This paper proposes full-Bayes priors for time-varying parameter vector autoregressions (TVP-VARs) which are more robust and objective than existing choices proposed in the literature. We formulate the priors in a way that they allow for straightforward posterior computation, they require...

This paper proposes full-Bayes priors for time-varying parameter vector autoregressions (TVP-VARs) which are more robust and objective than existing choices proposed in the literature. We formulate the priors in a way that they allow for straightforward posterior computation, they require...

The present study, investigates the predictability of Samp;P CNX NIFTY Index returns using Support vector machines (SVM). The performance of the SVM model in forecasting Nifty index returns is rigorously evaluated in terms of widely used statistical metrics like mean absolute error, root mean...

This paper provides new indices of global macroeconomic uncertainty and investigates the cross-country transmission of uncertainty using a global vector autoregressive (GVAR) model. The indices measure the dispersion of forecasts that results from parameter uncertainty in the GVAR. Relying on...

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...

This paper provides new indices of global macroeconomic uncertainty and investigates the cross-country transmission of uncertainty using a global vector autoregressive (GVAR) model. The indices measure the dispersion of forecasts that results from parameter uncertainty in the GVAR. Relying on...

This paper provides new indices of global macroeconomic uncertainty and investigates the cross-country transmission of uncertainty using a global vector autoregressive (GVAR) model. The indices measure the dispersion of forecasts that results from parameter uncertainty in the GVAR. Relying on...

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...

Testing for causation—defined as the preceding impact of the past value(s) of one variable on the current value of another when all other pertinent information is accounted for—is increasingly utilized in empirical research using the time-series data in different scientific disciplines. A...

This paper examines the effect of different dimensions of uncertainty on expectations of WTI crude oil futures momentum traders at a daily level. We consider two concepts of uncertainty and two momentum trading indicators based on technical analysis. In addition, we also use wavelet techniques...