With the popularity of investment and the diversified development of financial instruments, so it has become a common way to obtain additional wealth through investments. Among them, the high liquidity of stocks and the low barriers to entry have made them subject to general investment. With the flourishing development of Fintech, the invention of intelligent stock-selection platform. Therefore, lead to more convenient and efficient investment. This study combined with fundamental, technical and chip factors, and based on the MCDM method to explore the considerations and decisions of selecting stock among LARGAN, CHPT and TSMC. MCDM method can find out the relative relationship of various factors, and calculate the weights of each factor, find out the key evaluation criteria, order the investment target based on the weights of each factor, and make the best decision. First of all, through the review of relevant literatures, the "Fundamental", "Technical", and "Chip"were selected as the facets of this study. And further in-depth discussion, we identified "Price to Earning Ratio", "Earnings Per Share", "Return on Equity", "Moving Average", "Stochastic Index", "short selling/margin ratio", and "Net-Bought By Institutional Investors" seven minor factors. During the research period, 16 valid questionnaires were recovered from the experts and scholars in related fields. And then using DEMATEL method to calculate the relevance of criterions, we found that "Earnings Per Share" is the most influential factor, which means this factor most easily affects other criterions. And "Net-Bought By Institutional Investors" has maximum relevance, which means experts and scholars consider the criterion is the most important selection criteria. Next, applying the DANP method to calculate the weights of criterions, we found that "Net-Bought By Institutional Investors" has the highest weights, while "Stochastic Index" has the lowest weights, that is to say, this factor is less important to experts and scholars. Finally, we use the VIKOR method for investment evaluation, according to the results from data analysis, TSMC has the highest total performance value, and also the lowest total performance gaps, which is the optimal decision relatively.