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A new nonlinearity test to circumvent the limitation of Volterra expansion with application
Yongchang Hui,Wing-Keung Wong,Zhidong Bai,Zhen-Zhen Zhu 한국통계학회 2017 Journal of the Korean Statistical Society Vol.46 No.3
In this paper we study estimating the joint conditional distributions of bivariate longitudinal outcomes using regression models and copulas. For the estimation of marginal models we consider a class of time-varying transformation models and combine the two marginal models using Gaussian copulas. Our models and estimation method can be applied in many situations where the conditional mean-based models are not good enough. Gaussian copulas combined with time-varying transformation models may allow convenient and easy-to-interpret modeling for the joint conditional distributions for bivariate longitudinal data. We derive the asymptotic properties for the copula based estimators of the joint conditional distribution functions. For illustration we apply our estimation method to an epidemiological study of childhood growth and blood pressure and also investigate finite sample properties of our procedures through a simulation study.
( James J. Kung ),( Wing Keung Wong ) 세종대학교 경제통합연구소 (구 세종대학교 국제경제연구소) 2009 Journal of Economic Integration Vol.24 No.1
In the aftermath of the Asian financial crisis, a series of reform and liberalization measures have been implemented in Singapore to upgrade its financial markets. This study investigates whether these measures have led to less profitability for those investors who employ technical rules for trading stocks. Our results show that the three trading rules consistently generate higher annual returns for 1988-1996 than those for 1999-2007. Further, they generally perform better than the buy-and-hold (BH) strategy for 1988-1996 but perform no better than the BH strategy for 1999-2007. These findings suggest that the efficiency of the Singapore stock market has been considerably enhanced by the measures implemented after the crisis.
Examining Stock Volatility in the Segmented Chinese Stock Markets: A SWARCH Approach
ZHUO QIAO,WEIWEI QIAO,Wing-Keung Wong 연세대학교 동서문제연구원 2010 Global economic review Vol.39 No.3
This study adopts the SWARCH model to examine the volatile behavior and volatility linkages among the four major segmented Chinese stock indices.We find strong evidence of a regime shift in the volatility of the four markets, and the SWARCH model appears to outperform standard generalized autoregressive conditional heteroskedasticity (GARCH) family models. The evidence suggests that, compared with the A-share markets, B-share markets stay in a high-volatility state longer and are more volatile and shift more frequently between high- and low-volatility states. In addition, the relative magnitude of the high-volatility compared with that of the low-volatility state in the B-share markets is much greater than the case in the two A-share markets. B-share markets are found to be more sensitive to international shocks, while A-share markets seem immune to international spillovers of volatility. Finally, analyses of the volatility spillover effect among the four stock markets indicate that the A-share markets play a dominant role in volatility in Chinese stock markets.
ZHUO QIAO,WEIWEI QIAO,Wing-Keung Wong 연세대학교 동서문제연구원 2011 Global economic review Vol.40 No.3
Many researchers have investigated the existence of day-of-the-week effects in different financial markets. However, they have usually adopted a parametric approach, which is known to have a few limitations. This paper adopts a non-parametric stochastic dominance (SD) approach to examine the day-of-the-week effects in Chinese stock markets. In contrast to the extensive evidence of day-of-the-week effects disclosed by a parametric mean-variance (MV) approach, our SD tests show that the day-of-the-week effect is much weaker. We find that there are only Wednesday effects in Chinese A-share and B-share stock markets.