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In a recent paper, using data from Forbes Global 2000, we have observed that the upper tail of the firm size distribution (by assets) falls off much faster than a Pareto distribution. The missing mass was suggested as an indicator of the size of the Shadow Banking (SB) sector. This short note provides the latest figures of the missing assets for 2013, 2014 and 2015. In 2013 and 2014 the dynamics of the missing assets continued being strongly correlated with estimates of the size of the SB sector of the Financial Stability Board. In 2015 we find a sharp decrease in the size of missing assets, suggesting that the SB sector is deflating.
Using public data (Forbes Global 2000) we show that the asset sizes for the largest global firms follow a Pareto distribution in an intermediate range, that is ``interrupted by a sharp cut-off in its upper tail, where it is totally dominated by finan
We consider how to optimally allocate investments in a portfolio of competing technologies using the standard mean-variance framework of portfolio theory. We assume that technologies follow the empirically observed relationship known as Wrights law,
The number of Italian firms in function of the number of workers is well approximated by an inverse power law up to 15 workers but shows a clear downward deflection beyond this point, both when using old pre-1999 data and when using recent (2014) dat
We analyze export data aggregated at world global level of 219 classes of products over a period of 39 years. Our main goal is to set up a dynamical model to identify and quantify plausible mechanisms by which the evolutions of the various exports af
This article provides an overview of Supervised Machine Learning (SML) with a focus on applications to banking. The SML techniques covered include Bagging (Random Forest or RF), Boosting (Gradient Boosting Machine or GBM) and Neural Networks (NNs). W