• Journal of Intelligence and Information Systems
• /
• v.16 no.2
• /
• pp.19-32
• /
• 2010

Volatility plays a central role in both academic and practical applications, especially in pricing financial derivative products and trading volatility strategies. This study presents a novel mechanism based on generalized autoregressive conditional heteroskedasticity (GARCH) models that is able to enhance the performance of intelligent volatility trading systems by predicting Korean stock market volatility more accurately. In particular, we embedded the concept of the volatility asymmetry documented widely in the literature into our model. The newly developed Korean stock market volatility index of KOSPI 200, VKOSPI, is used as a volatility proxy. It is the price of a linear portfolio of the KOSPI 200 index options and measures the effect of the expectations of dealers and option traders on stock market volatility for 30 calendar days. The KOSPI 200 index options market started in 1997 and has become the most actively traded market in the world. Its trading volume is more than 10 million contracts a day and records the highest of all the stock index option markets. Therefore, analyzing the VKOSPI has great importance in understanding volatility inherent in option prices and can afford some trading ideas for futures and option dealers. Use of the VKOSPI as volatility proxy avoids statistical estimation problems associated with other measures of volatility since the VKOSPI is model-free expected volatility of market participants calculated directly from the transacted option prices. This study estimates the symmetric and asymmetric GARCH models for the KOSPI 200 index from January 2003 to December 2006 by the maximum likelihood procedure. Asymmetric GARCH models include GJR-GARCH model of Glosten, Jagannathan and Runke, exponential GARCH model of Nelson and power autoregressive conditional heteroskedasticity (ARCH) of Ding, Granger and Engle. Symmetric GARCH model indicates basic GARCH (1, 1). Tomorrow's forecasted value and change direction of stock market volatility are obtained by recursive GARCH specifications from January 2007 to December 2009 and are compared with the VKOSPI. Empirical results indicate that negative unanticipated returns increase volatility more than positive return shocks of equal magnitude decrease volatility, indicating the existence of volatility asymmetry in the Korean stock market. The point value and change direction of tomorrow VKOSPI are estimated and forecasted by GARCH models. Volatility trading system is developed using the forecasted change direction of the VKOSPI, that is, if tomorrow VKOSPI is expected to rise, a long straddle or strangle position is established. A short straddle or strangle position is taken if VKOSPI is expected to fall tomorrow. Total profit is calculated as the cumulative sum of the VKOSPI percentage change. If forecasted direction is correct, the absolute value of the VKOSPI percentage changes is added to trading profit. It is subtracted from the trading profit if forecasted direction is not correct. For the in-sample period, the power ARCH model best fits in a statistical metric, Mean Squared Prediction Error (MSPE), and the exponential GARCH model shows the highest Mean Correct Prediction (MCP). The power ARCH model best fits also for the out-of-sample period and provides the highest probability for the VKOSPI change direction tomorrow. Generally, the power ARCH model shows the best fit for the VKOSPI. All the GARCH models provide trading profits for volatility trading system and the exponential GARCH model shows the best performance, annual profit of 197.56%, during the in-sample period. The GARCH models present trading profits during the out-of-sample period except for the exponential GARCH model. During the out-of-sample period, the power ARCH model shows the largest annual trading profit of 38%. The volatility clustering and asymmetry found in this research are the reflection of volatility non-linearity. This further suggests that combining the asymmetric GARCH models and artificial neural networks can significantly enhance the performance of the suggested volatility trading system, since artificial neural networks have been shown to effectively model nonlinear relationships.

• Journal of Korean Society of Disaster and Security
• /
• v.9 no.2
• /
• pp.23-32
• /
• 2016

Today the issue of deterioration of industrial complexes that are located close to life space of residents has been raised as a cause of threats to the safety of local communities. In this study, in order to improve the current risk analysis and scope of community notification, simulated threat zones were comparatively analyzed by utilizing the threat zones of alternative accident scenarios and modes of seasonal weather, and the area with a high probability of damage upon the leakage of toxic substances was predicted by examining wind directions observed at each time slot for each season. In addition, limit evacuation time and minimum separation distance to minimize casualties were suggested, and a proposal to enable more reasonable safety measures for on-site workers and nearby residents made by reviewing the risk management plan currently utilized for emergency response.

• Journal of Intelligence and Information Systems
• /
• v.9 no.1
• /
• pp.139-155
• /
• 2003

This paper presents the new methodology of analyzing and classifying patterns of customers in mobile telecommunication market to enhance the performance of predicting the credit information based on the decision tree and neural network. With the application of variance selection process from decision tree, the systemic process of defining input vector's value and the rule generation were developed. In point of customer management, this research analyzes current customers and produces the patterns of them so that the company can maintain good customer relationship and makes special management on the customer who has huh potential of getting out of contract in advance. The real implementation of proposed method shows that the predicted accuracy is higher than existing methods such as decision tree(CART, C4.5), regression, neural network and combined model(CART and NN).

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.7 no.3
• /
• pp.518-523
• /
• 2006

Due to keen competition among companies, they have segmented customers and they are trying to offer specially targeted customer by means of the distinguished method. In accordance, data mining techniques are noted as the effective method that extracts useful information. This paper explores customer segmentation of the home study company using a hybrid decision tree and artificial neural network model. With the application of variance selection process from decision tree, the systemic process of defining input vector's value and the rule generation were developed. In point of customer management, this research analyzes current customers and produces the patterns of them so that the company can maintain good customer relationship. The case study shows that the predicted accuracy of the proposed model is higher than those of regression, decision tree (CART), artificial neural networks.

• Proceedings of the Korean Association for Survey Research Conference
• /
• 2001.04a
• /
• pp.37-57
• /
• 2001

Much effort has been made to measure regional difference showing the pattern of regionalism in Korea. Focusing the concept of social distance, this paper examines various election and regional preference data. The paper presets three major findings. First current election data show clear regional cleavage. Second, regional discrimination and prejudice is often found in one' s everyday life. Third, political aspect of regionalism is strongly related to social aspect of regionalism. These findings suggest that regionalism in Korea will survive for the time being. The regionalism is rooted in everyday life. To political elites, it became an attractive and economic way to maintain their power. This tendency will promote the preference for parliamentary system among political elites and the possibility of appearance of regional party.

• Journal of the Korean Chemical Society
• /
• v.26 no.1
• /
• pp.7-17
• /
• 1982

In order to predict substituent and Lewis acid effects on the regiospecificity of the Diels-Alder reaction, and to investigate the competition for the complexation of Lewis acid between diene and dienophile, frontier orbital theory has been applied to thermal and catalyzed Diels-Alder reaction by means of CNDO/2 MO method. It has been found that: (1) Lewis acid coordinated preferentially with diene rather than dienophile when carbonyl oxygen of acetoxy substituted diene had larger negative atomic charges than that of dienophile. (2) Most of the reaction were neutral electron demand type, and hence 4-C, 2-C and quantitative secondary orbital interacion methods were generally in good accord with experiments. (3) Sulfur activated the adjacent terminal carbon atom greatly to increase diene LUMO-dienophile HOMO interaction through vacant-d-orbital participation, and played an important role in controlling regioselectivity of neutral electron demand reaction type.

• Journal of the Korean Chemical Society
• /
• v.29 no.1
• /
• pp.23-30
• /
• 1985

PMO expressions for ${\pi}^{\ast}$-${\pi}^{\ast}$ orbital interaction have been derived. Important differences between ${\pi}$-${\pi}$ and ${\pi}^{\ast}$-${\pi}^{\ast}$ interactions predicted by PMO expressions are : (ⅰ) energy splitting in ${\pi}^{\ast}$-${\pi}^{\ast}$ interaction will be greater than that in ${\pi}$-${\pi}$ interaction, (ⅱ) energy change due to interaction will be more destabilizing in ${\pi}^{\ast}$-${\pi}^{\ast}$ than in ${\pi}$-${\pi}$ interaction. These predictions were borne out in experimental data and in results of MO theoretical computations. It was pointed out that both STeO-3G and INDO-LCBO methods underestimate ${\pi}^{\ast}$-${\pi}^{\ast}$ orbital interaction and in order to estimate properly with MO theoretical calculation, use of split valence basis set is required.

• Survey Research
• /
• v.2 no.1
• /
• pp.37-57
• /
• 2001

Much effort has been made to measure regional difference showing the pattern of regionalism in Korea. Focusing the concept of social distance. this paper examines various election and regional preference data. The paper presets three major findings. First. current election data show clear regional cleavage. Second. regional discrimination and prejudice is often found in one's everyday life. Third, political aspect of regionalism is strongly related to social aspect of regionalism. These findings suggest that regionalism in Korea will survive for the time being. The regionalism is rooted in everyday life . To political elites. it became an attractive and economic way to maintain their power. This tendency will promote the preference for parliamentary system among political elites and the possibility of appearance of regional party

• Journal of the Korean Chemical Society
• /
• v.28 no.5
• /
• pp.284-292
• /
• 1984

This paper aims to predict the substituent and Lewis acid catalysis effect or reactivity on the regioselectivity of (4+2) cycloaddition reaction of the substituted-E-arene-diazocyanides and nitrosobenzenes. Frontier orbital theory (FMO) has been applied to thermal and catalyzed Diels-Alder reaction by means of CNDO/2 and EHT-SPD methods. It has been found that: (1) The above reaction is positive rho(${\rho}$) values in Hammett equation, so it takes normal electron demand reaction, and four-frontier orbitals and Anh methods are identical with experimental major regioisomer.(2) When electron withdrawing radicals are substituted HOMO and LUMO energies of dienophiles are reduced, and the reactivity is increased. (3) The major regioisomer is predicted as B type, as the Lewis acid makes complexes of dienophile, and polaries LUMO coefficients of dienophile in an opposite way. (4) The linear correlation of Hammett is indicated in the graph of stabilized energies(${\Delta}$E) and sigma(${\sigma}$).

• Korean Journal of Culture and Social Issue
• /
• v.18 no.3
• /
• pp.415-433
• /
• 2012

This study was conducted in order to explain the effect of driving behavior determinants such as drivers' personality and attitude that may induce risky driving behavior and to develop a valid method for discriminating risky drivers using the determinants. In the results of surveying 534 adult drivers, 5 driving behavior determinants (avoidance of problems, benefit/stimulus seeking, interpersonal anxiety, interpersonal anger, and aggression) were found to have a statistically significant effect on drivers' various risky driving behaviors. Using these factors, drivers were grouped according to risk levels (normal drivers, unintentionally risky drivers, and intentionally risky drivers). This result suggests that drivers' dangerous behavior level can be predicted using psychological factors such as their personality and attitude. Accordingly, if the driving behavior determinant model and the base score system used in this study are improved through further research, they are expected to be useful in predicting drivers' recklessness in advance, identifying problems, and providing differentiated safe driving education services based on the results.