2021

Volume 37, n° 3, July–September 2021

Baumeister C, Guérin P. A comparison of monthly global indicators for forecasting growth, pp. 1276-1295. doi:10.1016/j.ijforecast.2021.02.008
Cipollini F, Gallo GM, Palandri A. A dynamic conditional approach to forecasting portfolio weights, pp. 1111-1126. doi:10.1016/j.ijforecast.2020.12.002
Levene M, Fenner T. A stochastic differential equation approach to the analysis of the 2017 and 2019 UK general election polls, pp. 1227-1234. doi:10.1016/j.ijforecast.2021.02.002
Guizzardi A, Pons FME, Angelini G, Ranieri E. Big data from dynamic pricing: A smart approach to tourism demand forecasting, pp. 1049-1060. doi:10.1016/j.ijforecast.2020.11.006
Nystrup P, Lindström E, Møller JK, Madsen H. Dimensionality reduction in forecasting with temporal hierarchies, pp. 1127-1146. doi:10.1016/j.ijforecast.2020.12.003
Satoh D. Discrete Gompertz equation and model selection between Gompertz and logistic models, pp. 1192-1211. doi:10.1016/j.ijforecast.2021.01.005
Galvão AB, Garratt A, Mitchell J. Does judgment improve macroeconomic density forecasts? International Journal of Forecasting. 2021;37(3):1247-1260. doi:10.1016/j.ijforecast.2021.02.007
Fildes R, Goodwin P. Engaging research with practice — An invited editorial, pp. 1047-1048. doi:10.1016/j.ijforecast.2021.04.007
Erratum regarding missing Declaration of Competing Interest statement in previously published article, pp. 1297. doi:10.1016/j.ijforecast.2021.01.007
Erratum regarding missing Declaration of Competing Interest statement in previously published article, pp. 1296. doi:10.1016/j.ijforecast.2021.01.006
Erratum regarding missing Declaration of Competing Interest statement in previously published article, pp. 1317-1318. doi:10.1016/j.ijforecast.2021.01.018
Erratum regarding missing Declaration of Competing Interest statements in previously published articles, pp. 1298-1299. doi:10.1016/j.ijforecast.2021.01.008
Erratum regarding missing Declaration of Competing Interest statements in previously published articles, pp. 1302-1303. doi:10.1016/j.ijforecast.2021.01.010
Erratum regarding missing Declaration of Competing Interest statements in previously published articles, pp. 1304-1305. doi:10.1016/j.ijforecast.2021.01.011
Erratum regarding missing Declaration of Competing Interest statements in previously published articles, pp. 1321-1322. doi:10.1016/j.ijforecast.2021.01.020
Erratum regarding missing Declaration of Competing Interest statements in previously published articles, pp. 1323-1324. doi:10.1016/j.ijforecast.2021.01.021
Erratum regarding missing Declaration of Competing Interest statements in previously published articles, pp. 1329-1330. doi:10.1016/j.ijforecast.2021.01.024
Erratum regarding missing Declaration of Competing Interest statements in previously published articles, pp. 1312-1313. doi:10.1016/j.ijforecast.2021.01.015
Erratum regarding missing Declaration of Competing Interest statements in previously published articles, pp. 1314-1315. doi:10.1016/j.ijforecast.2021.01.016
Erratum regarding missing Declaration of Competing Interest statements in previously published articles, pp. 1300-1301. doi:10.1016/j.ijforecast.2021.01.009
Erratum regarding missing Declaration of Competing Interest statements in previously published articles, pp. 1316. doi:10.1016/j.ijforecast.2021.01.017
Erratum regarding missing Declaration of Competing Interest statements in previously published articles, pp. 1306-1307. doi:10.1016/j.ijforecast.2021.01.012
Erratum regarding missing Declaration of Competing Interest statements in previously published articles, pp. 1308-1309. doi:10.1016/j.ijforecast.2021.01.013
Erratum regarding missing Declaration of Competing Interest statements in previously published articles, pp. 1310-1311. doi:10.1016/j.ijforecast.2021.01.014
Erratum regarding missing Declaration of Competing Interest statements in previously published articles, pp. 1319-1320. doi:10.1016/j.ijforecast.2021.01.019
Erratum regarding missing Declaration of Competing Interest statements in previously published articles, pp. 1325-1326. doi:10.1016/j.ijforecast.2021.01.022
Erratum regarding missing Declaration of Competing Interest statements in previously published articles, pp. 1331-1332. doi:10.1016/j.ijforecast.2021.01.025
Erratum regarding missing Declaration of Competing Interest statements in previously published articles, pp. 1327-1328. doi:10.1016/j.ijforecast.2021.01.023
Solat K, Tsang KP. Forecasting exchange rates with elliptically symmetric principal components, pp. 1085-1091. doi:10.1016/j.ijforecast.2020.11.007
Adams PA, Adrian T, Boyarchenko N, Giannone D. Forecasting macroeconomic risks, pp. 1173-1191. doi:10.1016/j.ijforecast.2021.01.003
Lasek J, Gagolewski M. Interpretable sports team rating models based on the gradient descent algorithm, pp. 1061-1071. doi:10.1016/j.ijforecast.2020.11.008
Semenoglou A-A, Spiliotis E, Makridakis S, Assimakopoulos V. Investigating the accuracy of cross-learning time series forecasting methods, pp. 1072-1084. doi:10.1016/j.ijforecast.2020.11.009
García JR, Pacce M, Rodrigo T, Ruiz de Aguirre P, Ulloa CA. Measuring and forecasting retail trade in real time using card transactional data, pp. 1235-1246. doi:10.1016/j.ijforecast.2021.02.005
Chan JCC. Minnesota-type adaptive hierarchical priors for large Bayesian VARs, pp. 1212-1226. doi:10.1016/j.ijforecast.2021.01.002
Yan X, Wang H, Wang W, Xie J, Ren Y, Wang X. Optimal model averaging forecasting in high-dimensional survival analysis, pp. 1147-1155. doi:10.1016/j.ijforecast.2020.12.004
Pigini C. Penalized maximum likelihood estimation of logit-based early warning systems, pp. 1156-1172. doi:10.1016/j.ijforecast.2021.01.004
Brave SA, Gascon C, Kluender W, Walstrum T. Predicting benchmarked US state employment data in real time, pp. 1261-1275. doi:10.1016/j.ijforecast.2021.02.006
Lyócsa Š, Molnár P, Výrost T. Stock market volatility forecasting: Do we need high-frequency data? International Journal of Forecasting. 2021;37(3):1092-1110. doi:10.1016/j.ijforecast.2020.12.001

(résumés du n° 3/2021)

Volume 37, n° 2, April–June 2021

Vassallo D, Buccheri G, Corsi F. - A DCC-type approach for realized covariance modeling with score-driven dynamics, pp. 569-586. doi:10.1016/j.ijforecast.2020.07.006
Qu L. - A new approach to estimating earnings forecasting models: Robust regression MM-estimation, pp. 1011-1030. doi:10.1016/j.ijforecast.2020.11.003
de Bondt GJ, Hahn E, Zekaite Z. - ALICE: Composite leading indicators for euro area inflation cycles, pp. 687-707. doi:10.1016/j.ijforecast.2020.09.001
Casey E. - Are professional forecasters overconfident?, pp. 716-732. doi:10.1016/j.ijforecast.2020.09.002
Zeng Z, Li M. - Bayesian median autoregression for robust time series forecasting, pp. 1000-1010. doi:10.1016/j.ijforecast.2020.11.002
Ganics G, Odendahl F. - Bayesian VAR forecasts, survey information, and structural change in the euro area, pp. 971-999. doi:10.1016/j.ijforecast.2020.11.001
Kim D, Kang KH. - Conditional value-at-risk forecasts of an optimal foreign currency portfolio, pp. 838-861. doi:10.1016/j.ijforecast.2020.09.011
Kath C, Ziel F. - Conformal prediction interval estimation and applications to day-ahead and intraday power markets, pp. 777-799. doi:10.1016/j.ijforecast.2020.09.006
Berge TJ, Chang AC, Sinha NR. - Corrigendum to “Evaluating the conditionality of judgmental forecasts” [Int. J. Forecast. 35 (2019) 1627–1635], pp. 672-674. doi:10.1016/j.ijforecast.2020.08.006
Clements MP. - Do survey joiners and leavers differ from regular participants? The US SPF GDP growth and inflation forecasts, pp. 634-646. doi:10.1016/j.ijforecast.2020.08.003
Taylor JW. - Evaluating quantile-bounded and expectile-bounded interval forecasts, pp. 800-811. doi:10.1016/j.ijforecast.2020.09.007
Dimitriadis T, Schnaitmann J. - Forecast encompassing tests for the expected shortfall, pp. 604-621. doi:10.1016/j.ijforecast.2020.07.008
Melchior C, Zanini RR, Guerra RR, Rockenbach DA. - Forecasting Brazilian mortality rates due to occupational accidents using autoregressive moving average approaches, pp. 825-837. doi:10.1016/j.ijforecast.2020.09.010
Rubaszek M. - Forecasting crude oil prices with DSGE models, pp. 531-546. doi:10.1016/j.ijforecast.2020.07.004
Martin VL, Tang C, Yao W. - Forecasting the volatility of asset returns: The informational gains from option prices, pp. 862-880. doi:10.1016/j.ijforecast.2020.09.012
Calvo-Pardo H, Mancini T, Olmo J. - Granger causality detection in high-dimensional systems using feedforward neural networks, pp. 920-940. doi:10.1016/j.ijforecast.2020.10.004
Prestwich SD, Tarim SA, Rossi R. - Intermittency and obsolescence: A Croston method with linear decay, pp. 708-715. doi:10.1016/j.ijforecast.2020.08.010
Bojer CS, Meldgaard JP. - Kaggle forecasting competitions: An overlooked learning opportunity, pp. 587-603. doi:10.1016/j.ijforecast.2020.07.007
Greenwood-Nimmo M, Nguyen VH, Shin Y. - Measuring the Connectedness of the Global Economy, pp. 899-919. doi:10.1016/j.ijforecast.2020.10.003
Vrontos SD, Galakis J, Vrontos ID. - Modeling and predicting U.S. recessions using machine learning techniques, pp. 647-671. doi:10.1016/j.ijforecast.2020.08.005
Liu Y, Ye C, Sun J, Jiang Y, Wang H. - Modeling undecided voters to forecast elections: From bandwagon behavior and the spiral of silence perspective, pp. 461-483. doi:10.1016/j.ijforecast.2020.06.011
Li H, Sheng XS, Yang J. - Monitoring recessions: A Bayesian sequential quickest detection method, pp. 500-510. doi:10.1016/j.ijforecast.2020.06.013
Wilms I, Rombouts J, Croux C. - Multivariate volatility forecasts for stock market indices, pp. 484-499. doi:10.1016/j.ijforecast.2020.06.012
Arvanitis S, Post T, Potì V, Karabati S. - Nonparametric tests for Optimal Predictive Ability, pp. 881-898. doi:10.1016/j.ijforecast.2020.10.002
Richardson A, van Florenstein Mulder T, Vehbi T. - Nowcasting GDP using machine-learning algorithms: A real-time assessment, pp. 941-948. doi:10.1016/j.ijforecast.2020.10.005
Opschoor A, Lucas A. - Observation-driven models for realized variances and overnight returns applied to Value-at-Risk and Expected Shortfall forecasting, pp. 622-633. doi:10.1016/j.ijforecast.2020.07.009
Cho D. - On the predictability of the distribution of excess returns in currency markets, pp. 511-530. doi:10.1016/j.ijforecast.2020.07.003
Costantini M, Kunst RM. - On using predictive-ability tests in the selection of time-series prediction models: A Monte Carlo evaluation, pp. 445-460. doi:10.1016/j.ijforecast.2020.06.010
Jokubaitis S, Celov D, Leipus R. - Sparse structures with LASSO through principal components: Forecasting GDP components in the short-run, pp. 759-776. doi:10.1016/j.ijforecast.2020.09.005
Liu Y, Davanloo Tajbakhsh S, Conejo AJ. - Spatiotemporal wind forecasting by learning a hierarchically sparse inverse covariance matrix using wind directions, pp. 812-824. doi:10.1016/j.ijforecast.2020.09.009
Fildes R, Goodwin P. - Stability in the inefficient use of forecasting systems: A case study in a supply chain company, pp. 1031-1046. doi:10.1016/j.ijforecast.2020.11.004
Yen Y-M, Yen T-J. - Testing forecast accuracy of expectiles and quantiles with the extremal consistent loss functions, pp. 733-758. doi:10.1016/j.ijforecast.2020.09.004
Hoga Y. - The uncertainty in extreme risk forecasts from covariate-augmented volatility models, pp. 675-686. doi:10.1016/j.ijforecast.2020.08.009
Meira E, Cyrino Oliveira FL, Jeon J. - Treating and Pruning: New approaches to forecasting model selection and combination using prediction intervals, pp. 547-568. doi:10.1016/j.ijforecast.2020.07.005
Bastos BQ, Cyrino Oliveira FL, Milidiú RL. - U-Convolutional model for spatio-temporal wind speed forecasting, pp. 949-970. doi:10.1016/j.ijforecast.2020.10.007

( résumé n° 2/2021)

Volume 37, n° 1, January-March 2021

Alexander, C., Lazar, E., Stanescu, S. - Analytic moments for GJR-GARCH (1, 1) processes, pp. 105–124. https://doi.org/10.1016/j.ijforecast.2020.03.005
Amato, U., Antoniadis, A., De Feis, I., Goude, Y., Lagache, A. - Forecasting high resolution electricity demand data with additive models including smooth and jagged components, pp. 171–185. https://doi.org/10.1016/j.ijforecast.2020.04.001
An, Y., An, J., Cho, S. - Artificial intelligence-based predictions of movie audiences on opening Saturday, pp. 274–288. https://doi.org/10.1016/j.ijforecast.2020.05.005
Bellotti, A., Brigo, D., Gambetti, P., Vrins, F. - Forecasting recovery rates on non-performing loans with machine learning, pp. 428–444. https://doi.org/10.1016/j.ijforecast.2020.06.009
Chen, W., Xu, H., Jia, L., Gao, Y. - Machine learning model for Bitcoin exchange rate prediction using economic and technology determinants, pp. 28–43. https://doi.org/10.1016/j.ijforecast.2020.02.008
Cipollini, F., Gallo, G.M., Otranto, E. - Realized volatility forecasting: Robustness to measurement errors, pp. 44–57. https://doi.org/10.1016/j.ijforecast.2020.02.009
Cooke, R.M., Marti, D., Mazzuchi, T. - Expert forecasting with and without uncertainty quantification and weighting: What do the data say?, pp. 378–387. https://doi.org/10.1016/j.ijforecast.2020.06.007
Dichtl, H., Drobetz, W., Neuhierl, A., Wendt, V.-S. - Data snooping in equity premium prediction, pp. 72–94. https://doi.org/10.1016/j.ijforecast.2020.03.002
Feng, L., Shi, Y., Chang, L. - Forecasting mortality with a hyperbolic spatial temporal VAR model, pp. 255–273. https://doi.org/10.1016/j.ijforecast.2020.05.003
Gallego, J., Rivero, G., Martínez, J. - Preventing rather than punishing: An early warning model of malfeasance in public procurement, pp. 360–377. https://doi.org/10.1016/j.ijforecast.2020.06.006
Gilbert, C., Browell, J., McMillan, D. - Probabilistic access forecasting for improved offshore operations, pp. 134–150. https://doi.org/10.1016/j.ijforecast.2020.03.007
Gonçalves, C., Bessa, R.J., Pinson, P. - A critical overview of privacy-preserving approaches for collaborative forecasting, pp. 322–342. https://doi.org/10.1016/j.ijforecast.2020.06.003
Graziani, C., Rosner, R., Adams, J.M., Machete, R.L. - Probabilistic recalibration of forecasts, pp. 1–27. https://doi.org/10.1016/j.ijforecast.2019.04.019
Hewamalage, H., Bergmeir, C., Bandara, K. - Recurrent Neural Networks for Time Series Forecasting: Current status and future directions, pp. 388–427. https://doi.org/10.1016/j.ijforecast.2020.06.008
Hillebrand, E., Lukas, M., Wei, W. - Bagging weak predictors, pp. 237–254. https://doi.org/10.1016/j.ijforecast.2020.05.002
Kauppi, H., Virtanen, T. - Boosting nonlinear predictability of macroeconomic time series, pp. 151–170. https://doi.org/10.1016/j.ijforecast.2020.03.008
Martínez-Martín, J., Rusticelli, E. - Keeping track of global trade in real time, pp. 224–236. https://doi.org/10.1016/j.ijforecast.2020.04.005
Mongrain, P., Nadeau, R., Jérôme, B. - Playing the synthesizer with Canadian data: Adding polls to a structural forecasting model, pp. 289–301. https://doi.org/10.1016/j.ijforecast.2020.05.006
Panagiotelis, A., Athanasopoulos, G., Gamakumara, P., Hyndman, R.J. - Forecast reconciliation: A geometric view with new insights on bias correction, pp. 343–359. https://doi.org/10.1016/j.ijforecast.2020.06.004
Rizzi, S., Kjærgaard, S., Bergeron Boucher, M.-P., Camarda, C.G., Lindahl-Jacobsen, R., Vaupel, J.W. - Killing off cohorts: Forecasting mortality of non-extinct cohorts with the penalized composite link model, pp. 95–104. https://doi.org/10.1016/j.ijforecast.2020.03.003
Rummens, A., Hardyns, W. - The effect of spatiotemporal resolution on predictive policing model performance, pp. 125–133. https://doi.org/10.1016/j.ijforecast.2020.03.006
Rybinski, K. - Ranking professional forecasters by the predictive power of their narratives, pp. 186–204. https://doi.org/10.1016/j.ijforecast.2020.04.003
Saha, M., Santara, A., Mitra, P., Chakraborty, A., Nanjundiah, R.S. - Prediction of the Indian summer monsoon using a stacked autoencoder and ensemble regression model, pp. 58–71. https://doi.org/10.1016/j.ijforecast.2020.03.001
Sommer, B., Pinson, P., Messner, J.W., Obst, D. - Online distributed learning in wind power forecasting, pp. 205–223. https://doi.org/10.1016/j.ijforecast.2020.04.004
Song, L., Shi, Y., Tso, G.K.F., Lo, H.P. - Forecasting week-to-week television ratings using reduced-form and structural dynamic models, pp. 302–321. https://doi.org/10.1016/j.ijforecast.2020.06.002

(résumé n° 1/2021) * en attente de la réception de la version papier *

Dernière modification le 22.03.2022