In this issue we have: A multivariate generalized independent factor GARCH model with an application to financial stock returns ; Recent Changes in Crop Production Costs and Implications for Regional Competitiveness.
|We propose a new multivariate factor GARCH model, the GICA-GARCH model , where the data are assumed to be generated by a set of independent components (ICs). This model applies independent component analysis (ICA) to search the conditionally heteroskedastic latent factors. We will use two ICA approaches to estimate the ICs. The first one estimates the components maximizing their non-gaussianity, and the second one exploits the temporal structure of the data. After estimating the ICs, we fit an univariate GARCH model to the volatility of each IC. Thus, the GICA-GARCH reduces the complexity to estimate a multivariate GARCH model by transforming it into a small number of univariate volatility models. We report some simulation experiments to show the ability of ICA to discover leading factors in a multivariate vector of financial data. An empirical application to the Madrid stock market will be presented, where we com! pare the forecasting accuracy of the GICA-GARCH model versus the orthogonal GARCH one.|
|Keywords:||ICA, Multivariate GARCH, Factor models, Forecasting volatility|
|By:||Olson, Kent D.
|Rapid increases in input prices have cast a large shadow over the enthusiasm created by higher product prices. In this paper we forecast the trends in input prices and use these trends to forecast production costs for corn, soybeans, and wheat at the national level, and for regions within the U.S. Although the Heartland is forecast to maintain its competitive edge in corn costs, the Northern Great Plains and Prairie Gateway regions are forecast to increase their competitive advantage due to using less fertilizer and chemicals on average which results in relative costs decreasing for these regions. For soybeans, the Heartland is forecast to maintain its competitive edge although the Eastern Uplands region was forecast to increase its competitive advantage due to using less fertilizer and chemicals. With wheat, the Prairie Gateway region was forecast to have the best improvement in relative costs, while the Northern! Great Plains loses some competitive edge. However, since individual farms have different costs due to physical conditions and timing of input purchases, and crop prices are fluctuating, actual profit levels are hard to predict.|
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