Multi-Level Technical Analysis Knowledge System Platform for Stock Market
| Autor: | Kuang-Yu Han, 韓光宇 |
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| Rok vydání: | 2015 |
| Druh dokumentu: | 學位論文 ; thesis |
| Popis: | 103 Investing in stocks is an indispensable and vital way for most investors. Therefore, ways to find out the secrecy of improving the performance of such investment is absolutely important. This study implements a multi-level filtering mechanism knowledge platform for investing in stocks. Each level allows users to choose an appropriate technical knowledge setting, then use the trading strategies in the final level. The knowledge platform allows users to find quickly the combination of knowledge settings, trading strategies, and the effects. As a study, we verify the knowledge settings among several researches by using the system. As a result, we found that Huang Shao Fu’s triple filtration system in a downward trend get better performance. In the upcoming trend, the knowledge settings provided by Zhang Qing Liang by using KD Stochastic parameters is better. Finally, we tuned the KD Stochastic parameters and find a best combination for investment in the period. |
| Databáze: | Networked Digital Library of Theses & Dissertations |
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