—Stock market is regarded as a highly dynamic and
complex environment consisting of opportunities and risks. All
participants want to earn profits by adopting their investment
strategies. One of the most famous investment strategies is value
investing, which attracts both practitioners and researchers’
attention all over the world. Empirical studies have consistently
found that value stocks outperform the market in the long run,
but it often encounters obstacles to implement this strategy in
practices. Due to the need of in-depth analysis of financial
statements, investors not only need accounting knowledge but
also investment expertise. Among previous studies, the
accounting-based fundamental analysis (F-score) has been a
widely accepted model for value investing. The F-score model
proposed nine fundamental signals to measure a firm’s
financial prospect. However, it is difficult to acquire the implicit
knowledge and interactive considerations of senior experts.
Thus, the evaluation processes of investment experts cannot be
revealed for the others’ reference. To improve the limitations,
this paper integrates fuzzy set theory and decision methods to
propose an innovative model for distinguishing strong financial
prospect stocks within high book-to-market (B/M) banking
stocks. Our empirical study shows the practicability of our
proposed method. It also provides the relative weights and the
interdependence of each measurement variables for the value
—investing style, F-score, fuzzy, ANP.
First Auther, Shen Kao-Yi is with the Department of Finance, Chinese
Culture University (SCE); 231, Sec.2, Chien-Kuo S. Road., Taipei, Taiwan
(corresponding author’s phone number: 886-2-2700-5858 ext.8676; fax:
886-2-27075312; e-mail: email@example.com).
Second Author, Yan Min-Ren is with the Department of International
Business Administration, Chinese Culture University (SCE), Taipei, Taiwan
Cite:Shen Kao-Yi and Yan Min-Ren, "A Hybrid Value Investing Method for the Evaluation of Banking Stocks," International Journal of Trade, Economics and Finance vol.1, no.3, pp. 277-282, 2010.