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This purpose of this study is to empirically investigate the investors overreaction and underreaction behaviours across the sectoral stock indices in the Indonesian stock market.

Nine weekly sectoral stock indices, comprising agriculture; mining; basic industry and chemicals; miscellaneous industry; consumer goods industry; property and real estate; infrastructure, utilities and transportation; finance; and trade, service and investment for the period 2009-2012 were analysed using the paired dependent sample t-test. To provide more insightful empirical evidence, the presence of market anomaly of investor’s overreaction and underreaction was examined on five observations with different vulnerable times.

The study documented that the overreaction anomaly was present among the winner portfolios in the entire sectoral indices. With the exception of the sectoral index of basic industry and chemicals on the loser portfolio, the study documented the presence of underreaction anomaly among all other sectoral indices in Indonesia. These findings implied that the investors might be able to gain significant profits investing their monies in the sectoral stock market in Indonesia by implementing the contrarian strategy.

Originality in this paper lies in the discussion of overreaction of investors in Indonesia where the stock market has great potential and has different characteristics and different problems from other regions.

The study examines the impact of behavioral biases, such as herd behavior, overconfidence and reactions to ESG News, on Socially Responsible Investing (SRI) decisions in the Indian context. Additionally, it explores gender differences in SRI decisions, thereby deepening the understanding of the factors shaping SRI choices and their implications for sustainable finance and gender-inclusive investment strategies.

The study employs Bayesian linear regression to analyze the impact of behavioral biases on SRI decisions among Indian investors since it accommodates uncertainties and integrates prior knowledge into the analysis. Posterior distributions are determined using the Markov chain Monte Carlo technique, ensuring robust and reliable results.

The presence of behavioral biases presents challenges and opportunities in the financial sector, hindering investors’ SRI engagement but offering valuable opportunities for targeted interventions. Peer advice and hot stocks strongly predict SRI engagement, indicating external influences. Investors reacting to extreme ESG events increasingly integrate sustainability into investment decisions. Gender differences reveal a greater inclination of women towards SRI in India.

The sample size was relatively small and restricted to a specific geographic region, which may limit the generalizability of the findings to other areas. While efforts were made to select a diverse sample, the results may represent something different than the broader population. The research focused solely on individual investors and did not consider the perspectives of institutional investors or other stakeholders in the SRI industry.

The study's practical implications are twofold. First, knowing how behavioral biases, such as herd behavior, overconfidence, and reactions to ESG news, affect SRI decisions can help investors and managers make better and more sustainable investment decisions. To reduce biases and encourage responsible investing, strategies might be created. In addition, the discovery of gender differences in SRI decisions, with women showing a stronger propensity, emphasizes the need for targeted marketing and communication strategies to promote more engagement in sustainable finance. These implications provide valuable insights for investors, managers, and policymakers seeking to advance sustainable investment practices.

The study has important social implications. It offers insights into the factors influencing individuals' SRI decisions, contributing to greater awareness and responsible investment practices. The gender disparities found in the study serve as a reminder of the importance of inclusivity in sustainable finance to promote balanced and equitable participation. Addressing these disparities can empower individuals of both genders to contribute to positive social and environmental change. Overall, the study encourages responsible investing and has a beneficial social impact by working towards a more sustainable and socially conscious financial system.

This study addresses a significant research gap by employing Bayesian linear regression method to examine the impact of behavioral biases on SRI decisions thereby offering more meaningful results compared to conventional frequentist estimation. Furthermore, the integration of behavioral finance with sustainable finance offers novel perspectives, contributing to the understanding of investors, investment managers, and policymakers, therefore, catalyzing responsible capital allocation. The study's exploration of gender dynamics adds a new dimension to the existing research on SRI and behavioral finance.

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.

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.

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.

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.

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.

This article aims to examine the link between uncertainty and analysts' reaction to earnings announcements for a sample of European firms during the period 1997-2007. In the same way as Daniel et al., the authors posit that overconfidence leads to an overreaction to private information followed by an underreaction when the information becomes public.

In this study, the authors test analysts' overconfidence through the overreaction preceding a public announcement followed by an underreaction after the announcement. If overconfidence occurs, over- and underreactions should be, respectively, observed before and after the public announcement. If uncertainty boosts overconfidence, the authors predict that these two combined misreactions should be stronger when uncertainty is higher. Uncertainty is defined according to technology intensity, and separate two types of firms: high-tech or low-tech. The authors use a sample of European firms during the period 1997-2007.

The results support the overconfidence hypothesis. The authors jointly observe the two phenomena of under- and overreaction. Overreaction occurs when the information has not yet been made public and disappears just after public release. The results also show that both effects are more important for the high-tech subsample. For robustness, the authors sort the sample using analyst forecast dispersion as a proxy for uncertainty and obtain similar results. The authors also document that the high-tech stocks crash in 2000-2001 moderated the overconfidence of analysts, which then strongly declined during the post-crash period.

This study offers interesting insights in two ways. First, in the area of financial markets, it provides a test of a major over- and underreaction model and implements it to analysts' reactions through their revisions (versus investors' reactions through stock returns). Second, in a broader way, it deals with the link between uncertainty and biases. The results are consistent with the experimental evidence and extend it to a cross-sectional analysis that reinforces it as pointed out by Kumar.

The purpose of this paper is to: first, test if information-adjusted noise model (IANM) can be applied in China; second, quantify noise trader risk, overreaction, underreaction and information pricing errors in that market; and third, explain the relationship between noise trader risk and return.

The authors use a behavioural asset pricing model (BAPM), CAPM, the information-adjusted noise model and model proposed by Ramiah and Davidson (2010).

The findings show that noise traders are active 99.7 per cent of the time on the Shenzhen A-share market. Furthermore, our results suggest that the Shenzhen market overreacts 41 per cent of the time, underreacts 18 per cent of the time and information pricing errors occur 40 per cent of the time.

Various methods have been applied to the Chinese stock market in an effort to measure noise trading activities and all of them failed to account for information arrival. Our study uses a superior and alternative model to detect noise trader risk, overreaction and underreaction in China.

This study aims to examine the behaviour of institutional and retail investors in response to news about industry leaders (peer firms) and to determine its impact on the stock prices of other firms (focal firms) within the same industry.

The study investigates the impact of peer news on investor behaviour of Chinese A-shares listed on the Shanghai and Shenzhen Stock Exchanges from 2010 to 2019. The media coverage of industry leaders is sourced from prominent Chinese online financial outlets and the Chinese Financial Press. Support vector machine is applied to identify the positive, neutral and negative news within the articles. The study uses event study and logistic regression to examine the effects of peer news on focal firms’ investor behaviour.

The results show that both good and bad news about leaders cause peers’ stock prices to increase initially, but then reverse within one quarter. Further analysis reveals that when leaders’ shares receive positive news coverage, institutional investors tend to exert excessive abnormal buying pressure on peers’ shares, resulting in overreactions. Conversely, retail investors do not actively trade on peers on leaders’ news day due to limited attention. In addition, the study shows that short-selling constraint inhibits bad news from reflecting in the stock prices.

The study highlights differences in investor behaviour. The finding that institutional investors tend to overreact more to peer firms’ news when focal firms are smaller and have a lower frequency of information disclosure supports the salient theory. This is consistent with the previous framework that suggests overreaction is more pronounced when it is difficult to combine external sources of information to evaluate the focal firms. In contrast, retail investors do not engage in active trading on peers on leaders’ news day due to the limited attention theory.

What explains patterns in stock prices is an important question. One such pattern, price momentum, is a well-known capital markets anomaly where recent stock price performance appears to continue into the future. This momentum is frequently thought to reflect delayed reaction by investors to unspecified information (i.e. underreaction). This study aims to provide a useful insight regarding momentum: potential mispricing related to accounting fundamentals appears to conceal longer-term reversals in price momentum. Controlling for these fundamentals reveals that price momentum reverses, indicating that investor overreaction is a potentially important source of stock price momentum. The evidence presented in this study emphasizes the importance of decoupling momentum and accounting fundamentals to achieve a more complete understanding of what explains stock price momentum.

This study explores this question by examining the longer-term performance of momentum stocks in the US market after decoupling it from performance related to accounting fundamentals using returns to fundamentals-based factors as controls in time series regressions.

This study finds evidence of clear reversals in the remaining price momentum. These reversals provide a new insight into the momentum effect because they imply that the component of price momentum not traceable to accounting fundamentals reflects investor overreaction rather than underreaction.

The findings indicate that the underlying nature of the information driving price movements is important to achieving a complete understanding of what explains price momentum. To the best of the author’s knowledge, no other study has examined the behavior of stock price momentum while controlling for accounting fundamentals.

We investigate institutional investors’ trading behavior of acquiring firm stocks surrounding merger activities for the period 1992–2001. We label investment companies and independent investment advisors as active institutions and banks, nonbank trusts, and insurance companies as passive institutions. We analyze the trading behavior of active and passive institutions surrounding merger announcements and their eventual resolution. Our results indicate that active institutions significantly increase their holdings of acquiring firm stocks for mergers with higher announcement period abnormal return and this increase is more pronounced for stock mergers than cash mergers. Active institutions display preference for stock proposals at the merger announcement on the basis of their prior beliefs and this is explained by the “overreaction phenomenon.” However, they update their beliefs between announcement and final resolution as more information arrives into the market. Finally, active institutions appear to correct their overreaction behavior by displaying their greater preference for cash proposals as compared to stock proposals at the quarter of eventual outcome. The trading behavior of passive institutions suggests that these institutions disregard the market response of merger announcement in trading acquiring firm stocks at the announcement quarter. The passive institutions gradually update their beliefs and utilize the information released at the announcement in rebalancing their portfolios at the final resolution.

Introduction: According to the effective market hypothesis, investors act rationally when making an investment decision. The hypothesis assumes that investors invest in a way that maximizes their returns, taking into account the new information received. If the information released on the market is interpreted in the same way by all investors, no investor would be able to earn above the market. This hypothesis is valid in case of efficient markets. In the event that investors show irrational behavior to the information released on the market, the markets move away from efficiency. Overreaction behavior is one of the non-rational behaviors of investors. Overreaction behavior involves investors overreacting by misinterpreting the new information released to the market. According to De Bondt and Thaler’s (1985), overreaction hypothesis in the event that investors overreact to the news coming to the market, after a period the false evaluation, the price of the security is corrected with the reversal movement, without the need of any positive or negative information. Aim: The purpose of this study is to examine investors’ overreaction behavior in mergers and acquisitions. For this purpose, overreaction behavior was analyzed for companies whose stocks are traded on the Borsa Istanbul, which were involved in mergers or acquisitions. Method: In the study, companies that made mergers and acquisitions for the period 2007–2017 were determined, and abnormal returns and cumulative abnormal returns were calculated by using monthly closing price data of these companies. Moreover, whether investors overreact to the merger and acquisition decision is examined separately for one-, three- and five-year periods. Findings: As a result of the research, it has been observed that there is a reverse return for one-, three-, and five-year periods. However, it has been determined that the overreaction hypothesis is valid for only one year.

The purpose of this study is to analyze market inefficiencies in the market for cryptocurrencies by providing a comprehensive analysis of short-term (over)reactions that follow significant price changes of such currencies.

This study identifies and analyzes overreactions and mispricing in markets for cryptocurrencies by applying a broad set of thresholds that depend on market-specific dynamics and volatilities. This study also analyzes the returns on days following abnormal returns and identifies significant differences from normal returns using the t-test and the Mann–Whitney U-test. The researchers further complement the literature by using end-of-the-day returns in addition to high-low returns. Additionally, this study considers a broad sample of 50 cryptocurrencies for an expanded time span (2015–2020) that includes the big currencies as well as smaller currencies.

Findings detect the existence of overreactions and, thus, market inefficiencies in crypto markets. The findings for different methodological approaches are similar, which underpins the robustness of the findings. By considering a broad sample that includes small and big currencies, we can show the existence of a market size effect. By considering a broad set of thresholds, the authors further found evidence for a magnitude effect, which means that higher initial abnormal returns are related to higher inefficiencies.

This paper has practical implications. Market inefficiencies were detected, which can be used in practical trading to obtain excess returns. In fact, methodological approach of this study and its results can be used to derive a strategy for trading in cryptocurrencies that can be easily implemented. Based on the study’s findings, the authors can expect positive access returns by applying this trading strategy.

The authors complement the literature on market inefficiencies and mispricing in crypto markets by analyzing price patterns after initial abnormal returns. Researchers contribute by applying different methodological approaches in addition to the approaches used so far, by considering a set of different thresholds and by applying a much broader data set that enables the study to analyze additional aspects.