Testing market imperfections via genetic programming
Created by W.Langdon from
gp-bibliography.bib Revision:1.8051
- @PhdThesis{Jansen:thesis,
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author = "Sebastian Jansen",
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title = "Testing market imperfections via genetic programming",
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school = "Institut fur Financial Management, Universitaet
Hohenheim",
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year = "2011",
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type = "Dr. oec",
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address = "Bonn, Germany",
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month = "17 " # mar,
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keywords = "genetic algorithms, genetic programming, Market
Efficiency, Excess Returns",
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URL = "http://opus.ub.uni-hohenheim.de/volltexte/2011/588/",
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URL = "http://opus.ub.uni-hohenheim.de/volltexte/2011/588/pdf/Dissertation_Testing_Market_Imperfections_via_Genetic_Programming_Sebastian_Jansen.pdf",
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size = "161 pages",
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abstract = "The thesis checks the validity of the efficient
markets hypothesis focusing on stock markets. Technical
trading rules are generated by using an evolutionary
optimisation algorithm (Genetic Programming) based on
training samples. The trading rules are subsequently
applied to data samples unknown to the algorithm
beforehand. The benchmark strategy consists of a
classic buy-and-hold strategy in the DAX and the Hang
Seng. The trading rules generally fail at consistently
beating the benchmark thus indicating that market
efficiency holds.",
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abstract = "Gegenstand der Dissertation ist die Uberpruefung von
Markteffizienz auf Aktienmaerkten. Hierzu werden
technische Handelsregeln mit Hilfe eines evolutionaeren
Optimierungsalgorithmus (Genetic Programming) anhand
von Trainingsdaten erlernt und anschliessend auf eine
unbekannte Zeitreihe angewandt. Als Benchmark dient
eine klassische buy-and-hold Strategie im DAX und Hang
Seng. Es zeigt sich, dass die mittels Genetic
Programming generierten Handelsstrategien den Benchmark
auf risikoadjustierter Basis nicht durchgaengig
schlagen konnen und somit die These effizienter Maerkte
fuer den DAX und den Hang Seng gueltig ist.",
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notes = "in English. Supervisor Prof. Dr. Hans-Peter Burghof",
- }
Genetic Programming entries for
Sebastian Jansen
Citations