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 2021-12-01 to 2025-12-01.)

Article	Citations
Not feeling the buzz: Correction study of mispricing and inefficiency in online sportsbooks	600
Adaptively aggregated forecast for exponential family panel model	280
FRED-SD: A real-time database for state-level data with forecasting applications	254
Fan charts 2.0: Flexible forecast distributions with expert judgement	187
Systemic bias of IMF reserve and debt forecasts for program countries	172
An overview of the effects of algorithm use on judgmental biases affecting forecasting	158
Blending gradient boosted trees and neural networks for point and probabilistic forecasting of hierarchical time series	142
FFORMPP: Feature-based forecast model performance prediction	124
Portfolio selection under non-gaussianity and systemic risk: A machine learning based forecasting approach	116
Forecasting the Covid-19 recession and recovery: Lessons from the financial crisis	82
Survey density forecast comparison in small samples	81
Towards a real-time prediction of waiting times in emergency departments: A comparative analysis of machine learning techniques	80
Forecasting stock market volatility with regime-switching GARCH-MIDAS: The role of geopolitical risks	80
A survey of models and methods used for forecasting when investing in financial markets	79
The profitability of lead–lag arbitrage at high frequency	76
The decrease in confidence with forecast extremity	67
Machine learning applications in hierarchical time series forecasting: Investigating the impact of promotions	64
Short-term forecasting of the coronavirus pandemic	62
Guest editorial: In memory of Professor John Edward Boylan, 1959–2023	61
Responses to the discussions and commentaries of the M5 Special Issue	60
A time-varying skewness model for Growth-at-Risk	59
Nonparametric expected shortfall forecasting incorporating weighted quantiles	59
Subjective-probability forecasts of existential risk: Initial results from a hybrid persuasion-forecasting tournament	56
Forecasting intermittent time series with Gaussian Processes and Tweedie likelihood	55
Weekly economic activity: Measurement and informational content	55

Tree-based heterogeneous cascade ensemble model for credit scoring	54
Forecasting with gradient boosted trees: augmentation, tuning, and cross-validation strategies	53
Forecasting using variational Bayesian inference in large vector autoregressions with hierarchical shrinkage	51
A fast and scalable ensemble of global models with long memory and data partitioning for the M5 forecasting competition	51
Fundamental determinants of exchange rate expectations	50
Too similar to combine? On negative weights in forecast combination	48
Multi-population mortality projection: The augmented common factor model with structural breaks	46
Forecasting football results and exploiting betting markets: The case of “both teams to score”	45
Real estate illiquidity and returns: A time-varying regional perspective	44
Editorial Board	43
The M5 competition: Conclusions	42
How does training improve individual forecasts? Modeling differences in compensatory and non-compensatory biases in geopolitical forecasts	42
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
A robust support vector regression model for electric load forecasting	40
Forecasting the equity premium with frequency-decomposed technical indicators	40
Improving forecast stability using deep learning	39
Forecasting: theory and practice	38
An assessment of the marginal predictive content of economic uncertainty indexes and business conditions predictors	37
Variability of the Lee–Carter model parameters	35
Editorial Board	35
Editorial Board	34
Model combinations through revised base rates	34
Forecasting South Korea’s presidential election via multiparty dynamic Bayesian modeling	33
Exploring the representativeness of the M5 competition data	32
Sequential optimization three-way decision model with information gain for credit default risk evaluation	31
Forecasting presidential elections: Accuracy of ANES voter intentions	31
Post-script—Retail forecasting: Research and practice	31
Nowcasting GDP with a pool of factor models and a fast estimation algorithm	31
Evaluating probabilistic classifiers: The triptych	30
A disaster response model driven by spatial–temporal forecasts	30
Optimal hierarchical EWMA forecasting	30
Forecasting Australian fertility by age, region, and birthplace	30
Rejoinder: How to “improve” prediction using behavior modification	30
The structural Theta method and its predictive performance in the M4-Competition	29
Forecasting expected shortfall: Should we use a multivariate model for stock market factors?	28
Forecasting GDP growth rates in the United States and Brazil using Google Trends	26
Network log-ARCH models for forecasting stock market volatility	26
Deep Probabilistic Koopman: Long-term time-series forecasting under periodic uncertainties	26
Enhancing capacity planning through forecasting: An integrated tool for maintenance of complex product systems	26
Whispers in the oil market: Exploring sentiment and uncertainty insights	26
Forecasting crude oil futures market returns: A principal component analysis combination approach	25
Forecasting corporate default risk in China	25
Retail forecasting: Research and practice	25
Portfolio return prediction and risk price heterogeneity	24
Editorial Board	24
Judgment in macroeconomic output growth predictions: Efficiency, accuracy and persistence	24
Forecasting with trees	24
Mining semantic features in current reports for financial distress prediction: Empirical evidence from unlisted public firms in China	24
Combining forecasts for universally optimal performance	23

Hawkes process modeling of COVID-19 with mobility leading indicators and spatial covariates	23
Nowcasting U.S. state-level CO2 emissions and energy consumption	23
A loss discounting framework for model averaging and selection in time series models	23
Targeting predictors in random forest regression	23
Forecasting electoral violence	22
A Bayesian Dirichlet auto-regressive moving average model for forecasting lead times	22
M6 investment challenge: The role of luck and strategic considerations	22
Internal consistency of household inflation expectations: Point forecasts vs. density forecasts	21
A review and comparison of conflict early warning systems	21
Technical analysis, spread trading, and data snooping control	20
Forecasting stock market return with anomalies: Evidence from China	20
Discussion of “Thirty years on: A review of the Lee–Carter method for forecasting mortality”	19
False dichotomy alert: Improving subjective-probability estimates vs. raising awareness of systemic risk	19
Counterfactual reconciliation: Incorporating aggregation constraints for more accurate causal effect estimates	19
M5 accuracy competition: Results, findings, and conclusions	18
Hierarchical mortality forecasting with EVT tails: An application to solvency capital requirement	18
Partisan bias, attribute substitution, and the benefits of an indirect format for eliciting forecasts and judgments of trend	17
Forecast value added in demand planning	17
Guest Editorial: Food and Agriculture Forecasting	17
Quasi-average predictions and regression to the trend: An application to the M6 financial forecasting competition	17
Predicting value at risk for cryptocurrencies with generalized random forests	17
The power of narrative sentiment in economic forecasts	17
Mixed-frequency machine learning: Nowcasting and backcasting weekly initial claims with daily internet search volume data	17
Editorial Board	17
Guest editorial: Economic forecasting in times of COVID-19	16
Sensitivity and uncertainty in the Lee–Carter mortality model	16
Static and dynamic models for multivariate distribution forecasts: Proper scoring rule tests of factor-quantile versus multivariate GARCH models	16
Robust returns ranking prediction and portfolio optimization for M6	16
Factor-augmented forecasting in big data	16
Accelerating peak dating in a dynamic factor Markov-switching model	16
Predicting monthly biofuel production using a hybrid ensemble forecasting methodology	16
The uncertainty track: Machine learning, statistical modeling, synthesis	15
Machine learning algorithms for forecasting and backcasting blood demand data with missing values and outliers: A study of Tema General Hospital of Ghana	15
Demand forecasting under lost sales stock policies	15
Properties of the reconciled distributions for Gaussian and count forecasts	15
On forecast stability	15
Betting on a buzz: Mispricing and inefficiency in online sportsbooks	15
Physics-informed Gaussian process regression for states estimation and forecasting in power grids	15
Volatility analysis for the GARCH–Itô–Jumps model based on high-frequency and low-frequency financial data	15
Embrace the differences: Revisiting the PollyVote method of combining forecasts for U.S. presidential elections (2004 to 2020)	14
Lee–Carter models: The wider context	14
Dynamic linear models with adaptive discounting	14
Editorial Board	14
HARd to beat: The overlooked impact of rolling windows in the era of machine learning	14
Cross-temporal forecast reconciliation at digital platforms with machine learning	13
Trust the experts? The performance of inflation expectations, 1960–2023	13
Nowcasting with panels and alternative data: The OECD weekly tracker	13
Leveraging image-based generative adversarial networks for time series generation	13
Relative performance of judgmental methods for forecasting the success of megaprojects	13
Real-time hurricane damage nowcasts	13
Hierarchical transfer learning with applications to electricity load forecasting	13