OOIR: Observatory of International Research

Papers

(The TQCC of International Journal of Forecasting is 13. 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 2022-01-01 to 2026-01-01.)

Article	Citations
Not feeling the buzz: Correction study of mispricing and inefficiency in online sportsbooks	623
Adaptively aggregated forecast for exponential family panel model	294
Blending gradient boosted trees and neural networks for point and probabilistic forecasting of hierarchical time series	256
FFORMPP: Feature-based forecast model performance prediction	192
Systemic bias of IMF reserve and debt forecasts for program countries	187
An overview of the effects of algorithm use on judgmental biases affecting forecasting	165
FRED-SD: A real-time database for state-level data with forecasting applications	142
Survey density forecast comparison in small samples	125
Towards a real-time prediction of waiting times in emergency departments: A comparative analysis of machine learning techniques	123
Portfolio selection under non-gaussianity and systemic risk: A machine learning based forecasting approach	87
Fan charts 2.0: Flexible forecast distributions with expert judgement	86
Forecasting the Covid-19 recession and recovery: Lessons from the financial crisis	81
A survey of models and methods used for forecasting when investing in financial markets	80
Forecasting stock market volatility with regime-switching GARCH-MIDAS: The role of geopolitical risks	80
The profitability of lead–lag arbitrage at high frequency	77
The decrease in confidence with forecast extremity	67
Short-term forecasting of the coronavirus pandemic	66
Guest editorial: In memory of Professor John Edward Boylan, 1959–2023	62
Subjective-probability forecasts of existential risk: Initial results from a hybrid persuasion-forecasting tournament	61
Nonparametric expected shortfall forecasting incorporating weighted quantiles	61
Responses to the discussions and commentaries of the M5 Special Issue	61
A time-varying skewness model for Growth-at-Risk	60
Forecasting intermittent time series with Gaussian Processes and Tweedie likelihood	58
Multi-population mortality projection: The augmented common factor model with structural breaks	58
A fast and scalable ensemble of global models with long memory and data partitioning for the M5 forecasting competition	57

Machine learning applications in hierarchical time series forecasting: Investigating the impact of promotions	57
Forecasting using variational Bayesian inference in large vector autoregressions with hierarchical shrinkage	55
Fundamental determinants of exchange rate expectations	55
Tree-based heterogeneous cascade ensemble model for credit scoring	53
Forecasting with gradient boosted trees: augmentation, tuning, and cross-validation strategies	52
Weekly economic activity: Measurement and informational content	49
Too similar to combine? On negative weights in forecast combination	49
Editorial Board	46
Real estate illiquidity and returns: A time-varying regional perspective	46
Forecasting football results and exploiting betting markets: The case of “both teams to score”	46
The M5 competition: Conclusions	43
How does training improve individual forecasts? Modeling differences in compensatory and non-compensatory biases in geopolitical forecasts	43
Forecasting and policy when “we simply do not know”	42
A robust support vector regression model for electric load forecasting	41
Forecasting the equity premium with frequency-decomposed technical indicators	41
Cognitive reflection, arithmetic ability and financial literacy independently predict both inflation expectations and forecast accuracy	40
Hierarchical forecasting with a top-down alignment of independent-level forecasts	40
Improving forecast stability using deep learning	39
Forecasting: theory and practice	39
An assessment of the marginal predictive content of economic uncertainty indexes and business conditions predictors	38
Model combinations through revised base rates	35
Editorial Board	35
Editorial Board	35
Variability of the Lee–Carter model parameters	35
Forecasting South Korea’s presidential election via multiparty dynamic Bayesian modeling	34
Could the Bank of England have avoided mis-forecasting UK inflation during 2021–24?	33
Exploring the representativeness of the M5 competition data	32
Forecasting presidential elections: Accuracy of ANES voter intentions	31
Post-script—Retail forecasting: Research and practice	31
Sequential optimization three-way decision model with information gain for credit default risk evaluation	31
Combining forecasts under structural breaks using Graphical LASSO	31
Optimal hierarchical EWMA forecasting	31
Nowcasting GDP with a pool of factor models and a fast estimation algorithm	31
Evaluating probabilistic classifiers: The triptych	30
Forecasting Australian fertility by age, region, and birthplace	29
Rejoinder: How to “improve” prediction using behavior modification	29
A disaster response model driven by spatial–temporal forecasts	28
Forecasting expected shortfall: Should we use a multivariate model for stock market factors?	27
Deep Probabilistic Koopman: Long-term time-series forecasting under periodic uncertainties	27
The structural Theta method and its predictive performance in the M4-Competition	27
Whispers in the oil market: Exploring sentiment and uncertainty insights	27
When to be discrete: The importance of time formulation in the modeling of extreme events in finance	27
Forecasting with trees	26
Enhancing capacity planning through forecasting: An integrated tool for maintenance of complex product systems	26
Modeling and forecasting intraday spot volatility	26
Forecasting GDP growth rates in the United States and Brazil using Google Trends	26
Forecasting crude oil futures market returns: A principal component analysis combination approach	25
Network log-ARCH models for forecasting stock market volatility	24
Mining semantic features in current reports for financial distress prediction: Empirical evidence from unlisted public firms in China	24
Retail forecasting: Research and practice	24

Judgment in macroeconomic output growth predictions: Efficiency, accuracy and persistence	24
Forecasting corporate default risk in China	24
Portfolio return prediction and risk price heterogeneity	24
A loss discounting framework for model averaging and selection in time series models	23
Editorial Board	23
Reactions to the Bernanke Review from Bank of England watchers	22
Hawkes process modeling of COVID-19 with mobility leading indicators and spatial covariates	22
Nowcasting U.S. state-level CO2 emissions and energy consumption	22
Targeting predictors in random forest regression	22
Forecasting electoral violence	21
M6 investment challenge: The role of luck and strategic considerations	21
Combining forecasts for universally optimal performance	19
Anticipating humanitarian emergencies with a high risk of conflict-induced displacement	19
A Bayesian Dirichlet auto-regressive moving average model for forecasting lead times	19
A review and comparison of conflict early warning systems	19
Internal consistency of household inflation expectations: Point forecasts vs. density forecasts	18
Hierarchical mortality forecasting with EVT tails: An application to solvency capital requirement	18
Counterfactual reconciliation: Incorporating aggregation constraints for more accurate causal effect estimates	18
Discussion of “Thirty years on: A review of the Lee–Carter method for forecasting mortality”	18
Forecasting stock market return with anomalies: Evidence from China	18
Technical analysis, spread trading, and data snooping control	18
Partisan bias, attribute substitution, and the benefits of an indirect format for eliciting forecasts and judgments of trend	17
The power of narrative sentiment in economic forecasts	17
False dichotomy alert: Improving subjective-probability estimates vs. raising awareness of systemic risk	17
All forecasters are not the same: Systematic patterns in predictive performance	17
M5 accuracy competition: Results, findings, and conclusions	17
Forecast value added in demand planning	16
Demand forecasting under lost sales stock policies	16
Machine learning algorithms for forecasting and backcasting blood demand data with missing values and outliers: A study of Tema General Hospital of Ghana	16
Volatility analysis for the GARCH–Itô–Jumps model based on high-frequency and low-frequency financial data	16
On forecast stability	16
Quasi-average predictions and regression to the trend: An application to the M6 financial forecasting competition	16
Predicting monthly biofuel production using a hybrid ensemble forecasting methodology	16
Sensitivity and uncertainty in the Lee–Carter mortality model	16
Physics-informed Gaussian process regression for states estimation and forecasting in power grids	16
Mixed-frequency machine learning: Nowcasting and backcasting weekly initial claims with daily internet search volume data	16
Guest Editorial: Food and Agriculture Forecasting	15
Editorial Board	15
Accelerating peak dating in a dynamic factor Markov-switching model	15
Jump persistence and temporal aggregation of tail risk	15
Static and dynamic models for multivariate distribution forecasts: Proper scoring rule tests of factor-quantile versus multivariate GARCH models	15
Beyond the numbers: The role of people and processes in central bank forecasting	15
Predicting value at risk for cryptocurrencies with generalized random forests	15
Robust returns ranking prediction and portfolio optimization for M6	15
Factor-augmented forecasting in big data	14
Properties of the reconciled distributions for Gaussian and count forecasts	14
Guest editorial: Economic forecasting in times of COVID-19	14
A functional mixture prediction model for dynamically forecasting cumulative intraday returns of crude oil futures	14
The uncertainty track: Machine learning, statistical modeling, synthesis	13
Editorial Board	13
Lee–Carter models: The wider context	13
Dynamic linear models with adaptive discounting	13
Embrace the differences: Revisiting the PollyVote method of combining forecasts for U.S. presidential elections (2004 to 2020)	13