• The Pure and Applied Mathematics
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• v.16 no.1
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• pp.121-131
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• 2009

In this paper we examine the relation among law-invariant coherent risk measures with the Fatou property, distortion risk measures and spectral risk measures, and give a new proof of the relation among them. It is also shown that the spectral risk measure satisfies the monotonicity with respect to stochastic dominance and the comonotonic additivity.

• Journal of The Korean Society of Agricultural Engineers
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• v.55 no.4
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• pp.73-82
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• 2013

The main objective of this study was to evaluate Representative Concentration Pathways (RCP) scenarios-based flood risk at a Si-Gun level. A bias correction using a quantile mapping method with the Generalized Extreme Value (GEV) distribution was performed to correct future precipitation data provided by the Korea Meteorological Administration (KMA). A series of proxy variables including CN80 (Number of days over 80 mm) and CX3h (Maximum precipitation during 3-hr) etc. were used to carry out flood risk assessment. Indicators were normalized by a Z-score method and weighted by factors estimated by principal component analysis (PCA). Flood risk evaluation was conducted for the four different time periods, i.e. 1990s, 2025s, 2055s, and 2085s, which correspond to 1976~2005, 2011~2040, 2041~2070, and 2071~2100. The average flood risk indices based on RCP4.5 scenario were 0.08, 0.16, 0.22, and 0.13 for the corresponding periods in the order of time, which increased steadily up to 2055s period and decreased. The average indices based on RCP8.5 scenario were 0.08, 0.23, 0.11, and 0.21, which decreased in the 2055s period and then increased again. Considering the average index during entire period of the future, RCP8.5 scenario resulted in greater risk than RCP4.5 scenario.

• 대한예방의학회:학술대회논문집
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• 1994.02a
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• pp.681-691
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• 1994

The American Conference of Governmental Industrial Hygienists (ACGIH) has proposed a threshold limit value (TLV) for benzene of 0.1 ppm. Individuals representing the American Petroleum Institute (API)and the Chemical Manufacturers Association (CMA) have argued that 1) the risk assessment by Rinsky .et al. which ACGIH partially relied upon for its proposed TLV overestimates the risk; however, at the exposures levels of interest - (e.g., 0.1 to 1.0 ppm) for establishing a benzene TLV, the Rinsky et al. assessment provides lower estimates of leukemia risk than most others; 2) ACGIH should not use the Dow study for direct observational evidence of leukemia risk associated with low-level benzene exposure because of confounding exposure; however, it is unlikely that confounding exposures played a role in the excess of leukemia demonstrated in the study, and the Dow cohort was exposed to an average benzene concentration of about 5.5 ppm benzene for 7.11 years (31:1.5 ppm-years), while some of the individuals in the study who died from leukemia were exposed to an average of only 1.0 ppm without the opportunity for highpeak exposures; 3) the Occupational Safety and Health Administration (OSHA) established an 8-hour time-weighted average (TWA) of 1.0 ppm in 1987, and there is no new evidence that would justify reducing the TWA below that level; however, the OSHA TWA of 1.0 ppm was based on economic feasibility and the level of excess risk remaining at 1.0 ppm, i.e., 10 excess leukemia deaths per 1000 workers over an occupational lifetime (45 years) according to OSHA's preferred estimate leaves behind I risk considered significant by OSHA. In addition, chromosomal studies among workers and in animals exposed to benzene indicate that low-level exposure, i.e., 1.0 ppm, is associated with elevated Cytogenetic damage. On the basis of adverse health effects data alone, in this author's opinion, it would be poor science and poor public health policy to establish a benzene TLV greater than 0.1 ppm.

• Asia-Pacific Journal of Business
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• v.12 no.1
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• pp.135-149
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• 2021

Purpose - I analyzes risk-to-performance evaluated in the market using data from sale and lease back. Specifically, I analyze from the perspective of financial institutions that purchase sale and lease back based on the cases of investment by ship investment companies and acquisition of ships. Design/methodology/approach - I use 49 sale and lease back data from 2017 to 2019 for empirical analysis. Findings - The main results of this paper are as follows. First, after sale and lease back of domestic ships, the average amount of sales by the leased shipping company is 25.1 billion won, the average amount of investment by the purchased financial institution is 14.6 billion won (60%) and the average length of the ship is nine years. In ship finance, sale and lease back is deemed to be appropriately used as a means of restructuring for a large amount of money. Second, the main risk factor for sale and lease back of domestic ships is credit risk and can be measured in VaR in practice. As a result of the empirical analysis, the average credit risk burden ratio is 9%. As a major risk factor, low creditworthiness of restructuring companies is the key. Third, as a result of measuring the profitability of financial institutions that purchase sale and lease back of domestic ships at a net current price, it has an average value of 300 million won, but the deviation by case is very large. Fourth, the risk adjusted performance of sale and lease back of domestic ships is 0.54 on average compared to the total risk capital, and 0.52 compared to the stock-risk capital, and as with profitability earlier, the deviation of each case is very large and misaligned. In order to boost the sale and lease back market for large and long-term assets, in order to overcome low profitability as a prerequisite for future participation of commercial purchased financial institutions, it is expected that purchase decisions based on expectations versus risk will be necessary. Research implications or Originality - The results of this paper are expected to broaden the understanding of sale and lease back and foster the ability to assess long-term risk and performance. Based on this, it is believed that rapid restructuring of companies through sale and lease back of large amounts of long-term assets will greatly increase the utility of the domestic financial market.

• Journal of the Korean Data and Information Science Society
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• v.22 no.6
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• pp.1065-1074
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• 2011

During several decades, many researchers in the field of finance have studied Value at Risk (VaR) to measure the market risk. VaR indicates the worst loss over a target horizon such that there is a low, pre-specified probability that the actual loss will be larger (Jorion, 2006, p.106). In this paper, we compare conditional copula method with two conventional VaR forecasting methods based on simple moving average and exponentially weighted moving average for measuring the risk of the portfolio, consisting of two domestic stock indices. Through real data analysis, we conclude that the conditional copula method can improve the accuracy of portfolio VaR forecasting in the presence of high kurtosis and strong correlation in the data.

• Journal of Environmental Health Sciences
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• v.36 no.6
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• pp.456-464
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• 2010

Recently, heavy metals contamination of the agricultural soil and crops surrounding mining areas has been identified as one of the most serious environmental problems in South Korea. The Ministry of the Environment in Korea conducted a Preliminary National Environmental Health Survey (PNEHS) in abandoned metal mines in 2007. The priority for a subsequent detailed examination was ranked from the results of PNEHS. The studied mine which was ranked as being of the highest priority is located in the midwestern part of Korea and was operated from 1911 to 1985. In this study, the contamination levels of the heavy metals in the abandoned metal mine were investigated. From the results, the average daily dose (ADD), target hazard quotient (THQ) and target cancer risk of the heavy metals were evaluated. The concentration of arsenic (As) in all of the tailings from the mine was higher than its countermeasure standard of Korea. In particular, the highest concentration of As, 330 mg/kg, was up to 15 times higher than its countermeasure standard. The average concentration of As in agricultural soils was higher than the warning standard of Korea, and higher than its countermeasure standard at six sites. The average concentrations of the analyzed heavy metals in agricultural soil were below the warning standard, but concentrations of cadmium (Cd) and lead (Pb) at 4 sites were higher than its warning standard. The average concentration of As in surface water exceeded the warning standard of Korea. The value of the THQ of As for the tailings was higher than the health protection standard 1. The value of THQ of As for the farmlands was lower than the standard, while the hazard index (HI) of As was higher than the standard. The value of target cancer risk (TCR) of As, $6.44{\times}10^{-4}$, were higher than the health protection standard of a lifetime risk for TCR at $1{\times}10^{-6}$. This suggests that the residents around the metal mines are exposed to As pollution with a carcinogenic risk.

• Journal of the Korean Operations Research and Management Science Society
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• v.37 no.3
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• pp.135-150
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• 2012

This paper presents a portfolio model for a long-term power generation mix problem. The proposed portfolio model evaluates generation mix by considering the tradeoffs between the expected cost for power generation and its variability. Unlike conventional portfolio models measuring variance, we introduce Conditional Value-at-Risk (CVaR) in designing the variability with aims to considering events that are enormously expensive but are rare such as nuclear power plant accidents. Further, we consider uncertainties associated with future electricity demand, fuel prices and their correlations, and capital costs for power plant investments. To obtain an objective generation by each energy source, we employ the sample average approximation method that approximates the stochastic objective function by taking the average of large sample values so that provides asymptotic convergence of optimal solutions. In addition, the method includes Monte Carlo simulation techniques in generating random samples from multivariate distributions. Applications of the proposed model and method are demonstrated through a case study of an electricity industry with nuclear, coal, oil (OCGT), and LNG (CCGT) in South Korea.

• Proceedings of the KSR Conference
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• 2011.10a
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• pp.3099-3103
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• 2011

In measurement of risk voltages; the step and touch voltage, the distance between the current electrode and the ground electrode recedes up to several hundred meters as the scale of grounding system increases. This paper dealt with the measurement method of risk voltage in a restricted space. The risk voltage was analyzed depending on the distance and the direction of the current electrode from the ground electrode in a $10[m]{\times}10[m]$ mesh grounding system. The average value of risk voltages measured at a point 20 [m] away from the current electrode was deviated below 5 [%] from that measured at 100 [m] point. Consequently, the evaluation of risk voltage of a large-scale grounding system buried in a spatially restricted place is available if the current electrode is installed in symmetry to the ground electrode.

• Journal of the Korean Data and Information Science Society
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• v.18 no.4
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• pp.915-925
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• 2007

Multivariate GARCH has been useful to model dynamic relationships between volatilities arising from each component series of multivariate time series. Methodologies including EWMA(Exponentially weighted moving-average model), DVEC(Diagonal VEC model), BEKK and CCC(Constant conditional correlation model) models are comparatively reviewed for bivariate time series. In addition, these models are applied to evaluate VaR(Value at Risk) and to construct joint prediction region. To illustrate, bivariate stock prices data consisting of Samsung Electronics and LG Electronics are analysed.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2022.11a
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• pp.133-134
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• 2022

Recently, the criteria for assessing industrial accidents have been replaced by the mortality rate. It was found that the number of deaths from excavation work was the highest among construction machinery. The risk assessment is being conducted, however the industrial accident mortality rate has not decreased. Accordingly, this study aims to provide the basic for the create of a risk assessment model specialized in construction work at excavator. It provides absolute value from the risk model which is capable of delivery the probability of a disaster. In addition, we provide a relative risk model that compares the risk through scores between detailed works. The relative risk model is combined by likelihood and severity; the likelihood indicates the frequency of accidents and the severity indicates seriousness of fatal accidents. A variable that reflects the conditions of the construction site was added to the risk assessment model based on past disaster cases. And using the concepts of probability and average, the risk assessment process was quantified and used as an objective indicator. Therefore, the model is expected to reduce disasters by raising the awareness of disasters.