Impact of herding on the returns in the Indian stock market: an empirical study

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Sunaina Kanojia ◽  
Deepti Singh ◽  
Ashutosh Goswami
Keyword(s):  
Stock Market ◽  
Stock Returns ◽  
Market Condition ◽  
Individual Investors ◽  
Herd Behavior ◽  
Market Conditions ◽  
Absolute Deviation ◽  
Cross Sectional ◽  
Content Type ◽  
Indian Stock Market

PurposeHerd behavior has been studied herein and tested based on primary respondents from Indian markets.Design/methodology/approachThe paper expounds the empirical evidence by applying the cross-sectional absolute deviation method and reporting on herd behavior among decision-makers who are engaged in trading in the Indian stock market. Further, the study attempts to analyze the market-wide herding in the Indian stock market using 2230 daily, 470 weekly and 108 monthly observations of Nifty 50 stock returns for a period of nine years from April 1, 2009 to March 31, 2018 during the normal market conditions, extreme market conditions and in both increasing and decreasing market conditions.FindingsIn a span of a decade witnessing different market cycles, the authors’ results exhibit that there is no evidence of herding in any market condition in Indian stock market primarily due to the dominance of institutional investors and secondly because of low market participation by individual investors.Originality/valueThe results reveal that there is no impact of herd behavior on the stock returns in the Indian equity market during the normal market conditions. It highlights that the participation of individuals who are more prone to herding is more evident for short-run investments, contrary to long-term holdings.

scholarly journals Herding behavior and stock market conditions

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Abdollah Ah Mand ◽  
Hawati Janor ◽  
Ruzita Abdul Rahim ◽  
Tamat Sarmidi
Keyword(s):  
Stock Market ◽  
Global Financial Crisis ◽  
Emerging Market ◽  
Developed Countries ◽  
Herding Behavior ◽  
Market Conditions ◽  
Absolute Deviation ◽  
Cross Sectional ◽  
Content Type ◽  
Market Return

Purpose The purpose of this paper is to investigate whether market conditions have an effect on investors’ propensity to herd in an emerging economy’s stock market. Additionally, given the lack of research on Islamic behavioral finance, the authors further investigate if the herding phenomenon is distinct in Islamic versus conventional stocks. Design/methodology/approach The authors used daily data for the period of 1995–2016 according to the herding behavior model of Chang et al. (2000), which relies on cross-sectional absolute deviation of returns. Findings Findings reveal the herding behavior of investors among Shariah-compliant during up and down market exits with non-linear relationship to the market return, while for conventional stocks herding behavior does not exist with linear nor nonlinear relationships during the up and down market. Furthermore, for the whole market, herding behavior only exists during upmarket with a nonlinear relationship to the market return. However, this relationship is not significant. Moreover, the results of this study are robust with respect to the effect of the Asian and global financial crisis. Practical implications The findings are useful for investors to identify which market conditions are associated with rational and irrational behavior of investors. Originality/value Most of the theoretical and empirical studies on herding behavior have focused on developed countries. Only a few studies have paid attention to the herding behavior in Islamic financial markets, particularly in the context of an emerging market such as Malaysia. This study fills this void.

Herd behavior in the French stock market

2017 ◽  
Vol 16 (4) ◽  
pp. 497-515 ◽  
Author(s):  
Houda Litimi
Keyword(s):  
Stock Market ◽  
Trading Volume ◽  
Design Methodology ◽  
Garch Model ◽  
Herd Behavior ◽  
Conditional Volatility ◽  
Herding Behavior ◽  
Absolute Deviation ◽  
Cross Sectional ◽  
Content Type

Purpose This paper aims to investigate the herding behavior in the French stock market and its effect on the idiosyncratic conditional volatility at a sectoral level. Design/methodology/approach This sample covers all the listed companies in the French stock market, classified by sector, over four major crisis periods. The author modifies the cross-sectional absolute deviation (CSAD) model to include trading volume and investors sentiment as herding triggers. Furthermore, the author uses a modified GARCH model to investigate the effect of herding on conditional volatility. Findings Herding is present in the French market during crises, and it is present in only some sectors during the entire period. The main trigger for investors to embark into a collective herding movement differs from one sector to another. Furthermore, herding behavior has an inhibiting effect on market conditional volatility. Originality/value The author modifies the CSAD model to investigate the presence of herding in the French stock market at a sectoral level during turmoil periods. Furthermore, the particularly designed GARCH model provides new insights on the effect of herding and volume turnover on the conditional volatility.

Islamic finance and herding behavior: an application to Gulf Islamic stock markets

2018 ◽  
Vol 10 (2) ◽  
pp. 192-206 ◽  
Author(s):  
Imed Medhioub ◽  
Mustapha Chaffai
Keyword(s):  
Saudi Arabia ◽  
Stock Market ◽  
Stock Returns ◽  
Stock Markets ◽  
Future Research ◽  
Herd Behavior ◽  
Herding Behavior ◽  
Cross Sectional ◽  
Monthly Data ◽  
Content Type

Purpose The purpose of this paper is to examine the herding behavior in GCC Islamic stock markets. Design/methodology/approach The authors followed the methodology developed by Chiang and Zheng (2010) to test herding behavior. Cross-sectional tests have been considered in this paper. The authors use both OLS and GARCH estimations to examine herding behavior by using a sample of GCC Islamic stock markets. Findings By applying monthly data for the period between January 2006 and February 2016 for five Islamic GCC stock returns (Bahrain, Kuwait, Qatar, Saudi Arabia and UAE), results suggest a significant evidence of herd behavior in Saudi and Qatari Islamic stock markets only. When the authors take into account the existence of asymmetry in herd behavior between down- and up-market periods, evidence of herding behavior during down market periods in the case of Qatar and Saudi Arabia was found. In addition, the authors found that Kuwaiti and Emirates Islamic stock markets herd with the local conventional stock market, showing the interdependencies between Islamic and conventional markets. Research limitations/implications In this paper, the authors found an absence of herding behavior in some Islamic stock markets (Bahrain, Kuwait and Emirates). This is not the result of Shariah guidelines in these Islamic markets, but this is mainly due to the weak oscillations of returns which are very close to zero. In our future research, the authors could apply daily data and compare the results to those obtained in this paper by using monthly data. Originality/value This paper provides a practical framework in order to analyze the herding behavior concept for GCC Islamic stock markets. Its originality consists of linking the herding behavior to ethics and morality to verify whether the properties and guidelines of Islam are respected in Islamic stock markets. To the best of the authors’ knowledge, no other paper has treated the case of herding behavior in Islamic stock markets and taking into account the possible influence of the conventional market on the Islamic stock market that may impact herding behavior.

Artificial intelligence in financial services: a qualitative research to discover robo-advisory services

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Ankita Bhatia ◽  
Arti Chandani ◽  
Rizwana Atiq ◽  
Mita Mehta ◽  
Rajiv Divekar
Keyword(s):  
Artificial Intelligence ◽  
Stock Market ◽  
Financial Services ◽  
Future Research ◽  
Individual Investors ◽  
Content Type ◽  
Advisory Services ◽  
Wealth Management ◽  
Management Scenario ◽  
Indian Stock Market

Purpose The purpose of this study is to gauge the awareness and perception of Indian individual investors about a new fintech innovation known as robo-advisors in the wealth management scenario. Robo-advisors are comprehensive automated online advisory platforms that help investors in managing wealth by recommending portfolio allocations, which are based on certain algorithms. Design/methodology/approach This is a phenomenological qualitative study that used five focussed group discussions to gather the stipulated information. Purposive sampling was used and the sample comprised investors who actively invest in the Indian stock market. A semi-structured questionnaire and homogeneous discussions were used for this study. Discussion time for all the groups was 203 min. One of the authors moderated the discussions and translated the audio recordings verbatim. Subsequently, content analysis was carried out by using the NVIVO 12 software (QSR International) to derive different themes. Findings Factors such as cost-effectiveness, trust, data security, behavioural biases and sentiments of the investors were observed as crucial points which significantly impacted the perception of the investors. Furthermore, several suggestions on different ways to enhance the awareness levels of investors were brought up by the participants during the discussions. It was observed that some investors perceive robo-advisors as only an alternative for fund/wealth managers/brokers for quantitative analysis. Also, they strongly believe that human intervention is necessary to gauge the emotions of the investors. Hence, at present, robo-advisors for the Indian stock market, act only as a supplementary service rather than a substitute for financial advisors. Research limitations/implications Due to the explorative nature of the study and limited participants, the findings of the study cannot be generalised to the overall population. Future research is imperative to study the dynamic nature of artificial intelligence (AI) theories and investigate whether they are able to capture the sentiments of individual investors and human sentiments impacting the market. Practical implications This study gives an insight into the awareness, perception and opinion of the investors about robo-advisory services. From a managerial perspective, the findings suggest that additional attention needs to be devoted to the adoption and inculcation of AI and machine learning theories while building algorithms or logic to come up with effective models. Many investors expressed discontent with the current design of risk profiles of the investors. This helps to provide feedback for developers and designers of robo-advisors to include advanced and detailed programming to be able to do risk profiling in a more comprehensive and precise manner. Social implications In the future, robo-advisors will change the wealth management scenario. It is well-established that data is the new oil for all businesses in the present times. Technologies such as robo-advisor, need to evolve further in terms of predicting unstructured data, improvising qualitative analysis techniques to include the ability to gauge emotions of investors and markets in real-time. Additionally, the behavioural biases of both the programmers and the investors need to be taken care of simultaneously while designing these automated decision support systems. Originality/value This study fulfils an identified gap in the literature regarding the investors’ perception of new fintech innovation, that is, robo-advisors. It also clarifies the confusion about the awareness level of robo-advisors amongst Indian individual investors by examining their attitudes and by suggesting innovations for future research. To the best of the authors’ knowledge, this study is the first to investigate the awareness, perception and attitudes of individual investors towards robo-advisors.

Do Indian stock market sentiments impact contemporaneous returns?

2018 ◽  
Vol 7 (3) ◽  
pp. 332-346
Author(s):  
Divya Aggarwal ◽  
Pitabas Mohanty
Keyword(s):  
Stock Market ◽  
Stock Returns ◽  
Temporal Dynamics ◽  
Stock Exchange ◽  
Principal Component ◽  
Stock Index ◽  
Content Type ◽  
Investor Sentiments ◽  
Indian Stock Market ◽  
The Impact

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.

Shifts in Herd Mentality of Investors in Uncertain Market Conditions: New Evidence in the Context of a Frontier Stock Market

2018 ◽  
Vol 10 (3(J)) ◽  
pp. 203-219 ◽  
Author(s):  
Kalugala Vidanalage Aruna Shantha
Keyword(s):  
Stock Market ◽  
Learning Effect ◽  
Stock Exchange ◽  
Psychological Effects ◽  
Herd Behavior ◽  
Absolute Deviation ◽  
Cross Sectional ◽  
Post Market ◽  
And Behavior ◽  
New Evidence

This paper examines the herding phenomenon in the context of a frontier stock market, the Colombo Stock Exchange of Sri Lanka, employing the cross - sectional absolute deviation methodology to daily frequencies of data for the period from April, 2000 to September, 2016. The results show significant changes in magnitude and pattern of herding over different episodes of the market. The herd behavior is strongly presence irrespective of the direction of the market movement in the 2000 - 2008 period, during which investments in the stock market is affected by the country’s political instability resulting from the civil war. The evidence also shows herd behavior during the period of market bubble whereas negative herding in the market crash period. However, it becomes less likely to occur during the period after the market crash. The lower tendency to herd during the post- market crash period supports the Adaptive Market Hypothesis, implying that investors are likely to realize the irrationality of herding and learn to be more rational as a consequence of significant losses experienced during the period of the market crash. Accordingly, these findings suggest that period- specific characteristics of the market and the associated psychological effects to investors such as overconfidence and panics would cause changes to their beliefs and behavior, the experiences of which would subsequently produce learning effect to minimize their irrationality in decision making.

Impact of behavioral factors on investors’ financial decisions: case of the Egyptian stock market

2019 ◽  
Vol 12 (1) ◽  
pp. 30-55 ◽  
Author(s):  
Noura Metawa ◽  
M. Kabir Hassan ◽  
Saad Metawa ◽  
M. Faisal Safa
Keyword(s):  
Stock Market ◽  
Behavioral Finance ◽  
Investor Sentiment ◽  
Investment Decisions ◽  
Demographic Characteristics ◽  
Individual Investors ◽  
Herd Behavior ◽  
Behavioral Factors ◽  
Content Type ◽  
Positive Effects

Purpose This paper aims to investigate the relationship between investors’ demographic characteristics (age, gender, education level and experience) and their investment decisions through behavioral factors (sentiment, overconfidence, overreaction and underreaction and herd behavior) as mediator variables in the Egyptian stock market. Design/methodology/approach This paper collects data from a structured questionnaire survey carried out among 384 local Egyptian, foreign, institutional and individual investors. This paper used a partial multiple regression method to analyze the effect of investors’ demographic characteristics on investment decisions through behavioral factors as the mediator variable. Findings Investor sentiment, overreaction and underreaction, overconfidence and herd behavior significantly affect investment decisions. Also, age, gender and the level of education have significant positive effects on investment decisions by investors. Experience does not play a significant role in investment decisions, but as investors gain experience, they tend to overlook the emotional factors. Practical implications The findings of this paper would help to understand common behavioral patterns of investors and indicate a path toward the growth of the Egyptian stock market. Originality/value There is a lack of research in behavioral finance covering Middle East and North African markets. This paper attempts to fulfill the gap by analyzing behavioral factors in the Egyptian market.

Investor attention using the Google search volume index – impact on stock returns

2019 ◽  
Vol 11 (1) ◽  
pp. 55-69 ◽  
Author(s):  
Vighneswara Swamy ◽  
Munusamy Dharani
Keyword(s):  
Stock Market ◽  
Stock Returns ◽  
Volume Index ◽  
Trading Behavior ◽  
Excess Returns ◽  
Investor Attention ◽  
Content Type ◽  
Search Volume ◽  
Indian Stock Market ◽  
Google Search

Purpose The purpose of this paper is to investigate whether the investor attention using the Google search volume index (GSVI) can be used to forecast stock returns. The authors also find the answer to whether the “price pressure hypothesis” would hold true for the Indian stock market. Design/methodology/approach The authors employ a more recent fully balanced panel data for the period from July 2012 to Jun 2017 (260 weeks) of observations for companies of NIFTY 50 of the National Stock Exchange in the Indian stock market. The authors are motivated by Tetlock (2007) and Bijl et al. (2016) to employ regression approach of econometric estimation. Findings The authors find that high Google search volumes lead to positive returns. More precisely, the high Google search volumes predict positive and significant returns in the subsequent fourth and fifth weeks. The GSVI performs as an useful predictor of the direction as well as the magnitude of the excess returns. The higher quantiles of the GSVI have corresponding higher excess returns. The authors notice that the domestic investor searches are correlated with higher excess returns than the worldwide investor searches. The findings imply that the signals from the search volume data could be of help in the construction of profitable trading strategies. Originality/value To the best of the authors knowledge, no paper has examined the relationship between Google search intensity and stock-trading behavior in the Indian stock market. The authors use a more recent data for the period from 2012 to 2017 to investigate whether search query data on company names can be used to predict weekly stock returns for individual firms. This study complements the prior studies by investigating the relationship between search intensity and stock-trading behavior in the Indian stock market.

scholarly journals Enterprise feedback management (EFM): what lies beyond the hype?

2020 ◽  
Vol 32 (1) ◽  
pp. 53-69
Author(s):  
Lerzan Aksoy ◽  
Sabine Benoit ◽  
Shreekant G. Joag ◽  
Jay Kandampully ◽  
Timothy Lee Keiningham ◽  
...  
Keyword(s):  
Stock Market ◽  
Financial Performance ◽  
Stock Returns ◽  
Market Performance ◽  
Cross Sectional ◽  
Content Type ◽  
Financial Outcomes ◽  
Stock Market Performance ◽  
Scientific Papers ◽  
Market Valuations

PurposeThe needs of CMOs to utilize a firm's data productively in order to support decision-making combined with the reported benefits of enterprise feedback management solutions has resulted in a rapid rise in usage and valuation of EFM providers. The explicit promise of EFM providers is improved financial performance, whereas there is no scientific research investigating this link. To investigate the link between EFM usage and financial performance is core of this research.Design/methodology/approachTo gain insight into this link survey data from 127 US-based firms on their usage of EFM platforms was linked to their stock market performance over several years.FindingsThis research did not find any significant positive relationships between different aspects of EFM usage investigated and stock returns. It is important to note that these results should not be taken as validation that EFM systems do not result in positive financial outcomes for firms. It may be that superior market performance as measured through stock returns is difficult to observe through a cross-sectional analysis. Instead these results indicate that superior market performance as measured through stock market performance is not an obvious, generalizable outcome for firms that have adopted EFM systems.Originality/valueEFM has rapidly grown across many consumer facing industries, with EFM platform providers receiving very high market valuations on relatively small revenue streams. This is one of the first scientific papers to study the usage and impact of these EFM systems.

Personality traits and motivation of individual investors towards herding behaviour in Indian stock market

Kybernetes ◽  
2019 ◽  
Vol 49 (2) ◽  
pp. 384-405
Author(s):  
Sharda Kumari ◽  
Bibhas Chandra ◽  
J.K. Pattanayak
Keyword(s):  
Stock Market ◽  
Personality Traits ◽  
Structural Equation ◽  
Small Sample ◽  
Individual Investors ◽  
Motivating Factors ◽  
Content Type ◽  
Emotional Factors ◽  
Cognitive Capability ◽  
Indian Stock Market

Purpose The purpose of this paper is to investigate the relationships between personality, motivating factors and herding behaviour of individual investors. Investors’ personality has been classified consonant to the personality traits (compliant, aggressive and detached) encapsulated in Horney’s tripartite model. Design/methodology/approach To carry out this study, the author surveyed 363 individual investors of the Indian stock market using a structured questionnaire. Structural equation modelling is used to empirically test the relationships between personality, three motivating factors (cognitive capability, emotional factors and social factors) and herding behaviour. Findings The result reveals that, expect compliant personality, none shows proclivity towards herding behaviour. Investors possessing compliant personality are more influenced by social motivating factors; however, cognitive factor motivates aggressive personality, inhibiting herding behaviour. Furthermore, investors having detached personality are not influenced by any motivating factors of herding. Research limitations/implications The limitation is the difficulty in generalizing the results to overall country populations as the Indian stock market has a huge turnover every day, and the author’s survey consisted of only small sample of individual investors. Practical implications The outcomes of this study could possibly unveil a new insight to discern the behaviour of individual investors in the Indian stock market. Originality/value The influences of personality on investment choices have been investigated before, but the influence of personality specifically on herding behaviour has not being adequately investigated in an emerging economy like India, as very scanty literature is available on the influence of personality on herding behaviour. The study addresses this gap and further explores the association of personality with different motivating factors that cause herding bias.

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