Informed Investment Decisions Research Articles

National Bombay Stock Trade Market Expectation Utilizing KNN Calculation

Predicting stock prices is a fascinating and difficult area of study. The economies of developed nations are compared to their power economies. As a result of their easy profits and low risk rate of return, stock markets are currently regarded as an illustrious trading field. For researchers in data mining and business, the stock market is thought to be a good place to work because of its numerous and constantly changing information sources. In order to assist investors, management, decision-makers, and users in making correct and informed investment decisions, we used the k-nearest neighbour algorithm and a non-linear regression approach in this paper to predict stock prices for a sample of six major companies listed on the Jordanian stock exchange. The results indicate that the KNN algorithm is reliable with a low error ratio; Consequently, the outcomes were reasonable and rational. Additionally, the prediction results were nearly identical to the actual stock prices, depending on the data on the stock price.

The Influence of ESG Principles on the Activities of Non-State Pension Funds of the Russian Federation

According to the data presented, slightly more than 60 % of all pension funds of the pension market of the Russian Federation are invested in one way or another in the Russian economy, therefore, the analysis and forecast of the development of a particular sector of the economy in the perspective of the ESG agenda determines the future standard of living of pensioners of the next generations. It is concluded that in light of the rapidly changing prospects of climate change, depletion of limited resources, and increasing income inequality, it is already necessary to take into account and predict ESG risks for NPFs. The study determined that the ESG agenda already has an impact on the activities of the NPF. The society expects from all subjects an awareness of responsibility for the future state of the economy, economy and society. The research formulated two directions in the strategic development of the NPF: the adjustment of the investment strategy taking into account the principles of sustainable investment, and the introduction of ESG principles into the current activities of the NPF. It is noted that when making investment decisions, NPFs today face the problems of finding a suitable asset, access to the necessary information, and the adequacy of existing ESG ratings for making an informed investment decision. The study concluded that the application of these principles in current activities will have a beneficial effect on the reputation profile of NPFs, which will have a positive impact on the effectiveness of their activities.

A Risk-Return Analysis of SBI Mutual Fund

The aim of this study is to analyse the financial performance of SBI equity fund using statistical parameters (Standard Deviation, Beta, and Correlation Coefficient) and ratio analysis (Sharpe Ratio, Treynor Ratio). The study collected five years of data from SBI mutual fund house and focused on providing insights into the financial performance of selected mutual fund schemes. The findings of the study suggest that all SBI mutual funds have yielded more returns than bank fixed deposits.. Notably, the SBI Small Cap fund has been identified as the most volatile fund with the highest returns, while the SBI PSU fund has been found to be less volatile but with lower returns. The research findings could help investors understand the financial performance of mutual fund schemes better, enabling them to make informed investment decisions based on their risk profiles Key Words: Mutual fund, financial performance, risk return analysis

Long term currency forecast with multiple trend corrected exponential smoothing with shifting lags

In the current global economy, exchange rate forecasting is critical for investors and businesses seeking to make informed investment decisions and manage risk. While many short-term exchange rate forecasting methods exist, long-term forecasting methods are limited and often fail to account for the complex macroeconomic factors that influence exchange rate trends. However, investors need to have an analytically examined basis for deciding to invest, which requires knowing more about the future values of the related market currency. This paper proposes a new Multiple Trend Corrected Exponential Smoothing with Shifting Lags model to forecast long-term exchange rates, which incorporates multiple trend corrections and shifting lags to provide more accurate predictions of future currency values. We apply the proposed method to six currency pairs (USD/EUR, USD/NOK, USD/TRY, USD/CNY, USD/XOF, and USD/MGF) from 2006 to 2018 and compare its performance to existing methods, such as moving average, weighted moving average, and exponential smoothing. Our results show that the proposed model provides more accurate long-term exchange rate forecasts for developed countries than existing methods. Our findings have important implications for investors and businesses seeking to manage currency risk and make informed investment decisions in the global economy.

EXPLORING THE RELATIONSHIP BETWEEN MARUTI SUZUKI INDIA LIMITED 'S FINANCIAL STATEMENTS AND ITS STOCK PERFORMANCE

This study aims to explore the relationship between Maruti Suzuki India Limited's financial statements and its stock performance. Maruti Suzuki is a leading automobile manufacturer in India, and analyzing its financial statements can provide insights into the company's financial health, growth potential, and overall performance. The study focuses on key financial ratios that can indicate the company's financial strength and profitability, such as return on equity, operating margin, and debt-to-equity ratio. The research utilizes quantitative analysis to examine the relationship between these financial metrics and the company's stock performance. The study findings provide valuable insights for investors and analysts looking to make informed investment decisions in the automobile industry. Understanding the link between financial statements and stock performance can help investors assess the company's performance, identify potential risks, and make informed investment decisions. Keywords: Financial Analysis, Ratios, Stock Performance, Growth, Financial Position.

Feasibility Study of Student Financing Startup Company for BRI Ventures Investments Study Case of: “Company A”

The problem faced by BRI Venture is to determine the feasibility of investing in Company A, a start-up in the student financing market in Indonesia. The valuation of start-ups in Indonesia is difficult, making it challenging for BRI Venture to assess the viability of the investment. This study aims to provide a comprehensive analysis of the factors affecting Company A’s business, both internally and externally, in order to make an informed investment decision. The study focuses on three key research objectives: (1) to examine the macroeconomic and industry impact on Company A’s business by using Porter’s Five Forces model, PESTLE model, and market sizing; (2) to examine the internal aspects impacting Company A’s business by using the VRIO model; and (3) to determine the valuation of Company A by using the DCF and relative valuation methods. The findings of the study reveal that the Indonesian student financing market presents both opportunities and challenges. The PESTEL analysis highlights the increasing demand for student loans in Indonesia, creating growth opportunities for the industry. However, the Five Porter framework analysis highlights the intense competition, strong buyer bargaining power, and weak supplier bargaining power, which may make it difficult for new entrants to succeed. The VRIO Framework analysis suggests that Company A has a number of sources of sustained competitive advantage, including adaptable repayment terms, technological capabilities, and market position, indicating that Company A’s internal situation is strong. The Absolute Valuation and Relative Valuation results indicate that Company A valuation is between $59 million and $73 million. In conclusion, while the Indonesian student financing market presents a growth opportunity, BRI Venture must carefully consider the challenges and competition in the market before making an investment in Company A. The internal analysis of Company A suggests that it has a strong position in the market, with a range of assets and competencies that can offer a sustainable competitive advantage. The valuation results provide a range of potential equity stake that BRI Venture could ask for if an investment in Company A is made.

A Study of Nestlé Financial Analysis

Nestlé is a well-known food and beverage corporation in Malaysia and worldwide. The vision of the Nestlé company is to provide 'Good Food, Good Life to the consumers. 'Good Food, Good Life' displays the promise they commit themselves to every day, everywhere as the leading Nutrition, Health, and Wellness Company globally. The purpose of this study is to analyze the financial performance of Nestlé within five consecutive years, which is from 2016 to 2020. Financial performance must be compared to track their progress in terms of stability, liquidity, profitability, and market share retention. To compare financial performance, quantitative data from the annual report were required. Market value ratios, profitability ratios, efficiency ratios, and liquidity ratios are used to analyze a company's financial performance. Our paper provides information on the ratios that revealed the company's financial performance. This paper can be used as a guide that highlights an overview of the company's financial health, allowing investors and stakeholders to make informed investment decisions.

A Study on Impact of Big Five Personality on Investment Decisions of Mutual Fund Investors: Mediation by Risk

Mutual fund investment in India has gained significant popularity over the years as an avenue for individuals to participate in the capital markets. Understanding these psychological factors can help investors recognize and mitigate potential biases in their decision-making processes. Being aware of one’s personality, risk behavior, seeking diverse perspectives, and maintaining a long-term investment horizon can contribute to more rational and informed investment decisions. Additionally, seeking professional advice and engaging in continuous learning and self-reflection can further enhance investment decision-making abilities. Individual differences within each personality trait can significantly influence investment decisions. Additionally, other factors such as financial literacy, investment knowledge, and personal circumstances also play a role in shaping investment behavior and risk tolerance. This paper attempts to explore the nuanced relationships between personality traits, risk, and mutual fund investment decisions.

A Study on Impact of Big Five Personality on Investment Decisions of Mutual Fund Investors: Mediation by Risk

Mutual fund investment in India has gained significant popularity over the years as an avenue for individuals to participate in the capital markets. Understanding these psychological factors can help investors recognize and mitigate potential biases in their decision-making processes. Being aware of one’s personality, risk behavior, seeking diverse perspectives, and maintaining a long-term investment horizon can contribute to more rational and informed investment decisions. Additionally, seeking professional advice and engaging in continuous learning and self-reflection can further enhance investment decision-making abilities. Individual differences within each personality trait can significantly influence investment decisions. Additionally, other factors such as financial literacy, investment knowledge, and personal circumstances also play a role in shaping investment behavior and risk tolerance. This paper attempts to explore the nuanced relationships between personality traits, risk, and mutual fund investment decisions.

Economic viability of value-added cashew products processed in Southeast zone, Nigeria

The “Agricultural Promotion Policy (2016–2020)” is an initiative of Nigeria’s government, designed to create jobs and wealth for participants in the agricultural value chains through value addition to export crops such as cashew. However, it is not known how cashew processors have exploited this opportunity to improve their economic returns from value-added cashew products, processed in the Southeast zone, Nigeria. Consequently, this study analysed the economic viability of value-added cashew products processed in the Southeast zone of Nigeria. Specifically, the objective was to determine the cost-benefit analysis, rate of return on investment, net income, and variability of value-added cashew products processed in the Southeast zone, Nigeria. A descriptive research design involving a cross-sectional survey of 353 randomly sampled participants was administered with a structured questionnaire. Ratio statistics, gross margin, benefit-cost ratio analysis, rate of return and ANOVA were applied to analyze the data. The results show that variable cost constitutes >96 but ≤98% of the total cost of cashew value addition. The average net income from 1 kg of value-added cashew products is profitable with cashew kernel yielding the highest net income (N2,724.4 (US $7.6) > cashew nut (N2,547.9 (US $7.1)) > both cashew products (N2,340.4 (US $6.5)). The benefit-cost ratios for 1 kg of value-added cashew nut and cashew kernel were slightly higher (1:1.4) respectively than that of both cashew products (1:1.3), suggesting that value-added cashew products deliver positive net income to the processors. Equally, the rate of returns (RORs) for 1 kg of value-added cashew products yield the highest (38.1%) in cashew kernel > cashew nut (37.4%) > both cashew products (34.1%). The coefficient of dispersion (COD) in revenue and cost of value-added products shows the least risk in cashew kernel (0.097) and the highest risk in both cashew products (0.122). The study provides empirical evidence for potential small and medium-scale investors to make an informed investment decision about value addition to cashew products. It is recommended that government should encourage people to engage in value addition to cashew products because of its high rate of return, and assist processors with credit to procure modern processing equipment to enhance profitability and income generation.

Artificial intelligence in investment management, asset management and warehouse management

Artificial Intelligence (AI) has revolutionized diverse industries, including investment, asset, and warehouse management. In this analysis, the exploration of the applications and benefits of AI in each domain highlights how it enhances decision-making and optimizes operations efficiently. AI analyzes extensive financial data to make informed investment decisions, create personalized portfolios, and predict market trends in investment management. Asset Management leverages AI's predictive capabilities to monitor asset performance, assess risks, and optimize asset allocation strategies. AI tools can continuously monitor the environment and activities of a warehouse. This study explains AI and its impact on investment, asset, and warehouse management. The impact of AI is undeniable, and creates opportunities for better performance, reduced costs, and enhanced customer satisfaction.

INVESTMENT BEHAVIOUR OF INDIVIDUAL INVESTORS REGARDING SHARIA STOCK INVESTMENT: A SYSTEMATIC REVIEW

The main purpose of this paper is to review existing relevant pieces of literature on the behavior of investors toward investment in sharia stocks and bring into focus the factors that affect investors’ behavior in investment decision-making regarding sharia stocks. The paper is descriptive and exploratory and based on secondary data sourced from trusted e-journals, research databases, and e-magazines. The factors that influence investment decisions can be complex and may vary from one individual to another. Some studies have found that religiosity, and specifically adherence to religious values and principles, can influence investment decisions. However, not all studies have found a significant relationship between investment behavior regarding sharia stocks and the concept of religiosity. Other factors may also play a dominant role in determining decisions for prudent investments, such as financial literacy along with sharia literacy, financial behavior, and financial habits among others. Investors who are more financially literate may be better equipped to make informed investment decisions. Overall, the theory of planned financial behavior provides a resourceful framework for understanding investment behavior in many studies. Keywords: Sharia Literacy, Equity Market, Sharia Stock, Behavioral Finance, Investors’ Behavior DOI： https://doi.org/10.35741/issn.0258-2724.58.3.35

LINDA AND ENTROPY CONCENTRATION INDICES AS INSTRUMENTS OF CREDIT RISK MANAGEMENT

In all the financial organizations of the world, the homogenous distribution of profitable assets receives a lot of attention. The most homogeneous distribution or diversification of assets according to economic sectors, regions or ratings enables organizations to control possible credit risks, thus ensuring their financial stability and business continuity. In our article, we will use two coefficients: Linda and Entropy coefficients, with the help of which we will get a more accurate estimate of the level of concentration. For these indicators, the easy calculation can be considered as an advantage, which stimulates managerial operative decision-making. Moreover, the Linda and Entropy coefficients provide a quantitative measure of the concentration of assets in a portfolio, which helps organizations determine the extent to which their portfolio is diversified. This is crucial for making informed investment decisions and managing risk effectively. Thus, financial organizations can ensure a well-diversified portfolio.

Capital Expenditure and Future Firm Performance: Evidence from Firms Listed on the Stock Exchange of Thailand

Abstract: Purpose – Capital expenditure reflects a company's investment in long-term assets expected to generate value for shareholders over time. Such expenses mostly expect to improve a company's future performance. This research aims to explore the relationship between capital expenditure and future firm performance. Design/methodology/approach –A sample (n=475) of registered companies listed on the stock exchange of Thai (SET) from 2000-2016 was selected. The time period selected for this research allows the researchers to analyze the relationship during the period of economic growth and stability. Secondary data was harvested from the Thomson Reuters Datastream database. Findings – A regression analysis showed a negative relationship between capital expenditure and future firm performance, as measured by return on assets (ROA) and dividends. Notably, this negative relationship was found to be statistically significant across the board, first for all companies and second for a unique subset of larger companies. Originality/value - Such findings go against general expectations. Subsequently, the study has implications for general practice, investment, and the academe.In particular, it sheds light on the potential impact of agency on investment expenses. Practically, registered SET companies can use this insight to make informed investment decisions; investors to make investment decisions, and lenders to make lending decisions. Overall, this research provides value for various stakeholders across financial exchanges.

The plant-based milk market in the context of CAPM and three-factor model – the case of Oatly

The article examines the performance of Oatly, a plant-based food company, and the factors that influence its re-turns. Considering the CAPM and Fama-French three-factor models, tracking market volatility is a key factor for investors. The findings reveal that market risk significantly affects Oatly's performance, as shown by the positive relationship between the intercept and Mkt-RF. Investors must monitor market trends closely to make informed investment decisions. The analysis of Oatly's beta value indicates that it is a low-risk investment option, making it an attractive option for investors seeking stable returns. The study highlights the importance of investing in low-risk options, especially in the plant-based food industry. In conclusion, this study provides valuable insights into the determinants of Oatly's returns and offers a comprehensive understanding for investors seeking low-risk investments. Monitoring market trends and risks is essential for investors in the plant-based food sector, and this study serves as a useful guide for making informed investment decisions. Oatly's low-risk profile makes it an at-tractive investment option, and investors must stay vigilant and keep track of market changes to make the most of this opportunity. This study offers important insights that can help investors navigate the complex and dy-namic world of plant-based food investments.

Pre-market individual investors’ sentiment and IPO initial performance of the emerging market

The volatility of the initial return and trading volume is evident from early observations of the Malaysian initial public offering (IPO) market on the first trading day. Making informed investment decisions is essential for a more accurate assessment of businesses and capital security. Investors should therefore be aware of what influences IPO initial return and trading volume. However, only a few amounts of prior research on the initial return and trading volume on the first trading day of an IPO has focused on the issue of investors’ reaction. Specifically, previous studies have not taken into consideration how individual investors feel about IPO companies as the primary influence. In this study, the sentiment of individual investors is measured using the Google Search Volume Score (GSVS), a practical approximation (Da et al., 2011). This is because most people who use Google to look up information, particularly about recently released equities, are individual investors. Between 2004 and 2020, 271 initial public offerings (IPOs) listed on Bursa Malaysia’s Main Market and Access, Certainty, Efficiency (ACE) Market made up the study sample. This study demonstrated that pre-market investor sentiment significantly and favourably effects IPO initial return and trading volume on the first trading day based on ordinary least square regression (OLS) models.

Enhancing Stock Market Predictability: A Comparative Analysis of RNN And LSTM Models for Retail Investors

The stock markets are important components of the global financial system and have a considerable impact on an economy's growth and stability. This research article uses algorithms, notably deep learning, to increase the prediction of stock values. The efficacy and precision of long short-term memory (LSTM) and recurrent neural networks (RNN) algorithms to estimate stock prices are compared in this study. The paper investigates the potential of deep learning algorithms in creating a more predictable and trustworthy environment for the stock market. The study utilizes historical market data obtained from the Alpha Vault API and evaluates the performance of the RNN and LSTM models in forecasting stock prices. The results indicate that LSTM exhibits superior precision and is better suited for stock price prediction, while RNN faces certain challenges. Overall, this research contributes to the understanding of the application of deep learning algorithms in stock market analysis, to make informed investment decisions, thereby reducing risks and maximizing returns.

ФОНДОВЫЕ РЫНКИ РОССИИ И АМЕРИКИ: АНАЛИЗ, ПРОБЛЕМЫ И ПЕРСПЕКТИВЫ ИНВЕСТИЦИЙ

The stock market is an excellent tool not only for preserving, but also for increasing your capital. In conditions of geopolitical tension, it is extremely important for an investor to monitor all trends and be aware of the risks of investing in the financial assets of a particular state. This article is a study of the stock markets of Russia and the United States with the aim of analyzing, identifying problems and assessing investment prospects. The authors conduct a comprehensive analysis of two stock exchanges, considering various factors and the degree of their influence on the markets. The article uses methods of comparative analysis, statistical calculations, and logical inference to determine the main trends and patterns, as well as identify problems faced by investors. During the study, the authors discovered a number of differences between the domestic stock market and the American one. For example, the US stock market is more developed and attracts more investment than the Russian one. The Russian stock market suffers to a greater extent from problems with stability and unpredictability, which are caused by periodic geopolitical tensions, as well as strong fluctuations in the exchange rate. The article also examines the prospects for investing in securities of Russian and American companies. The authors point to the significant potential of the Russian market due to its large number of undervalued stocks and opportunities for long-term investment. However, they also list a number of measures and conditions that the domestic market needs to attract more investors and achieve sustainable growth. During the article, the authors offer recommendations for investing in the stock markets of Russia and America. The authors encourage investors to evaluate the risks and rewards of each market and consider their individual investment objectives and opportunities. They also emphasize the need for awareness and continuous assessment of market conditions to make informed investment decisions. This work represents a valuable contribution to the understanding of these stock exchanges and can serve as a basis for further research and the development of investment strategies.

Pattern Classification of Stock Price Moving

The stock is one of the most important instruments of finance. However, the tendency of stock always has a high level of irregularity. In stock market, the stock price moving is considered as a time series problem. Clustering method on stock data is one of the machine learning methods and it is one of the most important analysis methods of technical analysis. The aim of this project is to find an efficient unsupervised learning way to analysis the stock market data to make classification of the patterns on different stock price moving data and get useful information for investment decisions by implementing different clustering algorithms. For this aim, the research objective of this project is to compare several of clustering methods like K-means algorithm, EM algorithm, Canopy algorithm, specify the best number of clusters for each clustering method by several evaluation indexes, show the result of each clustering method and make evaluation on the results of these clustering methods on stock market data of standard S&P 500 stock marketing data. In addition, Weka 3 and Matlab are used to implement the clustering methods and evaluation program. Data visualization shows clearly that those public companies in the same cluster have similar stock price moving pattern. The experiment shows the result that K-means algorithm and EM algorithm perform effectively in stock price moving and Canopy algorithm can be used before K-means algorithm to improve the efficiency.

A Proposed Tool for Non-Profit Portfolio Strategy

The growth-share matrix was created by Bruce D. Henderson for the Boston Consulting Group in 1970 to help corporations analyze their business units and inform investment decisions. Strategic planning is generally considered vital to business success, and the BCG matrix is only one of a number of models used by corporations for strategic planning. Non-profit organizations also rely on strategic planning but, by contrast, they have very few portfolio modeling tools to assist them. Christian ministries, in particular, are called to operate diligently and efficiently in Scriptures such as the Parable of the Talents in Matthew 25 but can struggle due to the lack of strategic planning tools available to them. This article attempts a measured step into that space by proposing a model that non-profit organizations might use for strategic planning. Instead of the growth-share axes utilized by the BCG matrix, this article proposes a Profit-Impact (PI) matrix. As an explanatory test for the proposed model, the authors will apply it to the multi-line ministry organization, Mission of Hope. After introducing the ministry and its Haitian context, the authors will use the ministry’s multiple ventures to demonstrate the utility of the PI matrix and make recommendations concerning how it could strategically spread its resources among its different ventures to best pursue its goals. The authors will conclude with a review of the model’s contribution to non-profit strategy and suggest additional research to further these efforts.