Trading Systems: Secrets of the Masters
Trading Systems: Secrets of the Masters
Discrete Random Signals and Statistical Signal Processing
Discrete Random Signals and Statistical Signal Processing
Robust blind source separation by beta divergence
Neural Computation
Nonnegative Matrix and Tensor Factorizations: Applications to Exploratory Multi-way Data Analysis and Blind Source Separation
Csiszár’s divergences for non-negative matrix factorization: family of new algorithms
ICA'06 Proceedings of the 6th international conference on Independent Component Analysis and Blind Signal Separation
A multi-agent decision support system for stock trading
IEEE Network: The Magazine of Global Internetworking
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The paper presents a new method for multidimensional representation of financial information in the context of technical analysis. Typically, technical analysis of given financial instrument does not take into account a broader view on the market. We want to analyze the information about the environment of the primary instrument. Hence, there is the problem of the results synthesis in a coherent and a transparent way. In this paper we propose aggregation of the information from different sources into a single aggregate graph which enables a technical analysis. The complete information is obtained with the p-norms approach. To assess the impact of particular information on the primary instrument we applied divergence measures such as Csiszár divergence and Beta divergence. Practical experiment on the stock exchange data confirmed the validity of proposed approach.