http://chineseinput.net/에서 pinyin(병음)방식으로 중국어를 변환할 수 있습니다.
변환된 중국어를 복사하여 사용하시면 됩니다.
( 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.
A Bootstrap Analysis of the Nikkei 225
( James J. Kung ),( Andrew P. Carverhill ) 세종대학교 경제통합연구소(구 세종대학교 국제경제연구소) 2012 Journal of Economic Integration Vol.27 No.3
This study intends to find out whether or not the Nikkei 225 evolves over time in accordance with the following four widely used processes for determining stock prices: random walk with a drift, AR(1), GARCH(1,1), and GARCH(1,1)-M. Given the fact that, in actuality, we have but one sample of time series data, the motivation of this study is to make use of the bootstrap technology to deal with this one-sample problem. Specifically, we use the bootstrap technique to generate 2,000 artificial Nikkei series from each process and compute the return from the trading rule for each of the 2,000 artificial Nikkei series. Then, we construct a 95% bootstrap percentile interval with these 2,000 returns and determine if it contains the return computed from the actual Nikkei series. If it does, we claim that returns from the artificial Nikkei series are in agreement with those from the actual Nikkei series. Our results show that, of the four processes, GARCH(1,1)-M generates returns that are most agreeable with those computed from the actual Nikkei series. An important implication of this study is that a proper model for pricing Nikkei-related derivatives is one that uses the GARCH(1,1)-M process to depict the dynamics of the Nikkei return series.