• The Korean Journal of Financial Management
• /
• v.26 no.3
• /
• pp.139-169
• /
• 2009

This paper introduces the modified VaR which takes into account the asymmetry and fat-tails of financial asset distribution, and then compares its out-of-sample forecast performance with traditional VaR model such as historical simulation model and Riskmetrics. The empirical tests using stock indices of 6 countries showed that the modified VaR has the best forecast accuracy. At the test of independence, Riskmetrics and GARCH model showed best performances, but the independence was not rejected for the modified VaR. The Monte Carlo simulation using skew t distribution again proved the best forecast performance of the modified VaR. One of many advantages of the modified VaR is that it is appropriate for measuring VaR of the portfolio, because it can reflect not only the linear relationship but also the nonlinear relationship between individual assets of the portfolio through coskewness and cokurtosis. The empirical analysis about decomposing VaR of the portfolio of 6 stock indices confirmed that the component VaR is very useful for the re-allocation of component assets to achieve higher Sharpe ratio and the active risk management.

• Journal of the Korean Data and Information Science Society
• /
• v.18 no.4
• /
• pp.915-925
• /
• 2007

Multivariate GARCH has been useful to model dynamic relationships between volatilities arising from each component series of multivariate time series. Methodologies including EWMA(Exponentially weighted moving-average model), DVEC(Diagonal VEC model), BEKK and CCC(Constant conditional correlation model) models are comparatively reviewed for bivariate time series. In addition, these models are applied to evaluate VaR(Value at Risk) and to construct joint prediction region. To illustrate, bivariate stock prices data consisting of Samsung Electronics and LG Electronics are analysed.

• Journal of Information Processing Systems
• /
• v.15 no.5
• /
• pp.1201-1210
• /
• 2019

Stock price is characterized as being mutable, non-linear and stochastic. These key characteristics are known to have a direct influence on the stock markets globally. Given that the stock price data often contain both linear and non-linear patterns, no single model can be adequate in modelling and predicting time series data. The autoregressive integrated moving average (ARIMA) model cannot deal with non-linear relationships, however, it provides an accurate and effective way to process autocorrelation and non-stationary data in time series forecasting. On the other hand, the neural network provides an effective prediction of non-linear sequences. As a result, in this study, we used a hybrid ARIMA and neural network model to forecast the monthly closing price of the Shanghai composite index and Shenzhen component index.

• Journal of The Korean Astronomical Society
• /
• v.48 no.5
• /
• pp.299-311
• /
• 2015

We report first results from KVN and VERA Array (KaVA) VLBI observations obtained in the frame of our Plasma-physics of Active Galactic Nuclei (PAGaN) project. We observed eight selected AGN at 22 and 43 GHz in single polarization (LCP) between March 2014 and April 2015. Each source was observed for 6 to 8 hours per observing run to maximize the uv coverage. We obtained a total of 15 deep high-resolution images permitting the identification of individual circular Gaussian jet components and three spectral index maps of BL Lac, 3C 111 and 3C 345 from simultaneous dual-frequency observations. The spectral index maps show trends in agreement with general expectations – flat core and steep jets – while the actual value of the spectral index for jets shows indications for a dependence on AGN type. We analyzed the kinematics of jet components of BL Lac and 3C 111, detecting superluminal proper motions with maximum apparent speeds of about 5c. This constrains the lower limits of the intrinsic component velocities to ~ 0.98c and the upper limits of the angle between jet and line of sight to ~20°. In agreement with global jet expansion, jet components show systematically larger diameters d at larger core distances r, following the global relation d ≈ 0.2r, albeit within substantial scatter.

• Biomolecules & Therapeutics
• /
• v.27 no.6
• /
• pp.553-561
• /
• 2019

Rab25, a member of the Rab11 small GTPase family, is central to achieving cellular polarity in epithelial tissues. Rab25 is highly expressed in epithelial cells of various tissues including breast, vagina, cervix, the gastrointestinal tract, and skin. Rab25 plays key roles in tumorigenesis, mainly by regulating epithelial differentiation and proliferation. However, its role in skin physiology is relatively unknown. In this study, we demonstrated that Rab25 knock-out (KO) mice show a skin barrier dysfunction with high trans-epidermal water loss and low cutaneous hydration. To examine this observation, we investigated the histology and epidermal differentiation markers of the skin in Rab25 KO mice. Rab25 KO increased cell proliferation at the basal layer of epidermis, whereas the supra-basal layer remained unaffected. Ceramide, which is a critical lipid component for skin barrier function, was not altered by Rab25 KO in its distribution or amount, as determined by immunohistochemistry. Notably, levels of epidermal differentiation markers, including loricrin, involucrin, and keratins (5, 14, 1, and 10) increased prominently in Rab25 KO mice. In line with this, depletion of Rab25 with single hairpin RNA increased the expression of differentiation markers in a human keratinocyte cell line, HaCaT. Transcriptomic analysis of the skin revealed increased expression of genes associated with skin development, epidermal development, and keratinocyte differentiation in Rab25 KO mice. Collectively, these results suggested that Rab25 is involved in the regulation of epidermal differentiation and proliferation.