• 지능정보연구
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• 제8권1호
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• pp.1-13
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• 2002

비상장기업이나 신규상장기업의 경우 주식거래량과 거래가격이 없거나 불충분하므로 최근 활발히 연구되고 있는 VaR(Value-at-Risk)를 파악하지 못한다. 본 연구에서는 비상장기업 및 신규상장기업의 미래 가격위험의 척도인 VaR를 추정하는 방법론을 제시하고, 이를 시스템(VAS-CBR)으로 구현하였다. 구체적으로는 사례기반추론(Case Based Reasoning: CBR) 기법을 이용하여 기존의 상장회사들 중에서 신규 및 비상장기업과 유사한 재무적, 비재무적 특성을 갖는 상장기업을 찾아내고, 유사기업의 VaR를 근거로 신규 및 비상장기업의 VaR를 간접적으로 추정하였다. 또한 개발 시스템의 예측력 제고를 위한 운용방안 및 시스템의 예측력을 실험을 통하여 밝혔다.

• 응용통계연구
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• 제26권1호
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• pp.163-185
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• 2013

본 논문에서는 장기기억 변동성 모형의 필요성을 Value-at-Risk(VaR) 추정의 관점에서 알아본다. 이를 위해, KOSPI 수익률의 VaR을 FIGARCH, FIEGACH와 같은 장기기억 변동성 모형과 GARCH, EGARCH와 같은 단기기억 변동성 모형을 적용하여 각각 추정한 후, 각 변동성 모형에 따른 추정의 적절성을 사후검증을 통하여 비교해 본다. 사후검증을 통해, KOSPI 수익률 과정이 장기기억 속성을 가짐을 확인할 수 있으며, 적절한 VaR의 추정을 위해서는 장기기억 변동성 모형을 적용하는 것이 필요함을 알 수 있다.

• 유통과학연구
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• 제11권10호
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• pp.55-62
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• 2013

Purpose - The purpose of this study is to suggest a risk factor that significantly explains foreign currency risk premia. In recent years, some studies have found that the performance of the simultaneous consumption risk model improves considerably when tested on foreign currency portfolios, which are constructed based on the international interest rates differentials. However, this paper focuses on the long-run consumption risk factor. In our empirical research, we found that the real excess returns of high interest rate currency portfolios depreciate on average, when the future American long-run consumption growth rate appears low. This makes the high interest rate currency portfolios have relatively high risk premia. Meanwhile, the real excess returns of low interest rate currency portfolios appreciate on average, under the same conditions, which results in relatively low risk premia for these portfolios. Therefore, this long-run consumption risk factor might explain why low interest rate currencies do not appreciate as much as the interest rate differential, and why high interest rate currencies do not depreciate as much as the interest rate differential. Research design, data, methodology - In our explanation, we provide new evidence on the success of long-run consumption risks in currency risk premia by focusing on the long-run consumption risks borne by American representative investors. To uncover the hidden link between exchange rates and long-run consumption growth, we set the eight currency portfolios as our basic assets, which have been built based on the foreign interest rates of eighty countries. As these eight currency portfolios are rebalanced every year, the first group always contains the lowest interest rate currencies, and the last group contains the highest interest rate currencies. Against these basic eight currency portfolios, we estimate the long-run consumption risk model. We use recursive utility framework and the stochastic discount factor that depends on the present value of expected future consumption growth rates. We find that our model is optimized in the two-year period of constructing the durable consumption expectation factor. Our main results surprisingly surpass the performance of the existing benchmark simultaneous consumption model in terms of R², relatively risk aversion coefficient γ, and p-value of J-test. Results - The performance of our model is superior. R², relatively risk aversion coefficient γ, and p-value of J-test of our long-run durable consumption model are 90%, 93%, and 65.5%, respectively, while those of EZ-DCAPM are 87%, 113%, and 62.8%, respectively. Thus, we can speculate that the risk premia in foreign currency markets have been determined by the long-run consumption risk. Conclusions - The aggregate long-run consumption growth risk explains a large part of the average change in the real excess returns of foreign currency portfolios. The real excess returns of high interest rate currency portfolios depreciate on average when American long-run consumption growth rate is low, and the real excess returns of low interest rate currency portfolios appreciate under the same conditions. Thus, the low interest rate currency portfolios allow investors to hedge against aggregate long-run consumption growth risk.

• 산업공학
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• 제24권2호
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• pp.119-127
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• 2011

Most companies have been increasing temporary work projects to maximize the usage of their resources. They also have been developing the effective techniques for analyzing and managing the state of the projects. In order to monitor the state of a project in real-time and predict the project's future state more accurately, this paper suggests the Bayesian Network (BN) as a tool for discovering the causes of project risk and presenting the failure probability of the project. The proposed BN modeling method with consideration of the Earned Value Management (EVM) method shows how to induce the predictive and conditional probability of the risk occurrence in the future. The advantages of the suggested model are (1) that the cause of a project risk can be easily figured out via the BN, (2) that the future value of the project can be sufficiently increased by updating relevant components of the project, and (3) that more credible prediction can be made in the similar and future situation by using the data obtained in current analysis. A numerical example is also given.

• 재무관리연구
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• 제24권3호
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• pp.153-186
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• 2007

It is well known that the distributional properties of financial asset returns exhibit fatter-tails and skewer-mean than the assumption of normal distribution. The correct assumption of return distribution might improve the estimated performance of the Value-at-Risk(VaR) models in financial markets. In this paper, we estimate and compare the VaR performance using the RiskMetrics, GARCH and FIGARCH models based on the normal and skewed-Student-t distributions in two daily returns of the Korean Composite Stock Index(KOSPI) and Korean Won-US Dollar(KRW-USD) exchange rate. We also perform the expected shortfall to assess the size of expected loss in terms of the estimation of the empirical failure rate. From the results of empirical VaR analysis, it is found that the presence of long memory in the volatility of sample returns is not an important in estimating an accurate VaR performance. However, it is more important to consider a model with skewed-Student-t distribution innovation in determining better VaR. In short, the appropriate assumption of return distribution provides more accurate VaR models for the portfolio managers and investors.

• Communications for Statistical Applications and Methods
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• 제28권1호
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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.

• 한국기술혁신학회:학술대회논문집
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• 한국기술혁신학회 2000년도 추계 학술대회(The 2000 Autumn Conference of korea Technology Inovation Society)(한국기술혁신학회)
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• pp.259-277
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• 2000

In this paper, we suggest theoretical grounds on the problem of R&D portfolio with different option premiums utilizing the Real Options Model, which has received intensified attention as the method of assessment of R&D project with high risk. Even though there have been many studies focused on the evaluation of option value of single project from technology valuation's perspective. there are few study on the portfolio of multiple technology investment by option value using. This paper bears practical importance by showing simple examples with the option value of investment alternatives and the valuation of related risk, the construction of optimum portfolio in technology investment alternatives.

• 대한안전경영과학회지
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• 제15권3호
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• pp.1-6
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• 2013

This study was conducted to compare the value of the working environment measurement with the expected exposure value drawn by using a program, thereby going to investigate whether it is available to the risk assessment of domestic workplace. We used the ECETOC TRA program which is one of the exposure predictive models. Four kinds of substances were measured in two workplace which was exposed to organic solvents and one kind of substance was measured in three workplace which was exposed to dusts and then an exposure assessment of chemical risk factors was conducted. The result value of the working environment measurement, solid substance exceeded standard in one site, and it was found that the other solid and liquid substances were within the standard. The value of the exposure assessment program showd the same result; it was higher than the value of the working environment measurement, suggesting that due to its nature, the exposure assessment program is run only on the worst situation. Therefore, it was found that when the exposure assesment program is used, variables should be substituted only after accurately assessing the workplace and it is a good idea to assess the risk beforehand with the exposure assessment program in the case of the workplace which employs no more than 5 people and where it is hard to assess the working environment.

• 한국물환경학회지
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• 제27권3호
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• pp.364-370
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• 2011

Water quality criteria for human health protection are derived based on the human health risk assessment. Water quality criteria in Korean freshwater bodies have been derived according to the equations developed by the US Environmental Protection Agency. The equations include the fish intake parameter, which is very important factor that significantly influences on the criteria derivation. So far, several fish intake values were used in human health risk assessment for water quality standards and effluent standards. However, these values are not consistent and they refer to various sources. Therefore, there is a need to suggest the most appropriate value of fish intake parameter to derive freshwater quality criteria in Korea. In this study, national and international fish intake values were widely collected and evaluated to select the adequate value of fish intake parameter that can be applied in Korea. The USEPA presented fish intake parameter as the 17.5 g/day for general adults and sport fishers and 142.4 g/day for subsistence fishers. In Korean reports, wide range values of 2 to 67.7 g/day were suggested as fish intake value. These values included finfish and shellfish intakes in common but had various habits. This study found that the 52.4 g/day suggested in Korean Exposure Factors Handbook published by the Ministry of Environment in 2007 seemed to be the suitable fish intake parameter to derive the freshwater quality criteria in Korea. The value is based on water corrected intakes of finfish and shellfish present in freshwater and coastal areas. We expect that this report can be useful to select suitable fish intake value in human health risk assessment for establishing freshwater quality standard in Korea.

• 한국안전학회지
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• 제33권6호
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• pp.77-84
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• 2018

Report documents of industrial and occupational accidents have continuously been accumulated in private and public institutes. Amongst others, information on narrative-texts of accidents such as accident processes and risk factors contained in disaster report documents is gaining the useful value for accident analysis. Despite this increasingly potential value of analysis of text information, scientific and algorithmic text analytics for safety management has not been carried out yet. Thus, this study aims to develop data processing and visualization techniques that provide a systematic and structural view of text information contained in a disaster report document so that safety managers can effectively analyze accident risk factors. To this end, the risk factor map using text mining and self-organizing map is developed. Text mining is firstly used to extract risk keywords from disaster report documents and then, the Self-Organizing Map (SOM) algorithm is conducted to visualize the risk factor map based on the similarity of disaster report documents. As a result, it is expected that fruitful text information buried in a myriad of disaster report documents is analyzed, providing risk factors to safety managers.