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 2021-09-01 to 2025-09-01.)

Article	Citations
Not feeling the buzz: Correction study of mispricing and inefficiency in online sportsbooks	1265
Blending gradient boosted trees and neural networks for point and probabilistic forecasting of hierarchical time series	544
Adaptively aggregated forecast for exponential family panel model	249
Fan charts 2.0: Flexible forecast distributions with expert judgement	236
FRED-SD: A real-time database for state-level data with forecasting applications	181
FFORMPP: Feature-based forecast model performance prediction	143
Systemic bias of IMF reserve and debt forecasts for program countries	140
Survey density forecast comparison in small samples	138
Portfolio selection under non-gaussianity and systemic risk: A machine learning based forecasting approach	126
Forecasting the Covid-19 recession and recovery: Lessons from the financial crisis	116
Towards a real-time prediction of waiting times in emergency departments: A comparative analysis of machine learning techniques	98
An overview of the effects of algorithm use on judgmental biases affecting forecasting	77
Forecasting stock market volatility with regime-switching GARCH-MIDAS: The role of geopolitical risks	76
Guest editorial: In memory of Professor John Edward Boylan, 1959–2023	75
Short-term forecasting of the coronavirus pandemic	74
Forecasting government support in Irish general elections: Opinion polls and structural models	72
Responses to the discussions and commentaries of the M5 Special Issue	67
The decrease in confidence with forecast extremity	58
The profitability of lead–lag arbitrage at high frequency	58
A fast and scalable ensemble of global models with long memory and data partitioning for the M5 forecasting competition	58
Machine learning applications in hierarchical time series forecasting: Investigating the impact of promotions	57
Fundamental determinants of exchange rate expectations	56
Macroeconomic data transformations matter	56
Tree-based heterogeneous cascade ensemble model for credit scoring	56
Forecasting with gradient boosted trees: augmentation, tuning, and cross-validation strategies	52

Nonparametric expected shortfall forecasting incorporating weighted quantiles	52
Subjective-probability forecasts of existential risk: Initial results from a hybrid persuasion-forecasting tournament	52
Dynamic factor models with clustered loadings: Forecasting education flows using unemployment data	51
Too similar to combine? On negative weights in forecast combination	50
Forecasting using variational Bayesian inference in large vector autoregressions with hierarchical shrinkage	47
Multi-population mortality projection: The augmented common factor model with structural breaks	47
Weekly economic activity: Measurement and informational content	45
A survey of models and methods used for forecasting when investing in financial markets	44
A time-varying skewness model for Growth-at-Risk	42
Forecasting football results and exploiting betting markets: The case of “both teams to score”	41
Editorial Board	41
How does training improve individual forecasts? Modeling differences in compensatory and non-compensatory biases in geopolitical forecasts	39
The M5 competition: Conclusions	39
Hierarchical forecasting with a top-down alignment of independent-level forecasts	36
Cognitive reflection, arithmetic ability and financial literacy independently predict both inflation expectations and forecast accuracy	36
Real estate illiquidity and returns: A time-varying regional perspective	35
Forecasting and policy when “we simply do not know”	35
Improving forecast stability using deep learning	35
A robust support vector regression model for electric load forecasting	34
Forecasting multiparty by-elections using Dirichlet regression	33
Forecasting the equity premium with frequency-decomposed technical indicators	32
Forecasting: theory and practice	31
Variability of the Lee–Carter model parameters	31
Editorial Board	31
An assessment of the marginal predictive content of economic uncertainty indexes and business conditions predictors	30
Model combinations through revised base rates	29
Editorial Board	29
Exploring the representativeness of the M5 competition data	28
Combining forecasts under structural breaks using Graphical LASSO	28
Optimal hierarchical EWMA forecasting	28
Modelling non-stationary ‘Big Data’	27
Forecasting presidential elections: Accuracy of ANES voter intentions	27
Sequential optimization three-way decision model with information gain for credit default risk evaluation	26
Post-script—Retail forecasting: Research and practice	26
Nowcasting GDP with a pool of factor models and a fast estimation algorithm	26
A disaster response model driven by spatial–temporal forecasts	25
Forecasting South Korea’s presidential election via multiparty dynamic Bayesian modeling	25
Evaluating probabilistic classifiers: The triptych	24
Forecasting Australian fertility by age, region, and birthplace	24
Forecasting GDP growth rates in the United States and Brazil using Google Trends	23
Forecasting with trees	23
Forecasting corporate default risk in China	23
Enhancing capacity planning through forecasting: An integrated tool for maintenance of complex product systems	23
Forecasting expected shortfall: Should we use a multivariate model for stock market factors?	22
The structural Theta method and its predictive performance in the M4-Competition	22
Deep Probabilistic Koopman: Long-term time-series forecasting under periodic uncertainties	22
Rejoinder: How to “improve” prediction using behavior modification	22
Mixed random forest, cointegration, and forecasting gasoline prices	22
Network log-ARCH models for forecasting stock market volatility	22
Forecasting crude oil futures market returns: A principal component analysis combination approach	21

Retail forecasting: Research and practice	21
When to be discrete: The importance of time formulation in the modeling of extreme events in finance	21
Hawkes process modeling of COVID-19 with mobility leading indicators and spatial covariates	20
Editorial Board	20
Judgment in macroeconomic output growth predictions: Efficiency, accuracy and persistence	20
Portfolio return prediction and risk price heterogeneity	19
Spurious relationships in high-dimensional systems with strong or mild persistence	19
Combining forecasts for universally optimal performance	19
A loss discounting framework for model averaging and selection in time series models	19
Targeting predictors in random forest regression	19
A Bayesian Dirichlet auto-regressive moving average model for forecasting lead times	19
Mining semantic features in current reports for financial distress prediction: Empirical evidence from unlisted public firms in China	19
Nowcasting U.S. state-level CO2 emissions and energy consumption	19
Internal consistency of household inflation expectations: Point forecasts vs. density forecasts	18
Reactions to the Bernanke Review from Bank of England watchers	18
A review and comparison of conflict early warning systems	18
M6 investment challenge: The role of luck and strategic considerations	18
Anticipating humanitarian emergencies with a high risk of conflict-induced displacement	18
Counterfactual reconciliation: Incorporating aggregation constraints for more accurate causal effect estimates	17
Hierarchical mortality forecasting with EVT tails: An application to solvency capital requirement	17
Temporal Fusion Transformers for interpretable multi-horizon time series forecasting	17
Technical analysis, spread trading, and data snooping control	17
Discussion of “Thirty years on: A review of the Lee–Carter method for forecasting mortality”	16
Sparse estimation of dynamic principal components for forecasting high-dimensional time series	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
M5 accuracy competition: Results, findings, and conclusions	15
Forecasting stock market return with anomalies: Evidence from China	15
Partisan bias, attribute substitution, and the benefits of an indirect format for eliciting forecasts and judgments of trend	15
The power of narrative sentiment in economic forecasts	15
Predicting value at risk for cryptocurrencies with generalized random forests	14
A functional mixture prediction model for dynamically forecasting cumulative intraday returns of crude oil futures	14
Editorial Board	14
Robust returns ranking prediction and portfolio optimization for M6	14
Guest editorial: Economic forecasting in times of COVID-19	14
Demand forecasting under lost sales stock policies	14
Forecast value added in demand planning	14
Guest Editorial: Food and Agriculture Forecasting	14
Factor-augmented forecasting in big data	14
Machine learning algorithms for forecasting and backcasting blood demand data with missing values and outliers: A study of Tema General Hospital of Ghana	14
Physics-informed Gaussian process regression for states estimation and forecasting in power grids	13
Accelerating peak dating in a dynamic factor Markov-switching model	13
Sensitivity and uncertainty in the Lee–Carter mortality model	13
Lee–Carter models: The wider context	12
Static and dynamic models for multivariate distribution forecasts: Proper scoring rule tests of factor-quantile versus multivariate GARCH models	12
Quasi-average predictions and regression to the trend: An application to the M6 financial forecasting competition	12
Editorial Board	12
Mixed-frequency machine learning: Nowcasting and backcasting weekly initial claims with daily internet search volume data	12
On forecast stability	12
Editorial Board	12
Predicting monthly biofuel production using a hybrid ensemble forecasting methodology	12
Volatility analysis for the GARCH–Itô–Jumps model based on high-frequency and low-frequency financial data	12