Decisions Of Investors Research Articles

Legal environment as a factor in the inflow of Foreign Direct Investment: Case of Serbia

The economic growth and development of a country depend on the inflow of foreign direct investment, and the legal environment factors play an important role in securing it. Compared to other countries in South-Eastern Europe, Serbia has achieved remarkable results in terms of FDI inflows over the last ten years. The research examines the impact of the legal environment on FDI inflows in Serbia. The study was conducted using a quantitative approach and a survey technique based on a structured questionnaire. The basic set of the research consists of the 300 most prominent foreign investors (response rate of 28%) who invested capital in Serbia in the period 2011-2019. The results of the conducted research show that ownership in Serbian companies is the most important factor in the legal environment that influences a foreign investor's decision to invest capital in these companies. The results show that labor legislation, law enforcement, and confidence in the legal system can significantly contribute to a foreign investor's decision to invest capital in Serbia. The legal environment's implications influence investor decisions and shape the overall investment climate of a country. A well-structured and investor-friendly legal framework will increase Serbia's competitiveness and attractiveness for foreign investments.

Application of artificial intelligence Sensors based on random forest algorithm in financial recognition models

Due to the important role of financial information disclosed by enterprises in investor decision-making and economic policy formulation, the corporate market has set the latest standards and requirements for the quality of financial reports. In the current situation, financial recognition work is mainly completed manually, which is inefficient and prone to errors, and is not suitable for large-scale applications. Therefore, we conduct in-depth research on financial recognition models. Firstly, we analyzed the random forest algorithm and used the SMOTE algorithm to expand the sample data. We successfully constructed an optimized random forest algorithm model, which can better improve accuracy and reduce misjudgment rates. Secondly, combined with the current financial data analysis of artificial intelligence technology, the steps for data management and data extraction were designed. Finally, while establishing a financial recognition model, a channel for obtaining internet information and a program for processing this information were also established. After experimental verification, the random forest model has shown better fitting performance in the field of financial fraud identification, providing more reliable support for applications in this field. Therefore, the financial recognition model constructed using artificial intelligence technology based on random forest algorithm has significant value in both theoretical and practical aspects, effectively reducing corporate financial risks.

PENGARUH UMUR, GENDER, KEAKTIFAN, EXPERTISE FINANCE DAN MASA JABATAN KOMITE AUDIT TERHADAP MANAJEMEN LABA

Financial report information is a basic reference for making investment decisions for investors and shareholders. The profit achieved by a company is often a measure in assessing a company's performance. This shows that the existence of profits in financial statements is very important so that supervision over its presentation is needed to avoid earnings management behavior by management, which can obscure financial information to make it less appropriate to current developments. One effort that can be made is to make changes in the management of business entities by having an audit sub-organization division or known as an audit committee as part of improving company control. In this research, testing the existence of an audit committee focuses more on the personal characteristics of each member. In this research, testing the existence of an audit committee focuses more on the personal characteristics of each member. The aim of this research is to examine and analyze the influence of the factors age, sex or gender, level of activity, experience in financial expertise and the general term of office of the audit committee on earnings management. This quantitative research used eighty-five samples of manufacturing companies listed on the Indonesia Stock Exchange for the 2017-2019 period. The research sample was determined using a purposive sampling technique with reference to certain criteria. The data analysis technique used is multiple linear regression. The results of this study show that the age of the audit committee has a negative effect on earnings management, while the gender of the audit committee, the level of activity of the audit committee, understanding of the audit committee's financial expertise and the age of the audit committee's term of office have no effect on earnings management.

THE IMPACT OF ARTIFICIAL INTELLIGENCE RECOMMENDATIONS ON INDIVIDUAL INVESTOR DECISIONS

Purpose- Although artificial intelligence technology is a new technology, it affects every aspect of our lives by finding a very fast field of activity. Artificial intelligence technology, which also shows its effect in the field of finance, is seen to have many applications. There are many alternatives in the investment markets, it will take a long time to make a profit in the markets and a certain amount of knowledge is required. People cannot master the data in all markets when they will invest, but technological developments provide the opportunity to invest by storing each data or observing their changes. This study aims to investigate the effects of artificial intelligence technology on individual investor decisions. Methodology- The study consists of individual investors who live in Diyarbakır province and generally make investments. The questionnaire prepared in accordance with the scope of the study was applied to 1800 participants using face-to-face survey method. The 22 statements prepared in accordance with the scope of the study were applied to the participants. The questionnaires that 1616 participants answered correctly and accurately were included in the scope of the study. In order to ensure the reliability of the study statements, Cronbach's Alpha was calculated and this rate was determined as 91%. The answers given to the study statements were transferred to the tables as a result of the analyses. The transferred information was tried to be interpreted. In addition, frequency tables, t-test and anaova analysis were used in the analysis of the study data. Findings- Thanks to artificial intelligence algorithms, which is one of this technology, it analyses the data in the market and enables the investor who wants to invest to trade in the market by giving buy and sell orders. Thus, artificial intelligence technology allows the investor to make more profitable investments by guiding the investor. Conclusion- As a result, it is possible to say that the individual investors participating in the research do not have sufficient knowledge about artificial intelligence technologies, but they have an interest in investing using artificial intelligence technologies. In addition, it has been determined that the older the age, the lower the education level, the higher the income level and the married investors are insecure about investing using artificial intelligence technology.

Revving Up or Stalling Out? A Comprehensive SWOC Analysis of BSE listed India's Auto Sector

Purpose: The primary purpose of this research paper is to conduct a comprehensive SWOC (Strengths, Weaknesses, Opportunities, and Challenges) analysis of the Indian automobile sector, which plays a vital role in the economy by contributing to GDP, employment, and technological progress. Amidst globalization, technological changes, and evolving consumer preferences, the industry faces numerous internal and external factors affecting its performance. By systematically evaluating these factors, the research aims to provide insights into the sector's current state and future prospects, informing strategic decisions for stakeholders, policymakers, and investors. This study fills a gap in existing literature by offering a holistic assessment using the SWOC framework, uncovering strengths, weaknesses, opportunities, and challenges to support the industry's competitiveness and sustainability. Design/Methodology/Approach: The study employs a qualitative research approach, utilizing both primary and secondary data sources. Primary data includes industry reports, company publications, and expert interviews, while secondary data encompasses academic journals, government publications, and reputable online sources. SWOC analysis is conducted to identify and evaluate the internal strengths and weaknesses of the industry, as well as external opportunities and challenges it faces. Findings/Results: The SWOC analysis reveals several key insights into the Indian auto industry. Strengths such as a skilled workforce and a growing domestic market are counterbalanced by weaknesses such as infrastructure bottlenecks and regulatory challenges. Opportunities arising from technological advancements and export potential are tempered by threats such as global competition and changing consumer preferences. Originality/Value: This research contributes to the existing literature by offering a comprehensive assessment of the Indian auto industry through the SWOC framework. By synthesizing insights from various data sources, the paper provides valuable insights for industry stakeholders, policymakers, and investors seeking to navigate the complexities of the Indian automotive landscape. Paper Type: Descriptive Research

Research on Prediction and Analysis of Shanghai Stock Index Based on the ARIMA Model

This study aims to analyze the future trends of the Shanghai Composite Index (SSE Composite Index), a primary stock index on the Shanghai Stock Exchange (SSE). The SSE Composite Index not only serves as a crucial indicator of the Chinese capital market but also attracts global attention as a focal point in financial markets worldwide. Its fluctuations have broad impacts, influencing decisions of investors and the global economic environment. Due to the increasing limitations of traditional forecasting methods such as moving averages and exponential smoothing in the face of the complexity and uncertainty of financial markets, this paper chooses to employ the Autoregressive Integrated Moving Average (ARIMA) model for more accurate and sophisticated predictions. The paper provides a literature review to outline relevant studies, delves into the specific processes of data preprocessing and model establishment, and concludes with empirical analysis and result discussions. The study suggests that the ARIMA model remains effective and feasible in predicting the SSE Composite Index.

The impact of financial analysts’ spirituality on their socially responsible investing decisions: a mediating role of social consciousness

PurposeThis paper aims to contribute to the social aspect of corporate social responsibility literature by examining the influence of financial analysts’ spirituality on their socially responsible investing (SRI) decisions relating to a profitable organization, which is alleged by the media to employ children as laborers in hazardous works in Pakistan. This study also investigates whether analysts’ social consciousness mediates between their spirituality and investing decisions.Design/methodology/approachA scenario-based survey was administered to 124 financial analysts at leading financial institutions in Pakistan. Data were analyzed using regression, analysis of variance and mediation analysis on SPSS 26.FindingsThe findings demonstrate that financial analysts’ spirituality negatively influences their SRI decisions to invest in a profitable organization, which is alleged to employ children in hazardous work that may harm them physically and psychologically. The findings also express that analysts’ social consciousness intervenes in the association between analysts’ spirituality and SRI decisions.Practical implicationsThe findings of this study may interest regulators, multinational firms and researchers in recognizing the importance of individuals’ values for increasing socially responsible investments and addressing social issues such as the exploitation of children.Social implicationsThis study encourages firms to recognize the importance of spiritual and socially conscious corporate conviction while designing strategies and policies. For example, the financial industry may incorporate fundamental personal values such as stewardship, dignity and fairness into its investment plans.Originality/valueThis study provides rigorous insights and contributes to contemporary studies by providing empirical evidence that individuals’ intrinsic values and consciousness drive their judgments.

The Influence of Behavioural Factor on Retail Investors Decision Making in IPO Investment

This study explains about the influence of behavioural factors on retail investors in decision-making processes when considering the investments in Initial Public Offerings (IPOs). IPOs represent an attracting investment opportunity for the retail investors, often they are characterized by significant up-and-downs and uncertainty. Understanding the psychological factors for guiding investors decisions in this factor is crucial for both investors and the market regulators. Outlining over the behavioural finance theories and the actual evidence, this research explores various psychological biases and emotional influences that may affect the retail investors during the IPO investment decision-making. psychological biases such as overconfidence, group behaviour, and loosing, along with the emotional factors like fear of missing out (FOMO) and loss aversion, are analyzed in the factors of IPO investments. Here the methodology involves a combination of quantitative analysis, utilizing survey data from the retail investors, and the qualitative examination ofrelevant literature and case studies. By analyzing the behavioural factors influencing the IPO investment decisions this research study intends to give understandings right nto the primary mechanisms driving retail investors behaviour in IPO markets.

A Comprehensive Analysis of Behavioral Finance and its Impact on Investment Decisions

This paper thoroughly examines behavioral finance, challenging traditional financial theories by questioning investor rationality and market efficiency. Focusing on five key phenomena—loss aversion, short-term momentum, long-term reversal, framing effect, and endowment effect—the analysis relies on real-world observations to reveal how psychological biases significantly impact investor decisions and financial markets. Loss aversion, especially evident during financial crises, highlights humans' tendency to avoid potential losses rather than pursuing equivalent gains. The study explores short-term momentum and long-term reversal, challenging market efficiency theories by illustrating how past performance influences future returns. Emphasizing cognitive biases like framing and endowment effects, the paper underscores their role in diverse investment decisions and irrational asset overvaluation based on a sense of ownership. It advocates for incorporating these biases in financial models, regulations, and investment strategies, emphasizing their importance for stakeholders to navigate the financial landscape, minimize instability, and capitalize on opportunities. The research establishes a foundation for a holistic finance approach, respecting and leveraging human behavior for market stability and benefit.

Forecasting tail risk of skewed financial returns having exponential‐polynomial tails

AbstractAggregated long and short trading risk positions of speculative assets over time are likely to be unequal. This may be because of irrational decisions of traders and investors as well as catastrophic events that lead to pronounce or salient market crashes. Returns of such assets are therefore more likely to have one polynomial tail and one exponential tail. The generalized hyperbolic (GH) skewed Student‐t distribution is known to handle such situations quite well. In this paper, we use generalized autoregressive conditional heteroscedasticity (GARCH) models to empirically show the superiority of the GH skewed Student‐t distribution in forecasting the extreme tail risks of cryptocurrency returns in the presence of substantial skewness in comparison with some competing distributions. Furthermore, we show the practical significance of the GH skewed Student‐t distribution‐based risk forecasts in computing daily capital requirements. Evidence from the study suggests that the GH skewed Student‐t distribution model tends to be superior in forecasting volatility and expected shortfall (ES) but not value‐at‐risk. In addition, the distribution yields higher value‐at‐risk (VaR) exceptions but surprisingly avoids the red zone of the Basel II accord penalty zones and produces lower but optimal daily capital requirements. Therefore, in the presence of substantially skewed returns having exponential‐polynomial tails, we recommend the use of the GH skewed Student‐t distribution for parametric GARCH models in forecasting extreme tail risk.

Investment Decisions of the Individual Investors in the Capital Market of Bangladesh

Investment decisions of the individual investors in the capital market are influenced by various factors. Main objective of this study is to find out the influences of the factors on investment decisions of individual investors in the capital market in Bangladesh. A highly structured questionnaire has been used to collect primary data from 384 individual investors who are traded in the Dhaka Stock Exchange (DSE). The study respondents have been selected at a simple random method. Analysis of variance (ANOVA), multiple regression model, graphs, charts and tabular analysis have been used to analyze collected data and to test hypotheses of the study. The results showed that EPS has positive influence (β=0.0682, t=1.2439 and p=0.2143, test of hypothesis 2) on investment decisions and rank of EPS is 4 with mean score of 3.8099 and S.D=0.5087 (table 3). It has also found that dividend has positive relationship (β=0.0590, t=1.1054 and p=0.2697, test of hypothesis 3) with investment decisions and dividend is ranked 6 with mean score of 3.5755 and S.D=0.5593 (table 3). Accordingly, P/E ratio has a negative influence (β =-0.0069, t=-0.1341 and p=0.8934) on investment decisions of the individual investors. Therefore, this study will be very helpful to the individual investors to make correct investment decisions by analysing EPS, dividend trends and P/E ratio of the company.

A STUDY ON BEHAVIORAL BIASES IN INVESTMENT DECISION

This research prospects how an individuals behavioral biases affect investment decisions. Behavioral biases are rational tendencies that influence the decisions of the people, especially in fields like investing. This study does a qualitative investigation of behavioral biases in investing decisions. Investors frequently make irrational judgments as a result of behavioral biases that originate from intellectual and emotional reasons. This research tries to discover prevalent behavioral biases influencing investing choices and comprehend the effect they have on financial results by combining findings from prior studies. The literature analysis stresses the major biases that influence investment behavior, including herd mentality, loss aversion, and overconfidence. The study emphasizes how crucial the intent is to identify and counteract these biases to enhance financial outcomes and investment decision-making. KEYWORDS: Behavioral biases, investment decisions, qualitative investigation.

Young Investors' Decision to Select Islamic Mutual Fund Investment Applications for Students in Jember: The Impact of Brand Image, Electronic Word of Mouth, and Perceived Ease of Use

This study aims to determine the effect of brand image, electronic word of mouth, and perceived ease of use on young investors decisions in choosing Islamic mutual fund investment applications for students in Jember. This type of research uses explanatory research and uses a quantitative approach. Researchers used primary data obtained from distributing questionnaires to students in Jember with a sample of 150 respondents. The technique used was purposive sampling technique to select samples. Multiple linear regression analysis is the method used in this study using SPSS software version 26. This study shows the results that the t test (partial) variable electronic reviews and perceived convenience affect young investors in choosing an Islamic mutual fund investment application while brand image does not affect young investors decisions in choosing investment applications

Impact of Personality Traits on Investment Decisions with the Moderating Effect of Financial Literacy

At the heart of any economic advancement lies the pivotal decision-making process. For investors seeking to deploy their capital strategically and enhance their returns, the art of selecting investments is paramount. There are several factors to consider before choosing an investment. This study's goal is to evaluate the influence of personality characteristics (extraversion and neuroticism) on investing decisions, with financial literacy serving as a moderating factor. 204 investors and master's level students made up the sample size for the questionnaire survey that was done for this study in order to collect primary data from the intended respondents. Using the SPSS software, this survey was conducted. Analysing the data and verifying the hypotheses involved the use of statistical methods including mean, standard deviations, correlation, and regressions. The analysis's findings indicated that neuroticism, extraversion, and investment decisions all have a significant impact. Financial literacy also has a positive and significant impact on investment decisions, but it does not moderate the relationship between these three variables and investment decisions.

Behavioral Biases and Regional Diversity: An In-Depth Analysis of Their Influence on Investment Decisions - A SEM & MICOM Approach

The Basic purpose of the study was to understand the impact of behavioral biases on Global Investors investment Decisions and whether there is any significant difference of the impact on investment Decisions of Global investors due to regional diversity. The data was collected from 467 Global investors from China and India SEM was used to test the hypothesis and Followed by Multi- group analysis. The results revealed that Behavioral biases have a significant on investment decisions of Global Investors. The impact was found more on India Global investors than that of China. The insight into how regional diversity can magnify or attenuate these biases offers valuable guidance for global investment firms seeking to tailor their services to a culturally diverse clientele. Understanding the interplay between behavioral biases and regional disparities allows for the development of region-specific financial products and advice, better aligning investment strategies with the unique needs and risk tolerance of investors from different parts of the world. The originality of this research lies in its nuanced examination of how behavioral biases, in conjunction with regional disparities, can offer valuable insights for both investors and financial practitioners, enhancing our comprehension of the intricate dynamics at play in the global investment sphere.

The Impact of Accounting Information Quality on Corporate Investor Relations Research

This paper aims to explore the impact of accounting information quality on corporate investor relations and proposes corresponding enhancement strategies. The paper begins with an overview of accounting information quality and analyzes its importance to investors. It then delves into the impact of accounting information quality on investors, such as the effects of information asymmetry and information transparency on investor decision-making and trust. Furthermore, strategies for improving accounting information quality are proposed, providing reference for enterprises to optimize their accounting information quality.

Analysis of Profit Quality and Esg: Investor Determinants in Decision Making

This research aims to interpret the concepts of ESG and earnings quality in terms of their influence on investor decisions. Using an interpretive paradigm, this researcher tries to interpret the meaning of ESG factors and earnings quality by researching social phenomena. Data was obtained using in-depth interviews with lecturers, students and general investors who were key informants. The method used is the snowbolling system. The interview results are grouped and data reduction is carried out before being analyzed and conclusions drawn or verified. Triangulation was also carried out using different question techniques asked to ensure the validity of the data to key informants. By using triangulation techniques, researchers ensure that the data obtained is valid. The results of this research found that ESG factors and earnings quality are interpreted in material terms, environmental and social responsibility and goodness or spirituality in the context of determining factors in investment decisions. Empirically, in a broader sense, ESG factors and earnings quality are not only interpreted as financial benefits but as a reflection of investor awareness of their positive impact on the environment and social and mutual benefits.

Spillover effects of multidimensional information in Fed statements on China's bond market

This paper shows significant information spillover effects of Fed statements on China's bond market. Regarding Fed monetary policy statements as external shocks, we extract both monetary policy information and narrative sentiment information from the statements, with the sentiment data measured using the text analysis method. Furthermore, it investigates spillover effects of the multidimensional Fed information on investors' trading behaviors in China's bond market, using the event study method. Our study emphasizes three key findings. First, both monetary policy and textual sentiment within Fed statements influence trading decisions of China's bond investors, generating international spillover effects. Importantly, the role of textual sentiments as an additional spillover channel of Fed statements has been overlooked in existing literature. Second, the US monetary policy information influences investors' expectations of China's short-term interest rates and their perceptions of risks associated with holding China's long-term bonds, while the Fed's negative and uncertain sentiments primarily impact investors' short-term rate expectations. Moreover, the spillover effects of Fed sentiments on China's yield curve cannot be blocked by China's managed floating exchange rate regime. Third, the heterogeneity test reveals that spillover effects of multidimensional information in Fed conventional monetary policy statements on China's bond market are stronger than those of Fed unconventional monetary policy statements. These findings suggest that Fed narrative sentiments should be incorporated into the research framework of international spillover effect of monetary policy, especially amidst the current period characterized by growing anticipation of federal funds rate cuts and enduring monetary policy uncertainty, providing valuable insights for trading decisions of China's bond market investors.

THE ROLE OF INTERNATIONAL ACCOUNTING STANDARDS IN FOSTERING CORPORATE REPORTING TRANSPARENCY

This research investigates the multifaceted impact of International Accounting Standards (IAS) on corporate reporting transparency. Amidst the interconnected global business landscape, the study aims to discern global adoption trends, financial reporting quality, stakeholder perceptions, implementation challenges, and the responsiveness of IAS to industry dynamics. Through meticulous analyses spanning the years 2010 to 2020, the research unfolds key insights.The adoption of IAS is a critical facet of global financial reporting, influencing business practices, investor decisions, and regulatory frameworks. Understanding its impact is paramount for policymakers, standard-setters, and businesses navigating an increasingly interconnected and diverse financial ecosystem.This research seeks to comprehensively examine the intricate relationship between IAS and corporate reporting transparency. By delving into adoption trends, financial metrics, stakeholder perspectives, implementation challenges, and update responsiveness, the study aims to provide a holistic view of the global accounting landscape.The analysis reveals a consistent upward trajectory in global IAS adoption, with North America and the Asia-Pacific region playing pivotal roles. Financial reporting quality experiences substantial improvements, particularly benefiting smaller enterprises. Stakeholder perceptions vary across regions and professional roles, emphasizing the need for tailored communication strategies. Implementation challenges, including legal framework complexities and cultural differences, underscore the intricate nature of global adoption. The frequency of IAS updates showcases the adaptability of standards to emerging trends, emphasizing sector-specific implications.This research concludes that IAS significantly influences corporate reporting transparency, offering a standardized framework for diverse business scales. Challenges in implementation necessitate targeted interventions, with recommendations focusing on stakeholder communication, tailored support for small enterprises, and addressing legal and cultural complexities. The adaptability of IAS to industry dynamics reaffirms its role as a responsive and evolving standard. As businesses, regulators, and standard-setters move forward, continuous collaboration and flexibility become imperative for navigating the complexities of a globally harmonized financial reporting landscape.

Kaitan Mental Accounting Dan Perilaku Keuangan Terhadap Keputusan Investasi Investor Milenial Post Pandemi Covid 19

The Covid-19 pandemic has made online purchases increase quite dramatically. T The focus of mental accounting is how one should respond and evaluate a situation when there are two or more possible outcomes. The concept of behavioral finance takes into account various types of investors in the perception of risk associated with investment decisions. In this study, an analysis was carried out regarding how the influence of Mental accounting and Behavioral finance owned by Millennial investors in Denpasar on investment decisions. The sample was taken using a purposive sampling technique, so that the total sample is 100 millennial investors. The results of this study show that mental accounting and behavioral finance positively and significantly influence the investment decisions of millennial investors in Denpasar.