• Title/Summary/Keyword: Risk based Value Index

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Prediction of coal and gas outburst risk at driving working face based on Bayes discriminant analysis model

  • Chen, Liang;Yu, Liang;Ou, Jianchun;Zhou, Yinbo;Fu, Jiangwei;Wang, Fei
    • Earthquakes and Structures
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    • v.18 no.1
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    • pp.73-82
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    • 2020
  • With the coal mining depth increasing, both stress and gas pressure rapidly enhance, causing coal and gas outburst risk to become more complex and severe. The conventional method for prediction of coal and gas outburst adopts one prediction index and corresponding critical value to forecast and cannot reflect all the factors impacting coal and gas outburst, thus it is characteristic of false and missing forecasts and poor accuracy. For the reason, based on analyses of both the prediction indicators and the factors impacting coal and gas outburst at the test site, this work carefully selected 6 prediction indicators such as the index of gas desorption from drill cuttings Δh2, the amount of drill cuttings S, gas content W, the gas initial diffusion velocity index ΔP, the intensity of electromagnetic radiation E and its number of pulse N, constructed the Bayes discriminant analysis (BDA) index system, studied the BDA-based multi-index comprehensive model for forecast of coal and gas outburst risk, and used the established discriminant model to conduct coal and gas outburst prediction. Results showed that the BDA - based multi-index comprehensive model for prediction of coal and gas outburst has an 100% of prediction accuracy, without wrong and omitted predictions, can also accurately forecast the outburst risk even for the low indicators outburst. The prediction method set up by this study has a broad application prospect in the prediction of coal and gas outburst risk.

Triglyceride and Glucose (TyG) Index is a Clinical Surrogate Marker for the Diagnosis of Metabolic Syndrome

  • Shin, Kyung-A
    • Biomedical Science Letters
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    • v.23 no.4
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    • pp.348-354
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    • 2017
  • TyG (triglyceride and glucose) index using triglyceride and fasting blood glucose is recommended as a useful marker for insulin resistance. The present study evaluated the usefulness of TyG index in diagnosing metabolic syndrome and suggested an optimal cut-off value. The subjects of this study were adult 4,415 adults aged 20 to 80 years who underwent health screening at J General Hospital from January 2016 to January 2017. Metabolic syndrome was based on AHA/NHLBI (American Heart Association/National Heart, Lung, and Blood Institute) criteria. TyG index correlated with metabolic syndrome risk factors including HOMA-IR. Compared with the participants in the lowest quartile of TyG index, odds ratios and 95% confidence intervals for metabolic syndrome were 8.5 (3.005~23.903), 20.0 (17.190~23.407) for those in the third, and the fourth quartile of TyG index. The optimal cut-off value of the metabolic syndrome was 8.81 for TyG index (sensitivity 86.7%, specificity 80.1%) and area under the ROC curve (AUC) was 0.894. In conclusion, TyG index is effective to identify individuals at risk for metabolic syndrome.

Performance Analysis of Economic VaR Estimation using Risk Neutral Probability Distributions

  • Heo, Se-Jeong;Yeo, Sung-Chil;Kang, Tae-Hun
    • The Korean Journal of Applied Statistics
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    • v.25 no.5
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    • pp.757-773
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    • 2012
  • Traditional value at risk(S-VaR) has a difficulity in predicting the future risk of financial asset prices since S-VaR is a backward looking measure based on the historical data of the underlying asset prices. In order to resolve the deficiency of S-VaR, an economic value at risk(E-VaR) using the risk neutral probability distributions is suggested since E-VaR is a forward looking measure based on the option price data. In this study E-VaR is estimated by assuming the generalized gamma distribution(GGD) as risk neutral density function which is implied in the option. The estimated E-VaR with GGD was compared with E-VaR estimates under the Black-Scholes model, two-lognormal mixture distribution, generalized extreme value distribution and S-VaR estimates under the normal distribution and GARCH(1, 1) model, respectively. The option market data of the KOSPI 200 index are used in order to compare the performances of the above VaR estimates. The results of the empirical analysis show that GGD seems to have a tendency to estimate VaR conservatively; however, GGD is superior to other models in the overall sense.

Risk assessment of heavy metals in soil based on the geographic information system-Kriging technique in Anka, Nigeria

  • Johnbull, Onisoya;Abbassi, Bassim;Zytner, Richard G.
    • Environmental Engineering Research
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    • v.24 no.1
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    • pp.150-158
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    • 2019
  • Soil contaminated with heavy metals from artisanal gold mining in Anka Local Government Area in Northwestern Nigeria was investigated to evaluate the human health risk as a result of heavy metals. Measured concentration of heavy metals and exposure parameters were used to estimate human carcinogenic and non-carcinogenic risk. GIS-based Kriging method was utilized to create a prediction maps of human health risks and probability maps of heavy metals concentrations exceeding their threshold limits. Hazard index calculation showed that 21 out of 23 locations are posing non-cancer risk for children. Adults and children are at high cancer risk in all locations as the total cancer risk exceeded $1{\times}10^{-6}$ (the lower limit CTR value). Kriging model showed that only a very small area in Anka has a hazard index of less than unity and cumulative target risk of less than $1{\times}10^{-4}$, indicating a significant carcinogenic and non-carcinogenic risks for children. The probability of heavy metals to exceed their threshold concentrations around the study area was also found to be high.

Risk Assessment of Drought for Regional Upland Soil According to RCP8.5 Scenario Using Soil Moisture Evaluation Model (AFKE 0.5)

  • Seo, Myung-Chul;Cho, Hyeon-Suk;Seong, Ki-Yeong;Kim, Min-Tae;Park, Tae-Seon;Kang, Hang-Won;Shin, Kook-Sik
    • Korean Journal of Soil Science and Fertilizer
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    • v.46 no.6
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    • pp.434-444
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    • 2013
  • In order to evaluate drought risk at upland according to climate change scenario (RCP8.5), we have carried out the simulation using agricultural water balance estimation model, called AFKAE0.5, at 66 weather station sites in 2020, 2046, 2050, 2084, and 2090. Total Drought Risk Index between the first month (f) and last month (l) (TDRI(f/l)) and maximum continuous drought risk index (MCDRI(f/l)) were defined as the index for analyzing pattern and strength of drought simulated by the model. Based on distribution maps of MCDRI (1/12), drought strength was predicted to be most severe in 2084 for all regions. Some regions showed severe risk of drought meaning over 20 days of MCDRI (1/12) in the other years, while MCDRI (1/12) in other regions did not reach 5 days. Even though maximum value of TDRI (1/12) in 2090 was greater than in 2050, more severe drought risk in 2050 than in 2090 was predicted based on MCDRI (4/6). It implies that drought risk should be assessed for each crop with its own growing season.

An Application of TAM and TRI on the Factors Affecting Internet Banking Adoption in Bangladesh

  • AMIN, Md. Iftekharul;ERFAN, Nafis;NAVID, Mashrur;KHAN, Mohammed Shafiul Alam;ISLAM, Md. Shariful
    • The Journal of Asian Finance, Economics and Business
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    • v.9 no.9
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    • pp.75-91
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    • 2022
  • This study assesses the Internet banking adoption tendency by existing bank customers of Bangladesh. Currently, almost all the leading banks in the country have implemented Internet banking platforms. However, the active user count remains relatively low and there hasn't been any conclusive research on the drivers and inhibitors of Internet banking. This study evaluates the reasons and quantitatively establishes the factors leading to the adoption and usage continuance of internet banking by existing bank customers. Responses from 460 bank account holders were collected via online questionnaires using a purposive sampling approach, and a core conceptual framework based on Technology Acceptance Model (TAM) and Technology Readiness Index (TRI) was used. The study concluded that internet banking adoption is significantly impacted by the ease of use, customer service, and technology familiarity. Similarly, customer satisfaction is affected by the perceived value and the perceived risk. Through regression analysis, it was found that usage continuance is 89% explained by adoption and customer satisfaction. Multi-group moderation showed significant impact by groups divided based on usage frequency, income level, and age. Perceived risk weakened the impact of perceived value and technology familiarity on usage adoption. Additionally, perceived risk reduced the impact of consumer satisfaction and usage continuance.

A Study on the Degree of Collision Risk through Analysing the Risk Attitude of Vessel Traffic Service Operators (해상교통관제사의 위험태도 분석을 통한 선박 충돌 위험도 연구)

  • Lee, Jin-Suk;Song, Chae-Uk
    • Journal of Navigation and Port Research
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    • v.41 no.3
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    • pp.93-102
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    • 2017
  • When VTSOs (Vessel Traffic Service Operator) determine the degree of collision risk for two vessels, they consider comprehensive information about each vessel's course, speed, DCPA, TCPA, and encountering situation. In this study, we proposed a utility function based on the risk attitudes of VTSOs toward the Risk Index (RI). The RI was calculated using the risk of encounter, the risk of approach, and the risk of time for two vessels in order to predict each ship's collision risk from the VTS viewpoint. We obtained each coefficient of the RI and the risk attitude through a survey of collision risks among VTSOs of Korea. In order to verify whether the proposed utility is reasonable, we validated by applying the degree of collision risk to some historical cases of accidents in Busan port along with the Ship of ES value($ES_S$) of ES(Environmental Stress) model.

Speciation and Ecological Risk Assessment of Trace Metals in Surface Sediments of the Masan Bay (마산만 표층퇴적물에서 미량금속의 화학적 존재형태 및 생태계 위해도 평가)

  • Sun, Chul-In;Lee, Young-Ju;An, Jung-Hyun;Lee, Yong-Woo
    • The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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    • v.19 no.2
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    • pp.155-163
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    • 2014
  • Total concentration and chemical speciation of trace metals (Cu, Pb, Zn, Cd, and Ni) were determined to evaluate pollution level and potential ecological risk in surface sediments of the Masan Bay. The results showed that the trace metal concentrations, except for Ni, were high in the inner Masan Bay. Based on the chemical speciation of metals in sediments, the percentage of total concentrations of Cd and Pb in non-residual fraction was 92% and 88%, respectively, indicating that these metals originated mainly from anthropogenic sources. However, Ni (70%) was dominant in residual fraction. Pollution load index (PLI) and ecological risk index (ERI) values in the inner bay indicate the presence of anthropogenic pollution and considerable-moderate ecological risk, respectively. Ecological index (Ei) value for Cd was high at most stations in the Masan Bay, and Cd content was the highest in acid soluble fraction, which presents the highest ecological risk. The results obtained in this study indicate that Cd presents a high potential ecological risk to benthic biota in the Masan Bay.

On the Applicability of the Extreme Distributions to Korean Stock Returns (한국 주식 수익률에 대한 Extreme 분포의 적용 가능성에 관하여)

  • Kim, Myung-Suk
    • Korean Management Science Review
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    • v.24 no.2
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    • pp.115-126
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    • 2007
  • Weekly minima of daily log returns of Korean composite stock price index 200 and its five industry-based business divisions over the period from January 1990 to December 2005 are fitted using two block-based extreme distributions: Generalized Extreme Value(GEV) and Generalized Logistic(GLO). Parameters are estimated using the probability weighted moments. Applicability of two distributions is investigated using the Monte Carlo simulation based empirical p-values of Anderson Darling test. Our empirical results indicate that both the GLO and GEV models seem to be comparably applicable to the weekly minima. These findings are against the evidences in Gettinby et al.[7], who claimed that the GEV model was not valid in many cases, and supported the significant superiority of the GLO model.

Can the Skewed Student-t Distribution Assumption Provide Accurate Estimates of Value-at-Risk?

  • Kang, Sang-Hoon;Yoon, Seong-Min
    • The Korean Journal of Financial Management
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    • v.24 no.3
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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.

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