We present a detailed bubble analysis of the Bitcoin to US Dollar price dynamics from January 2012 to February 2018. We introduce a robust automatic peak detection method that classifies price time series into periods of uninterrupted market growth (drawups) and regimes of uninterrupted market...

The aim of this article is to examine how the dynamics of correlations between two emerging countries (Brazil and Mexico) and the US evolved from January 2003 to December 2013. The main contribution of this study is to explore whether the plunging stock market in the US, in the aftermath of...

Information on economic policy uncertainty (EPU) does matter in predicting oil returns especially when accounting for omitted nonlinearities in the relationship between these two variables via a time-varying coefficient approach. In this work, we compare the forecastability of standard, Bayesian...

In this paper, we study the effectiveness of carry trade strategies during and after the financial crisis using a flexible approach to modeling currency returns. We decompose the currency returns into multiplicative sign and absolute return components, which exhibit much greater predictability...

This paper considers the problem of forecasting real and financial macroeconomic variables across a large number of countries in the global economy. To this end, a global vector autoregressive (GVAR) model previously estimated over the 1979:Q1–2003:Q4 period by Dees, de Mauro, Pesaran, and...

The ex-ante forecast of the SP500 index discussed in Fantazzini (2010a), covering the time sample 14/04/2009-09/10/2010, and originally submitted to the Economics Bulletin on the 15/05/2009 is analyzed. It is found that the realized values of the SP500 index trailed the forecasted values quite...

Forecasting the world economy is a difficult task given the complex interrelationships within and across countries. This paper proposes a number of approaches to forecast short-term changes in selected world economic variables and aims, first, at ranking various forecasting methods in terms of...

The substantial fluctuations in oil prices in the wake of the COVID-19 pandemic and the Russian invasion of Ukraine have highlighted the importance of tail events in the global market for crude oil which call for careful risk assessment. In this paper we focus on forecasting tail risks in the...

A reflection on the lackluster growth over the decade since the Global Financial Crisis has renewed interest in preventative measures for a long-standing problem. Advances in machine learning algorithms during this period present promising forecasting solutions. In this context, the paper...

The energy transition requires substantial amounts of metals such as copper, nickel, cobalt and lithium. Are these metals a key bottleneck? We identify metal-specific demand shocks, estimate supply elasticities and pin down the price impact of the energy transition in a structural scenario...