This paper provides a new index of global macroeconomic uncertainty and investigates the cross-country transmission of uncertainty using a global vector autoregressive (GVAR) model. The index measures the dispersion of forecasts resulting from parameter uncertainty in the GVAR. Over the period...

We propose an approach for jointly measuring global macroeconomic uncertainty and bilateral spillovers of uncertainty between countries using a global vector autoregressive (GVAR) model. Over the period 2000Q1-2020Q4, our global index is able to summarize a variety of uncertainty measures, such...

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...

This paper deals with the economics of Bitcoins in two ways. First, it broadens the discussion on how to capture Bitcoins using economic terms. Center stage in this analysis take the discussion of some unique characteristics of this market as well as the comparison of Bitcoins and gold. Second,...

We examine 24 global factor premiums across the main asset classes via replication and new-sample evidence spanning 217 years of data. Replication yields ambiguous evidence within a unified testing framework with methods that account for p-hacking. The new-sample evidence reveals that the large...

The objectives are to discern how the three financial sectors' CDS spreads interrelate to each other and with three other risks under the full sample and two subperiods: The 2007 Great Recession, and the 2009 recovery, and to assess the impact of QE1 on those risks in the second subperiod. The...

This study sheds new light on the question of whether or not sentiment surveys, and the expectations derived from them, are relevant to forecasting economic growth and stock returns, and whether they contain information that is orthogonal to macroeconomic and financial data. I examine 16...

The research was conducted in order to study the volatility in gold price returns and its investigation. The data has been collected on daily basis for the tenure of a couple of years starting from 1st January 2009 to 31st September 2011. The models used to run the data are: standard deviation...

The slope coefficient estimator in predictive regressions for stock returns is biased by a lagged stochastic regressor. There is also a spurious regression if the underlying expected return is highly persistent. This paper studies how the interactions between the two biases affect inferences...

We obtain new methodological and empirical perspectives on the fundamental risk-return tradeoff in stock returns by imposing economic and asset pricing motivated constraints on the equity premium. In contrast to highly ambiguous past empirical findings, these constraints result in a nonlinear...