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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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| Lehmann, Niklaus; Finger, Robert. |
| We investigate impacts of climate change (CC) and likely increases in price risks on income, income variability, utility and on adaptation responses in crop production in Western Switzerland. To this end, a bio-economic model is used that combines a crop growth model with an economic decision model non-parametrically using genetic algorithms. Our analysis focuses on the farm-level, which enables us to integrate a much wider set of potential adaptation responses in our analysis. The model is applied to four scenarios that represent likely changes in environmental conditions due to CC as well as increasing price risks due to market liberalization, and combinations thereof. It shows that CC has the larger influence on farm-level income and utility as well as... |
| Tipo: Presentation |
Palavras-chave: Genetic Algorithms; Agricultural Modeling; Climate Change; Price risks; Risk and Uncertainty; Q12. |
| Ano: 2012 |
URL: http://purl.umn.edu/122533 |
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