Context Of Stock Market Research Articles

Are investors attentive before a one-off holiday?

PurposeThis study investigates investor trading behaviour around regular and one-off public holidays on the Sydney Stock Exchange (SSX) from 1901 to 1950. The purpose is to examine whether trading patterns differ between regular holidays, which are known in advance, and one-off holidays, which are unexpected. The study provides insights into the predictability of holidays and its influence on market activity, contributing to the broader literature on investor inattention and market anomalies.Design/methodology/approachUsing a novel dataset constructed from handwritten share price lists covering 14,224 trading days, we perform quantitative analysis to assess trading volume before and after regular and one-off public holidays. Ordinary least squares regression models are employed to identify the presence of a holiday effect, accounting for various fixed effects and time-varying factors such as geopolitical events.FindingsWe find that trading volume is significantly lower on the day before regular holidays and higher on the day after, consistent with the investor inattention hypothesis. In contrast, no significant holiday effect is observed for one-off holidays. This suggests that predictability plays a crucial role in influencing investor behaviour, with irregular, less predictable holidays having less impact on trading patterns.Research limitations/implicationsThe study is limited by the historical nature of the data, which may not fully capture the diversity of modern trading environments. Additionally, the analysis is restricted to the SSX and may not be generalisable to other markets or time periods. Future research could explore similar effects in different contexts or with more recent data.Practical implicationsThis research provides valuable insights for market participants and regulators by demonstrating how the predictability of holidays influences market activity. Understanding these patterns could help in making more informed decisions during periods of expected low trading volumes.Social implicationsThe study underscores the role of public holidays in shaping investor behaviour, with broader implications for understanding how societal events influence financial markets. This is particularly relevant in discussions about the impact of unexpected events on market stability.Originality/valueThis is the first study to compare the effects of regular and one-off public holidays on trading volumes in a historical stock market context. Our findings highlight the importance of event predictability in financial markets, offering a new perspective on how historical market behaviours can inform current financial theories.

Exploring the Influence of Post-Earnings Announcement Drift and Investor Sentiments on Investor Trading Behavior: A Qualitative Analysis

"Post-Earnings-Announcement Drift" is a market phenomenon, which refers to investors’ tendency to overreact to the earnings announcements in conducting their investment decisions. However, this effect shows up gradually over the whole period that stock of the company is being sold out following a bullet earnings surprise. Form radically different treatments from the efficient market hypothesis (EMH), where prices of stocks will be able to quickly and fully adjust to any new coming information, it takes time for the drift to reveal itself. This happens as a slow and eventual process. This research study investigates the impact of investor sentiments and post earnings announcements drift on investor trading behavior within the Pakistan stock market context. Twelve participants that comprises of institutional and individual investors, were selected using the convenience sampling methods. Semi-structured interviews were conducted to explore the fluctuations in stock prices, investment strategies, and the market conditions. NVivo software was employed to analyze the interview transcripts, revealing themes related to the fundamental analysis, dividend importance, decision-making strategies, sources of information, investor sentiments, earnings announcements, stock pricing, information leakage, and the market anomalies. The findings highlight the significance of both the rational analysis and emotional responses in investment decisions, the importance of timely earnings disclosures, and the presence of market anomalies and the information leakage.

The Current Status and Future Prospects of Machine Learning in the Chinese Stock Market

This article explores the current status and prospects of machine learning techniques in the stock market of china. It begins by providing an overview of the relevant concepts of machine learning and analyzing its strengths and weaknesses in the stock market context. The article also introduces the current application of machine learning techniques in the gobal stock market. In the methodology section, several machine learning models that have performed well in the stock market are listed. The article then summarizes and analyzes the specific applications of machine learning and its algorithms in the stock market of China, highlighting the advantages and limitations due to the unique characteristics of the market.Finally, the article concludes by summarizing the aforementioned content and providing an outlook on the future development direction of machine learning technology in the stock market of chinese. While the performance of machine learning technology in the stock market has its pros and cons, it is undeniable that it holds an important position in the future development of the financial market, especially within the wave of innovation and progress in the financial industry.

Enhancing purchasing stock intention in investor–brands interaction: the moderated mediation role of sector knowledge

PurposeThis study seeks to investigate the interrelationships among sector reputation, purchasing stock intention, sector engagement and attitude toward the sector. Moreover, it aims to explore the moderating role of sector knowledge in the indirect relationship between sector reputation and purchasing stock intention, mediated by sector engagement and/or attitude toward the sector.Design/methodology/approachDrawing upon the theory of planned behavior, the research framework is empirically tested. A survey involving 300 potential and actual investors was conducted, representing individuals investing in tourism brands within the Egyptian stock market. The validity and reliability of the constructs were assessed using AMOS, while Hayes’s PROCESS macro was employed to examine the mediation and moderated mediation effects.FindingsThe findings reveal that sector reputation significantly influences sector engagement, attitude toward the sector and purchasing stock intention. Furthermore, the attitude toward the sector serves as an explanatory factor for investors’ propensity to purchase stocks of tourism brands. The study confirms the serial mediation effect of sector engagement and attitude toward the sector, respectively, in the relationship between sector reputation and purchasing stock intention. Additionally, it confirms the moderated mediation role of sector knowledge in the relationship between sector reputation and purchasing stock intention, mediated by attitude toward the sector.Practical implicationsThe research outcomes suggest that executives in the tourism industry should identify key determinants to enhance purchasing stock intention by fostering greater sector engagement and fostering positive attitudes toward the tourism sector.Originality/valueThis study contributes to the existing literature by shedding light on the importance of maintaining a positive brand reputation and emphasizing the influential role of investors’ knowledge, engagement and attitude in shaping investment decisions in the stock market. These insights contribute to the understanding of investor behavior and have practical implications for organizations in managing their brand reputation and fostering positive customer–brand interactions in the stock market context, thus the current study was conducted.

The sickle and the garlic chives: Volatility in the Chinese stock market

AbstractThis essay explores the meaning that volatility assumes in the Chinese stock market context. Drawing on discussions from ‘mom and pop’ online forums, it argues investors operate in a relational position with the Chinese state regulators that both sustain and threaten their market activities. Chinese stock markets are known to be the most volatile in the world. To face the state's arbitrary intervention in the market, investors must constantly juggle the options of either leaning on and trusting the regulators’ capacity to protect and rescue their stocks or engaging in risky margin trading and short-selling activities. This contradictory behavior is reflected in the popular self-mocking meme that keeps circulating in investors online forums, the one of the jiucai (meaning ‘garlic chives’). The investors often use it with irony to describe their own tendency to throw cash into the markets again and again, hoping to regain the money they lost in previous investments, never learning a lesson. Linking the financial with the biopolitical dimension, the essay takes the jiucai meme to show the extent to which volatility points to the production of new subjects whose resilience involves the adoption of practices of speculation to conjure a future for themselves that is reborn multiple times.

Systemic risk in China new energy stock markets

PurposeThe purpose of the paper is to assess the systemic risk in the new energy stock markets of China.Design/methodology/approachThis paper first uses the VaR method to study individual stock market risks. It then introduces the DCC model to capture the dynamic conditional correlation among the new energy stock markets.FindingsThe paper shows a generally upward trend of the stock market risk over time in the recent decade. Among all the markets considered, the solar power market demonstrates the highest risk, closely followed by the wind power market, while the hydropower market exhibits the lowest risk. Furthermore, the average dynamic conditional correlations among the new energy markets stay high during the period under investigation though daily correlations vary and significantly declined in 2020.Originality/valueTo the best of the authors’ knowledge, this paper is the first of its kind to study the systemic risk within the new energy stock market context. In addition, it not only investigates individual new energy stock market risks but also examines the dynamic linkages among those markets, thus providing comprehensive and unprecedented evidence of systemic risk in China new energy markets, which have useful implications for both regulators and investors.

The sum of all SCARES COVID-19 sentiment and asset return

In this study, I constitute a search based COVID-19 sentiment index using Google search volume. I develop an alternative Scared COVID-19 Attitude Revealed by Eager Search (SCARES) index using the household search volume i.e. “coronavirus pandemic”, “coronavirus epidemic”, and “coronavirus outbreak” of United States (US) during the COVID-19 pandemic. Using daily data from May 1, 2020 to July 30, 2021, I find that SCARES index negatively explains stock market return and subsequent return reversals, implying that households’ increased pandemic sentiment negatively affects equity market return. Furthermore, decile regressions on characteristics-sorted portfolio returns show that SCARES index predicts the return reversals of firms that are small, less profitable, and with low investment. I also report that COVID-19 search shocks of households do not significantly predict any of the Fama-French five-factors except SMB (small-minus-big). Moreover, I use two state Markov switching model and find that structural breaks associated with pandemic phases make SCARES positively related to indices i.e. twitter based uncertainty, volatility index, economic policy uncertainty, and business condition in high volatility regime. Finally, sub-period analysis reports that, in stock market context, people start to react slowly and become relatively less responsive to the COVID-19 search keywords. The findings of this paper can assist key stakeholders in the market to carefully analyze the asset return pattern during pandemic regimes.

Digital platforms in the news industry: how social media platforms impact traditional media news viewership

ABSTRACT We examine how social media plays the role of an attention driver for traditional media. Social media attracts and channels attention to a topic. This attention triggers people to seek further information that is reported professionally in traditional media. Specifically, the volume of social media posts about a stock influences the attention to this stock the next day, proxied by the viewership of news articles on the same stock published the next day. We test this hypothesis in the stock market context because social media is less likely than traditional media to diffuse fundamental information in the stock market. Analysing stock-related news articles and stock-related social media posts from Sina Finance and Sina Weibo, we find that the social media post volume of a stock at time t-1 is associated with the traditional media viewership of the same stock at time t. This effect is amplified when social media sentiment about the stock is more intense or positive, and with an increase in the volume of verified social media posts about the stock. Our results provide evidence that social media platforms act as attention drivers, which differ from the information channel functions discussed in prior literature.

The Impact of ESG Ratings on the Systemic Risk of European Blue-Chip Firms

There are diverging results in the literature on whether engaging in ESG related activities increases or decreases the financial and systemic risks of firms. In this study, we explore whether maintaining higher ESG ratings reduces the systemic risks of firms in a stock market context. For this purpose we analyse the systemic risk indicators of the constituent stocks of S&P Europe 350 for the period of January 2016–September 2020, which also partly covers the COVID-19 period. We apply a VAR-MGARCH model to extract the volatilities and correlations of the return shocks of these stocks. Then, we obtain the systemic risk indicators by applying a principle components approach to the estimated volatilities and correlations. Our focus is on the impact of ESG ratings on systemic risk indicators, while we consider network centralities, volatilities and financial performance ratios as control variables. We use fixed effects and OLS methods for our regressions. Our results indicate that (1) the volatility of a stock’s returns and its centrality measures in the stock network are the main sources contributing to the systemic risk measure, (2) firms with higher ESG ratings face up to 7.3% less systemic risk contribution and exposure compared to firms with lower ESG ratings and (3) COVID-19 augmented the partial effects of volatility, centrality measures and some financial performance ratios. When considering only the COVID-19 period, we find that social and governance factors have statistically significant impacts on systemic risk.

Encountering Covid-19 in the Stock Market Context

COVID-19 has hit the world tremendously and transformed regular daily routines into a new normative way of life. The consequence of COVID-19 has had a notable impression on the world economy, including current world investment. Therefore, investors nowadays have to face changes in their investments. The hurdles of the overall world economy are making the stock market decline day by day. Accordingly, investors should be wise to ascertain the appropriate time to enter the market to invest than before. Hence, this research attempted to explain the current market situation with the situation of investors. This study was administered based on a literature review that highlighted the writings and results of prior studies related to the stock market in Malaysia. Generally, the method used to produce this study was a qualitative approach that included highlighting and analysing secondary data obtained through documents, research results, or reviewed writings. The data captured were then analysed systematically using content analysis techniques writing. This survey was done, and the results confirmed that even though investors were worried, anxious and desired it all to end soon, they still strived their best to deliver and invest as best they could by gaining knowledge in whatever method they could to ensure they were not failing continuously in this volatile market as the impacts of the COVID-19 pandemic.

Calendar anomalies in the stock markets: conventional vs Islamic stock indices

PurposeIn this study, the authors evaluate seven calendar anomalies’–the day of the week, weekend, the month of the year, January, the turn of the month (TOM), Ramadan and Eid festivals–effects in both the conventional and Islamic stock indices of Bangladesh. Also, the authors examine whether these anomalies differ between the two indices.Design/methodology/approachThe authors select the Dhaka Stock Exchange (DSE) Broad Index (DSEX) and the DSEX Shariah Index (DSES) of the DSE as representatives of the conventional and Islamic stock indices respectively. To carry out the investigation, the authors employ the generalized autoregressive conditional heteroskedasticity (GARCH) typed models from January 25, 2011, to March 25, 2020.FindingsThe study’s results indicate the presence of all these calendar anomalies in either conventional or Islamic indices or both, except for the Ramadan effect. Some significant differences in the anomalies between the two indices (excluding the Ramadan effect) are detected in both return and volatility, with the differences being somewhat more pronounced in volatility. The existence of these calendar anomalies argues against the efficient market hypothesis of the stock markets of Bangladesh.Practical implicationsThe study’s results can benefit investors and portfolio managers to comprehend different market anomalies and make investment strategies to beat the market for abnormal gains. Foreign investors can also be benefited from cross-border diversifications with DSE.Originality/valueTo the authors’ knowledge, first the calendar anomalies in the context of both conventional and Islamic stock indices for comparison purposes are evaluated, which is the novel contribution of this study. Unlike previous studies, the authors have explored seven calendar anomalies in the Bangladesh stock market's context with different indices and data sets. Importantly, no study in Bangladesh has analyzed calendar anomalies as comprehensively as the authors’.

THE IMPACT OF BEHAVIORAL BIASES ON INVESTMENT PERFORMANCE: DOES FINANCIAL LITERACY MATTER?

This paper aims to investigate the impact of behavioral biases and financial literacy on investment performance in an emerging stock market context. Based on data collected from a sample of 196 Moroccan investors operating in Casablanca stock exchange, we test the research hypotheses using structural equation modeling. Out of the four heuristics examined in our proposed conceptual framework (i.e. overconfidence, representativeness, anchoring and herding), only overconfidence and representativeness had a significant positive impact on financial performance. Our results also suggest a significant positive impact of financial literacy on representativeness, while it was found negatively associated with overconfidence. This research paper is the first of its kind to investigate the existence of heuristics in an African, Arab and emerging market. As well, the current study is among the earliest attempts to examine how behavioral biases relate to investors performance.Keywords: Heuristics; financial literacy; investment performance; stock market; SEM.JEL Classification: G02.DOI: https://doi.org/10.32479/ijefi.11318

A Hybrid Portfolio Selection Model

It is generally observed that investors approach asset managers and financial analysts to recommend a customized portfolio based on certain personalized preferences. The article discusses a methodology to build a hybrid personalized multi-criteria model in the Indian stock market context suiting investor preferences. The analytical hierarchy process (AHP) was used to compute the criteria weights and data envelopment analysis (DEA) was adopted to screen the best portfolios which were subsequently ranked by a fuzzy technique for order of preference by similarity to ideal solution (FTOPSIS) and evaluation based on distance from average solution (EDA). The rankings of portfolios were validated for robustness with the actual rankings awarded by Credit Rating Information Services of India Limited (CRISIL) to demonstrate the efficacy of the hybrid model and it was found that Fuzzy TOPSIS and EDA rankings were consistent with the CRISIL rankings proposed by expert investors.

Testing good securities disclosure: Tales of the reasonable investor

The reasonable investor test has developed in Australia both in the law of misleading and deceptive conduct in relation to securities and in the enquiry into the materiality of information in the stock market context. The former involves the question of whether a reasonable investor would have been influenced by misleading conduct, whereas the latter involves the question of whether a reasonable investor or person would expect that information would have caused investors to trade or otherwise act (the two issues can clearly be related). The test raises various issues including how it applies to a diverse class and whether it is interchangeable with a market test (the writer argues it is not). The test also exists in the United States and has been raised, but then specifically rejected, by the courts in Ireland. The development of behavioural law and economics leads to the question of whether the test can, or should, be modified in view of the allegedly non-rational attributes of investors. The author argues that the test has sufficient flexibility to accommodate such attributes in appropriate cases.

Practice and effectiveness of internal corporate governance mechanisms in Saudi Arabia Stock Market: A review of empirical evidence

The aim of this paper is to shed light on the Saudi corporate governance code, its practices and effectiveness. To do so, the paper conducted a detailed review of the articles of the code related to internal corporate governance mechanisms and the previous studies regarding its effectiveness in Saudi stock market context. The main finding is that the provisions of Saudi corporate governance code are adequate. Annual reports (2009-2014) show an increase in the level of the compliance by listed companies, indicating that the code is achieving its aims. However, the empirical evidence seems to suggest that the code has an insignificant impact on company's performance and mitigating earnings management. The main reasons behind that are the following: the code is still in its early stages, there is weak legal enforcement, and there are also some social, cultural, and economic factors. Therefore, the code needs more time for good practice and improvement to achieve its purposes.

Non-sympathetic FRN responses to drops in others’ stocks

Previous neuroeconomic studies have observed that people display sympathetic neural responses toward others’ misfortunes. We argue that the reverse emotions, such as gloating or schadenfreude, may also emerge in certain circumstances. To examine this theory, we recorded feedback-related negativity (FRN) toward others’ large or small gains or losses in a stock market context. We adopted the framework of social distance, according to which we hypothesized that because others in the stock market are far away, unidentified, and indistinct, people would show less sympathy or even schadenfreude toward others’ large losses. The results indicated that FRN at Fz was significantly less negative when observing larger decreases in others’ stock, indicating that others’ large losses are not unexpected negative events in the stock market and suggesting the existence of schadenfreude. Our research contributes to the understanding of social neurofinance by demonstrating the schadenfreude effect in relation to the stock market. This study also provides new information regarding the relationship between FRN and the social emotions that form the expectations of gain and loss.

Does XBRL adoption reduce information asymmetry?

This paper examines whether or not XBRL (eXtensible Business Reporting Language) adoption reduces information asymmetry in a stock market context. Student t-tests and multiple regression analysis were employed to examine the effect of XBRL adoption on information asymmetry in the capital market. A significant and negative association exists between XBRL adoption and information asymmetry, which implies that the adoption of XBRL may lead to the reduction of the information asymmetry in the Korean stock market. In addition, the effect of XBRL adoption on reducing information asymmetry is stronger for large-sized companies than for medium-sized and small-sized companies. Based on these findings, the demand for XBRL-enabled applications and services in the capital market is expected to grow while governments should promote XBRL adoption for business reporting.

Losers, Winners, and Biased Trades

When faced with sequential information, consumers tend to fall prey to one of two well-known heuristics: the hot (or cold) hand and the gambler's fallacy. The authors relate these two traditionally separate heuristics to differences in accepting (buy) versus rejecting (sell) decisions. They identify trend length as a contextual moderating variable and show an asymmetry between buying and selling frames. When applied to a stock market context, a consistent finding is that consumers prefer to buy past winners and sell past losers even when neither should be preferred. This behavior violates the normative rule of buy low and sell high.

Stock market context of the Lévy walks with varying velocity

We developed the most general Lévy walks with varying velocity, shorter called the Weierstrass walks (WW) model, by which one can describe both stationary and non-stationary stochastic time series. We considered a non-Brownian random walk where the walker moves, in general, with a velocity that assumes a different constant value between the successive turning points, i.e., the velocity is a piecewise constant function. This model is a kind of Lévy walks where we assume a hierarchical, self-similar in a stochastic sense, spatio-temporal representation of the main quantities such as waiting-time distribution and sojourn probability density (which are principal quantities in the continuous-time random walk formalism). The WW model makes possible to analyze both the structure of the Hurst exponent and the power-law behavior of kurtosis. This structure results from the hierarchical, spatio-temporal coupling between the walker displacement and the corresponding time of the walks. The analysis uses both the fractional diffusion and the super Burnett coefficients. We constructed the diffusion phase diagram which distinguishes regions occupied by classes of different universality. We study only such classes which are characteristic for stationary situations. We thus have a model ready for describing the data presented, e.g., in the form of moving averages; the operation is often used for stochastic time series, especially financial ones. The model was inspired by properties of financial time series and tested for empirical data extracted from the Warsaw stock exchange since it offers an opportunity to study in an unbiased way several features of stock exchange in its early stage.