Securities Market Research Articles

Differences in economic consequences of union dissolution across gender and ethnic groups in Belgium and Israel

ABSTRACT Given increased ethnic diversity in Europe and Israel in recent decades, coupled with high union dissolution rates, the study compares two case studies exemplifying diverse ethnic and immigrant societies – Belgium and Israel. We examine differences between ethnic, migrant, and gender groups in each country, and the intersections between them, regarding the economic outcome of union dissolution, as well as the effect of reemployment on these consequences. The study adds to the broad discussion on union dissolution and inequality in the dimensions of ethnicity, migration and gender and their intersections across countries. Growth models were applied to data from two longitudinal sources: the Data Warehouse on Labor Market and Social Security for Belgium and administrative data from tax authorities with the National Insurance Institute database for Israel. Results show that change in income upon separation is gendered and varies between ethnic/migrant groups in both countries. Cross-country differences were found in the effect of reemployment mainly among women, as it increases the income of minority-group women in Belgium but not Israel. The study emphasizes the importance of the intersectionality perspective in comparative studies, revealing the interplay between ethnicity, gender, and country in how ex-partners cope with the financial consequences of union dissolution.

Price Volatility Mitigation and the Securities Market Financial Performance of Listed Insurance Firms at Nairobi Securities Exchange.

The performance of securities market globally plays an important role in both local and international markets. The high rise of such markets has given an increase in the number or risks associated with firms registered at the stock market. This study therefore sought to examine the effect of price volatility mitigation on the securities market financial performance of listed insurance firms in Kenya. The study adopted a descriptive research design and a quantitative research approach. The target population was 548 staff working in finance, investment, risk, actuarial and operations departments in the six insurance firms listed in Nairobi Securities Exchange. The sample size was determined using Yamane's Formula and stratified random sampling was used in the selection of the sample size. The study made use of both primary and secondary data. The study used a data extraction tool to collect secondary data from the annual reports and financial statements of the insurance companies. The study made use of structured questionnaires to collect primary data. The questionnaires generated quantitative data. Descriptive and inferential statistics was used in analyzing quantitative data with the help of the Statistical Package for Social Sciences (SPSS version 24) statistical software. Descriptive statistics included frequency distribution, percentages, mean, and standard deviation. Inferential data analysis was done using Pearson correlation coefficient and linear regression analysis. The study found that price volatility mitigation has a positive and significant effect on securities market financial performance of listed insurance firms in Kenya. The study recommends that insurance firms should focus on implementing strategies to effectively manage supply and demand dynamics within the securities market. This includes closely monitoring market trends, analyzing supply-demand imbalances, and adjusting pricing and stock clearance strategies accordingly. By actively managing supply-demand dynamics, firms can mitigate price volatility risks and enhance securities market financial performance

Warren Buffett and Berkshire Hathaway's Recent Investment Strategy Changes and the Reasons for the Corresponding Risk Measures

With the development and changes of the world economy, the size of the global securities market is gradually increasing, and the investment methods available for citizens to choose from are becoming more diverse. Stocks, as one of the most important investment methods, have also received increasing attention from investors. After experiencing a slow economic recovery, the distribution of global stock and securities markets is also constantly expanding. In recent years, the global ETF market has crossed new milestones, with a scale exceeding $11 trillion for the first time, showing an unstoppable development trend, reflecting the recovery and growth of the global securities market after experiencing the financial crisis. In addition, global stock indices have generally risen. Especially for assets that are lagging behind in 2023, it shows an upward trend in the global securities market after entering 2024. Due to the continuous changes and maturity of the economic landscape and securities market, it has brought huge social dividends and increased investor willingness. As an outstanding representative in the fields of stock and securities investment, Buffett's investment ideas and strategies have been highly valued by the general public. Therefore, studying typical cases of Buffett's investments has a guiding significance. This article will analyze Buffett's investment preferences and performance from 2023 to the first half of 2024, starting from the current international background and combining Buffett's value investment philosophy. It will provide reference suggestions for investment industry practitioners and regulatory agencies.

A Case Study on The Failed IPO of Xi'an Xintong Pharmaceutical Research Co., Ltd. on The SSE STAR Market

In order to support the development of innovative enterprises and promote the transformation and upgrading of China's economy, the science and technology innovation board was officially opened on June 13 of 2019, and the first batch of companies were listed on July 22, with a total of 25 companies. China's securities market has entered a stage of reform and development from the approval system to the registration system. The registration system can lower the threshold for enterprises to go public, improve the speed of enterprise listing, and help enterprises quickly obtain capital and resources and expand the scale of enterprises. However, enterprises under the registration system need to pay more attention to corporate governance and information disclosure in order to bear more market risks and regulatory pressures. This paper takes Xi'an Xintong Pharmaceutical Research Co., Ltd. as the research object to explore the reasons behind the failure of its IPO on the Science and Technology Innovation Board, and summarizes the conclusions, which has certain research significance. This paper first uses the literature analysis method to conduct a detailed analysis of the literature related to the Science and Technology Innovation Board and IPO, which provides some theoretical support for the following paper. Then, the basic situation of the case company, the main business, financial data and the motivation for the IPO failure were introduced in detail. Finally, suggestions are given according to the reasons for failure and summarized.

Multimodal market information fusion for stock price trend prediction in the pharmaceutical sector

With the evolution of China's market economy, the securities market is increasingly anchoring a pivotal role in the nation's economic landscape. Consequently, stock trend forecasting has garnered heightened attention among scholars and practitioners. This research pioneers the use of multimodal information to predict stock market fluctuations. Based on our experimental results, LSTM + Transformer performs better in handling multimodal data for stock movement prediction tasks regarding accuracy, F1-score, precision, and recall. Additionally, we employed the Granger causality test and Impulse response test to investigate the causal relationships between sentiment and stock trends, as well as the interplay between COVID-related indicators and stock trajectories. We identified discernible causal links between sentiments, COVID indicators, and stock trends for select pharmaceutical stocks. Our findings can provide valuable guidance for investors and market regulators, especially within the pharmaceutical industry. Understanding investor sentiment and the impact of the pandemic on severity can assist in effective stock commentary management and improve investment strategies.

Economic Risk Mitigation and the Securities Market Financial Performance of Listed Insurance Firms at Nairobi Securities Exchange.

The performance of the global securities market plays a crucial role in both local and international economies. The rise of these markets has increased the risks associated with firms listed on the stock market. This study aimed to examine the effect of economic risk mitigation on the financial performance of listed insurance firms in Kenya's securities market. A descriptive research design and a quantitative research approach were adopted. The target population consisted of 548 staff members working in finance, investment, risk, actuarial, and operations departments across the six insurance firms listed on the Nairobi Securities Exchange. The sample size was determined using Yamane's Formula, and stratified random sampling was employed to select the sample. Both primary and secondary data were utilized in this study. Secondary data were collected using a data extraction tool from the annual reports and financial statements of the insurance companies, while structured questionnaires were used to gather primary data. The collected data were analyzed using descriptive and inferential statistics with the help of SPSS (version 24). Descriptive statistics included frequency distribution, percentages, mean, and standard deviation, while inferential data analysis was conducted using Pearson correlation coefficient and linear regression analysis. The study found that economic risk mitigation has a positive and significant effect on securities market financial performance of listed insurance firms in Kenya.

Correlation and Impact of SSEC and SZI Empirical evidence based on VAR model

Today, the world economy is experiencing globalization and diversification, and China's economy is also developing rapidly, also the development speed of the capital market has been significantly improved. Among them, the impact of the development of the securities industry on China's capital market cannot be ignored. As the two major stock exchanges in China, the Shanghai Stock Exchange and the Shenzhen Stock Exchange are not to be underestimated in the securities market. Therefore, the Shanghai Securities Composite Index (SSEC) and the Shenzhen Securities Component Index (SZI) represent the direction of China's stock market to a certain extent. Therefore, this paper will start from the perspective of SSEC and SZI, select the data for a total of 10 years from 2009-2018, and try to construct the VAR model, and finally draw the impulse response function graphs of both of them. The basic conclusions of the study are the SSEC has a relatively large impact on the capital market, while the SZI has a relatively small impact on the capital market. Therefore, the inspiration for investors is that the SSEC is more informative and useful when making investments.

Long Run Impact of Mergers and Acquisitions Activities on Acquirer’s Return of Firms Listed in Eastern Africa Securities Markets

This study investigated the impact of mergers and acquisitions activities of acquiring firm return in the long run on firms listed in Eastern Africa Securities Markets. The final sample comprised of twenty five (25) completed mergers and acquisitions firms publicly trading in Eastern Africa securities markets merging with or acquiring either a private or a public target firm for the period between 1998 to 2015. Carhat four factor model was used to compute long run cumulative abnormal return. The findings of the study were insignificant. Consequently, the null hypothesis was not rejected, leading to the conclusion that, in the long ru, M&A activities do not generate significant returns to acquiring firms listed on Eastern Africa securities markets. The findings of this study resonates with majority of the existing studies.

Application of Artificial Intelligence in the Securities Market

Artificial Intelligence (AI) involves creating machines that replicate human cognitive functions, enabling them to think and act similarly to people. In the context of stock trading, AI refers to the use of technology designed to buy and sell shares with increased precision and efficiency compared to human capabilities. AI-driven systems are currently employed to predict stock market trends and analyze trading patterns among investors and brokers. Prominent financial institutions on Wall Street, such as Goldman Sachs and Morgan Stanley, are increasingly adopting specialized AI solutions, including data mining, natural language processing, and self-learning algorithms. These tools operate with greater speed than everyday applications. Additionally, AI aids wealth management firms in continuously monitoring market movements and adjusting portfolios to achieve target profits. While AI can significantly reduce workload and provide real-time recommendations, it does not entirely eliminate the need for human oversight. Keywords: artificial intelligence, securities, trading, forecasting.

Demographic changes, technology growth, and retirement policy reform: Implications for U.S. housing dynamics

As the population aging process continues, concerns about how this situation impacts the housing market and social security rise. To address this question, this paper presents a developed and calibrated general equilibrium life-cycle model incorporating two production sectors to analyze the impacts of demographic structure changes and retirement policy reforms on housing price fluctuations and household choices. The model calibrated to the U.S. macroeconomic data between 1968 and 2018 suggests that in an economy with unlimited land supply, the housing supply curve exhibits perfect elasticity, rendering demographic changes insignificant in housing price fluctuations, while technological advancements lead to decreased prices. A 1% growth in productivity in both sectors results in a 2.6% decrease in house prices. Furthermore, a 1% decrease in population and a 5-year early retirement led to significant reductions of 25% and 30% in individual social security payments and 9% and 18% in interest rates, respectively. This suggests that during a recession caused by demographic structural changes, households become more conservative and prioritize precautionary saving strategies, increasing savings and investing more in housing assets. Consistent with empirical findings, during an economic boom, a decline in the capital-output ratio and the real housing price suggests a decrease in savings and housing asset investment. The rise in consumption drives the capital demand of the non-housing sector to increase, stimulating business expansion and labor inflow.

The economic burden of long COVID in Australia: more noise than signal?

To estimate the potential economic burden of long COVID in Australia. A stock-and-flow model of weekly estimated numbers of people with long COVID (January 2021 to June 2023); application of proxy cost estimates from people living with myalgic encephalomyelitis/chronic fatigue syndrome; time series analysis of labour market and social security datasets. The working age Australian population. The likely number of Australians severely impacted by long COVID; the economic cost of long COVID; and the impacts of long COVID, determined by analysis of labour market data. At its peak in late 2022, between 181 000 and 682 000 Australians may have experienced some long COVID symptoms, of whom 40 000-145 000 may have been severely affected. Severe cases potentially decreased to affecting 10 000-38 000 people by June 2023. The likely economic burden of long COVID in Australia during 2022 was between $1.7 billion and $6.3 billion (some 0.07% to 0.26% of gross domestic product). Labour market data suggest that between 25 000 (February 2023) and 103 000 (June 2023) more working age Australians reported being unable to work due to long term sickness than would have been predicted based on pre-COVID-19 trends. This does not appear to have translated into increased claims for Disability Support Pensions, but numbers of working age Carer Allowance recipients have grown markedly since 2022. Long COVID likely imposed a small but significant aggregate toll on the Australian economy, while exposing tens of thousands of Australians to substantial personal economic hardship and contributing to labour market supply constraints. Yet while some signal from long COVID is discernible in the labour force data, Australia lacks adequate direct surveillance data to securely guide policy making.

Potential of the securities market in Russia

Potential of the securities market in Russia

Analysis Of The Impact Of Traditional Market Revitalization On Increasing Traders' Income (Case Study Of Pekkae Modern Market, Barru Regency)

This research aims to analyze the impact of traditional market revitalization on increasing traders' income, focusing on the case of Pekkae Modern Market in Barru Regency. The market revitalization was initiated by the government to enhance the competitiveness of traditional markets in response to the growing dominance of modern markets. This study using a qualitative approach with a case study method. Data were collected through in-depth interviews with traders and market managers, as well as direct observations of the physical changes and market management post-revitalization. The findings indicate that the market revitalization has positively affected traders' income due to the increased consumer visits and improved market facilities, which have become more comfortable and orderly. Additionally, changes in stall arrangement, parking area expansion, and improvements in market cleanliness and security have also contributed to enhancing the market's appeal to consumers. Thus, traditional market revitalization can be considered an effective strategy in supporting the sustainability and development of traditional markets in the modern era.

Deep learning-based high-frequency jump test for detecting stock market manipulation: evidence from China’s securities market

PurposeThis study aims to tackle the critical issue of detecting stock market manipulation, which undermines the integrity and stability of financial markets globally. Even enhanced with machine learning, traditional statistical methods often struggle to analyze high-frequency trading data effectively due to inherent noise and the limited availability of publicly known manipulation cases. This leads to poor model generalization and a tendency toward over-fitting. Focusing on China's securities market, our study introduces an innovative approach that employs deep learning-based high-frequency jump tests to overcome these challenges and to develop a more effective method for identifying manipulative activities.Design/methodology/approachWe employed the “Jump Variation – Time-of-Day” (JV-TOD) non-parametric technique for jump tests on high-frequency data, coupled with the synthetic minority over-sampling technique (SMOTE) algorithm for re-balancing sample data. Our approach trains a deep neural network (DNN) on refined data to enhance its ability to identify manipulation patterns accurately.FindingsOur results show that the deep neural network model, calibrated with high-frequency price jump data, identifies manipulation behavior more specifically and accurately than traditional models. The model achieved an accuracy rate of 94.64%, an F1-score of 95.26% and a recall rate of 95.88%, significantly outperforming traditional models. These results demonstrate the effectiveness of our approach in mitigating over-fitting and improving the robustness of market manipulation detection.Practical implicationsThe proposed model provides regulatory entities and financial institutions with a more efficient tool to monitor and counteract market manipulation, thereby improving market fairness and investor protection.Originality/valueBy integrating the JV-TOD jump test with deep learning, this study proposed a new approach to market manipulation detection. The innovation is in its capacity to detect subtle manipulation signals that traditional methods typically overlook. Our model, which is trained on jump test data enhanced by the SMOTE algorithm, excels at learning complex manipulation patterns. This enhances both detection accuracy and robustness. In contrast to existing methods that are challenged by the noisy and intricate nature of high-frequency data, our approach shows enhanced performance in identifying nuanced market manipulations, offering a more effective and reliable method for detecting market manipulation.

The Role Of Emotional Intelligence in The Board Of Directors and Its Impact On The Performance and Value Of Institutions and Conservative Practices In Light Of Crises (Applied Research On a Sample Of Banks Listed On ISX)

This research aims to underscore the significance of women's emotional intelligence in enhancing the effectiveness of the Board of Directors, a crucial component of internal governance, particularly during crises. Despite strides made in recent decades in appointing women to senior roles in government, business, and education, challenges persist in improving women's leadership opportunities, especially in developing countries. The study utilizes statistical methods, including Pearson's correlation, to analyze the relationships between variables within a sample of banks listed on the Iraqi securities market, comparing periods before and during the COVID-19 pandemic (2019 and 2020). The goal is to measure the impact of female emotional intelligence on the Board of Directors' ability to manage crises, focusing on variables such as conservative accounting policies, Board compensation and benefits, meeting frequency, the ratio of external auditor fees to enterprise capital, enterprise capital, share profitability, and the market-to-share profitability ratio. Findings indicate that emotional intelligence (measured by the number of females on the Board) positively influences conservative accounting policies and meeting frequency during crisis periods. Conversely, the pre-crisis period showed a negative relationship, suggesting a proactive and risk-responsive stance by women during crisis. Additionally, the study observed an inverse relationship between crisis periods and both Board compensation and external auditor fee ratios, implying a cost-reduction strategy facilitated by female emotional intelligence. The crisis period also saw an increase in the profitability of individual shares and the market-to-share profitability ratio. The research recommends expanding the study to compare the role of emotional intelligence in Boards between developing and developed economies.

Precarious employment expectancy by history of mental-health-related sickness absence in Finland

Abstract Background Poor mental health may lead to labour market insecurity including precarious employment and vice versa. Less is known of how mental health is associated with cumulative engagement in precarious employment over the working career. We examined how the working career is expected to be distributed into precarious and other types of employment by history of mental-health-related sickness absence. Methods We used a register-based 70% population sample to examine wage-earners living in Finland in 2018. Applying the Sullivan method, we calculated the expectancy of precarious and non-precarious employment between age 25 and 63 (N = 1268666) based on a novel measure (score with items on temporariness, agency employment, multijob holding, underemployment and income level) and limited employment (due to which precariousness could not be assessed) among those with and without compensated (granted after 10 weekdays) sickness absence due to mental disorders in the past five years (mental SA history). Results Precarious employment expectancy was higher among those with than among those without a mental SA history (2.5 vs. 1.5 among men and 3.5 vs. 2.8 years among women). The difference in the limited employment expectancy was in the same direction, but much larger among men (6.5 vs. 3.3 among men and 4.4 vs. 3.4 years among women). Men with a mental SA history were expected to spend almost a fourth of their working career with either precarious or limited employment, whereas for men without such a history the number was 13%. Conclusions Individuals with mental disorders have notable accumulation of precarious employment over the working career. They also spend excessive time with limited employment, which may have similar elements as precarious employment and reflect broader labour market insecurity. Attempts should be made to ensure that insecure employment conditions among people with mental health problems do not further deteriorate their health and work ability. Key messages • People with mental disorders spend a disproportionate part of their working career either precariously employed or facing other insecurities in the labour market. • Interventions aiming to promote health and work ability should take into account the interplay between poor mental health and poor employment conditions.

Influence of Corporate Information Transparency on Foreign Institutional Investors' Shareholding Behavior: Evidence from Public Listed Companies in China

In 2003, China implemented the Qualified Foreign Institutional Investor (QFII) system, which has garnered considerable interest from international institutional investors in the mainland market. As global investors, QFIIs depend significantly on precise, thorough information to bolster their investing criteria. Consequently, the transparency of corporate information becomes a crucial factor for QFIIs. However, due to the relatively late development of the Chinese market, an imbalanced structure of listed companies and information asymmetry, the information disclosure of listed companies has been subject to certain degrees of distortion. Therefore, to better facilitate the development of China's securities market and to help QFIIs fully realize their advanced value investment strategies, this paper aims to study the impact of corporate information transparency on the stockholding behavior of foreign institutional investors. This paper begins by reviewing the literature on the factors influencing institutional investor holdings, corporate transparency, and the characteristics of foreign institutional investors' stockholding. It then defines the concepts of corporate information transparency and foreign institutional investors, analyzes the current state of information transparency in Chinese listed companies, and examines the development of the QFII system in China. The theoretical framework explores the mechanisms through which corporate information transparency influences the stockholding behavior of foreign institutional investors. In the empirical analysis, the paper plans to measure the information transparency of listed companies from three perspectives: earnings quality, information ratings by the Shenzhen Stock Exchange, and the number of analyst followings, to investigate how corporate information transparency influences QFII stockholding behavior.

Securities Markets in Which Some Investors Receive Information About Cash Flow Betas

We analyze a single-factor setting in which there is private information regarding cash flows as well as their betas. Private information about betas, together with market makers’ risk aversion and mean betas’ nonnegativity, implies a nonlinear price schedule whose stochastic slope covaries positively with order flow when the expected factor payoff is positive and vice versa. We predict a negative relation between the covariance and expected returns and an attenuation of the beta anomaly in asset returns after accounting for this relation. Empirical tests confirm these predictions. This paper was accepted by Lukas Schmid, finance. Funding: L. Yang acknowledges the Social Sciences and Humanities Research Council of Canada [Grant 435-2021-0040] and Bank of Canada Fellowship for financial support. Supplemental Material: The online appendix and data files are available at https://doi.org/10.1287/mnsc.2022.02061 .

Research on Portfolio Investment in the Risky U.S. Stock Market Based on the Mean-Variance Model

Abstract: Against the backdrop of a thriving securities market and economy, there is a growing demand among investors for stock portfolio models in risky markets. This paper explores the application of the mean-variance model in this context, aiming to assist investors in making more informed investment decisions in an uncertain market. Through an in-depth analysis of the mean-variance model, the main conclusion of this paper is that certain stocks, such as AAPL, receive a higher investment proportion due to their lower risk and stable expected returns. In contrast, some high-risk or low-expected-return stocks, such as SBUX, MSFT, and QCOM, hold a smaller or zero proportion in the portfolio. This conclusion highlights the importance of balancing risk and return when constructing a portfolio and provides investors with specific asset allocation recommendations. It can help them effectively control risk while pursuing maximum returns, thereby achieving long-term stable investment gains.

Financing Sustainability: Unveiling the Role of Government Debt in Carbon Reduction Performance

The existing literature on government debt has predominantly focused on its influence on economic growth, with relatively limited attention paid to its ecological implications. Government debt, as an important financial tool, plays an essential role in improving the quality of economic development, yet its impact on sustainable governance remains underexplored. Against this backdrop, this paper investigates the relationship between government debt and carbon reduction using a sample of Chinese listed companies from 2010 to 2023. After excluding missing and financial firm data, our final sample includes 26,535 observations. We obtained these data from the China Security Market Accounting Research (CSMAR) database and the Wind database. This study utilizes ordinary least squares (OLS) as the baseline regression and identifies a significant positive impact of government debt on carbon emissions. Further, the moderating analysis suggests that the positive impact of government debt on carbon reduction is particularly stronger in state-owned (SOEs) and heavily polluting enterprises. To ensure the robustness of these findings, we also use fixed-effects models and the generalized method of moments (GMM), validating the consistency of the findings. This research provides critical practical and theoretical insights for regulators and adds to the prevailing body of literature on emissions reduction.