Securities Market Research Articles

Financial market trend prediction model based on LSTM neural network algorithm

The financial market has randomness, and the prediction of the financial market is an important task in the financial market. In traditional financial market prediction models, the prediction results are often unsatisfactory. So it needs to introduce new models for financial analysis. To solve this problem, this paper analyzed a financial market trend prediction model based on LSTM (Long Short-Term Memory) NN (Neural Network) algorithm, and conducted an empirical analysis on the Shanghai stock index dataset. This paper first introduced the LSTM NN algorithm, and then divided it into training set, test set and comparison set according to the data characteristics. At last, this paper used the data preprocessing method to verify the LSTM NN algorithm. The experimental results showed that the LSTM NN algorithm analyzed in this paper can effectively improve the generalization ability of financial market trend prediction models while ensuring the prediction accuracy. Through experimental analysis, this paper found that the average accuracy rate of using LSTM NN algorithm was 2.25% higher than that of using traditional NN algorithm. This research is primarily aimed at developing effective methods for predicting stock market trends in the continuously evolving Chinese securities market. The core objective is to empower investors with precise guidance by enabling them to make well-informed investment decisions. Achieving accurate predictions holds the potential to significantly impact economic operations in a positive way. Therefore, this research direction is of paramount importance, offering substantial value both in academic exploration and practical application.

Short-term Securities Market Surveillance Measures and Market Performance– An Empirical Analysis

Regulators use securities market surveillance as an essential tool to guard against market manipulation, safeguard investors, and maintain the effectiveness of the markets. In an effort to thwart open market manipulation SEBI in consultation with the exchanges has put in place a unique surveillance mechanism known as Additional Surveillance Measures (ASM). The short-term impact of this surveillance measure on stock prices and trading volume is examined in this study, using event study methodology. The sample data consists of 245 instances, where companies were subject to ASM surveillance actions for a brief period. The results of the study show that the Cumulative Abnormal Return (CAR) on the stocks decreased after inclusion into STASM and the same persisted after exclusion also. However, the average abnormal volume (AAV) changed significantly in the pre- and post-event period.

Cultural Branding in the Arab Region

The comparative study of cultural policies in the Arab region remains a relatively underexplored domain, particularly in how these policies influence nation branding and nation-building efforts. This exploratory study seeks to contribute to this nascent field by adopting a comparative lens to examine the cultural policies of three Arab nations: the United Arab Emirates (UAE), Saudi Arabia and Egypt. Through a document analysis of key policies from these countries, this research unveils the intricate ways cultural strategies are employed to articulate and disseminate national, ethical and political ideologies. The article articulates how each country’s approach to cultural policy—commodification in the UAE, securitisation in Egypt and religionisation in Saudi Arabia—reflects and is shaped by unique local, regional and global power dynamics. By contextualising these policies within broader frameworks of market forces, security concerns and religious influences, the study offers insights into the complex interplay between cultural policymaking and nation branding in the Arab world.

Number of Volatility Regimes in the Muscat Securities Market Index in Oman Using Markov-Switching GARCH Models

The predominant approach for studying volatility is through various GARCH specifications, which are widely utilized in model-based analyses. This study focuses on assessing the predictive performance of specific GARCH models, particularly the Markov-Switching GARCH (MS-GARCH). The primary objective is to determine the optimal number of regimes within the MS-GARCH framework that effectively captures the conditional variance of the Muscat Securities Market Index (MSMI). To achieve this, we employ the Akaike Information Criterion (AIC) to compare different MS-GARCH models, estimated via Maximum Likelihood Estimation (MLE). Our findings indicate that the chosen models consistently exhibit at least two regimes across various GARCH specifications. Furthermore, a validation using the Value at Risk (VaR) confirms the accuracy of volatility forecasts generated by the selected models.

Управление маркетинговой безопасностью для обеспечения экономической безопасности предприятия

The article is devoted to the study of approaches to understanding marketing security and its impact on economic security. Based on the study of scientific publications devoted to ensuring marketing security, the relationship between marketing and economic security is revealed, and marketing tools that influence economic security are identified. The purpose of the study is to formulate modern trends and marketing tools designed to ensure marketing security. In conclusion, the directions and processes that should be included in a modern marketing security system to ensure economic security are determined.

Shades of grand corruption among allocative efficiency and institutional settings. The case of Italy

This paper examines the underexplored impact of the procedures in public contracts on market allocation efficiency that are at risk of corruption. We integrated the GMM-SYS estimator with analyses of a balanced panel database of all the provinces in Italy between the period 2013–2021. The use of a high level of spatial granularity in an under-researched context revealed two distinct scenarios. In competitive markets, a more entrepreneurial and less widespread form of corruption emerged which may enhance market efficiency (bottom-up pattern). Conversely, in a context with limited market competition and low institutional quality, corruption indicators may be less useful due to potential pre-bribery behavior (top-down pattern). Our study underscores the capacity of corrupt suppliers to exploit market opportunities and secure selection. We found that corruption risk practices within public contracts have the potential to improve market efficiency, thus rendering them appealing to corrupt suppliers due to their capacity to deliver economic advantages. This also applies to provinces with high-quality governance. Additionally, the paper highlights the limitations of indicators in alternative contexts. The paper has significant implications for policymakers in defining assignation criteria in high-quality contexts, but also offers insights into the effectiveness of grand corruption indicators for academics.

INVESTOR PERCEPTION TOWARDS THE STOCK MARKET

A stock market is a market in which stocks are bought and sold. It is also called industrial securities market, because it is the market for the trading of company stocks i.e. corporate securities; both those securities listed on stock exchange as well as those only traded privately. The term ‘Stock Market’ is often used as synonymous to ‘Stock Exchange’. But there is a difference in the two terms. Stock exchange is a corporation in the business of bringing buyers and sellers of stocks together. It is a major part of stock market, but not whole of it. Because a stock market besides stock exchanges also includes the market for new issue of securities. Thus the stock market can be divided into two constituents as follows: - 1. Primary Market or New Issue Market 2. Secondary Market or Stock Exchange

The impact of green innovation on the carbon performance of Chinese manufacturing enterprises: Moderating role of internal governance

With the increasing problems of global warming, ecological damage, and excessive consumption of resources, a greater number of countries are focusing on corporate carbon performance and carbon emissions. Enterprises can save energy and reduce emissions through green innovation, which will improve the efficiency of carbon use and contribute to higher levels of corporate carbon performance. Meanwhile, effective corporate governance can improve enterprise performance, while internal governance systems can affect enterprise carbon performance. This study aims to reveal how the green innovation affect carbon performance of enterprises and the role of internal governance. So this study utilizes the data of China's A-share listed manufacturing companies from 2010 to 2020 to examine the impact of green innovation on corporate carbon performance through a fixed-effects model, and to examine the impact of corporate internal governance structure on green innovation and carbon performance through a moderating-effects model. The data used in this study are mainly from China Securities Market and Accounting Research Database (CSMAR) and China Research Data Service Platform (CNRDS), and the robustness test is conducted by replacing the independent variables using the 2sls method. The findings indicate that green innovation has a significant contribution to enterprise performance on carbon. Ownership concentration and executive political connections negatively moderated the relationship between green innovation and carbon performance. Director compensation positively moderates the relationship between green innovation and carbon performance. This research provides a theoretical groundwork for future studies on green innovation and carbon performance, and its findings are instructive for both the introduction of government policies and the restructuring of internal corporate governance.

Share Repurchase and Cash Dividend - Substitute or Complement? Analysis from the Vietnam Securities Market

Purpose: The purpose of this report was to assess the relationship among the cash dividend payout and share repurchase, through essential cash distribution methods adopted by Vietnamese publicly listed companies. The complementary along with substitute relationship from these financial practices might contribute to determine the financial managerial behavior in Vietnam as a leading development emerging market within Asia Pacific area. Design/methodology/approach: The research applied regression analysis technique to determine the nonlinear relationship among the share repurchase and cash dividend. Findings: The research found the nonlinear relationship among the change in dividend along with the repurchase yield. Moreover, the research found a significant positive correlation which reveals the prominent of complementary impact in the complete sample. The results and estimations of the research are consistent in robustness tests. There is a nonlinear relationship between the change in dividend and the repurchase yield. In addition, a significantly positive correlation reveals the dominant of complementary effect in the whole sample. The results are consistent in robustness tests. Research limitations/implications: It is crucial to ensure that there is an essential scope for the enhancement which remains and it is a component of the future study such as the influence of the stock dividend through various practice while companies are partly dominated or effected by the government, through the characteristics as the emerging markets such as Vietnam, as they are interesting topics which need further study. Originality/value: Through a comprehensive analysis, the study outcomes propose that Vietnamese listed companies should meticulously assess their future growth concerning share repurchase and other capital distribution activities. This strategy should take into account the involvement of various stakeholders and their benefit.

Safety and Security of E-commerce Transactions Based on Blockchain Technology

The safety and security of e-commerce transactions are critical in today's digital landscape, where cyber risks abound. Blockchain technology's decentralized, transparent, and immutable ledger system offers a viable solution to these concerns. This study investigates the use of Distributed Ledger Technology (DLT), specifically Decentralized Identifiable Distributed Ledger Technology (DIDLT), in conjunction with the innovative Blockchain Consent Algorithm (BCA), to improve the safety and security of e-commerce transactions. Secure data storage and retrieval in e-commerce can be achieved by accurate digital signature production, key generation, blockchain building, and validation. This paper investigates how DIDLT, which combines decentralized identity management with blockchain technology, and BCA, a cutting-edge consensus algorithm designed for blockchain environments, work together to protect e-commerce transactions from identity theft, payment fraud, and data manipulation. This paper throws insight into DIDLT and BCA's potential to transform the e-commerce safety and security market by providing an in-depth analysis of their implementation. Using the incorporated DIDLT-BCA model significantly improves the safety effectiveness of the network, resulting in 98% security, shorter performance times of as much as 150 milliseconds, and mining times of up to 0.98 s.

Medicalisation of Unemployment: An Analysis of Sick Leave for the Unemployed in Germany Using a Three-Level Model

The study investigates whether sick leave for the unemployed is used to address problems of labour market integration – a process that can theoretically be conceptualised as the medicalisation of unemployment. Estimating a multilevel logistic regression model on a sample of N = 20,196 individuals from the German panel study Labour Market and Social Security (PASS) reveals that, on average, 18% of the unemployed are on sick leave due to poor health. However, given a comparable state of health, the probability increases for men, older individuals and those with lower educational levels. These findings are crucial as they reveal a dual role of sick leave in a context with limited access to disability pensions: as a protective measure for sick, unemployed individuals and as medicalisation of unemployment by excluding those who face non-medical barriers to labour market integration.

Genetic algorithms as a tool for the formation and evolution of trading strategies in the securities market

Subject. This article deals with the tools for the formation and evolution of trading strategies in the securities market. Objectives. The article aims to develop a mathematical framework and a formalized algorithm for the formation and evolution of trading strategies in the securities market. Methods. For the study, I used a genetic algorithm as an evolutionary optimization model. Results. The article presents an original mathematical description of a tool for the formation and evolution of strategies using genetic algorithms and a formalized algorithm sufficient for implementation in general-purpose programming languages. Conclusions and Relevance. The results obtained are the basis for further research in the field of autonomous evolution of trading strategies, and the described models will allow further research on the basis of specific software tools. The work is of practical value for private and institutional investors, for whom the trading strategy in the securities market is one of the fundamental aspects of their activities.

Internal Determinant Of Firm’s Security Returns On Commercial Banks Listed On Nairobi Securities Exchange

The market for securities improves the exchange of shares of public firms. Companies utilize the essential market to float shares to the public through an initial public offer in return for financed capital. A firm’s performance concerning equities is a solid marker of how it is fairing financially and its contribution to the macroeconomy. The equity market records are a sign of the monetary solidness of the economy. Thus, the current study sought to establish the influence of market determinants on stock market returns among listed commercial banks at Nairobi Securities Exchange in Kenya. In Kenya, such risks as liquidity risks, non-performing loans (NPLs), and poor performance, among others, have been of significant concern for quite some time. Many studies have been carried out in Kenya concerning the stock market performance of the banking sector. While there may be several factors, such as favorable government policies, explaining these performances, there is a shortage of information on the justification of strategic bank factors influencing the financial performance of these banks. Hence, the research sought to address hypothesis around the influence of the determinants such as capital adequacy, asset quality, management efficiency and influence of liquidity on stock market returns among Commercial Banks listed in Nairobi Securities Exchange. The research adopted credit risk theory, liquidity risk theory transaction cost theory, capital structure theory and signaling hypothesis theory. The study also applied panel data analysis and survey design on 10-year primary and secondary data from from 2013 to 2022. The target population constituted 11 commercial banks listed on Nairobi Securities Exchange. The study used quantitative data sorted and analyzed using descriptive and inferential statistical techniques. The descriptive analysis results were in the form of mean, standard deviations, frequencies, and percentage forms. Tables, diagrams, and charts were adopted. From the study findings, asset quality and management efficiency ratios had a negative and significant association with stock market returns respectively. On the other hand, capital adequacy and liquidity had a positive and significant relationship with stock market returns respectively. Based on the study results, the study recommends that banks should balance asset quality and lending stringency due to its negative correlation with stock returns. Strengthening capital adequacy and maintaining optimal liquidity positively impact stock market returns. In addition, a focus on service quality and employee morale is recommended for indirect benefits on stock performance.

РОЗВИТОК ТА ІНСТИТУЦІЙНІ ТРАНСФОРМАЦІЇ ФОНДОВОГО РИНКУ УКРАЇНИ

The article examines the development and institutional transformations of the Ukrainian stock market. It has been confirmed that in Ukraine there is a pronounced bank-centric nature of the financial system by comparing indicators of the ratio of capitalization of listed companies and bank loans to Ukraine's GDP. It was determined that the Ukrainian stock market during the research period is constantly developing and transforming and attracts the attention of both domestic and foreign investors. Ukraine follows international standards in the field of exchange activity and works to improve the regulatory framework for market development. The most important institutional transformations in the domestic stock market under the influence of legislative changes are characterized. Separate quantitative aspects of the development of the domestic stock market for 2012-2022 were analyzed. It was noted that the transformations of the stock market were characterized not only by changes in the quantitative indicators of the development of the securities market of Ukraine, but also had a significant impact on the institutional, regulatory, intermediary, technical and information infrastructure of the domestic stock market. The most important directions of the transformation of the stock market of Ukraine, in particular of an institutional and digital nature, are substantiated. The key aspects of the transformation of the stock market related to digitalization processes are highlighted: electronic trading is a tool that allows you to trade securities online directly through electronic trading platforms; increasing transparency promotes quick and effective dissemination of information about companies, their financial condition and development prospects; the growing role of robot-advisors who can provide investment advice, analyze markets and predict risks; increasing the availability of services for small investors through digital platforms; changes in the structure of the market due to digital technologies lead to changes in the structure of the stock market, in particular, to an increase in the role of alternative trading platforms and a decrease in the importance of traditional exchanges. In the institutional environment, increased requirements for companies wishing to go through the listing procedure on the stock exchanges contributed to the exit of inefficient and fictitious issuers, ensuring a higher level of investor confidence in the market. However, we note that this has also led to a narrowing of the number of companies willing and able to meet these requirements, which may limit investment opportunities in the market.

A Comprehensive Discourse on Shallow Learning and its Applications

Shallow learning, a fundamental approach in machine learning, encompasses a variety of algorithms and techniques aimed at learning patterns and making predictions from labelled data. Unlike deep learning, which involves complex architectures with multiple layers of abstraction, shallow learning focuses on simpler models with limited complexity. This abstract explores the essence of shallow learning, its algorithms, applications, and challenges. Shallow learning algorithms include classic methods such as decision trees, support vector machines, k-nearest neighbours, and logistic regression, among others. These algorithms are typically trained using supervised learning techniques, where the model learns from input-output pairs to make predictions on new, unseen data. Shallow learning models excel in tasks such as classification and regression, where the goal is to assign labels or predict continuous values to input data. Applications of shallow learning span across various domains, including healthcare, finance, marketing, and cyber security. In healthcare, shallow learning models are used for disease diagnosis and prognosis prediction based on patient data. In finance, these models aid in fraud detection, credit scoring, and stock market prediction. Marketing applications involve customer segmentation and churn prediction, while in cyber security; shallow learning is utilized for malware detection and network intrusion detection.

Financial priorities and the growth border of the Russian economy

Subject. The article investigates the role of foreign exchange reserves in the development of the Russian economy, the securities market development, and the banking system stability. Objectives. The aim is to review the monetary policy options under international sanctions strengthening. Methods. I apply methods of statistical, neural network, and cluster analysis. Results. The study established that it is impossible to reduce currency risks by issuing shares listed in the domestic market in foreign currency. The preferred directions of Russia's monetary policy are as follows: strengthening the country's international investment position, increasing the volume of the Federal bond market, and increasing the issue of shares listed in the domestic market in rubles. Conclusions. The growth boundary of the Russian economy is determined by such parameters as the amount of funds in escrow accounts of individuals, the size of insurance and pension reserves.

Securities Markets and Their Regulation in Zambia: A New Dawn or a Rebranding of the Old Norms?

Securities markets are a barometer for the economic progression of any country. The quest to harness the maximum benefits that such markets afford has led governments to enact specific legislation and develop appropriate policies. Despite enacting legislation in 1970, it was only in 1993 that the Zambian securities market was established. Simultaneously, the Securities Act 1993 was also enacted. However, it was replete with shortcomings, leading to its repeal and replacement by the Securities Act 2016 (amended by the Securities (Amendment) Act 21 of 2022; hereinafter the Securities Act 2016 as amended). The Securities Act 2016 as amended has for the most part been hailed as a progressive piece of legislation that has incorporated global best practices aimed at enhancing the securities market. There is optimism that the Securities Act 2016 as amended has breathed new life into the securities industry which was seemingly ailing and on life support. It remains questionable, however, whether the Securities Act 2016 as amended enhances the performance of the securities market by effectively fostering fair and efficient trading and ensuring financial integrity, or if it simply reiterates the problems of its predecessor or worse still creates new challenges. In this article the author critically assesses the Securities Act 2016 as amended to ascertain the extent to which it conforms to the IOSCO Principles 2017 and the practices of other countries such as Kenya, whose Capital Markets Act Chapter 485 offers greater clarity.

Ways to Increase the Efficiency of Investment Activities of Insurance Companies in Uzbekistan

This article aims to develop scientific and methodological proposals and practical recommendations to improve the methodology for assessing the effectiveness of investment activities of insurance organizations. The work uses scientific methods for studying the processes of economic reality - systematic analysis, generalization, grouping, observation, logical and comparative methods of analysis, abstract logical thinking, comparative analysis, mathematical modeling, econometric analysis, actuarial calculations, etc. Based on the systematization of information on investment activities, investment policies, and experience of insurance companies in developed countries, the use of statistical and mathematical methods of data processing, diversification of the financial and investment activities of insurance companies, recommendations, and indicators used to assess the effectiveness of insurance companies have been developed, identified and classified into individual areas, external and internal factors influencing the financial stability of insurance organizations, the possibilities of increasing the amount of profit they receive are substantiated, proposals are given to improve the methodology for managing the investment portfolio of insurance companies, and prospects for the development of modern options for investment activities are identified. The effective organization of the mechanism for monitoring the financial stability of insurance companies allows for minimizing the level of missed opportunities in achieving the company’s strategic goals based on econometric forecasting of financial stability and assessment of financial risks. In order to strengthen the role of insurance companies in increasing the investment potential of the country Uzbekistan, it is proposed to develop the securities market, the market for government, corporate, and municipal bonds.

Board gender diversity and corporate social responsibility

Based on a total of 1,590 listed non-financial firms on the Taiwan Stock Exchange and the Taipei Exchange (formerly the Over The Counter securities market) covering the period of 2007~2020, this study examines whether firm's performance on Corporate Social Responsibility (CSR) is affected by corporate board gender diversity. Based on the Upper Echelons Theory, the Agency Theory and the Resource Dependence Theory, increasing the number of female director to achieve higher level of gender diversity brings forth traits such as compassion, kindness, helpfulness, empathy, interpersonal sensitivity, a willingness to nurture, and a greater concern for others' well-being. These traits help firms form policies that prioritize stakeholders' welfare. Moreover, board gender diversity corresponds to a more diverse and broad background, understanding and experience of business operations, enabling firms to better understand where the key interest groups they face are and what they value. This allows firms to make more effective and better-performing decision in CSR. Through correlation analysis and multiple regression estimation, the principal outcome shows that greater degree of board gender diversity is associated with better CSR performance, confirming the hypothesis that a more gender diversified board enhances the efficiency of monitoring and advising function of board and then forming corporate strategies and implementations toward a better stakeholders’ management.

‘You are less credible in life, less reliable… people don’t want to give you a chance’ - a qualitative study on the experience of inferiority among non-standard workers in Belgium

ABSTRACT Workers in non-standard employment arrangements are often perceived as belonging to the periphery of the labour market. Consequently, many suffer from feelings of inferiority. This study explores how inferiority is expressed and experienced in the work life of non-standard workers and beyond. Interviews with 38 non-standard workers from Belgium were analysed thematically. Inferiority expresses itself through a series of metaphors: a jack of all trades, disposable product, and outsider. In addition, not having financial independence feeds into feelings of inferiority. Moreover, the labour market and social security regulations have created disparities between standard and non-standard workers that have accordingly fed experiences of inferiority as well. Finally, inferiority is perpetuated beyond the work context, for example, in the form of discrimination on the housing market and in the general image of non-standard employment as inferior by many people in society. This study highlights that governments and employers need to increase their efforts to equalise the rights and treatment between non-standard and standard workers. This could decrease non-standard workers’ feelings of inferiority and consequently improve their overall well-being.