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We develop a high-dimensional and partly nonlinear non-Gaussian dynamic factor model for the decomposition of systematic default risk conditions into a set of latent components that correspond with macroeconomic/financial, default-specific (frailty), and industry-specific effects. Discrete...
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transparent by nature. However, parameter estimation, signal extraction of the dynamic factors, and the econometric analysis …
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A macro-prudential policy maker can manage risks to financial stability only if currentand future risks can be reliably assessed. We propose a novel framework to assessfinancial system risk. Using a dynamic factor framework based on state-space methods, we model latent macro-financial and credit...
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We develop a multivariate unobserved components model to extract business cycle and financial cycle indicators from a panel of economic and financial time series of four large developed economies. Our model is flexible and allows for the inclusion of cycle components in different selections of...
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We develop a new targeted maximum likelihood estimation method that provides improved forecasting for misspecified …-validation procedure. In a set of Monte Carlo experiments we reveal that the estimation method can significantly improve the forecasting …
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