The estimation of risk at extreme levels of significance (such as 0.1%) can be crucial to capture the losses during market downturns, such as the global financial crisis and the COVID-19 market crash. For many existing models, it is challenging to estimate risk at extreme levels of significance....

We apply functional data analysis to survey expectations data, and show that functional principal component analysis combined with functional regression analysis is a fruitful way of capturing the effects of others' forecasts on a respondent's inflation forecasts. We estimate forward-looking...

We propose a sequential monitoring scheme to find structural breaks in real estate markets. The changes in the real estate prices are modeled by a combination of linear and autoregressive terms. The monitoring scheme is based on a detector and a suitably chosen boundary function. If the...