While the monotonic binning algorithm has been widely used in scorecard and PD model (Probability of Default) developments, the similar idea can be generalized to LGD (Loss Given Default) models. 674 more words
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As mentioned in the previous post (https://statcompute.wordpress.com/2017/06/29/model-operational-loss-directly-with-tweedie-glm/), we often need to model non-negative numeric outcomes with zeros in the operational loss model development. Tweedie GLM provides a convenient interface to model non-negative losses directly by assuming that aggregated losses are the Poisson sum of Gamma outcomes, which however might not be well supported empirically from the data generation standpoint. 769 more words
In the previous post (https://statcompute.wordpress.com/2017/06/29/model-operational-loss-directly-with-tweedie-glm), it has been explained why we should consider modeling operational losses for non-material UoMs directly with Tweedie models. However, for material UoMs with significant losses, it is still beneficial to model the frequency and the severity separately. 748 more words
In the development of operational loss forecasting models, the Frequency-Severity modeling approach, which the frequency and the severity of a Unit of Measure (UoM) are modeled separately, has been widely employed in the banking industry. 574 more words
This would be a very high-level simplification of what in reality is an incredibly complex exercise involving risk modeling experts and quants.
Banking “stress tests” are usually presented to the bank by regulators as a macroeconomic scenario (i.e.: unemployment rate increases, inflation decreases, etc.) which must then be converted to financial “risk factors” that impact the bank in some way. 158 more words
Before doing any certification in the field of networking you should have answers of following questions.
why should i learn networking?
is making career in field of networking safe? 1,138 more words