Output details
11 - Computer Science and Informatics
University of York
Output title
A learning adaptive Bollinger band system
Type
E - Conference contribution
Name of conference/published proceedings
2012 IEEE Conference on Computational Intelligence for Financial Engineering and Economics (CIFEr 2012) : New York City, New York, USA, 29-30 March 2012
Volume number
-
Issue number
-
First page of article
40
ISSN of proceedings
-
Year of publication
2012
Number of additional authors
1
Additional information
<24>CiFEr is the main IEEE conference in its area. This article contributes to the state-of-the-art in financial forecasting through the development of a novel adaptive approach based on heterogeneous meta-learning, the strengths of which are confirmed on both simulated and real-world data. A methodological contribution to machine learning is also made as the Learning Classifier System paradigm is extended to make use of a population of signal processors other than classifiers. The resulting tool extends substantially the potential of a popular financial indicator (Bollinger Bands) by optimising its parameters, and exploiting the power of a population of such indicators.
Interdisciplinary
-
Cross-referral requested
-
Research group
G - Artificial Intelligence
Citation count
0
Proposed double-weighted
No
Double-weighted statement
-
Reserve for a double-weighted output
No
Non-English
No
English abstract
-
