Financial Market Participants Research Articles

Analysis and Prediction of Financial Stock Risk Value Based On Improved FAST-ICA Algorithm and GARCH Model

This study focuses on improving the FAST-ICA algorithm and GARCH model to more accurately analyze and predict the value at risk of financial stocks. Accurately measuring stock risk is crucial for investors and securities managers in today's financial markets, as it directly affects investment decisions and risk control. We have improved the FAST-ICA algorithm and proposed the TS-ICA algorithm, aiming to improve the separation performance and iteration efficiency of the algorithm. And we combine the TNA method for data preprocessing to eliminate noise and improve the robustness and prediction accuracy of the model. In terms of GARCH model, we constructed the TS-ICA-GARCH model using the independent decomposition results of the TS-ICA algorithm to more accurately predict the volatility and value at risk (VaR) of stocks. Through empirical analysis and backtesting, we have verified the superiority of the TS-ICA-GARCH model in measuring risk, especially in extreme market conditions with stronger coping ability. This study provides a more reliable risk assessment tool for financial market participants, which helps to develop more effective investment strategies and risk management measures.

An study of liquidity shock, financial market participation on hollowing behavior of controlling shareholder

Agency conflict between controlling shareholders and small and medium-sized shareholders has become a key issue of concern and research in academia. However, existing studies have less thought about external root causes leading to their hollowing out behavior, especially the lack of in-depth research on the role of liquidity shocks in the mechanism between hollowing out behavior and market participation. Based on market participation perspective, empirical evidence from listed companies from 2006 to 2022, this paper empirically finds liquidity shocks significantly inhibit efficiency of controlling shareholders' hollowing out behavior; at the same time, financial market participation strengthens this inhibitory effect.

Dynamic Optimization of Investment Portfolio Based on Self-Attention Mechanism - LSTM Model Prediction

In the era of big data and advanced computational capabilities, financial market participants are continuously searching for innovative strategies to gain a competitive edge. A potential pathway emerges in the domain of deep learning, especially with regard to the LSTM neural architectures, which are renowned for their ability to handle and make predictions based on time series data. This study delves into the utilization of LSTM for predicting stock prices, emphasizing the advantages of dynamic investment portfolios in the rapidly fluctuating market conditions. Utilizing a dynamic window approach for time series data preprocessing, a self-attention mechanism - LSTM model was designed to anticipate the tendency of annual closing prices for five stocks from 2022 to 2023, Utilizing the initial 80% of stock price data as training set and allocating the residual 20% for validation. The performance of the dynamic optimization portfolio model was assessed by dynamically adjusting the weights of the stocks based on the last 20% of the data, and was subsequently compared to actual market cumulative returns. The findings indicate not only that the LSTM model offers a commendable level of accuracy in predicting stock prices, but also that the recursive algorithm for the dynamic optimization portfolio, constrained by maximum returns and minimal standard deviation, consistently outperforms the general market.

Financial Literacy, Financial Technology Literacy, and Capital Market Participation

Objective: This study aims to determine the effect of financial literacy and fintech literacy on capital market participation. It also examines the effects of individual characteristics (i.e., gender, age, student's allowances and income, parent's education, and parent's income) on financial and fintech literacy. Design/Methods/Approach: This study obtained 349 data from email and field surveys using purposive sampling. Data analysis was performed using OLS and path analysis. Findings: Results show that the level of student financial literacy is sufficiently literate, with a moderate level of fintech literacy but low capital market participation. The results also show financial and fintech literacy positively affects capital market participation. Financial literacy also exhibits indirect effects on capital market participation. Analysis of the determinants of literacy shows that gender, age, student allowances, and income have a significant positive effect on financial literacy and fintech literacy. We also find that parental education and income show a negative effect on fintech literacy. Originality/Value: This study is the first to examine the relationship between financial literacy, fintech literacy, and capital market participation in young adults in metropolitan cities in Indonesia. The results are expected to provide insight for the authorities of the monetary system and the capital market to develop strategies for the more intense involvement of young adults in the capital market. Practical/Policy implication: This study highlights the importance of educating students about financial and fintech literacy to increase their participation in the capital market. Decision-makers should focus on providing intense education on portfolio investment, risk and return, and investment instruments. Financial authorities should also collaborate with fintech operators and securities companies to promote capital market products through fintech and educate the public with more comprehensive information.

Analysis of the Use of CAPM in Investing Decisions in the Financial Sector Listed on the IDX for the Period 2020 – 2022

This study aims to analyze the use of the Capital Asset Pricing Model (CAPM) in making investment decisions in the financial sector listed on the Indonesia Stock Exchange (IDX) during the 2020-2022 period. This research method involves collecting historical stock price data and financial data of companies listed in the IDX financial sector during the period under study. This research uses a descriptive research design with a quantitative approach and uses secondary data. Furthermore, statistical analysis will be conducted to test the effect of using CAPM on investment decisions. The results of this study are expected to provide valuable insights for investors and financial market participants. This research can also help in identifying companies in the financial sector that have higher return potential based on CAPM-based analysis.

Digital financial inclusion and tourism development

Digital financial inclusion is reshaping the development of the Chinese economy. This paper examines the impact of digital financial inclusion on tourism development. Using a large sample of 281 Chinese prefecture-level cities for the 2011–2018 period, we find that digital financial inclusion is positively associated with tourism development. The results are consistent in various robustness tests. Mechanism tests show that digital financial inclusion promotes tourism development by enhancing individuals' financial market participation, promoting entrepreneurship activities in the tourism industry, and increasing individuals’ tourism consumption. Further analysis shows that the positive association with digital financial inclusion is more prominent in non-eastern regions and in cities with rich travel resources. Our study suggests that digital financial inclusion is an important factor that promotes tourism development.

Green financial technologies: behavioral aspects of development

Methods. The theoretical and methodological basis of the scientific research was the results of domestic and foreign research on the creation and development of eco-projects in the context of the creation and development of financial innovations and technologies. In order to achieve the set goals, scientific provisions and conclusions in the work are based on the basic concepts of behavioral theory and institutional theory of financial market development. The main research methods were empirical methods, which allowed to investigate the development trajectories of individual Green FinTech projects, induction and deduction methods, which allowed to analyze the behavioral aspects of typical users of Green FinTech projects, products and services of the financial market. Results. The study demonstrated that there are practically no comprehensive studies on the behavioral aspects of the creation and development of Green FinTech projects and products. It was the behavioral approach that made it possible to understand, analyze and predict direct and indirect incentives for the development of such eco-projects, to find the appropriate institutional levers that will ensure the intensive spread of Green FinTech. Based on the analysis of the development trajectories of successful Green FinTech eco-projects, such behavioral aspects of financial market participants as propensity to innovation, propensity to risk, environmental awareness, appropriate financial literacy, ability and readiness to use innovative financial tools and platforms, integration into the digital space were investigated . The key obstacles to the development of Green FinTech were studied: the lack of standardized indicators for measuring the impact on the environment and the sustainability of financial products; regulatory complexities, the missing regulatory framework, technological barriers, the problem of cyber security and confidentiality of customer data, the biased attitude of some consumers towards environmental initiatives. Proposals are made to overcome them and improve the institutional structure of the financial market. Novelty. The work improved the scientific and methodological approach to the analysis of consumer behavior of Green FinTech projects on the financial market, in particular it was scientifically proven that the use of financial services in the field of Green FinTech requires a certain mental, educational and behavioral readiness from the economic subject, which, in turn, requires institutional compliance with the structure of the financial market. Practical value. The practical significance is that the established behavioral aspects, as well as the key obstacles that restrain the development of the Green FinTech field, allow for the formation of a sound strategy for the development of Green FinTech at the micro and macro level.

Impact of financial literacy on financial inclusion and household financial decisions: exploring the role of ICTs

The objective of this paper is to assess the extent of financial literacy and the impact of access to and use of ICTs (information and communication technologies) on household financial decisions, such as savings, retirement planning, household budgeting, and engagement in financial markets. This study analyzes survey data collected from 409 households belonging to the low- and middle-income brackets across four cities in Pakistan. By employing probit model, it finds that a higher level of (advanced) financial literacy is associated with an increased likelihood of improved savings and household budgeting. However, the overall financial literacy score (basic plus advanced) is associated only with savings decision. Additionally, the results reveal that the ICTs adoption plays a role in influencing decisions related to financial market participation and savings. The results also show that financial literacy, along with ICTs, positively influences financial market participation and retirement decisions. Nevertheless, results suggest mixed impacts of financial literacy and ICTs on financial decisions which lends partial support to the study hypotheses. In conclusion, our results underscore the importance of financial literacy alongside ICT adoption to promote financial market participation and improve household financial management.

Predicting stock market crashes on the African stock markets: evidence from log-periodic power law model

PurposeThis study aims to predict stock market crashes identified by the CMAX approach (current index level relative to historical maximum) during periods of global and local events, namely the subprime crisis of 2008, the political and social instability of 2011 and the COVID-19 pandemic.Design/methodology/approachOver the period 2004–2020, a log-periodic power law model (LPPL) has been employed which describes the price dynamics preceding the beginning dates of the crisis. In order to adjust the LPPL model, the Global Search algorithm was developed using the “fmincon” function.FindingsBy minimizing the sum of square errors between the observed logarithmic indices and the LPPL predicted values, the authors find that the estimated parameters satisfy all the constraints imposed in the literature. Moreover, the adjustment line of the LPPL models to the logarithms of the indices closely corresponds to the observed trend of the logarithms of the indices, which was overall bullish before the crashes. The most predicted dates correspond to the start dates of the stock market crashes identified by the CMAX approach. Therefore, the forecasted stock market crashes are the results of the bursting of speculative bubbles and, consequently, of the price deviation from their fundamental values.Practical implicationsThe adoption of the LPPL model might be very beneficial for financial market participants in reducing their financial crash risk exposure and managing their equity portfolio risk.Originality/valueThis study differs from previous research in several ways. First of all, to the best of the authors' knowledge, the authors' paper is among the first to show stock market crises detection and prediction, specifically in African countries, since they generate recessionary economic and social dynamics on a large extent and on multiple regional and global scales. Second, in this manuscript, the authors employ the LPPL model, which can expect the most probable day of the beginning of the crash by analyzing excessive stock price volatility.

Government digital policy breaks the mystery of “limited participation” in China's home finance market

This study uses a two-step approach to construct a multi-period double-difference model and introduces a quasi-natural experiment of the Broadband China pilot policy to investigate whether household financial market participation at the urban level is affected by the digital economy, which is significant for promoting Chinese households' shift from savings to investment and alleviating the long-standing problem of insufficient household financial market participation in China. In terms of direct impact, the digital economy increases the household financial market participation rate of urban residents by 3.26%, and increases the financial market participation rate of highly financially literate households by 2.14%; in terms of indirect impact, the development of the digital economy increases the total number of household smart Internet devices by 8.27%, and similarly increases the attention to household financial information by a significant 4.22%, which further positively influences the household financial market participation rate. This paper also evaluates the individual and regional differences of the digital economy on household financial market participation, and the estimated causal effect of the digital economy on household financial market participation is purer, which expands the scope of research on the digital economy and household financial market participation, and provides a certain reference basis and policy inspiration for the government to promote the construction of the digital economy.

The role of leading financial institutions in the realization of the ESG agenda

Aim. To identify trends and directions of development of ESG-agenda of the Russian banking sector in the new geopolitical environment.Objectives. To analyze the reaction of the Russian banking sector to the promotion of ESGagenda by the West in the pre-sanctions period and the change of priorities after the introduction of large-scale financial and technological sanctions for Russia; to determine the required transformation of business strategies and risk management systems; to propose additional measures of support from the state to increase the priority of sovereign technologies in the implementation of ESG-transformation and the development of a competitive national system of standards.Methods. The authors applied a mixed method of analysis, combining qualitative and quantitative data, to form the empirical base of the study. Content analysis and empirical methods were used to analyze qualitative data. In turn, quantitative data were processed using statistical and logical tools.Results. The conducted research allowed to confirm the effectiveness of ESG-tool in the realization of the concept of sustainable development. It was determined that the significant driving force of ESG-transformation today is mainly large banks. However, the potential of ESG-transformation on the part of banks may be exhausted, and the practical part of fulfillment of plans reflected in their ESG-policies requires additional incentives from the state.Conclusions. Based on the results of the conducted research, it becomes clear that it is necessary to form a competitive Russian sovereign ESG-model, which should include a national regulatory framework, technological standards, and domestic platform IT management systems. Strengthening the work in this direction’ financial market participants are most able to influence the introduction of innovations in the sphere of tools for achieving sustainable development goals (SDGs) and national projects, to take into account national interests in view of ESG-agenda realization, to ensure their development and financing.

A Study of Bayesian Quantile Regression for Forecasting RMB Exchange Rates

Accurate forecasting of the RMB exchange rate is crucial for global financial market participants. This study proposes a Bayesian quantile regression approach to enhance the forecasting method. This paper uses RMB and US dollar exchange rate data from the State Administration of Foreign Exchange from 2018 to 2022 to build a Bayesian quantile regression model and empirically analyze the RMB exchange rate forecast. The results show that the proposed Bayesian quantile regression model yields accurate forecasts, with a root mean squared error (RMSE) of 1.8329 and a mean absolute error (MAE) of 1.2988. Furthermore, robustness and sensitivity analyses confirm the model's reliability. The findings of this study have practical implications for financial market participants and policymakers in managing and responding to foreign exchange risk.

Social trust and risky financial market participation: Evidence from China

ABSTRACT The Chinese government has promoted the development of risky financial markets under the market-oriented reform period. Meanwhile, social trust has changed with institutional transitions. This study investigates the influence of social trust on risky financial market participation in China based on the national longitudinal data of 2014–2018. It also estimates the effects of social trust by education, age, urban/rural hukou resident groups, and periods. The empirical results indicate that social trust positively affects the probability of holding risky financial assets and their shares. However, these effects turn insignificant when accounting for unobservable individual heterogeneity. The positive effect of social trust is more pronounced among the younger generation, highly educated groups, women, and urban hukou residents compared to their counterparts. Additionally, the positive impact of social trust is observed to be stronger in the period following the 2015 stock market crash shock than in the period before 2015.

Central Credit Institution: Forgotten History and Possible Innovations in Modern Conditions

The subject of the study is the historical experience of creating the Central Credit Institution of urban public banks of the Russian Empire and the possibility of its application in modern conditions.The purpose of the study is to develop practical measures to create a special banking association of local banks on the terms formulated by the Bank of Russia for the purpose of discussion with financial market participants, representatives of the expert and scientific community’s.The relevance of the study is due to the request of the Bank of Russia, the Association of Banks of Russia in the search for new approaches to expanding the development potential of local banks through the creation of special banking associations. The United State Archives of the Orenburg Region served as the research location. The research methodology is based on the use of historical and logical analysis methods. The development of the Central Credit Institution of urban public banks at the beginning of the last century was studied in relation to its historical context and various stages of preparation. The surviving justifications, draft constituent documents, draft charter may be of interest when developing specific practical proposals for the creation of a special banking association of modern local banks with them accepting joint liability for each other’s obligations, maintaining partial operational independence and delegating a number of functions to the parent bank. It is concluded that the results of the study can be applied by the Bank of Russia, the Association of Banks of Russia and proactive local banks to develop practical measures for the creation of a special banking association of local banks declared by the Bank of Russia.

Digital skills and household financial asset allocation

This research explores the impact of digital skills on household financial asset allocation using data from China Family Panel Studies spanning 2014 to 2020. The findings demonstrate that digital skills contribute to improved allocation of risky assets. They influence financial market participation by enhancing information acquisition and shaping risk attitudes. Moreover, variations emerge in the effect of digital skills based on urban and rural distinctions and wealth disparities. This study sheds light on the dynamic role of digital skills in shaping household financial behaviors and offers insights into reducing wealth inequality.

Global transformation of crowdfunding model types: Experience for Russia and practical recommendations

Subject. This article examines the issues of development of crowdfunding and the transformation of its model types in world practice and in Russia. Objectives. Based on the analysis of foreign practices, the article aims to trace the evolution of the global transformation of model types of crowdfunding from 2007 to 2023, as well as determine the prospects for the development of crowdfunding in Russia. Methods. For the study, I used the logical and systems approaches, analysis and synthesis, comparative analysis, and classification. Results. The article finds that the number of model types of crowdfunding in the global economy is constantly increasing, which reflects the demand for alternative sources of financing. In the Russian Federation, there are two developed types of crowdfinancing only, namely, the provision of loans and the purchase of equity securities placed using the investment platform. Conclusions and Relevance. In the context of sanctions pressure, the problem of developing own independent crowdfunding platforms is becoming more and more urgent. This will contribute to increasing the level of financial stability and ensure a certain financial sovereignty in attracting and allocating resources. The results can be used by participants in the Russian financial market, public authorities, as well as research and educational organizations when considering options for the development of alternative sources of financing.

Return and Volatility Connectedness in Electronic Warehouse Receipt Market of Turkey

Over the course of the last century, globalization and integration have increased significantly around the world. The rise in economic and financial globalization and integration has increased the connectedness between national economies and financial markets and secured an important place in the systemic risk spillover. It is important to analyze the issue in terms of different markets. Food prices around the world have increased significantly over the last 20 years. The price and volatility increase associated with food products lead to important socioeconomic and social problems. In this context, it will be important for decision-makers to assess the issue from the perspective of financial markets and to understand and reveal the dynamic structure of food commodity markets. This study aims to examine the connectedness of return and volatility in the Electronic Warehouse Receipt (EWR) market, where agricultural commodities are traded in Turkey, and to analyze its dynamic structure that changes over time. In this study, the Diebold-Yilmaz connectedness measurement method based on the forecast error variance decomposition after the VAR (p) model was used to analyze the connectedness between financial assets. According to the results of the static analysis performed, it was observed that while the return connectedness in the EWR market is very low, the volatility connectedness is at a higher level than the return connectedness. Based on the results of the dynamic analysis, no trend was observed in return connectedness; however, rapid increases and decreases were observed for certain periods. On the other hand, while an increasing trend was observed in the dynamic analysis of volatility connectedness, sudden increases and decreases were observed during periods of crisis. Of all agricultural commodities, it was observed that barley was the asset that sent the most net shock into the system. The EWR market in Turkey has come up recently. The market's structure, dynamics, and synchronization with other markets are still at a low level. The spillover effect of return and volatility shocks in the market are also low. The findings of this study can be used by producers, financial market participants and various decision makers for risk management, hedging and profit maximization purposes.

Effect of introduction of German and Hungarian bank levies on banks’ risk-taking behavior

Policymakers introduce bank levies (BLs) to reduce the probability of crises. In this study, we evaluate the effects of the Hungarian and German BLs implemented in 2010 and 2011, respectively, on the banks’ risk-taking behavior. Our analysis compares two completely different BL designs. The German BL is designed to increase as banks’ total liabilities increase, while the Hungarian BL is assessed on total assets. The results unambiguously demonstrate that a BL on assets increases banks’ credit risk. The results of analyzing the influence that introducing BLs has had on the German banking sector demonstrate that BL on liabilities decreases banks’ credit risk. An improved understanding of the impact of regulation on the risky activity of EU banks is very important for a wide range of financial market participants, including borrowers, shareholders regulators and supervisors, especially during turbulent times caused by the COVID-19 pandemic and the Russian war in Ukraine.

Cyclicality of liquidity creation: Nonlinear evidence from US bank holding companies

AbstractUsing a panel smooth transition regression framework on a new proxy of the business cycle (BC) index and quarterly data of US bank holding companies from 1993Q1 to 2020Q1, our results provide empirical support for the theory that the BC has a nonlinear effect on liquidity creation. We find a positive and highly significant nonlinear effect of the BC on liquidity creation, which not only supports the pro‐cyclicality of liquidity creation but also improves the liquidity creation estimation compared to previous studies. The results are robust to different proxies of the BC and model specifications. We also document that US bank holding companies create liquidity more during the expansion phase (normal times) than during the recession phase (crisis times) of the BC, suggesting an asymmetrical effect of BC changes on liquidity creation. Our findings have important implications for financial market participants by suggesting that banks should keep alternative sources of funding on hand during the BC recession phase. Insights from our study also provide policy implications for central banks and prudent supervisors to consider when incentivizing banks, for instance, by lowering regulatory requirements, adjusting the policy rate, or implementing any other quantitative easing policy during the BC recession phase to keep the financial system efficient.

The relationship between geopolitical risks, renewable energy and economic growth in OPEC+ countries

The geopolitical risk (GPR) can be described as the risk connected with some crisis (e.g., wars, terrorist attacks, and conflicts between nations). Besides many other characteristics, OPEC+ countries are prone to risks and uncertainties. According to Bloom (2009) uncertainty is a broader concept that reflects ambiguity in the minds of decision-makers and policymakers about the possible future that spreads across macroeconomic to microeconomic levels. For instance, volatilities in GDP growth and oil prices affect investment decisions, plants' production schedule and individual's consumption habits. Researchers use different proxies of uncertainty that ranges from economic data such as volatility of oil prices, stock markets and GDP to news published in daily papers (Baker, Bloom, and Davis, 2016) since its broader existence implies no specific measures (Bloom, 2009). Extent empirical literature affirms significantly negative effects of uncertainty on the entire economy. Caldara and Iacoviello (2018) have introduced a new-based global uncertainty index, which covers country-specific and region-specific uncertainties measures. They included all words, linked with geopolitical tensions and are exogenous to macroeconomic uncertainties, published in 11 prominent newspapers. This geopolitical risk (GPR) index identified events such as 'Paris assaults', 4 'Iraq invasion', 'tensions during Gulf Wars', and '9/11 WTC attacks in USA'. Geopolitical risks such as wars, terrorist acts, military attacks, or diplomatic conflicts around the world are of major concern to businesses, financial market participants, public media, and policy makers. Considering the novelty and the significance of GPR, we investigate the impacts of geopolitical risks on three key elements of OPEC+ countries that have also global implication: economic growth, oil prices and energy exports. Keywords: Geopolitical risks, , renewable energy, OPEC+ countries.