Giuseppe Storti : Citation Profile

Are you Giuseppe Storti?

Università degli Studi di Salerno

8

H index

6

i10 index

170

Citations

RESEARCH PRODUCTION:

19

Articles

26

Papers

1

Chapters

RESEARCH ACTIVITY:

   22 years (2000 - 2022). See details.
   Cites by year: 7
   Journals where Giuseppe Storti has often published
   Relations with other researchers
   Recent citing documents: 26.    Total self citations: 17 (9.09 %)

MORE DETAILS IN:
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   Permalink: http://citec.repec.org/pst454
   Updated: 2023-03-25    RAS profile: 2022-11-04    
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Relations with other researchers

Works with:

Bauwens, Luc (3)

Amendola, Alessandra (2)

Authors registered in RePEc who have co-authored more than one work in the last five years with Giuseppe Storti.

Is cited by:

Bauwens, Luc (9)

Maheu, John (7)

bouoiyour, jamal (7)

Haas, Markus (7)

Hafner, Christian (6)

DIONGUE, Abdou Ka (6)

Clements, Adam (6)

Laurent, Sébastien (5)

Selmi, Refk (5)

Amendola, Alessandra (5)

Gallo, Giampiero (5)

Cites to:

Engle, Robert (53)

Bollerslev, Tim (46)

Bauwens, Luc (29)

Shephard, Neil (28)

Andersen, Torben (25)

Patton, Andrew (21)

Hansen, Peter (20)

Gallo, Giampiero (18)

Lunde, Asger (16)

Laurent, Sébastien (16)

Diebold, Francis (15)

Main data

Where Giuseppe Storti has published?

Journals with more than one article published# docs
International Journal of Forecasting3
Statistical Methods & Applications3
JRFM3
Computational Statistics & Data Analysis2

Working Papers Series with more than one paper published# docs
MPRA Paper / University Library of Munich, Germany5
Papers / arXiv.org3
Computing in Economics and Finance 2006 / Society for Computational Economics2

Recent works citing Giuseppe Storti (2022 and 2021)

YearTitle of citing document
2022The Cross-Sectional Intrinsic Entropy. A Comprehensive Stock Market Volatility Estimator. (2022). Ausloos, Marcel ; Vinte, Claudiu. In: Papers. RePEc:arx:papers:2205.00104.

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2021Determinants of Leverage in Emerging Markets: Empirical Evidence. (2021). Vazquez, Maria ; Sensini, Luca ; Chen, Yarong. In: International Journal of Economics and Financial Issues. RePEc:eco:journ1:2021-02-6.

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2021Predicting risk in energy markets: Low-frequency data still matter. (2021). Výrost, Tomᚠ; Vrost, Toma ; Todorova, Neda ; Lyocsa, Tefan. In: Applied Energy. RePEc:eee:appene:v:282:y:2021:i:pa:s0306261920315567.

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2022The impact of COVID-19 on commodity options market: Evidence from China. (2022). Xu, Hao ; Chen, Jilong. In: Economic Modelling. RePEc:eee:ecmode:v:116:y:2022:i:c:s0264999322002395.

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2021Choosing the frequency of volatility components within the Double Asymmetric GARCH–MIDAS–X model. (2021). Gallo, Giampiero ; Amendola, Alessandra ; Candila, Vincenzo. In: Econometrics and Statistics. RePEc:eee:ecosta:v:20:y:2021:i:c:p:12-28.

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2021A DCC-type approach for realized covariance modeling with score-driven dynamics. (2021). Corsi, Fulvio ; Buccheri, Giuseppe ; Vassallo, Danilo. In: International Journal of Forecasting. RePEc:eee:intfor:v:37:y:2021:i:2:p:569-586.

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2022Random coefficient state-space model: Estimation and performance in M3–M4 competitions. (2022). Silvestrini, Andrea ; Sbrana, Giacomo. In: International Journal of Forecasting. RePEc:eee:intfor:v:38:y:2022:i:1:p:352-366.

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2022Optimal and robust combination of forecasts via constrained optimization and shrinkage. (2022). Vrins, Frederic ; Gambetti, Paolo ; Roccazzella, Francesco. In: International Journal of Forecasting. RePEc:eee:intfor:v:38:y:2022:i:1:p:97-116.

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2022Modeling and forecasting realized portfolio weights. (2022). Gribisch, Bastian ; Golosnoy, Vasyl. In: Journal of Banking & Finance. RePEc:eee:jbfina:v:138:y:2022:i:c:s0378426622000048.

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2021Multivariate Analysis of Cryptocurrencies. (2021). Candila, Vincenzo. In: Econometrics. RePEc:gam:jecnmx:v:9:y:2021:i:3:p:28-:d:586873.

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2021Does the Choice of Realized Covariance Measures Empirically Matter? A Bayesian Density Prediction Approach. (2021). Yang, Qiao ; Liu, Jia ; Jin, Xin. In: Econometrics. RePEc:gam:jecnmx:v:9:y:2021:i:4:p:45-:d:695927.

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2021Identifying the Role of Gold on Sustainable Investment in Indonesia: The DCC-GARCH Approach. (2021). Huruta, Andrian Dolfriandra ; Nugroho, Bayu Adi ; Robiyanto, Robiyanto ; Suyanto, Suyanto ; Frensidy, Budi. In: Economies. RePEc:gam:jecomi:v:9:y:2021:i:3:p:119-:d:620561.

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2021Improving Hotel Room Demand Forecasts for Vienna across Hotel Classes and Forecast Horizons: Single Models and Combination Techniques Based on Encompassing Tests. (2021). Gunter, Ulrich. In: Forecasting. RePEc:gam:jforec:v:3:y:2021:i:4:p:54-919:d:689837.

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2021Technical Analysis of Tourism Price Process in the Eurozone. (2021). Bojnec, Tefan ; Griar, Sergej. In: JRFM. RePEc:gam:jjrfmx:v:14:y:2021:i:11:p:517-:d:666054.

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2021A Survey on Volatility Fluctuations in the Decentralized Cryptocurrency Financial Assets. (2021). Kyriazis, Nikolaos A. In: JRFM. RePEc:gam:jjrfmx:v:14:y:2021:i:7:p:293-:d:582208.

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2021Multivariate Analysis of Energy Commodities during the COVID-19 Pandemic: Evidence from a Mixed-Frequency Approach. (2021). Morelli, Giacomo ; Candila, Vincenzo ; Andreani, Mila ; Petrella, Lea. In: Risks. RePEc:gam:jrisks:v:9:y:2021:i:8:p:144-:d:612252.

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2021The closest strong efficient targets in the FDH technology: an enumeration method. (2021). Dizaji, Sadighi R ; Vakili, J. In: Journal of Productivity Analysis. RePEc:kap:jproda:v:55:y:2021:i:2:d:10.1007_s11123-020-00594-6.

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2022R-estimators in GARCH models: asymptotics and applications. (2022). Mukherjee, Kanchan ; Liu, Hang. In: Econometrics Journal. RePEc:oup:emjrnl:v:25:y:2022:i:1:p:98-113..

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2022Forecasting volatility during the outbreak of Russian invasion of Ukraine: application to commodities, stock indices, currencies, and cryptocurrencies. (2022). Maecka, Marta ; Fiszeder, Piotr. In: Equilibrium. Quarterly Journal of Economics and Economic Policy. RePEc:pes:ierequ:v:17:y:2022:i:4:p:939-967.

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2022The information content of sentiment indices for forecasting Value at Risk and Expected Shortfall in equity markets. (2022). Naimoli, Antonio. In: MPRA Paper. RePEc:pra:mprapa:112588.

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2022Estimation and computations for Gaussian mixtures with uniform noise under separation constraints. (2022). Coretto, Pietro. In: Statistical Methods & Applications. RePEc:spr:stmapp:v:31:y:2022:i:2:d:10.1007_s10260-021-00578-2.

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2021A simple linear alternative to multiplicative error models with an application to trading volume. (2021). Clements, Adam ; Volkov, Vladimir ; Hurn, Stan. In: Working Papers. RePEc:tas:wpaper:38716.

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2021A New Parametrization of Correlation Matrices. (2021). Hansen, Peter ; Archakov, Ilya. In: Econometrica. RePEc:wly:emetrp:v:89:y:2021:i:4:p:1699-1715.

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2021A large constrained time?varying portfolio selection model with DCC?MIDAS: Evidence from Chinese stock market. (2021). He, Yaoyao ; Jiang, Cuixia ; Zuo, Junqing ; Xu, Qifa. In: International Journal of Finance & Economics. RePEc:wly:ijfiec:v:26:y:2021:i:3:p:3417-3435.

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2021Conditional covariance matrix forecast using the hybrid exponentially weighted moving average approach. (2021). Kuang, Wei. In: Journal of Forecasting. RePEc:wly:jforec:v:40:y:2021:i:8:p:1398-1419.

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2022Bootstrap VAR forecasts: The effect of model uncertainties. (2022). Fresoli, Diego . In: Journal of Forecasting. RePEc:wly:jforec:v:41:y:2022:i:2:p:279-293.

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Works by Giuseppe Storti:

YearTitleTypeCited
2021Nonparametric Expected Shortfall Forecasting Incorporating Weighted Quantiles In: Papers.
[Full Text][Citation analysis]		paper0
2022Nonparametric expected shortfall forecasting incorporating weighted quantiles.(2022) In: International Journal of Forecasting.
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This paper has another version. Agregated cites: 0		article
2021Modelling uncertainty in financial tail risk: a forecast combination and weighted quantile approach In: Papers.
[Full Text][Citation analysis]		paper0
2022A multivariate semi-parametric portfolio risk optimization and forecasting framework In: Papers.
[Full Text][Citation analysis]		paper0
2009A Component GARCH Model with Time Varying Weights In: Studies in Nonlinear Dynamics & Econometrics.
[Full Text][Citation analysis]		article35
2007A component GARCH model with time varying weights.(2007) In: LIDAM Discussion Papers CORE.
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2009A component GARCH model with time varying weights.(2009) In: LIDAM Reprints CORE.
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2007A Component GARCH Model with Time Varying Weights.(2007) In: Discussion Papers (ECON - Département des Sciences Economiques).
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2006A component GARCH model with time varying weights.(2006) In: Computing in Economics and Finance 2006.
[Citation analysis]
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2006A GARCH (1,1) estimator with (almost) no moment conditions on the error term In: LIDAM Discussion Papers CORE.
[Full Text][Citation analysis]		paper1
2012Computationally efficient inference procedures for vast dimensional realized covariance models In: LIDAM Discussion Papers CORE.
[Full Text][Citation analysis]		paper3
2013Computationally efficient inference procedures for vast dimensional realized covariance models.(2013) In: LIDAM Reprints CORE.
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2012Dynamic conditional correlation models for realized covariance matrices In: LIDAM Discussion Papers CORE.
[Full Text][Citation analysis]		paper20
2014Forecasting comparison of long term component dynamic models for realized covariance matrices In: LIDAM Discussion Papers CORE.
[Full Text][Citation analysis]		paper16
2016Forecasting comparison of long term component dynamic models for realized covariance matrices.(2016) In: LIDAM Reprints CORE.
[Citation analysis]
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2016A dynamic component model for forecasting high-dimensional realized covariance matrices In: LIDAM Discussion Papers CORE.
[Full Text][Citation analysis]		paper14
2017A dynamic component model for forecasting high-dimensional realized covariance matrices.(2017) In: LIDAM Reprints CORE.
[Citation analysis]
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2017A dynamic component model for forecasting high-dimensional realized covariance matrices.(2017) In: Econometrics and Statistics.
[Full Text][Citation analysis]
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2020A Dynamic Component Model for Forecasting High-Dimensional Realized Covariances Matrices.(2020) In: Working Papers.
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2016Multiplicative Conditional Correlation Models for Realized Covariance Matrices In: LIDAM Discussion Papers CORE.
[Full Text][Citation analysis]		paper2
2017Least squares estimation for GARCH (1,1) model with heavy tailed errors In: LIDAM Discussion Papers CORE.
[Full Text][Citation analysis]		paper0
2014Least squares estimation for GARCH (1,1) model with heavy tailed errors.(2014) In: MPRA Paper.
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2006Minimum distance estimation of GARCH(1,1) models In: Computational Statistics & Data Analysis.
[Full Text][Citation analysis]		article9
2008A GMM procedure for combining volatility forecasts In: Computational Statistics & Data Analysis.
[Full Text][Citation analysis]		article5
2022Improving the accuracy of tail risk forecasting models by combining several realized volatility estimators In: Economic Modelling.
[Full Text][Citation analysis]		article2
2019Heterogeneous component multiplicative error models for forecasting trading volumes In: International Journal of Forecasting.
[Full Text][Citation analysis]		article1
2019Heterogeneous component multiplicative error models for forecasting trading volumes.(2019) In: MPRA Paper.
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This paper has another version. Agregated cites: 1		paper
2020A Model Confidence Set approach to the combination of multivariate volatility forecasts In: International Journal of Forecasting.
[Full Text][Citation analysis]		article8
2020Improving Many Volatility Forecasts Using Cross-Sectional Volatility Clusters In: JRFM.
[Full Text][Citation analysis]		article2
2020Financial Time Series: Methods and Models In: JRFM.
[Full Text][Citation analysis]		article0
2021Forecasting Volatility and Tail Risk in Electricity Markets In: JRFM.
[Full Text][Citation analysis]		article1
2009Combination of multivariate volatility forecasts In: SFB 649 Discussion Papers.
[Full Text][Citation analysis]		paper11
2005Evaluating Business Incentives Through DEA. An Analysis on Capitalia Firm Data In: MPRA Paper.
[Full Text][Citation analysis]		paper2
2018Time Varying Heteroskedastic Realized GARCH models for tracking measurement error bias in volatility forecasting In: MPRA Paper.
[Full Text][Citation analysis]		paper0
2018Time Varying Heteroskedastic Realized GARCH models for tracking measurement error bias in volatility forecasting.(2018) In: MPRA Paper.
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2000A NON LINEAR TIME SERIES APPROACH TO MODELLING ASYMMETRY IN STOCK MARKET INDEXES In: Computing in Economics and Finance 2000.
[Full Text][Citation analysis]		paper2
2002A non-linear time series approach to modelling asymmetry in stock market indexes.(2002) In: Statistical Methods & Applications.
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2006The combination of volatility forecasts In: Computing in Economics and Finance 2006.
[Citation analysis]		paper0
2003Likelihood inference in BL-GARCH models In: Computational Statistics.
[Full Text][Citation analysis]		article4
2021A GARCH-Type Model with Cross-Sectional Volatility Clusters In: Springer Books.
[Citation analysis]		chapter0
2002Measuring cross-country technological catch-up through variable-parameter FDH In: Statistical Methods & Applications.
[Full Text][Citation analysis]		article5
2003BL-GARCH models and asymmetries in volatility In: Statistical Methods & Applications.
[Full Text][Citation analysis]		article12
2020Corporate Governance, Investment, Profitability and Insolvency Risk: Evidence from Italy In: Advances in Management and Applied Economics.
[Full Text][Citation analysis]		article2
2020Time-varying parameters realized GARCH models for tracking attenuation bias in volatility dynamics In: Quantitative Finance.
[Full Text][Citation analysis]		article2
2017Least?squares estimation of GARCH(1,1) models with heavy?tailed errors In: Econometrics Journal.
[Full Text][Citation analysis]		article2
2015Model Uncertainty and Forecast Combination in High?Dimensional Multivariate Volatility Prediction In: Journal of Forecasting.
[Full Text][Citation analysis]		article9

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