Decisions Of Investors Research Articles

Investors’ Perception of their Investment Decision on the Basis of ESG – A Case Study in Kolkata

Investors are pillar of any country’s economy. They are investing their hard-earned money for the development of the company as well as gaining profit for themselves. This study emphasized on the perception of investors based on Kolkata by considering ESG (Environmental, Social and Governance) before taking their investment decision. ESG consideration for investing decisions is becoming more common as a crucial aspect of sustainable development due to global financial crisis. ESG analyses the characteristics of investments that affect risk management, sustainable return, and accountability. Primary data has been collected with the help of Google Form with well-structured questionnaire by using Likert 5-point scale from 55 investors in Kolkata to do this research work. Descriptive statistics, reliability test, normality test and Mann Whitney U test have been done to justify the objectives of the study. Kolmogorov-Smirnov and Shapiro-Wilk test result suggest that the data are non-normal and it indicates performing of non-parametric test. Analysis of the study applied Mann Whitney U test to know the interdependency on the basis of gender and investment horizon as grouping variable. It reveals that there is no interdependency between gender and investment horizon with investors’ perception of their investment decision in Kolkata based on ESG performance of the company.

Bionic-inspired oil price prediction: Auditory multi-feature collaboration network

Predictions of the oil price are critical to support intelligent decision-making for individual investors, governments, and corporations, but a challenging task since there are complex nonlinear and random fluctuations involved in series. Additionally, most existing methods mainly focus on the data-layer fitting, and inherit uninterpretable design flowcharts and unclear layer functions. Based on the fact that living things evolve numerous advanced cognition processes after long-term interactions with environments, it is a promising problem to design bionic deep prediction networks. In this paper, an auditory-inspired multi-feature collaboration network (AMFC-Net) is explored to predict the oil price, and includes the feature extraction, brain memory, and comprehensive prediction blocks. Specifically, through imitating that complex sounds are captured by auditory canals and converted into electrical impulses, the first block adopts four typical activation functions to extract multi-group complementary features for detecting nonlinear changes. Through imitating that electrical impulses are transformed to the left and right hemispheres for handling and analyzing, the second block realizes gating and cooperation mechanisms to learn long short-term dependencies and highlight core information. Through imitating that information is sent to higher cerebral cortices for sensing the environment, the third block maps relationships from features to targets for producing final predictions. In summary, multi-channel convolution operations establish the imitations of both form (clear functional layer) and spirit (layer-by-layer collaboration), which not only ensure the prediction effectiveness but also improve the AMFC-Net interpretability. Three experiments (comparison with 12 machine learning methods), three experiments (comparison with 8 hybrid methods under decomposition plus ensemble framework), and seven discussions under two real-world oil price datasets all indicate that the proposed AMFC-Net is superior and suitable to predict the oil price.

How Behavioral Finance Impacts Investor Decision-Making: an Empirical Study of the Pakistan Stock Exchange

This research intended to explore the impact of behavioral finance on investor decision making within Pakistan stock exchange (PSX). A Quantitative explanatory research was used. Data was collected using convenience sampling from retail investors from a representative sample. 412 filled questionnaires were used for the analysis. Data was tested through Smart PLS that is an application that runs using structure equation modeling (SEM). In broad terms, our empirical findings suggest that an excessive risk-taking culture can be a source of financial instability. Our findings suggest that financial behavioral biases such as, herd mentality, overconfidence and loss aversion that significantly affect investor decision-making in the stock market have practical implications for market practitioners and policy makers suggesting the need for better understanding of investor behavior and strategies to promote more rational share pricing in the stock market. In recognizing and dealing with these biases, market participants’ individual investment decisions could potentially be enhanced and in resolving market inefficiencies, these biases could be their mitigation.

Analysis of the Use of CAPM in Investing Decisions in the Financial Sector Listed on the IDX for the Period 2020 – 2022

This study aims to analyze the use of the Capital Asset Pricing Model (CAPM) in making investment decisions in the financial sector listed on the Indonesia Stock Exchange (IDX) during the 2020-2022 period. This research method involves collecting historical stock price data and financial data of companies listed in the IDX financial sector during the period under study. This research uses a descriptive research design with a quantitative approach and uses secondary data. Furthermore, statistical analysis will be conducted to test the effect of using CAPM on investment decisions. The results of this study are expected to provide valuable insights for investors and financial market participants. This research can also help in identifying companies in the financial sector that have higher return potential based on CAPM-based analysis.

An examination of the impact of corporate sustainability practices on decision-making for Chinese investors

This paper examines the impact of corporate sustainability practices on Chinese investors' decision-making within China's unique CSR framework shaped by government directives. Through focus group discussions with 36 MBA participants from Zhejiang University, the study reveals a general preference for prioritising sustainability in investment appraisal, reflecting the Chinese government's strong stance on CSR. Trust in CSR disclosure depended on historical accuracy and third-party verification. As China strengthens its sustainability directives, this study predicts greater integration of sustainability metrics in China's investment strategies and highlights the symbiotic relationship between state policies, corporate practices and investor perceptions.

After COVID-19 Epidemic Restriction: Investor Sentiment and Stock Market Response

The economic situation and the direction of the stock market after the pandemic have become hot topics of concern for society. Despite numerous studies on the association between the stock market and investor sentiment, there is a dearth of consolidated and all-encompassing research on the subject in the context of the COVID-19 pandemic. Therefore, this article compiles pertinent information and literature on the stock markets of the United States and China amidst and following the pandemic. It delves into the connection and fundamental drivers between investor sentiment and stock returns, along with market crises, by scrutinizing and organizing the data. From the perspectives of stock returns and market crises, investor sentiment significantly affects long-term stock market returns and the occurrence of market crises by influencing investor behavior. Media orientation, herding behavior, and overreaction further explain the behavior and decisions of investors during this particular period, as well as the repercussions of these steps on the economy and the stock market need to be analyzed. These research findings contribute to a better understanding of market behavior for investors and regulatory agencies, enabling them to formulate strategies and measures to address market fluctuations and risks. The results underscore the noteworthy influence of investor sentiment on stock market returns and during market crises. Additionally, factors such as media influence, herding behavior, and overreaction shed light on the behavior and decisions of investors during this unique period.

A Literature Study of Behavior Finance and Investor Decision-Making

One of the most contentious topics in the development of modern financial economics has been the rationality of financial markets. Conventional finance postulates that investors are rational and impartial, capable of critically assessing the risks and returns associated with investments, and thus making unbiased investment decisions. Nevertheless, as time went on, there were increasing voices from a considerable academic community against the rationality assumption. Among those, behavioral finance has developed to challenge the legitimacy of the rational theory's underlying premises. It has emerged as a field that focuses on studying the actual behavior of investors in financial markets. The paper examines some consensus of traditional financial theories and anomalies in the stock market to introduce prominent cognitive biases influencing people when making investment decisions. It explores emotions behind the cognitive biases and the ways to impact investor behavior and thus gives suggestions about how to reduce errors in financial markets and capitalize on the mistakes of others by adopting an investment strategy that runs counter to common practice.

The Impact of Financial Indicators on Different Types of Investors

This article begins by delineating the historical trends in stock prices exhibited by three focal companies. A thorough analysis of these stock price trends ensues, accompanied by an elucidation of various investor profiles. Following this, an evaluation of market responsiveness, debt management efficiency, profitability, and prospective developmental trends is conducted through the computation of diverse financial ratios and indicators. A detailed examination of market responsiveness, debt management efficiency, and profitability enables us to attain a deeper comprehension of the financial robustness of these companies. Concurrently, an exploration of their future development trajectories allows us to prognosticate their prospects within the competitive market landscape. This information is of paramount importance for prospective investors, as it can aid them in making judicious investment choices and formulating personalized investment strategies. Ultimately, drawing upon the comprehensive analysis, tailored recommendations are devised for potential investors. These recommendations are meticulously tailored to the specific characteristics of each company, providing invaluable guidance for the strategic orientation and investment decisions of astute investors.

Portfolio Based on AR Model Using 5 Stocks

An investment portfolio is a collection of stocks, bonds, and financial derivatives held by investors or financial institutions, aimed at diversifying risks and maximizing returns. This article selects stocks of Manulife, BOA, Apple, PLC, and National Pharmaceutical Group from October 21, 2022 to August 9, 2023. This article uses AR model, minimum variance model, and maximum Sharpe's ratio model to predict stock prices, and establishes investment portfolios based on the predicted values. Firstly, based on the first 75% of the data, this article predicts the last 25% of the data. Secondly, based on the prediction, the minimum variance model and the maximum Sharpe ratio model are applied and compared with SP500 within the same time frame. However, the results indicate that the SP500 index performs best in terms of yield. This study suggests that purchasing market index funds is an important investment decision for investors during the volatile US dollar interest rate hike cycle.

Do Emotions Influence Investor Behavior?

Despite much discussion in the psychology and marketing literature as to how emotions influence decision-making, this area of analysis has been largely neglected in the finance literature. We redress this important gap by using proxies for emotions drawn from the news and social media to evaluate their influence on investment decisions and ultimately asset pricing. We find strong evidence to support that emotions do influence investor decision-making and provide important insights into the nature of this relationship. In general, we find those positive emotions such as trust and optimism are more influential in shaping investors’ reactions than are negative emotions. Finally, the emotions based on the news media listings have a greater influence on stock valuations than those based on social media listings.

Reconciling sustainability preferences and behavior — The case of mutual fund investments

This study analyzes the interaction between sustainability preferences and investment behavior, particularly in the context of mutual fund investments. Based on survey data from a representative sample of Swedish mutual fund investors, we observe that while a majority of respondents express a willingness to sacrifice returns for more sustainable investments, only a minority claim to have actively invested in sustainable funds. This highlights a discrepancy between preferences and behavior, which we show can be understood by (in)attentiveness in the financial decision-making process. We reveal that sustainability-motivated investors are less attentive than those motivated by returns, leading to potential misalignment with their preferences. This finding emphasizes the significance of banks taking (in)attentiveness into account when communicating with customers. Information is effective for return-focused investors, while nudges and boosts may better facilitate decisions for sustainability-focused investors.

Forecasting the price of oil: A cautionary note

We study the out-of-sample predictability of monthly crude oil prices using forecast combinations constructed from several individual predictor forecasts. Our empirical results indicate that combination forecasts of monthly average oil prices are more accurate than the no-change forecast with statistically significant reductions in mean square forecast errors (MSFE) and significant directional accuracy at every horizon up to 24 months, consistent with earlier evidence that forecast combinations greatly enhance the forecastability of oil prices. In contrast, we find no significant MSFE reductions or directional accuracy for forecasts of end-of-month oil prices at almost all horizons. Furthermore, we document that end-of-month forecasts when used to guide investment and hedging decisions of investors, statistically, do not deliver superior economic value to investors. Overall, the implication of our results is that the statistical and economic significance of forecasts of oil prices is heavily influenced by the construction of the underlying oil price series and provide a cautionary note on which oil price series to use in forecasting.

Nexus of the CSR disclosures and corporate financial performance: evidence from Asian countries climate policy uncertainty.

Financial performance is a critical aspect of a company's overall health and sustainability. It directly influences investor decisions, stock market performance, credit ratings, and the company's ability to access capital. Corporate financial performance is influenced by multitude of facts, both internal and external such as disclosure of the information, and social and environmental factors. On the ground of the facts, we aimed to investigate non-financial firms that belong to Asian economies affected by climate policy uncertainty and corporate social responsibility disclosures in terms of their financial performance. To conduct quantitative study analysis, we used the two effective statistical tools such as two-stage regression method and generalized method of movement (GMM). Our results show that corporate high value of social responsibility disclosure and climate policy uncertainty has significant negative impact on return on asset (ROA) of the listed organizations of China, Pakistan, and India. Moreover, CSR disclosure attributes higher values such as social (SC) and governance score (GOV), and climate policy uncertainty (CPU) has significant negative relationship with return on equity (ROE) and earning per share (EPS) respectively, while a higher value of ESG total score and the environmental (ENV) score has a significant positive impact on ROE and EPS. Additionally, the research concludes that climate policy uncertainty is a key factor that motivates CSR disclosure practices, which ultimately improves corporate financial performance. Moreover, we concluded from our finding that the climate policy uncertainty creates ambiguity surrounding government regulations, international agreements, or market mechanisms that affect financial performance. Moreover, environmental disclosure information that has the large part in total ESG scores attract the investors around the globe which leads to rise in the financial performance, while the other attributes of the CSR disclosure decrease performance. This study advocated the great implications for researchers, investors, the government, and regulatory authorities. Policy makers can make the policy about the CSR disclosure for creating the good image of the organization to attract investors around the globe.

Indian institutional investor's portfolio concentration decision: skill and performance

PurposeThis study examined Indian institutional investors' holding data to understand their investment strategy (Portfolio Concentration/Diversification) and explored whether their skills were associated with their portfolio strategy and performance. The study introduced a new proxy to identify skilled investors by forecasting abnormal returns. Moreover, the study also highlighted where skilled Indian investors put their money for long-term investment.Design/methodology/approachThis study measures portfolio concentration based on the number of holdings, the Hirschman–Herfindahl index (HHI) and benchmarks adjusted industry concentration. The study introduced a new proxy to identify skilled investors. We measured Investors' performance with the help of Carhart's four factors model and examined the relationship between variables through various regression models.FindingsThe study concluded a negative relationship between portfolio concentration and performance. However, skilled Indian investors get rewards from portfolio concentration decisions. It was found that skilled investors with few stocks and an industry concentration in their portfolio show a positive association between concentration and fund performance. Additionally, this study found Indian investors showing their faith in the financial sector for long-term investment.Originality/valueThis study examined Indian institutional investors' portfolio concentration strategy and introduced a new proxy to measure investors' skills.

Risk Tolerance in Investment Decisions: Are Personality Traits the Real Triggers?

Purpose: Investment decisions of investors are strongly influenced by their risk tolerance. Previous research suggests that risk tolerance is influenced by various social, economic, demographic and psychological factors. This research aims to extend the investigative line of inquiry regarding the influence of one such psychological factor, that is, personality, on the risk tolerance of small investors without limiting their asset class or classifying them into any groups. Design/Methodology/Approach: A quantitative research method is used to measure personality traits and risk tolerance in the investment decisions of small investors in Kashmir. The study uses a structured questionnaire adopted in parts from various established scales to collect data from small investors. Correlations and multiple regression have been used to arrive at the results. Findings: Results of the study indicated that extrovert and open-to-experience individuals showed tolerance to risk. In contrast, conscientious, neurotic and agreeable individuals were risk-averse in the geographical location considered for this study. The results imply that financial advisors must consider the personality traits of investors when giving investment advice to small investors. Practical Implications: It becomes essential for financial planners and advisors to follow an investor-centric approach wherein they consider the personal characteristics of individuals when giving investment advice, and they must design the portfolios/investment avenues according to the investors’ personalities. The results of this study show that investors with different characters have different risk-taking capabilities, and a particular investor will feel comfortable investing in a specific risk-class asset. Originality/Value: There is no study or research about the influence of personality traits on risk tolerance in investment decisions in this particular geographical area, that is, Kashmir. Therefore, this study will contribute significantly towards understanding investor behaviour and help financial advisors and investment bankers suggest appropriate investment avenues.

Motivation for households' investment in photovoltaics in Czechia: An exploratory factor analysis

Photovoltaics (PV) are an integral part of the climate neutrality transition; aside from reducing fossil fuel consumption, they provide additional and impactful private and societal benefits. When purchasing PV, the decision-making of small investors is a complex process. We investigate how households decide to invest in PV on rooftops. From a sample of over 2500 respondents, we found that while personal financial benefits are the primary motivation for acquiring PV plants, other variables, such as production independence and ecological benefits were almost equally important. The factor analysis revealed four latent motivation factors that drive the decision-making: economic, technical, ecological, and surroundings. Additionally, households are not fully homogenous in their decision-making. Education, income, and age influenced the attribution of importance the respondents gave to the specific factors. Conversely, the settlement size was not a strong predictor of the decision-making. The results imply the need for diversified policy design across different groups of investors.

Analysis of Stock Value in the Science and Technology Innovation Board Market: A Principal Component Analysis Approach

The factors influencing stock returns have been extensively studied in the current academic sphere. In this study, the factor analysis method is employed to assess the investment value of stocks in the Science and Technology Innovation Board market (STAR Market) using indicators such as asset-liability ratio, current ratio, quick ratio, gross profit amount, YoY growth rate of net assets, asset return rate A, return on equity ratio ROEA, operating net profit margin, earnings per share of net assets, sales operating profit margin, and YoY growth rate of total assets. Factor scores are derived using principal component analysis. The obtained factor scores are ranked in descending order, revealing that Juchen Corporation holds a factor score of 1.11, ranking first among all companies and demonstrating the highest investment value. Following closely are EastMicro Semiconductor and Baochu Electronics. Additionally, this paper summarizes the stock performance of 20 other companies, offering investors a reference for value-based investment decisions. The quantitative findings of this study facilitate informed decision-making for investors, serving as a valuable reference for their investment strategies.

Price of Ethereum Token Effect on the Non-Fungible Token User Trading Activities in the 2020s

This research investigates the relationship between the price of the Ethereum token and Non-Fungible Token (NFT) trading activities on the Ethereum blockchain in the 2020s. Through regression analysis and t-tests, the study explores how changes in Ethereum's price and price volatility influence NFT trading behaviors. The regression analysis reveals significant positive correlations between Ethereum's price and various NFT trading variables, indicating that an increase in Ethereum's price positively impacts sales volume, unique sellers, unique buyers, and average sales of NFTs. Conversely, Ethereum's price volatility demonstrates significant negative associations with NFT trading activities, suggesting that market uncertainty and risk aversion influence investor decisions. The findings provide valuable insights for practitioners, investors, and traders in the NFT market, offering guidance for decision-making strategies and market trends; however, the study also acknowledges limitations in establishing causal relationships and suggests future research directions. Understanding the dynamics between Ethereum's price and NFT trading activities is crucial in navigating the evolving landscape of blockchain-based assets and decentralized markets.

A Closer Look of How Individual Investor Make Investment Decision: Systematic Review

The aim of this study is to examine the existing literature on the factors that influence the investment decisions made by individual investors. The employed methodology is a systematic literature review conducted using the PRISMA approach. The choice of Scopus as the information source was based on its status as the largest and well reputable scientific database. We obtained data from internet databases that contain extensive collections of scholarly studies, journal articles, and conference papers. These resources are written in English and are readily available to the authors. Using a predetermined string, 275 articles were extracted from Scopus. Ultimately, 137 papers were found to fit the criteria for analysis in discussing the factors that determine investing decisions for individual investors. The result show that there are five main determinant of investment decision for individual investor: Financial literacy, emotional biases, gender, generation y and long-term orientation. The implications of this study will be discussed later.

Does religion matter to angels? Exploring the influence of religion in entrepreneurial investor decision-making

Despite the pervasive influence religion has on society, the role of religion in angel investor decision-making remains unknown. This study tests a model of how religion – both as a guiding institutional logic and a personal religious belief – influences angel investor evaluations. Drawing on the similarity attraction paradigm and expectancy violation theory, two scenario-based experiments find religion has a persistent but nuanced influence on investor evaluations. Generally, religious claims are a double-edged sword, either repelling or attracting angel investors. Specifically, faith-driven investors form positive evaluations of the venture but only when these evaluations are mediated by entrepreneur authenticity. By comparison, traditional angel investors form negative evaluations when religious claims are present, except for when angel investor religiosity is high. This suggests that faith-driven and traditional angel investors use different bases for evaluating entrepreneurs and ventures. Overall, our results have important implications for understanding the theological turn to entrepreneurship by finding religion as a double-edge sword, a multilevel influence, and a cognitive mechanism within investor decision-making.