We propose to pool alternative systemic risk rankings for financial institutions using the method of principal components. The resulting overall ranking is less affected by estimation uncertainty and model risk. We apply our methodology to disentangle the common signal and the idiosyncratic...

This paper analyses the long-memory properties of high frequency financial time series. It focuses on temporal aggregation and the influence that this might have on the degree of dependence of the series. Fractional integration or I(d) models are estimated with a variety of specifications for...

We develop a new targeted maximum likelihood estimation method that provides improved forecasting for misspecified linear autoregressive models. The method weighs data points in the observed sample and is useful in the presence of data generating processes featuring structural breaks, complex...

This paper employs a price-based measure of integration, namely stock return differentials between ten emerging Asian economies and the US (as an indicator of global integration), as well as Japan and the Asian region (as two alternative indicators of regional integration), to test for mean...

We introduce a dynamic network model of interbank lending and estimate the parameters by indirect inference using network statistics of the Dutch interbank market from mid-February 2008 through April 2011. We find that credit-risk uncertainty and peer monitoring are significant factors in...

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...