Open Access Helper

OpenAlex Citation Counts

OpenAlex Citations Logo

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:

Forecasting in Economics and Finance
Graham Elliott, Allan Timmermann
Annual Review of Economics (2016) Vol. 8, Iss. 1, pp. 81-110
Open Access | Times Cited: 65

Showing 1-25 of 65 citing articles:

Artificial intelligence and machine learning in finance: Identifying foundations, themes, and research clusters from bibliometric analysis
John W. Goodell, Satish Kumar, Weng Marc Lim, et al.
Journal of Behavioral and Experimental Finance (2021) Vol. 32, pp. 100577-100577
Closed Access | Times Cited: 480
Machine learning advances for time series forecasting
Ricardo Masini, Marcelo C. Medeiros, Eduardo Mendes
Journal of Economic Surveys (2021) Vol. 37, Iss. 1, pp. 76-111
Open Access | Times Cited: 244
The GDP-Temperature relationship: Implications for climate change damages
Richard G. Newell, Brian Prest, Steven Sexton
Journal of Environmental Economics and Management (2021) Vol. 108, pp. 102445-102445
Closed Access | Times Cited: 197
Forecasting stock market volatility with various geopolitical risks categories: New evidence from machine learning models
Zibo Niu, Chenlu Wang, Hongwei Zhang
International Review of Financial Analysis (2023) Vol. 89, pp. 102738-102738
Closed Access | Times Cited: 32
On the forecastability of food insecurity
Pietro Foini, Michele Tizzoni, Giulia Martini, et al.
Scientific Reports (2023) Vol. 13, Iss. 1
Open Access | Times Cited: 24
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
Seasonal Methods of Demand Forecasting in the Supply Chain as Support for the Company’s Sustainable Growth
Anna Borucka
Sustainability (2023) Vol. 15, Iss. 9, pp. 7399-7399
Open Access | Times Cited: 15
GHENet: Attention-based Hurst exponents for the forecasting of stock market indexes
João B. Florindo, R. R. P. Lima, Francisco Alves dos Santos, et al.
Physica A Statistical Mechanics and its Applications (2025), pp. 130540-130540
Closed Access
Forecasting crude oil prices with shrinkage methods: Can nonconvex penalty and Huber loss help?
Limin Xing, Yue‐Jun Zhang
Energy Economics (2022) Vol. 110, pp. 106014-106014
Closed Access | Times Cited: 20
Nowcasting Chinese GDP in a data-rich environment: Lessons from machine learning algorithms
Qin Zhang, Ni He, Xu Hao
Economic Modelling (2023) Vol. 122, pp. 106204-106204
Closed Access | Times Cited: 11
Embodied Cost of Collusive Bidding: Evidence from China’s Construction Industry
Xiaowei Wang, Kunhui Ye, David Arditi
Journal of Construction Engineering and Management (2021) Vol. 147, Iss. 6
Closed Access | Times Cited: 25
Forecasting stock returns with large dimensional factor models
Alessandro Giovannelli, Daniele Massacci, Stefano Soccorsi
Journal of Empirical Finance (2021) Vol. 63, pp. 252-269
Open Access | Times Cited: 19
Focusing on regions of interest in forecast evaluation
Hajo Holzmann, Bernhard Klar
The Annals of Applied Statistics (2017) Vol. 11, Iss. 4
Open Access | Times Cited: 23
The role of higher moments in predicting China's oil futures volatility: Evidence from machine learning models
Hongwei Zhang, Xinyi Zhao, Wang Gao, et al.
Journal of commodity markets (2023) Vol. 32, pp. 100352-100352
Closed Access | Times Cited: 6
Does crude oil futures price really help to predict spot oil price? New evidence from density forecasting
Lan Bai, Xiafei Li, Yu Wei, et al.
International Journal of Finance & Economics (2020) Vol. 27, Iss. 3, pp. 3694-3712
Closed Access | Times Cited: 17
Data snooping in equity premium prediction
Hubert Dichtl, Wolfgang Drobetz, Andreas Neuhierl, et al.
International Journal of Forecasting (2020) Vol. 37, Iss. 1, pp. 72-94
Closed Access | Times Cited: 17
Evaluating Strategic Forecasters
Rahul Deb, Mallesh M. Pai, Maher Said
American Economic Review (2018) Vol. 108, Iss. 10, pp. 3057-3103
Open Access | Times Cited: 15
Integration between technical indicators and artificial neural networks for the prediction of the exchange rate: Evidence from emerging economies
Osama Wagdi, Eman Salman, Hatem Albanna
Cogent Economics & Finance (2023) Vol. 11, Iss. 2
Open Access | Times Cited: 4
Message in a bottle: Forecasting wine prices
Bernardina Algieri, Leonardo Iania, Arturo Leccadito, et al.
Journal of Wine Economics (2024) Vol. 19, Iss. 1, pp. 64-91
Open Access | Times Cited: 1
Pooling and Winsorizing Machine Learning Forecasts to Predict Stock Returns with High-Dimensional Data
Erik Mekelburg, Jack Strauss
Journal of Empirical Finance (2024) Vol. 79, pp. 101538-101538
Open Access | Times Cited: 1
Constructing hierarchical time series through clustering: Is there an optimal way for forecasting?
Bohan Zhang, Anastasios Panagiotelis, Han Li
International Journal of Forecasting (2024)
Open Access | Times Cited: 1
Daily Stock Returns Characteristics and Forecastability
Anthony D. Joseph, Maurice Larrain, Claude Turner
Procedia Computer Science (2017) Vol. 114, pp. 481-490
Open Access | Times Cited: 10
Forecasting Stock Returns with Large Dimensional Factor Models
Alessandro Giovannelli, Daniele Massacci, Stefano Soccorsi
SSRN Electronic Journal (2017)
Open Access | Times Cited: 9
A PMI-Based Real GDP Tracker for the Euro Area
Gabe de Bondt
Journal of Business Cycle Research (2018) Vol. 15, Iss. 2, pp. 147-170
Closed Access | Times Cited: 7
Big Data Analytics: principles, trends and tasks (a survey)
O.S. Balabanov
PROBLEMS IN PROGRAMMING (2019), Iss. 2, pp. 047-068
Open Access | Times Cited: 7
Page 1 - Next Page

Scroll to top