• Journal of the Korean Data and Information Science Society
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• v.27 no.4
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• pp.959-967
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• 2016

Distributional assumptions on equity returns play a key role in valuation theories for derivative securities. Elberlein and Keller (1995) investigated the distributional form of compound returns and found that some of standard assumptions can not be justified. Instead, Generalized Hyperbolic (GH) distribution fit the empirical returns with high accuracy. Hu and Kercheval (2007) also show that the normal distribution leads to VaR (Value at Risk) estimate that significantly underestimate the realized empirical values, while the GH distributions do not. We consider saddlepoint approximations to estimate the VaR and the ES (Expected Shortfall) which frequently encountered in finance and insurance as measures of risk management. We supposed GH distributions instead of normal ones, as underlying distribution of linear portfolios. Simulation results show the saddlepoint approximations are very accurate than normal ones.

• Journal of the Korean Magnetics Society
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• v.7 no.5
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• pp.237-242
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• 1997

The microstructure and soft magnetic properties of as-deposited Fe-Hf-O thin film alloys, which are produced at $P_{O2}=10%$ by rf magnetron sputtering method in $Ar+O_2$ mixed gas atmosphere, is investigated. Newly developed $Fe_{82}Hf_{3.4}O_{14.6}$ film exhibits good soft magnetic properties with $4{\pi}M_s=17.7$ kG, $H_c=0.7$ Oe and ${\mu}_{eff}$(0.5~100MHz)=2,500, respectively. The Fe-Hf-O films are composed of $\alpha$-Fe nanograins and amorphous phase with larger amounts of Hf and O elements which chemically combine each other. With increasing Hf area fraction, Hf and O contents increased proportionally. It was considered that O content in films was determined by Hf contents, because O was chemically combined with Hf. It results from decreasing the $\alpha$-Fe grain size by precipitates (Hf and O), high electrical resistivity. The $Fe_{82}Hf_{3.4}O_{14.6}$ film exhibits the quality factor (Q=$\mu$'/$\mu$") of 25 at 20 MHz. These good frequency characteristics are considered to be superior to other films already reported.o other films already reported.

• Journal of Intelligence and Information Systems
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• v.23 no.4
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• pp.147-168
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• 2017

There have been many studies on accurate stock market forecasting in academia for a long time, and now there are also various forecasting models using various techniques. Recently, many attempts have been made to predict the stock index using various machine learning methods including Deep Learning. Although the fundamental analysis and the technical analysis method are used for the analysis of the traditional stock investment transaction, the technical analysis method is more useful for the application of the short-term transaction prediction or statistical and mathematical techniques. Most of the studies that have been conducted using these technical indicators have studied the model of predicting stock prices by binary classification - rising or falling - of stock market fluctuations in the future market (usually next trading day). However, it is also true that this binary classification has many unfavorable aspects in predicting trends, identifying trading signals, or signaling portfolio rebalancing. In this study, we try to predict the stock index by expanding the stock index trend (upward trend, boxed, downward trend) to the multiple classification system in the existing binary index method. In order to solve this multi-classification problem, a technique such as Multinomial Logistic Regression Analysis (MLOGIT), Multiple Discriminant Analysis (MDA) or Artificial Neural Networks (ANN) we propose an optimization model using Genetic Algorithm as a wrapper for improving the performance of this model using Multi-classification Support Vector Machines (MSVM), which has proved to be superior in prediction performance. In particular, the proposed model named GA-MSVM is designed to maximize model performance by optimizing not only the kernel function parameters of MSVM, but also the optimal selection of input variables (feature selection) as well as instance selection. In order to verify the performance of the proposed model, we applied the proposed method to the real data. The results show that the proposed method is more effective than the conventional multivariate SVM, which has been known to show the best prediction performance up to now, as well as existing artificial intelligence / data mining techniques such as MDA, MLOGIT, CBR, and it is confirmed that the prediction performance is better than this. Especially, it has been confirmed that the 'instance selection' plays a very important role in predicting the stock index trend, and it is confirmed that the improvement effect of the model is more important than other factors. To verify the usefulness of GA-MSVM, we applied it to Korea's real KOSPI200 stock index trend forecast. Our research is primarily aimed at predicting trend segments to capture signal acquisition or short-term trend transition points. The experimental data set includes technical indicators such as the price and volatility index (2004 ~ 2017) and macroeconomic data (interest rate, exchange rate, S&P 500, etc.) of KOSPI200 stock index in Korea. Using a variety of statistical methods including one-way ANOVA and stepwise MDA, 15 indicators were selected as candidate independent variables. The dependent variable, trend classification, was classified into three states: 1 (upward trend), 0 (boxed), and -1 (downward trend). 70% of the total data for each class was used for training and the remaining 30% was used for verifying. To verify the performance of the proposed model, several comparative model experiments such as MDA, MLOGIT, CBR, ANN and MSVM were conducted. MSVM has adopted the One-Against-One (OAO) approach, which is known as the most accurate approach among the various MSVM approaches. Although there are some limitations, the final experimental results demonstrate that the proposed model, GA-MSVM, performs at a significantly higher level than all comparative models.

• Journal of the Korean Society of Food Science and Nutrition
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• v.33 no.7
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• pp.1212-1217
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• 2004

The aim of this study was to investigate Quality characteristics of Pleurospermum kamtschaticum to increase the value of functional food resources. To examine Quality characteristics of Pleurospermum kamtschaticum, various factors such as color, texture, fiber, minerals, tannin, crude proteins, crude lipids and sensory quality, were determined using physicochemical methods. The contents of dietary fiber were 0.57％ and 0.54％ in each 100 g of leaf and stem parts (freeze drying base). In mineral content, potassium was the highest value in both of leaf and stem parts (freeze drying base). The contents of tannin were 108.1 $\mu$g/mL and 20.9 $\mu$g/mL in leaf and stem parts (fresh base) respectively. Blanching stems showed significant difference in hardness from freeze-drying leaves. The antioxidative activity in ethanol extracts of Pleurospermum kamtschaticum was investigated using peroxide value and free radical scavenging activity. Free radical scavenging activity in ethanol extracts of Pleurospermum kamtschaticum was 43.5％ in a 100 $\mu$g/mL level, and the antioxidative index was 1.09 in a 500 $\mu$g/mL level. For functional food using Pleurospermum kamtschaticum the contents of crude proteins and lipids were about 9％ and 26％, respectively. The results from sensory evaluation of each treatment older age showed a better acceptability.

• Journal of Environmental Policy
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• v.4 no.2
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• pp.31-55
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• 2005

Dangsan forests and Rural Community Forests(RCF) have been historical assets for the rural communities of more than 40,000 in Korea and they have provided an identity through the cultural heritage. The Dangsan forests and the RCF are parts of a unique cultural landscape in the rural areas as components of stream landscape. In many cases, the Dangsan forests and the RCF are located close to stream corridors. The objective of this study was to understand the function of the Dangsan forests and the RCF on stream water quality and to evaluate its ecological landscape values. Through the consideration of international concensus and domestic government policy for close-to-nature stream, we could find out that Dangsan forests and RCF's have close relationship with the close-to-nature streams. The water quality of the streams close to the Dangsan forests and the RCF are maintained with local culture. It is also compared to the streams located where Dangsan forests and the RCF are absent. Eight study sites were selected. Water samples were collected at three different locations at each study site. Water samples were analyzed for temperature, pH, total P, total N, dissolved oxygen, EC, BOD, COD and SS. Aquatic invertebrates were observed as water quality indicator species. The results showed that the number of aquatic invertebrate species, GPI, DO, EC, BOD, and SS were significantly improved in stream water due to the presence of the Dangsan forests and the RCF. The role of Dangsan forests and the RCF was evident in the conservation of stream landscape and rural culture as well as in maintaining stream water quality. The management schemes of the streams with Dangsan forests and the RCF's are also suggested.

• Journal of Animal Science and Technology
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• v.52 no.1
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• pp.9-16
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• 2010

A previous study has shown that the g.17924G>A polymorphism of fatty acid synthase (FASN) is associated with unsaturated fatty acid composition in the Hanwoo beef, hence this study was conducted to evaluate the effect of single nucleotide polymorphisms (SNPs) within FASN gene on the selection phenotypes of Hanwoo breeding stock. A total of 925 progeny test steers were used to genotype g.11280G>A, g.13125T>C, and g.17924G>A polymorphisms and significant associations were found among g.11280G>A, g.17924G>A, and carcass traits, such as carcass weight, backfat thickness, and beef quantity index. No significant association was found between g.13125T>C and carcass traits. Although the degree of linkage disequilibrium (LD) was not strong among g.11280G>A, g.13125T>C, and g.17924G>A in the LD analysis, four major haplotype classes were formed with the genotypic information within the FASN gene; the frequencies of the halpotypeswere -GCG-[0.378], -ATG-[0.301], -GTA-[0.191], and -ACG-[0.063], respectively. Phenotypic association was performed among these haploptypes, and the haplotype 2 (-ATG-)was significantly associated with higher carcass weight when compared to the other haplotypes, i.e. haplotype 1 (-GCG-) and haplotype 3 (-GTA-). A copy number of the FASN haplotype 3 (-GTA-) had also a significant association with carcass weight of subjects. In conclusion, it was observed that two polymorphisms (g.11280G>A and g.17924G>A) and their haplotypes within the FASN gene are consistently associated with carcass traits. Therefore, it is desirable to use the FASN polymorphisms for pre-selection program as genetic marker with improved carcass yield and beef quality of the Hanwoo sire at the Hanwoo Improvement Center as well as for commercial Hanwoo producers, the FASN genotypic information can be used for a part of selecting Hanwoo dam for superior calf production.

• Korean Security Journal
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• no.48
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• pp.9-33
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• 2016

The purpose of the present study was to find out cause-and-effect relationship between job requirements and job resources, with job burnout as a mediator variable, and the effects of these variables on organizational effectiveness. The population in the present study was private security guards employed by 13 private security companies in Seoul and Gyeonggi-do areas, and a survey was conducted on 500 security guards selected using purposive sampling technique. Out of 460 questionnaires distributed, 429 responses, excluding 31 outliers or insincere responses, were used for data analysis. For analysis, data were coded and entered into SPSS 18.0 and AMOS 18.0, which were used to analyze the data. Descriptive analyses were performed to find out sociodemographic characteristics of the respondents. The exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) were used to test the validity of the measurement tool, and the Cronbach's Alpha coefficients were calculated to test the reliability. To find out the significance of relationships among variables, Pearson's correlation analysis was performed. Covariance Structure Analysis (CSA) was performed to test the relationship among latent factors of a model for job requirements, job resources, job burnout, and organizational effectiveness of the private security guards, and the fitness of the model analyzed with CSA was determined by the goodness-of-fit index ($x^2$, df, p, RMR, GFI, CFI, TLI, RMSEA). The level of significance was set at .05, and the following results were obtained. First, even though the effect of job requirements on job burnout was not statistically significant, it had a positive influence overall, and this result can be considered such that the higher the perception of job requirements by the member of the organization, the higher the perception of job burnout. Second, the influence of job resources on job burnout was negative, which can be considered that the higher the perception of job resources, the lower the perception of job burnout. Third, even though the influence of job requirements on organizational effectiveness was statistically nonsignificant, it had a negative influence overall, and this result can be considered that the higher the perception of job requirements, the lower the perception of organizational effectiveness. Fourth, job resources had a positive influence on organizational effectiveness, and it can be considered that the higher the perception of job resources, the higher the perception of organizational effectiveness. Fifth, the results of the analysis between job burnout and organizational effectiveness revealed that, even though the influence of job burnout on organizational effectiveness was statistically nonsignificant, it had partial negative influences on sublevels of organizational effectiveness, and this may suggest that the higher the perception of job burnout by the organization members, the lower the organizational effectiveness. Sixth, the analysis of mediating role in the relationship between job requirements and organizational effectiveness, job burnout was taking partial mediating role between job requirements and organizational effectiveness. These results suggest that reducing job burnout by managing job requirements, organizational effectiveness that leads to job satisfaction, organizational commitment, and turnover intention can be maximized. Seventh, the analysis of mediating role in the relationship among job requirements, job resources, and organizational effectiveness, job burnout was assuming a partial mediating role in the relationships among job requirements, job resources, and organizational effectiveness. These results suggest that organizational effectiveness can be maximized by either lowering job requirements or burnout management through reorganizing job resources.