Search results for: stock markets

Authors: Pankhudi Khandelwal

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The revenue models of digital giants such as Facebook and Google, use targeted advertising for revenues. Such a model requires huge amounts of consumer data. While the data protection law deals with the protection of personal data, however, this data is acquired by the companies on the basis of consent, performance of a contract, or legitimate interests. This paper analyses the role that competition law can play in evading these loopholes for the protection of data and privacy of online consumers. Digital markets have certain distinctive features such as network effects and feedback loop, which gives incumbents of these markets a first-mover advantage. This creates a situation where the winner takes it all, thus creating entry barriers and concentration in the market. It has been also seen that this dominant position is then used by the undertakings for leveraging in other markets. This can be harmful to the consumers in form of less privacy, less choice, and stifling innovation, as seen in the cases of Facebook Cambridge Analytica, Google Shopping, and Google Android. Therefore, the article aims to provide a legal framework wherein the data protection law and competition law can come together to provide a balance in regulating digital markets. The issue has become more relevant in light of the Facebook decision by German competition authority, where it was held that Facebook had abused its dominant position by not complying with data protection rules, which constituted an exploitative practice. The paper looks into the jurisdictional boundaries that the data protection and competition authorities can work from and suggests ex ante regulation through data protection law and ex post regulation through competition law. It further suggests a change in the consumer welfare standard where harm to privacy should be considered as an indicator of low quality.

Keywords: data protection, dominance, ex ante regulation, ex post regulation

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Authors: Nellija Titova

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Latvia, Lithuania, and Estonia, as Baltic Countries, have gone throughout transformational changes since 90s leading to the high level of economic development. As countries departing Soviet Union with industrialization policy moved to service economies, the issues of intangibles, human capital, structural capital, and innovation capital have gained impetus. Following the growing demand of practitioners and later academia, intellectual capital as a discipline, which appeared in 90s, became fundamental nowadays. Aim of the paper is to analyze the Baltic companies entering stock markets at Nasdaq Baltic from the perspective of Intellectual Capital. Methodology of the research is based on a longitudinal analysis of the companies using composite ratios of Intellectual Capital and Business performance in the period 2012-2019. Data for 2020 as COVID year) were excluded from the analysis. Findings allow concluding there is a pattern of influence and companies clearly experience the systemic impact of IC on business performance, identifying also time effect investing in intangibles.

Keywords: intellectual capital, impact analysis, longitudinal effect, composite ratios

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Authors: Mohammad Azam

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This work is an endeavor to empirically investigate the Gross Domestic Product-Growth as mediating variable between various factors and portfolio returns using a broad sample of 522 financial and non-financial firms enlisted on Pakistan Stock Exchange between January-1993 and June-2022. The study employs the Structural Equation modeling and Ordinary Least Square regression to determine the findings before and during the Covid-19 epidemiological situation, which has not received due attention by researchers. The analysis reveals that market and investment factors are redundant, whereas size and value show significant results, whereas Gross Domestic Product-Growth performs significant mediating impact for the whole time frame. Using before Covid-19 period, the results reveal that market, value, and investment are redundant, but size, profitability, and Gross Domestic Product-Growth are significant. During the Covid-19, the statistics indicate that market and investment are redundant, though size and Gross Domestic Product-Growth are highly significant, but value and profitability are moderately significant. The Ordinary Least Square regression shows that market and investment are statistically insignificant, whereas size is highly significant but value and profitability are marginally significant. Using the Gross Domestic Product-Growth augmented model, a slight growth in R-square is observed. The size, value and profitability factors are recommended to the investors for Pakistan Stock Exchange. Conclusively, in the Pakistani market, the Gross Domestic Product-Growth indicates a feeble moderating effect between risk-premia and portfolio returns.

Keywords: asset pricing puzzle, mediating role of GDP-growth, structural equation modeling, COVID-19 pandemic, Pakistan stock exchange

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Authors: Taufik Nugroho, Firsty Dzainuurahmana, Tika Widiastuti

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The polemic about the salt crisis re-emerged, this is a classic problem in Indonesia and is still a homework that is not finished yet. This salt crisis occurs due to low productivity of salt commodities that have not been able to meet domestic demand and lack of salt productivity caused by several factors. One of the biggest factors of the crisis is the weather anomaly that disrupts salt production, less supportive technology and price stability. This study will try to discuss the salt scarcity and crisis solution in Islamic view. As for the conclusion of this study is the need for equilibrium or balancing between demand and supply, need to optimize the role of the government as Hisbah to maintain the balance of market mechanisms and prepare the stock system of salt stock by buying farmers products at reasonable prices then storing them.

Keywords: crisis, Islamic solution, scarcity, salt

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Authors: Lynmar M. Didal, Ramises G. Manzano Jr., Jacque Bon-Isaac C. Aboy

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This study analyzes the performance of global minimum variance and naive portfolios across different economic periods, using monthly stock returns from the Philippine Stock Exchange Index (PSEI), S&P 500, and Dow Jones Industrial Average (DOW). The performance is evaluated through the Sharpe ratio, Sortino ratio, Jensen’s Alpha, Treynor ratio, and Information ratio. Additionally, the study investigates the impact of short selling on portfolio performance. Six-time periods are defined for analysis, encompassing events such as the global financial crisis and the COVID-19 pandemic. Findings indicate that the Naive portfolio generally outperforms the GMV portfolio in the S&P 500, signifying higher returns with increased volatility. Conversely, in the PSEI and DOW, the GMV portfolio shows more efficient risk-adjusted returns. Short selling significantly impacts the GMV portfolio during mid-GFC and mid-COVID periods. The study offers insights for investors, suggesting the Naive portfolio for higher risk tolerance and the GMV portfolio as a conservative alternative.

Keywords: portfolio performance, global minimum variance, naïve portfolio, risk-adjusted metrics, short-selling

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Authors: Juniarti, Yusniwati, Anwar. A, Armansyah, Febriamansyah, R.

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Simawang area is one of the critical areas (sub-optimal) that experienced drought from climate changes. Potential dry land belonging to sub-optimal in Simawang, West Sumatera, Indonesia not been fully utilized for agricultural cultivation. Simawang village, West Sumatera, Indonesia is formerly known as the rice barn, due to the climate change area is experiencing a drought, so the rice fields that were once productive now a grazing paddock because of lack of water. This study aims to calculate the soil carbon stock in Simawang village, West Sumatera Indonesia. The study was conducted in Simawang village, Tanah Datar regency, West Sumatera from October 2014 until December 2017. The study was conducted on sub-optimal land to be planted with Cymbopogon nardus L. (Sereh wangi in Indonesian language). Composite soil sampling conducted at a depth of 0-20 cm, 20 – 40 cm. Based on the depth of soil carbon stocks gained higher ground 6473 t ha-1 at a depth of 0-20 cm at a depth of 20-40 cm. Efforts to increase soil carbon is expected to be cultivated through Cymbopogon nardus L. planting has been done.

Keywords: climate changes, sereh wangi (Cymbopogon nardus L.), soil carbon stock, sub optimal land

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Authors: Charles Lee

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The Principal Orthogonal Decomposition (POD) technique has been used as a model reduction tool for many applications in engineering and science. In principle, one begins with an ensemble of data, called snapshots, collected from an experiment or laboratory results. The beauty of the POD technique is that when applied, the entire data set can be represented by the smallest number of orthogonal basis elements. It is the such capability that allows us to reduce the complexity and dimensions of many physical applications. Mathematical formulations and numerical schemes for the POD method will be discussed along with applications in NASA’s Deep Space Large Antenna Arrays, Satellite Image Reconstruction, Cancer Detection with DNA Microarray Data, Maximizing Stock Return, and Medical Imaging.

Keywords: reduced-order methods, principal component analysis, cancer detection, image reconstruction, stock portfolios

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Authors: Chih-Hsiang Chang

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This study provides insight into the effects of investor sentiment, excess optimism, overconfidence, the disposition effect, and herding formation on momentum profits. This study contributes to the field by providing a further examination of the relationship between psychological factors and momentum profits. The empirical results show that there is no evidence of significant momentum profits in Taiwan’s stock market. Additionally, investor sentiment in Taiwan’s stock market significantly influences its momentum profits.

Keywords: momentum profits, psychological factors, herding formation, investor sentiment

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Authors: Juniarti Yuni

Abstract:

Simawang area is one of the critical areas (sub-optimal) that experienced drought from climate changes. Potential dry land belonging to sub-optimal in Simawang, West Sumatera, Indonesia not been fully utilized for agricultural cultivation. Simawang village, West Sumatera, Indonesia is formerly known as the rice barn, due to the climate change area is experiencing a drought, so the rice fields that were once productive now a grazing paddock because of lack of water. This study aims to calculate the soil carbon stock in Simawang village, West Sumatera Indonesia. The study was conducted in Simawang village, Tanah Datar regency, West Sumatera from October 2014 until December 2017. The study was conducted on sub-optimal land to be planted with Cymbopogon nardus L. (Sereh wangi in Indonesian language). Composite soil sampling conducted at a depth of 0-20 cm, 20–40 cm. Based on the depth of soil carbon stocks gained higher ground 6473 T/Ha at a depth of 0-20 cm at a depth of 20-40 cm. Efforts to increase soil carbon is expected to be cultivated through Cymbopogon nardus L. planting has been done.

Keywords: climate changes, sereh wangi (Cymbopogon nardus L.), soil carbon stock, sub optimal land

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Authors: Lydia Nkechi Philip

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Due to its well-documented commitment to sustainability across diverse global markets, Unilever, a multinational consumer goods powerhouse, serves as a compelling case study. The study's goal is to critically examine Unilever's CSR initiatives, assessing their alignment with international standards and the impact on consumer perceptions and loyalty. The study investigates how Unilever's CSR practices resonate with consumers in various regions using a mixed-methods approach that includes surveys and interviews. The conceptual framework considers the role of sustainable marketing practices as a bridge builder in the CSR-consumer relationship. The findings are expected to provide valuable insights for businesses seeking to navigate the complex terrain of global markets while remaining ethical and sustainable. As consumers place a higher value on socially responsible brands, this study examines Unilever's CSR impact on consumer behavior. The abstract captures the essence of the study, providing a sneak peek at the methodology, key objectives, and anticipated contributions to our understanding of CSR's role in shaping consumer attitudes and loyalty in the global marketplace.

Keywords: Unilever, consumer loyalty, sustainable marketing practices, consumer loyalties

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Authors: Jasman Tuyon, Zamri Ahmad

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Behavioral asset pricing research has been gaining momentum since in 1990s. However, it is still incomplete and has been criticized for some philosophical, theoretical and model specification limitations. Due to these drawbacks, investors’ behaviors as a source of risk in behavioral asset pricing modeling still remains disputable. This paper aims to address these issues with an alternative perspective based on behavioral finance paradigm. Specifically, this paper proposes a theoretical linkages of both fundamental and behavioral risks on stock prices formation and an extension of the multifactor stock pricing model by combining multi-factor fundamentals and behavioral risks factors.

Keywords: behavioral finance, multifactor asset pricing, behavioral risks, fundamental risks

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Authors: Taissir Fekih Romdhane

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This paper proposes a mobile web application named Pharmacy-Station that sells medicines and permits user to search for medications based on their symptoms, making it is easy to locate a specific drug online without the need to visit a pharmacy where it may be out of stock. This application is developed using the jQuery Mobile framework, which uses many web technologies and languages such as HTML5, PHP, JavaScript and CSS3. To test the proposed application, we used data from popular pharmacies in Saudi Arabia that included important information such as location, contact, and medicines in stock, etc. This document describes the different steps followed to create the Pharmacy-Station application along with screenshots. Finally, based on the results, the paper concludes with recommendations and further works planned to improve the Pharmacy-Station mobile application.

Keywords: pharmacy, mobile application, jquery mobile framework, search, medicine

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Authors: L. Maiza, A. Cantagrel, M. Forestier, G. Laucoin, T. Regali

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Evaluation of High Frequency Trading (HFT) impact on financial markets is very important for traders who use market analysis to detect winning transaction opportunity. Analysis of HFT data on tobacco commodity market is discussed here and interesting linear relationship has been shown between trading frequency and difference between averaged trading prices above and below considered trading frequency. This may open new perspectives on markets data understanding and could provide possible interpretation of Adam Smith invisible hand.

Keywords: financial market, high frequency trading, analysis, impacts, Adam Smith invisible hand

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Authors: Josip Visković, Josip Arnerić, Ante Rozga

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Based on the fact that volatility is time varying in high frequency data and that periods of high volatility tend to cluster, the most successful and popular models in modelling time varying volatility are GARCH type models. When financial returns exhibit sudden jumps that are due to structural breaks, standard GARCH models show high volatility persistence, i.e. integrated behaviour of the conditional variance. In such situations models in which the parameters are allowed to change over time are more appropriate. This paper compares different GARCH models in terms of their ability to describe structural changes in returns caused by financial crisis at stock markets of six selected central and east European countries. The empirical analysis demonstrates that Markov regime switching GARCH model resolves the problem of excessive persistence and outperforms uni-regime GARCH models in forecasting volatility when sudden switching occurs in response to financial crisis.

Keywords: central and east European countries, financial crisis, Markov switching GARCH model, transition probabilities

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Authors: Wee Tong Liaw, Elaine Wong Yee Sing

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Since 2001, many companies in Singapore have voluntarily participated in the bi-annual Singapore HEALTH Award initiated by the Health Promotion Board of Singapore (HPB). The Singapore HEALTH Award (SHA), is an industry wide award and assessment process. SHA assesses and recognizes employers in Singapore for implementing a comprehensive and sustainable health promotion programme at their workplaces. The rationale for implementing a sustained health promoting workplace and participating in SHA is obvious when company management is convinced that healthier employees, business productivity, and profitability are positively correlated. However, performing research or empirical studies on the impact of a sustained health promoting workplace on stock returns are not likely to yield any interests in the absence of a systematic and independent assessment on the comprehensiveness and sustainability of a health promoting workplace in most developed economies. The principles of diversification and mean-variance efficient portfolio in Modern Portfolio Theory developed by Markowitz (1952) laid the foundation for the works of many financial economists and researchers, and among others, the development of the Capital Asset Pricing Model from the work of Sharpe (1964), Lintner (1965) and Mossin (1966), and the Fama-French Three-Factor Model of Fama and French (1992). This research seeks to support the rationale by studying whether there is a significant relationship or impact of a sustained health promoting workplace on the performance of companies listed on the SGX. The research shall form and test hypotheses pertaining to the impact of a sustained health promoting workplace on company’s performances, including stock returns, of companies that participated in the SHA and companies that did not participate in the SHA. In doing so, the research would be able to determine whether corporate and fund manager should consider the significance of a sustained health promoting workplace as a risk factor to explain the stock returns of companies listed on the SGX. With respect to Singapore’s stock market, this research will test the significance and relevance of a health promoting workplace using the Singapore Health Award as a proxy for non-diversifiable risk factor to explain stock returns. This study will examine the significance of a health promoting workplace on a company’s performance and study its impact on stock price performance and beta and examine if it has higher explanatory power than the traditional single factor asset pricing model CAPM (Capital Asset Pricing Model). To study the significance there are three key questions pertinent to the research study. I) Given a choice, would an investor be better off investing in a listed company with a sustained health promoting workplace i.e. a Singapore Health Award’s recipient? II) The Singapore Health Award has four levels of award starting from Bronze, Silver, Gold to Platinum. Would an investor be indifferent to the level of award when investing in a listed company who is a Singapore Health Award’s recipient? III) Would an asset pricing model combining FAMA-French Three Factor Model and ‘Singapore Health Award’ factor be more accurate than single factor Capital Asset Pricing Model and the Three Factor Model itself?

Keywords: asset pricing model, company's performance, stock prices, sustained health promoting workplace

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Authors: Oluwaseun Adeleke, Samuel O. Ikani, Fidelis Edet, Anthony Nwala, Mopelola Raji, Simeon Christian Chukwu

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Background: The Delivering Innovations in Selfcare (DISC) project aims to increase access to self-care options for women of reproductive age, starting with self-inject subcutaneous depot medroxyprogesterone acetate (DMPA-SC) contraception services. However, the project has faced challenges in ensuring the continuous availability of the commodity in health facilities. Although most states in the country rely on the federal ministry of Health for supplies, some are gradually funding the procurement of Family Planning (FP) commodities. This attempt is, however, often accompanied by procurement delays and purchases inadequate to meet demand. This dilemma was further exacerbated by the commencement of demand generation activities by the project in supported states which geometrically increased commodity utilization rates and resulted in receding stock and occasional service disruptions. Strategies: The project deployed various strategies were implemented to ensure the continuous availability of commodities. These include facilitating inter-facility transfer, monthly tracking of commodity utilization, and alerting relevant authorities when stock levels reach a minimum. And supporting state-level procurement of DMPA-SC commodities through catalytic interventions. Results: Effective monitoring of commodity inventory at the facility level and strategic engagement with federal and state-level logistics units have proven successful in mitigating stock-out of commodities. It has helped secure up to 13,000 units of DMPA-SC commodities from federal logistics units and enabled state units to prioritize supported sites. This has ensured the continuity of DMPA-SC services and an increasing trend in the practice of self-injection. Conclusion: A functional supply chain is crucial to achieving commodity security, and without it, health programs cannot succeed. Stakeholder engagement, stock management and catalytic interventions have provided both short- and long-term measures to mitigate stock-outs and ensured a consistent supply of commodities to clients.

Keywords: family planning, contraception, DMPA-SC, self-care, self-injection, commodities, stock-out

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Authors: Priti Bajpai, Mohammed Shibil

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This paper utilizes a comparative case study design to examine a regional onion market. The particular case of onion markets is used to understand perishable product supply chains. The site for the study is Dubai, United Arab Emirates. Results from a six-month field study are outlined. In particular, the findings suggest that firms should examine adding additional destinations to their supply chain. Further, we argue that utilizing Dubai as a supply chain hub is in certain cases counterproductive. Implications for food supply chains and regional trade are discussed.

Keywords: supply chains, food markets, onion trade, field study

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Authors: Frankie Burgos, Emely Munar, Conrado Basa

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This paper aimed at developing an artificial neural network (ANN) model specifically for the Philippine Stock Exchange index closing value. The inputs to the ANN are US Dollar and Philippine Peso(USD-PHP) exchange rate, GDP growth of the country, quarterly inflation rate, 10-year bond yield, credit rating of the country, previous open, high, low, close values and volume of trade of the Philippine Stock Exchange Index (PSEi), gold price of the previous day, National Association of Securities Dealers Automated Quotations (NASDAQ), Standard and Poor’s 500 (S & P 500) and the iShares MSCI Philippines ETF (EPHE) previous closing value. The target is composed of the closing value of the PSEi during the 627 trading days from November 3, 2011, to May 30, 2014. MATLAB’s Neural Network toolbox was employed to create, train and simulate the network using multi-layer feed forward neural network with back-propagation algorithm. The results satisfactorily show that the neural network developed has the ability to model the PSEi, which is affected by both internal and external economic factors. It was found out that the inputs used are the main factors that influence the movement of the PSEi closing value.

Keywords: artificial neural networks, artificial intelligence, philippine stocks exchange index, stocks trading

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Authors: Cristian Pauna

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Trading the financial markets is a widespread activity today. A large number of investors, companies, public of private funds are buying and selling every day in order to make profit. Algorithmic trading is the prevalent method to make the trade decisions after the electronic trading release. The orders are sent almost instantly by computers using mathematical models. This paper will present a price prediction methodology based on a multi-dimensional neural network. Using the Fisher transform, the neural network will be instructed for a low-latency auto-adaptive process in order to predict the price evolution for the next period of time. The model is designed especially for algorithmic trading and uses the real-time price series. It was found that the characteristics of the Fisher function applied at the nodes scale level can generate reliable trading signals using the neural network methodology. After real time tests it was found that this method can be applied in any timeframe to trade the financial markets. The paper will also include the steps to implement the presented methodology into an automated trading system. Real trading results will be displayed and analyzed in order to qualify the model. As conclusion, the compared results will reveal that the neural network methodology applied together with the Fisher transform at the nodes level can generate a good price prediction and can build reliable trading signals for algorithmic trading.

Keywords: algorithmic trading, automated trading systems, financial markets, high-frequency trading, neural network

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Authors: Cheng-yu Hsieh, Bo Zhang, Ahmed Hambaba

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Stock market prediction has long been an area of interest for both expert analysts and investors, driven by its complexity and the noisy, volatile conditions it operates under. This research examines the efficacy of combining the Patch Time Series Transformer (PatchTST) with wavelet transforms, specifically focusing on Haar and Daubechies wavelets, in forecasting the adjusted closing price of the S&P 500 index for the following day. By comparing the performance of the augmented PatchTST models with traditional predictive models such as Recurrent Neural Networks (RNNs), Convolutional Neural Networks (CNNs), Long Short-Term Memory (LSTM) networks, and Transformers, this study highlights significant enhancements in prediction accuracy. The integration of the Daubechies wavelet with PatchTST notably excels, surpassing other configurations and conventional models in terms of Mean Absolute Error (MAE) and Mean Squared Error (MSE). The success of the PatchTST model paired with Daubechies wavelet is attributed to its superior capability in extracting detailed signal information and eliminating irrelevant noise, thus proving to be an effective approach for financial time series forecasting.

Keywords: deep learning, financial forecasting, stock market prediction, patch time series transformer, wavelet transform

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Authors: Babak Salekmahdy

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Microfinance is often seen as a means of repairing credit markets and unleashing the potential contribution of impoverished people who rely on self-employment. Since the 1990s, the microfinance industry has expanded rapidly, opening the path for additional kinds of social entrepreneurship and social investment. However, current data indicate relatively few average consumer effects, opposing pushback against microfinance. This research reconsiders microfinance statements, stressing the variety of data on impacts and the essential (but limited) role of reimbursements. The report finishes by explaining a shift in thinking: from microfinance as a strictly defined enterprise finance to microfinance as a more widely defined home finance. Microfinance, under this perspective, provides advantages by providing liquidity for various requirements rather than just by increasing income.

Keywords: microfinance, small business, economic development, credit markets

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Authors: Petar Dobrev

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There is no agreed-upon definition of firm quality. While profitability and stock performance often qualify as popular proxies of quality, in this project, we aim to identify quality without relying on a firm’s financial statements or stock returns as selection criteria. Instead, we use firm-level data on management practices across small to medium-sized U.S. manufacturing firms from the World Management Survey (WMS) to measure firm quality. Each firm in the WMS dataset is assigned a mean management score from 0 to 5, with higher scores identifying better-managed firms. This management score serves as our proxy for firm quality and is the sole criteria we use to separate firms into portfolios comprised of high-quality and low-quality firms. We define high-quality (low-quality) firms as those firms with a management score of one standard deviation above (below) the mean. To study whether this proxy for firm quality can identify better-performing firms, we link this data to Compustat and The Center for Research in Security Prices (CRSP) to obtain firm-level data on financial performance and monthly stock returns, respectively. We find that from 1999 to 2019 (our sample data period), firms in the high-quality portfolio are consistently more profitable — higher operating profitability and return on equity compared to low-quality firms. In addition, high-quality firms also exhibit a lower risk of bankruptcy — a higher Altman Z-score. Next, we test whether the stocks of the firms in the high-quality portfolio earn superior risk-adjusted excess returns. We regress the monthly excess returns on each portfolio on the Fama-French 3-factor, 4-factor, and 5-factor models, the betting-against-beta factor, and the quality-minus-junk factor. We find no statistically significant differences in excess returns between both portfolios, suggesting that stocks of high-quality (well managed) firms do not earn superior risk-adjusted returns compared to low-quality (poorly managed) firms. In short, our proxy for firm quality, the WMS management score, can identify firms with superior financial performance (higher profitability and reduced risk of bankruptcy). However, our management proxy cannot identify stocks that earn superior risk-adjusted returns, suggesting no statistically significant relationship between managerial quality and stock performance.

Keywords: excess stock returns, management, profitability, quality

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Authors: Seyedmohsen Mortazavi

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The purpose of this research is to investigate the personality types of internal auditors on the quality of financial reporting in companies admitted to the Tehran Stock Exchange. Personality type is one of the issues that emphasizes the field of auditors' behavior, and this field has attracted the attention of shareholders and stock companies today, because the auditors' personality can affect the type of financial reporting and its quality. The research is applied in terms of purpose and descriptive and correlational in terms of method, and a researcher-made questionnaire was used to check the research hypotheses. The statistical population of the research is all the auditors, accountants and financial managers of the companies admitted to the Tehran Stock Exchange, and due to their large number and the uncertainty of their exact number, 384 people have been considered as a statistical sample using Morgan's table. The researcher-made questionnaire was approved by experts in the field, and then its validity and reliability were obtained using software. For the validity of the questionnaire, confirmatory factor analysis was first examined, and then using divergent and convergent validity; Fornell-Larker and cross-sectional load test of the validity of the questionnaire were confirmed; Then, the reliability of the questionnaire was examined using Cronbach's alpha and composite reliability, and the results of these two tests showed the appropriate reliability of the questionnaire. After checking the validity and reliability of the research hypotheses, PLS software was used to check the hypotheses. The results of the research showed that the personalities of internal auditors can affect the quality of financial reporting; The personalities investigated in this research include neuroticism, extroversion, flexibility, agreeableness and conscientiousness, all of these personality types can affect the quality of financial reporting.

Keywords: flexibility, quality of financial reporting, agreeableness, conscientiousness

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Authors: Longqing Li

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The paper addresses the inefficiency of the classical model in measuring the Value-at-Risk (VaR) using a normal distribution or a Student’s t distribution. Specifically, the paper focuses on the one day ahead Value-at-Risk (VaR) of major stock market’s daily returns in US, UK, China and Hong Kong in the most recent ten years under 95% confidence level. To improve the predictable power and search for the best performing model, the paper proposes using two leading alternatives, Extreme Value Theory (EVT) and a family of GARCH models, and compares the relative performance. The main contribution could be summarized in two aspects. First, the paper extends the GARCH family model by incorporating EGARCH and TGARCH to shed light on the difference between each in estimating one day ahead Value-at-Risk (VaR). Second, to account for the non-normality in the distribution of financial markets, the paper applies Generalized Error Distribution (GED), instead of the normal distribution, to govern the innovation term. A dynamic back-testing procedure is employed to assess the performance of each model, a family of GARCH and the conditional EVT. The conclusion is that Exponential GARCH yields the best estimate in out-of-sample one day ahead Value-at-Risk (VaR) forecasting. Moreover, the discrepancy of performance between the GARCH and the conditional EVT is indistinguishable.

Keywords: Value-at-Risk, Extreme Value Theory, conditional EVT, backtesting

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Authors: Innocent Uzougbo Onwuegbuzie

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Healthcare delivery in low-income markets is fraught with numerous challenges, including limited access to essential medical resources, inadequate healthcare infrastructure, and a significant shortage of trained healthcare professionals. These constraints lead to suboptimal health outcomes and a higher incidence of preventable diseases. This paper explores the application of Wireless Sensor Networks (WSNs) as a transformative solution to enhance healthcare delivery in these underserved regions. WSNs, comprising spatially distributed sensor nodes that collect and transmit health-related data, present opportunities to address critical healthcare needs. Leveraging WSN technology facilitates real-time health monitoring and remote diagnostics, enabling continuous patient observation and early detection of medical issues, especially in areas with limited healthcare facilities and professionals. The implementation of WSNs can enhance the overall efficiency of healthcare systems by enabling timely interventions, reducing the strain on healthcare facilities, and optimizing resource allocation. This paper highlights the potential benefits of WSNs in low-income markets, such as cost-effectiveness, increased accessibility, and data-driven decision-making. However, deploying WSNs involves significant challenges, including technical barriers like limited internet connectivity and power supply, alongside concerns about data privacy and security. Moreover, robust infrastructure and adequate training for local healthcare providers are essential for successful implementation. It further examines future directions for WSNs, emphasizing innovation, scalable solutions, and public-private partnerships. By addressing these challenges and harnessing the potential of WSNs, it is possible to revolutionize healthcare delivery and improve health outcomes in low-income markets.

Keywords: wireless sensor networks (WSNs), healthcare delivery, low-Income markets, remote patient monitoring, health data security

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Authors: L. Feleagă, M. Dumitrașcu, N. Feleagă

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This article is a research on corporate governance. The aim of the study is to focus a special attention on the importance of corporate social responsibility and corporate governance, which are relevant, indeed necessary, for organizations. In this regard, we analyzed the corporate social responsibility in the context of corporate governance for companies listed on Bucharest and Bombay Stock Exchange. Therefore, we bring into the spotlight some differences between India and Romania linked with the importance ascribed to corporate social responsibility of a company. We presented the results of the demarche and we concluded suggestions regarding further research in this area. The study increases the awareness, identifies and articulates desirable behaviors, which are not intended to be exhaustive.

Keywords: corporate governance, corporate social responsibility, disclosure, listed companies

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Authors: Juniarti, Agus Arianto Toly

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This study aims to examine the effect of capital expenditure on the investors’ responses. The respondents were companies with the best stock performance in each sector in 2017. The observation period is 2017 to 2019. Top 10 companies in each sector with the best stock performance in companies listed on the Indonesia Stock Exchange were selected. The main variables are a growth signal which is proxied by growth in capital spending and capital expenditure, and risk and investor response, which is proxied by CAR. Financial performance as measured by ROA is a control variable in this study. The results showed that the signal of growth as measured by capital expenditures responded positively by the market, the risk moderates this influence, companies with high risk will be responded negatively by investors and vice versa. This finding corrects previous findings that only looked at the signal aspect of growth, without linking it to risk. In addition, these findings reinforce the argument that investors buy the future of the company, not a momentary financial performance. This can be seen from the absence of ROA influence on investor response. This study found that companies need to manage risk appropriately, because the risk aspect of the company is a crucial factor for investors. High risks will eliminate the benefits of strategic decisions in this case in the form of capital expenditures.

Keywords: capital expenditure, growth signals, investor response, risk

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Authors: Adel M. Qatawneh

Abstract:

This paper aimed to determine the importance of knowledge innovation for external audit on anti-corruption in the entire Jordanian bank companies are listed in Amman Stock Exchange (ASE). The study importance arises from the need to recognize the Knowledge innovation for external audit and anti-corruption as the development in the world of business, the variables that will be affected by external audit innovation are: reliability of financial data, relevantly of financial data, consistency of the financial data, Full disclosure of financial data and protecting the rights of investors to achieve the objectives of the study a questionnaire was designed and distributed to the society of the Jordanian bank are listed in Amman Stock Exchange. The data analysis found out that the banks in Jordan have a positive importance of Knowledge innovation for external audit on anti-corruption. They agree on the benefit of Knowledge innovation for external audit on anti-corruption. The statistical analysis showed that Knowledge innovation for external audit had a positive impact on the anti-corruption and that external audit has a significantly statistical relationship with anti-corruption, reliability of financial data, consistency of the financial data, a full disclosure of financial data and protecting the rights of investors.

Keywords: knowledge innovation, external audit, anti-corruption, Amman Stock Exchange

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Authors: Gunnar Oskarsson, Gudjon Helgi Egilsson

Abstract:

Due to globalization, small and medium-sized enterprises (SME) increasingly offer their products and services in foreign markets. The main reasons are either to compensate for a decreased market share in their home market or to exploit opportunities in foreign markets, which are becoming less distant and better accessible than before. International markets are particularly important for companies located in a small economy and offering specialized products. Although more accessible, entering international markets is both expensive and difficult. In order to select the most appropriate markets, it is, therefore, important to gain an insight into the factors that have an impact on success, or potential failure. Although there has been a reasonable volume of research into the theory of internationalization, there is still a need to gain further understanding of the decision-making process of SMEs in small economies and the most important characteristics that distinguish between success and failure. The main objective of this research is to enhance knowledge on the internationalization of SMEs, including the drivers for the decision to internationalize, and the most important factors contributing to success in their internationalization activities. A qualitative approach was found to be most appropriate for this kind of research, with the objective of gaining a deeper understanding and discovering factors which impact a company’s decision-making and potential success. In-depth interviews were conducted with 14 companies in different industries located in Iceland, a country extensively dependent on export revenues. The interviews revealed several factors as drivers of internationalization and, not surprisingly, the most frequently mentioned source of motivation was that the local market is inadequate to maintain a sustainable operation. Good networking relationships were seen as a particular priority for potential success, searching for new markets was mainly carried out through the internet, although sales exhibitions and sales trips were also considered important. When it comes to the final decision as to whether a market should be considered for further analysis, economy, labor cost, legal environment, and cultural barriers were the most common factors to be weighted. The ultimate answer to successful internationalization, however, is largely dependent on a coordinated and experienced management team. The main contribution of this research is offering an insight into factors affecting decision-making in the internationalization process of SMEs, based on the opinion and experience of managers of SMEs in a small economy.

Keywords: internationalization, success factors, small and medium-sized enterprises (SMEs), drivers, decision making

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Authors: Godwin Chigozie Okpara

Abstract:

This paper using standard GARCH, EGARCH, and TARCH models on day of the week return series (of 246 days) from the Nigerian Stock market estimated the model variants’ VaR. An asymmetric return distribution and fat-tail phenomenon in financial time series were considered by estimating the models with normal, student t and generalized error distributions. The analysis based on Akaike Information Criterion suggests that the EGARCH model with student t innovation distribution can furnish more accurate estimate of VaR. In the light of this, we apply the likelihood ratio tests of proportional failure rates to VaR derived from EGARCH model in order to determine the short and long positions VaR performances. The result shows that as alpha ranges from 0.05 to 0.005 for short positions, the failure rate significantly exceeds the prescribed quintiles while it however shows no significant difference between the failure rate and the prescribed quantiles for long positions. This suggests that investors and portfolio managers in the Nigeria stock market have long trading position or can buy assets with concern on when the asset prices will fall. Precisely, the VaR estimates for the long position range from -4.7% for 95 percent confidence level to -10.3% for 99.5 percent confidence level.

Keywords: downside risk, value-at-risk, failure rate, kupiec LR tests, GARCH models

Procedia PDF Downloads 437