• Industrial Engineering and Management Systems
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• v.12 no.4
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• pp.406-415
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• 2013

The present study examines a set of financial ratios in predicting the up or down movements of stock prices in the context of a securities law, the Sarbanes-Oxley Act of 2002 (SOA), controlling for macroeconomic variables. Using the logistic regression with proxy betas to alleviate the incompatibility problem between the firm-specific financial ratios and macroeconomic indicators, we report evidence that financial ratios are meaningful predictors of stock price changes, which subdue the influence of macroeconomic indicators on stock returns, and more importantly that the SOA truly improves the stock price predictability of financial ratios for the markup sample. The empirical results further suggest that industry and time effects exist and that for the markdown sample the SOA actually deteriorates the predictive power of financial ratios.

• KDI Journal of Economic Policy
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• v.38 no.3
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• pp.53-77
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• 2016

Financial soundness in the household sector matters for financial stability and for the real economy. The level of household debt in Korea raises concern about the financial soundness of the household sector due to its size, growth rate and quality. Against this backdrop, we assess the financial vulnerability of borrowers based on an analysis of credit bureau (CB) data, in which the actual credit activities of most individuals are recorded at a high frequency in Korea. We construct over-indebtedness indicators from the CB data and then assess the predictability of forthcoming defaults. Based on the over-indebtedness indicators, we show how borrowers are distributed in terms of over-indebtedness and how the over-indebted differ from average borrowers in terms of their characteristics. Furthermore, we show how the aggregate credit risk in the household sector would change under macroeconomic distress by analyzing how each borrower's credit quality would be affected by adverse shocks. The findings of this paper may contribute to assessing household debt vulnerability and to enhancing regulatory and supervisory practices for financial stability.

• Journal of Information Technology Services
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• v.19 no.2
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• pp.109-124
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• 2020

Facing the 4^th Industrial Revolution era, researches on artificial intelligence have become active and attempts have been made to apply machine learning in various fields. In the field of finance, Robo Advisor service, which analyze the market, make investment decisions and allocate assets instead of people, are rapidly expanding. The stock price prediction using the machine learning that has been carried out to date is mainly based on the prediction of the market index such as KOSPI, and utilizes technical data that is fundamental index or price derivative index using financial statement. However, most researches have proceeded without any explicit verification of the prediction rate of the learning data. In this study, we conducted an experiment to determine the degree of market prediction ability of basic indicators, technical indicators, and system risk indicators (AR) used in stock price prediction. First, we set the core parameters for each financial indicator and define the objective function reflecting the return and volatility. Then, an experiment was performed to extract the sample from the distribution of each parameter by the Markov chain Monte Carlo (MCMC) method and to find the optimum value to maximize the objective function. Since Robo Advisor is a commodity that trades financial instruments such as stocks and funds, it can not be utilized only by forecasting the market index. The sample for this experiment is data of 17 years of 1,500 stocks that have been listed in Korea for more than 5 years after listing. As a result of the experiment, it was possible to establish a meaningful trading strategy that exceeds the market return. This study can be utilized as a basis for the development of Robo Advisor products in that it includes a large proportion of listed stocks in Korea, rather than an experiment on a single index, and verifies market predictability of various financial indicators.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.12
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• pp.19-29
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• 2021

This study aims to measure financial inclusion and examine its impact on income inequality in a panel of 18 Asian countries over the period 1997-2017. Two alternative approaches for developing financial inclusion index are used: one approach following the methodology of Sarma (2008), while the other is the Dynamic Factor Model (DFM)-based index. The impact of individual indicators and index of financial inclusion on inequality in income is analyzed. The Generalized Method of Moment (GMM) approach is used for empirical analysis. The results indicate that micro-level financial inclusion has a weak negative and statistically significant impact on income inequality. Macro-level index and all individual indicators of financial inclusion do not affect income inequality in the selected sample of economies. The income inequality issues have different natures and cannot be fixed by financial inclusion only. It needs holistic structural reforms to enable fair distribution of income and make an equitable financial system. Financial inclusion is a relatively less important intervention tool regarding fixing the issue of income inequality. This is one of the first studies that used the DFM method for financial inclusion indices construction.

• East Asian Journal of Business Economics (EAJBE)
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• v.12 no.2
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• pp.1-7
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• 2024

Purpose: This study delves into the application of the Ohlson 1995 valuation model, particularly addressing the intricacies of the "Other information" variable. Our goal is to pinpoint the most suitable variables for substitution within this category, focusing specifically on the Mongolian Stock Exchange (MSE) context. Research design, data, and methodology: Employing data spanning from 2012 to 2022 from 60 MSE-listed companies, we conduct a comprehensive analysis encompassing both financial and non-financial indicators. Through meticulous examination, we aim to identify which variables effectively substitute for the "Other information" component of the Ohlson model. Results: Our findings reveal significant outcomes. While all financial variables within the model exhibit importance, certain non-financial indicators, notably the company's level and state ownership participation, emerge as particularly influential in determining stock prices on the MSE. Conclusions: This study not only contributes to a deeper understanding of valuation dynamics within the MSE but also provides actionable insights for future research endeavors. By refining key variables within the Ohlson model, this research enhances the accuracy and efficacy of financial analysis practices. Moreover, the implications extend to practitioners, offering valuable insights into the determinants of stock prices in the MSE and guiding strategic decision-making processes.

• Journal of Korea Trade
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• v.23 no.7
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• pp.113-127
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• 2019

Purpose - This paper investigates whether financial crises could be the indicators of capital outflow waves or vice versa in Korea. Korea has experienced two severe financial crises, which are the Asian Crisis and the global financial crisis. Although there were many variables associated with these two remarkable events, one notable variable was gross capital outflows, which had significantly increased around them. Motivated by existing literature which built theoretical frameworks explaining the relationship between capital flight and financial crises, we examine the empirical evidence for this relationship. Design/methodology - We use panel data from 61 countries including Korea from 1980 to 2009 to study the associations between capital flight and diverse financial crises such as banking, currency, debt, and inflation crises. To be specific, we use the complementary log-log model to see whether capital outflow waves are reliable indicators for domestic financial crises. Findings - The results show, first, that banking, currency, and inflation crises are associated with capital flight. Second, debt crises are also associated with capital flight, but the result is not robust to different specifications. And, third, the positive associations between capital flight and crises are mainly driven by banking flows rather than FDI and portfolio flows. Originality/value - This paper is one of a few studies that investigates domestic (not foreign) investors' behavior during financial turmoil. Furthermore, theoretical studies which provide contradictory explanations on the movements of gross capital outflows during financial crises emphasizes the importance of empirical evidence in this paper.

• International journal of advanced smart convergence
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• v.11 no.1
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• pp.101-110
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• 2022

The purpose of this study is to evaluate the efficiency of financial support for rural industry revitalization in eastern China. Comparative analysis of the efficiency of provincial financial support for rural industrial revitalization in eastern China can provide reference for various provinces to formulate financial policies for rural revitalization. In the research process, 5 evaluation indicators were selected using the panel data of the 2016-2021 "China Financial Statistical Yearbook" and "China Statistical Yearbook", and the DEA and Malmquist index methods were used for calculation. The results show that the average efficiency of financial support for rural revitalization in the 10 eastern provinces from 2015 to 2020 was generally higher, with the efficiency values all higher than 0.8, and reached 0.908 in 2017. The comprehensive efficiency of financial support for rural industry revitalization in Tianjin, Shanghai and Hainan has reached the best. From 2015 to 2020, the total factor productivity of financial support for rural industry revitalization in the eastern region has a "V"-shaped fluctuation. Total factor productivity has the fastest growth. The provinces are Beijing, Hebei and Shandong showing negative growth. It is recommended that relevant provinces improve their strategies for financial support for the revitalization of rural industries. The scope of future research should be expanded to most areas of China and the evaluation indicators should be optimized.

• Journal of Distribution Science
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• v.13 no.10
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• pp.5-13
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• 2015

Purpose - This study aims to suggest appropriate policies and performance indicators for financial aid recipients. It analyzes the existing regular government policy funds support project, especially its propriety and reasonability. Research design, data, and methodology - When financial aid is effective, it should be able to predict small enterprise business results. Additionally, there should be an evaluation, checking before and after performance rates so that the rate of achievement and outcome can be measured. This study's contribution for small enterprises is in researching the best way to improve this support system. Results - The Small Enterprise and Market Service (SEMAS), currently designated as a support organization for implementing the government financial aid project, has assessment indicators. However, these focus mainly on quantitative indicators and survey results. Conclusions - In the future, there is some need to draw up measures, setting the right direction for developing policies for the small enterprise fund loans and improving the management of the plans. Eventually, this effort will dispel concerns about the present support policy, which is considered to be weakening small enterprises.

• Health Policy and Management
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• v.12 no.3
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• pp.54-76
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• 2002

This study investigated how much EVA which evaluate firm's value can explain hospital bankruptcy prediction as a explanatory variable including financial indicators in Korea. In this study, artificial neural network and logit regression which are traditional statistical were used as the model for bankruptcy prediction. Data used in this study were financial and economic value added indicators of 34 bankrupt and -:4 non-bankrupt hospitals from the Database of Korean Health Industry Development Institute. The main results of this study were as follows: First, there was a significant difference between the financial variable model including EVA and the financial variable model excluding EVA in pre-bankruptcy analysis. Second, EVA could forecast bankruptcy hospitals up to 83% by the logistic analysis. Third, the EVA model outperformed the financial model in terms of the predictive power of hospital bankruptcy. Fourth, The predictive power of neural network model of hospital bankruptcy was more powerful than the legit model. After all the result of this study will be useful to future study on EVA to evaluate bankruptcy hospitals forecast.

• Journal of Distribution Science
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• v.21 no.3
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• pp.71-82
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• 2023

Purpose: This study examines the distribution of income diversification in improving the financial sustainability of private universities amidst difficulties in operational funding during the Covid-19 pandemic with IT Capability moderation. Research design, data and methodology: Closed survey aimed at 468 financial sector leaders from 189 private universities in ten provinces in Indonesia. Results: All income diversification activity variables have a significant positive effect on financial sustainability. In the analysis of liquidity indicators, there are two activities that have a significant positive effect, namely goods and services (β=0.337) and profitable financial management (β=0.124). Furthermore, the results of the solvency indicator test obtained significant positive results in Goods and Services Activities (β=0.337), Commercial Intellectuals (β=0.161), Commercial Contracts (β=0.103), and Profitable Financial Management (β=0.147). The results of the test of higher education growth indicators on three activities have a significant positive effect, namely Goods and Services (β = 0.290), Endowments (β = 0.158), and Commercial Contracts (β = 0.134). The results of the moderation test conclude that IT Capability strengthens the effect of income diversification on financial sustainability. Conclusion: The results of the study as a recommendation for private universities in developing income diversification with information system technology-based management.