• Journal of information and communication convergence engineering
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• v.19 no.4
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• pp.228-233
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• 2021

In this study, we analyze the credit information (loan, delinquency information, etc.) of individual business owners to generate voluminous training data to establish a bankruptcy prediction model through a partial synthetic training technique. Furthermore, we evaluate the prediction performance of the newly generated data compared to the actual data. When using conditional tabular generative adversarial networks (CTGAN)-based training data generated by the experimental results (a logistic regression task), the recall is improved by 1.75 times compared to that obtained using the actual data. The probability that both the actual and generated data are sampled over an identical distribution is verified to be much higher than 80%. Providing artificial intelligence training data through data synthesis in the fields of credit rating and default risk prediction of individual businesses, which have not been relatively active in research, promotes further in-depth research efforts focused on utilizing such methods.

• The Journal of Asian Finance, Economics and Business
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• v.9 no.7
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• pp.197-203
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• 2022

The agricultural sector has an important contribution to the economic development of Vietnam in particular and other countries in general. The growth of enterprises in the industry is an important bridge in promoting the economic development of the country. Currently, the policies of the Government of Vietnam always create favorable conditions for enterprises to conduct business, especially enterprises in the agricultural sector. The study aims to assess factors influencing the profitability of listed firms in Vietnam's stock market. Using 40 enterprises in the agricultural industry listed on the Ho Chi Minh City Stock Exchange and the Hanoi Stock Exchange and using advanced econometric modeling, dealing with defects in the regression model, the research results show that large-scale firm has higher economic efficiency than small-scale firm. In addition, a firm with higher use of loan capital is associated with a more efficient firm, reflected in the relatively good debt management ability of enterprises in the agricultural sector. Adversely, growth and age do not have any impact on firm performance. Macroeconomic factors do not impact profitability. Finally, the study has some policy implications for developing agricultural businesses in the case of Vietnam.

• The Journal of Industrial Distribution & Business
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• v.9 no.5
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• pp.63-72
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• 2018

Purpose - This work analyzes, in detail, the specification of vector error correction model (VECM) and thus examines the relationships and impact among seven economic variables for USA - balance on current account (BCA), index of stock (STOCK), gross domestic product (GDP), housing price indices (HOUSING), a measure of the money supply that includes total currency as well as large time deposits, institutional money market funds, short-term repurchase agreements and other larger liquid assets (M3), real rate of interest (IR_REAL) and household credits (LOAN). In particular, we search for the main explanatory variables that have an effect on stock and real estate market, respectively and investigate the causal and dynamic associations between them. Research design, data, and methodology - We perform the time series vector error correction model to infer the dynamic relationships among seven variables above. This work employs the conventional augmented Dickey-Fuller (ADF) and Phillips-Perron (PP) unit root techniques to test for stationarity among seven variables under consideration, and Johansen cointegration test to specify the order or the number of cointegration relationship. Granger causality test is exploited to inspect for causal relationship and, at the same time, impulse response function and variance decomposition analysis are checked for both short-run and long-run association among the seven variables by EViews 9.0. The underlying model was analyzed by using 108 realizations from Q1 1990 to Q4 2016 for USA. Results - The results show that all the seven variables for USA have one unit root and they are cointegrated with at most five and three cointegrating equation for USA. The vector error correction model expresses a long-run relationship among variables. Both IR_REAL and M3 may influence real estate market, and GDP does stock market in USA. On the other hand, GDP, IR_REAL, M3, STOCK and LOAN may be considered as causal factors to affect real estate market. Conclusions - The findings indicate that both stock market and real estate market can be modelled as vector error correction specification for USA. In addition, we can detect causal relationships among variables and compare dynamic differences between countries in terms of stock market and real estate market.

• Journal of Distribution Science
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• v.13 no.11
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• pp.39-46
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• 2015

Purpose - In Korea, there has been a recent trend that shows housing prices have risen rapidly following the International Monetary Fund crisis. The rapid rise in housing prices is spreading recognition of this as a factor in housing price volatility. In addition, this raises the expectations of housing prices in the future. These expectations are based on the assumption that a relationship exists between the current housing prices and expected housing prices in the real estate industry. By performing an empirical analysis on the validity of the claim that an increase in current housing prices can be correlated with expected housing prices, this study examines whether a long-term equilibrium relationship exists between expected housing prices and existing housing prices. If such a relationship exists, the recovery of equilibrium from disequilibrium is analyzed to derive related implications. Research design, data, and methodology - The relationship between current housing prices and expected housing prices was analyzed empirically using the Vector Error Correction Model. This model was applied to the co-integration test, the long-term equilibrium equation among variables, and the causality test. The housing prices used in the analysis were based on the National Housing Price Trend Survey released by Kookmin Bank. Additionally, the Index of Industrial Product and the Consumer Price Index were also used and were obtained from the Bank of Korea ECOS. The monthly data analyzed were from January 1987 to May 2015. Results - First, a long-term equilibrium relationship was established as one co-integration between current housing price distribution and expected housing prices. Second, the sign of the long-term equilibrium relationship variable was consistent with the theoretical sign, with the elasticity of housing price distribution to expected housing price, the industrial production, and the consumer price volatility revealed as 1.600, 0.104,and 0.092, respectively. This implies that the long-term effect of expected housing price volatility on housing price distribution is more significant than that of the industrial production and consumer price volatility. Third, the sign of the coefficient of the error correction term coincided with the theoretical sign. The absolute value of the coefficient of the correction term in the industrial production equation was 0.006, significantly larger than the coefficients for the expected housing price and the consumer price equation. In case of divergence from the long-term equilibrium relationship, the state of equilibrium will be restored through changes in the interest rate. Fourth, housing-price volatility was found to be causal to expected housing price, and was shown to be bi-directionally causal to industrial production. Conclusions - Based on the finding of this study, it is required to relieve the association between current housing price distribution and expected housing price by using property taxes and the loan-to-value policy to stabilize the housing market. Further, the relationship between housing price distribution and expected housing price can be examined and tested using a sophisticated methodology and policy variables.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.12
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• pp.377-384
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• 2020

Banking is very regulated by the government and even has to follow regulations issued by the Basel Committee on Banking Supervision, which regulates banking in the world. According to Basel III, banks must provide capital reserves called capital buffers. The purpose of this study is to examine the factors that determine capital buffer. Factors thought to affect the capital buffer studied consisted of profitability (ROA), credit risk (NPL), liquidity risk (LDR), capital adequacy in the previous period (CARt-1), management risk (NIM), and ratio of operating risk (OER). The population in this study is conventional banks listed on the Indonesia Stock Exchange, as many as 42 banks, with a sample of 40 banks taken by purposive sampling method with an observation period of four years with quarterly data (2016-2019). To test the hypotheses, regression panel data is used. After being tested, it turns out that the fixed effect model is better than the common effect and random effect. The results of the study with fixed effect models show that ROA, NPL, and OER significantly and negatively affect capital buffer. CAR_t-1 has a positive and significant effect on capital buffer, while LDR and NIM do not affect capital buffer.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.6
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• pp.39-46
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• 2020

Playing an important role in developing the economy and overall developments of the country, commercial banks have to be aware of their crucial presence in order to perform well and contribute significantly. At the same time, as a place to receive deposits, banks are required to be in safe situations to avoid bankruptcy or deal with financial crises. This research seeks to identify the determinants of Capital Adequacy Ratio and Banks' performance as well as the relationship between these two dependent variables. The paper uses 128 observations of 16 Vietnamese commercial banks during the period from 2010 to 2017, with two simultaneous dependent variables CAR and ROE, and independent variables including Return on Assets, Tobin Q, Credit growth, GDP growth, Equity to Deposits, Loans to Deposits, Bank size, Cost to Income, Liquidity risk, Provision for Loan loss ratio, Non-performing loans and Inflation. The results reveal that Capital Adequacy Ratio and Banks' Performance have statistically significant relationship and Credit growth, GDP growth, Equity-to-Deposit ratio and Cost-to-Income ratio all have significant effects on two dependent variables. The findings of this study suggest that commercial banks should control the respective elements in order to maintain adequate level of capital and also create effective performance.

• Land and Housing Review
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• v.9 no.1
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• pp.1-9
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• 2018

As the government announced Real Estate Policies on August 02, most areas except for Seoul cities face increasing business risks. Moreover, the government control over financial sectors' loan leads to the highly possible contraction of new distribution markets. The market trend could bring about the reduction of new demand in PF (Private Financing) business that large construction companies mainly concentrate on, and even the business already obtained has a high risk of being distributed, which could result in substantially low profitability. The currently unstable financial structure of most construction companies is caused by the hike of the prime cost of foreign plants except for that of a few construction companies. If PF (Private Financing) business also faces a difficult situation in such a financial condition, even large construction companies come to have the high possibility of a deficiency in credit rating. Accordingly, the major business that large construction companies concentrate on needs the sufficient business review. It is desirable to make a bid for business guaranteeing stability rather than business solely in consideration of profitability, when participating in a competition for a new construction contract.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.3
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• pp.127-135
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• 2020

The paper aims to examine whether business cycles affect the link between financial development and bank risk, measured by Zscore and non-performing loans to total loans in six Southeast Asian countries, namely Indonesia, Philippines, Malaysia, Singapore, Thailand and Vietnam. This study uses a sample of 95 listed commercial banks over a 15-year period between 2004 and 2018 in the six Southeast Asian countries. This study employs panel OLS regression and modifications to tackle issues such as endogeneity and heteroscedasticity. The results show that the impact of stock market development (the ratio of the market capitalization to GDP) on Zscore is significantly positive, whereas its effect on non-performing loans is significantly negative. The findings suggest that financial development, in terms of stock market capitalization, improves banks' Zscores and reduces their level of non-performing loans, suggesting that financial development on average reduces bank risk. The impact of business cycle is insignificant towards bank risk, thus rejecting both counter- and pro-cyclical hypotheses, except for the case of risk indicator of loan loss provisions. Examining the joint effect of the business cycle and financial development on bank risk, we find that the phase of business cycles generally does not moderate the link between financial development and bank risk.

• Asian Journal of Business Environment
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• v.10 no.1
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• pp.37-43
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• 2020

Purpose: The purpose of this study was to examine the relationship between portfolio quality and financial sustainability of microfinance institutions in Kenya. Research Design, Data, and Methodology: The analysis was based on a panel dataset of 30 microfinance institutions for the period of 2010 to 2018. Data was obtained from the Microfinance information exchange (MIX) database, and it was analyzed through descriptive and inferential statistics with the aid of STATA. Based on the results of the Hausman test, the study adopted the fixed effect regression model to test the research hypothesis. Results: The study found that portfolio quality had a positive significant effect on financial sustainability of Microfinance institutions in Kenya (β= 0. 211; p-value < 0.05). For the control variables; firm age had a positive effect (β= 0.773; p-value <0.05), while firm size (β= -0. 749; p-value < 0.05) had a negative effect on financial sustainability. Conclusions: The study concluded that portfolio quality has an important influence on the financial sustainability of microfinance institution. The study recommends that managers of microfinance institutions should devise good collection policies to improve portfolio quality while lessening loan default rate. The portfolio quality may improve the overall profitability and enhance investor confidence in their strategic decision-making on refinancing.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.9
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• pp.351-362
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• 2020

This research investigates the credit management guidelines to strengthen Thai industrial sector. The research has been simulated from the findings of both qualitative and quantitative of 500 questionnaires distributed to industrial business executives in Thailand. The data were analyzed by descriptive analysis categorized into SME and large enterprises, and SEM to conduct the model in consistent with the empirical data. The results show that: (1) the credit management guidelines consist of 4 factors: a) characteristics management b) financial management c) operations management and d) assets management. The business executives gave overall importance on the guidelines at a high level with an average of 3.86. (2) The development of SEM shows that the model fits with the empirical data at Chi-Square probability level = 0.084, CMIN/DF = 1.164, GFI = 0.965 and RMSEA = 0.018. (3) The characteristics management directly influences the financial management and the operation management. The financial management directly influences on the assets management. The assets management has direct influence on the operations management. The findings show that the characteristics management is the essential starting component in SEM and the financial management factor has the most influence in the assets management variable with standard regression weight of 0.990.