Forex exchange prediction using support vector machine

• Main Author: Modi Ayush
• Other Authors: Wang Lipo
• Format: Final Year Project
• Language: English
• Published: 2015
• Subjects: DRNTU::Engineering::Electrical and electronic engineering::Control and instrumentation::Control engineering
• Online Access: http://hdl.handle.net/10356/64661
• Institution: Nanyang Technological University

Foreign Exchange Market is a fast moving market with the highest returns as compared to other forms of financial trading. This makes it very popular among traders and financial investors. It is thus important to come up with tools to predict the future price and movement of this market. Many multi-national companies also eye such researches and products as it helps them cut losses when trading in multiple currencies. Computational Intelligence has come up as a major field to be used in technical analysis for foreign market exchange prediction and has been fairly popular as it reduces the error in the predicted data more than other traditional models. Among various computational intelligence model, Support Vector Machine and Support Vector Regression are relatively newer techniques but has been producing better results as compared to other algorithms. This paper reviews the literature in this field and analyses the current state of research. It further notes the efficacy of various hybrid models based on Support Vector Machine and discusses the future areas of based on the analysis of the current state of research.