We show that machine learning methods, in particular, extreme trees and neural networks
(NNs), provide strong statistical evidence in favor of bond return predictability. NN forecasts …

How did the Subprime Crisis, a problem in a small corner of US financial markets, affect the
entire global banking system? To shed light on this question we use principal components …

Abstract The Term Auction Facility (TAF), the first auction-based liquidity initiative by the
Federal Reserve during the global financial crisis, was aimed at improving conditions in the …

This paper adds to the research efforts that aim to bridge the divide between macro and
micro approaches to exchange rate economics by examining the linkages between …

This paper provides a comprehensive evaluation of the short-horizon predictive ability of
economic fundamentals and forward premiums on monthly exchange-rate returns in a …

This chapter provides a comprehensive review of the statistical and economic methods used
for evaluating exchange rate predictability. It analyzes the short‐horizon forecasting …

This article investigates the out-of-sample predictability of bond excess returns. We assess
the economic value of the forecasting ability of empirical models based on long-term forward …

Using a broad selection of 53 carbon (EUA) related, commodity and financial predictors, we
provide a comprehensive assessment of the out-of-sample (OOS) predictability of weekly …

How are financial markets pricing the monetary policy outlook? We use surveys to
decompose excess returns on money market instruments into expectation errors and term …

We analyze the effects of prudential regulation on short-term interest rates. The European
Market Infrastructure Regulation (EMIR) induces clearing houses (CCPs) to supply large …