In this paper, we prove that a fast fixed-point algorithm known as the FastICA algorithm, depending on maximisation of the non-gaussianity via the negentropy approach, is one of the best algorithms for solving the Independent Component Analysis (ICA) model. We compare this algorithm with the gradient algorithm and use the Abu Dhabi Islamic Bank (ADIB) as an illustrative example to evaluate these two algorithms’ performance. Our experimental results show that the FastICA algorithm is more robust and faster than the gradient algorithm in stock market analysis.

1. FULLTEXT: A Comparative Study of FastICA and Gradient Algorithms for Stock Market Analysis, Zip archive data, at least v2.0 to extract, 0.2MB

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