• 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.

• Journal of Applied Reliability
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• v.16 no.2
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• pp.78-89
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• 2016

Purpose: In this paper, we investigate whether the endeavors for Six Sigma quality management by a firm have positive effects on its financial performance and the length of Six Sigma implemented period affects its financial status. We find a relationship between Six Sigma implemented period and several financial performance index using a smoothing spline function. Methods: A smoothing spline function is used in order to analyze the relationship between efforts for quality management and financial performance. Specifically, the return on assets, return on equity, sales cost and business fee are investigated as dependent variables and the efforts for quality management as independent variable. Results: As a result of the analysis, the indication is that companies that put effects into the Six Sigma quality management have a positive result in its financial status. In detail, the efforts for Six Sigma quality management have positive effects on total asset turnover ratio and Six Sigma implemented period on net income to net sales ratio. Additionally, companies with longer (shorter) period of Six Sigma program have more (less) improvement in its financial status. Conclusion: It can be concluded that the company's efforts for quality management positively influence financial performance.

• Asian Journal of Business Environment
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• v.10 no.2
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• pp.23-31
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• 2020

Purpose: The purpose of this paper is to find out the impact of financial leverage on firm's profitability in the listed textile sector of Bangladesh. Research design, data and methodology: A sample of 22 DSE listed textile firms has been used to conduct the study. In this study, firm profitability is measured by Return on Equity (ROE) and both short term debt and long term debt are used as the as proxies of financial leverage. Pooled Ordinary Least Squares (OLS), Fixed Effect (FE), and Generalized Method of Moments (GMM) models have been used to test the relationship between financial leverage and profitability of firms. Result: This study finds a significant negative relationship between leverage and firm's profitability using the Pooled OLS method. The result is also consistent with the fixed effect and GMM method. This result implies that firm's profitability is negatively affected by the firm's capital structure. Conclusion: The study concludes that maximum textile firms use external debt as a source of finance as they don't have sufficient internally generated funds. This study recommends that firm should give more emphasize on generating fund internally to meet up their financing needs.

• 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.7 no.8
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• pp.33-40
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• 2020

The main aim of the study is to test a house pricing model by combining hedonic and asset-based pricing models. An understanding of the relationship between house pricing and its return (the rental income) helps to establish houses as a significant asset class. The model tested the relationship between house pricing (dependent variable) and the house attributes (independent variables) derived from Freeman's framework of housing attributes. This study uses a large data-set of 1,899 sample of new, high-end houses purchased between 2016 and 2019 collected from the national capital region of India (Delhi-NCR). The algorithm was built in R-Script, and stepwise multiple linear regression was used to analyze the model. The analysis of the model proves that the three significant variables, namely, carpet area, pay-off, and annual maintenance charges explain the price function. Further, the model is statistically fit. The major contribution of the study is to understand the key factors and their influence on the house pricing. The model will be helpful in risk assessment in the housing investment and enhance the chances of investment. Policy-makers can use information about the underlying valuation drivers of the house prices to stabilize the market and also in framing the tax policies.

• Journal of Distribution Science
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• v.16 no.10
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• pp.55-64
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• 2018

Purpose - The most important goal of corporate management is the maximization of firm value in the market. Executives of companies are making effort to increase corporate value and initiate various management strategies, which is to develop the products or service with value. Through these efforts, consumer satisfaction grows and loyalty increases, which leads to the positive change of customer satisfaction index. The purpose of this research is to find out the abnormal return after the KCSI(Korean Customer Satisfaction Index) is announced. Research design, data, and methodology - This research data is collected from 11 years' stock price in KOSPI market and KCSI. The authors analyze the abnormal return triggered by the announcement of KCSI through the event study. Results - First, newly enlisted companies in the KCSI show statistically significant short-term abnormal rate of return. Second, the value of the customer satisfaction index is not the level of customer satisfaction but the direction of the change in the CSI. Conclusion - Customer satisfaction has the important intangible asset in the marketing area. However, firms' investment for CS is not an easy decision, because of the difficulty to measure the effect on corporate market value. This research investigates the change of the market value after the announcement of KCSI. Based on the results, firms have to keep trying to increase KCSI relative to the previous year. And the small company has to struggle for being newly listed in the KCSI.

• The Korean Journal of Financial Management
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• v.25 no.1
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• pp.23-49
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• 2008

We test the hypothesis that the gradual diffusion of information across asset markets leads to cross-asset return predictability in Korea. And, the aim of this paper is related to forecast the stock market, business cycle index and industrial production by various indicators of economic activities in Korea. For this, our paper sets models and focuses on empirical test. The stock market on this month correlate with industries in Korea. The stock market doesn't lead to industries. The industries and macroeconomic variables have high correlation. We test that gradual diffusion of industrial information will predict stock market in Korea. For this, we analysis on possibility of Granger cause by VAR models between industries and stock market. As a result, 21 portfolios cause to Kospi statistically significance at 5%. Especially, the Beverage portfolio has bilateral Granger causality to Kospi. In case of Internet and Cosmetics portfolio, Kospi has unilateral Granger causality to it. The predictability of specific industries has a relation to Macroeconomic variables. What industrial portfolios predict to Business Coincidence Index? The only 6 industrial portfolios of 36 portfolios have a statistically significance at 10%. And, 9 portfolios have a statistically significance at 5%.

• 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 Korean Society of Industrial and Systems Engineering
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• v.40 no.4
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• pp.38-45
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• 2017

As the competitiveness of SMEs (small and medium enterprises) is getting more and more improved and globalized, the government provides various consulting services to secure the competitiveness of small and medium firms and support stable growth. However, the assessment of the result from the government's support is generally focused on non-financial factors, such as customer satisfaction and analysis of improvement effect. This paper is in regards to the statistical analysis of how much the government's support in the form of providing consulting services contributes to financial outcomes in terms of profitability and growth. ROA (return on asset) and ROS (return on sales), which are investment profitability and sales profitability respectively, are chosen as an indicator of profitability. For analysis of growth, sales revenue and total asset growth are used. The samples are 44 corporations which are supported by government, and 150 corporations which are selected for comparison, with corporate growth support center program by the Ministry of Trade, Industry, and Energy chosen as the consulting model. After gathering the yearly balance sheets and income statements of the samples from CRETOP, Korea Enterprise Data, the analysis is conducted in the way of identifying the statistical significance of financial difference in the same period between corporates taking consulting services and corporates which have not, and the difference of financial outcomes from the corporates taking consulting services before and after consulting services. As a result, in terms of business growth, it is turned out to have positive difference both in growth ratio and profitability compared to the compared corporations at the significant level. Therefore, it is obvious that the consulting program which government provides to SMEs have direct influence practically to the corporates' management performance.

• 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.