| Forecasting S&P 500 volatility: Long memory, level shifts, leverage effects, day-of-the-week seasonality, and macroeconomic announcements M Martens, D Van Dijk, M De Pooter International Journal of forecasting 25 (2), 282-303, 2009 | 180 | 2009 |
| Predicting the daily covariance matrix for s&p 100 stocks using intraday data—but which frequency to use? M Pooter, M Martens, D Dijk Econometric Reviews 27 (1-3), 199-229, 2008 | 156 | 2008 |
| Examining the Nelson-Siegel class of term structure models: In-sample fit versus out-of-sample forecasting performance M De Pooter Available at SSRN 992748, 2007 | 148 | 2007 |
| Modeling and forecasting S&P 500 volatility: Long memory, structural breaks and nonlinearity M Martens, M De Pooter, DJC Van Dijk Tinbergen Institute discussion paper, 2004 | 113 | 2004 |
| The liquidity effects of official bond market intervention M De Pooter, RF Martin, S Pruitt Journal of Financial and Quantitative Analysis 53 (1), 243-268, 2018 | 93 | 2018 |
| Term structure forecasting using macro factors and forecast combination M De Pooter, F Ravazzolo, DJC Van Dijk FRB International Finance Discussion Paper, 2010 | 78 | 2010 |
| International spillovers of monetary policy J Ammer, M De Pooter, CJ Erceg, SB Kamin IFDP Notes, 2016 | 59 | 2016 |
| Are long-term inflation expectations well anchored in Brazil, Chile and Mexico? M De Pooter, PT Robitaille, I Walker, M Zdinak De Pooter, M., P. Robitaille, I. Walker, and M. Zdinak, 337-400, 2014 | 58 | 2014 |
| Are long-term inflation expectations well anchored in Brazil, Chile and Mexico? M De Pooter, PT Robitaille, I Walker, M Zdinak De Pooter, M., P. Robitaille, I. Walker, and M. Zdinak, 337-400, 2014 | 58 | 2014 |
| Testing for changes in volatility in heteroskedastic time series-a further examination M De Pooter, D Van Dijk Report/Econometric Institute, Erasmus University Rotterdam, 2004 | 56 | 2004 |
| An improved methodology to measure flag performance for the shipping industry M Perepelkin, S Knapp, G Perepelkin, M De Pooter Marine Policy 34 (3), 395-405, 2010 | 40 | 2010 |
| Predicting the term structure of interest rates: Incorporating parameter uncertainty, model uncertainty and macroeconomic information M De Pooter, F Ravazzolo, DJC Van Dijk Model Uncertainty and Macroeconomic Information (October 25, 2007), 2007 | 40 | 2007 |
| Predicting the daily covariance matrix for S&P 100 stocks using intraday data-But which frequency to use? M De Pooter, M Martens, DJC van Dijk Tinbergen Institute discussion paper, 2005 | 28 | 2005 |
| Reprint: Monetary policy uncertainty and monetary policy surprises M De Pooter, G Favara, M Modugno, J Wu Journal of International Money and Finance 114, 102401, 2021 | 27 | 2021 |
| The effects of official bond market intervention in Europe M De Pooter, R Martin, S Pruitt Federal Reserve Board of Governors mimeo, 2012 | 24 | 2012 |
| Bayesian near-boundary analysis in basic macroeconomic time-series models M De Pooter, F Ravazzolo, R Segers, HK Van Dijk Bayesian Econometrics, 2008 | 22 | 2008 |
| Cheap Talk and the Efficacy of the ECB's Securities Market Programme: Did Bond Purchases Matter? M De Pooter, DS Rebecca, RF Martin, S Pruitt | 18 | 2015 |
| Unlocking the treasury market through trace D Brain, M De Pooter, D Dobrev, MJ Fleming, P Johansson, C Jones, ... Tony and Shachar, Or, Unlocking the Treasury Market Through Trace (September …, 2018 | 11 | 2018 |
| International Spillovers of Monetary Policy.(No. 2016-02-08-1) J Ammer, M De Pooter, CJ Erceg, SB Kamin Washington: Board of Governors of the Federal Reserve System (US). models, 2016 | 11 | 2016 |
| Predicting the term structure of interest rates M De Pooter, F Ravazzolo, D van Dijk Working Paper, 2007 | 11 | 2007 |
