Stock Market is always being the most important role in modern capital market. And Stock Market is becoming one the most popular investment tools these days. Because of the Globalization of capital markets, the spreading of capital becomes faster and easier. The development of capital markets evoke the interesting of scholars and the field of stock market prediction attract scholars and researchers from different background. There are two approaches of predicting stock market - fundamental analysis and technical analysis. The purpose of my work was to predict three stock markets in the world, namely Taiwan Weighted Index (IDXWT), Hong Kong Hang Seng Index (HSI) and Dow Jones Industrial Average (DJI) using technical analysis and Dynamic Bayesian Network (DBN).This thesis is based on Wang¡¦s thesis [Wan05] ¡§Investment Decision Support with Dynamic Bayesian Networks¡¨. According to different characteristic of 3 stock markets, we divide 3 different markets into 3 experiments. For each market, we expect we can find the best indicators and trading signals. The first experiment involves Taiwan Weighted Index as our prediction target; the second one uses Hong Kong Hang Seng Index and the third experiment employs Dow Jones Industrial Average. As a result, Taiwan Stock market (both 15-day and 20-day Moving Average)can make higher returns than buy-and-hold, RSI_6 and KD. And we also have the same conclusion of Hang Seng Index and Dow Jones Industrial Average. The best return from 15-day MA and 20-day MA of Taiwan Stock market is 47.95% and 60.21%, respectively. Moreover, the best result of Hang Seng Index is 60.06% for 4 years and 25.83% for Dow Jones Industrial Average. All of the best results can make higher returns than each of their buy-and-hold, RSI_6 and KD. In the conclusion, we may say that this paper can provide a direction to investors while they are using these technical indicators to predict these particular stock markets.
| Identifer | oai:union.ndltd.org:NSYSU/oai:NSYSU:etd-0620107-163418 |
| Date | 20 June 2007 |
| Creators | Ieong, KuongCheong |
| Contributors | BingChiang Jeng, Yuh-Jiuan Tsay, Yao-tsung Chen, Wei-Po Lee, Chia-Mei Chen |
| Publisher | NSYSU |
| Source Sets | NSYSU Electronic Thesis and Dissertation Archive |
| Language | English |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0620107-163418 |
| Rights | off_campus_withheld, Copyright information available at source archive |
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