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 2020-04-01 to 2024-04-01.)

Article	Citations
DeepAR: Probabilistic forecasting with autoregressive recurrent networks	807
Temporal Fusion Transformers for interpretable multi-horizon time series forecasting	497
Recurrent Neural Networks for Time Series Forecasting: Current status and future directions	428
Forecasting: theory and practice	263
Forecasting for COVID-19 has failed	199
The impact of sentiment and attention measures on stock market volatility	146
Kaggle forecasting competitions: An overlooked learning opportunity	121
M5 accuracy competition: Results, findings, and conclusions	111
Retail forecasting: Research and practice	103
Forecasting volatility and co-volatility of crude oil and gold futures: Effects of leverage, jumps, spillovers, and geopolitical risks	101
Machine learning model for Bitcoin exchange rate prediction using economic and technology determinants	98
Forecasting stock price volatility: New evidence from the GARCH-MIDAS model	95
The impact of the COVID-19 pandemic on business expectations	95
Incorporating textual information in customer churn prediction models based on a convolutional neural network	77
Daily retail demand forecasting using machine learning with emphasis on calendric special days	75
Forecasting global equity market volatilities	72
Principles and algorithms for forecasting groups of time series: Locality and globality	70
A novel text-based framework for forecasting agricultural futures using massive online news headlines	70
Predicting bank insolvencies using machine learning techniques	63
Forecasting commodity prices out-of-sample: Can technical indicators help?	52
The role of text-extracted investor sentiment in Chinese stock price prediction with the enhancement of deep learning	50
Forecast combinations for value at risk and expected shortfall	46
Predicting monthly biofuel production using a hybrid ensemble forecasting methodology	46
Forecast reconciliation: A geometric view with new insights on bias correction	45
Neural basis expansion analysis with exogenous variables: Forecasting electricity prices with NBEATSx	42

COVID-19: Forecasting confirmed cases and deaths with a simple time series model	41
Macroeconomic forecasting with large Bayesian VARs: Global-local priors and the illusion of sparsity	40
The M5 competition: Background, organization, and implementation	39
Forecasting with trees	38
Nowcasting GDP using machine-learning algorithms: A real-time assessment	37
Forecasting recovery rates on non-performing loans with machine learning	35
Measuring the Connectedness of the Global Economy	35
Probabilistic electricity price forecasting with NARX networks: Combine point or probabilistic forecasts?	35
Forecasting realized volatility of agricultural commodity futures with infinite Hidden Markov HAR models	35
Forecasting the Covid-19 recession and recovery: Lessons from the financial crisis	33
Preventing rather than punishing: An early warning model of malfeasance in public procurement	33
Hawkes process modeling of COVID-19 with mobility leading indicators and spatial covariates	32
Forecast combinations: An over 50-year review	32
Oil price shocks and economic growth: The volatility link	32
Forecasting crude oil market volatility using variable selection and common factor	32
Combining survey long-run forecasts and nowcasts with BVAR forecasts using relative entropy	32
Comparing the forecasting performances of linear models for electricity prices with high RES penetration	31
Investigating the accuracy of cross-learning time series forecasting methods	30
Big data from dynamic pricing: A smart approach to tourism demand forecasting	29
Forecasting with news sentiment: Evidence with UK newspapers	29
Recent advances in intra-hour solar forecasting: A review of ground-based sky image methods	29
The M5 uncertainty competition: Results, findings and conclusions	29
Extension of the Elo rating system to margin of victory	28
Artificial bee colony-based combination approach to forecasting agricultural commodity prices	28
Forecasting cryptocurrency volatility	28
Crude oil price forecasting incorporating news text	28
Stock market volatility forecasting: Do we need high-frequency data?	28
Predicting ordinary and severe recessions with a three-state Markov-switching dynamic factor model	27
Endemic-epidemic models with discrete-time serial interval distributions for infectious disease prediction	26
Forecasting value at risk and expected shortfall with mixed data sampling	26
Multivariate volatility forecasts for stock market indices	26
On single point forecasts for fat-tailed variables	26
Forecasting realized volatility of agricultural commodities	26
Forecasting risk measures using intraday data in a generalized autoregressive score framework	25
Short-term forecasting of the coronavirus pandemic	25
Forecasting sales using online review and search engine data: A method based on PCA–DSFOA–BPNN	25
High-frequency monitoring of growth at risk	25
Forecasting third-party mobile payments with implications for customer flow prediction	24
Treating and Pruning: New approaches to forecasting model selection and combination using prediction intervals	24
Probabilistic forecasting of heterogeneous consumer transaction–sales time series	24
Forecasting macroeconomic risks	24
Comparing trained and untrained probabilistic ensemble forecasts of COVID-19 cases and deaths in the United States	24
Minnesota-type adaptive hierarchical priors for large Bayesian VARs	24
A comparison of monthly global indicators for forecasting growth	23
Can Google search data help predict macroeconomic series?	23
Comparing the accuracy of several network-based COVID-19 prediction algorithms	23
Prediction of the Indian summer monsoon using a stacked autoencoder and ensemble regression model	23
Probabilistic forecasting in day-ahead electricity markets: Simulating peak and off-peak prices	23
Spatio-temporal modeling of yellow taxi demands in New York City using generalized STAR models	22
Temperature anomaly detection for electric load forecasting	22

Forecasting inflation with online prices	22
Forecasting in humanitarian operations: Literature review and research needs	22
Forecasting crude oil futures market returns: A principal component analysis combination approach	22
Five dimensions of the uncertainty–disagreement linkage	22
Forecasting crude oil prices with DSGE models	22
Nowcasting unemployment insurance claims in the time of COVID-19	21
Forecasting high resolution electricity demand data with additive models including smooth and jagged components	20
Semi-parametric dynamic asymmetric Laplace models for tail risk forecasting, incorporating realized measures	20
Forecasting Bitcoin with technical analysis: A not-so-random forest?	20
Transparent modeling of influenza incidence: Big data or a single data point from psychological theory?	19
A critical overview of privacy-preserving approaches for collaborative forecasting	19
An empirical investigation of water consumption forecasting methods	19
Forecasting Brazilian mortality rates due to occupational accidents using autoregressive moving average approaches	19
Stability in the inefficient use of forecasting systems: A case study in a supply chain company	19
Global economic policy uncertainty aligned: An informative predictor for crude oil market volatility	18
The effect of spatiotemporal resolution on predictive policing model performance	18
Forecasting election results by studying brand importance in online news	18
Bagging weak predictors	18
Predicting loss given default in leasing: A closer look at models and variable selection	18
Forecasting loss given default for peer-to-peer loans via heterogeneous stacking ensemble approach	18
Conformal prediction interval estimation and applications to day-ahead and intraday power markets	18
Mining semantic features in current reports for financial distress prediction: Empirical evidence from unlisted public firms in China	17
Modeling and predicting U.S. recessions using machine learning techniques	17
Forecasting unemployment insurance claims in realtime with Google Trends	17
Probabilistic population forecasting: Short to very long-term	17
Realized volatility forecasting: Robustness to measurement errors	17
Stochastic volatility models with ARMA innovations: An application to G7 inflation forecasts	17
Trading and non-trading period realized market volatility: Does it matter for forecasting the volatility of US stocks?	17
The COVID-19 shock and challenges for inflation modelling	17
Quantile forecasting with mixed-frequency data	17
Distributed ARIMA models for ultra-long time series	16
The recurrence of financial distress: A survival analysis	16
Spatial dependence in microfinance credit default	16
Statistical learning and exchange rate forecasting	16
Probabilistic energy forecasting using the nearest neighbors quantile filter and quantile regression	16
A robust support vector regression model for electric load forecasting	16
Calibration of deterministic NWP forecasts and its impact on verification	15
An information-theoretic approach for forecasting interval-valued SP500 daily returns	15
A Model Confidence Set approach to the combination of multivariate volatility forecasts	15
Model-based pre-election polling for national and sub-national outcomes in the US and UK	15
Bayesian median autoregression for robust time series forecasting	15
A three-frequency dynamic factor model for nowcasting Canadian provincial GDP growth	15
Rethinking weather station selection for electric load forecasting using genetic algorithms	15
Assessing and predicting small industrial enterprises’ credit ratings: A fuzzy decision-making approach	15
Probabilistic access forecasting for improved offshore operations	14
Expert forecasting with and without uncertainty quantification and weighting: What do the data say?	14
Forecasting volatility with time-varying leverage and volatility of volatility effects	14
Online distributed learning in wind power forecasting	14
Realized volatility forecast with the Bayesian random compressed multivariate HAR model	14
Mixed random forest, cointegration, and forecasting gasoline prices	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
Factor extraction using Kalman filter and smoothing: This is not just another survey	14
Forecasting CPI inflation components with Hierarchical Recurrent Neural Networks	13
Spatio-temporal probabilistic forecasting of wind power for multiple farms: A copula-based hybrid model	13
Informational efficiency and behaviour within in-play prediction markets	13
Classification-based model selection in retail demand forecasting	13
Forecasting from others’ experience: Bayesian estimation of the generalized Bass model	13
FFORMPP: Feature-based forecast model performance prediction	13
Election forecasting: Too far out?	12
Forecasting and forecast narratives: The Bank of England Inflation Reports	12
Forecasting electricity prices with expert, linear, and nonlinear models	12
Exploring the representativeness of the M5 competition data	12
Evaluating quantile-bounded and expectile-bounded interval forecasts	12
A Bayesian approach for predicting food and beverage sales in staff canteens and restaurants	12
Sequential optimization three-way decision model with information gain for credit default risk evaluation	12
Forecasting European carbon returns using dimension reduction techniques: Commodity versus financial fundamentals	12
Nowcasting food inflation with a massive amount of online prices	12