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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:

Do Jumps Matter for Volatility Forecasting? Evidence from Energy Markets
Marcel Prokopczuk, Lazaros Symeonidis, Chardin Wese Simen
Journal of Futures Markets (2015) Vol. 36, Iss. 8, pp. 758-792
Open Access | Times Cited: 116

Showing 1-25 of 116 citing articles:

Forecasting oil price realized volatility using information channels from other asset classes
Stavros Degiannakis, George Filis
Journal of International Money and Finance (2017) Vol. 76, pp. 28-49
Open Access | Times Cited: 252
Oil Prices and Stock Markets: A Review of the Theory and Empirical Evidence
Stavros Degiannakis, George Filis, Vipin Arora
The Energy Journal (2018) Vol. 39, Iss. 5, pp. 85-130
Open Access | Times Cited: 240
Harnessing jump component for crude oil volatility forecasting in the presence of extreme shocks
Feng Ma, Yin Liao, Yaojie Zhang, et al.
Journal of Empirical Finance (2019) Vol. 52, pp. 40-55
Closed Access | Times Cited: 172
The incremental information content of investor fear gauge for volatility forecasting in the crude oil futures market
Xu Gong, Boqiang Lin
Energy Economics (2018) Vol. 74, pp. 370-386
Closed Access | Times Cited: 169
The effect of green energy, global environmental indexes, and stock markets in predicting oil price crashes: Evidence from explainable machine learning
Sami Ben Jabeur, Rabeh Khalfaoui, Wissal Ben Arfi
Journal of Environmental Management (2021) Vol. 298, pp. 113511-113511
Open Access | Times Cited: 111
Forecasting the realized volatility of the oil futures market: A regime switching approach
Feng Ma, M.I.M. Wahab, Dengshi Huang, et al.
Energy Economics (2017) Vol. 67, pp. 136-145
Closed Access | Times Cited: 151
Structural breaks and volatility forecasting in the copper futures market
Xu Gong, Boqiang Lin
Journal of Futures Markets (2017) Vol. 38, Iss. 3, pp. 290-339
Closed Access | Times Cited: 148
Which sentiment index is more informative to forecast stock market volatility? Evidence from China
Chao Liang, Linchun Tang, Yan Li, et al.
International Review of Financial Analysis (2020) Vol. 71, pp. 101552-101552
Closed Access | Times Cited: 137
Forecasting realized oil-price volatility: The role of financial stress and asymmetric loss
Κωνσταντίνος Γκίλλας, Rangan Gupta, Christian Pierdzioch
Journal of International Money and Finance (2020) Vol. 104, pp. 102137-102137
Open Access | Times Cited: 132
Forecasting volatility and co-volatility of crude oil and gold futures: Effects of leverage, jumps, spillovers, and geopolitical risks
Manabu Asai, Rangan Gupta, Michael McAleer
International Journal of Forecasting (2020) Vol. 36, Iss. 3, pp. 933-948
Open Access | Times Cited: 120
A closer look into the global determinants of oil price volatility
Ioannis Chatziantoniou, Michail Filippidis, George Filis, et al.
Energy Economics (2021) Vol. 95, pp. 105092-105092
Open Access | Times Cited: 93
Forecasting the aggregate oil price volatility in a data-rich environment
Feng Ma, Jing Liu, M.I.M. Wahab, et al.
Economic Modelling (2018) Vol. 72, pp. 320-332
Closed Access | Times Cited: 88
Financial modelling, risk management of energy instruments and the role of cryptocurrencies
Toan Luu Duc Huynh, Muhammad Shahbaz, Muhammad Ali Nasir, et al.
Annals of Operations Research (2020) Vol. 313, Iss. 1, pp. 47-75
Open Access | Times Cited: 78
Global economic policy uncertainty aligned: An informative predictor for crude oil market volatility
Yaojie Zhang, Mengxi He, Yudong Wang, et al.
International Journal of Forecasting (2022) Vol. 39, Iss. 3, pp. 1318-1332
Closed Access | Times Cited: 52
Forecasting realized volatility of oil futures market: A new insight
Feng Ma, Yu Wei, Li Liu, et al.
Journal of Forecasting (2018) Vol. 37, Iss. 4, pp. 419-436
Open Access | Times Cited: 82
Is economic policy uncertainty important to forecast the realized volatility of crude oil futures?
Feng Ma, M.I.M. Wahab, Jing Liu, et al.
Applied Economics (2017) Vol. 50, Iss. 18, pp. 2087-2101
Closed Access | Times Cited: 78
Forecasting the oil futures price volatility: Large jumps and small jumps
Jing Liu, Feng Ma, Ke Yang, et al.
Energy Economics (2018) Vol. 72, pp. 321-330
Closed Access | Times Cited: 75
Global equity market volatility spillovers: A broader role for the United States
Daniel Bunčić, Katja Gisler
International Journal of Forecasting (2016) Vol. 32, Iss. 4, pp. 1317-1339
Open Access | Times Cited: 75
Forecasting the volatility of Bitcoin: The importance of jumps and structural breaks
Dehua Shen, Andrew Urquhart, Pengfei Wang
European Financial Management (2019) Vol. 26, Iss. 5, pp. 1294-1323
Open Access | Times Cited: 71
The role of jumps and leverage in forecasting volatility in international equity markets
Daniel Bunčić, Katja Gisler
Journal of International Money and Finance (2017) Vol. 79, pp. 1-19
Closed Access | Times Cited: 69
Forecasting oil futures price volatility: New evidence from realized range-based volatility
Feng Ma, Yaojie Zhang, Dengshi Huang, et al.
Energy Economics (2018) Vol. 75, pp. 400-409
Closed Access | Times Cited: 67
On realized volatility of crude oil futures markets: Forecasting with exogenous predictors under structural breaks
Jiawen Luo, Qiang Ji, Tony Klein, et al.
Energy Economics (2020) Vol. 89, pp. 104781-104781
Open Access | Times Cited: 61
Natural gas volatility prediction: Fresh evidence from extreme weather and extended GARCH-MIDAS-ES model
Chao Liang, Zhenglan Xia, Xiaodong Lai, et al.
Energy Economics (2022) Vol. 116, pp. 106437-106437
Closed Access | Times Cited: 37
Oil futures volatility predictability: New evidence based on machine learning models
Xinjie Lu, Feng Ma, Jin Xu, et al.
International Review of Financial Analysis (2022) Vol. 83, pp. 102299-102299
Closed Access | Times Cited: 33
Multi-perspective investor attention and oil futures volatility forecasting
Hui Qu, Guo Li
Energy Economics (2023) Vol. 119, pp. 106531-106531
Closed Access | Times Cited: 22
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