• Journal of Intelligence and Information Systems
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• v.26 no.1
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• pp.135-149
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• 2020

Artificial intelligences are changing world. Financial market is also not an exception. Robo-Advisor is actively being developed, making up the weakness of traditional asset allocation methods and replacing the parts that are difficult for the traditional methods. It makes automated investment decisions with artificial intelligence algorithms and is used with various asset allocation models such as mean-variance model, Black-Litterman model and risk parity model. Risk parity model is a typical risk-based asset allocation model which is focused on the volatility of assets. It avoids investment risk structurally. So it has stability in the management of large size fund and it has been widely used in financial field. XGBoost model is a parallel tree-boosting method. It is an optimized gradient boosting model designed to be highly efficient and flexible. It not only makes billions of examples in limited memory environments but is also very fast to learn compared to traditional boosting methods. It is frequently used in various fields of data analysis and has a lot of advantages. So in this study, we propose a new asset allocation model that combines risk parity model and XGBoost machine learning model. This model uses XGBoost to predict the risk of assets and applies the predictive risk to the process of covariance estimation. There are estimated errors between the estimation period and the actual investment period because the optimized asset allocation model estimates the proportion of investments based on historical data. these estimated errors adversely affect the optimized portfolio performance. This study aims to improve the stability and portfolio performance of the model by predicting the volatility of the next investment period and reducing estimated errors of optimized asset allocation model. As a result, it narrows the gap between theory and practice and proposes a more advanced asset allocation model. In this study, we used the Korean stock market price data for a total of 17 years from 2003 to 2019 for the empirical test of the suggested model. The data sets are specifically composed of energy, finance, IT, industrial, material, telecommunication, utility, consumer, health care and staple sectors. We accumulated the value of prediction using moving-window method by 1,000 in-sample and 20 out-of-sample, so we produced a total of 154 rebalancing back-testing results. We analyzed portfolio performance in terms of cumulative rate of return and got a lot of sample data because of long period results. Comparing with traditional risk parity model, this experiment recorded improvements in both cumulative yield and reduction of estimated errors. The total cumulative return is 45.748%, about 5% higher than that of risk parity model and also the estimated errors are reduced in 9 out of 10 industry sectors. The reduction of estimated errors increases stability of the model and makes it easy to apply in practical investment. The results of the experiment showed improvement of portfolio performance by reducing the estimated errors of the optimized asset allocation model. Many financial models and asset allocation models are limited in practical investment because of the most fundamental question of whether the past characteristics of assets will continue into the future in the changing financial market. However, this study not only takes advantage of traditional asset allocation models, but also supplements the limitations of traditional methods and increases stability by predicting the risks of assets with the latest algorithm. There are various studies on parametric estimation methods to reduce the estimated errors in the portfolio optimization. We also suggested a new method to reduce estimated errors in optimized asset allocation model using machine learning. So this study is meaningful in that it proposes an advanced artificial intelligence asset allocation model for the fast-developing financial markets.

• Korean Management Science Review
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• v.31 no.3
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• pp.1-12
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• 2014

This study suggests the two types DEA models such as DEA CCR model and Super Efficiency model to evaluate the value of a company and to apply them for the investments. 14 kinds of real data of companies such as EV/EBITDA, EPS growth rate, PCR, PER, dividend yield, PBR, stock price/net current asset, debt ratio, current ratio, ROE, operating margin, inventory turnover, accounts receivable turnover, and sales growth ratio were used as input variables of DEA models. 12 year data from December 30, 2000 up to December 30, 2012 were collected, and the data with negative, missing and 0 values were removed reflecting the characteristics of the DEA. In order to verify the effectiveness of the models, we compared the historical variability and rate of return of both models those of the market. Study results are as follows. First, two DEA models are more stable than market in terms of rate of return because the historical variability of both models are less than that of market. Second, Super Efficiency model is more stable than CCR model. Lastly, the cumulative rate of return of Super Efficiency model (434%) is greater than that of the CCR model (420%) and that of the market (269%).

• The Journal of Asian Finance, Economics and Business
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• v.8 no.5
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• pp.287-292
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• 2021

The article analyzes the impact of capital structure on the firm value of chemical companies listed on the stock market of Vietnam. Data was collected from the financial statements of 23 chemical firms listed on the Vietnam stock market from 2012 to 2019. Quantitative research method with regression model according to OLS, FEM, REM method is used; FGLS method is used to overcome the model's defects. In this research, firm value (Tobin's Q) is a dependent variable. Capital structure (DA), Return on assets (ROA), Asset turnover (AT), fixed assets (TANG), Solvency (CR), Firm size (SZ), Firm Age (AGE), and revenue growth rate (GR) are independent variables in the study. The analysis results show that the capital structure of firms in the chemical industry listed on the Vietnam stock market has an inverse correlation with firm value. Besides, firms with greater asset turnover, business size, and number of years of operation have lower firm value. This article helps corporate executives improve corporate value by adjusting their capital structure properly. Chemical firms adjusted their capital structure in the direction of gradually decreasing the debt ratio and gradually increasing equity. Firms use high debt, which has the effect of reducing the firm value of firms in the chemical industry.

• Health Policy and Management
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• v.18 no.2
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• pp.19-38
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• 2008

Financial ratios are key indicators of an organization's financial and business conditions. Among various financial indicators, profitability, financial structure, financial activity and liquidity ratios are frequently used and analyzed. Using the structural equation modeling(SEM) technique, this study examines the structural causal relationships among key financial indicators. Data for this study are taken from complete financial statements from 142 hospitals that passed the standardization audit undertaken by the Korean Hospital Association from 1998 to 2001 for the purpose of accrediting teaching hospitals. In order to improve comparability, ratio values are standardized using the Blom's normal distribution. The final model of the SEM has four latent constructs: financial activity(total asset turnover, fixed asset turnover), liquidity(current ratio, quick ratio, collection period), financial structure(total debt to equity, long-term debt to equity, fixed assets to fund balance), and profitability(return on assets, normal profit to total assets, operating margin to gross revenue, normal profit to gross revenue). While examining several model fit indices(Chi-square (df) = 178.661 (40), likelihood ratio=4.467, RMR=.11, GFI=.849, RMSEA=.157), the final SEM we employed shows a relatively good fit. After examining the path coefficient of the constructs, the financial structure of the hospital affects the hospital's profitability in a statistically significant way. A hospital which utilizes its liabilities, more specifically fixed liabilities, and makes a stable investment decision for fixed assets was found to have a higher profitability than other hospitals. Then, the standard path coefficients were examined to directly compare the influence of variables. It was found that there were no statistically significant path coefficients among constructs. When it comes to variables, however, statistically significant relationships were found. between. financial activity and. fixed. asset turnover, and between profitability and normal profit to gross revenue. These results show that the observed variables of fixed asset turnover and normal profit to gross revenue can be used as indicators representing financial activity and profitability.

• Journal of the Korea Society for Simulation
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• v.33 no.1
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• pp.27-34
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• 2024

This study aims to propose an optimal asset allocation that minimizes the risk of insufficient realized replacement rates compared to the OECD average replacement rate. To do this, we set the shortfall risk of replacement rates and calculates an asset allocation plan to minimize this risk based on the period of enrollment, the income level and additional contribution. We consider stocks and deposits as investment assets, using Monte Carlo simulation with a GBM model to generate return distributions for stocks. Our result show that, for individuals with a enrollment period of less than 30 years, participants should invest a minimum of 70-80% of their funds in risky assets to minimize the shortfall risk. However, the proportion of funds that need to be invested in risky assets declines significantly when participants contribute an additional premiums. This effect is particularly pronounced among low-income individuals. Therefore, to achieve OECD average replacement rates, the government needs to incentivize participants to invest more in risky assets, while also providing policies to encourage additional contributions, especially for the low-income population.

• Journal of the Korean Data and Information Science Society
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• v.21 no.2
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• pp.219-229
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• 2010

There have been many researches on the risk management due to rapid increase of various risk factors for financial assets. Aa a method for comprehensive risk management, Value at Risk (VaR) is developed. For estimation of VaR, it is important task to solve the problem of asymmetric distribution of the return rate with heavy tail. Most real distributions of the return rate have high positive kurtosis and low negative skewness. In this paper, some alternative distributions are used to be fitted to real distributions of the return rate of financial asset. And estimates of VaR obtained by using these fitting distributions are compared with those obtained from real distribution. It is found that normal mixture distribution is the most fitted where its skewness and kurtosis of practical distribution are close to real ones, and the VaR estimation using normal mixture distribution is more accurate than any others using other distributions including normal distribution.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.18 no.6
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• pp.11-26
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• 2023

This study aimed to empirically analyze the effect of Korean companies' FDI(Foreign Direct Investment) on their financial performances, particularly divided into profitability, stability, growth and activity, while comparing distinct financial performances between SMEs(small and medium-sized enterprises) and large enterprises whose corporate attributes are different from each other. As research subjects, this study selected FDI Korean companies from the directory of oversea-expanded companies of KOTRA(Korea Trade-Investment Promotion Agency) and used financial data from a total of 409 companies(136 SMEs and 273 large enterprises) with complete financial data for the first five years after the initial investment out of all the financial data from 1990 to 2021. The analysis results can be summarized as follows; In the profitability sector, FDI had positive effects on ROA(Return on Assets) and ROS(Return on Sales) of SMEs, while having negative effects on those of large enterprises to the contrary. In the stability sector, FDI had no statistical significance for SMEs, while having significantly negative effect on LEV(Debt to Equity Ratio) of large enterprises. In the growth sector, FDI had significantly negative effect on AGR(Asset Growth) of SMEs, but showed no significant results for large enterprises. In the activity sector, FDI showed no statistical significance for SMEs, while having positive effects on ATR(Asset Turnover Ratio) and FATA(Fixed Asset Turnover Ratio) of large enterprises. In conclusion, it was found that when having made FDI, SMEs and large enterprises showed different financial performances from each other in terms of profitability, stability, growth and activity.

• The Journal of Asian Finance, Economics and Business
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• v.9 no.3
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• pp.275-283
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• 2022

This study aims to investigate the influence of internal factors on the bankruptcy risk of an enterprise through a sample of 439 companies listed on the Vietnamese stock exchange. The research collected secondary data from annual audited financial statements from 2008 to 2019 of listing companies. Using two different regression models with two dependent variables, six independent and control variables, we discovered that three of the model's six factors, namely return on total assets, current payment rate, and financial leverage, influence the risk of bankruptcy and account for 86.78% of the variations in firm bankruptcy risk. Financial leverage has the opposite effect on the Z-score index, increasing the risk of bankruptcy of listed firms. Return on total assets and current ratio have a positive impact on the Z-score index, reducing the risk of bankruptcy of listed companies. The findings also revealed that there is no evidence that the size of a corporation, its fixed asset investment ratio, or the size of an auditing firm have an impact on the Z-score index. These findings provide crucial evidence for business owners and managers, as well as shareholders making future capital investment decisions. Our findings can be applied to other businesses in Vietnam and similar jurisdictions.

• KDI Journal of Economic Policy
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• v.30 no.2
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• pp.225-270
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• 2008

We analyze macroeconomic consequences of pay-as-you-go (PAYGO) public pension system with a simple overlapping generations model. Contrary to large body of existing literatures offering quantitative results based on simulation study, we take another route by adopting a highly simplified framework in search of qualitatively tractable analytical results. The main contribution of our results lies in providing a sound theoretical foundation that can be utilized in interpreting various quantitative results offered by simulation studies of large scale general equilibrium models. We present a simple overlapping generations model with a defined benefit(DB) PAYGO public pension system as a benchmark case and derive an analytical equilibrium solution utilizing graphical illustration. We also discuss the modifications of the benchmark model required to encompass a defined contribution(DC) public pension system into the basic framework. Comparative statics analysis provides three important implications; First, introduction and expansion of the PAYGO public pension, DB or DC, result in lower level of capital accumulation and higher expected rate of return on the risky asset. Second, it is shown that the progress of population aging is accompanied by lower capital stock due to decrease in both demand and supply of risky asset. Moreover, risk premium for risky asset increases(decreases) as the speed of population aging accelerates(decelerates) so that the possibility of so-called "the great meltdown" of asset market cannot be excluded although the odds are not high. Third, it is most likely that the switch from DB PAYGO to DC PAYGO would result in lower capital stock and higher expected return on the risky asset mainly due to the fact that the young generation regards DC PAYGO pension as another risky asset competing against the risky asset traded in the market. This theoretical prediction coincides with one of the firmly established propositions in empirical literature that the currently dominant form of public pension system has the tendency to crowd out private capital accumulation.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.4
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• pp.81-95
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• 2020

The main objective of this research is to investigate the impact of board size and board composition on financial performance of banks. The sample of this study consists on two countries listed bank sector Pakistan and China. The annul data is used from 2009-2018 to find the objective of this study. The Panel regression model is used to check the relationship between dependent and independent variables. Return on Asset and Return on Equity is used as performance checker dependent variables. The results of this study confirm board size coefficient value positive for ROA and negative for ROE but shows insignificant behavior for Pakistani banking sector while in Chinese banking sector the coefficient value of board size positively for ROA and ROE at 10% level. The board composition coefficient shows the negatively significant with ROA but insignificantly related to ROE for Pakistani banking sector. However, in Chinese banking sector the coefficient value of board composition is insignificant for both ROA and ROE. This study is helpful for banks, management of banks, policy makers, researcher as well as Government.