Pattern Recognition Through Perceptually Important Points In Financial Time Series
Price
Free (open access)
Transaction
Volume
38
Pages
12
Published
2004
Size
402 kb
Paper DOI
10.2495/CF040241
Copyright
WIT Press
Author(s)
G. Zaib, U. Ahmed & A. Ali
Abstract
Technical Analysis is a financial risk management practice that has been in use since the advent of the stock market and Pattern Recognition is an indivisible part of it. There has been a lot of research into pattern recognition in time series. Existing pattern recognition techniques lack dynamic extensibility. They do not provide any interfaces in order to include new patterns for recognition dynamically. This limits the operability of these techniques to a particular domain. This research devises a new technique for domain independent pattern recognition while giving sufficient speed and accuracy. This enables it to be used by critical Decision Support Systems for time series of different domains. The system emulates the human visual cognition process by implementing the
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