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|Title:||Interpretable multi-criteria fuzzy rule based decision models for hedge fund management|
|Citation:||Proceedings of the 2010 IEEE Congress on Evolutionary Computation, held in Barcelona, Spain, July 18-23 2010: pp.1-8|
|Series/Report no.:||IEEE Congress on Evolutionary Computation|
|Conference Name:||Congress on Evolutionary Computation (2010 : Barcelona, Spain)|
|Adam Ghandar, Zbigniew Michalewicz and Ralf Zurbruegg|
|Abstract:||This paper describes an approach to constructing fuzzy rules for predictive modeling that involves a local search heuristic and an evolutionary algorithm. This approach is applied for learning strategies to manage a portfolio that comprises positions in the share market. We provide experimental results comparing the approach to random strategies and the market index. A non-linear prediction model that relates asset performance to a large set of explanatory variables is represented with fuzzy rules. Rulebases are combined to build multi-criteria recommendations for trading decisions that consider different forecast horizons and both risk and return criteria.|
|Appears in Collections:||Aurora harvest|
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