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Article
Publication date: 18 May 2021

Prajwal Eachempati and Praveen Ranjan Srivastava

A composite sentiment index (CSI) from quantitative proxy sentiment indicators is likely to be a lag sentiment measure as it reflects only the information absorbed in the…

Abstract

Purpose

A composite sentiment index (CSI) from quantitative proxy sentiment indicators is likely to be a lag sentiment measure as it reflects only the information absorbed in the market. Information theories and behavioral finance research suggest that market prices may not adjust to all the available information at a point in time. This study hypothesizes that the sentiment from the unincorporated information may provide possible market leads. Thus, this paper aims to discuss a method to identify the un-incorporated qualitative Sentiment from information unadjusted in the market price to test whether sentiment polarity from the information can impact stock returns. Factoring market sentiment extracted from unincorporated information (residual sentiment or sentiment backlog) in CSI is an essential step for developing an integrated sentiment index to explain deviation in asset prices from their intrinsic value. Identifying the unincorporated Sentiment also helps in text analytics to distinguish between current and future market sentiment.

Design/methodology/approach

Initially, this study collects the news from various textual sources and runs the NVivo tool to compute the corpus data’s sentiment polarity. Subsequently, using the predictability horizon technique, this paper mines the unincorporated component of the news’s sentiment polarity. This study regresses three months’ sentiment polarity (the current period and its lags for two months) on the NIFTY50 index of the National Stock Exchange of India. If the three-month lags are significant, it indicates that news sentiment from the three months is unabsorbed and is likely to impact the future NIFTY50 index. The sentiment is also conditionally tested for firm size, volatility and specific industry sector-dependence. This paper discusses the implications of the results.

Findings

Based on information theories and empirical findings, the paper demonstrates that it is possible to identify unincorporated information and extract the sentiment polarity to predict future market direction. The sentiment polarity variables are significant for the current period and two-month lags. The magnitude of the sentiment polarity coefficient has decreased from the current period to lag one and lag two. This study finds that the unabsorbed component or backlog of news consisted of mainly negative market news or unconfirmed news of the previous period, as illustrated in Tables 1 and 2 and Figure 2. The findings on unadjusted news effects vary with firm size, volatility and sectoral indices as depicted in Figures 3, 4, 5 and 6.

Originality/value

The related literature on sentiment index describes top-down/ bottom-up models using quantitative proxy sentiment indicators and natural language processing (NLP)/machine learning approaches to compute the sentiment from qualitative information to explain variance in market returns. NLP approaches use current period sentiment to understand market trends ignoring the unadjusted sentiment carried from the previous period. The underlying assumption here is that the market adjusts to all available information instantly, which is proved false in various empirical studies backed by information theories. The paper discusses a novel approach to identify and extract sentiment from unincorporated information, which is a critical sentiment measure for developing a holistic sentiment index, both in text analytics and in top-down quantitative models. Practitioners may use the methodology in the algorithmic trading models and conduct stock market research.

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Article
Publication date: 31 October 2018

Divya Aggarwal and Pitabas Mohanty

The purpose of this paper is to analyse the impact of Indian investor sentiments on contemporaneous stock returns of Bombay Stock Exchange, National Stock Exchange and…

Abstract

Purpose

The purpose of this paper is to analyse the impact of Indian investor sentiments on contemporaneous stock returns of Bombay Stock Exchange, National Stock Exchange and various sectoral indices in India by developing a sentiment index.

Design/methodology/approach

The study uses principal component analysis to develop a sentiment index as a proxy for Indian stock market sentiments over a time frame from April 1996 to January 2017. It uses an exploratory approach to identify relevant proxies in building a sentiment index using indirect market measures and macro variables of Indian and US markets.

Findings

The study finds that there is a significant positive correlation between the sentiment index and stock index returns. Sectors which are more dependent on institutional fund flows show a significant impact of the change in sentiments on their respective sectoral indices.

Research limitations/implications

The study has used data at a monthly frequency. Analysing higher frequency data can explain short-term temporal dynamics between sentiments and returns better. Further studies can be done to explore whether sentiments can be used to predict stock returns.

Practical implications

The results imply that one can develop profitable trading strategies by investing in sectors like metals and capital goods, which are more susceptible to generate positive returns when the sentiment index is high.

Originality/value

The study supplements the existing literature on the impact of investor sentiments on contemporaneous stock returns in the context of a developing market. It identifies relevant proxies of investor sentiments for the Indian stock market.

Details

South Asian Journal of Business Studies, vol. 7 no. 3
Type: Research Article
ISSN: 2398-628X

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Article
Publication date: 11 May 2015

Chi-Lu Peng, Kuan-Ling Lai, Maio-Ling Chen and An-Pin Wei

– This study aims to investigate whether and how different sentiments affect the stock market’s reaction to the American Customer Satisfaction Index (ACSI) information.

Abstract

Purpose

This study aims to investigate whether and how different sentiments affect the stock market’s reaction to the American Customer Satisfaction Index (ACSI) information.

Design/methodology/approach

The portfolio approach, with time-varying risk factor loadings and the asset-pricing models, is borrowed from the finance literature to investigate the ACSI-performance relationship. A direct sentiment index is used to examine how investors’ optimistic, neutral and pessimistic sentiments affect the aforementioned relation.

Findings

This paper finds that customer satisfaction is a valuable intangible asset that generates positive abnormal returns. On average, investing in the Strong-ACSI Portfolio is superior to investing in the market index. Even when the stock market holds pessimistic beliefs, investors can beat the market by investing in firms that score well on customer satisfaction. The out-performance of our zero-cost, long–short ACSI strategy also confirms the mispricing of ACSI information in pessimistic periods.

Research limitations/implications

Findings are limited to firms covered by the ACSI data.

Practical implications

Finance research has further documented evidence of the stock market under-reacting to intangible information. For example, firms with higher research and development expenditures, advertising, patent citations and employee satisfaction all earn superior returns. Literature also proves that investors efficiently react to tangible information, whereas they undervalue intangible information. In summary, combining our results and those reported in the literature, customer satisfaction is value-relevant for both investors and firm management, particularly in pessimistic periods.

Originality/value

This study is the first to investigate how sentiment affects the positive ACSI-performance relationship, while considering the time-varying property of risk factors. This study is also the first to show that ACSI plays a more important role during pessimistic periods. This study contributes to the growing literature on the marketing–finance interface by providing better understanding of how investor emotional states affect their perceptions and valuations of customer satisfaction.

Details

European Journal of Marketing, vol. 49 no. 5/6
Type: Research Article
ISSN: 0309-0566

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Article
Publication date: 29 June 2018

Myungsun Kim, Robert Kim, Onook Oh and H. Raghav Rao

The purpose of this paper is to examine the role of online freelance stock analysts in correcting mispricing of hard-to-value firms during sentiment-driven market periods.

Abstract

Purpose

The purpose of this paper is to examine the role of online freelance stock analysts in correcting mispricing of hard-to-value firms during sentiment-driven market periods.

Design/methodology/approach

The sample covers 23,758 Seeking Alpha articles obtained for the period between January 2005 and September 2011. The authors use OLS regressions to test the stock market reaction around Seeking Alpha analysts’ reports. The information in online analysts’ reports is measured by the tone of stock articles posted in SeekingAlpha.com (SA).

Findings

The analysis reveals that the degree of negative tone of their stock articles is related to three-day stock returns around the article posting dates. It further reveals that the relation between these returns and prevailing market sentiment depends on firm-specific susceptibility to the market sentiment. The three-day stock returns are higher during low market sentiment periods for firms that are more susceptible to the market sentiment, hence, harder to value. The tone of the stock articles during low sentiment periods also predicts the news in the forthcoming earnings.

Practical implications

The findings help stock investors identify value-relevant information provided by online freelance stock analysts, particularly for hard-to-value stocks and during the low market sentiment period.

Originality/value

This study utilizes a unique dataset obtained from SA. This is the first paper to examine whether online analysts help investors correct potential undervaluation of hard-to-value firms during the low market sentiment period.

Details

Managerial Finance, vol. 44 no. 8
Type: Research Article
ISSN: 0307-4358

Keywords

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Article
Publication date: 17 May 2019

Divya Aggarwal

The purpose of this paper is to review and discuss the literature focusing on defining and measuring sentiments so as to understand their role in stock market behavior.

Abstract

Purpose

The purpose of this paper is to review and discuss the literature focusing on defining and measuring sentiments so as to understand their role in stock market behavior.

Design/methodology/approach

Critical review of the literature by analyzing myriad scholarly articles. The study is based on an analysis of 81 scholarly articles to critically analyze the approach toward defining and measuring market sentiments. The articles have been examined to identify and critique different classification of sentiment measures. A discussion is built to scrutinize the sentiment measures under the purview of theoretical underpinnings of the investor sentiment theory as well.

Findings

With more than five decades of research, the sentiment construct in finance literature is still ill-defined. Myriad empirical proxies of sentiment measures have led to conflicting results. The sentiment construct defined in financial theories needs to be revisited from the lens of sentiments defined in psychology.

Research limitations/implications

The study is limited to analyzing the role of individual and institutional sentiments in equity markets. There is a need to explore sentiments with respect to different investment styles and strategies along with the type of investors.

Practical implications

Developing a suitable sentiment proxy can result in devising profitable trading strategies for investors. Understanding factors driving investor sentiments will help regulators to become more proactive and frame better policies.

Originality/value

This paper has leveraged psychology literature to highlight the limitations in development of sentiment construct in finance literature. By identifying stylized facts from reviewing the empirical literature, it highlights areas for future research.

Details

Qualitative Research in Financial Markets, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1755-4179

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Article
Publication date: 17 May 2021

Nevi Danila, Kamilah Kamaludin, Sheela Sundarasen and Bunyamin Bunyamin

The purpose of this paper is to examine investor sentiment by measuring the impact of market sentiment shocks on the volatility of the Islamic stock index of five ASEAN…

Abstract

Purpose

The purpose of this paper is to examine investor sentiment by measuring the impact of market sentiment shocks on the volatility of the Islamic stock index of five ASEAN countries, with noise traders as a proxy for market sentiment.

Design/methodology/approach

The GJR-GARCH model is used to capture the empirically observed fact that negative shocks in the past period have a stronger impact on variance than positive shocks in the present.

Findings

All five ASEAN Islamic stock indices show clustering volatility. However, only three countries, namely, Malaysia, Thailand and Singapore, demonstrate leverage effects. In addition, the effect of market sentiment on Islamic stock index returns is observed in the Indonesian and Malaysian markets, which are the two largest Islamic markets with a dominant Muslim population in the ASEAN. This finding implies that the trading behaviours of Muslim investors in the Shariah market are the same as their behaviours in the conventional market, that is, nonadherence to the Sunnah.

Practical implications

Whilst establishing investment strategies, creating portfolios and providing client-advisory services, investors and fund managers should factor in the presence of market sentiment and its impact on stock performance and volatility. In addition, a capital market system preventing rumour-based transactions is compelling.

Social implications

In some markets, the Islamic financial products awareness should be increased through education to attract increased domestic investors with the potential to boost growth in the Islamic stock market.

Originality/value

Investigation market sentiment impacts on the Islamic stock index using noise traders as a proxy.

Details

Journal of Islamic Accounting and Business Research, vol. 12 no. 3
Type: Research Article
ISSN: 1759-0817

Keywords

Content available
Article
Publication date: 10 July 2020

Ranjan Dasgupta and Sandip Chattopadhyay

The determinants of investors’ sentiment based on secondary stock market proxies in many empirical studies are reported. However, to the best of our knowledge, no study…

Abstract

Purpose

The determinants of investors’ sentiment based on secondary stock market proxies in many empirical studies are reported. However, to the best of our knowledge, no study undertakes investor sentiment drivers developed from primary survey measures by constructing an investor sentiment index (ISI) in relation to market drivers to date. This study aims to fill this research gap by first developing the ISI for the Indian retail investors and then examining which of the stock market drivers impacts such sentiment.

Design/methodology/approach

The ISI is constructed using the mean scores of eight statements as formulated based on popular direct investor sentiment surveys undertaken across the world. Then, we use the multiple regression approach overall and for top 33.33% (high-sentiment) and bottom 33.33% (low-sentiment) investors based on the responses of 576 respondents on 18 statements (proxying eight study hypotheses) collected in 2016. Moreover, the demography-based classification based investors’ sentiment is examined to make our results more robust and in-depth.

Findings

On an overall basis, the IPO activities/issues and information certainty, trading volume and momentum and institutional investors’ investment activities market drivers significantly and positively impact retail investors is examined. However, only IPO activities/issues and information certainty influences both high- and low-sentiment investors. It is intriguing to report that nature of the stock markets show conflicting results for high- (negative significant) and low- (positive significant) sentiment investors.

Originality/value

The construction of the ISI from primary survey measure is for the first time in Indian context in relation to investigating the stock market drivers influential to retail investors’ sentiment. In addition, hypothesized market drivers are also unique, each representing different fundamental and technical characteristics associated with the Indian market.

Details

Rajagiri Management Journal, vol. 14 no. 2
Type: Research Article
ISSN: 0972-9968

Keywords

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Article
Publication date: 28 February 2020

Mobeen Ur Rehman and Nicholas Apergis

This study aims to investigate the impact of sentiment shocks based on US investor sentiments, bearish and bullish market conditions. Earlier studies, though very few…

Abstract

Purpose

This study aims to investigate the impact of sentiment shocks based on US investor sentiments, bearish and bullish market conditions. Earlier studies, though very few, only consider the effect of investor sentiments on stock returns of emerging frontier Asian (EFA) markets.

Design/methodology/approach

This study uses the application of regime switching model because of its capability to explore time-varying causality across different regimes unlike traditional linear models. The Markov regime switching model uses regime switching probabilities for capturing the potential asymmetries or non-linearity in a model, in this study’s case, thereby adjusting investor sentiments shocks to stock market returns.

Findings

The results of the Markov regime switching method suggests that US sentiment, bullish and bearish market shocks act as a main contributors for inducing variation in EFA stock market returns. The study’s non-parametric robustness results highlight an asymmetric relationship across the mean series, whereas a symmetric relationship across variance series. The study also reports Thailand as the most sensitive market to global sentiment shocks.

Research limitations/implications

The sensitivity of the EFA markets to these global sentiment shocks highlights their sensitivity and implications for investors relying merely on returns correlation and spillover. These findings also suggest that spillover from developed to emerging and frontier equity markets only in the form of returns following traditional linear models may not be appropriate.

Practical implications

This paper supports the behavioral aspect of investors and resultant spillover from developed market sentiments to emerging and frontier market returns across international equity markets offering more rational justification for an irrational behavior.

Originality/value

The study’s motivation to use the application of regime switching models is because of its capability to explore time-varying causality across different regimes unlike traditional linear models. The Markov regime switching model uses regime switching probabilities for capturing the potential asymmetries or non-linearity in a model, in the study’s case, thereby adjusting investor sentiments shocks to stock market returns. It is also useful of the adjustment attributable to exogenous events.

Details

Journal of Economic Studies, vol. 47 no. 3
Type: Research Article
ISSN: 0144-3585

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Article
Publication date: 12 November 2019

Saurabh Gupta and Saumitra N. Bhaduri

The purpose of this paper is to investigate investor behavior under two broad categories, market-wide sentiment and herding.

Abstract

Purpose

The purpose of this paper is to investigate investor behavior under two broad categories, market-wide sentiment and herding.

Design/methodology/approach

Using a dynamic factor model, that extracts distinct latent factors representing fluctuations in asset returns due to changes in fundamentals as well as investors’ sentiments, the paper investigates the impact of investor behavior on asset pricing.

Findings

Consistent with the literature, the results suggest that the behavioral factors play a significant role in explaining variation in the asset prices. However, the degree of influence depends on the nature of the stocks or portfolios. The findings conform to the hypothesis that behavioral factors play a more important role in explaining the price movements of high and medium valued stocks than those of smaller valued stocks. Further, the behavioral factors also exhibit high auto-correlation, depicting the pervasive nature of such factors, and proving that information cascades and other behavioral mechanisms propagate over a period of time leading to bubbles and market crashes. Finally, since herding is often associated with market volatility, the authors test the hypothesis using two measures of volatility and the result shows positive significant associations between them as suggested in the literature.

Originality/value

The paper presents a dynamic factor model to study the impact of investor behavior on asset returns using a conventional three factors model with behavioral factors. A factor model is proposed to extract distinct latent factors representing fluctuations in asset returns due to changes in fundamentals as well as investors’ sentiments. The study investigates investor behavior under two broad categories, market-wide sentiment and herding. Consistent with the literature, the results suggest that the behavioral factors play a significant role in explaining variation in the asset prices. However, the degree of influence depends on the nature of the stocks or portfolios. The findings conform to the hypothesis that behavioral factors play a more important role in explaining the price movements of high and medium valued stocks than those of smaller valued stocks. Further, the behavioral factors also exhibit high auto-correlation, depicting the pervasive nature of such factors, and proving that information cascades and other behavioral mechanisms propagate over a period of time leading to bubbles and market crashes.

Details

Review of Behavioral Finance, vol. 11 no. 4
Type: Research Article
ISSN: 1940-5979

Keywords

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Article
Publication date: 8 January 2020

Chaiyuth Padungsaksawasdi

Considering the unique data of the gold investor sentiment index in Thailand, the purpose of this paper is to investigate the bivariate dynamic relationship between the…

Abstract

Purpose

Considering the unique data of the gold investor sentiment index in Thailand, the purpose of this paper is to investigate the bivariate dynamic relationship between the gold investor sentiment index and stock market return, as well as that between the gold investor sentiment index and stock market volatility, using the panel vector autoregression (PVAR) methodology. The author presents and discusses the findings both for the full sample and at the industry level. The results support prior literature that stocks in different industries do not react similarly to investor sentiment.

Design/methodology/approach

The PVAR methodology with the GMM estimation is found to be superior to other static panel methodologies due to considering both unobservable time-invariant and time-variant factors, as well as being suitable for relatively short time periods. The panel data approach improves the statistical power of the tests and ensures more reliable results.

Findings

In general, a negative and unidirectional association from gold investor sentiment to stock returns is observed. However, the gold sentiment-stock realized volatility relationship is negative and bidirectional, and there exists a greater impact of a stock’s realized volatility on gold investor sentiment. Importantly, evidence at the industry level is stronger than that at the aggregate level in both return and volatility cases, confirming the role of gold investor sentiment in the Thai stock market. The capital flow effect and the contagion effect explain the gold sentiment-stock return relationship and the gold sentiment-stock volatility relationship, respectively.

Research limitations/implications

The gold price sentiment index can be used as a factor for stock return predictability and stock realized volatility predictability in the Thai equity market.

Practical implications

Practitioners and traders can employ the gold price sentiment index to make a profit in the stock market in Thailand.

Originality/value

This is the first paper to use panel data to investigate the relationships between the gold investor sentiment and stock returns and between the gold investor sentiment and stocks’ realized volatility, respectively.

Details

International Journal of Managerial Finance, vol. 16 no. 3
Type: Research Article
ISSN: 1743-9132

Keywords

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