Stock data analysis

• Main Author: Chua, Alfred Jia Peng.
• Other Authors: Foo Say Wei
• Format: Final Year Project
• Language: English
• Published: 2009
• Subjects: DRNTU::Engineering::Electrical and electronic engineering::Computer hardware, software and systems
• Online Access: http://hdl.handle.net/10356/18013
• Institution: Nanyang Technological University

This report provides an in-depth documentation on the progress of developing a software application that enables its user to analyze stock data through the use of technical indicators and alert the user on buying and selling opportunities from its built-in trading systems. Five technical indicators have been selected for back testing so as to uncover profitable trading strategies. These five indicators fall under different categories of indicators - MACD is used for identifying trending markets, Bollinger Bands for spotting volatility (can also be used for trends), and Slow Stochastic, CCI and RSI (momentum indicators) are used for checking overbought and oversold conditions. It has been observed that trend and volatility indicators, such as the MACD and Bollinger Bands produced better returns compared to the momentum indicators, despite the fact that momentum indicators generally have better wins to losses ratio. The best returns are achieved when MACD, Bollinger Bands, Slow Stochastic and RSI are combined to generate buy/sell signals. This shows that trend and momentum indicators can complement one another and produce even better results than when the indicators are used independently. The end product is a trading strategy or system that utilizes the MACD to identify trend reversals, Bollinger Bands for spotting channel breakouts, and Slow Stochastic and RSI to detect oversold levels. Stop-loss orders are also employed to this strategy to limit losses and preserve capital; returns obtained are lower than without stop-loss but still outperformed the return of the STI in the back testing period.