• Korea Trade Review
• /
• v.48 no.4
• /
• pp.189-208
• /
• 2023

This paper analyzed the dynamic conditional correlation between the Korean ETS market, energy market and stock market. This paper conducted an empirical analysis using daily data of Korea's carbon credit trading price, WTI crude oil futures price, and KOSPI index from February 2, 2015 to December 30, 2021. First, the volatility of the three markets was analyzed using the GARCH model, and then the dynamic conditional correlations between the three markets were studied using the bivariate DCC-GARCH model. The research results are as follows. First, it was found that the Korean ETS market has a higher rate of return and higher investment risk than the stock market. Second, the yield volatility of the Korean ETS market was found to be most affected by external shocks and least affected by the volatility information of the market itself. Third, the correlation between the Korean ETS market and the stock market was stronger than that of the WTI crude oil futures market. This paper analyzed the correlation between the Korean ETS market, energy market, and stock market and confirmed that the level of financialization in the Korean ETS market is quite low.

• Management & Information Systems Review
• /
• v.38 no.4
• /
• pp.79-93
• /
• 2019

This study analyzed the information effect of KOSPI200 market and KOSPI200 futures market and volume synchronized probability of informed trading (VPIN). The data period is 760 days from July 8, 2015 to August 9, 2018, and the intraday trading data is used based on the trading period of the KOSPI 200 Index. The findings of the empirical analysis are as follows. First, as a result of regression analysis of the same parallax, when the level of VPIN is high, the return and volatility of KOSPI200 are high. Second, the KOSPI200 returns before and after the VPIN measurement and the return of the KOSPI200 future had a positive relationship with the VPIN. The cumulative returns of KOSPI200 futures were positive for about 15 minutes.Finally, we find that portfolios with high levels of VPIN showed high KOSPI200 and KOSPI200 futures return. These results confirmed the applicability of VPIN as a trading strategy index. The above results suggest that KOSPI200 and KOSPI200 futures markets will be able to explore volatility and price changes, and also be useful indicators of financial market risk.

• Journal of Convergence for Information Technology
• /
• v.11 no.9
• /
• pp.94-108
• /
• 2021

This study is to identify the internal and external factors of a company that can affect the rate of change in the inventory turnover ratio. In addition, by appropriately managing or responding to these factors, changes in the inventory turnover ratio do not occur abruptly, so that the company's business and financial performance can be improved. To confirm this, factors such as gross profit margin, cash flow volatility, advertising expenses, inflation, exchange rate rise, and leading economic index were selected, and these factors were predicted to affect the change rate of inventory turnover. Data of 85,878 companies were obtained from domestic securities listings, KOSDAQ listings, and externally audited companies, and multiple regression analysis was performed using the data. Gross profit margin and cash flow volatility have a significant positive (+) effect, advertising expenses have a negative (-) significant effect, and inflation and exchange rate rises have a negative (-) significant effect. As an influence, the leading economic index was tested to have a significant positive (+) effect. Through this, it is suggested that manufacturing companies can improve their business performance and achieve operational efficiency by well understanding and appropriately managing factors that can affect the change rate of inventory turnover.

• Journal of Digital Convergence
• /
• v.13 no.11
• /
• pp.45-55
• /
• 2015

This study used for KOSPI, KOSDAQ, entertainment culture and digital contents index that is related to cultural contents industry. There was investigated the each stock price index and return trends for a total 597 weeks to July 2015 from March 2004. They looked the content-related stocks about investment worth to comparative analysis the return, volatility, correlation, synchronization phenomena etc. of each stock index. When we saw the growth potential of the cultural contents industry forward, looked forward to the investment possibility of related stocks. Analysis Result cultural content related stocks showed a higher rate after the last 2008 global financial crisis. Recent as high interest in the cultural contents industry, we could see that the investment merit increases slowly. In the future, the cultural content industry is expected to continue to evolve. The increase of investments value in the cultural content related businesses is much expectation.

• The Journal of the Korea Contents Association
• /
• v.19 no.11
• /
• pp.549-557
• /
• 2019

The purpose of this study is to investigate the parallelism and volatility with Korea by using the Export Volume Index of Korea, Canada, Brazil, UK and Australia. The analysis period was prepared for indicator analysis, numerical analysis and model analysis using annual data for a total of 28 years from 1990 to 2017. In the correlation analysis, Korea showed high correlation in Canada, UK and Brazil, but low in Australia. In the coefficient of regression analysis, Brazil, Canada and UK are moving in a positive direction with their dependent variables (Korea), but appear to be almost unaffected by Australia. In order to increase Korea's exports in the future, Australia, Brazil, India, Vietnam and Singapore are emerging as new markets, which requires continuous attention. Although this study selected Canada, UK, Brazil, and Australia, it is expected that an objective and reliable study will be produced if more diverse countries are selected and analyzed in the future.

• Journal of Korea Port Economic Association
• /
• v.34 no.4
• /
• pp.181-190
• /
• 2018

The goal of this study is empirically to investigate the asymmetric relationship between two variables using the dry cargo freight rates and raw material price data from January 2012 to May 2018. First, we estimate the asymmetry of macroeconomic indicators of commodity prices by using a two - step threshold cointegration test. Second, the asymmetric relation test of the trade balance of existing commodity price changes is tested by bypassing to the high frequency dry cargo freight rate index. As a result of the estimation, in contrast to the existing linear analysis, each boundary value for the lower limit and the upper limit has different asymmetry. This implies that the period of fluctuation of the sudden residual that causes irregular rate of return fluctuations does not establish a long term equilibrium relationship between the raw material price and the dry cargo freight rate. Therefore, in order to consider the sudden price change in the analysis, it is necessary to include the band of inaction that controls the irregular volatility, which is consistent with the asymmetry hypothesis.

• Journal of Convergence for Information Technology
• /
• v.9 no.9
• /
• pp.133-140
• /
• 2019

Following the recent US trade deficit, the trade war began between Korea and Japan in July. Korea's trade dependence is about 60% or more, indicating high export dependence and import dependence. The purpose of this study is to examine export amount, export volume, export price index, Treasury bond interest rate and analyze how index affects export amount. This study attempts to analyze the comovement and volatility with export amount. For this purpose, monthly data for each indicator were selected for a total of 234 months from January 2000 to June 2019. As a result of analysis, exports amount and exports volume showed very high comovement, exports amount and interest rates showed low comovement, but exports amount and exports prices showed very low comovement. In the future, Korea should continue to increase exports amount in view of its high dependence on trade, along with policies to expand the domestic market. To this end, strategy to increase exports volume should be presented. Korea should increase the logistics environment and competitiveness of each port and airport, improve domestic and overseas network construction and support services of logistics companies.

• Journal of Intelligence and Information Systems
• /
• v.17 no.3
• /
• pp.187-201
• /
• 2011

KOSPI200 index is the Korean stock price index consisting of actively traded 200 stocks in the Korean stock market. Its base value of 100 was set on January 3, 1990. The Korea Exchange (KRX) developed derivatives markets on the KOSPI200 index. KOSPI200 index futures market, introduced in 1996, has become one of the most actively traded indexes markets in the world. Traders can make profit by entering a long position on the KOSPI200 index futures contract if the KOSPI200 index will rise in the future. Likewise, they can make profit by entering a short position if the KOSPI200 index will decline in the future. Basically, KOSPI200 index futures trading is a short-term zero-sum game and therefore most futures traders are using technical indicators. Advanced traders make stable profits by using system trading technique, also known as algorithm trading. Algorithm trading uses computer programs for receiving real-time stock market data, analyzing stock price movements with various technical indicators and automatically entering trading orders such as timing, price or quantity of the order without any human intervention. Recent studies have shown the usefulness of artificial intelligent systems in forecasting stock prices or investment risk. KOSPI200 index data is numerical time-series data which is a sequence of data points measured at successive uniform time intervals such as minute, day, week or month. KOSPI200 index futures traders use technical analysis to find out some patterns on the time-series chart. Although there are many technical indicators, their results indicate the market states among bull, bear and flat. Most strategies based on technical analysis are divided into trend following strategy and non-trend following strategy. Both strategies decide the market states based on the patterns of the KOSPI200 index time-series data. This goes well with Markov model (MM). Everybody knows that the next price is upper or lower than the last price or similar to the last price, and knows that the next price is influenced by the last price. However, nobody knows the exact status of the next price whether it goes up or down or flat. So, hidden Markov model (HMM) is better fitted than MM. HMM is divided into discrete HMM (DHMM) and continuous HMM (CHMM). The only difference between DHMM and CHMM is in their representation of state probabilities. DHMM uses discrete probability density function and CHMM uses continuous probability density function such as Gaussian Mixture Model. KOSPI200 index values are real number and these follow a continuous probability density function, so CHMM is proper than DHMM for the KOSPI200 index. In this paper, we present an artificial intelligent trading system based on CHMM for the KOSPI200 index futures system traders. Traders have experienced on technical trading for the KOSPI200 index futures market ever since the introduction of the KOSPI200 index futures market. They have applied many strategies to make profit in trading the KOSPI200 index futures. Some strategies are based on technical indicators such as moving averages or stochastics, and others are based on candlestick patterns such as three outside up, three outside down, harami or doji star. We show a trading system of moving average cross strategy based on CHMM, and we compare it to a traditional algorithmic trading system. We set the parameter values of moving averages at common values used by market practitioners. Empirical results are presented to compare the simulation performance with the traditional algorithmic trading system using long-term daily KOSPI200 index data of more than 20 years. Our suggested trading system shows higher trading performance than naive system trading.

• Journal of Korean Society of Water and Wastewater
• /
• v.22 no.5
• /
• pp.523-529
• /
• 2008

Algal blooms in a local eutrophic lake often produces the musty and earthy taste & odor problems. Since the odor causing compounds(OCCs) including geosmin and 2-MIB have their own volatility, the OCCs can be removed from water by air stripping methods. Removal of TON(threshold odor number) as an index for OCCs could be fitted well with the first order equations($R^2=0.9$ above), where the air stripping coefficient of TON, k was in the range between 0.0055 and 0.0097 according to the aeration time. k within 30min aeration tests was 0.0097, while it was 0.0055 where the aeration time extended to 150min. With 15 mg/L of PAC, removal of TON was not simulated with 1st order equation within 30min aeration. Within 30min aeration, OCCs rather than geosmin and/or 2-MIB could be removed easily by air stripping or PAC adsorption, while OCCs such as geosmin and/or 2-MIB could be removed slowly by air stripping after 30min aeration. Geosmin and 2-MIB were not readily removed by air stripping(k of them were 0.0018~0.0047 and 0.0018~0.0034, respectively at different air flow rates). Geosmin could be removed by air stripping a little better than 2-MIB.

• The Korean Journal of Applied Statistics
• /
• v.19 no.1
• /
• pp.33-41
• /
• 2006

In this paper, we analyse the volatilities in financial data such as stock prices and exchange rates in term of a class of nonlinear time series models. We compare the performance of Generalized Autoregressive Conditional Heteroscadastic(GARCH) , Integrated GARCH(IGARCH), Exponential GARCH(EGARCH) models by KOSPI (Korean stock Prices Index) data. The estimation for the parameters in the models was carried out by the ML methods.