• Journal of Intelligence and Information Systems
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• v.23 no.2
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• pp.107-122
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• 2017

Volatility in the stock market returns is a measure of investment risk. It plays a central role in portfolio optimization, asset pricing and risk management as well as most theoretical financial models. Engle(1982) presented a pioneering paper on the stock market volatility that explains the time-variant characteristics embedded in the stock market return volatility. His model, Autoregressive Conditional Heteroscedasticity (ARCH), was generalized by Bollerslev(1986) as GARCH models. Empirical studies have shown that GARCH models describes well the fat-tailed return distributions and volatility clustering phenomenon appearing in stock prices. The parameters of the GARCH models are generally estimated by the maximum likelihood estimation (MLE) based on the standard normal density. But, since 1987 Black Monday, the stock market prices have become very complex and shown a lot of noisy terms. Recent studies start to apply artificial intelligent approach in estimating the GARCH parameters as a substitute for the MLE. The paper presents SVR-based GARCH process and compares with MLE-based GARCH process to estimate the parameters of GARCH models which are known to well forecast stock market volatility. Kernel functions used in SVR estimation process are linear, polynomial and radial. We analyzed the suggested models with KOSPI 200 Index. This index is constituted by 200 blue chip stocks listed in the Korea Exchange. We sampled KOSPI 200 daily closing values from 2010 to 2015. Sample observations are 1487 days. We used 1187 days to train the suggested GARCH models and the remaining 300 days were used as testing data. First, symmetric and asymmetric GARCH models are estimated by MLE. We forecasted KOSPI 200 Index return volatility and the statistical metric MSE shows better results for the asymmetric GARCH models such as E-GARCH or GJR-GARCH. This is consistent with the documented non-normal return distribution characteristics with fat-tail and leptokurtosis. Compared with MLE estimation process, SVR-based GARCH models outperform the MLE methodology in KOSPI 200 Index return volatility forecasting. Polynomial kernel function shows exceptionally lower forecasting accuracy. We suggested Intelligent Volatility Trading System (IVTS) that utilizes the forecasted volatility results. IVTS entry rules are as follows. If forecasted tomorrow volatility will increase then buy volatility today. If forecasted tomorrow volatility will decrease then sell volatility today. If forecasted volatility direction does not change we hold the existing buy or sell positions. IVTS is assumed to buy and sell historical volatility values. This is somewhat unreal because we cannot trade historical volatility values themselves. But our simulation results are meaningful since the Korea Exchange introduced volatility futures contract that traders can trade since November 2014. The trading systems with SVR-based GARCH models show higher returns than MLE-based GARCH in the testing period. And trading profitable percentages of MLE-based GARCH IVTS models range from 47.5% to 50.0%, trading profitable percentages of SVR-based GARCH IVTS models range from 51.8% to 59.7%. MLE-based symmetric S-GARCH shows +150.2% return and SVR-based symmetric S-GARCH shows +526.4% return. MLE-based asymmetric E-GARCH shows -72% return and SVR-based asymmetric E-GARCH shows +245.6% return. MLE-based asymmetric GJR-GARCH shows -98.7% return and SVR-based asymmetric GJR-GARCH shows +126.3% return. Linear kernel function shows higher trading returns than radial kernel function. Best performance of SVR-based IVTS is +526.4% and that of MLE-based IVTS is +150.2%. SVR-based GARCH IVTS shows higher trading frequency. This study has some limitations. Our models are solely based on SVR. Other artificial intelligence models are needed to search for better performance. We do not consider costs incurred in the trading process including brokerage commissions and slippage costs. IVTS trading performance is unreal since we use historical volatility values as trading objects. The exact forecasting of stock market volatility is essential in the real trading as well as asset pricing models. Further studies on other machine learning-based GARCH models can give better information for the stock market investors.

• Analytical Science and Technology
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• v.27 no.2
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• pp.79-91
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• 2014

Solubility data of carbon dioxide ($CO_2$) in 1-butyl-3-methylpiperidinium bis(trifluoromethylsulfonyl)imide ($[bmpip][Tf_2N]$) ionic liquid are presented at pressures up to about 30 MPa and at temperatures between 303 K and 343 K. As far as we know, the data on the $CO_2$ solubility in the $[bmpip][Tf_2N]$ ionic liquid have never been reported in the literature by other investigators. The solubilities of $CO_2$ were determined by measuring the bubble point or cloud point pressures of the $CO_2+[bmpip][Tf_2N]$ mixtures with various compositions using a high-pressure equilibrium apparatus equipped with a variable-volume view cell. To observe the effect of the cation composing the ionic liquid on the $CO_2$ solubility, the $CO_2$ solubilities in $[bmpip][Tf_2N]$ used in this study were compared with those in 1-butyl-3-methylimidazolium bis(trifluoromethylsulfonyl)-imide ($[bmim]Tf_2N]$). As the equilibrium pressure increased, the $CO_2$ solubility in $[bmpip][Tf_2N]$ increased sharply. On the other hand, the $CO_2$ solubility decreased with increasing temperature. The mole fraction-based $CO_2$ solubilities were almost the same for both $[bmpip][Tf_2N]$ and $[bmim][Tf_2N]$, regardless of temperature and pressure. The phase equilibrium data for the $CO_2+[bmpip][Tf_2N]$ systems have been correlated using the Peng-Robinson equation of state.

• The Korean Journal of Financial Management
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• v.20 no.1
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• pp.163-190
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• 2003

This study tests the hypothesis of market efficiency through the information spillover effects over price and volatility across countries by using open-to-close(daytime) returns and close-to-open(overnight) returns of NASDAQ, KOSDAQ and JASDAQ data from January 3, 1997 to December 21, 2000. Based on Granger-causality and time-varying AR(1)-GARCH(1, 1)-M models we document that the evidence of statistically significant conditional mean and volatility spillovers effects from the daytime returns and volatility of NASDAQ to the overnight returns and volatility of KOSDAQ is observed both before and after the IMF foreign currency crisis but not to the close-to-open return before the IMF foreign currency crisis. We can understand the information spillover effect from NASDAQ to KOSDAQ on the overnight rather than the daytime grows more significantly after the IMF foreign currency crisis. We also find the interactive information spillover effect between NASDAQ and JASDAQ both before and after the IMF financial crisis, in particular, to close-to-open return. In addition, the market efficiency between KOSDAQ and NASDAQ is on an increasing trend through IMF foreign currency crisis.

• Applied Chemistry for Engineering
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• v.27 no.3
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• pp.291-298
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• 2016

In this study, zwitterionic surfactants were added to liposome systems at different pH conditions to understand the effect of surfactants on liposome characteristics. For this purpose, amine oxide surfactants having different hydrocarbon chain lengths were synthesized and the structure of the resulting product was elucidated by using $^1H$ NMR, $^{13}C$ NMR, and FT-IR. In addition, the physical properties of newly synthesized surfactants such as critical micelle concentration (CMC), surface tension and isoelectric point were measured. The stability characteristics of liposome systems including average particle sizes and zeta potentials were measured by varying pH and hydrocarbon chain lengths of an amine oxide surfactant. Effects of the pH and hydrocarbon chain length of an amine oxide surfactant on fluidity of a liposome membrane were also examined by measuring the deformability and the binding degree between the surfactant and liposome.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.38 no.4
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• pp.362-370
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• 2001

In this paper, we proposed multispectral image compression method using CIP (classified inter-channel prediction) and SVQ (selective vector quantization) in wavelet domain. First, multispectral image is wavelet transformed and classified into one of three classes considering reflection characteristics of the subband with the lowest resolution. Then, for a reference channel which has the highest correlation and the same resolution with other channels, the variable VQ is performed in the classified intra-channel to remove spatial redundancy. For other channels, the CIP is performed to remove spectral redundancy. Finally, the prediction error is reduced by performing SVQ. Experiments are carried out on a multispectral image. The results show that the proposed method reduce the bit rate at higher reconstructed image quality and improve the compression efficiency compared to conventional methods. Index Terms-Multispectral image compression, wavelet transform, classfied inter-channel prediction, selective vetor quantization, subband with lowest resolution.

• Journal of KIISE:Software and Applications
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• v.33 no.3
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• pp.277-288
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• 2006

Product line engineering (PLE) is a new effective approach to software reuse, where applications are generated by instantiating a core asset which is a large-grained reuse unit. Hence, a core asset is a key element of PLE, and therefore the reusability of the core asset largely determines the success of PLE projects. A tore asset is a reusable part not a whole system, and supports not only variable functions but also common functions. However, there are limitations to evaluate reusability of core asset that has these unique characteristics. This paper proposes a comprehensive quality system for evaluating the reusability of core assets, based on ISO/IEC 9126. We first identify the key characteristics of core assets, and derive the set of quality attributes that characterizes the reusability of core assets. finally, we define metrics for each quality attribute. In addition, we provide guidelines for applying the metrics and perform a case study based on rental product line. Using the proposed quality system, reusability of core assets can be more effectively and correctly evaluated.

• Research in Plant Disease
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• v.8 no.4
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• pp.199-206
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• 2002

It was investigated on the relationship of the rice blast epidemics and the real-time meteorological factors, at the experimental paddy field in 1997. Weather factors(temperature, relative humidity, irradiation, precipitation, the direction of wind, wind speed, soil temperature and leaf-wetness, etc) were measured by using the automated weather station. The most influenced weather factor to blast epidemics, was the average max-temp($R^2$= 0.95) during 10 days before leaf blast epidemics, while the least thing was wind speed($R^2$= 0.24). The most potential weather factors correlated with the blast epidemics were T-ave(average temperature), T-max(maximum temperature), RH(Relative Humidity) and RD(Relative Humidity > 90% hrs). A statistics model(the regression equation) of the blast epidemics with the potential weather factors, was established as tallows ; Y = -3410.91 - 23.91 $\times$ T-ave ＋ 28.56 $\times$ T-max ＋ 41.0 $\times$ RH - 3.75 $\times$ RD, ($R^2$= 0.99). (T-ave >= 19$^{\circ}C$, T-max - T-ave >= 5.2$^{\circ}C$ and RH% >= 90.4%). According to the fitness test($\chi$$^2$) of the model, the observed blast disease severity was quite close to those expected.

• Journal of the Korean Society of Radiology
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• v.11 no.5
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• pp.303-312
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• 2017

The central goal of Gamma Knife radiosurgery(GKRS) is to maximize the conformity of the prescription isodose surface, and to minimize the radiation effect of the normal tissue surrounding the target volume. There are the various kinds of indices related with the quality of treatment plans such as conformity index, coverage, selectivity, beam-on time, gradient index(GI), and conformity/gradient index(CGI). As the best treatment plan evaluation tool, we must check by all means conformity index, GI, and CGI among them. Specially, GI and CGI related with complication of healthy normal tissue is more indispensible than conformity index. Then author calculated and statistically analysed CGI, the newly defined conformity/gradient index as well as GI being applied widely using the treatment planning system Leksell GammaPlan(LGP) and the verification method Variable Ellipsoid Modeling Technique(VEMT). In the study 10 patients with intracranial lesion treated by GKRS were included. Author computed the indices from LGP and VEMT requiring only four parameters: the prescribed isodose volume, the volume with dose > 30%, the target volume, and the volume of half the prescription isodose. All data were analyzed by paired t-test, which is statistical method used to compare two different measurement techniques. No statistical significance in GI at 10 cases was observed between LGP and VEMT. Differences in GI ranged from -0.14 to 0.01. The newly defined gradient index calculated by two methods LGP and VEMT was not statistically significant either. Author did not find out the statistical difference for the prescribed isodose volume between LGP and VEMT. CGI as the evaluation index for determining the best treatment plan is not significant statistically also. Differences in CGI ranged from -4 to 3. Similarly newly defined Conformity/Gradient index for GKRS was also estimated as the metric for the evaluation of the treatment plans through statistical analysis. Statistical analyses demonstrated that VEMT was in excellent agreement with LGP when considering GI, new gradient index, CGI, and new CGI for evaluating the best plans of GKRS. Due to the application of the fast and easy evaluation tool through LGP and VEMT author hopes CGI and newly defined CGI as well as gradient indices will be widely used.

• Journal of the Korean Institute of Telematics and Electronics C
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• v.35C no.10
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• pp.69-77
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• 1998

This paper presents a new efficient and stable multilevel partitioning algorithm for VLSI circuit design. The performance of multilevel partitioning algorithms that are proposed to enhance the performance of previous iterative-improvement partitioning algorithms for large scale circuits, depend on choice of construction methods for partition hierarchy. As the most of previous multilevel partitioning algorithms forces experimental constraints on the process of hierarchy construction, the stability of their performances goes down. The lack of stability causes the large variation of partition results during multiple runs. In this paper, we minimize the use of experimental constraints and propose a new method for constructing partition hierarchy. The proposed method clusters the cells with the connection status of the circuit. After constructing the partition hierarchy, a partition improvement algorithm, HYIP$^{[11]}$ using hybrid bucket structure, unclusters the hierachy to get partition results. The experimental results on ACM/SIGDA benchmark circuits show improvement up to 10-40% in minimum outsize over the previous algorithm $^{[3] [4] [5] [8] [10]}$. Also our technique outperforms ML$^{[10]}$ represented multilevel partition method by about 5% and 20% for minimum and average custsize, respectively. In addition, the results of our algorithm with 10 runs are better than ML algorithm with 100 runs.

• Korean Chemical Engineering Research
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• v.54 no.2
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• pp.213-222
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• 2016

Solubility data of hydrogen sulfide ($H_2S$) and methane ($CH_4$) in two kinds of ionic liquids with the same anion: 1-ethyl-3-methylimidazolium trifluoromethanesulfonate ([emim][TfO]) and 1-butyl-1-methylpyrrolidinium trifluoromethanesulfonate ([bmpyr][TfO]) are presented at pressures up to about 30 MPa and at temperatures between 303 K and 343 K. The gas solubilities in ionic liquids were determined by measuring the bubble point pressures of the gas + ionic liquid mixtures with various compositions at different temperatures using a high-pressure equilibrium apparatus equipped with a variable-volume view cell. The $H_2S$ solubilities in ionic liquid increased with the increase of pressure and decreased with the increase of temperature. On the other hand, the $CH_4$ solubilities in ionic liquid increased significantly with the increase of pressure, but there was little effect of temperature on the $CH_4$ solubility. For the ionic liquds [emim][TfO] and [bmpyr][TfO] with the same anion, the solubility of $H_2S$ as a molality basis was substantially similar, regardless of the temperature and pressure conditions as a molar concentration basis. Comparing the solubilities of $H_2S$ and $CH_4$ in the ionic liquid [emim][TfO], the solubilities of $H_2S$ were much greater than those of $CH_4$. For the same type of ionic liquid, the solubility data of $H_2S$ and $CH_4$ obtained in this study were compared to the solubility data of $CO_2$ from the literature. When compared at the same pressure and temperature conditions, the $CO_2$ solubility was in between the solubility of $H_2S$ and $CH_4$.