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

Working Papers

2024

1. A semi-parametric dynamic conditional correlation framework for risk forecasting
   Papers, arXiv.org

2021

2. Modelling uncertainty in financial tail risk: a forecast combination and weighted quantile approach
   Papers, arXiv.org
3. 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

4. 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 Discussion Papers CORE, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE) (2016) View citations (5)
   LIDAM Reprints CORE, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE) (2017) View citations (16)
   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

5. 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

6. 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

7. 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

8. 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)
9. 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

10. 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

11. 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

12. 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)
13. Combination of multivariate volatility forecasts
    SFB 649 Discussion Papers, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk

2006

14. 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)
15. The combination of volatility forecasts
    Computing in Economics and Finance 2006, Society for Computational Economics

2005

16. Evaluating Business Incentives Through DEA. An Analysis on Capitalia Firm Data
    MPRA Paper, University Library of Munich, Germany View citations (2)

2000

17. 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

1. Improving the accuracy of tail risk forecasting models by combining several realized volatility estimators
   Economic Modelling, 2022, 107, (C) View citations (7)
2. 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

3. Forecasting Volatility and Tail Risk in Electricity Markets
   JRFM, 2021, 14, (7), 1-17 View citations (3)

2020

4. A Model Confidence Set approach to the combination of multivariate volatility forecasts
   International Journal of Forecasting, 2020, 36, (3), 873-891 View citations (11)
5. Corporate Governance, Investment, Profitability and Insolvency Risk: Evidence from Italy
   Advances in Management and Applied Economics, 2020, 10, (4), 10 View citations (3)
6. Financial Time Series: Methods and Models
   JRFM, 2020, 13, (5), 1-3
7. Improving Many Volatility Forecasts Using Cross-Sectional Volatility Clusters
   JRFM, 2020, 13, (4), 1-23 View citations (3)
8. Time-varying parameters realized GARCH models for tracking attenuation bias in volatility dynamics
   Quantitative Finance, 2020, 20, (11), 1849-1878 View citations (5)

2019

9. 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

10. 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)
11. Least‐squares estimation of GARCH(1,1) models with heavy‐tailed errors
    Econometrics Journal, 2017, 20, (2), 221-258 View citations (2)

2016

12. 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

13. Model Uncertainty and Forecast Combination in High‐Dimensional Multivariate Volatility Prediction
    Journal of Forecasting, 2015, 34, (2), 83-91 View citations (11)

2009

14. 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

15. A GMM procedure for combining volatility forecasts
    Computational Statistics & Data Analysis, 2008, 52, (6), 3047-3060 View citations (10)

2006

16. Minimum distance estimation of GARCH(1,1) models
    Computational Statistics & Data Analysis, 2006, 51, (3), 1803-1821 View citations (13)

2003

17. BL-GARCH models and asymmetries in volatility
    Statistical Methods & Applications, 2003, 12, (1), 19-39 View citations (13)
18. Likelihood inference in BL-GARCH models
    Computational Statistics, 2003, 18, (3), 387-400 View citations (5)

2002

19. 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)
20. Measuring cross-country technological catch-up through variable-parameter FDH
    Statistical Methods & Applications, 2002, 11, (1), 109-125 View citations (6)

Chapters

2021

1. A GARCH-Type Model with Cross-Sectional Volatility Clusters
   Springer