A COMPARATIVE STUDY OF FASTICA AND GRADIENT ALGORITHMS FOR STOCK MARKET ANALYSIS
A COMPARATIVE STUDY OF FASTICA AND GRADIENT ALGORITHMS FOR STOCK MARKET ANALYSIS

Summary/Abstract: In this paper we proved that a fast fixed point algorithm known as FastICA algorithm depending on maximization the nongaussianity by using the ne-gentropy approach is one of the best algorithm for solving ICA model. We compare this algorithm with Gradient algorithm. The Abu Dhabi Islamic Bank (ADIB) used as illustrative example to evaluate the performance of these two algorithms. Experimental results show that the FastICA algorithm is more robust and faster than Gradient algorithm in stock market analysis.

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