Details about Giuseppe Storti
Access statistics for papers by Giuseppe Storti.
Last updated 2023-02-24. Update your information in the RePEc Author Service.
Short-id: pst454
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Working Papers
2024
- A semi-parametric dynamic conditional correlation framework for risk forecasting
Papers, arXiv.org
2021
- Modelling uncertainty in financial tail risk: a forecast combination and weighted quantile approach
Papers, arXiv.org
- Nonparametric Expected Shortfall Forecasting Incorporating Weighted Quantiles
Papers, arXiv.org View citations (1)
See also Journal Article Nonparametric expected shortfall forecasting incorporating weighted quantiles, International Journal of Forecasting, Elsevier (2022) View citations (5) (2022)
2020
- A Dynamic Component Model for Forecasting High-Dimensional Realized Covariances Matrices
Working Papers, Dipartimento di Scienze Economiche e Statistiche, Università degli Studi di Salerno 
Also in LIDAM Reprints CORE, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE) (2017) View citations (16) LIDAM Discussion Papers CORE, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE) (2016) View citations (5)
See also Journal Article A dynamic component model for forecasting high-dimensional realized covariance matrices, Econometrics and Statistics, Elsevier (2017) View citations (17) (2017)
2019
- Heterogeneous component multiplicative error models for forecasting trading volumes
MPRA Paper, University Library of Munich, Germany View citations (1)
See also Journal Article Heterogeneous component multiplicative error models for forecasting trading volumes, International Journal of Forecasting, Elsevier (2019) View citations (1) (2019)
2018
- Time Varying Heteroskedastic Realized GARCH models for tracking measurement error bias in volatility forecasting
MPRA Paper, University Library of Munich, Germany 
Also in MPRA Paper, University Library of Munich, Germany (2018)
2017
- Least squares estimation for GARCH (1,1) model with heavy tailed errors
LIDAM Discussion Papers CORE, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE) 
Also in MPRA Paper, University Library of Munich, Germany (2014)
2016
- Forecasting comparison of long term component dynamic models for realized covariance matrices
LIDAM Reprints CORE, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE) View citations (17)
Also in LIDAM Discussion Papers CORE, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE) (2014) View citations (14)
See also Journal Article Forecasting Comparison of Long Term Component Dynamic Models for Realized Covariance Matrices, Annals of Economics and Statistics, GENES (2016) View citations (3) (2016)
- Multiplicative Conditional Correlation Models for Realized Covariance Matrices
LIDAM Discussion Papers CORE, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE) View citations (7)
2013
- Computationally efficient inference procedures for vast dimensional realized covariance models
LIDAM Reprints CORE, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE) View citations (2)
Also in LIDAM Discussion Papers CORE, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE) (2012) View citations (4)
2012
- Dynamic conditional correlation models for realized covariance matrices
LIDAM Discussion Papers CORE, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE) View citations (26)
2009
- A component GARCH model with time varying weights
LIDAM Reprints CORE, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE) View citations (25)
Also in Discussion Papers (ECON - Département des Sciences Economiques), Université catholique de Louvain, Département des Sciences Economiques (2007) View citations (3) LIDAM Discussion Papers CORE, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE) (2007) View citations (2) Computing in Economics and Finance 2006, Society for Computational Economics (2006)
See also Journal Article A Component GARCH Model with Time Varying Weights, Studies in Nonlinear Dynamics & Econometrics, De Gruyter (2009) View citations (31) (2009)
- Combination of multivariate volatility forecasts
SFB 649 Discussion Papers, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk
2006
- A GARCH (1,1) estimator with (almost) no moment conditions on the error term
LIDAM Discussion Papers CORE, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE) View citations (1)
- The combination of volatility forecasts
Computing in Economics and Finance 2006, Society for Computational Economics
2005
- Evaluating Business Incentives Through DEA. An Analysis on Capitalia Firm Data
MPRA Paper, University Library of Munich, Germany View citations (2)
2000
- A NON LINEAR TIME SERIES APPROACH TO MODELLING ASYMMETRY IN STOCK MARKET INDEXES
Computing in Economics and Finance 2000, Society for Computational Economics View citations (3)
See also Journal Article A non-linear time series approach to modelling asymmetry in stock market indexes, Statistical Methods & Applications, Springer (2002) View citations (4) (2002)
Journal Articles
2022
- Improving the accuracy of tail risk forecasting models by combining several realized volatility estimators
Economic Modelling, 2022, 107, (C) View citations (7)
- Nonparametric expected shortfall forecasting incorporating weighted quantiles
International Journal of Forecasting, 2022, 38, (1), 224-239 View citations (5)
See also Working Paper Nonparametric Expected Shortfall Forecasting Incorporating Weighted Quantiles, Papers (2021) View citations (1) (2021)
2021
- Forecasting Volatility and Tail Risk in Electricity Markets
JRFM, 2021, 14, (7), 1-17 View citations (3)
2020
- A Model Confidence Set approach to the combination of multivariate volatility forecasts
International Journal of Forecasting, 2020, 36, (3), 873-891 View citations (10)
- Corporate Governance, Investment, Profitability and Insolvency Risk: Evidence from Italy
Advances in Management and Applied Economics, 2020, 10, (4), 10 View citations (3)
- Financial Time Series: Methods and Models
JRFM, 2020, 13, (5), 1-3
- Improving Many Volatility Forecasts Using Cross-Sectional Volatility Clusters
JRFM, 2020, 13, (4), 1-23 View citations (3)
- Time-varying parameters realized GARCH models for tracking attenuation bias in volatility dynamics
Quantitative Finance, 2020, 20, (11), 1849-1878 View citations (5)
2019
- Heterogeneous component multiplicative error models for forecasting trading volumes
International Journal of Forecasting, 2019, 35, (4), 1332-1355 View citations (1)
See also Working Paper Heterogeneous component multiplicative error models for forecasting trading volumes, MPRA Paper (2019) View citations (1) (2019)
2017
- A dynamic component model for forecasting high-dimensional realized covariance matrices
Econometrics and Statistics, 2017, 1, (C), 40-61 View citations (17)
See also Working Paper A Dynamic Component Model for Forecasting High-Dimensional Realized Covariances Matrices, Working Papers (2020) (2020)
- Least‐squares estimation of GARCH(1,1) models with heavy‐tailed errors
Econometrics Journal, 2017, 20, (2), 221-258 View citations (2)
2016
- Forecasting Comparison of Long Term Component Dynamic Models for Realized Covariance Matrices
Annals of Economics and Statistics, 2016, (123-124), 103-134 View citations (3)
See also Working Paper Forecasting comparison of long term component dynamic models for realized covariance matrices, LIDAM Reprints CORE (2016) View citations (17) (2016)
2015
- Model Uncertainty and Forecast Combination in High‐Dimensional Multivariate Volatility Prediction
Journal of Forecasting, 2015, 34, (2), 83-91 View citations (11)
2009
- A Component GARCH Model with Time Varying Weights
Studies in Nonlinear Dynamics & Econometrics, 2009, 13, (2), 33 View citations (31)
See also Working Paper A component GARCH model with time varying weights, LIDAM Reprints CORE (2009) View citations (25) (2009)
2008
- A GMM procedure for combining volatility forecasts
Computational Statistics & Data Analysis, 2008, 52, (6), 3047-3060 View citations (10)
2006
- Minimum distance estimation of GARCH(1,1) models
Computational Statistics & Data Analysis, 2006, 51, (3), 1803-1821 View citations (13)
2003
- BL-GARCH models and asymmetries in volatility
Statistical Methods & Applications, 2003, 12, (1), 19-39 View citations (13)
- Likelihood inference in BL-GARCH models
Computational Statistics, 2003, 18, (3), 387-400 View citations (5)
2002
- A non-linear time series approach to modelling asymmetry in stock market indexes
Statistical Methods & Applications, 2002, 11, (2), 201-216 View citations (4)
See also Working Paper A NON LINEAR TIME SERIES APPROACH TO MODELLING ASYMMETRY IN STOCK MARKET INDEXES, Computing in Economics and Finance 2000 (2000) View citations (3) (2000)
- Measuring cross-country technological catch-up through variable-parameter FDH
Statistical Methods & Applications, 2002, 11, (1), 109-125 View citations (6)
Chapters
2021
- A GARCH-Type Model with Cross-Sectional Volatility Clusters
Springer
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