Securities Market Research Articles

Comparative Analysis of GARCH-Based Volatility Models of Financial Market Volatility: A Case of Nairobi Security Market PLC, Kenya

This paper conducted a comprehensive comparative analysis of various GARCH (Generalized Autoregressive Conditional Heteroskedasticity) models to forecast financial market volatility, with a specific focus on the Nairobi Stock Exchange Market. The examined models include symmetric and asymmetric GARCH types, such as sGARCH, GJR-GARCH, AR (1) GJG-GARCH, among others. The primary objective is to identify the most suitable model for capturing the complex dynamics of financial market volatility. The study employs rigorous evaluation criteria, including the Akaike Information Criterion (AIC), Bayesian Information Criterion (BIC), Mean Error (ME), and Root Mean Absolute Error (RMAE), to assess the performance of each model. These criteria facilitate the selection of the optimal model for volatility forecasting. The analysis reveals that the GJR-GARCH (1,1) model emerges as the best-fit model, with AIC and BIC values of −5.5008 and −5.4902, respectively. This selection aligns with the consensus in the literature, highlighting the superiority of asymmetric GARCH models in capturing volatility dynamics. The comparison also involves symmetric GARCH models, such as sGARCH (1,1), and other asymmetric models like AR (1) GJG-GARCH. While these models were considered, the GJR-GARCH (1,1) model demonstrated superior forecasting capabilities. The study emphasizes the importance of accurate model selection and the incorporation of asymmetry in volatility modeling. The research provides essential insights into financial market volatility modeling and forecasting using both asymmetric and symmetric GARCH models. These findings have significant implications for government policymakers, financial institutions, and investors, offering improved tools for risk assessment and decision-making during periods of market turbulence.

The value of lending to bellwether firms by institutional investors

We predict that institutional investors in loan syndicates charge bellwether firms lower loan spreads as compensation for having access to private information that can help identify trading opportunities in other firms' public market securities. Consistent with this prediction, when lending to bellwether firms, institutional investors charge a loan premium that is between 17 and 25 bps lower relative to non-bellwether firms, and earn annualized excess returns of 1.5–2.2% from trading in other firms' securities. Findings from cross-sectional analyses reveal that the reduction in loan spread is larger when the value of private information from bellwether firms is higher. Additionally, institutional lenders' excess returns are lower when lending to more transparent bellwether borrowers and when they pay a lower price—as reflected in loan spreads—in exchange for the private information, supporting the notion that the value of private information relates to institutional investors’ trading performance.

Research on investment returns prediction based on machine learning

With the development of the Internet and the continuous improvement of the information disclosure mechanism of the securities market, individual investors have more and more ways to obtain investment information, including company research reports from analysts. However, analysts have mixed qualifications and publish a huge number of reports. For retail investors, how to analyze and distinguish these reports and make informed investment decisions based on them has become the key to profiting in a securities market where information is asymmetrical and risks and opportunities coexist. This is a priority that every retail investor should prioritize. In recent years, machine learning has become increasingly widely used in the financial sector, especially in the prediction of return on investment. In this work, a most advanced machine learning model Transformer is used, which is widely used in a variety of scenarios due to its advantages in processing sequence data. The Transformer model can effectively process and analyze large-scale financial time series data through the self-attention mechanism to capture subtle fluctuations and potential correlations in the market. We designed a Transformer-based architecture to combine multi-source data such as market macroeconomic indicators, stock trading data, and social sentiment analysis for comprehensive learning. Experimental results show that the model significantly improves the accuracy of investment return prediction and provides investors with efficient analysis tools.

The first public offering of a corporate bond issuance and the expected impact on the securities market and economy in Albania

This study aims to investigate the anticipated importance of the inaugural corporate bond issuance through public offering on the Albanian Stock Exchange (ALSE) and its potential ramifications for the bond market, investors, the broader financial sector, and the Albanian economy. Given that the ALSE has been predominantly characterized by government bonds, the initial public offering of the first corporate bond represents a noteworthy landmark that could facilitate the advancement of the Albanian financial market. We will scrutinize how this progression may result in heightened market liquidity, by appealing to both domestic and international investors, thereby increasing the aggregate trading volume and liquidity, within the exchange. Additionally, we will deliberate on the function of corporate bonds in diversifying the array of financial instruments accessible on the ALSE, which may assist in risk mitigation and the cultivation of a more stable financial environment. Moreover, we will analyze how the issuance of corporate bonds could promote superior corporate governance practices, culminating in increased transparency, more rigorous financial reporting, and bolstered investor confidence. Finally, we will contemplate the potential of corporate bond issuances to stimulate economic growth by supplying companies with an alternative avenue of funding for expansion and investment initiatives. This can result in job generation, enhanced productivity, and comprehensive economic development in Albania. By examining the anticipated consequences of the first corporate bond issuance on the ALSE, this study will illuminate the potential advantages and challenges associated with this development, laying the groundwork for future inquiries as the market undergoes further evolution.

Security market in Africa: the place of Russia and new opportunities

Security market in Africa: the place of Russia and new opportunities

Improving the Efficiency of Securities Market Operations amid Economic Turbulence

Improving the Efficiency of Securities Market Operations amid Economic Turbulence

State as a Special Participant of the Securities Market in the Russian Federation: The Financial Law Aspect

State as a Special Participant of the Securities Market in the Russian Federation: The Financial Law Aspect

A Study of the Impact of Investor Sentiment on Stock Investment Returns

This study examines the influence of investor sentiment on stock investment returns in China's rapidly developing yet volatile securities market. Utilizing principal component analysis, a comprehensive investor sentiment index is constructed from six key indicators. The dynamic relationship between investor sentiment and stock market return volatility is explored through a Vector Autoregression (VAR) model and Generalized Autoregressive Conditional Heteroskedasticity (GARCH) models. The findings reveal a significant bidirectional correlation, with positive optimism exerting a greater impact on stock returns than negative pessimism. The findings of this study indicate that investor sentiment exhibits a heightened sensitivity to declining returns as opposed to rising ones, offering valuable insights for both investors and policymakers.

Prioritizing the product development roadmap of Zains SAAS using Analytical Hierarchy Process (AHP)

Purpose: This study aims to prioritize the development of Zains using the Analytical Hierarchy Process (AHP). Research Methodology: focusing on the key factors influencing development priorities, and combines qualitative data from a Focus Group Discussion (FGD) with the Board of Directors (BOD) of CNT and quantitative data from digital surveys. Qualitative data provide insights into strategic priorities, challenges, and development goals, while quantitative data obtained through the AHP method determine the relative importance of various criteria and alternatives. This study identifies the key criteria for product development, including market demand, financial impact, technological relevance, operational efficiency, compliance, and security. Affinity Diagrams and TOWS Matrix were used to analyze qualitative data from the FGD. The proposed alternatives include mobile application feature enhancements, AI-powered financial insights integration, and enhanced security features.The AHP results indicate that the integration of AI-powered financial insights is the primary alternative in the Zains development roadmap. Results: These findings provide insights for CNT to optimize the development of Zains and to maintain their relevance and competitiveness in the SaaS market. These recommendations are beneficial for other SaaS providers facing similar challenges.

Measuring Shareholder Wealth in Light of Creative Accounting Practices

The aim of the research is to shed light on shareholder wealth and explain its definition and the role of management in increasing shareholder wealth and indicators. To achieve the aim of the research, the economic units listed on the Iraqi Securities Market, which completed their final accounts and totaled (138), were selected as a group for research with the identification of (9) expenses and a single hotel. of Iraqi hotels and (5) companies listed on the Iraqi Stock Exchange as a sample for research, and the researchers came to a group of conclusions, the most important of which is that shareholder wealth is the value that shareholders receive as a result of their investment in the company's shares and is measured through the increase in the market value of the shares that they own it and what profits they receive, and the researchers presented a set of recommendations, the most important of which was investors' depend in modern performance measures based on market value added and economic value added because these measures have the ability to measure the real impact of economic performance on wealth.

The Savings of Corporate Giants

Abstract We construct a novel panel data set to provide new evidence on how the largest nonfinancial firms manage their financial assets. Our granular data show that, over the past decade, bond portfolios have grown to be at least as large as cash-like instruments, driven by the meteoric rise of corporate bond holdings. To shed light on the drivers of this growth, we conduct a pair of event studies around the 2017 tax reform and the 2020 liquidity crisis. We find that large holdings of marketable securities are primarily driven by cross-border tax incentives, while cash-like instruments are driven by liquidity motives. (JEL G32, G35, G11, E440)

Exploring the interconnection between international crude oil and silver rates volatilities: Novel evidence from the COVID-19 pandemic

Several research studies globally focus on the volatility of gold and oil prices, neglecting an examination of silver price volatility in relation to other market commodities. The current Covid-19 pandemic has led to various uncertainties and fluctuations in financial and stock exchange markets, yet existing literature primarily concentrates on individual product rates rather than combined rate changes. Our study aims to bridge this research gap by analyzing the relationship between oil rates, silver rates, oil rate transitions, and silver rate transitions on the security exchange in China from 1990 to 2022, using the ARDL approach and Nonlinear ARDL for a comprehensive assessment. The findings reveal a significant impact of silver and oil rates on China's security exchange in the future, with the negative effects of oil rate changes and a positive effect of silver rate transitions. In the short term, oil and silver rates play a crucial role in influencing China's security exchange, highlighting the importance of monitoring these trends for investors. It is recommended that investors respond prudently to market transitions, particularly by considering silver as a secure option during times of uncertainty, while policymakers should implement appropriate measures to manage the rapid fluctuations from oil to the security market.

ESG rating uncertainty and institutional investment—evidence from China

Using panel data on China's A-share listed enterprises from 2015 to 2022, this study applies a fixed effects model of the year, industry, and region to empirically test the impact of ESG ratings and ESG rating uncertainty on institutional investment. The results of this study find that: (1) ESG ratings significantly and positively affect institutional investment, but the existence of ESG rating uncertainty significantly and negatively affects institutional investment. Meanwhile, ESG rating uncertainty weakens the influence of ESG ratings on institutional investment. (2) Institutional investors are more sensitive to the ESG rating uncertainty of enterprises that are government-related (state-owned and politic connected), executive-right-expanded, loss-making, non-heavy-polluting, non-high-tech, and in the eastern region. Meanwhile, passive institutional investors are more sensitive to the ESG rating uncertainty. (3) The number of institutional investors, government subsidies, and securities market performance are the channels through which ESG rating uncertainty affects institutional investment.

ENSURING CRIMINOLOGICAL SECURITY OF THE FINANCIAL MARKET IN RUSSIA

With the introduction of the digital economy and new financial products in Russia, changes have taken place in the financial services market. Against this background, illegal financial activities have sharply increased. This was facilitated by the expansion of information and telecommunication technologies, their use in all spheres of activity, including the development of domestic digital platforms, which increased the implementation of financial transactions in the stock markets, securities market, insurance sector, etc. At the same time, the risks of negative manifestations in the economic sphere have increased, which has influenced the growth of economic crime, which has become more organized, professional and, given the development of digital transformation, transnational. We should not fail to note its corrupt nature. The process launched by the state to stabilize and increase the rate of development of the state economy causes only positive reactions from society, but when the rate of development increases, problems arise, which destructive forces use in their own interests, for personal enrichment, where, breaking the law, they do not consider public opinion, do not pay attention to the state structures responsible for the security of this sector of the economy. It is crimes in the financial market that distinguish criminals of a new format from the old mastodons of criminal activity, and such qualities as high cohesion, organization, and competence allow them to establish control over various systems of life of society and the state, entering not only the sector of business and commerce, but also the budget sector, where continuing to establish monopoly control, lobbying their interests in various spheres of economic activity. One of such spheres at the current stage of formation of the digital economy is the financial market of Russia, which is subject to protection from criminal threats and criminogenic risks. In the current situation we cannot do without mechanisms to ensure the criminological security of the financial market, which requires the definition of the conceptual apparatus, the system of ensuring such security, the creation and construction of its structure and the definition of measures aimed at improving the level of such security. In conclusion of the article the author comes to the conclusion that the financial market of the Russian state does not fully use preventive measures, there are gaps both at the legislative level and in the organization of the financial market, which contributes to the growth of crimes in this area.

MORTGAGE LENDING AS A FACTOR OF SOCIAL AND ECONOMIC DEVELOPMENT OF THE COUNTRY

A mortgage and a mortgage loan are components of the mortgagesystem, the evolution of which dates back several millennia. During this period, there was a transformation of views on the mortgage -from a pledge -a plot of land to an understanding of the mortgage as a financial instrument in the mechanism of socio-economic development of the country.In the lands of Ukraine, the mortgage system arises and develops simultaneously with the development of banking. At the end of the 19th and the beginning of the 20th centuries. a network of mortgage banks was formed on the territory of Ukraine, and mortgages acquired credit functions and turned into a supply channel for investments in agriculture. In the modern period, a mortgage loan is an effective tool in the mechanism of development of the market economy. Mortgages not only stimulate the construction of new housing and provide housing for the country's population on a market basis, but also launch the mechanism for the development of the securities market, the banking and insurance market, and allow the creation of additional jobs in the construction industry and in the production of consumer durables. The action of the mortgage has a multiplicative effect and allows to achieve a significant socio-economic effect, is a factor in the birth of the middle class in societyand a prerequisite for the formation of social well-being. A key role in the development of mortgage lending in the modern period is played by the state program "eOselia", which began working in Ukraine in October 2022 and allowed to obtain a mortgage loan from 3% to 7% per annum. Since the beginning of the "eOselia" program in Ukraine, mortgage loans in the amount of more than 13 billion hryvnias have been issued, and more than 8,500 families have benefited from this program.Adapting the work of the mortgage system to the conditions of war, the aggravation of security risks and demographic changes, requires the participants of the mortgage market to improve the business models developed in pre-war times, to look for new forms for the restoration of mortgage lending, to conduct constant monitoring of social, political and economic factors. The adaptation mechanism on the part of the state provides for the strengthening of legal control over all elements of mortgage lending and maximum support through the transparency of pricing for mortgage loans.

ОСОБЛИВОСТІ ПРАВОВОГО РЕГУЛЮВАННЯ ТРУДОВИХ ВІДНОСИН ПРИВАТНИХ СУБ’ЄКТІВ ОХОРОННОЇ ДІЯЛЬНОСТІ В УКРАЇНІ ПІД ЧАС ДІЇ ВОЄННОГО СТАНУ

The article examines the peculiarities of legal regulation of labor relations of private subjects of security activities in Ukraine during martial law. The levels of legal regulation of labor relations of private subjects of security activity are described on the basis of modern regulatory documents. The stages of formation of security activity in Ukraine in modern conditions are revealed: dismantling of the security system that existed at the previous stages of its development; the appearance of numerous private subjects of security activity; demarcation of the security market between state and private subjects of security activity; creation of a legal basis for the activities of private subjects of security activities; during a pandemic and martial law – increased competition, increased number of qualified personnel (combatants), fluctuations in demand for services, increased technological requirements for the security system. It is indicated how the introduction of changes to the Licensing Conditions for conducting security activities is consistent with the requirements of the current legislation regarding the accounting of conscripts and reservists. According to the results of the analysis of the legislation, it was established that the trend of legal regulation of labor relations in the conditions of martial law in Ukraine is not specific, but for private entities of security activity, it takes into account the specifics of the industry. Key words: security activities, labor relations, legal regulation, martial law.

Portfolio Analysis of Multi-Factor Stock Selection Model Based on Investor Sentiment

Since 1990, China's securities market has been gradually improved. Domestic and foreign scholars have proposed many theoretically perfect investment models, but not many of them have been applied in practice because the market cannot satisfy the strict assumption conditions of the models. Foreign quantitative investment models are not necessarily effective in the Chinese market. Based on this, this paper takes the portfolio theory as a guide, uses the scoring method to construct a multi-factor stock selection model, and selects the relevant factors in combination with the characteristics of the Chinese market. Through empirical analyses, the validity of the multi-factor stock selection model with equal weight allocation in China's market is verified. In addition, this paper innovatively constructs an investor sentiment factor, combines the sentiment timing with the multi-factor stock selection model, optimises the timing on the basis of the multi-factor stock selection model, and proposes an investment strategy to obtain excess returns stably.

Privacy-preserving distributed market mechanism for active distribution networks

Amidst the worldwide efforts to decarbonize power networks, Local Electricity Markets (LEMs) in distribution networks are gaining importance due to the increased adoption of renewable energy sources and prosumers. Considering that LEMs involve data exchange among independent entities, privacy and cybersecurity are some of the main practical challenges in LEM design. This paper proposes a secure market protocol using innovations from distributed optimization and Secure MultiParty Computation (SMPC). The considered LEM is formulated as an uncertainty-aware joint market for energy and reserves with affine balancing policies. To achieve scalability and enable the use of SMPC, market clearing is solved using the Consensus ADMM algorithm. Subsequently, the data exchange among participants via ADMM iterations is protected using the Shamir secret-sharing scheme to ensure privacy. The market protocol is further reinforced by a secure and verifiable settlement process that uses SMPC and ElGamal commitments to verify market quantities and by a secure recovery scheme for missing network measurements. Finally, the feasibility and performance of the proposed LEM are evaluated on a 15-bus test network.

Cryptoeconomics: Financial Market Security Aspects and Implications for Managerial Accounting

"The development of modern information technologies and the processes of globalization are key factors for the emergence and spread of virtual currency. The legal status of cryptocurrency is still uncertain. It is considered both as a modern means of payment and as a speculative tool for illegal activities. However, despite such diametrically opposed interpretations, the fact that economic realities are constantly changing is unconditional. The IFRS reporting system is no exception, which should adapt to new challenges in a timely manner and take into account the need to disclose information about new progressive elements as much as possible. The article aims to analyze the economic and financial essence of cryptocurrencies, assess the phenomenon of the crypto economy and its impact on the financial market and monetary policy, as well as to outline appropriate implications for the corporate level – namely, for management accounting. The methodology is based on a theoretical analysis of cryptographic protocols and tools for investment and macroeconomic analysis, some approaches of economic theory. It is shown that although today cryptocurrency is a speculative, high-risk instrument, cryptoeconomics is increasingly integrating into the global financial market, while the potential risks of this process still outweigh its benefits. Accordingly, at the micro-level, management accountants must understand the related risks and be able to explain the implications to the management team and the board of directors. The originality of research consists of an attempt to combine the analysis of macro- and micro-implications of emerging crypto economics based on an economic theory foundation."

PANDEMIC’S IMPACT ON BURSA MALAYSIA SECTORS: A COMPREHENSIVE STUDY UTILIZING OLSM AND ESM

The pandemic has the potential to induce significant stock market volatility as a consequence of investor decisions, while movement restrictions may force the closure of many small-to-medium enterprises (SMEs). Despite this, there is a noticeable absence of comprehensive perspectives on the pandemic's impact across all sectors in Bursa Malaysia. Consequently, this paper endeavors to scrutinize the sector within Bursa Malaysia most profoundly affected by Covid-19. Employing the Ordinary Least Squares method (OLSM) method and the Event Study Method (ESM), the study compares stock returns and risks. The independent variables encompass daily counts of Covid-19 cases and deaths in three countries—Malaysia, the United States, and China—as well as the Brent oil price. The study focuses on 13 sectorial indices, including construction, consumer products, energy, finance, healthcare, industrial products, plantations, property, real estate investment trusts, technology, telecommunications and media, transportation and logistics, and utilities. Utilizing the ESM, the study investigates the daily average return, abnormal return, and expected return of each sector to gauge the impact of Covid-19. Historical data from March 18 to May 3 over three years (2019 to 2021) is employed. Results indicate that an increase in Covid-19 cases in Malaysia correlates with a decrease in the performance of these 13 sectors. Consequently, this study contributes to enhancing investor comprehension of sectorial indices' volatility and significance during the pandemic, aiding them in monitoring sectoral performance in the securities market.