Optimistic Sentiment Research Articles

Investor Sentiment and Stock Price Crash Risk: Evidence from China

ABSTRACT We study the cross-sectional effects of investor sentiment on stock price crash risk from the perspective of investor behavioural biases. We develop a firm-specific investor sentiment measure, and find that stocks with stronger investor sentiment are more prone to a future price crash. The positive relation is more pronounced for stocks eligible for margin trading, as higher investor sentiment induces greater margin buy/cover by optimistic investors. Short interest moderates the impact of optimistic sentiment on crash risk. The positive relation is also particularly prominent for stocks with a more speculative appeal, especially for those with lower institutional ownership.

Does intellectual capital have any influence on stock price crash risk?

PurposeThis paper explores the influence between intellectual capital (IC) and the risk of stock price crashes by using company performance as an intervening variable.Design/methodology/approachThis study empirically analyzes the impact of the efficiency of IC on stock price crash risk using a sample size of 152 companies listed on the Indonesia Stock Exchange (IDX) during 2018. To test the research hypotheses, regression analysis and path analysis were applied. In addition, the researchers added exploration to several studies to strengthen the results of this study.FindingsThis study’s findings indicate that investors' optimistic (pessimistic) sentiment regarding stock price volatility has obscured aspects of the financial performance of listed companies. This finding implies that investor sentiment has dominated influence on stock price crash risk so that the aspects of IC are obscured.Originality/valueThis research provides new information that IC disclosure in the stock market needs to include knowledge of the volatility of stock prices in order to reveal stock price crash risk.

Investor sentiment and predictability for volatility on energy futures Markets: Evidence from China

This research specifically reveals the predictability for the volatility on energy futures markets when involving investor sentiment, using the newly launched China’s INE crude oil futures as an incremental evidence. First, we propose a novel investor sentiment index captures the feature of instant sentiment conversion and the internet attention for energy futures markets. Second, we present the nexus between the proposed novel investor sentiment and conditional volatility, which shows that the proposed investor sentiment significantly impacts on return and volatility. It indicates that the emerging markets filled with noise traders like China are more deeply influenced by investor sentiment and bring about more volatility. Third, the results of dual leverage effects in modeling energy futures volatility shows that the optimistic (pessimistic) sentiment shift has negative(positive) effects on volatility, and downward (upward) shocks from bad news (good news) are followed by greater volatility. Fourth, incorporating the novel investor sentiment into models can significantly improve volatility forecasting accuracy because of its smaller loss function results compared with the benchmark models without sentiment. Moreover, high frequency realized volatility and range-based volatility are regarded as real volatility to examine the predictability, and Diebold Mariano test is used to present the difference of forecasting ability. Our results are robust by using the data from China’s Thermal Coal Futures. Overall, we present that the novel investor sentiment can be utilized for monitoring and predicting volatility shocks for emerging markets with lots of noise traders.

News Tone, Investor Sentiment, and Liquidity Premium

Using textual media tone as investor sentiment measure, we find that in China, firms with a more pessimistic (optimistic) news tone lead to more (less) active trading, higher (lower) depth, or spread. This negative (positive) effect of investor sentiment on trading activity or stock liquidity is robust to controlling other firm characteristics and macroeconomic conditions. We observe that the liquidity premium is significant in China, which is more pronounced across firms with an optimistic sentiment. Additionally, we decompose liquidity into the sentiment-driven and non-sentiment-driven (NSD) components and find that the NSD premium is declining. This decline stems from a higher sensitivity of sentiment to liquidity. Besides, we also find that NSD premium performs better following high economic policy uncertainty and low growth of margin trading and stocks with low shareholdings of institutional investors.

Sentiments and Real Business Cycles

We introduce sentiments under incomplete information into an otherwise standard real business cycle model. Individual firms receive signals about their idiosyncratic demand shocks which are confounded by sentiments. Sentiments coordinate optimal decisions of individuals through their extraction of the aggregate economic conditions from the signals. We show that there exists a sentiment-driven rational expectations equilibrium in addition to a fundamental equilibrium. Optimistic sentiments boost the aggregate economy, leading to positive comovements among output, consumption, investment, and hours worked. We calibrate a full-blown dynamic stochastic general equilibrium model based on U.S. aggregate data and find that sentiment shocks substantially amplify the aggregate fluctuations.

Social Media Sentiment and IPO Pricing

This study attempts to examine the impact of social media attention and sentiment on IPO pricing. Specifically, by using social media sentiment as a proxy for retail investors’ valuation, I attempt to examine the theoretical predictions in prior studies (Ljungqvist, Nanda and Sigh (2006), Cornelli, Goldreich, and Ljungqvist (2006), and Derrien (2005)) that overoptimism of sentiment investors leads to initial overpricing of IPO followed by long-term reversal. Using posts on Stocktwits during pre-IPO period, I have constructed measurements of investor attention and sentiment. The empiri- cal results are generally consistent with the theoretical predictions that retail investor overoptimism leads to higher IPO first day price run up and worse long-term perfor- mance. Additionally, using machine learning techniques to classify untagged posts, I have found similar results when sentiment measures are constructed by classified un- tagged posts. Results with sentiment measures constructed by these classified posts imply that more optimistic sentiment leads to a higher turnover rate shortly after IPO, indicating that informed investors are selling overpriced IPO shares to sentiment retail investors.

Bitcoin Sentiment Index, Bitcoin Performance and US Dollar Exchange Rate

This study introduces a comprehensive Google search volume based Bitcoin Sentiment Index (BSI) and investigates its symmetric and asymmetric association with Bitcoin's returns, volume, and volatility, and with United States Dollar (USD) exchange rates. Our results indicate a positive association of BSI with Bitcoin's returns and volume, but a negative relationship with its return volatility. Besides, Bitcoin's optimistic sentiments have an asymmetric relationship with the USD exchange rate in the short-run, and the Bitcoin price has an asymmetric and negative association with USD in the short-run and long-run. We also found a 35.47% speed of adjustment to long-run equilibrium.

The momentum and reversal effects of investor sentiment on stock prices

In this paper, we illustrate the real function relationship between the stock returns and change of investor sentiment based on the nonparametric regression model. The empirical results show that when the change of investor sentiment is moderate, the stock return is positively correlated with the change of investor sentiment, presenting an obvious momentum effect. However, the stock return is negatively correlated with the change of investor sentiment if the change of investor sentiment is dramatic, presenting significant reversal effects. Moreover, the degree of reversal effect caused by extremely optimistic sentiment is greater than that driven by extremely pessimistic sentiment, which shows a significant asymmetry. Our findings offer a partial explanation for financial anomalies such as the mean reversion of stock returns, the characteristic of slow rise and steep fall in China's stock market and so on.

The Nonlinear Relationship between Investor Sentiment, Stock Return, and Volatility

Based on the DSSW model, we analyze the nonlinear impact mechanism of investor sentiment on stock return and volatility by adjusting its hypothesis in Chinese stock market. We examine the relationship between investor sentiment, stock return, and volatility by applying OLS regression and quantile regression. Our empirical results show that the effects of investor sentiment on stock market return are asymmetric. There is “Freedman effect” in Chinese stock market, but only optimistic sentiment has a significant nonlinear impact on stock market returns when the stock market is a balanced market or a bear market. Meanwhile, “create the space effect” does exist in Chinese stock market too. It only exists when the market is in equilibrium, and only pessimistic sentiment has the nonlinear effect on stock market volatility.

The Influence of Classroom Illumination Environment on the Efficiency of Foreign Language Learning

This paper investigated foreign language learning efficiency in four different illumination environments (in different illuminance and color temperatures), focusing on the influence of the illumination environment on foreign language learners’ sentimental status, by means of foreign language skills testing in mind-map, objective evaluation of physiological reaction, and subjective evaluation of psychological reaction. It was shown that in different illumination environments, the language skills of foreign language learners were different, and their psychological and physiological reactions varied, which influenced the efficiency of foreign language learning. The results indicated that the ideal learning space was in high illuminance and low color temperature, which increased the stimulation in foreign language learners; promoted the formation of optimistic sentiment; and enhanced their interest in, and the quality and efficiency of, foreign language learning.

Sentiment and Technical Analysis

This paper studies the effectiveness of technical trading approaches in market environments of varying sentiment. Due to short-sale constraints, overpricing with high sentiment (i.e. relatively optimistic sentiment) is more prevalent compared to underpricing with low sentiment (i.e. relatively pessimistic sentiment) and this effect is stronger on difficult-to-arbitrage securities. The authors find consistent evidence over the period of 1993-2010 that the examined set of technical indicators perform better during periods of high sentiment than during periods of low sentiment. Moreover, this sentiment effect is relatively more pronounced for small stocks. These findings hold after a number of robustness checks are applied and highlight the importance of incorporating the sentiment effect when using technical indicators.

The Relationship between Hedge Fund Performance and Stock Market Sentiment

We examine the dynamic effect of aggregate stock market sentiment on the performance of various hedge fund styles. We find that hedge funds typically perform better during periods of optimistic sentiment and that for different hedge fund styles there is a differential response of hedge fund returns to positive and negative sentiment shocks. We also find that changes in aggregate investor sentiment have a larger effect on hedge fund performance during periods of high conditional volatility. Our results suggest there is a strong asymmetry in the relationship between hedge fund performance and investor sentiment.

Overconfidence, Sentiment and Beta Herding: A Behavioral Explanation of the Low-Beta Anomaly

We investigate asset returns using the concept of beta herding, which measures cross-sectional variations in betas induced by investors whose beliefs about the market are biased due to changes in confidence or sentiment. Overconfidence or optimistic sentiment causes beta herding (compression of individual assets’ betas towards the market beta), while under-confidence or pessimistic sentiment leads to adverse beta herding (dispersion of betas away from the market beta). We find that beta herding is related to the low-beta anomaly, as high beta stocks underperform low beta stocks on a risk-adjusted basis exclusively following periods of adverse beta herding. As an explanation of the low-beta anomaly, we propose the persistence of bias in betas (i.e., a large difference in betas) that lasts for more than one year as market uncertainty continues.

An Innovative Sentiment Analysis to Measure Herd Behavior

We propose an innovative and forward-looking method to examine investor herd behavior and identify fundamental-driven spurious herding. A sentence-based sentiment analysis approach is conceived to automatically extract attitudes or emotions from textual documents. Then we build a mathematical model to discern herd behavior by exploiting the sentiment indices. Empirical tests in the Chinese stock market indicate that there exists significant true herd behavior among blue-chips. Investors with pessimistic sentiment are more likely to herd than those with optimistic sentiment. Moreover, macroeconomic information tends to play a dominant role in the decision-making processes, and the lack of rapid and efficient firm-specific information enables people to herd around the market consensus.

Do Sentiment and Exchange Rate Share Memories? An Application of Multifractional Process Modeling

We use the notion of local Holder regularity to investigate the roughness of the pattern of EUR/USD exchange rate process as well as the corresponding investor sentiment dynamic process. Specifically, we use the pointwise Holder exponent to measure the local Holder regularity of a multifractional process. This application extends the increment ratio method to estimate the pointwise Holder exponent of multifractional Brownian motion function. Our testing and comparison results show that both the exchange rate and the sentiment proxy's local Holder regularities are time-varying and are more homogeneous during crises periods. More importantly, in contrast to the optimistic sentiment, the roughness of the pessimistic sentiment dynamic process displays only slightly higher similarity to that of EUR/USD exchange rate. These results suggest that the EUR/USD exchange rate process and the pessimistic sentiment dynamic process share a common pattern of smoothness, which implies that they share a similar memory pattern.

Sentiment and the Performance of Technical Indicators

This article studies the effectiveness of technical trading approaches in market environments of varying sentiment. Because of short-sale constraints, overpricing with high sentiment (i.e., relatively optimistic sentiment) is more prevalent compared to underpricing with low sentiment (i.e., relatively pessimistic sentiment), and this effect is stronger on difficult-to-arbitrage securities. The authors find consistent evidence over the period from 1993 to 2010 that the examined set of technical indicators perform better during periods of high sentiment than during periods of low sentiment. Moreover, this sentiment effect is relatively more pronounced for small stocks. These findings hold after a number of robustness checks are applied, and they highlight the importance of incorporating the sentiment effect when using technical indicators.

Mainstream Versus Heterodox View on Financial Innovation

There is much controversy surrounding something what is conventionally called ?financial innovation?. Yet, it should be in any case seen as a relatively substantial element in the functioning of modern economies. However, its general impact should be assessed from quite different perspectives, depending on its particular behavior, and subsequently, the role it plays in an economy. In terms of economic fluctuations, financial innovations are frequently assessed based on the cycle amplitude. The amplitude may typically be determined by efforts to evade a regulatory framework set by a central authority in the country. Most importantly, this contribution follows either Post Keynesian or Regulation School logic, trying to clarify business cycle volatility with respect to the intensity of innovative activities in the financial sector. At the same time, it also strives to specify the most important standpoints of contemporary mainstream economics. Its main conclusion is that higher intensity of financial innovation usually leads to a higher volatility of the business cycles, namely due to excessive pessimistic or optimistic sentiment and influx of supplementary credit. Additionally, at times it may also lead to so called self-fulfilling prophecy, which itself contributes to the major vector direction of the economy.

Mainstream Versus Heterodox View on Financial Innovation

Abstract There is much controversy surrounding something what is conventionally called “financial innovation”. Yet, it should be in any case seen as a relatively substantial element in the functioning of modern economies. However, its general impact should be assessed from quite different perspectives, depending on its particular behavior, and subsequently, the role it plays in an economy. In terms of economic fluctuations, financial innovations are frequently assessed based on the cycle amplitude. The amplitude may typically be determined by efforts to evade a regulatory framework set by a central authority in the country. Most importantly, this contribution follows either Post Keynesian or Regulation School logic, trying to clarify business cycle volatility with respect to the intensity of innovative activities in the financial sector. At the same time, it also strives to specify the most important standpoints of contemporary mainstream economics. Its main conclusion is that higher intensity of financial innovation usually leads to a higher volatility of the business cycles, namely due to excessive pessimistic or optimistic sentiment and influx of supplementary credit. Additionally, at times it may also lead to so called self-fulfilling prophecy, which itself contributes to the major vector direction of the economy.

Financial Market in August 2013

In August 2013, the MICEX index saw a monthly fall of 2.4% after Sberbank and VTB encountered some downtrend in the stock market. Furthermore, stock market capitalization contracted by 2.2% to Rb 23.41 trillion, or 37.4% of GDP. The domestic corporate bond market was governed by fairly optimistic sentiments, irrespective of adverse trend concerning macroeconomic indicators and forecasts for Russia. The key market indicators were driven by an uptrend, contrary to expectations of a seasonal downtrend.

Alpha Momentum and Price Momentum

We analyze a novel alpha momentum strategy that invests in stocks based on three-factor alphas. In contrast to the common price momentum strategy, our ranking accounts only for this stock-specific component which we estimate using daily returns. The empirical analysis for the U.S. and for Europe shows that i) past alpha has power in predicting the cross-section of stock returns, ii) alpha momentum exhibits less dynamic factor exposures than price momentum and iii) alpha momentum dominates price momentum only in the U.S. Connecting both strategies to behavioral explanations, alpha momentum is more related to an underreaction to firm-specific news while price momentum is primarily driven by price overshooting due to momentum trading. In addition, both strategies are more profitable following periods of optimistic sentiment which can be explained by impediments to the short-selling of loser stocks in the U.S. and by increased momentum trading in winner stocks in Europe.