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OpenAlex Citation Counts

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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

Comparison of Value-at-Risk models using the MCS approach
Mauro Bernardi, Leopoldo Catania
Computational Statistics (2016) Vol. 31, Iss. 2, pp. 579-608
Closed Access | Times Cited: 48

Showing 1-25 of 48 citing articles:

Forecasting risk with Markov-switching GARCH models:A large-scale performance study
David Ardia, Keven Bluteau, Kris Boudt, et al.
International Journal of Forecasting (2018) Vol. 34, Iss. 4, pp. 733-747
Open Access | Times Cited: 136
Predicting Time-Varying Parameters with Parameter-Driven and Observation-Driven Models
Siem Jan Koopman, André Lucas, Marcel Scharth
The Review of Economics and Statistics (2015) Vol. 98, Iss. 1, pp. 97-110
Open Access | Times Cited: 128
Re-examining Bitcoin Volatility: A CAViaR-based Approach
Zhenghui Li, Hao Dong, Christos Floros, et al.
Emerging Markets Finance and Trade (2021) Vol. 58, Iss. 5, pp. 1320-1338
Open Access | Times Cited: 76
The driving forces of green bond market volatility and the response of the market to the COVID-19 pandemic
Min Liu
Economic Analysis and Policy (2022) Vol. 75, pp. 288-309
Closed Access | Times Cited: 64
A new losses (revenues) probability model with entropy analysis, applications and case studies for value-at-risk modeling and mean of order-P analysis
Ibrahim Elbatal, L. S. Diab, Anis Ben Ghorbal, et al.
AIMS Mathematics (2024) Vol. 9, Iss. 3, pp. 7169-7211
Open Access | Times Cited: 11
Selection of Value at Risk Models for Energy Commodities
Alessandro G. Laporta, Luca Merlo, Lea Petrella
Energy Economics (2018) Vol. 74, pp. 628-643
Closed Access | Times Cited: 72
The model confidence set package for R
Mauro Bernardi, Leopoldo Catania
International Journal of Computational Economics and Econometrics (2018) Vol. 8, Iss. 2, pp. 144-144
Open Access | Times Cited: 70
Forecasting cryptocurrency volatility
Leopoldo Catania, Stefano Grassi
International Journal of Forecasting (2021) Vol. 38, Iss. 3, pp. 878-894
Closed Access | Times Cited: 44
Modelling Crypto-Currencies Financial Time-Series
Leopoldo Catania, Stefano Grassi
SSRN Electronic Journal (2017)
Closed Access | Times Cited: 53
Combining Value-at-Risk forecasts using penalized quantile regressions
Sebastian Bayer
Econometrics and Statistics (2017) Vol. 8, pp. 56-77
Closed Access | Times Cited: 41
The heterogeneous linkage of economic policy uncertainty and oil return risks
Hao Dong, Yue Liu, Jiaqi Chang
Green Finance (2019) Vol. 1, Iss. 1, pp. 46-66
Open Access | Times Cited: 36
GAS and GARCH based value-at-risk modeling of precious metals
Peterson Owusu, Aviral Kumar Tiwari, George Tweneboah, et al.
Resources Policy (2021) Vol. 75, pp. 102456-102456
Closed Access | Times Cited: 29
Assessing systemic risk and connectedness among dirty and clean energy markets from the quantile and expectile perspectives
Khreshna Syuhada, Arief Rachman Hakim, Djoko Suprijanto
Energy Economics (2023) Vol. 129, pp. 107261-107261
Closed Access | Times Cited: 9
Forecasting realized volatility: Does anything beat linear models?
Rafael R. Branco, Alexandre Rubesam, Mauricio Zevallos
Journal of Empirical Finance (2024) Vol. 78, pp. 101524-101524
Closed Access | Times Cited: 3
Trading and non-trading period realized market volatility: Does it matter for forecasting the volatility of US stocks?
Štefan Lyócsa, Neda Todorova
International Journal of Forecasting (2019) Vol. 36, Iss. 2, pp. 628-645
Closed Access | Times Cited: 28
Price Risk Analysis using GARCH Family Models: Evidence from Shanghai Crude Oil Futures Market
Shuhua Bei, Aijun Yang, H. Pei, et al.
Economic Modelling (2023) Vol. 125, pp. 106367-106367
Closed Access | Times Cited: 7
Monitoring Value-at-Risk and Expected Shortfall Forecasts
Yannick Hoga, Matei Demetrescu
Management Science (2022) Vol. 69, Iss. 5, pp. 2954-2971
Closed Access | Times Cited: 11
Downside Risk Evaluation with the R Package GAS
David Ardia, Kris Boudt, Leopoldo Catania
The R Journal (2019) Vol. 10, Iss. 2, pp. 410-410
Open Access | Times Cited: 18
Risk spillover effects of international crude oil market on China’s major markets
Siming Liu, Honglei Gao, Peng Hou, et al.
AIMS energy (2019) Vol. 7, Iss. 6, pp. 819-840
Open Access | Times Cited: 17
Formulating MCoVaR to Quantify Joint Transmissions of Systemic Risk across Crypto and Non-Crypto Markets: A Multivariate Copula Approach
Arief Rachman Hakim, Khreshna Syuhada
Risks (2023) Vol. 11, Iss. 2, pp. 35-35
Open Access | Times Cited: 5
Modeling returns volatility: Realized GARCH incorporating realized risk measure
Wei Jiang, Qingsong Ruan, Jianfeng Li, et al.
Physica A Statistical Mechanics and its Applications (2018) Vol. 500, pp. 249-258
Closed Access | Times Cited: 16
Value at Risk Performance in Cryptocurrencies
Danai Likitratcharoen, Teerasak Na Ranong, Ratikorn Chuensuksomboon, et al.
The Journal of Risk Management (2018) Vol. 22, Iss. 1, pp. 11-28
Closed Access | Times Cited: 15
Semi-nonparametric risk assessment with cryptocurrencies
Inés Jiménez, Andrés Mora‐Valencia, Javier Perote
Research in International Business and Finance (2021) Vol. 59, pp. 101567-101567
Open Access | Times Cited: 12
Score-driven cryptocurrency and equity portfolios
Szabolcs Blazsek, Richard Bowen
Applied Economics (2023) Vol. 56, Iss. 18, pp. 2109-2128
Closed Access | Times Cited: 4
A New Star Is Born: Does the VIX1D Render Common Volatility Forecasting Models for the U.S. Equity Market Obsolete?
Stefan Albers
SSRN Electronic Journal (2023)
Closed Access | Times Cited: 4
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