Manuela Braione
Personal Details
First Name: | Manuela |
Middle Name: | |
Last Name: | Braione |
Suffix: | |
RePEc Short-ID: | pbr536 |
[This author has chosen not to make the email address public] | |
https://independent.academia.edu/ManuelaBraione | |
Terminal Degree: | 2016 (from RePEc Genealogy) |
Affiliation
Soluzioni per il sistema economico SOSE S.p.A.
https://www.sose.it/roma
via mentore maggini 48C - 00143 Roma - Italy
Research output
Jump to: Working papers ArticlesWorking papers
- BAUWENS, Luc & BRAIONE, Manuela & STORTI, Giuseppe, 2016.
"A dynamic component model for forecasting high-dimensional realized covariance matrices,"
LIDAM Discussion Papers CORE
2016001, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
- Bauwens, Luc & Braione, Manuela & Storti, Giuseppe, 2017. "A dynamic component model for forecasting high-dimensional realized covariance matrices," Econometrics and Statistics, Elsevier, vol. 1(C), pages 40-61.
- Luc Bauwens & Manuela Braione & Giuseppe Storti, 2020. "A Dynamic Component Model for Forecasting High-Dimensional Realized Covariances Matrices," Working Papers 3_234, Dipartimento di Scienze Economiche e Statistiche, Università degli Studi di Salerno, revised Jul 2020.
- Luc BAUWENS, Manuela BRAIONE and Giuseppe STORTI & Luc BAUWENS, Manuela BRAIONE and Giuseppe STORTI & Luc BAUWENS, Manuela BRAIONE and Giuseppe STORTI, 2017. "A dynamic component model for forecasting high-dimensional realized covariance matrices," LIDAM Reprints CORE 2812, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
- BAUWENS, Luc & BRAIONE, Manuela & STORTI, Giuseppe, 2016. "Multiplicative Conditional Correlation Models for Realized Covariance Matrices," LIDAM Discussion Papers CORE 2016041, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
- BRAIONE, Manuela, 2016.
"A time-varying long run HEAVY model,"
LIDAM Discussion Papers CORE
2016002, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
- Braione, Manuela, 2016. "A time-varying long run HEAVY model," Statistics & Probability Letters, Elsevier, vol. 119(C), pages 36-44.
- BAUWENS, Luc & BRAIONE, Manuela & STORTI, Giuseppe, 2014.
"Forecasting comparison of long term component dynamic models for realized covariance matrices,"
LIDAM Discussion Papers CORE
2014053, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
- Luc Bauwens & Manuela Braione & Giuseppe Storti, 2016. "Forecasting Comparison of Long Term Component Dynamic Models for Realized Covariance Matrices," Annals of Economics and Statistics, GENES, issue 123-124, pages 103-134.
- Luc Bauwens & Manuela Braione & Giuseppe Storti, 2016. "Forecasting comparison of long term component dynamic models for realized covariance matrices," LIDAM Reprints CORE 2923, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
Articles
- Atella, Vincenzo & Braione, Manuela & Ferrara, Giancarlo & Resce, Giuliano, 2023. "Cohesion Policy Funds and local government autonomy: Evidence from Italian municipalities," Socio-Economic Planning Sciences, Elsevier, vol. 87(PB).
- Manuela Braione & Nicolas K. Scholtes, 2016. "Forecasting Value-at-Risk under Different Distributional Assumptions," Econometrics, MDPI, vol. 4(1), pages 1-27, January.
- Braione, Manuela, 2016.
"A time-varying long run HEAVY model,"
Statistics & Probability Letters, Elsevier, vol. 119(C), pages 36-44.
- BRAIONE, Manuela, 2016. "A time-varying long run HEAVY model," LIDAM Discussion Papers CORE 2016002, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
- Luc Bauwens & Manuela Braione & Giuseppe Storti, 2016.
"Forecasting Comparison of Long Term Component Dynamic Models for Realized Covariance Matrices,"
Annals of Economics and Statistics, GENES, issue 123-124, pages 103-134.
- Luc Bauwens & Manuela Braione & Giuseppe Storti, 2016. "Forecasting comparison of long term component dynamic models for realized covariance matrices," LIDAM Reprints CORE 2923, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
- BAUWENS, Luc & BRAIONE, Manuela & STORTI, Giuseppe, 2014. "Forecasting comparison of long term component dynamic models for realized covariance matrices," LIDAM Discussion Papers CORE 2014053, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
Citations
Many of the citations below have been collected in an experimental project, CitEc, where a more detailed citation analysis can be found. These are citations from works listed in RePEc that could be analyzed mechanically. So far, only a minority of all works could be analyzed. See under "Corrections" how you can help improve the citation analysis.Working papers
- BAUWENS, Luc & BRAIONE, Manuela & STORTI, Giuseppe, 2016.
"A dynamic component model for forecasting high-dimensional realized covariance matrices,"
LIDAM Discussion Papers CORE
2016001, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
- Bauwens, Luc & Braione, Manuela & Storti, Giuseppe, 2017. "A dynamic component model for forecasting high-dimensional realized covariance matrices," Econometrics and Statistics, Elsevier, vol. 1(C), pages 40-61.
- Luc Bauwens & Manuela Braione & Giuseppe Storti, 2020. "A Dynamic Component Model for Forecasting High-Dimensional Realized Covariances Matrices," Working Papers 3_234, Dipartimento di Scienze Economiche e Statistiche, Università degli Studi di Salerno, revised Jul 2020.
- Luc BAUWENS, Manuela BRAIONE and Giuseppe STORTI & Luc BAUWENS, Manuela BRAIONE and Giuseppe STORTI & Luc BAUWENS, Manuela BRAIONE and Giuseppe STORTI, 2017. "A dynamic component model for forecasting high-dimensional realized covariance matrices," LIDAM Reprints CORE 2812, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
Cited by:
- Golosnoy, Vasyl & Gribisch, Bastian & Seifert, Miriam Isabel, 2019. "Exponential smoothing of realized portfolio weights," Journal of Empirical Finance, Elsevier, vol. 53(C), pages 222-237.
- Naimoli, Antonio & Storti, Giuseppe, 2019.
"Heterogeneous component multiplicative error models for forecasting trading volumes,"
MPRA Paper
93802, University Library of Munich, Germany.
- Naimoli, Antonio & Storti, Giuseppe, 2019. "Heterogeneous component multiplicative error models for forecasting trading volumes," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1332-1355.
- Vassallo, Danilo & Buccheri, Giuseppe & Corsi, Fulvio, 2021. "A DCC-type approach for realized covariance modeling with score-driven dynamics," International Journal of Forecasting, Elsevier, vol. 37(2), pages 569-586.
- Qifa Xu & Junqing Zuo & Cuixia Jiang & Yaoyao He, 2021. "A large constrained time‐varying portfolio selection model with DCC‐MIDAS: Evidence from Chinese stock market," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(3), pages 3417-3435, July.
- Amendola, Alessandra & Candila, Vincenzo & Gallo, Giampiero M., 2019. "On the asymmetric impact of macro–variables on volatility," Economic Modelling, Elsevier, vol. 76(C), pages 135-152.
- Jin, Xin & Maheu, John M & Yang, Qiao, 2017.
"Bayesian Parametric and Semiparametric Factor Models for Large Realized Covariance Matrices,"
MPRA Paper
81920, University Library of Munich, Germany.
- Xin Jin & John M. Maheu & Qiao Yang, 2018. "Bayesian Parametric and Semiparametric Factor Models for Large Realized Covariance Matrices," Working Paper series 18-02, Rimini Centre for Economic Analysis.
- Xin Jin & John M. Maheu & Qiao Yang, 2019. "Bayesian parametric and semiparametric factor models for large realized covariance matrices," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 34(5), pages 641-660, August.
- Hartkopf, Jan Patrick & Reh, Laura, 2023. "Challenging golden standards in EWMA smoothing parameter calibration based on realized covariance measures," Finance Research Letters, Elsevier, vol. 56(C).
- BRAIONE, Manuela, 2016.
"A time-varying long run HEAVY model,"
LIDAM Discussion Papers CORE
2016002, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
- Braione, Manuela, 2016. "A time-varying long run HEAVY model," Statistics & Probability Letters, Elsevier, vol. 119(C), pages 36-44.
- Bollerslev, Tim & Patton, Andrew J. & Quaedvlieg, Rogier, 2020. "Multivariate leverage effects and realized semicovariance GARCH models," Journal of Econometrics, Elsevier, vol. 217(2), pages 411-430.
- Jian, Zhihong & Deng, Pingjun & Zhu, Zhican, 2018. "High-dimensional covariance forecasting based on principal component analysis of high-frequency data," Economic Modelling, Elsevier, vol. 75(C), pages 422-431.
- Golosnoy, Vasyl & Gribisch, Bastian, 2022. "Modeling and forecasting realized portfolio weights," Journal of Banking & Finance, Elsevier, vol. 138(C).
- Amendola, Alessandra & Candila, Vincenzo & Gallo, Giampiero M., 2021. "Choosing the frequency of volatility components within the Double Asymmetric GARCH–MIDAS–X model," Econometrics and Statistics, Elsevier, vol. 20(C), pages 12-28.
- Jan Patrick Hartkopf, 2023. "Composite forecasting of vast-dimensional realized covariance matrices using factor state-space models," Empirical Economics, Springer, vol. 64(1), pages 393-436, January.
- Diego Fresoli, 2022. "Bootstrap VAR forecasts: The effect of model uncertainties," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(2), pages 279-293, March.
- Conrad, Christian & Stuermer, Karin, 2017. "On the economic determinants of optimal stock-bond portfolios: international evidence," Working Papers 0636, University of Heidelberg, Department of Economics.
- BAUWENS, Luc & BRAIONE, Manuela & STORTI, Giuseppe, 2016.
"Multiplicative Conditional Correlation Models for Realized Covariance Matrices,"
LIDAM Discussion Papers CORE
2016041, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
Cited by:
- Golosnoy, Vasyl & Gribisch, Bastian & Seifert, Miriam Isabel, 2019. "Exponential smoothing of realized portfolio weights," Journal of Empirical Finance, Elsevier, vol. 53(C), pages 222-237.
- Amendola, Alessandra & Braione, Manuela & Candila, Vincenzo & Storti, Giuseppe, 2020. "A Model Confidence Set approach to the combination of multivariate volatility forecasts," International Journal of Forecasting, Elsevier, vol. 36(3), pages 873-891.
- Hartkopf, Jan Patrick & Reh, Laura, 2023. "Challenging golden standards in EWMA smoothing parameter calibration based on realized covariance measures," Finance Research Letters, Elsevier, vol. 56(C).
- Vogler, Jan & Golosnoy, Vasyl, 2023. "Unrestricted maximum likelihood estimation of multivariate realized volatility models," European Journal of Operational Research, Elsevier, vol. 304(3), pages 1063-1074.
- Jan Patrick Hartkopf, 2023. "Composite forecasting of vast-dimensional realized covariance matrices using factor state-space models," Empirical Economics, Springer, vol. 64(1), pages 393-436, January.
- Gribisch, Bastian & Hartkopf, Jan Patrick, 2023. "Modeling realized covariance measures with heterogeneous liquidity: A generalized matrix-variate Wishart state-space model," Journal of Econometrics, Elsevier, vol. 235(1), pages 43-64.
- Gribisch, Bastian & Hartkopf, Jan Patrick & Liesenfeld, Roman, 2020. "Factor state–space models for high-dimensional realized covariance matrices of asset returns," Journal of Empirical Finance, Elsevier, vol. 55(C), pages 1-20.
- BRAIONE, Manuela, 2016.
"A time-varying long run HEAVY model,"
LIDAM Discussion Papers CORE
2016002, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
- Braione, Manuela, 2016. "A time-varying long run HEAVY model," Statistics & Probability Letters, Elsevier, vol. 119(C), pages 36-44.
Cited by:
- Bauwens, Luc & Xu, Yongdeng, 2023.
"DCC- and DECO-HEAVY: Multivariate GARCH models based on realized variances and correlations,"
International Journal of Forecasting, Elsevier, vol. 39(2), pages 938-955.
- Bauwens, Luc & Xu, Yongdeng, 2019. "DCC and DECO-HEAVY: a multivariate GARCH model based on realized variances and correlations," Cardiff Economics Working Papers E2019/5, Cardiff University, Cardiff Business School, Economics Section, revised Aug 2021.
- BAUWENS Luc, & XU Yongdeng,, 2019. "DCC-HEAVY: A multivariate GARCH model based on realized variances and correlations," LIDAM Discussion Papers CORE 2019025, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
- BAUWENS, Luc & BRAIONE, Manuela & STORTI, Giuseppe, 2014.
"Forecasting comparison of long term component dynamic models for realized covariance matrices,"
LIDAM Discussion Papers CORE
2014053, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
- Luc Bauwens & Manuela Braione & Giuseppe Storti, 2016. "Forecasting Comparison of Long Term Component Dynamic Models for Realized Covariance Matrices," Annals of Economics and Statistics, GENES, issue 123-124, pages 103-134.
- Luc Bauwens & Manuela Braione & Giuseppe Storti, 2016. "Forecasting comparison of long term component dynamic models for realized covariance matrices," LIDAM Reprints CORE 2923, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
Cited by:
- Bauwens, Luc & Xu, Yongdeng, 2023.
"DCC- and DECO-HEAVY: Multivariate GARCH models based on realized variances and correlations,"
International Journal of Forecasting, Elsevier, vol. 39(2), pages 938-955.
- Bauwens, Luc & Xu, Yongdeng, 2019. "DCC and DECO-HEAVY: a multivariate GARCH model based on realized variances and correlations," Cardiff Economics Working Papers E2019/5, Cardiff University, Cardiff Business School, Economics Section, revised Aug 2021.
- Bauwens, Luc & Braione, Manuela & Storti, Giuseppe, 2017.
"A dynamic component model for forecasting high-dimensional realized covariance matrices,"
Econometrics and Statistics, Elsevier, vol. 1(C), pages 40-61.
- Luc Bauwens & Manuela Braione & Giuseppe Storti, 2020. "A Dynamic Component Model for Forecasting High-Dimensional Realized Covariances Matrices," Working Papers 3_234, Dipartimento di Scienze Economiche e Statistiche, Università degli Studi di Salerno, revised Jul 2020.
- Luc BAUWENS, Manuela BRAIONE and Giuseppe STORTI & Luc BAUWENS, Manuela BRAIONE and Giuseppe STORTI & Luc BAUWENS, Manuela BRAIONE and Giuseppe STORTI, 2017. "A dynamic component model for forecasting high-dimensional realized covariance matrices," LIDAM Reprints CORE 2812, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
- BAUWENS, Luc & BRAIONE, Manuela & STORTI, Giuseppe, 2016. "A dynamic component model for forecasting high-dimensional realized covariance matrices," LIDAM Discussion Papers CORE 2016001, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
- Naimoli, Antonio & Storti, Giuseppe, 2019.
"Heterogeneous component multiplicative error models for forecasting trading volumes,"
MPRA Paper
93802, University Library of Munich, Germany.
- Naimoli, Antonio & Storti, Giuseppe, 2019. "Heterogeneous component multiplicative error models for forecasting trading volumes," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1332-1355.
- Xin Jin & John M. Maheu, 2014.
"Bayesian Semiparametric Modeling of Realized Covariance Matrices,"
Working Paper series
34_14, Rimini Centre for Economic Analysis.
- Jin, Xin & Maheu, John M, 2014. "Bayesian Semiparametric Modeling of Realized Covariance Matrices," MPRA Paper 60102, University Library of Munich, Germany.
- Jin, Xin & Maheu, John M., 2016. "Bayesian semiparametric modeling of realized covariance matrices," Journal of Econometrics, Elsevier, vol. 192(1), pages 19-39.
- Vassallo, Danilo & Buccheri, Giuseppe & Corsi, Fulvio, 2021. "A DCC-type approach for realized covariance modeling with score-driven dynamics," International Journal of Forecasting, Elsevier, vol. 37(2), pages 569-586.
- L. Bauwens & E. Otranto, 2020.
"Modelling Realized Covariance Matrices: a Class of Hadamard Exponential Models,"
Working Paper CRENoS
202007, Centre for North South Economic Research, University of Cagliari and Sassari, Sardinia.
- Bauwens, Luc & Otranto, Edoardo, 2022. "Modeling Realized Covariance Matrices: A Class of Hadamard Exponential Models," LIDAM Reprints CORE 3202, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
- Luc Bauwens & Edoardo Otranto, 2023. "Modeling Realized Covariance Matrices: A Class of Hadamard Exponential Models," Journal of Financial Econometrics, Oxford University Press, vol. 21(4), pages 1376-1401.
- Bauwens, Luc & Otranto, Edoardo, 2020. "Modelling Realized Covariance Matrices: a Class of Hadamard Exponential Models," LIDAM Discussion Papers CORE 2020034, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
- Jin, Xin & Maheu, John M & Yang, Qiao, 2017.
"Bayesian Parametric and Semiparametric Factor Models for Large Realized Covariance Matrices,"
MPRA Paper
81920, University Library of Munich, Germany.
- Xin Jin & John M. Maheu & Qiao Yang, 2018. "Bayesian Parametric and Semiparametric Factor Models for Large Realized Covariance Matrices," Working Paper series 18-02, Rimini Centre for Economic Analysis.
- Xin Jin & John M. Maheu & Qiao Yang, 2019. "Bayesian parametric and semiparametric factor models for large realized covariance matrices," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 34(5), pages 641-660, August.
- Hartkopf, Jan Patrick & Reh, Laura, 2023. "Challenging golden standards in EWMA smoothing parameter calibration based on realized covariance measures," Finance Research Letters, Elsevier, vol. 56(C).
- BRAIONE, Manuela, 2016.
"A time-varying long run HEAVY model,"
LIDAM Discussion Papers CORE
2016002, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
- Braione, Manuela, 2016. "A time-varying long run HEAVY model," Statistics & Probability Letters, Elsevier, vol. 119(C), pages 36-44.
- Conrad, Christian & Stuermer, Karin, 2017. "On the economic determinants of optimal stock-bond portfolios: international evidence," Working Papers 0636, University of Heidelberg, Department of Economics.
- BAUWENS Luc, & XU Yongdeng,, 2019. "DCC-HEAVY: A multivariate GARCH model based on realized variances and correlations," LIDAM Discussion Papers CORE 2019025, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
- Gribisch, Bastian & Hartkopf, Jan Patrick, 2023. "Modeling realized covariance measures with heterogeneous liquidity: A generalized matrix-variate Wishart state-space model," Journal of Econometrics, Elsevier, vol. 235(1), pages 43-64.
- Marchese, Malvina & Kyriakou, Ioannis & Tamvakis, Michael & Di Iorio, Francesca, 2020. "Forecasting crude oil and refined products volatilities and correlations: New evidence from fractionally integrated multivariate GARCH models," Energy Economics, Elsevier, vol. 88(C).
- Gribisch, Bastian & Hartkopf, Jan Patrick & Liesenfeld, Roman, 2020. "Factor state–space models for high-dimensional realized covariance matrices of asset returns," Journal of Empirical Finance, Elsevier, vol. 55(C), pages 1-20.
- Harry Vander Elst & David Veredas, 2017. "Smoothing it Out: Empirical and Simulation Results for Disentangled Realized Covariances," Journal of Financial Econometrics, Oxford University Press, vol. 15(1), pages 106-138.
Articles
- Manuela Braione & Nicolas K. Scholtes, 2016.
"Forecasting Value-at-Risk under Different Distributional Assumptions,"
Econometrics, MDPI, vol. 4(1), pages 1-27, January.
Cited by:
- Sergej Gričar & Štefan Bojnec, 2021. "Technical Analysis of Tourism Price Process in the Eurozone," JRFM, MDPI, vol. 14(11), pages 1-25, October.
- Wei Kuang, 2021. "Dynamic VaR forecasts using conditional Pearson type IV distribution," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(3), pages 500-511, April.
- Jung-Bin Su, 2022. "The Research on the Interactions between the Emerging and Developed Markets: From Region and Structural Break Perspectives," Mathematics, MDPI, vol. 10(8), pages 1-38, April.
- Sobreira, Nuno & Louro, Rui, 2020. "Evaluation of volatility models for forecasting Value-at-Risk and Expected Shortfall in the Portuguese stock market," Finance Research Letters, Elsevier, vol. 32(C).
- Laura Garcia-Jorcano & Alfonso Novales, 2019.
"Volatility specifications versus probability distributions in VaR forecasting,"
Documentos de Trabajo del ICAE
2019-26, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.
- Laura Garcia‐Jorcano & Alfonso Novales, 2021. "Volatility specifications versus probability distributions in VaR forecasting," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(2), pages 189-212, March.
- Seul-Ki Park & Ji-Eun Choi & Dong Wan Shin, 2017. "Value at risk forecasting for volatility index," Applied Economics Letters, Taylor & Francis Journals, vol. 24(21), pages 1613-1620, December.
- Degiannakis, Stavros & Potamia, Artemis, 2017.
"Multiple-days-ahead value-at-risk and expected shortfall forecasting for stock indices, commodities and exchange rates: Inter-day versus intra-day data,"
International Review of Financial Analysis, Elsevier, vol. 49(C), pages 176-190.
- Degiannakis, Stavros & Potamia, Artemis, 2016. "Multiple-days-ahead value-at-risk and expected shortfall forecasting for stock indices, commodities and exchange rates: inter-day versus intra-day data," MPRA Paper 74670, University Library of Munich, Germany.
- Emrah ALTUN & Morad ALIZADEH & Gamze OZEL & Hüseyin TATLIDIL & Najmieh MAKSAYI, 2017. "Forecasting Value-At-Risk With Two-Step Method: Garch-Exponentiated Odd Log-Logistic Normal Model," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(4), pages 97-115, December.
- Marc Hallin & Carlos Trucíos, 2020. "Forecasting Value-at-Risk and Expected Shortfall in Large Portfolios: a General Dynamic Factor Approach," Working Papers ECARES 2020-50, ULB -- Universite Libre de Bruxelles.
- Thilini Mahanama & Abootaleb Shirvani & Svetlozar Rachev, 2021. "Global Index on Financial Losses due to Crime in the United States," Papers 2105.03514, arXiv.org.
- Malik Zaka Ullah & Fouad Othman Mallawi & Mir Asma & Stanford Shateyi, 2022. "On the Conditional Value at Risk Based on the Laplace Distribution with Application in GARCH Model," Mathematics, MDPI, vol. 10(16), pages 1-13, August.
- Owusu Junior, Peterson & Tiwari, Aviral Kumar & Tweneboah, George & Asafo-Adjei, Emmanuel, 2022. "GAS and GARCH based value-at-risk modeling of precious metals," Resources Policy, Elsevier, vol. 75(C).
- Hallin, Marc & Trucíos, Carlos, 2023. "Forecasting value-at-risk and expected shortfall in large portfolios: A general dynamic factor model approach," Econometrics and Statistics, Elsevier, vol. 27(C), pages 1-15.
- Li, Jiang-Cheng & Tao, Chen & Li, Hai-Feng, 2022. "Dynamic forecasting performance and liquidity evaluation of financial market by Econophysics and Bayesian methods," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 588(C).
- George-Jason Siouris & Alex Karagrigoriou, 2017. "A Low Price Correction for Improved Volatility Estimation and Forecasting," Risks, MDPI, vol. 5(3), pages 1-14, August.
- José Antonio Núñez-Mora & Roberto Joaquín Santillán-Salgado & Mario Iván Contreras-Valdez, 2022. "COVID Asymmetric Impact on the Risk Premium of Developed and Emerging Countries’ Stock Markets," Mathematics, MDPI, vol. 10(9), pages 1-36, April.
- Laura Garcia-Jorcano & Alfonso Novales, 2020.
"A dominance approach for comparing the performance of VaR forecasting models,"
Computational Statistics, Springer, vol. 35(3), pages 1411-1448, September.
- Laura Garcia-Jorcano & Alfonso Novales, 2019. "A dominance approach for comparing the performance of VaR forecasting models," Documentos de Trabajo del ICAE 2019-23, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.
- Hussein Khraibani & Bilal Nehme & Olivier Strauss, 2018. "Interval Estimation of Value-at-Risk Based on Nonparametric Models," Econometrics, MDPI, vol. 6(4), pages 1-30, December.
- Amiri , Hossein & Najafi Nejad , Mahmood & Mousavi , Seyede Mohadese, 2021. "Estimation of Value at Risk (VaR) Based On Lévy-GARCH Models: Evidence from Tehran Stock Exchange," Journal of Money and Economy, Monetary and Banking Research Institute, Central Bank of the Islamic Republic of Iran, vol. 16(2), pages 165-186, June.
- Thilini Mahanama & Abootaleb Shirvani & Svetlozar T. Rachev, 2021. "Global Index on Financial Losses Due to Crime in the United States," JRFM, MDPI, vol. 14(7), pages 1-16, July.
- Rehman, Mobeen Ur & Owusu Junior, Peterson & Ahmad, Nasir & Vo, Xuan Vinh, 2022. "Time-varying risk analysis for commodity futures," Resources Policy, Elsevier, vol. 78(C).
- Braione, Manuela, 2016.
"A time-varying long run HEAVY model,"
Statistics & Probability Letters, Elsevier, vol. 119(C), pages 36-44.
See citations under working paper version above.
- BRAIONE, Manuela, 2016. "A time-varying long run HEAVY model," LIDAM Discussion Papers CORE 2016002, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
- Luc Bauwens & Manuela Braione & Giuseppe Storti, 2016.
"Forecasting Comparison of Long Term Component Dynamic Models for Realized Covariance Matrices,"
Annals of Economics and Statistics, GENES, issue 123-124, pages 103-134.
See citations under working paper version above.
- Luc Bauwens & Manuela Braione & Giuseppe Storti, 2016. "Forecasting comparison of long term component dynamic models for realized covariance matrices," LIDAM Reprints CORE 2923, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
- BAUWENS, Luc & BRAIONE, Manuela & STORTI, Giuseppe, 2014. "Forecasting comparison of long term component dynamic models for realized covariance matrices," LIDAM Discussion Papers CORE 2014053, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
More information
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Featured entries
This author is featured on the following reading lists, publication compilations, Wikipedia, or ReplicationWiki entries:NEP Fields
NEP is an announcement service for new working papers, with a weekly report in each of many fields. This author has had 4 papers announced in NEP. These are the fields, ordered by number of announcements, along with their dates. If the author is listed in the directory of specialists for this field, a link is also provided.- NEP-ECM: Econometrics (4) 2015-04-11 2016-03-10 2016-03-17 2017-02-12
- NEP-ETS: Econometric Time Series (3) 2016-03-10 2016-03-17 2017-02-12
- NEP-FOR: Forecasting (3) 2015-04-11 2016-03-10 2016-03-17
- NEP-ORE: Operations Research (1) 2015-04-11
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