Using Technical Indexes to Quantify the Behavior of Market Profile

• Main Authors: Hung, Li-Tsu, 洪麗足
• Other Authors: Chen, An-Pin
• Format: Others
• Language: zh-TW
• Published: 2014
• Online Access: http://ndltd.ncl.edu.tw/handle/57686912700892249081

碩士 === 國立交通大學 === 管理學院資訊管理學程 === 102 === The "Market Profile" theory developed by J. Peter Steidlmayer has been used by investors to understand the psychological and behavioral responses of stock market traders in reaction to changes in the market. Previous studies have proved that the theory is able to effectively predict market trends. Moreover, trader behavior is qualitative market knowledge and requires many years of trading experience by investors in order to explain it. In recent years, trading software has become commonly available, so the ability to integrate market investor psychology theories with the full knowledge of trader behavior, assisted by information technology transactions, removes the need for subjective judgment. In order for investors to achieve the maximum profit, the method of quantifying trader behavior is an important issue. This study attempts to use the mathematical formulas of technical indicators to quantify the theoretical knowledge of market behavior, based on a back-propagation neural network architecture that shows the theoretical feasibility of quantifying market behavior. This study illustrates that analyzing the empirical market through quantitative indicators based on a neural network model is more effective in enhancing the accuracy of forecasting market fluctuations than by using technical indicators, and, therefore, the feasibility of quantifying the behavior is confirmed.