| Dynamic conditional correlation models for realized covariance matrices L Bauwens, G Storti, F Violante CORE DP 60, 104-108, 2012 | 60 | 2012 |
| A component GARCH model with time varying weights L Bauwens, G Storti Studies in Nonlinear Dynamics & Econometrics 13 (2), 2009 | 57 | 2009 |
| BL-GARCH models and asymmetries in volatility G Storti, C Vitale Statistical Methods and Applications 12, 19-39, 2003 | 49 | 2003 |
| A GMM procedure for combining volatility forecasts A Amendola, G Storti Computational Statistics & Data Analysis 52 (6), 3047-3060, 2008 | 33 | 2008 |
| Deep learning for volatility forecasting in asset management A Petrozziello, L Troiano, A Serra, I Jordanov, G Storti, R Tagliaferri, ... Soft Computing 26 (17), 8553-8574, 2022 | 29 | 2022 |
| A model confidence set approach to the combination of multivariate volatility forecasts A Amendola, M Braione, V Candila, G Storti International Journal of Forecasting 36 (3), 873-891, 2020 | 29 | 2020 |
| Model uncertainty and forecast combination in high‐dimensional multivariate volatility prediction A Amendola, G Storti Journal of Forecasting 34 (2), 83-91, 2015 | 29 | 2015 |
| Forecasting comparison of long term component dynamic models for realized covariance matrices L Bauwens, M Braione, G Storti Annals of Economics and Statistics/Annales d'Économie et de Statistique, 103-134, 2016 | 27 | 2016 |
| A dynamic component model for forecasting high-dimensional realized covariance matrices L Bauwens, M Braione, G Storti Econometrics and Statistics 1, 40-61, 2017 | 26 | 2017 |
| Minimum distance estimation of GARCH (1, 1) models G Storti Computational statistics & data analysis 51 (3), 1803-1821, 2006 | 18 | 2006 |
| Measuring cross-country technological catch-up through variable-parameter FDH S Destefanis, G Storti Statistical Methods and Applications 11, 109-125, 2002 | 18 | 2002 |
| Corporate governance, investment, profitability and insolvency risk: Evidence from Italy A Amendola, V Candila, L Sensini, G Storti Advances in Management and Applied Economics 4 (10), 185-202, 2020 | 17 | 2020 |
| Improving the accuracy of tail risk forecasting models by combining several realized volatility estimators A Naimoli, R Gerlach, G Storti Economic Modelling 107, 105701, 2022 | 15 | 2022 |
| Nonparametric expected shortfall forecasting incorporating weighted quantiles G Storti, C Wang International Journal of Forecasting 38 (1), 224-239, 2022 | 14 | 2022 |
| Likelihood inference in BL-GARCH models G Storti, C Vitale Computational Statistics 18 (3), 387-400, 2003 | 14 | 2003 |
| Multiplicative conditional correlation models for realized covariance matrices L Bauwens, M Braione, G Storti CORE DISCUSSION PAPER SERIES, 2020 | 13 | 2020 |
| Least‐squares estimation of GARCH (1, 1) models with heavy‐tailed errors A Preminger, G Storti The Econometrics Journal 20 (2), 221-258, 2017 | 13 | 2017 |
| Governance, innovation, profitability, and credit risk: Evidence from Italian manufacturing firms A Amendola, V Candila, L Sensini, G Storti International Journal of Business and Social Science 6 (11), 32-42, 2020 | 11 | 2020 |
| Time-varying parameters realized GARCH models for tracking attenuation bias in volatility dynamics R Gerlach, A Naimoli, G Storti Quantitative Finance 20 (11), 1849-1878, 2020 | 10 | 2020 |
| A non-linear time series approach to modelling asymmetry in stock market indexes A Amendola, G Storti Statistical Methods and Applications 11, 201-216, 2002 | 10 | 2002 |
Luc BauwensProfessor of Economics, Université catholique de LouvainVerified email at uclouvain.be