• Journal of Forest and Environmental Science
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• v.32 no.3
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• pp.302-310
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• 2016

The loss and degradation in tropical forest region are some of the current global concern. Hence, these issues elevated the role of rehabilitated forests in providing ecological products and services. The information on the carbon stock is important in relation to global carbon and biomass use, but lacking from the tropical region. This paper reports the assessment of tree and soil carbon stock in a chronosequence rehabilitated tropical forest stands in Malaysia. The study site was at the UPM-Mitsubishi Forest Rehabilitation Project, UPMKB. $20{\times}20m$ plot was established each and assessed in 2009 at 1-, 10- and 19-year-old sites while an adjacent ${\pm}23-year-old$ natural regenerating secondary forest plot was established for comparison. The overall total carbon stock was in the order of 19-year-old>${\pm}23-year-old$>10-year-old>1-year-old. When forest carbon stock is low, the soil component plays an important role in the carbon storage. The forest carbon recovery is crucial to increase soil carbon stock. The variations in the carbon stock showed the different stages of the forest recovery. Species survived after 19-years of planting are potential species for carbon sequestration activities in rehabilitated forest. Human intervention in rehabilitating degraded forest areas through tree planting initiatives is crucial towards recovering the forest ecological role especially in forest carbon stock capacity.

• The Journal of Information Technology
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• v.7 no.1
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• pp.1-22
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• 2004

This study examine the effects of changes in the dividend income tax rates, the corporate dividend policy, and the ownership structure on the stock valuation. The empirical findings indicate that : (1)firm's ownership structure is positively correlated with stock return ; (2) the interaction of firm's ownership structure and the dividend policy is positively correlated with stock return ; (3) the interaction of the changes in the dividend income tax rates and dividend policy is correlated with stock return ; (4) the interaction of the changes in the dividend income tax rates and firm's ownership structure is correlated with stock return ; (5) the interaction of the increases in the dividend income tax rates, firm's ownership structure, and the dividend policy is positively correlated with stock return. This suggests that non-taxing of capital gains provide tax shelters to individual investors and investors prefer non-taxing income to dividend income.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.7
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• pp.1593-1598
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• 2015

In this paper, we analyze the correlation between social sentiment and stock prices. Polarity analysis is conducted for the stock prices plunging and soaring duration. And it is performed for its prior period. Using these results, we analyze the relationship between the social sentiment and stock prices. We collected the past data of Dow Jones Industrial Average and detected the period of plunging and soaring. On the basis of the detected time, the New York Times articles are collected and polarity analysis is conducted. Frequency of negative terms is decreased and it of positive terms is increased during the stock prices soaring. There is a little difference between the frequency of negative and positive terms in the previous stock prices plunging or soaring. According to the correlation analysis, it shows a positive correlation between social sentiment and stock prices in the period of plunging and soaring. A significant correlation is not appeared in the previous stock prices plunging or soaring.

• The Journal of Information Systems
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• v.30 no.3
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• pp.21-45
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• 2021

Purpose This paper analyzed the impacts of domestic stock market by a global pandemic such as COVID-19. We investigated how the overall pattern of the stock market changed due to the impact of the COVID-19 pandemic. In particular, we analyzed in depth the pattern of stock price, as well, tried to find what factors affect on stock market index(KOSPI) in the healthcare industry due to the COVID-19 pandemic. Design/methodology/approach We built a data warehouse from the databases in various industrial and economic fields to analyze the changes in the KOSPI due to COVID-19, particularly, the changes in the healthcare industry centered on bio-medicine. We collected daily stock price data of the KOSPI centered on the KOSPI-200 about two years before and one year after the outbreak of COVID-19. In addition, we also collected various news related to COVID-19 from the stock market by applying text mining techniques. We designed four experimental data sets to develop decision tree-based prediction models. Findings All prediction models from the four data sets showed the significant predictive power with explainable decision tree models. In addition, we derived significant 10 to 14 decision rules for each prediction model. The experimental results showed that the decision rules were enough to explain the domestic healthcare stock market patterns for before and after COVID-19.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.10
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• pp.1435-1440
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• 2021

With the advent of the low interest rate era, many investors are flocking to the stock market. In the past stock market, people invested in stocks labor-intensively through company analysis and their own investment techniques. However, in recent years, stock investment using artificial intelligence and data has been widely used. The success rate of stock prediction through artificial intelligence is currently not high, so various artificial intelligence models are trying to increase the stock prediction rate. In this study, we will look at various artificial intelligence models and examine the pros and cons and prediction rates between each model. This study investigated as stock prediction programs using artificial intelligence artificial neural network (ANN), deep learning or hierarchical learning (DNN), k-nearest neighbor algorithm(k-NN), convolutional neural network (CNN), recurrent neural network (RNN), and LSTMs.

• The Journal of Industrial Distribution & Business
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• v.12 no.3
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• pp.43-49
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• 2021

Purpose: This study attempted to examine the risk of stock price plunge according to the firm's management strategy. Prospector firms value innovation and have high uncertainties due to rapid growth. There is a possibility of lowering the quality of financial reporting in order to meet market expectations while withstanding the uncertainty of the results. In addition, managers of prospector firms enter into compensation contracts based on stock prices, thus creating an incentive to withhold negative information disclosure to the market. Prospector firms' information opacity and delays in disclosure of negative information are likely to cause a sharp decline in share prices in the future. Research design, data and methodology: This study performed logistic analysis of KOSPI listed firms from 2014 to 2017. The independent variable is the strategic index, and is calculated by considering the six characteristics (R&D investment, efficiency, growth potential, marketing, organizational stability, capital intensity) of the firm. The higher the total score, the more it is a firm that takes a prospector strategy, and the lower the total score, the more it is a firm that pursues a defender strategy. In the case of the dependent variable, a value of 1 was assigned when there was a week that experienced a sharp decline in stock prices, and 0 when it was not. Results: It was found that the more firms adopting the prospector strategy, the higher the risk of a sharp decline in the stock price. This is interpreted as the reason that firms pursuing a prospector strategy do not disclose negative information by being conscious of market investors while carrying out venture projects. In other words, compensation contracts based on uncertainty in the outcome of prospector firms and stock prices increase the opacity of information and are likely to cause a sharp decline in share prices. Conclusions: This study's analysis of the impact of management strategy on the stock price plunge suggests that investors need to consider the strategy that firms take in allocating resources. Firms need to be cautious in examining the impact of a particular strategy on the capital markets and implementing that strategy.

• Journal of Korea Trade
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• v.23 no.7
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• pp.147-155
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• 2019

Purpose - As the U.S.-China trade war has become considerably worse, the Chinese government is considering applying non-tariff barriers to trade, especially local contents rule. The main purpose of this research is to check whether it is suitable for Korean investors to invest in the current Chinese capital market. Design/methodology - In order to check the stability of the recent Chinese capital market, we investigated the behavior of foreign equity investment (including Korean equity investment) in the Chinese capital market after China announced the Shanghai-Hong Kong Stock Connect (SH-HK Connect). In this paper, we researched whether international portfolio investment would or would not contribute to an increase the volatility of an emerging market's stock market (Chinese capital market) when foreign investors make investment decisions based on the objective of short-term gains by rushing into countries whose markets are booming and fleeing from countries whose markets are falling. Findings - The empirical results indicate that foreign investors show strong, negative feedback trading behavior with regard to the stock index of the Shanghai Stock Exchange (SSE), and when the performance of foreign investors in the Chinese stock market was fairly good. Also, we found evidence that the behavior of foreign investors significantly decreased volatility in SSE stock returns. Consequently, the SH-HK Connect brought on a win-win effect for both the Chinese capital market and foreign investors. Originality/value - It appeared that the Chinese capital market was very suitable for Korean investors after the China's declaration of the SH-HK Connect. However, the win-win effect was brought on by the Chinese government's aggressive capital control but the capital controls could possibly cause financial turmoil in the Chinese capital market. Therefore, Chinese reform in industrial structure and the financial sector should keep pace with suitable capital control policies.

• Journal of Environmental Science International
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• v.31 no.9
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• pp.767-779
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• 2022

In this study, sediment cores were sampled from tidal flats (six sites) in the west and south coastal wetlands, the blue carbon stock in the tidal flat sediments was calculated, and the blue carbon stock characteristics and influencing factors were analyzed. The sediment particle size of the west coastal tidal flats was larger than that of the south coastal tidal flats, and the organic carbon content in the south coastal tidal flats was more than twice that of the west coastal tidal flats. Blue carbon stock per unit area was 28.4~36.8 Mg/ha on the west coastal tidal flats and 69.8~89.8 Mg/ha on the south coastal tidal flats, which was more than twice higher in the south coastal tidal flats than in the west coastal tidal flats. The total amount of blue carbon stock in the tidal flats was the highest in Suncheon Bay tidal flats at 153,626 Mg, and followed by Gomso Bay tidal flats at 141,750 Mg, Hampyeong Bay tidal flats at 58,420 Mg, Dongdae Bay tidal flats at 44,900 Mg, Cheonsu Bay tidal flats at 36,880 Mg, and Jinhae Bay tidal flats at 26,205 Mg. Blue carbon stock per unit area was higher in the south coastal tidal flats, but the total amount of blue carbon stock in the tidal flats was higher in the west coast. The slope of the regression function of blue carbon stock with respect to the organic carbon content in the tidal flat sediments was estimated to be about 0.05 to 0.07, and the slope of the regression function was higher in the west coastal tidal flats than in the south coastal tidal flats.

• Journal of Industrial Convergence
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• v.21 no.1
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• pp.87-93
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• 2023

Determining the timing of buying and selling in stock investment is one of the most important factors to increase the return on stock investment. Buying low and selling high makes a profit, but buying high and selling low makes a loss. The price is determined by the quantity of buying and selling, which determines the price of a stock, and buying and selling is also related to corporate performance and economic indicators. The fear and greed index provided by CNN uses seven factors, and by assigning weights to each element, the weighted average defined as greed and fear is calculated on a scale between 0 and 100 and published every day. When the index is close to 0, the stock market sentiment is fearful, and when the index is close to 100, it is greedy. Therefore, we analyze the trading criteria that generate the maximum return when buying and selling the US S&P 500 index according to CNN fear and greed index, suggesting the optimal buying and selling timing to suggest a way to increase the return on stock investment.

• International Area Studies Review
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• v.15 no.1
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• pp.219-240
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• 2011

The main purpose of this study is to analyze the effects of stock price and real estate price on the money demand. We investigated the demand for money for 25 money units of 10 countries. To estimate the money demand functions, Johansen's cointegration and ARDL-bounds test were employed. Additionally, Stock and Watson's DOLS method was applied to estimate long-run cointegration vectors. According to the results of cointegration test, stock price and real estate price are crucial in the long-run equilibrium relationship. There were no cointegration relationships among money demand, real income, interest rate, and exchange rate in 12 money unit models. However, by including stock price and real estate price on the tested models, we could find strong cointegration relationships, using ARDL-bounds test. The results of DOLS confirm that stock price and real estate price are effective factors influencing on money demands. Especially, the coefficient of real estate price is statistically significant in the 19 out of 20 money unit models. However, the direction and magnitude of coefficients of asset prices are different across countries and money units.