• Journal of the Korea Academia-Industrial cooperation Society
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• v.7 no.2
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• pp.150-156
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• 2006

It is one of the most effective methods for improving the performance of electric railway vehicles to make better the wheel-rail adhesion characteristics. To study adhesion characteristic is to develop the equivalent reduction machine to experiment on the adhesion system. The experiment system makes it possible to change the wheel-rail adhesion force with various adhesion parameters, and therewith to test the adhesion control system with the reduction machine in a laboratory. In this paper, for improving adhesion performance shows actually control methods.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.4
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• pp.97-105
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• 2020

This paper explores the impact of capital structure on firm performance in the context of Vietnam. The paper investigates the different effect of capital structure on firm performance in state-owned and non-state enterprises listed on the Vietnam stock market. The panel data of research sample includes 488 non-financial listed companies on the Vietnam stock market for a period of six years, from 2013 to 2018. The Generalized Least Square (GLS) is employed to address econometric issues and to improve the accuracy of the regression coefficients. In this research, firm performance is measured by return on equity (ROE), return on assets (ROA), and earnings per share (EPS). The ratios of short-term liabilities, long-term liabilities, and total liabilities to total assets are proxy for capital structure. Firm sizes, growth rate, liquidity, and ratio of fixed assets to total assets are control variables in the study. The empirical results show that capital structure has a statistically significant negative effect on the firm performance. The result also shows this effect is stronger in state-owned enterprises than non-state enterprises in Vietnam. These evidences provide a new insight to managers of both state-owned and non-state enterprises on how to improve the firm's performance with capital structure.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.11
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• pp.79-86
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• 2021

In recent years, firm performance has been a topic that attracts many researchers. It is extremely important to identify the factors that change firm performance. In the current trend of competition and integration, foreign ownership, product market competition is found to reduce agency costs and impact firm performance. The purpose of this research is to investigate the relationship between foreign ownership, product market competition, and firm performance. Our research using a quantile regression model, through panel data of 290 companies listed on the Vietnam stock exchange (include Ho Chi Minh and Hanoi stock exchanges) from 2017 to 2019 that was collected by Thomson - Reuters DataStream has shown that foreign ownership and product market competition have a positive impact on Tobin's Q but are not statistically significant with ROA. Critically, our quantile regression results suppose foreign ownership, product market competition have a significantly larger positive impact in high-performing firms relative to low-performing firms. The results help propose solutions to planners and managers to change foreign ownership and product market competition to increase business performance. Besides, through quantile regression analysis, managers need to pay attention to the impact on foreign ownership, product market competition; there will be a difference between high-performing firms relative to low-performing firms.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.4
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• pp.391-402
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• 2021

This study aims to analyze the impact of the company's financial performance in mediating the relationship between Intellectual Capital and GCG on Corporate Value in banking companies listed on the Indonesia Stock Exchange (IDX). Also, this study analyzes the direct effect of intellectual capital and GCG on corporate value and the indirect effect through the company's financial performance. This study develops research of Chen et al. (2005) and measures Intellectual Capital with VAIC (Pulic, 1998). VAIC model is more accurate to measure Intellectual Capital because it can show potential intellectual use efficiently. The data used are banking companies listed on the IDX in 2014-2016 with purposive sampling technique and Data Analysis Technique used are path analysis. The results showed that the financial performance of banking companies was proven to mediate the relationship between intellectual capital and GCG. The role of GCG that can improve financial performance and corporate value is only GCG as measured by the ratio of independent commissioners and audit quality. Meanwhile, the financial performance and corporate value audited by the Big 4 will be greater than the financial performance and corporate value of the banking companies listed on the Indonesia Stock Exchange that are not audited by the Big 4.

• The Korean Journal of Financial Management
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• v.27 no.2
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• pp.35-62
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• 2010

This paper examines the existence of the fund performance persistence and the smart money effect in Korean stock market and tests the flow-induced price pressure (FIPP) hypothesis, that is, fund flows affect individual stock returns and mutual fund performance. This paper also tests whether the FIPP effect can cause the performance persistence using the monthly returns and stock holdings data of 2,702 Korean mutual funds from January 2002 to June 2008. The empirical results indicate that the performance persistence exists significantly for a long time but the smart money effect does not. The hedge portfolio constructed by buying funds with the highest past 12 months performance and selling funds with the lowest past 12 months performance earns 0.11%~1.05% monthly abnormal returns, on average, in 3 years from portfolio formation month, but the hedge portfolio constructed by buying funds with the highest past net fund inflows and selling funds with the lowest past net fund inflows cannot earn positive monthly abnormal returns and the size of negative abnormal returns of the portfolio increase as time goes on. We find the evidence that the FIPP hypothesis is significantly supported. We first estimate the FIPP measure for each individual stock using the trading volume resulting from past fund flows and then construct the hedge portfolio by buying stocks with the highest FIPP measure and selling stocks with the lowest FIPP measure. That portfolio earns significantly positive abnormal return, 1.01% at only portfolio formation month and cannot earn significant abnormal returns after formation month. But, the FIPP effect cannot cause the performance persistence because, within the same FIPP measure group, funds with higher past performance still earn higher monthly abnormal returns than those with lower past performance by 0.08%~0.77%, on average, in 2 years. These results imply that the main cause of the performance persistence in Korean stock market is the difference of fund managers' ability rather than the FIPP effect.

• The Research Journal of the Costume Culture
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• v.12 no.4
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• pp.547-565
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• 2004

The purpose of this study was to evaluate the level of SCM activities and the logistics performance by SCM of the three company types in fashion industry· fabric suppliers, apparel manufacturers, and retailers. The level of SCM activities was estimated through the examination of seven factors: commitment and leadership of a top management, flexibility of management, understanding of demand characteristics, integrated management organization, information system, cooperative partnership and communication and exchange of opinion. The logistics performance was measured by improvement in customer service(on time delivery ratio of products, returning rate, treat ratio for A/S, order fill rate, substitute providing capability for being out of stock) and delivery cost reduction. Through questionnaire survey, a total of 214 data for 108 companies of three company types were collected: 46 for 40 fabric suppliers, 123 for 64 apparel manufacturers and 45 for 4 retailers. The analysis of SCM activity levels showed that fabric suppliers had higher degrees in the factor of understanding of demand characteristics, and apparel manufacturers had higher degrees in the factor of information systems. For retailers, the factor of communication and exchange of opinion represented higher degrees. The study on relationship between the SCM activity levels and logistics performance showed that the SCM activity factor of understanding of demand characteristics greatly improved a substitute providing capability for being out of stock in fabric suppliers, and information system improved a substitute providing capability for being out of stock, on time delivery ratio of products and order fill rate in apparel manufacturers. In retailers, the SCM activity factor of understanding of demand characteristics decreased returning rate highly and improved on time delivery ratio of products. The study results showed that SCM activities in fashion industry brought more improvement in customer service levels rather than in delivery cost reduction.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.11 no.2
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• pp.204-208
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• 2018

In this paper, we proposed and evaluated the time series deep learning prediction model for learning fluctuation pattern of stock price. Recurrent neural networks, which can store previous information in the hidden layer, are suitable for the stock price prediction model, which is time series data. In order to maintain the long - term dependency by solving the gradient vanish problem in the recurrent neural network, we use LSTM with small memory inside the recurrent neural network. Furthermore, we proposed the stock price prediction model using bidirectional LSTM recurrent neural network in which the hidden layer is added in the reverse direction of the data flow for solving the limitation of the tendency of learning only based on the immediately preceding pattern of the recurrent neural network. In this experiment, we used the Tensorflow to learn the proposed stock price prediction model with stock price and trading volume input. In order to evaluate the performance of the stock price prediction, the mean square root error between the real stock price and the predicted stock price was obtained. As a result, the stock price prediction model using bidirectional LSTM recurrent neural network has improved prediction accuracy compared with unidirectional LSTM recurrent neural network.

• The Korean Journal of Financial Management
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• v.25 no.1
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• pp.141-176
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• 2008

This study provides an analysis of ex post efficient outcome, which can be said an objective of distressed restructurings, using the stock return of listed companies. The findings of this study are as follows: First, upon completing the distressed restructurings, reorganization and workout cases showed positive announcement effects, which was statistically significant. Also, composition cases displayed a positive value, but it was not statistically significant. Second, with respect to post-restructuring long-run stock performance, reorganization and composition showed underperformance after completion. However, workout cases showed overperformance after the completion. Third, multiple regression analysis to find factors affecting post-restructuring long-run stock performance suggests that higher asset decrease(ASSETCH), shareholder concentration (OWNCEN), largest shareholders' stake(OWN) have more positive impacts on long-run performance. However, change of the largest shareholder(OWNERCH) has negative impacts on long-run performance. Finally, change of the largest shareholder is a negative factor in the performance of the distressed restructurings. Therefore, this study implies that if M&A is used as a way of early completing the distressed restructurings, prudent judgment is required on whether a firm can recover its competitiveness and is likely to be economically viable again.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1996.04a
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• pp.745-748
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• 1996

Korea Composite Stock Price Index (KOSPI) was predicted using Cascade Correlation Network (CCN) model. CCN was suggested, by Fahlman and Lebiere [1990], to overcome the limitations of backpropagation algorithm such as step size problem and moving target problem. To test the applicability of CCN as a function approximator to the stock price movements, CCN was used as a tool for univariate time series analysis. The fitting and forecasting performance fo CCN on the KOSPI was compared with those of Multi-Layer Perceptron (MLP).

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2006.05a
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• pp.1453-1458
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• 2006

KTX Railway rolling stock wheel run its course to corrode, deteriorate and wear away through out the time. So it is natural that the performance and ability of wheel gets declined. The frequency characteristic analysis were accomplished to above trend and shock wave flow to wheels were examined. The result will be used to find Railway rolling stock wheel crack and maintenance method hereafter.