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Keywords:Quantile Regression 

Working Paper
Predicting Operational Loss Exposure Using Past Losses

Operational risk models, such as the loss distribution approach, frequently use past internal losses to forecast operational loss exposure. However, the ability of past losses to predict exposure, particularly tail exposure, has not been thoroughly examined in the literature. In this paper, we test whether simple metrics derived from past loss experience are predictive of future tail operational loss exposure using quantile regression. We find evidence that past losses are predictive of future exposure, particularly metrics related to loss frequency.
Finance and Economics Discussion Series , Paper 2016-2

Discussion Paper
Optimists and Pessimists in the Housing Market

Given momentum in house prices over business cycles, research on consumer beliefs since the financial crisis has honed in on the potential importance of extrapolative beliefs?myopically assuming trends in asset prices will continue. Extrapolation is frequently cited as a central reason for excessively optimistic expectations about future asset prices, featuring prominently, for example, in the irrational exuberance narrative of Shiller. Other influential work since the Great Recession has emphasized the outsized role that extrapolative optimists can have in bubble formation. In this post, we ...
Liberty Street Economics , Paper 20191016

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