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This paper presents a strategy for a generator to participate and to mitigate the risk effect of price volatility in the Colombian wholesale electricity market. The strategy is used to optimize the generator participation in the long-term market (bilateral market) and the spot market. Additionally, the strategy mitigates the risk of price exposure in the sport market using electricity forward contracts. Numerical results shows that the proposed methodology is more efficient than classical optimization models since this proposal considers the intrinsic price volatility of the long-term and spot markets. [ABSTRACT FROM AUTHOR]

The study of seismic intensity attenuation plays an important role in the analysis of menace that includes historical events. Mapping the intensity attenuation is usually done by regressing the intensity versus distance. Nowadays there are different ways to examine the characteristics of a seismic event using instrumental means, however, the experts face the problem of qualitative nature of the sources of information and the mapping of the relationship between intensity, magnitude and distance for the generation of risk scenarios based on historical information. This paper presents an alternative to map this relationship through artificial neural networks (ANN). As a result, we propose a procedure that was validated through the mapping of the intensities of 68 earthquakes that occurred northern South America, between 1766 and 2004. We found that ANNs present advantages with respect to the conventional models of regression: a. they preserve in a better way the first statistical moment, b. they reflect a minor approximation error and c. the variance explained by the ANN is better than the one from the models of statistical regression. [ABSTRACT FROM AUTHOR]

Modeling and forecasting exchange rates is a big economic headache. This paper uses an artificial neuronal network model to represent the Colombian real exchange index dynamics because it describes the series dynamics better than a self-regressive linear model does, as may be appreciated in the result of the verosimilitud radius contrast. The model was accepted after applying a series of standard tests and contrasting the results against those obtained using a self-regressive linear model. The results indicated that the current value of a series solely depends on its previous value. [ABSTRACT FROM AUTHOR]