8
H index
7
i10 index
187
Citations
Giuseppe Storti : Citation Profile
Università degli Studi di Salerno | RESEARCH PRODUCTION: 17 Articles 27 Papers 1 Chapters RESEARCH ACTIVITY:
MORE DETAILS IN: ABOUT THIS REPORT:
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24 years (2000 - 2024). Relations with other researchers
Works with: Authors registered in RePEc who have co-authored more than one work in the last five years with Giuseppe Storti. | Is cited by:
| Cites to:
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Main data
Where Giuseppe Storti has published?
| Journals with more than one article published | # docs |
|---|---|
| Statistical Methods & Applications | 3 |
| International Journal of Forecasting | 3 |
| JRFM | 3 |
| Computational Statistics & Data Analysis | 2 |
| Working Papers Series with more than one paper published | # docs |
|---|---|
| MPRA Paper / University Library of Munich, Germany | 5 |
| Papers / arXiv.org | 3 |
| Computing in Economics and Finance 2006 / Society for Computational Economics | 2 |
Recent works citing Giuseppe Storti (2024 and 2023)
| Year | Title of citing document |
|---|---|
| 2023 | Portfolio constructions in cryptocurrency market: A CVaR-based deep reinforcement learning approach. (2023). Zhang, Yongmin ; Jin, Huan ; Ding, Shusheng ; Cui, Tianxiang. In: Economic Modelling. RePEc:eee:ecmode:v:119:y:2023:i:c:s0264999322003157. Full description at Econpapers || Download paper |
| 2023 | Modeling realized covariance measures with heterogeneous liquidity: A generalized matrix-variate Wishart state-space model. (2023). Hartkopf, Jan Patrick ; Gribisch, Bastian. In: Journal of Econometrics. RePEc:eee:econom:v:235:y:2023:i:1:p:43-64. Full description at Econpapers || Download paper |
| 2023 | Unrestricted maximum likelihood estimation of multivariate realized volatility models. (2023). Golosnoy, Vasyl ; Vogler, Jan. In: European Journal of Operational Research. RePEc:eee:ejores:v:304:y:2023:i:3:p:1063-1074. Full description at Econpapers || Download paper |
| 2024 | Can inflation predict energy price volatility?. (2024). Batten, Jonathan ; Mo, DI ; Pourkhanali, Armin. In: Energy Economics. RePEc:eee:eneeco:v:129:y:2024:i:c:s0140988323006564. Full description at Econpapers || Download paper |
| 2023 | Assessment of advanced demand response value streams for water heaters in renewable-rich electricity markets. (2023). Rosengarten, Gary ; Hasan, Kazi N ; Stanley, Cameron ; Clift, Dean Holland. In: Energy. RePEc:eee:energy:v:267:y:2023:i:c:s0360544222034648. Full description at Econpapers || Download paper |
| 2023 | From BASEL III to BASEL IV and beyond: Expected shortfall and expectile risk measures. (2023). Nedeltchev, Dragomir C ; Zaevski, Tsvetelin S. In: International Review of Financial Analysis. RePEc:eee:finana:v:87:y:2023:i:c:s1057521923001618. Full description at Econpapers || Download paper |
| 2023 | Challenging golden standards in EWMA smoothing parameter calibration based on realized covariance measures. (2023). Reh, Laura ; Hartkopf, Jan Patrick. In: Finance Research Letters. RePEc:eee:finlet:v:56:y:2023:i:c:s1544612323005019. Full description at Econpapers || Download paper |
| 2023 | The information content of sentiment indices in forecasting Value at Risk and Expected Shortfall: a Complete Realized Exponential GARCH-X approach. (2023). Naimoli, Antonio. In: International Economics. RePEc:eee:inteco:v:176:y:2023:i:c:s2110701723000719. Full description at Econpapers || Download paper |
| 2023 | DCC- and DECO-HEAVY: Multivariate GARCH models based on realized variances and correlations. (2023). Bauwens, Luc ; Xu, Yongdeng. In: International Journal of Forecasting. RePEc:eee:intfor:v:39:y:2023:i:2:p:938-955. Full description at Econpapers || Download paper |
| 2023 | . Full description at Econpapers || Download paper |
| 2023 | Composite forecasting of vast-dimensional realized covariance matrices using factor state-space models. (2023). Hartkopf, Jan Patrick. In: Empirical Economics. RePEc:spr:empeco:v:64:y:2023:i:1:d:10.1007_s00181-022-02245-1. Full description at Econpapers || Download paper |
| 2023 | Modeling uncertainty in financial tail risk: A forecast combination and weighted quantile approach. (2023). Wang, Chao ; Storti, Giuseppe. In: Journal of Forecasting. RePEc:wly:jforec:v:42:y:2023:i:7:p:1648-1663. Full description at Econpapers || Download paper |
Works by Giuseppe Storti:
| Year | Title | Type | Cited |
|---|---|---|---|
| 2021 | Nonparametric Expected Shortfall Forecasting Incorporating Weighted Quantiles In: Papers. [Full Text][Citation analysis] | paper | 4 |
| 2022 | Nonparametric expected shortfall forecasting incorporating weighted quantiles.(2022) In: International Journal of Forecasting. [Full Text][Citation analysis] This paper has nother version. Agregated cites: 4 | article | |
| 2021 | Modelling uncertainty in financial tail risk: a forecast combination and weighted quantile approach In: Papers. [Full Text][Citation analysis] | paper | 0 |
| 2024 | A semi-parametric marginalized dynamic conditional correlation framework In: Papers. [Full Text][Citation analysis] | paper | 0 |
| 2009 | A Component GARCH Model with Time Varying Weights In: Studies in Nonlinear Dynamics & Econometrics. [Full Text][Citation analysis] | article | 35 |
| 2007 | A component GARCH model with time varying weights.(2007) In: LIDAM Discussion Papers CORE. [Full Text][Citation analysis] This paper has nother version. Agregated cites: 35 | paper | |
| 2009 | A component GARCH model with time varying weights.(2009) In: LIDAM Reprints CORE. [Citation analysis] This paper has nother version. Agregated cites: 35 | paper | |
| 2007 | A Component GARCH Model with Time Varying Weights.(2007) In: Discussion Papers (ECON - Département des Sciences Economiques). [Full Text][Citation analysis] This paper has nother version. Agregated cites: 35 | paper | |
| 2006 | A component GARCH model with time varying weights.(2006) In: Computing in Economics and Finance 2006. [Citation analysis] This paper has nother version. Agregated cites: 35 | paper | |
| 2006 | A GARCH (1,1) estimator with (almost) no moment conditions on the error term In: LIDAM Discussion Papers CORE. [Full Text][Citation analysis] | paper | 1 |
| 2012 | Computationally efficient inference procedures for vast dimensional realized covariance models In: LIDAM Discussion Papers CORE. [Full Text][Citation analysis] | paper | 3 |
| 2013 | Computationally efficient inference procedures for vast dimensional realized covariance models.(2013) In: LIDAM Reprints CORE. [Citation analysis] This paper has nother version. Agregated cites: 3 | paper | |
| 2012 | Dynamic conditional correlation models for realized covariance matrices In: LIDAM Discussion Papers CORE. [Full Text][Citation analysis] | paper | 21 |
| 2014 | Forecasting comparison of long term component dynamic models for realized covariance matrices In: LIDAM Discussion Papers CORE. [Full Text][Citation analysis] | paper | 19 |
| 2016 | Forecasting comparison of long term component dynamic models for realized covariance matrices.(2016) In: LIDAM Reprints CORE. [Citation analysis] This paper has nother version. Agregated cites: 19 | paper | |
| 2016 | A dynamic component model for forecasting high-dimensional realized covariance matrices In: LIDAM Discussion Papers CORE. [Full Text][Citation analysis] | paper | 16 |
| 2017 | A dynamic component model for forecasting high-dimensional realized covariance matrices.(2017) In: LIDAM Reprints CORE. [Citation analysis] This paper has nother version. Agregated cites: 16 | paper | |
| 2017 | A dynamic component model for forecasting high-dimensional realized covariance matrices.(2017) In: Econometrics and Statistics. [Full Text][Citation analysis] This paper has nother version. Agregated cites: 16 | article | |
| 2020 | A Dynamic Component Model for Forecasting High-Dimensional Realized Covariances Matrices.(2020) In: Working Papers. [Full Text][Citation analysis] This paper has nother version. Agregated cites: 16 | paper | |
| 2016 | Multiplicative Conditional Correlation Models for Realized Covariance Matrices In: LIDAM Discussion Papers CORE. [Full Text][Citation analysis] | paper | 6 |
| 2017 | Least squares estimation for GARCH (1,1) model with heavy tailed errors In: LIDAM Discussion Papers CORE. [Full Text][Citation analysis] | paper | 0 |
| 2014 | Least squares estimation for GARCH (1,1) model with heavy tailed errors.(2014) In: MPRA Paper. [Full Text][Citation analysis] This paper has nother version. Agregated cites: 0 | paper | |
| 2006 | Minimum distance estimation of GARCH(1,1) models In: Computational Statistics & Data Analysis. [Full Text][Citation analysis] | article | 9 |
| 2008 | A GMM procedure for combining volatility forecasts In: Computational Statistics & Data Analysis. [Full Text][Citation analysis] | article | 7 |
| 2022 | Improving the accuracy of tail risk forecasting models by combining several realized volatility estimators In: Economic Modelling. [Full Text][Citation analysis] | article | 5 |
| 2019 | Heterogeneous component multiplicative error models for forecasting trading volumes In: International Journal of Forecasting. [Full Text][Citation analysis] | article | 1 |
| 2019 | Heterogeneous component multiplicative error models for forecasting trading volumes.(2019) In: MPRA Paper. [Full Text][Citation analysis] This paper has nother version. Agregated cites: 1 | paper | |
| 2020 | A Model Confidence Set approach to the combination of multivariate volatility forecasts In: International Journal of Forecasting. [Full Text][Citation analysis] | article | 10 |
| 2020 | Improving Many Volatility Forecasts Using Cross-Sectional Volatility Clusters In: JRFM. [Full Text][Citation analysis] | article | 2 |
| 2020 | Financial Time Series: Methods and Models In: JRFM. [Full Text][Citation analysis] | article | 0 |
| 2021 | Forecasting Volatility and Tail Risk in Electricity Markets In: JRFM. [Full Text][Citation analysis] | article | 3 |
| 2009 | Combination of multivariate volatility forecasts In: SFB 649 Discussion Papers. [Full Text][Citation analysis] | paper | 13 |
| 2005 | Evaluating Business Incentives Through DEA. An Analysis on Capitalia Firm Data In: MPRA Paper. [Full Text][Citation analysis] | paper | 2 |
| 2018 | Time Varying Heteroskedastic Realized GARCH models for tracking measurement error bias in volatility forecasting In: MPRA Paper. [Full Text][Citation analysis] | paper | 0 |
| 2018 | Time Varying Heteroskedastic Realized GARCH models for tracking measurement error bias in volatility forecasting.(2018) In: MPRA Paper. [Full Text][Citation analysis] This paper has nother version. Agregated cites: 0 | paper | |
| 2000 | A NON LINEAR TIME SERIES APPROACH TO MODELLING ASYMMETRY IN STOCK MARKET INDEXES In: Computing in Economics and Finance 2000. [Full Text][Citation analysis] | paper | 2 |
| 2002 | A non-linear time series approach to modelling asymmetry in stock market indexes.(2002) In: Statistical Methods & Applications. [Full Text][Citation analysis] This paper has nother version. Agregated cites: 2 | article | |
| 2006 | The combination of volatility forecasts In: Computing in Economics and Finance 2006. [Citation analysis] | paper | 0 |
| 2003 | Likelihood inference in BL-GARCH models In: Computational Statistics. [Full Text][Citation analysis] | article | 4 |
| 2021 | A GARCH-Type Model with Cross-Sectional Volatility Clusters In: Springer Books. [Citation analysis] | chapter | 0 |
| 2002 | Measuring cross-country technological catch-up through variable-parameter FDH In: Statistical Methods & Applications. [Full Text][Citation analysis] | article | 5 |
| 2003 | BL-GARCH models and asymmetries in volatility In: Statistical Methods & Applications. [Full Text][Citation analysis] | article | 12 |
| 2020 | Corporate Governance, Investment, Profitability and Insolvency Risk: Evidence from Italy In: Advances in Management and Applied Economics. [Full Text][Citation analysis] | article | 3 |
| 2020 | Time-varying parameters realized GARCH models for tracking attenuation bias in volatility dynamics In: Quantitative Finance. [Full Text][Citation analysis] | article | 4 |
| In: . [Full Text][Citation analysis] | paper | 0 |
CitEc is a RePEc service, providing citation data for Economics since 2001. Last updated November, 3 2024. Contact: CitEc Team