TY - JFULL AU - Abdalla Kablan and Joseph Falzon PY - 2012/9/ TI - The Use of Dynamically Optimised High Frequency Moving Average Strategies for Intraday Trading T2 - International Journal of Economics and Management Engineering SP - 2051 EP - 2058 VL - 6 SN - 1307-6892 UR - https://publications.waset.org/pdf/692 PU - World Academy of Science, Engineering and Technology NX - Open Science Index 68, 2012 N2 - This paper is motivated by the aspect of uncertainty in financial decision making, and how artificial intelligence and soft computing, with its uncertainty reducing aspects can be used for algorithmic trading applications that trade in high frequency. This paper presents an optimized high frequency trading system that has been combined with various moving averages to produce a hybrid system that outperforms trading systems that rely solely on moving averages. The paper optimizes an adaptive neuro-fuzzy inference system that takes both the price and its moving average as input, learns to predict price movements from training data consisting of intraday data, dynamically switches between the best performing moving averages, and performs decision making of when to buy or sell a certain currency in high frequency. ER -