| Common business cycles and volatilities in US states and MSAs: The role of economic uncertainty R Gupta, J Ma, M Risse, ME Wohar Journal of Macroeconomics 57, 317-337, 2018 | 102 | 2018 |
| On the efficiency of the gold market: Results of a real-time forecasting approach C Pierdzioch, M Risse, S Rohloff International Review of Financial Analysis 32, 95-108, 2014 | 96 | 2014 |
| Combining wavelet decomposition with machine learning to forecast gold returns M Risse International Journal of Forecasting 35 (2), 601-615, 2019 | 80 | 2019 |
| The international business cycle and gold-price fluctuations C Pierdzioch, M Risse, S Rohloff The Quarterly Review of Economics and Finance 54 (2), 292-305, 2014 | 48 | 2014 |
| Forecasting house-price growth in the Euro area with dynamic model averaging M Risse, M Kern The North American Journal of Economics and Finance 38, 70-85, 2016 | 44 | 2016 |
| Are precious metals a hedge against exchange-rate movements? An empirical exploration using Bayesian additive regression trees C Pierdzioch, M Risse, S Rohloff The North American Journal of Economics and Finance 38, 27-38, 2016 | 42 | 2016 |
| Forecasting gold-price fluctuations: a real-time boosting approach C Pierdzioch, M Risse, S Rohloff Applied Economics Letters 22 (1), 46-50, 2015 | 41 | 2015 |
| Forecasting precious metal returns with multivariate random forests C Pierdzioch, M Risse Empirical Economics 58 (3), 1167-1184, 2020 | 39 | 2020 |
| Testing the optimality of inflation forecasts under flexible loss with random forests C Behrens, C Pierdzioch, M Risse Economic Modelling 72, 270-277, 2018 | 37 | 2018 |
| Cointegration of the prices of gold and silver: RALS-based evidence C Pierdzioch, M Risse, S Rohloff Finance Research Letters 15, 133-137, 2015 | 35 | 2015 |
| A boosting approach to forecasting the volatility of gold-price fluctuations under flexible loss C Pierdzioch, M Risse, S Rohloff Resources Policy 47, 95-107, 2016 | 34 | 2016 |
| A quantile-boosting approach to forecasting gold returns C Pierdzioch, M Risse, S Rohloff The North American Journal of Economics and Finance 35, 38-55, 2016 | 34 | 2016 |
| On international uncertainty links: BART-based empirical evidence for Canada R Gupta, C Pierdzioch, M Risse Economics Letters 143, 24-27, 2016 | 32 | 2016 |
| A test of the joint efficiency of macroeconomic forecasts using multivariate random forests C Behrens, C Pierdzioch, M Risse Journal of Forecasting 37 (5), 560-572, 2018 | 28 | 2018 |
| A boosting approach to forecasting gold and silver returns: economic and statistical forecast evaluation C Pierdzioch, M Risse, S Rohloff Applied Economics Letters 23 (5), 347-352, 2016 | 24 | 2016 |
| A real-time quantile-regression approach to forecasting gold returns under asymmetric loss C Pierdzioch, M Risse, S Rohloff Resources Policy 45, 299-306, 2015 | 23 | 2015 |
| A machine‐learning analysis of the rationality of aggregate stock market forecasts C Pierdzioch, M Risse International Journal of Finance & Economics 23 (4), 642-654, 2018 | 21 | 2018 |
| Fluctuations of the real exchange rate, real interest rates, and the dynamics of the price of gold in a small open economy C Pierdzioch, M Risse, S Rohloff Empirical Economics 51, 1481-1499, 2016 | 19 | 2016 |
| Using dynamic model averaging in state space representation with dynamic Occam’s window and applications to the stock and gold market M Risse, L Ohl Journal of Empirical Finance 44, 158-176, 2017 | 17 | 2017 |
| On REIT returns and (un-) expected inflation: Empirical evidence based on Bayesian additive regression trees C Pierdzioch, M Risse, R Gupta, W Nyakabawo Finance Research Letters 30, 160-169, 2019 | 16 | 2019 |
Mark WoharUniversity of Nebraska at OmahaBestätigte E-Mail-Adresse bei unomaha.edu
