• 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 Fisheries Business Administration
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• v.44 no.2
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• pp.1-17
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• 2013

We investigate the appropriateness of the fixed 12% discount rate to be used in estimating the amount of compensation for revoking a license for fishery business by the Enforcement Decree of Fisheries Act in Korea. We also suggest the appropriate discount rate fully reflecting the change of market interest rate in the Korean financial market. The capital asset pricing model, or, CAPM is the best known model of risk and return, and is widely used to estimate the expected rate of return for the risky projects. Even though the CAPM implies that the discount rate or the expected rate of return should change as the related market factors do, the discount rate used to estimate compensation for revoking a license for fishery business remains to be the same 12% rate for the last 15 years by law. During this period, however, the yield to maturity for the 5-year government bonds in Korea has dramatically changed from about 12% to less than 3%. In order to provide the fair compensation for the damages against the coastal fisheries and evaluate the intrinsic value of fishery resources in the coastal areas, we suggest that the appropriate discount rate should be determined by the yield to maturity of the government bonds with 5-year maturity, instead of the current fixed 12% interest rate.

• Journal of Distribution Science
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• v.14 no.4
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• pp.13-20
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• 2016

Purpose - This paper attempts to determine the importance of financial sustainability and the impact of Selling, General and Administrative Expenses (SG&A) on the financial sustainability of the IT industry. Research design, data, and methodology - Primarily the impact of SG&A expenditure on the sales revenue, assets, gross margins and profit is ascertained. After that the impact of SG&A expenditure, sales revenue, assets, gross margins and profit on the financial sustainability i.e., return on assets is worked out. Finally the impacts of financial sustainability i.e., return on assets on total enterprise value and market valuation multiples are found out. Results - The empirical result shows that SG&A expenditure most strongly impacted sales revenue, assets, gross margins and profit positively. Financial sustainability impacted in mixed manner with SG&A expenditure, sales revenue, assets, gross margins and profit. Assets and gross margins have weak positive impact on financial sustainability. Sales revenue has no impact on financial sustainability. Finally financial sustainability had moderate positive impact on total enterprise value and had no impact on market valuation multiples. Conclusions - SG&A expense has moderate positive impact on the financial sustainability and magnitude is very low.

• The Journal of Asian Finance, Economics and Business
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• v.6 no.2
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• pp.247-255
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• 2019

This study examines the different roles of cash flow in assessing investment returns in the Association of Southeast Asian Nations (ASEAN). The analysis covers over 900 listed firms across Malaysia, Indonesia, Philippines, Singapore and Thailand for the period post the Asian financial crisis of 2001-2017. Firm-level panel data analysis shows that cash flow factors are important in all contexts of cash return on assets, earnings quality and market value multiple across the region even after controlling for typical measures of profitability. The results suggest that firms should manage cash flow prudently in considerations of firm value from the shareholder's perspective, measured directly using stock return. Cash profitability on assets should become an important firm performance indicator, whilst higher cash component over reported earnings is preferred. The market also tends to respond favourably to cash flow yield as a price multiple in valuation, outpacing the role of earnings yield. Such findings are robust across the pre and post subprime crisis periods, across estimation methods pertaining to finance panel standard errors, as well as across static and dynamic considerations of returns. It is hence sensible to consider cash flow factors in the research pertaining to asset pricing and factor investing in the ASEAN region.

• Journal of the Korean Data Analysis Society
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• v.20 no.6
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• pp.2759-2769
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• 2018

The behavioral finance view on the existence of asset pricing anomalies is based on two factors: investors' sentiment and limits to arbitrage. This paper tries to examine the effect of investors' sentiment on the stock price in the Korean stock market. In order to measure investors' sentiment, we constructed the sentiment index using principal component of five sentiment variables. By using sentiment index as an additional independent variable to three risk factors, impacts of the sentiment index on individual stocks and 25 portfolios sorted by BM-size are examined. Main results found are as follows: 1) not only all three risk factors show positive impacts on the return of individual stock, but also the sentiment index has a positive impact. SI alone explains 15% of individual return variation. 2) among four independent variables, the most important factor turned out to be the market risk factor and investors' sentiment has better explanatory power on stock price than the size effect. 3) after controlling the market risk factor, the coefficient of the sentiment index for the smallest size and highest book/market value portfolios is significantly positive. 4) all the coefficients of the sentiment index for 25 portfolios sorted by BM-size have significant positive value after controlling size or (and) value.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.4
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• pp.699-707
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• 2021

The objective of this study is to examine the determinants of the liquidity of 17 commercial banks listed on the Vietnamese Stock Exchanges, HOSE, HNX and UPCoM. The study uses the quarterly audited financial statements from the first quarter of 2006 to first quarter of 2020; it includes 496 observations. Data on GDP and inflation are compiled from the International Monetary Fund and the General Statistics Office of Vietnam. Once collected, the data were organized along the line of unbalanced panel data. The results show that total asset size, return on total assets, and credit growth are positively associated with the liquidity of the listed banks; whereas the interaction between the bank size and the return on total assets has a negative impact on the liquidity of commercial banks listed on the HNX, HOSE, UPCoM. In order to maintain good liquidity, commercial banks need to focus on effective credit growth, ensure a high rate of profit over total assets, and at the same time focus on developing the scale of total assets. However, the development of the size of the total assets should be noted in the balance between the total assets and the rate of return on the total assets.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.4
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• pp.727-734
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• 2021

The study aims to examine and analyze the factors that affect the return on assets (ROA) by placing net interest margin (NIM) as a moderating variable in influencing ROA. This research was conducted on 27 banks listed on the Indonesia Stock Exchange (IDX) for the period 2015 to 2018 with a total sample data of 91. The data used is a combination of time series data and cross-section data. The sampling technique used was the purposive sampling method. The data analysis technique used was path analysis with multiple regression analysis technique. The results of the analysis showed that the capital adequacy ratio (CAR) and loan to deposit ratio (LDR) have a positive but insignificant effect on ROA. NIM as a moderating variable does not influence the impact of CAR on ROA. However, NIM as a moderating variable is able to influence the impact of LDR on ROA. From the results of this study, it is evident that the LDR will increase the ROA at banks that generate high NIM.

• 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 Intelligence and Information Systems
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• v.25 no.2
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• pp.39-55
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• 2019

Recently banks and large financial institutions have introduced lots of Robo-Advisor products. Robo-Advisor is a Robot to produce the optimal asset allocation portfolio for investors by using the financial engineering algorithms without any human intervention. Since the first introduction in Wall Street in 2008, the market size has grown to 60 billion dollars and is expected to expand to 2,000 billion dollars by 2020. Since Robo-Advisor algorithms suggest asset allocation output to investors, mathematical or statistical asset allocation strategies are applied. Mean variance optimization model developed by Markowitz is the typical asset allocation model. The model is a simple but quite intuitive portfolio strategy. For example, assets are allocated in order to minimize the risk on the portfolio while maximizing the expected return on the portfolio using optimization techniques. Despite its theoretical background, both academics and practitioners find that the standard mean variance optimization portfolio is very sensitive to the expected returns calculated by past price data. Corner solutions are often found to be allocated only to a few assets. The Black-Litterman Optimization model overcomes these problems by choosing a neutral Capital Asset Pricing Model equilibrium point. Implied equilibrium returns of each asset are derived from equilibrium market portfolio through reverse optimization. The Black-Litterman model uses a Bayesian approach to combine the subjective views on the price forecast of one or more assets with implied equilibrium returns, resulting a new estimates of risk and expected returns. These new estimates can produce optimal portfolio by the well-known Markowitz mean-variance optimization algorithm. If the investor does not have any views on his asset classes, the Black-Litterman optimization model produce the same portfolio as the market portfolio. What if the subjective views are incorrect? A survey on reports of stocks performance recommended by securities analysts show very poor results. Therefore the incorrect views combined with implied equilibrium returns may produce very poor portfolio output to the Black-Litterman model users. This paper suggests an objective investor views model based on Support Vector Machines(SVM), which have showed good performance results in stock price forecasting. SVM is a discriminative classifier defined by a separating hyper plane. The linear, radial basis and polynomial kernel functions are used to learn the hyper planes. Input variables for the SVM are returns, standard deviations, Stochastics %K and price parity degree for each asset class. SVM output returns expected stock price movements and their probabilities, which are used as input variables in the intelligent views model. The stock price movements are categorized by three phases; down, neutral and up. The expected stock returns make P matrix and their probability results are used in Q matrix. Implied equilibrium returns vector is combined with the intelligent views matrix, resulting the Black-Litterman optimal portfolio. For comparisons, Markowitz mean-variance optimization model and risk parity model are used. The value weighted market portfolio and equal weighted market portfolio are used as benchmark indexes. We collect the 8 KOSPI 200 sector indexes from January 2008 to December 2018 including 132 monthly index values. Training period is from 2008 to 2015 and testing period is from 2016 to 2018. Our suggested intelligent view model combined with implied equilibrium returns produced the optimal Black-Litterman portfolio. The out of sample period portfolio showed better performance compared with the well-known Markowitz mean-variance optimization portfolio, risk parity portfolio and market portfolio. The total return from 3 year-period Black-Litterman portfolio records 6.4%, which is the highest value. The maximum draw down is -20.8%, which is also the lowest value. Sharpe Ratio shows the highest value, 0.17. It measures the return to risk ratio. Overall, our suggested view model shows the possibility of replacing subjective analysts's views with objective view model for practitioners to apply the Robo-Advisor asset allocation algorithms in the real trading fields.