• Environmental and Resource Economics Review
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• v.16 no.4
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• pp.947-978
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• 2007

In this paper, we investigated a Value-at-Risk approach to the volatility of two crude oil markets (Brent and Dubai). We also assessed the performance of various VaR models (RiskMetrics, GARCH, IGARCH and FIGARCH models) with the normal and skewed Student-t distribution innovations. The FIGARCH model outperforms the GARCH and IGARCH models in capturing the long memory property in the volatility of crude oil markets returns. This implies that the long memory property is prevalent in the volatility of crude oil returns. In addition, from the results of VaR analysis, the FIGARCH model with the skewed Student-t distribution innovation predicts critical loss more accurately than other models with the normal distribution innovation for both long and short positions. This finding indicates that the skewed Student-t distribution innovation is better for modeling the skewness and excess kurtosis in the distribution of crude oil returns. Overall, these findings might improve the measurement of the dynamics of crude oil prices and provide an accurate estimation of VaR for buyers and sellers in crude oil markets.

• The Korean Journal of Applied Statistics
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• v.24 no.4
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• pp.597-607
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• 2011

Value at Risk(VaR) is being widely used as a simple tool for measuring financial risk. Although VaR has a few weak points, it is used as a basic risk measure due to its simplicity and easiness of understanding. However, it becomes very difficult to estimate the volatility of the portfolio (essential to compute its VaR) when the number of assets in the portfolio is large. In this case, we can consider the application of a dimension reduction technique; however, the ordinary factor analysis cannot be applied directly to financial data due to autocorrelation. In this paper, we suggest a dimension reduction method that uses the time-series factor analysis and DCC(Dynamic Conditional Correlation) GARCH model. We also compare the method using time-series factor analysis with the existing method using ordinary factor analysis by backtesting the VaR of real data from the Korean stock market.

• The Korean Journal of Financial Studies
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• v.11 no.1
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• pp.157-176
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• 2005

본 연구는 KOSPI자산 포트폴리오에 대한 VaR를 다양한 ARCH류 모형을 사용하여 추정하고 이들의 예측능력을 평가하였다. 활용된 모형은 우선 기본적인 GARCH(1,1)모형과 레버리지 효과를 감안한 TGARCH모형, 다양한 ARCH모형을 포괄할 수 있는 PGARCH모형, 변동성의 영속성을 고려한 IGARCH모형이 포함되었다. 모형 상호간의 성과비교에 추가하여 ARCH류 모형에서 수익률예측오차의 분포에 따라서 VaR의 예측성과가 얼마나 차이가 발생하는가를 확인하기 위하여 정규분포와 Student-t분포의 성과를 비교하였다. 마지막으로 VaR 추정시에 조건부평균을 무시하는 관례가 어느정도 타당성이 있는지를 확인하기 위하여 1시차 자기회귀과정에 입각한 조건부 평균을 감안한 결과를 검토하였다. ARCH류 모형에서 모형 설명력은 보다 정교한 모형인 TGARCH모형이나 PGARCH모형이 우월하게 나타났지만, VaR의 예측능력 우월성으로 이어지지는 않았다. Student-t분포를 가정한 경우 VaR모형 사후검증성과는 정규분포를 가정한 경우보다 모든 신뢰수준에서 개선되었으며, 조건부평균의 제거는 Student-t분포 가정하에서는 적합하지 않은 것으로 나타났다. ARCH류 모형에서 가장 단순한 형태인 IGARCH모형의 예측성과가 다른 모형들에 비하여 뒤떨어지지 않으며, 더욱 제약된 형태인 RiskMetrics의 EWMA모형이 사후검증에서 우수한 성과를 보여 단순한 모형의 유용성을 확인시켜주고 있다.

• The Korean Journal of Applied Statistics
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• v.24 no.5
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• pp.809-820
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• 2011

VaR(Value at risk) is a measure of market risk management and needs to be estimated for multiple distributions. In this paper, Copula functions are used to generate distributions of multivariate random variables. The dependence structure of random variables is classified by the exchangeable Copula, fully nested Copula, partially nested Copula. For the earning rate data of four Korean industries, the parameters of the Archimedean Copula functions including Clayton, Gumbel and Frank Copula are estimated by using three kinds of dependence structure. These Copula functions are then fitted to to the data so that corresponding VaR are obtained and explored.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.8 no.1
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• pp.65-75
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• 2009

A Vehicular Ad-Hoc Network (VANET) is a form of Mobile ad-hoc network, to provide temporary communications among nearby vehicles. Mobile node of VANET consumes energy and resource with participating in the member of network. Some node tends to have a selfishness to place one's own profits above cooperation with others. As result of selfish node, it reduces data accessibility and the efficiency of networks. In this paper, we propose noble method, Friendship-VaR that excludes selfish nodes from a group of VANET. Friendship-VaR enables to improve data accessibility by eliminating selfish nodes and sharing data among reliable nodes. Friendship-VaR determines selfishness of nodes by simple data exchange. The experiments shows proposed method outperform existing method in terms of data accessibility.

• Proceedings of the Korean Institute Of Construction Engineering and Management
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• autumn
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• pp.65-72
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• 2001

With the recent rising project complexities and competitive environments in the construction projects, a risk management is recognized as more important management tool than the others. However, as most risk management techniques applied to the construction projects are centered around their initial phases and risk analyses, they are not developed into general project management technique such as time management, cost management and quality management, etc., that are usually applied in the process of construction. Thus, this paper proposes a response process to construction project risks based on the risk threshold and its calculation methodology applying a concept of VaR to establish risk management as general management technique in the construction projects.

• The Korean Journal of Applied Statistics
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• v.29 no.4
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• pp.753-771
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• 2016

Value at Risk (VaR) is widely used as an important tool for risk management of financial institutions. In this paper we discuss estimation and back testing for VaR of the portfolio composed of KOSPI, Dow Jones, Shanghai, Nikkei indexes. The copula functions are adopted to construct the multivariate distributions of portfolio components from marginal distributions that combine extreme value theory and GARCH models. Volatility models with t distribution of the error terms using Gaussian, t, Clayton and Frank copula functions are shown to be more appropriate than the other models, in particular the model using the Frank copula is shown to be the best.

• Plant Biotechnology Reports
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• v.5 no.3
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• pp.289-295
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• 2011

The SpoU family of proteins catalyzes the methylation of transfer RNAs (tRNAs) and ribosomal RNAs (rRNAs). We characterized a putative tRNA/rRNA methyltransferase, VaSpoU1 of the SpoU family, from Viscum album (mistletoe). VaSpoU1 and other plant SpoU1s exhibit motifs of the SpoU methylase domain that are conserved with bacterial and yeast SpoU methyltransferases. VaSpoU1 transcripts were detected in the leaves and stems of V. album. VaSpoU1-GFP fusion proteins localized to both chloroplasts and mitochondria in Arabidopsis protoplasts. Sequence analysis similarly predicted that the plant SpoU1 proteins would localize to chloroplasts and mitochondria. Interestingly, mitochondrial localization of VaSpoU1 was inhibited by the deletion of a putative N-terminal presequence in Arabidopsis protoplasts. Therefore, VaSpoU1 may be involved in tRNA and/or rRNA methylation in both chloroplasts and mitochondria.

• Communications for Statistical Applications and Methods
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• v.15 no.5
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• pp.697-708
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• 2008

Operational risk is defined as the risk of loss resulting from inadequate or failed internal processes, people and systems, or external events. The advanced measurement approach proposed by Basel committee uses loss distribution approach(LDA) which quantifies operational loss based on bank's own historical data and measurement system. LDA involves two distribution fittings(frequency and severity) and then generates aggregate loss distribution by employing mathematical convolution. An objective validation for the operational risk measurement is essential because the operational risk measurement allows flexibility and subjective judgement to calculate regulatory capital. However, the methodology to verify the soundness of the operational risk measurement was not fully developed because the internal operational loss data had been extremely sparse and the modeling of extreme tail was very difficult. In this paper, we propose a methodology for the validation of operational risk measurement based on bootstrap confidence intervals of operational VaR(value at risk). We derived two methods to generate confidence intervals of operational VaR.

• The Korean Journal of Applied Statistics
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• v.24 no.5
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• pp.931-939
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• 2011

In practice, thresholds are determined by the two subjective assessment methods in a generalized pareto distribution of mean extreme function(MEF-graph) or Hill-graph. To remedy the problem of subjectiveness of these methods, we propose an alternative method to determine the threshold based on the robust statistics. We compared the MEF-graph, Hill-graph and our method through VaRs on the Korean stock market data from January 5, 1987 to August 3, 2009. As a result, the VaR based on the proposed method is not much different from the existing methods, and the standard deviation of VaR for our method was the smallest. The results show that our method can be a promising alternative to determine thresholds of the generalized pareto distributions.