• The Journal of Asian Finance, Economics and Business
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• v.9 no.5
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• pp.295-303
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• 2022

This study investigates the impact of globalization, coal consumption, and economic growth on CO₂ emissions in Malaysia by applying the Kuznets Environmental Curve model. The study employed the Autoregressive Distributed Lag modeling technique on time series data over the period of 1970-2018 to determine the short and long-run relationship between CO₂ emissions and a number of variables, including globalization, coal consumption, and economic growth. The results show that globalization increase CO₂ emissions in both the short and long run in Malaysia. Furthermore, the results reveal that economic growth and coal consumption degrade the environmental quality by accelerating the CO₂ emissions in the short-run and long run. As a result, the findings validate the Kuznets Environmental Curve hypothesis of an inverted U-shaped relationship between economic growth and CO₂ emissions in the long run for Malaysia. The findings of this study suggest that higher globalization levels and usage of coal consumption degrade the environmental quality in Malaysia. The findings also indicate the effect of economic growth on environmental degradation is positive at the initial stage but improves after the economy achieves a threshold level of income per capita in the economic development process with an inverted U-shaped pattern in the long run.

• Health Policy and Management
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• v.23 no.2
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• pp.112-123
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• 2013

Background: Under the risk of financial sustainability of National Health Insurance, Korean government attempted a series of regulations over pharmaceutical prices. The first price-cut was implemented to the hyperlipidemial treatments, and the prices of statins were reduced on 15th, April in 2009. The purposes of this study are 1) to investigate the impact of this price-cut on pharmaceutical expenditure, and 2) to identify the factors associated with drug-switch among statins. Methods: Using the national patients sample data, this study conducted time series analysis on the expenditures, prices, and volumes of statin drugs. To understand the factors associated with drug-switch, the multinomial logit model was analyzed at the patients level. Results: The results of time series analysis demonstrated that the price-cut of hyperlipidemic medicines did not lead to the reduced expenditure, suggesting the increased volume was the major cause. The multinomial logit analysis identified the switch of healthcare provider as the significant factor that was highly associated with drug-switch, implying the physicians' preference was the major motivation of drug-switch. Conclusion: Without control of utilization, price regulation itself could not reduce pharmaceutical expenditure. This suggests that the pharmaceutical regulations should be implemented on the basis of understanding of provider behaviors. The findings of this study will form the first step for further empirical studies.

• Korean Journal of Construction Engineering and Management
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• v.15 no.6
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• pp.105-112
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• 2014

The objective of this study is to examine the relationship between the degree of business diversification of a construction company and two of the indicators that represent financial stability, namely, a current ratio and a debt ratio, in order to draw policy implications. The current ratio and the debt ratio were used as variables that represent financial stability of a construction company. Berry-Herfindahl Index was used to measure the degree of business portfolio diversification of a construction company. For the analysis, quarterly time series data were retrieved from the financial information disclosure system of Korea's Financial Supervisory Service for the period between the first quarter of 2001 and the third quarter of 2013. The analysis results showed that a higher current ratio and a debt ratio led to a greater extent of business diversification. A higher level of business diversification led to a higher current ratio and a lower debt ratio. It was also shown that the impact of business diversification on the current ratio and the debt ratio outweighed the impact of changes in the current ratio and the debt ratio on business diversification. Meanwhile, an increase in the level of business diversification showed a quite positive effect as it raised the current ratio and lowered the debt ratio of a construction company. These findings suggest that diversification of business portfolio is essential for construction companies to strengthen their financial stability.

• Journal of the Korea Society of Computer and Information
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• v.28 no.8
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• pp.59-66
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• 2023

The Golden Cross is commonly seen as a buy signal in financial markets, but its reliability for predicting stock price movements is limited due to market volatility. This paper introduces a time-invariant approach that considers the Golden Cross as a singular event. Utilizing LSTM neural networks, we forecast significant stock price changes following a Golden Cross occurrence. By comparing our approach with traditional time series analysis and using a confusion matrix for classification, we demonstrate its effectiveness in predicting post-event stock price trends. To conclude, this study proposes a model with a precision of 83%. By utilizing the model, investors can alleviate potential losses, rather than making buy decisions under all circumstances following a Golden Cross event.

• The Korean Journal of Applied Statistics
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• v.24 no.1
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• pp.71-81
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• 2011

In this paper, we systematically analyzed the variation of KOSPI returns using a GARCH-ARJI(auto regressive jump intensity) model. This model is possibly to capture time varying volatility as well as time varying conditional jump intensity. Thus, we can decompose return volatility into usual variation explained by the GARCH model and unusual variation that resulted from external news or shocks. We found that the jump intensity implied on KOSPI return series clearly shows time varying. We also found that conditional volatility due to jump is generally smaller than that resulted from usual variation. We also analyzed the effect of 9.11 and the 2008 financial crisis on the volatility of KOSPI returns and conclude that there is strong and persistent impact on the KOSPI from the 2008 financial crisis.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.8
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• pp.311-324
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• 2021

Investors have increasingly become interested in macroeconomic antecedents in order to better understand the investment environment and estimate the scope of profitable investment in equity markets. This study endeavors to examine the interdependency between the macroeconomic antecedents (international oil price (COP), Domestic gold price (GP), Rupee-dollar exchange rates (ER), Real interest rates (RIR), consumer price indices (CPI)), and the BSE Sensex and Nifty 50 index return. The data is converted into a natural logarithm for keeping it normal as well as for reducing the problem of heteroscedasticity. Monthly time series data from January 1992 to July 2019 is extracted from the Reserve Bank of India database with the application of financial Econometrics. Breusch-Godfrey serial correlation LM test for removal of autocorrelation, Breusch-Pagan-Godfrey test for removal of heteroscedasticity, Cointegration test and VECM test for testing cointegration between macroeconomic factors and market returns,] are employed to fit regression model. The Indian market returns are stable and positive but show intense volatility. When the series is stationary after the first difference, heteroskedasticity and serial correlation are not present. Different forecast accuracy measures point out macroeconomics can forecast future market returns of the Indian stock market. The step-by-step econometric tests show the long-run affiliation among macroeconomic antecedents.

• Journal of the Korea Society of Computer and Information
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• v.8 no.3
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• pp.113-123
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• 2003

Many researches on the application of neural networks for making financial index prediction have proven their advantages over statistical and other methods. In this paper, a neural network model is proposed for the Buying, Holding or Selling timing prediction in stocks by the price index of stocks by inputting the closing price and volume of dealing in stocks and the technical indexes(MACD, Psychological Line). This model has an equalized multi-layer arithmetic function as well as the time series prediction function of backpropagation neural network algorithm. In the case that the numbers of learning data are unbalanced among the three categories (Buying, Holding or Selling), the neural network with conventional method has the problem that it tries to improve only the prediction accuracy of the most dominant category. Therefore, this paper, after describing the structure, working and learning algorithm of the neural network, shows the equalized multi-layer arithmetic method controlling the numbers of learning data by using information about the importance of each category for improving prediction accuracy of other category. Experimental results show that the financial index prediction using the equalized multi-layer arithmetic neural network has much higher correctness rate than the other conventional models.

• The Korean Journal of Applied Statistics
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• v.23 no.1
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• pp.41-47
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• 2010

In this paper, we show the performance evaluation of outlier detection methods based on the GARCH model. We first introduce GARCH model and the methods of outlier detection in the GARCH model. The results of small simulation and the real KOSPI data show the out-performance of the outlier detection method over the traditional method in the GARCH model.

• Journal of Korean Society for Quality Management
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• v.27 no.3
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• pp.51-66
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• 1999

This paper empirically investigates the impact of winning a quality award by investigating the rate of return of a firm's stock in the stock market, and by analyzing the contribution and effectiveness to a firm's competitiveness. It also compares the effect of firms winning MB(Malcolm Baldrige) award with that of firms winning Korean quality awards on the stock market. A comparative method is used to analyze the change of award-winning firms'rate of return and then they are classified by time-series, cross-sectional, firm's size, award agency, and the year of receiving the award. The number of firms employed in this study is 74, however, multiple award-winning firms are included in the analysis, which increased the sample size to 118. Results indicate that Korean quality awards improve an award-winning firms'market value but not as much as the MB award did.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.66 no.5
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• pp.745-749
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• 2017

Climate change and energy security are major factors for future national energy policy. To resolve these issues, many countries are focusing on creating new growth industries and energy services such as smartgrid, renewable energy, microgrid, energy management system, and peer to peer energy trading. The financial and economic evaluation of new energy services basically requires energy savings estimation technologies. This paper presents the baseline load estimation method, which is used to calculate energy savings resulted from participating in the new energy program, using moving average model with heating degree days (HDD) and cooling degree days (CDD) adjustment. To demonstrate the improvement of baseline load estimation accuracy, the proposed method is tested. The results of case studies are presented to show the effectiveness of the proposed baseline load estimation method.