Investor Pessimism and the German Stock Market: Exploring Google Search Queries

We analyze the relationship of retail investor sentiment and the German stock market by introducing four distinct investor pessimism indices (IPIs) based on selected aggregate Google search queries. We assess the predictive power of weekly changes in sentiment captured by the IPIs for contemporaneous and future DAX returns, volatility and trading volume. The indices are found to have individually varying, but overall remarkably high explanatory power. An increase in retail investor pessimism is accompanied by decreasing contemporaneous market returns and an increase in volatility and trading volume. Future returns tend to increase while future volatility and trading volume decrease. The outcome is in line with the conjecture of correction effects. Overall, the results are well in line with modern investor sentiment theory.     

Time-varying relationship of news sentiment,implied volatility and stock returns

I examine the relationship between aggregate news sentiment, S&P 500 index (SPX) returns, and changes in the implied volatility index (VIX). I find a significant negative contemporaneous relationship between changes in VIX and both news sentiment and stock returns. This relationship is asymmetric whereby changes in VIX are larger following negative news and/or stock market declines. Vector autoregression (VAR) analysis of the dynamics and cross-dependencies between variables reveals a strong positive relationship between previous and current period changes in implied volatility and stock returns, while current period and lagged news sentiment has a significant positive (negative) relationship with stock returns (changes in VIX). I develop a simple trading strategy whereby high (low) levels of implied volatility signal attractive opportunities to take short (long) positions in the underlying index, while extremely negative (positive) news sentiment signals opportunities to enter short (long) index positions. The investor fear gauge (VIX) appears to perform better than news sentiment measures in forecasting future returns.     

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.     

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.     

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.     

On the detection of extreme movements and persistent behaviour in Mediterranean stock markets: a wavelet-based approach

We combine the global Hurst exponent and Morlet wavelet multi-resolution analysis (MRA) to investigate the dynamic behaviour of six selected stock markets in the Mediterranean region. Specifically, we employ the resonance coefficients and their power spectra to identify potential extreme movements and long-term dependence in stock returns. Using weekly data for the period 2005 to 2010, our results reveal that the wavelet MRA is able to reconstruct the effects of major extreme shocks on stock returns of studied markets, such as the Asian financial crisis, the 9/11 terrorist attacks and the 2007–2009 financial crisis. Moreover, the wavelet-based global Hurst exponent indicates the presence of long-term dependencies in stock returns of all the considered markets, except for France where the anti-persistent behaviour is detected. Overall, our findings are useful to assess the stock market efficiency and provide new insights into stock market dynamics over different time scales.     

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.     

Daily market news sentiment and stock prices

In recent years there has been a tremendous growth in readily available news related to traded assets in international financial markets. This financial news is now available through real-time online sources such as Internet news and social media sources. The increase in the availability of financial news and investor’s ease of access to it has a potentially significant impact on market stock price movement as these news items are swiftly transformed into investors sentiment which in turn drives prices. In this study, we use the Thomson Reuters News Analytics (TRNA) data set to construct a series of daily sentiment scores for Dow Jones Industrial Average (DJIA) stock index constituents. We use these daily DJIA market sentiment scores to study the influence of financial news sentiment scores on the stock returns of these constituents using a multi-factor model. We augment the Fama–French three-factor model with the day’s sentiment score along with lagged scores to evaluate the additional effects of financial news sentiment on stock prices in the context of this model using Ordinary Least Square (OLS) and Quantile Regression (QR) to analyse the effect around the tail of the return distribution. We also conduct the analysis using the seven-day simple moving average (SMA) of the scores to account for news released on non-trading days. Our results suggest that even when market factors are taken into account, sentiment scores have a significant effect on Dow Jones constituent returns and that lagged daily sentiment scores are often significant, suggesting that information compounded in these scores is not immediately reflected in security prices and related return series. The results also indicate that the SMA measure does not have a significant effect on the returns. The analysis using Quantile Regression provides evidence that the news has more impact on left tail compared to the right tail of the returns.     

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.     

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.     

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.     

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”.     

Time-varying dependence structures of equity markets of China,ASEAN and the USA

Popular time-varying Copulas are used to analyse the dependence structure between the CSI 300 index return, the S&P 300 index return and the Association of South East Asian Nations (ASEAN) 80 index return. Results show that these three types of stock index returns have obvious time-varying characteristics. The US sub-prime mortgage crisis has strengthened the correlation among the three-stock index returns, whereas the dependence between China and the ASEAN stock markets is more sensitive to the financial crisis. The time-varying features of the extreme dependence risk between China-ASEAN and China-US are very different.     

How are Africa's emerging stock markets related to advanced markets? Evidence from copulas

The finance literature provides ample evidence that diversification benefits hinges on dependence between assets returns. A notable feature of the recent financial crisis is the extent to which assets that had hitherto moved mostly independently suddenly moved together resulting in joint losses in most advanced markets. This provides grounds to uncover the relative potential of African markets to provide diversification benefits by means of their correlation with advanced markets. Therefore, we examine the dependence structure between advanced and emerging African stock markets using copulas. Several findings are documented. First, dependence is time-varying and weak for most African markets, except South Africa. Second, we find evidence of asymmetric dependence, suggesting that stock return comovement varies in bearish and bullish markets. Third, extreme downward stock price movements in the advanced markets do not have significant spillover effects on Africa’s emerging stock markets. Our results, implying that African markets, with the exception of South Africa, are immune to risk spillover from advanced markets, improves the extant literature and have implications for portfolio diversification and risk management.     

Dynamic asset pricing model with heterogeneous sentiments

The systematic and important role of investor sentiment has been supported by some recent empirical and theoretical literatures. In this paper, we present a dynamic asset pricing model with heterogeneous sentiments and we find that the equilibrium stock price is the wealth-share-weighted average of the stock prices that would prevail in an economy with one sentiment investor only. Moreover, heterogeneous sentiments induce fluctuations in the wealth distribution, which increases stock return volatility and induces mean reversion in stock returns. The model offers a partial explanation for the financial anomaly of mean reversion.     

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.     

Price Clustering and Investor Sentiment

Among the anomalous findings in the finance literature, perhaps the most persistent is the finding that security prices tend to cluster on round pricing increments. The author examines how investor sentiment influences the degree of price clustering. Both univariate and multivariate tests show a contemporaneous correlation between price clustering and investor sentiment. Recognizing the need to make stronger causal inferences, the author conducts 2 additional sets of tests. First, the author uses the technology bubble period as natural experiment and examine the price clustering of technology vis-à-vis nontechnology stocks. Results show that price clustering is markedly higher in tech stocks than in nontech stocks during this period of rising, sector-specific, investor sentiment. Second, the author estimates a vector autoregression process and examines the impulse responses of price clustering to exogenous shocks in investor sentiment. The results from these tests indicate that causation flows from sentiment to clustering instead of the other way around.     

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.     

How index investment impacts commodities: A story about the financialization of agricultural commodities

This paper focuses on the impact of financial investors on agricultural prices, a phenomenon known as the financialization. In this aim, we check whether financial mechanisms drive extreme values and the mean of agricultural returns in the same way. Relying on the Threshold AutoRegressive Quantile (TQAR) methodology, we find evidence of reinforcement linkages between equity and agricultural markets since 2004, corresponding to the rise in inflows of institutional investors in commodity markets. These results show that agents impact more deeply commodity markets when the commodity index value is high. In addition, in extreme quantiles (0.75 and 0.90) of agricultural returns, the relationship between agricultural and stock returns is always significant when the commodity index return is in the higher regime. This finding suggests that, stock markets had a greater impact on agricultural price dynamics during the extreme movements which occurred during the 2007–2008 financial crisis, highlighting a potential influence of financial markets on the financialization of commodities.     

HAVE INSTITUTIONAL INVESTORS DESTABILIZED EMERGING MARKETS?

In the past few years, there has been a large increase in portfolio capital flows into emerging markets, mostly fueled by mutual funds and other institutional investors. Based on a simple variance ratio test, this paper finds that emerging stock markets as a group experienced a sharp increase in autocorrelation in total returns at a time when institutional investors began to expand significantly their holdings in these markets. These results are consistent with the view that institutional investor sentiment toward emerging markets as an asset class can at times play a critical role in determining asset prices, with shifts in sentiment resulting in periods of bubble-like booms and busts and asset price overshooting.