• International Journal of Computer Science & Network Security
• /
• v.21 no.4
• /
• pp.186-198
• /
• 2021

The introduction of digital technologies affects most socio-economic processes and activities in the economy, from agriculture to public services. Even though the world is currently only in the early stages of digital transformation, the digital economy is growing rapidly, especially in developing countries. Shortly, digital platforms will be able to replace the "invisible hand" of the market and turn it into digital. Some digital platforms have already reached global reach in some sectors of the economy. The growing value of data and artificial intelligence is reflected in the high capitalization of these enterprises. Their growing role has far-reaching consequences for the organization of economic activity and integration into the field of e-business. However, their importance and level of development in different countries differ significantly. The main purpose of this article is an assessment of the level and trends of the digital economy in the world and the identification of homogeneous groups of states following the main trends in the development of its components from among the EU countries. The methodology of the conducted research is based on the use of general scientific research methods in the analysis of secondary sources and the application of statistical methods of correlation-regression and cluster analysis. Macroeconomic indicators and components of DESI (Digital Economy and Society Index) were used for the analysis. Results. Based on the analysis established that most developed countries have a medium level of digitalization of the business environment and a high level of digitalization of socially oriented public services, while countries with lower GDP focus their policies on building digital infrastructure and training qualified personnel. The study summarizes and analyzes current trends in digital technology, analyzes the level and dynamics of integration of digital technologies of the studied EU countries, the level of development of e-business and e-commerce. The conceptualization of mechanisms of creation of added value in the digital economy is offered and the possible consequences of digitalization of the economy of developing countries are generalized.

• Journal of Convergence for Information Technology
• /
• v.11 no.1
• /
• pp.28-33
• /
• 2021

Since the stock price is a measure of the future value of the company, when analyzing the stock price, the company's growth potential, such as sales and profits, is considered and invested in stocks. In order to set the criteria for selecting stocks, institutional investors look at current industry trends and macroeconomic indicators, first select relevant fields that can grow, then select related companies, analyze them, set a target price, then buy, and sell when the target price is reached. Stock trading is carried out in the same way. However, general individual investors do not have any knowledge of investment, and invest in items recommended by experts or acquaintances without analysis of financial statements or growth potential of the company, which is lower in terms of return than institutional investors and foreign investors. Therefore, in this study, we propose a research method to select undervalued stocks by analyzing ROE, an indicator that considers the growth potential of a company, such as sales and profits, and predict the stock price flow of the selected stock through deep learning algorithms. This study is conducted to help with investment.

• The Journal of Asian Finance, Economics and Business
• /
• v.8 no.4
• /
• pp.83-91
• /
• 2021

Health is an outset of psychological, social, financial, and physical state. Several macroeconomic factors are entangled with health and mortality. Infant mortality and life expectancy are two keyguard on demographic research context on last few decades. On the other hand, foreign inflows play an unprecedent role for raising economic circulation and providing more opportunities to build a better society. The study aims to investigate the relationship between foreign direct investment (FDI), economic growth, and Bangladesh's health. This study employs time-series data from 1980 to 2018. Results show, with Auto-regressive Distribute Lag (ARDL) model, that there is significant cointegration among variables. Foreign investment and economic output relate significantly and positively to health. On the contrary, education is quasi-linked with a different sign-on different model. For model validation, pitfalls of time-series multicollinearity, heteroscedasiticy, and autocorrelation are not present. Also, CUSUM and CUSUMSQ tests are validating the model as stable and fit for future prediction. Medical assessment and education need more attention from the government as well as the private sector. FDI can play a catalyst role for improving the health sector, raising opportunity in educating and creating a better lifestyle. In order to optimize foreign investment, the government should implement necessary reforms and policies.

• The Journal of Asian Finance, Economics and Business
• /
• v.8 no.7
• /
• pp.55-66
• /
• 2021

The purpose of this study is to analyze the relationship and effects of variables both directly and indirectly (e.g., investment (INV), government expenditure (GE), unemployment rate (UR), economic growth (EG), and income inequality). The analytical phases consist, first, to transform the data using the Log Natural (Ln) method. Second, to check normality and multicollinearity of data. Third, to test direct effects of variables (government expenditure and investment effect on the unemployment rate and economic growth; investment on government expenditure; economic growth on unemployment rate; economic growth and unemployment rate on income inequality). Fourth, to test indirect effects using Sobel test, which involves UR and EG as intervening variable. Fifth, to test hypotheses with p-value < 0.05. The results of the study reveal that, of the 12 relationships, statistics show that 11 variations of the association have significant positive and negative effects. Theoretically, the different characters and goals of GE and INV in each country will have a different impact on EG and UR goals. The study provides an input, especially for the government. To create optimal EG through GE and INV, it is necessary to allocate budgets to industrial sectors that can absorb a massive labor force and to new economic growth sectors.

• The Southeast Asian review
• /
• v.27 no.4
• /
• pp.117-159
• /
• 2017

This study analyzed the driving factors of the enlargement process of ASEAN member countries from 1995 to 1999. The main research question is how can it explain the difference in the decision-making timing of countries wishing to join regional cooperation. This study focuses on why the countries that did not join ASEAN in the early years of ASEAN membership, since the mid - 1990s, and why they joined the different periods since the end of the Cold War. To this end, this study analyzed the accession process of Vietnam, Laos, Myanmar and Cambodia. The main argument of the study is that there is a time gap in the accession of ASEAN, but ultimately the regional cooperation is used to secure the legitimacy of maintaining the system. Most of the previous studies on the expansion of regional cooperation have discussed the expansion of regional cooperation in terms of macroeconomic changes such as international system change. However, this study focuses on the domestic political and economic situation of motivating individual member countries to join regional cooperation and this is complemented by a micro approach.

• The Journal of the Convergence on Culture Technology
• /
• v.7 no.1
• /
• pp.511-517
• /
• 2021

In this paper, we analyzed the impact of capital adequacy requirements on the profitability of Korean banks using DOLS model. As a result of the analysis, the impact of BIS capital ratios on commercial and regional banks was different. Demand for capital adequacy has a greater and more significant negative impact on regional banks than on commercial banks. It was shown that bank characteristic variables rather than macroeconomic variables have a more significant effect on bank profitability. In addition, a rise in the BIS capital ratio reduces the profitability of commercial and regional banks, and the higher the ratio of loan-loss provisions, the stronger the relationship. In the case of commercial banks, it is estimated that the demand for capital adequacy did not have a significant impact as they are relatively large and faithful in capital compared to regional banks. However, in the case of regional banks, safer assets need to be selected to meet the BIS capital ratio, and the increasing propotion of these safe assets seems to have a relatively greater negative impact on profitability. Consequency, the financial authorities should consider this results and implement the bank's capital regulation policy.

• Journal of Korea Society of Industrial Information Systems
• /
• v.25 no.6
• /
• pp.95-107
• /
• 2020

We analyze the performance of South Korea wholesalers and retailers during the period when COVID-19 emerged and began to spread in South Korea. Specifically, we choose operational efficiency as a proxy variable for reflecting corporate performance and apply stochastic frontier analysis for estimating operational efficiency. Importantly, in order to examine the impact of the COVID-19 period (Q1 to Q2 2020) on operational efficiency, we consider the quarterly fixed effect corresponding to the COVID-19 period. Our findings include: (ⅰ) the average level of operational ffficiency is approximately 0.7138 during the analysis period (Q1 2019 to Q2 2020); (ⅱ) the fixed effect of the COVID-19 period on operational efficiency is not significant; and (ⅲ) operational efficiency is positively correlated with the scale of the company. Moreover, from an academic perspective, we make a contribution by examining the relationship between the operational efficiency as a firm-level variable and the COVID-19 period as a macroeconomic variable.

• Journal of the Korea Society for Simulation
• /
• v.30 no.1
• /
• pp.75-85
• /
• 2021

In this paper, we present a deep neural network-based prediction model that processes and analyzes the corporate credit and personal credit information of individual business owners as a new method to predict the default rate of individual business more accurately. In modeling research in various fields, feature selection techniques have been actively studied as a method for improving performance, especially in predictive models including many features. In this paper, after statistical verification of macroeconomic indicators (macro variables) and credit information (micro variables), which are input variables used in the default rate prediction model, additionally, through the credit information feature selection method, the final feature set that improves prediction performance was identified. The proposed credit information feature selection method as an iterative & hybrid method that combines the filter-based and wrapper-based method builds submodels, constructs subsets by extracting important variables of the maximum performance submodels, and determines the final feature set through prediction performance analysis of the subset and the subset combined set.

• The Journal of the Convergence on Culture Technology
• /
• v.8 no.1
• /
• pp.435-440
• /
• 2022

This study analyzed the impact of changes in real estate prices on the soundness of Korean banks using multiple regression models. As a result of the analysis, changes in real estate prices significantly increase the banks' non-performing loans through the increase in loans. Among macroeconomic variables, short-term interest rates were found to have a significant effect on all soundness indicators such as BIS capital adequacy ratio, non-performing loans ratio, and liquidity coverage ratio. Among the bank characteristics indicators, the loan growth rate had a significant negative effect on BIS capital adequacy ratio, and the real estate mortgage rate had a significant positive effect. In additional, it was found that non-performing loans ratio and liquidity coverage ratio had a negative effect on BIS capital adequacy ratio.

• The Korean Journal of Applied Statistics
• /
• v.35 no.1
• /
• pp.49-62
• /
• 2022

Realized volatility is well known to have long memory, strong association with other global financial markets and interdependences among macroeconomic indices such as exchange rate, oil price and interest rates. This paper proposes autoencoder factor-augmented heterogeneous autoregressive (AE-FAHAR) model for realized volatility forecasting. AE-FAHAR incorporates long memory using HAR structure, and exogenous variables into few factors summarized by autoencoder. Autoencoder requires intensive calculation due to its nonlinear structure, however, it is more suitable to summarize complex, possibly nonstationary high-dimensional time series. Our AE-FAHAR model is shown to have smaller out-of-sample forecasting error in empirical analysis. We also discuss pre-training, ensemble in autoencoder to reduce computational cost and estimation errors.