The London Interbank Offered Rate (LIBOR) is a widely used indicator of funding conditions in the interbank market. As of 2013, LIBOR underpins more than $300 trillion of financial contracts, including swaps and futures, in addition to trillions more in variable-rate mortgage and student loans....

This paper introduces a major novelty: the empirical estimation of spot intraday yield curves based on tick-by-tick data on the Italian electronic interbank credit market (e-MID). To analyze the consequences of the recent financial crisis, we split the data into four periods, which include...

This paper introduces a major novelty: the empirical estimation of spot intraday yield curves based on tick by tick data on the Italian electronic interbank credit market (e-MID). To analyze the consequences of the recent financial crisis, we split the data into four periods which include events...

This paper introduces a major novelty: the empirical estimation of spot intraday yield curves based on tick-by-tick data on the Italian electronic interbank credit market (e-MID). To analyze the consequences of the recent financial crisis, we split the data into four periods, which include...

We propose a novel reinforcement learning approach to extract high-frequency aggregate growth expectations from asset prices. While much expectations-based research in macroeconomics and finance relies on low-frequency surveys, the multitude of events that pass between survey dates renders...

Previous research finds that machine learning methods predict short-term return variation in the cross-section of stocks, even when these methods do not impose strict economic restrictions. However, without such restrictions, the models' predictions fail to generalize in a number of important...

We show that the news is a rich source of data on distressed firm links that drive firm- level and aggregate risks. The news tends to report about links in which a less popular firm is distressed and may contaminate a more popular firm. This constitutes a contagion channel that yields...

In this paper we adopt a principal components analysis (PCA) to reduce the dimensionality of the term structure and employ autoregressive models (AR) to forecast principal components which, in turn, are used to forecast swap rates. Arguing in favor of structural variation, we propose data...

The paper proposes a data driven adaptive model selection strategy. The selection crite- rion measures economic exante forecasting content by means of trading implied cash flows. Empirical evidence suggests that the proposed strategy is neither exposed to selection bias nor to the risk of...

We propose a new approach to forecasting the term structure of interest rates, which allows to efficiently extract the information contained in a large panel of yields. In particular, we use a large Bayesian Vector Autoregression (BVAR) with an optimal amount of shrinkage towards univariate AR...