• Journal of Korea Port Economic Association
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• v.38 no.4
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• pp.107-118
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• 2022

In this study, daily data from January 2002 to June 2022 were used to investigate the relationship between risk-return relationship and market fear, uncertainty, stock market, and maritime freight index for the crude oil market. For this study, the time varying EGARCH-M model was applied to the risk-return relationship, and the wavelet consistency model was used to analyze the relationship between market fear, uncertainty, stock market, and maritime freight index. The analysis results of this study are as follows. First, according to the results of the time-varying risk-return relationship, the crude oil market was found to be related to high returns and high risks. Second, the results of correlation and Granger causality test, it was found that there was a weak correlation between the risk-return relationship and VIX, EPU, S&P500, and BDI. In addition, it was found that there was no two-way causal relationship in the risk-return relationship with EPU and S&P500, but VIX and BDI were found to affect the risk-return relationship. Third, looking at the results of wavelet coherence, it was found that the degree of the risk-return relationship and the relationship between VIX, EPU, S&P500, and BDI was time-varying. In particular, it was found that the relationship between each other was high before and after the crisis period (financial crisis, COVID-19). And it was found to be highly associated with organs. In addition, the risk-return relationship was found to have a positive relationship with VIX and EPU, and a negative relationship with S&P500 and BDI. Therefore, market participants should be well aware of economic environmental changes when making decisions.

• Journal of the Korean Society of Safety
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• v.32 no.5
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• pp.157-167
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• 2017

Millions of People die every year from diseases caused by exposure to outdoor air pollution. Especially, one of the most severe types of air pollution is fine particulate matter (PM10, PM2.5). South Korea also has been suffered from severe PM. This paper analyzes regional risks induced by PM10 and PM2.5 that have affected domestic area of Korea during 2014~2016.3Q. We investigated daily maxima of PM10 and PM2.5 data observed on 284 stations in South Korea, and found extremely high outlier. We employed extreme value distributions to fit the PM10 and PM2.5 data, but a single distribution did not fit the data well. For theses reasons, we implemented extreme mixture models such as the generalized Pareto distribution(GPD) with the normal, the gamma, the Weibull and the log-normal, respectively. Next, we divided the whole area into 16 regions and analyzed characteristics of PM risks by developing the FN-curves. Finally, we estimated 1-month, 1-quater, half year, 1-year and 3-years period return levels, respectively. The severity rankings of PM10 and PM2.5 concentration turned out to be different from region to region. The capital area revealed the worst PM risk in all seasons. The reason for high PM risk even in the yellow dust free season (Jun. ~ Sep.) can be inferred from the concentration of factories in this area. Gwangju showed the highest return level of PM2.5, even if the return level of PM10 was relatively low. This phenomenon implies that we should investigate chemical mechanisms for making PM2.5 in the vicinity of Gwangju area. On the other hand, Gyeongbuk and Ulsan exposed relatively high PM10 risk and low PM2.5 risk. This indicates that the management policy of PM risk in the west side should be different from that in the east side. The results of this research may provide insights for managing regional risks induced by PM10 and PM2.5 in South Korea.

• Journal of Korean Institute of Industrial Engineers
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• v.39 no.6
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• pp.535-545
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• 2013

The goal of stock investment is earning high rate or return with stability. To accomplish this goal, using a portfolio that distributes stocks with high rate of return with less variability and a stock price prediction model with high accuracy is required. In this paper, three methods are suggested to require these conditions. First of all, in portfolio re-balance part, Max-Return and Min-Risk (MRMR) model is suggested to earn the largest rate of return with stability. Secondly, Entering/Leaving Rule (E/L) is suggested to upgrade portfolio when particular stock's rate of return is low. Finally, to use outstanding stock price prediction model, a model based on Semi-Supervised Learning (SSL) which was suggested in last research was applied. The suggested methods were validated and applied on stocks which are listed in KOSPI200 from January 2007 to August 2008.

• Environmental and Resource Economics Review
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• v.15 no.2
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• pp.319-353
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• 2006

This paper shows how weather derivatives can be used to hedge against the price risk and volume risk of purchasing relatively large amounts of electricity. Our specific approach to designing new contracts for electricity is to focus on the return over a summer season rather than on the daily levels of demand and price. It is shown that correct market signals can be preserved in a contract and the associated financial risk can be offset by weather options. The advantage of combining a forward contract with a weather derivative is that the high prices on hot days or when the temperature is high reflect the underlying high cost of producing power when the load is high and that the combined contract with a weather derivative substantially reduces the volatility of the return.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.17 no.1
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• pp.29-43
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• 2022

This study measures the realized rate of return of venture capital(VC) fund at the level of investment agreement(as opposed to fund level returns reported by most of the relevant studies). It also measures the stock price return of the VC's portfolio firms (unlisted start-ups) at firm level(as opposed to fund returns) and its variance for the first time using unique data of the VC funds held by the Korean Venture Capital Association. Results of the analysis confirm that VC fund returns exceed individual stock price returns. Additionally, it is confirmed that VC portfolio firms exhibit a positive relationship between risk and return measured by total risk. Finally, we find that stock price returns at firm level are lower than that implied by the associated levels of risk. Consequently, this may make individual investors hesitate to directly buy unlisted startups' stocks even when investment in individual startup companies guarantees high risk-high returns relationship.

• Korean System Dynamics Review
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• v.8 no.1
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• pp.173-186
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• 2007

This research consists of (1) building (or molding) the Dynamics Simulation Model on Return Policy mainly used in publications, phonographs, and computer industry; which are seen used in supply chain contract known as effective control mechanism under the varied supply chain situations, and (2) analyzing the effects that return rates and seller's contract parameters have in the outcome of the model and (3) observing how the effectiveness of Return Policy changes under such circumstances where the buyer's sales ability and the seller's risk inclination are taken into account. Thus, the main purpose of this research lies in analyzing what exactly are the effects (and or outcome) that sales ability and risk inclination have in Return Policy, and additionally by conducting comprehensive research on Supply Chain Policy Dynamics Simulation Model, we will try to prove that not only the Systems Dynamics approach is highly contributive in supply chain management but also that it will serve as a foothold in future research. As a result of the research, supply chain achievement level turned out to be high when Return Policy is enforced, and the achievement level was even higher when seller's sales ability was taken into consideration along with the Return Policy. On the other hand, the achievement level decreased when the seller had risk aversive tendencies.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.11
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• pp.45-53
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• 2020

Past literatures have not studied the impact of real-world events or information on the return and volatility of virtual currencies, particularly on the COVID-19 event, day-of-the-week effect, daily high-low price spreads and information flow rate. The study uses the ARMA-GARCH model to capture Bitcoin's return and conditional volatility, and explores the impact of information flow rate on conditional volatility in the Bitcoin market based on the Mixture Distribution Hypothesis (Clark, 1973). There were 3,064 samples collected during the period from 1^st of January 2012 to 20^th April, 2020. Empirical results show that in the Bitcoin market, a daily high-low price spread has a significant inverse relationship for daily return, and information flow rate has a significant positive relationship for condition volatility. The study supports a significant negative relationship between information asymmetry and daily return, and there is a significant positive relationship between daily trading volume and condition volatility. When Bitcoin trades on Saturday & Sunday, there is a significant reverse relationship for conditional volatility and there exists a day-of-the-week volatility effect. Under the impact of COVID-19 event, Bitcoin's condition volatility has increased significantly, indicating the risk of price changes. Finally, the Bitcoin's return has no impact on COVID-19 events and holidays (Saturday & Sunday).

• Journal of Preventive Medicine and Public Health
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• v.52 no.4
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• pp.234-241
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• 2019

Objectives: To identify simultaneous behavioral changes in alcohol consumption, smoking, and weight using a fixed-effect model and to characterize their associations with disease status. Methods: This study included 7 000 529 individuals who participated in the national biennial health-screening program every 2 years from 2009 to 2016 and were aged 40 or more. We reconstructed the data into an individual-level panel dataset with 4 waves. We used a fixed-effect model for smoking, heavy alcohol drinking, and overweight. The independent variables were sex, age, lifestyle factors, insurance contribution, employment status, and disease status. Results: Becoming a high-risk drinker and losing weight were associated with initiation or resumption of smoking. Initiation or resumption of smoking and weight gain were associated with non-high-risk drinkers becoming high-risk drinkers. Smoking cessation and becoming a high-risk drinker were associated with normal-weight participants becoming overweight. Participants with newly acquired diabetes mellitus, ischemic heart disease, stroke, and cancer tended to stop smoking, discontinue high-risk drinking, and return to a normal weight. Conclusions: These results obtained using a large-scale population-based database documented interactions among lifestyle factors over time.

• Journal of Chest Surgery
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• v.32 no.11
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• pp.1004-1008
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• 1999

Background: Total anomalous pulmonary venous return is a relatively rare disease which has a very high mortality(80% within a year) if not properly corrected surgically. Material and Method: Twenty-six infants with total anomalous pulmonary venous return underwent repair between May, 1991 and February, 1996. Result: There were 19 boys and 7 girls. The mean age at operation was 2.6 months(range: 5 day to 11 month) and the mean body weight was 4.3kg(range:2.8 to 6.7 kg). Preoperative stabilization included ventilator for 5 patients and inotropic support for 6 patients. There were 6 hospital mortalities. Significant risk factors of operative mortality were preoperative ventilator care(p<0.03) and preoperative inotropic support(p<0.05). Age, body weight at operation, pulmonary venous obstruction, high pulmonary arterial pressure, spurasystemic right ventricular pressure or emergency operation did not affected the operative outcome. Postperative pulmonary venous obstruction occurred in three patients 2 or 3 months later, among them one patient was reoperated. The actuarial survival was 76% at 40 months. Conclusion: Although early mortality was high, repair of total anomalous pulmonary venous return should be attempted in early life, but the patients receiving ventilator care or inotropic support need special attention.

• Communications for Statistical Applications and Methods
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• v.28 no.1
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• pp.59-79
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• 2021

Value at Risk (VaR) is one of the most common risk management tools in finance. Since a portfolio of several assets, rather than one asset portfolio, is advantageous in the risk diversification for investment, VaR for a portfolio of two or more assets is often used. In such cases, multivariate distributions of asset returns are considered to calculate VaR of the corresponding portfolio. Copulas are one way of generating a multivariate distribution by identifying the dependence structure of asset returns while allowing many different marginal distributions. However, they are used mainly for bivariate distributions and are not widely used in modeling joint distributions for many variables in finance. In this study, we would like to examine the performance of various copulas for high dimensional data and several different dependence structures. This paper compares copulas such as elliptical, vine, and hierarchical copulas in computing the VaR of portfolios to find appropriate copula functions in various dependence structures among asset return distributions. In the simulation studies under various dependence structures and real data analysis, the hierarchical Clayton copula shows the best performance in the VaR calculation using four assets. For marginal distributions of single asset returns, normal inverse Gaussian distribution was used to model asset return distributions, which are generally high-peaked and heavy-tailed.