. In a low sentiment environment, the contrast is sharper and hence leads to stronger overreaction.     

The asymmetric effects of investor sentiment and monetary policy on stock prices

We examine the impact of investor sentiment and monetary policy on the stock prices under different market states based on the Markov-switching vector autoregression (MS-VAR) model. The results show that the sentiment shocks, more than monetary policy shocks, lead to not only much larger fluctuations of stock prices but also much longer duration in the stock market downturn than in the stock market expansion, which shows obvious asymmetric effect. Moreover, the responses of stock prices to the sentiment shocks present an immediate effect, while the responses of stock prices to the monetary policy shocks show one-period lag effect.