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.
| Identifer | oai:union.ndltd.org:LACETR/oai:collectionscanada.gc.ca:QMM.35711 |
| Date | January 1998 |
| Creators | Ipperciel, David. |
| Contributors | Goffin, Jean-Louis (advisor), Krysanowski, Lawrence (advisor) |
| Publisher | McGill University |
| Source Sets | Library and Archives Canada ETDs Repository / Centre d'archives des thèses électroniques de Bibliothèque et Archives Canada |
| Language | English |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
| Format | application/pdf |
| Coverage | Doctor of Philosophy (Faculty of Management.) |
| Rights | All items in eScholarship@McGill are protected by copyright with all rights reserved unless otherwise indicated. |
| Relation | alephsysno: 001656513, proquestno: NQ50190, Theses scanned by UMI/ProQuest. |
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