Stock market investment strategy and chart pattern reconnaissance: An intraday Dow Jones Index data application
This work introduces a new approximation of the flag price pattern recognition. A trading rule which provides positive risk-adjusted returns for intraday data of the Dow Jones Industrial Average Index is developed. In order to mitigate the ata snooping problem we use a data set of more than 90,000 o...
| Autor Principal: | Cervelló-Royo, Roberto; Facultad de Administración y Dirección de Empresas Universidad Politécnica de Valencia |
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| Otros Autores: | Guijarro Martínez, Francisco; Profesor Titular en el Depto. de Economía y Ciencias Sociales y Vicedecano de Alumnado, Relaciones con Empresa e Investigación en la Facultad de Administración y Dirección de Empresas de la Universidad Politécnica de Valencia (UPV), Michniuk, Karolina; Phd Candidate por la Hamburg University of Applied Sciences (HAW) y la Universidad Politécnica de Valencia (UPV) |
| Formato: | info:eu-repo/semantics/article |
| Idioma: | spa |
| Publicado: |
Pontificia Universidad Javeriana
2014
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| Materias: | |
| Acceso en línea: |
http://revistas.javeriana.edu.co/index.php/cuadernos_admon/article/view/8529 |
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| Sumario: |
This work introduces a new approximation of the flag price pattern recognition. A trading rule which provides positive risk-adjusted returns for intraday data of the Dow Jones Industrial Average Index is developed. In order to mitigate the ata snooping problem we use a data set of more than 90,000 observations, results are reported over 96 different configurations of the trading rule parameters. Results gathered from the whole sample confirm that the trading rule provides a positive return, even after considering the risk. Moreover, it beats the benchmark in the mean variance sense. |
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