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The performance of some new technical signals for investment timing /

Each of the three essays in this dissertation deals with asset timing or allocation using technical techniques and pattern recognition. The first essay uses a technical indicator, the stochastic oscillator, for market timing in the bond market. The trading strategy using this technical indicator is optimized using a genetic algorithm The second essay finds that a measure of market chaos improves the performance of a simple trend-following technique in the stock market. The last essay uses technical analysis for asset allocation. A neural network with technical indicator inputs outperforms both a passive asset mix strategy and a neural network with economic data as inputs.

Identiferoai:union.ndltd.org:LACETR/oai:collectionscanada.gc.ca:QMM.35711
Date January 1998
CreatorsIpperciel, David.
ContributorsGoffin, Jean-Louis (advisor), Krysanowski, Lawrence (advisor)
PublisherMcGill University
Source SetsLibrary and Archives Canada ETDs Repository / Centre d'archives des thèses électroniques de Bibliothèque et Archives Canada
LanguageEnglish
Detected LanguageEnglish
TypeElectronic Thesis or Dissertation
Formatapplication/pdf
CoverageDoctor of Philosophy (Faculty of Management.)
RightsAll items in eScholarship@McGill are protected by copyright with all rights reserved unless otherwise indicated.
Relationalephsysno: 001656513, proquestno: NQ50190, Theses scanned by UMI/ProQuest.

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