MARK's Column

Prof. Kai Keung Mark is a retired professor, Dept. of Biology, The Chinese University of Hong Kong and Dept. Head and Principal Lecturer, Dept. of Science, Hong Kong Institute of Education. He has three biotechnology patents. He uses his understanding of high technology to forecast market movements . He has published 13 articles in Financial Trend, and leading Hong Kong stock analysis journal plus many other Mark's letters since 1987. His prediction reliability rate reached 80%. He accurately predicted the October crash (10/18/87), the bottom level of 1990(3/5/90), the peak level of 1994 (5/11/92), the peak level of 1997 (2/12/96), the peak level of 2,000 (8/22/99), the peak in March 2000 (2/20/2000), the bottom in September, 2001, the US bottom in 2003 (5/28/2003), the HK bottom in 2003 (6/13/2003), the US peak in 2007 (11/14/2007), and the HK peak in 2007 (1/9/2008).

Near Term Strategy

May 23, 2000

The prediction that investors should take profit in the big drop as stated in the 4/15 and 5/5 Mark's column has been validated.
The HSI has penetrated the long support line established since August 1999 down side. This has bearish implications as stated in 5/5 Mark's Column.
There will be more major downward movements in the coming few months.
One good short term opportunity with gains of over 500-1,000 point is near. There will be a sharp upward recovery after such a big drop, but to catch this opportunity hinges on timing. One useful hint that the bottoming is the low trading volume, and the second hint is that the index has penetrated the fan line upside. The fan line is drawn between the final top (18,400), and the following correction (15,900).
The upswing is short, so do not hang on for too long. Take profit while you can.

The information above is supplied by the author specially for InTechTra's Hong Kong Stocks Report. The opinions in this special column is solely that of the author and may or may not represent the views of Hong Kong Stocks Report. InTechTra is indemnified for any damage or loss that might be associated with the use of the information.