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| Roberts, Matthew C.. |
| Although there is little academic research that supports the usefulness of technical analysis, its use remains widespread in commodity markets. Much prior research into technical analysis suffered from data-snooping biases. Using genetic programming, ex ante optimal technical trading strategies are identified. Because they are mechanically generated from simple arithmetic operators, they are free of the data-snooping bias common in technical analysis research. These rules are clearly capable of forecasting periods of high and low volatility, but rules generated for corn and soybeans cannot consistently generate profits in the presence of transactions costs. Rules generated for wheat futures produce profits that are weakly significant, both... |
| Tipo: Conference Paper or Presentation |
Palavras-chave: Technical Analysis; Genetic Algorithms; Commodity Markets; Futures Markets; Marketing. |
| Ano: 2003 |
URL: http://purl.umn.edu/18974 |
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