Investment Decisions In Stock Market Research Articles

Benchmarking asset pricing models in emerging markets: evidence from Borsa Istanbul

PurposeInvestors who can transfer their savings to investments in a well-regulated market benefit not only themselves but also economic development. Hence, it is crucial for fund owners to evaluate their stock market investment decisions. The goal of the study is to understand which model determines the asset returns most efficiently. In this regard, the validity of single and multi-index asset pricing models (capital asset pricing model-CAPM and Fama–French models) has been examined in the Turkish Stock Exchange for 2009–2020, with the quantile regression (QR) approach.Design/methodology/approachOn 18 portfolios comprised of quoted stocks in the Istanbul Stock Exchange 100 (ISE-100/BIST-100), we test the CAPM, the Fama and French three factor model (FF3) and the Fama and French five factor model (FF5). Empirical analyses have been carried out via QR approach regressing the portfolios' average weekly excess returns on risk premium/market factor (Rm-Rf), firm size, book value/market value (B/M), profitability and investments factors. QR estimation has been employed since QR is more effective and provides a better definition of the distribution’s tails.FindingsOur empirical findings have revealed that the average excess weekly returns can be explained more strongly via CAPM. Moreover, Fama and French models are expected to give more reliable result with more data, whereas the market premium would give robust results for the Turkish Capital Market.Practical implicationsIndividuals investing in financial assets must find the price model that best fits the market. The return can be approximated in the most appropriate manner using the right variables.Originality/valueThe study differs from other research by comparing the asset pricing models via examining the assets' weekly returns with QR in the Istanbul Stock Exchange 100 (ISE-100).

Heuristic Biases and Investment Decision-making of Stock Market Investors: A Review Paper

This article builds a theoretical and research framework by identifying numerous behavioural biases in investing decision-making through a survey of research publications in the field of behavioural finance. It outlines some of the early research that helped establish behavioural finance as a field of study and shows how it has developed through time. The purpose of the article is to carry a systematic review of the literature on heuristic biases, namely overconfidence, representativeness, anchoring, availability and gambler’s fallacy influencing stock market investment decisions, identifying the major gaps in the existing studies on behavioural biases. It also aims to raise specific questions for future research. In the present study, systematic literature review (SLR) technique has been employed. By looking at the research’s year of publication, the journal of publishing, the country of study, the type of study and the statistical methods employed, one can determine the relevance of the study. On the basis of keyword searches for ‘behavioural finance’ in various published journals, conference proceedings, working papers and some other published publications, the research papers are analysed. For the purpose of creating this article, research papers from the earliest studies (1970) to the most recent publications (2022) have been gathered over a period of years. The study also highlights some of the most recent research carried out in this area. The current study is based on 131 selected research papers that were published in reputable journals between 1970 and 2022. A significant portion of the body of literature on behavioural biases highlights the dearth of this type of study in emerging nations; increase in the number of studies after behavioural finance was applied to investment decision-making, the predominance of empirical research; the widespread use of regression analysis; the prevalence of studies on overconfidence bias and the dearth of studies on availability bias and gamblers fallacy. To the best of the authors’ knowledge, the article is a pioneering work in the field of behavioural finance to employ SLR method for a considerable span of time (1970–2022) and to evaluate all the heuristic biases involved in investment decision-making. The present research study is an integration of SLR and bibliometric analysis. The publications’ patterns have been revealed, and the relationships between different types of literature have shed information on the direction that further research should go in.

The Role of Anchoring Effect in the Stock Market Investment Decisions

Price anomalies in the stock market are often difficult to explain using traditional financial theories, and such price anomalies severely affect the specific investment behavior of investors in the stock market and the trend of stock price movements. In order to study the causes of these anomalies and conclude certain countermeasures, this paper combines behavioural economic theories to analyze the causes of stock price movements over a certain period of time in terms of stock price trends caused by psychological deviations of investors in a specific industry. In this paper, this study finds that relevant stock price data by analyzing stock price movements over a certain period of time and integrate them to further understand the impact of investors' psychological biases or heuristics on stock price movements. Finally, this paper provides targeted suggestions for investors and stock market policy makers to address the importance of psychological biases on investment decisions, and suggests investors to consider the influence of different psychological mechanisms in the process of stock investment and make more objective value estimates for stocks. Second, it is recommended that government departments should reduce their intervention in the stock market to reduce the impact of policy changes on the stock market and promote a healthier investment environment for the stock market. In addition, stock market policy makers establish stricter laws for the stock market to regulate the price changes and valuation system of the stock market.

Time-frequency nexus between COVID-19, economic policy uncertainty and China’s stock market during the COVID-19 period

ABSTRACT It is acknowledged that COVID-19 sentiment influences economic policy uncertainty, which is subsequently reflected in stock market investment decisions, resulting in stock price variations. In this scenario, we attempt to explore the influence of COVID-19 and economic policy uncertainty on China’s stock market using wavelet analysis. The findings of novel wavelet frameworks uncover a bi-directional lead-lag association between COVID-19 sentiment, economic policy uncertainty, and stock market returns in China. In addition, the most pronounced degree of causal associations for the concerned couples occurred in the short and medium-run horizons. Specifically, our results unveil that economic uncertainty and COVID-19 sentiment are the main transmitter of shocks, while the stock market is the recipients of shock spillovers. Our research provides policymakers and market participants with critical insights into the behavior of Chinese stock markets during the COVID-19 crisis.

ARE ENVIRONMENTAL, SOCIAL, AND GOVERNANCE FACTORS IMPACTING MALAYSIAN INVESTORS’ DECISIONS? AN EMPIRICAL ANALYSIS

Incorporating environmental, social, and governance (ESG) considerations into stock market investment decisions is crucial amidst the onset of the COVID-19 pandemic and world turmoil, as these are essential to sustainable development. The underpinning theory of the Theory of Planned Behaviour (TPB) is employed, and the ESG aspects are examined. A survey approach is adopted, and a total of 300 respondents are collected. Partial least squares (PLS) analysis is used to analyse the obtained data. The findings suggest that environmental, social, and governance factors have a significant impact on Malaysian investment decisions following geopolitical conflicts and the ongoing COVID-19 pandemic-related distortions. However, their investment horizon has no moderating effect on their investment decisions. This research has provided valuable insights for investors, institutions, communities, and regulators. Increased awareness of the impact of ESG on individual investment decisions in Malaysia could prompt private and public institutions to prioritise ESG practises for both long-term and short-term attributes as they strive to respond to the needs of individuals and society. Regulators should provide incentives to corporations that integrate EGS practises, which include providing subsidies and stimulating greater strategic flexibility through deregulation of establishments, thereby contributing to a more positive impact on the country's financial system.

A Novel Ensemble Learning Approach for Stock Market Prediction Based on Sentiment Analysis and the Sliding Window Method

Financial news disclosures provide valuable information for traders and investors while making stock market investment decisions. Essential but challenging, the stock market prediction problem has attracted significant attention from both researchers and practitioners. Conventional machine learning models often fail to interpret the content of financial news due to the complexity and ambiguity of natural language used in the news. Inspired by the success of recurrent neural networks (RNNs) in sequential data processing, we propose an ensemble RNN approach (long short-term memory, gated recurrent unit, and SimpleRNN) to predict stock market movements. To avoid extracting tens of thousands of features using traditional natural language processing methods, we apply sentiment analysis and the sliding window method to extract only the most representative features. Our experimental results confirm the effectiveness of these two methods for feature extraction and show that the proposed ensemble approach is able to outperform other models under comparison.

How Informed Investing Will Result In better Investment Decision in Stock Market with reference of Retail Investor from Maharashtra.

This research is related to study the new wave is coming into a Stock Market to earn easy money though online trading with the respect of industries and brokerages. The Indian Stock Market is one of the important elements in Indian economy which determines the growth in our Indian economy. In today’s competitive world there are millions of people having an Internet facility in their home and offices. From last 32 years since 1991, Globalization, privatization and Liberalization) the internet has impacted much on people perception and the present study is a way to find out the customer awareness about online trading. The main objective of the study is to understand how the investor or trader takes a decision in market and how this process can be made in better way with the help of traders based in Mumbai.

Impact of Stock Brokers on Investment Decisions in Stock Market

Investment of funds in the stock is quite remarkable among different business operations. The stock market could not be predicted upto a certain degree based on the recommendations given by the others. There are more investors during the pandemic who have been investing in the stock market. The investors are not much aware about the movement in stock market and thus behaving in a non-professional way. Many investors feel that they could make more money through professional guidance. There are many advisors who have been guiding people the way they are investing and they can apply certain tools which assist in predicting the movement in the market. The investors sometimes get influenced by the information which is circulating in the market or through news channels. The advice given by professionals could also help the investors in putting their money at the right place and at the right time. The only issue which the investors feel is that stock market cannot be predicted and hence they stay away from the share market. The investors should make an attempt to remain in the stock market for longer duration, only then they can fetch good returns from the stock market.

Investigating self-efficacy and behavioural bias on investment decisions

The determinants of irrational decisions on the stock market are found in numerous empirical studies. However, self-efficacy and behavioural biases have a sturdy influence on stock market investment decisions. Behavioural biases are formed with heuristics, prospect theory and herding effect concerning stock market investments. Self-efficacy is independent of behavioural biases but is closely connected with controlling behavioural intentions in decision-making. The research was conducted to find the influence of self-efficacy and behavioural biases in the decision of stock market investment. The study was conducted with 250 individual investors and applied the SEM technique. Findings indicated that heuristics had a positive relationship with behavioural biases, but behavioural biases reported a negative relationship with the herding effect and prospect theory. Heuristics were mostly developed on the intrinsic strength of individual investors; therefore, investors believe heuristics will be a better decision-making tool than prospect theory or the herding effect. Prospect theory is shaped and influenced by regret aversion, loss aversion, self-control and mental accounting. Financial literacy, risk tolerance, and peer support profoundly develop the self-efficacy of investors to make profitable investment decisions. Self-efficacy is formed by risk tolerance, financial literacy and peer support in the stock market investment decision and identified the evidence of individual investors not making rational decisions and facing one or more behavioural biases and self-efficacy factors. The study finds the combined effect of behavioural biases and self-efficacy in stock market investment decisions, which have significant implications among individual investors, particularly in emerging markets.

An Empirical Study on the Impact of Gen Z Investors’ Financial Literacy to Invest in the Indian Stock Market

Purpose : The aim behind conducting this research was to identify the influence of financial literacy (FL) on the stock market investment decisions of individuals belonging to Gen Z in India. Attitude toward investment (AT) and perceived behavioral control (PBC) were considered as the mediating factors related to the same, while social factors (SF) and subjective norms (SN) were considered as independent factors. Design/Methodology/Approach : A Google form was used to collect primary data; 401 valid responses were considered for the present research work. G* Power 3.1.9.2 software was applied to determine the sample size. The research applied a non-probability convenient sampling technique for collecting the data through a questionnaire. Initially, convenience sampling was used, followed by snowball sampling. The questionnaire was distributed to our friends and acquaintances in five Indian states (Madhya Pradesh, Chhattisgarh, West Bengal, Gujarat, and Maharashtra). Then, friends and acquaintances were asked to circulate the same survey to their friends and acquaintances in their respective cities, and so on. This research used confirmatory composite analysis to observe linear compound interrelationships. The SmartPLS software was utilized in order to conduct an analysis of partial least square structural equation modeling. Findings : Financial literacy had the highest positive effect on investment intention (β = 0.435). AT and PBC, which are the mediating variables, had a total positive effect of (β = 0.403) and (β = 0.275) on investment intention, respectively. FL had a total positive effect of (β = 0.358) and (β = 0.614) on AT and PBC, respectively. SF had a total positive effect of (β = 0.118) on AT, and SN had a total positive effect of (β = 0.219) on investment intention. Originality Value : The current study will undoubtedly aid in the development of an understanding of the most critical aspects impacting the stock market investing intentions of Gen Z.

Exploring the Linkages between Financial Literacy, Behavioral Biases, and Stock Market Decisions

The aim of this article is to find out the linkages between financial literacy, behavioral biases, and stock market investment decisions. Further, the primary objective is divided into two parts; first, the relationship between financial literacy and behavioral biases, namely cognitive biases (representative bias, hindsight bias, mental accounting bias, and anchoring bias) and emotional biases (overconfidence, disposition, herding, and familiarity bias) was investigated. Second, the relationship between above stated behavioral biases and stock market investment decisions were explored. To satisfy the objectives of the study, a descriptive cross-sectional research design with judgmental sampling was followed. The data were collected from 477 Indian stock market investors. We found that financial literacy significantly negatively influences all the cognitive biases whereas it does not influence emotional biases. All the cognitive and emotional biases significantly impact the stock market investment decisions. Additionally, it was noticed financial literacy significantly reduces hindsight bias whereas overconfidence bias highly influences the stock market investment decisions.

The Relationship between Psychological Factors, Risk Perception and Social Media on Investment Decision Making

The purpose of this paper is to examine the determinants of investor’s investment decision-making in Indian stock markets. The hypothesized direct and indirect effect of psychological factors (anger, positive mood, fear and stress) and risk perception on investment decision making are based on the Behavioural Economic theory. However, the Cultivation theory is used as the basis to test the moderating effect of social media on investment decision-making. The data for the present quantitative study was collected using online survey questionnaire distributed to stock market investors in India. The samples were collected using convenient and snowballing sampling. The research hypotheses were tested and analysed using Partial Least Squares approach for direct and indirect effect test and Product Indicator approach for moderation analysis. Risk perception found to be significant in mediating the relationships between psychological factors such as anger, positive mood and stress towards stock market investment decisions. However, social media does not moderate the relationships between all the tested psychological factors and stock market investment decisions among Indian investors. The findings are beneficial for the stock market investors to be aware of the effect of positive and negative psychological factors on their judgment on risk perception and investment decision making. Despite the claim that social media might strengthen the effect of psychological factors on investment decision-making, this was found to be insignificant in this research.

Importance of Machine Learning in Making Investment Decision in Stock Market

Executive Summary Predicting stock trends in the financial market is always demanding but satisfying as well. With the growing power of computing and the recent development of graphics processing unit and tensor processing unit, analysts and researchers are applying advanced techniques such as machine learning techniques more and more to predict stock price trends. In recent years, researchers have developed several algorithms to predict stock trends. To assist investors interested in investing in the stock market, preferably for a short period, it has become necessary to review research papers dealing on machine learning and analyse the importance of their findings in the context of how stock price trends generate trading signals. In this article, to achieve the stated task, authors scrutinized more than 50 research papers focusing on various machine learning algorithms with varied levels of input variables and found that though the performance of models measured by root-mean-square error (RMSE) for regression and accuracy score for classification models varied greatly, long short-term memory (LSTM) model displayed higher accuracy amongst the machine and deep learning models reviewed. However, reinforcement learning algorithm performance measured by profitability and Sharpe ratio outperformed all. In general, traders can maximize their profits by using machine learning instead of using technical analysis. Technical analysis is very easy to implement, but the profit based on it can vanish too soon or making a profit using technical analysis is almost difficult because of its simplicity. Hence, studying machine, deep and reinforcement learning algorithms is vital for traders and investors. These findings were based on the literature review consolidated in the result section.

Impact of Financial Literacy and Behavioural Biases on Investment Decision-making

Investors’ financial literacy entails making sound investment decisions and the behavioural biases or irrational behaviour in decision-making that are collectively formed by heuristic bias, framing effect, cognitive illusions and herd mentality factors. The present study examines the combined impact of financial literacy and behavioural biases on investment decisions. A questionnaire was developed using Likert scaling technique to elicit study variables and collected data was analysed using SEM technique. The results showed that heuristic bias had a significant positive association with the creation of behavioural bias in decision-making. However, the framing effect, cognitive illusions and herd mentality have negative associations in the formation of behavioural biases. Further, investors often practice and follow heuristic biases rather than other irrational techniques for making investment decisions. Therefore, the financial literacy of individual investors has a significant impact on affecting stock market investment decisions.

Behavioural errors and stock market investment decisions: recent evidence from Pakistan

PurposeThis study examines the role of behavioural factors, such as confidence, optimism, pessimism and rational expectation, in affecting investment decisions in the Pakistani stock market.Design/methodology/approachUsing daily trading data of Karachi Stock Exchange-100 index from January 2012 to December 2015, different regression models, including descriptive statistics and stationarity tests, are performed.FindingsResults indicate that stock market trading has suffered from pessimistic behaviour of investors. In the first model, the authors find a positive sign of confidence and negative sign of optimism with the trading volume. The second model shows a positive role of confidence and rational expectations in affecting the trading volume in daily, Monday and Friday samples. The results of the third model show a negative sign of both optimism and rational expectation with the trading volume. Furthermore, the next model shows a negative sign of confidence combined with pessimism while testing their relationship with the trading volume. Finally, results of the final model suggest that optimism negatively affects the trading volume, and on the other hand, pessimism has a positive impact on the trading volume.Research limitations/implicationsThe method and empirical testing of behavioural biases and their relationship with economic variable used in this study seem to be a promising way to better understand the role of psychology in deriving financial decisions for academics and policymakers.Originality/valueThis study uses secondary data for measuring behavioural biases and decomposes the effect between rational expectation and behavioural biases.

Do Banking and Financial Services Sectors Show Herding Behaviour in Indian Stock Market Amid COVID-19 Pandemic? Insights from Quantile Regression Approach

In India, the coronavirus (COVID-19) pandemic-induced country-wide regulatory lockdown and consequential supply-chain disruptions and market instability have all posed serious challenges before the regulators and policymakers. Amid the pandemic, the stock market showed return volatilities primarily due to the unexpected investors’ behaviour. One of the behavioural biases is herding, which has the power to wreck the market equilibrium and shatter the market efficiency. Given that the pandemic has generated unprecedented spirals of uncertainties across the globe, thereby creating interruptions in the pattern of stock market investment decisions, this study examined the herding behaviour of 54 stocks of banking and financial services sectors listed in the national stock exchange. In the quantile regression framework, the study provides evidence of the presence of herding for public sector banking and financial services under the bull market conditions during the pandemic in the 90th quantile of the return distribution. This finding has implications for the mispricing of financial assets in these sectors. So, the study suggests removing information asymmetry among the market participants and devising policy initiatives for ensuring market stability.

Weak form market efficiency test of Bangladesh Stock Exchange: an empirical evidence from Dhaka Stock Exchange and Chittagong Stock Exchange

Investors need to have an idea about stock market before making investment whether the stock markets are efficient or not to take investment decision in stock market. For that reason, measurement of market efficiency of stock market bears significance to investors. Bearing it in mind, the study is undertaken to find out the existence of weak form efficiency prevails in largest stock market of Bangladesh. In order to get perfect result Parametric and Non Parametric tests were conducted of DSE & CSE for 2013 to 2017. It was found from all tests that Dhaka and Chittagong Stock exchange are not weak form efficient. Therefore, the result of the study will act as a helping hand to researchers to find out the reason of Bangladesh stock market not being weak form efficient as well as providing measurement to make the stock market weak form efficient.

Household Leverage and Stock Market Investment Decisions

Household leverage has significant influence on their stock market investment decisions, controlling for age, gender, wealth, income, education background, and financial experience. Using a unique survey data in China, we provide evidence that individuals with higher household leverage are less likely to participate on the stock market. However, for stock market participators, higher household leverage is associated with higher investment rate on stocks and mutual funds. We further examine the underlying mechanisms by financial constraint and risk aversion. Financial constraint cannot explain the effect of leverage on respondents’ stock market participation, but is a good moderator variable for the influence of leverage on participators’ stock investment rate. The enhancement effect of leverage on the stock investment rate is stronger for the stock market participators when they face less severe financial constraint. Risk preference can help explain the household leverage effect. The impediment effect of household leverage on stock market participation only works when they are strongly risk averse while the enhancement effect of household leverage on stock investment rate only works when participators are slightly risk averse.

Effect of Board Independence on Earning Response Coefficient (ERC): Evidence from Pakistan

This study investigates whether board independence plays a significant role to enhance the Earning Response Coefficient (ERC) while controlling the established determinants of Earning Response Coefficient (Beta, Growth, Size and Earning Persistence). The study selected 250 non-financial firms of different sectors on the basis of purposive sampling technique which are enlisted in Pakistan stock exchange (PSX) for the time periods of eight years ranging from 2008 to 2015. Using reverse regression, it has been observed through statistical analysis that Beta is negatively related to ERC while others determinants (Growth, Size and Earning Persistence) are positively related to earning response coefficient (ERC). Moreover, the analysis result also suggested that corporate governance facet (Board independence) plays a significant role to enhance the earning response coefficient, because as per Pakistan Code of Corporate Governance (2012), the independent directors include those who are not connected to the companies, have no relationship with the companies and are free to exercise their judgment without any pressure. The important contribution for literature is that before making investment decision in stock market, investors should evaluate the corporate governance variables (Board independence) of the firms which can boost earning response coefficient (ERC). Secondly, previous studies (Shah,2017; and Collins & Kothari, 2004) and others researchers mostly worked on developed countries in the same area, but this research study is limited to emerging economy of Pakistan, that’s why it has great contribution for literature.

Factors Affecting Investors’ Perception towards Investment in Stock Market in Bangladesh: A Study on Investor’s of Khulna City

Purpose: This study aimed to identify the investors’ perceptions towards investment decision in stock market of Bangladesh and to compare the identified influential factors with respect to the demographic characteristics of the investors. Methodology: Data have been collected from 160 investors of Dhaka Stock Exchange through structured closed-ended questionnaire designed with 5 point Likert scale having 25 variables. Factor analysis has been used to identify 7 core factors: internal, informational, economic, individual, strength and affordability, goodwill and external factor that are affecting investor’s preferences. Independent Samples t-test, ANOVA and Welch test have been used to identify gender, age, education and income wise differences. Findings: The study found that there were no significance differences in 24 out of 25 variables in terms of gender, 20 out of 25 variables in terms of age, 10 out of 25 variables in terms of education and 23 out of 25 variables in terms of occupation of the investors. Value: Listed companies, authorities and concerned parties in Securities and Exchange Commission and government will be benefited from this study.