OOIR: Observatory of International Research

Papers

(The TQCC of International Journal of Forecasting is 12. The table below lists those papers that are above that threshold based on CrossRef citation counts [max. 250 papers]. The publications cover those that have been published in the past four years, i.e., from 2022-08-01 to 2026-08-01.)

Article	Citations
Not feeling the buzz: Correction study of mispricing and inefficiency in online sportsbooks	420
Systemic bias of IMF reserve and debt forecasts for program countries	242
FRED-SD: A real-time database for state-level data with forecasting applications	236
Adaptively aggregated forecast for exponential family panel model	230
Survey density forecast comparison in small samples	160
Blending gradient boosted trees and neural networks for point and probabilistic forecasting of hierarchical time series	106
Fan charts 2.0: Flexible forecast distributions with expert judgement	106
Towards a real-time prediction of waiting times in emergency departments: A comparative analysis of machine learning techniques	102
Portfolio selection under non-gaussianity and systemic risk: A machine learning based forecasting approach	98
An overview of the effects of algorithm use on judgmental biases affecting forecasting	89
Forecasting stock return distributions around the globe with quantile neural networks	74
Forecasting stock market volatility with regime-switching GARCH-MIDAS: The role of geopolitical risks	73
Forecasting using variational Bayesian inference in large vector autoregressions with hierarchical shrinkage	67
The profitability of lead–lag arbitrage at high frequency	67
Responses to the discussions and commentaries of the M5 Special Issue	66
A fast and scalable ensemble of global models with long memory and data partitioning for the M5 forecasting competition	64
Subjective-probability forecasts of existential risk: Initial results from a hybrid persuasion-forecasting tournament	63
Guest editorial: In memory of Professor John Edward Boylan, 1959–2023	63
The decrease in confidence with forecast extremity	62
Forecasting with gradient boosted trees: augmentation, tuning, and cross-validation strategies	60
Too similar to combine? On negative weights in forecast combination	59
Fundamental determinants of exchange rate expectations	58
Forecasting intermittent time series with Gaussian Processes and Tweedie likelihood	58
A survey of models and methods used for forecasting when investing in financial markets	53
Multi-population mortality projection: The augmented common factor model with structural breaks	50

Machine learning applications in hierarchical time series forecasting: Investigating the impact of promotions	49
Tree-based heterogeneous cascade ensemble model for credit scoring	48
Weekly economic activity: Measurement and informational content	48
A time-varying skewness model for Growth-at-Risk	45
Cognitive reflection, arithmetic ability and financial literacy independently predict both inflation expectations and forecast accuracy	41
Hierarchical forecasting with a top-down alignment of independent-level forecasts	41
Machine learning and insurer failure prediction	40
Editorial Board	37
How does training improve individual forecasts? Modeling differences in compensatory and non-compensatory biases in geopolitical forecasts	37
Forecasting and policy when “we simply do not know”	37
A robust support vector regression model for electric load forecasting	35
Real estate illiquidity and returns: A time-varying regional perspective	35
Improving disaggregated short-term food inflation forecasts with webscraped data	33
Improving forecast stability using deep learning	32
The M5 competition: Conclusions	32
Forecasting the equity premium with frequency-decomposed technical indicators	29
Variability of the Lee–Carter model parameters	28
An assessment of the marginal predictive content of economic uncertainty indexes and business conditions predictors	28
Combining forecasts under structural breaks using Graphical LASSO	28
Editorial Board	28
Editorial Board	28
External forcings and predictability of the Atlantic multidecadal oscillation: A model confidence set approach	26
Nowcasting GDP with a pool of factor models and a fast estimation algorithm	26
Forecasting South Korea’s presidential election via multiparty dynamic Bayesian modeling	26
Enhancing market return forecasts with an incident-based ESG indicator	26
Exploring the representativeness of the M5 competition data	26
Post-script—Retail forecasting: Research and practice	26
Forecasting presidential elections: Accuracy of ANES voter intentions	25
Optimal hierarchical EWMA forecasting	25
Could the Bank of England have avoided mis-forecasting UK inflation during 2021–24?	25
Model combinations through revised base rates	24
Forecasting Australian fertility by age, region, and birthplace	24
Rejoinder: How to “improve” prediction using behavior modification	24
Forecasting expected shortfall: Should we use a multivariate model for stock market factors?	23
Modeling and forecasting intraday spot volatility	23
Whispers in the oil market: Exploring sentiment and uncertainty insights	23
When to be discrete: The importance of time formulation in the modeling of extreme events in finance	23
The structural Theta method and its predictive performance in the M4-Competition	23
Forecasting crude oil futures market returns: A principal component analysis combination approach	22
Network log-ARCH models for forecasting stock market volatility	22
Evaluating probabilistic classifiers: The triptych	22
Forecasting with trees	22
Forecasting GDP growth rates in the United States and Brazil using Google Trends	22
Retail forecasting: Research and practice	21
Portfolio return prediction and risk price heterogeneity	21
Deep Probabilistic Koopman: Long-term time-series forecasting under periodic uncertainties	21
Judgment in macroeconomic output growth predictions: Efficiency, accuracy and persistence	21
Editorial Board	20
M6 investment challenge: The role of luck and strategic considerations	19
Targeting predictors in random forest regression	19

A loss discounting framework for model averaging and selection in time series models	19
Forecasting electoral violence	18
A Bayesian Dirichlet auto-regressive moving average model for forecasting lead times	18
Reactions to the Bernanke Review from Bank of England watchers	18
Anticipating humanitarian emergencies with a high risk of conflict-induced displacement	18
Internal consistency of household inflation expectations: Point forecasts vs. density forecasts	17
A review and comparison of conflict early warning systems	17
Nowcasting U.S. state-level CO2 emissions and energy consumption	16
False dichotomy alert: Improving subjective-probability estimates vs. raising awareness of systemic risk	16
All forecasters are not the same: Systematic patterns in predictive performance	16
Hierarchical mortality forecasting with EVT tails: An application to solvency capital requirement	16
Counterfactual reconciliation: Incorporating aggregation constraints for more accurate causal effect estimates	16
Discussion of “Thirty years on: A review of the Lee–Carter method for forecasting mortality”	16
Technical analysis, spread trading, and data snooping control	16
Forecasting stock market return with anomalies: Evidence from China	15
Predicting value at risk for cryptocurrencies with generalized random forests	15
Editorial Board	15
M5 accuracy competition: Results, findings, and conclusions	15
Accelerating peak dating in a dynamic factor Markov-switching model	15
The power of narrative sentiment in economic forecasts	15
Static and dynamic models for multivariate distribution forecasts: Proper scoring rule tests of factor-quantile versus multivariate GARCH models	15
Volatility analysis for the GARCH–Itô–Jumps model based on high-frequency and low-frequency financial data	15
Beyond the numbers: The role of people and processes in central bank forecasting	14
Partisan bias, attribute substitution, and the benefits of an indirect format for eliciting forecasts and judgments of trend	14
Demand forecasting under lost sales stock policies	14
On forecast stability	14
A functional mixture prediction model for dynamically forecasting cumulative intraday returns of crude oil futures	14
Sensitivity and uncertainty in the Lee–Carter mortality model	14
Forecast value added in demand planning	14
Quasi-average predictions and regression to the trend: An application to the M6 financial forecasting competition	14
Jump persistence and temporal aggregation of tail risk	14
Factor-augmented forecasting in big data	14
Mixed-frequency machine learning: Nowcasting and backcasting weekly initial claims with daily internet search volume data	14
Dynamic linear models with adaptive discounting	13
Integrating nowcasts into an ensemble of data-driven forecasting models for SARI hospitalizations in Germany	13
Embrace the differences: Revisiting the PollyVote method of combining forecasts for U.S. presidential elections (2004 to 2020)	13
Physics-informed Gaussian process regression for states estimation and forecasting in power grids	13
The uncertainty track: Machine learning, statistical modeling, synthesis	13
Robust returns ranking prediction and portfolio optimization for M6	13
HARd to beat: The overlooked impact of rolling windows in the era of machine learning	12
Real-time hurricane damage nowcasts	12
Realized volatility forecasting for new issues and spin-offs using multi-source transfer learning	12
Lee–Carter models: The wider context	12
Trust the experts? The performance of inflation expectations, 1960–2023	12
Properties of the reconciled distributions for Gaussian and count forecasts	12