International Journal of Forecasting

Volume 35, n° 4, October-December 2019

  • TAYLOR Nick - Forecasting returns in the VIX futures market, pp. 1193-1210
  • CATTIVELLI Luca, PIRINO Davide - A SHARP model of bid–ask spread forecasts, pp. 1211-1225
  • CARRIERO Andrea, GALVÃO Ana Beatriz, KAPETANIOS George - A comprehensive evaluation of macroeconomic forecasting methods, pp. 1226-1239
  • CLEMENTS Michael P. - Do forecasters target first or later releases of national accounts data?, pp. 1240-1249
  • BALLESTRA Luca Vincenzo, GUIZZARDI Andrea, PALLADINI Fabio - Forecasting and trading on the VIX futures market: A neural network approach based on open to close returns and coincident indicators, pp. 1250-1262
  • HASSANI Hossein, RUA António, SILVA Emmanuel Sirimal, THOMAKOS Dimitrios - Monthly forecasting of GDP with mixed-frequency multivariate singular spectrum analysis, pp. 1263-1272
  • DIMITRAKOPOULOS Stefanos, TSIONAS Mike - Ordinal-response GARCH models for transaction data: A forecasting exercise, pp. 1273-1287
  • SAXENA Harshit, APONTE Omar, MCCONKY Katie T. - A hybrid machine learning model for forecasting a billing period’s peak electric load days, pp. 1288-1303
  • KOKOSZKA Piotr, MIAO Hong, PETERSEN Alexander, SHANG Han Lin - Forecasting of density functions with an application to cross-sectional and intraday returns, pp. 1304-1317
  • YAO Xingzhi, IZZELDIN Marwan, LI Zhenxiong - A novel cluster HAR-type model for forecasting realized volatility, pp. 1318-1331
  • NAIMOLI Antonio, STORTI Giuseppe - Heterogeneous component multiplicative error models for forecasting trading volumes, pp. 1332-1355
  • KYRIAZI Foteini, THOMAKOS Dimitrios D., GUERARD John B. - Adaptive learning forecasting, with applications in forecasting agricultural prices, pp. 1356-1369
  • ARDIA David, BLUTEAU Keven, BOUDT Kris - Questioning the news about economic growth: Sparse forecasting using thousands of news-based sentiment values, pp. 1370-1386
Special Section: Energy Forecasting In The Big Data World, Guest Editors: Tao Hong and Pierre Pinson
  • HONG Tao, PINSON Pierre - Energy forecasting in the big data world, pp. 1387-1388
  • HONG Tao, XIE Jingrui, BLACK Jonathan - Global energy forecasting competition 2017: Hierarchical probabilistic load forecasting, pp. 1389-1399
  • ZIEL Florian - Quantile regression for the qualifying match of GEFCom2017 probabilistic load forecasting, pp. 1400-1408
  • DIMOULKAS I., MAZIDI P., HERRE L. - Neural networks for GEFCom2017 probabilistic load forecasting, pp. 1409-1423
  • SMYL Slawek, HUA N. Grace - Machine learning methods for GEFCom2017 probabilistic load forecasting, pp. 1424-1431
  • LANDGRAF Andrew J. - An ensemble approach to GEFCom2017 probabilistic load forecasting, pp. 1432-1438
  • ROACH Cameron - Reconciled boosted models for GEFCom2017 hierarchical probabilistic load forecasting, pp. 1439-1450
  • DE HOOG Julian, ABDULLA Khalid - Data visualization and forecast combination for probabilistic load forecasting in GEFCom2017 final match, pp. 1451-1459
  • KANDA Isao, VEGUILLAS J.M. Quintana - Data preprocessing and quantile regression for probabilistic load forecasting in the GEFCom2017 final match, pp. 1460-1468
  • HABEN Stephen, GIASEMIDIS Georgios, ZIEL Florian, ARORA Siddharth - Short term load forecasting and the effect of temperature at the low voltage level, pp. 1469-1484
  • MESSNER Jakob W., PINSON Pierre - Online adaptive lasso estimation in vector autoregressive models for high dimensional wind power forecasting, pp. 1485-1498
  • YANG Dazhi, WU Elynn, KLEISSL Jan - Operational solar forecasting for the real-time market, pp. 1499-1519
  • MARCJASZ Grzegorz, UNIEJEWSKI Bartosz, WERON Rafał - On the importance of the long-term seasonal component in day-ahead electricity price forecasting with NARX neural networks, pp. 1520-1532
  • UNIEJEWSKI Bartosz, MARCJASZ Grzegorz, WERON Rafał - Understanding intraday electricity markets: Variable selection and very short-term price forecasting using LASSO, pp. 1533-1547
  • LI Xuerong, SHANG Wei, WANG Shouyang - Text-based crude oil price forecasting: A deep learning approach, pp. 1548-1560

Special Section: Central Bank Forecasting, Guest Editors: Domenico Giannone, George Kapetanios and Michael McCracken

  • GIANNONE Domenico, KAPETANIOS George, MCCRACKEN Michael W. - Editorial: Central bank forecasting, pp. 1561-1563
  • REIFSCHNEIDER David, TULIP Peter - Gauging the uncertainty of the economic outlook using historical forecasting errors: The Federal Reserve’s approach, pp. 1564-1582
  • CROUSHORE Dean, VAN NORDEN Simon - Fiscal Surprises at the FOMC, pp. 1583-1595
  • CHIU Ching-Wai (Jeremy), HAYES Simon, KAPETANIOS George, THEODORIDIS Konstantinos - A new approach for detecting shifts in forecast accuracy, pp. 1596-1612
  • GALBRAITH John W., VAN NORDEN Simon - Asymmetry in unemployment rate forecast errors, pp. 1613-1626
  • BERGE Travis J., CHANG Andrew C., SINHA Nitish R. - Evaluating the conditionality of judgmental forecasts, pp. 1627-1635
  • GRANZIERA Eleonora, SEKHPOSYAN Tatevik - Predicting relative forecasting performance: An empirical investigation, pp. 1636-1657
  • ANGELINI Elena, LALIK Magdalena, LENZA Michele, PAREDES Joan - Mind the gap: A multi-country BVAR benchmark for the Eurosystem projection, pp. 1658-1668
  • DOMIT Sílvia, MONTI Francesca, SOKOL Andrej - Forecasting the UK economy with a medium-scale Bayesian VAR, pp. 1669-1678
  • DIEBOLD Francis X., SHIN Minchul - Machine learning for regularized survey forecast combination: Partially-egalitarian LASSO and its derivatives, pp. 1679-1691
  • BRAVE Scott A., BUTTERS R. Andrew, JUSTINIANO Alejandro - Forecasting economic activity with mixed frequency BVARs, pp. 1692-1707
  • KNOTEK Edward S., ZAMAN Saeed - Financial nowcasts and their usefulness in macroeconomic forecasting, pp. 1708-1724
  • CARUSO Alberto - Macroeconomic news and market reaction: Surprise indexes meet nowcasting, pp. 1725-1734
  • GORGI Paolo, KOOPMAN Siem Jan, LI Mengheng - Forecasting economic time series using score-driven dynamic models with mixed-data sampling - pp. 1735-1747
  • KNÜPPEL Malte, SCHULTEFRANKENFELD Guido - Assessing the uncertainty in central banks’ inflation outlooks, pp. 1748-1769
  • CAI Michael, NEGRO Marco Del, GIANNONI Marc P., GUPTA Abhi, ... MOSZKOWSKI Erica - DSGE forecasts of the lost recovery, pp. 1770-1789
  • AASTVEIT Knut Are, ANUNDSEN André K., HERSTAD Eyo I. - Residential investment and recession predictability, pp. 1790-1799
  • HAAS ORNELAS José Renato, BALTIERI MAUAD Roberto - Implied volatility term structure and exchange rate predictability, pp. 1800-1813
  • GARCIGA Christian, KNOTEK II Edward S. - Forecasting GDP growth with NIPA aggregates: In search of core GDP, pp. 1814-1828

(résumés du n° 4/2019)

Volume 35, n° 3, July-September 2019

  • ANATOLYEV Stanislav, BARUNÍK Jozef - Forecasting dynamic return distributions based on ordered binary choice, pp. 823-835
  • TRUCÍOS Carlos - Forecasting Bitcoin risk measures: A robust approach, pp. 836-847
  • DAVIG Troy, HALL Aaron Smalter - Recession forecasting using Bayesian classification, pp. 848-867
  • GRAEFE Andreas - Accuracy of German federal election forecasts, 2013 & 2017, pp. 868-877
  • LIELI Robert P., STINCHCOMBE Maxwell B., GROLMUSZ Viola M. - Unrestricted and controlled identification of loss functions: Possibility and impossibility results, pp. 878-890
  • DE GOOIJER Jan G., ZEROM Dawit - Semiparametric quantile averaging in the presence of high-dimensional predictors, pp.891-909
  • POST Thierry, KARABATI Selçuk, ARVANITIS Stelios - Robust optimization of forecast combinations, pp.910-926

Special Section: Forecasting issues in developing economies

  • GONZÁLEZ-RIVERA Gloria, LOUNGANI Prakash, SHENG Xuguang (Simon) - Forecasting issues in developing economies, pp. 927-928
  • LAHIRI Kajal, ZHAO Yongchen - International propagation of shocks: A dynamic factor model using survey forecasts, pp.929-947
  • GONZÁLEZ-RIVERA Gloria, MALDONADO Javier, RUIZ Esther - Growth in stress, pp. 948-966
  • LIU Yang, SHENG Xuguang Simon - The measurement and transmission of macroeconomic uncertainty: Evidence from the U.S. and BRIC countries, pp. 967-979
  • DAS Abhiman, LAHIRI Kajal, ZHAO Yongchen - Inflation expectations in India: Learning from household tendency surveys, pp. 980-993
  • CHAREMZA Wojciech, DÍAZ Carlos, MAKAROVA Svetlana - Quasi ex-ante inflation forecast uncertainty, pp. 994-1007
  • DUNCAN Roberto, MARTÍNEZ-GARCÍA Enrique - New perspectives on forecasting inflation in emerging market economies: An empirical assessment, pp. 1008-1031
  • ŁYZIAK Tomasz - Do global output gaps help forecast domestic inflation? Evidence from Phillips curves for Poland, pp. 1032-1041
  • SZAFRANEK Karol - Bagged neural networks for forecasting Polish (low) inflation, pp. 1042-1059
  • PINCHEIRA-BROWN Pablo, SELAIVE Jorge, NOLAZCO Jose Luis - Forecasting inflation in Latin America with core measures, pp. 1060-1071
  • WILDI Marc, MCELROY Tucker S. - The trilemma between accuracy, timeliness and smoothness in real-time signal extraction, pp. 1072-1084
  • AROMÍ J. Daniel - Medium term growth forecasts: Experts vs. simple models, pp. 1085-1099
  • PEDERSEN Michael - Anomalies in macroeconomic prediction errors–evidence from Chilean private forecasters, pp. 1100-1107
  • SINCLAIR Tara M. - Characteristics and implications of Chinese macroeconomic data revisions, pp. 1108-1117
  • BAILLIU Jeannine, HAN Xinfen, KRUGER Mark, LIU Yu-Hsien, THANABALASINGAM Sri - Can media and text analytics provide insights into labour market conditions in China?, pp. 1118-1130
  • AN Zidong, BALL Laurence, JALLES Joao, LOUNGANI Prakash - Do IMF forecasts respect Okun’s law? Evidence for advanced and developing economies, pp. 1131-1142
  • EICHER Theo S., KUENZEL David J., PAPAGEORGIOU Chris, CHRISTOFIDES Charis - Forecasts in times of crises, pp. 1143-1159
  • CHEN Sophia, RANCIERE Romain - Financial information and macroeconomic forecasts, pp. 1160-1174
  • STEINBUKS Jevgenijs - Assessing the accuracy of electricity production forecasts in developing countries, pp. 1175-1185
  • WRIGHT Jonathan H. - Some observations on forecasting and policy, pp. 1186-1192

Volume 35, n° 2, April-June 2019

  • WANG Rudan, MORLEY Bruce, STAMATOGIANNIS Michalis P. - Forecasting the exchange rate using nonlinear Taylor rule based models, pp. 429-442
  • TARASSOW Artur - Forecasting U.S. money growth using economic uncertainty measures and regularisation techniques, pp. 443-457
  • HUBER Florian, ZÖRNER Thomas O. - Threshold cointegration in international exchange rates:A Bayesian approach, pp. 458-473
  • THOMSON Mary E., POLLOCK Andrew C., ÖNKAL Dilek, GÖNÜL M. Sinan - Combining forecasts: Performance and coherence, pp. 474-484
  • CATANIA Leopoldo, GRASSI Stefano, RAVAZZOLO Francesco - Forecasting cryptocurrencies under model and parameter instability, pp. 485-501
  • LOBO Benjamin J., BROWN Donald E., GRAZAITIS Peter J. - Long-term forecasting of fuel demand at theater entry points, pp. 502-520
  • FRAZIER David T., MANEESOONTHORN Worapree, MARTIN Gael M., McCAB Brendan P.M. - Approximate Bayesian forecasting, pp. 521-539
  • KAZAK Ekaterina, POHLMEIER Winfried - Testing out-of-sample portfolio performance, pp. 540-554
  • CEPNI Oguzhan I., GÜNEY Ethem, SWANSON Norman R. - Nowcasting and forecasting GDP in emerging markets using global financial and macroeconomic diffusion indexes, pp. 555-572
  • WHEATCROFT Edward -  Interpreting the skill score form of forecast performance metrics, pp. 573-579
  • McADAM Peter, WARNE Anders - Euro area real-time density forecasting with financial or labor market frictions, pp. 580-600
  • RISSE Martin - Combining wavelet decomposition with machine learning to forecast gold returns, pp. 601-615
  • PANAGIOTELIS Anastasios, ATHANASPOULOS George, HYNDMAN Rob J., JIANG Bin, VAHID Farshid - Macroeconomic forecasting for Australia using a large number of predictors, pp. 616-633
  • ASIF M., McHALE I.G. - A generalized non-linear forecasting model for limited overs international cricket, pp. 634-640

Special Section: Forecasting, Uncertainty and Risk Management

  • MAKRIDAKIS Spyros, WILLIAMS Terry, KIRKHAM Richard, PAPADAKI Maria - Editorial: Forecasting, uncertainty and risk management, pp. 641-643
  • MARSHALL Alasdair, OJIAKO Udechukwu, WANG Victoria, LIN Fenfang, CHIPULU Maxwell -  Forecasting unknown-unknowns by boosting the risk radar within the risk intelligent organisation, pp. 644-658
  • MAKRIDAKIS Spyros, KIRKHAM Richard, WAKEFIELD Ann, PAPADAKI Maria, KIRKHAM J., LONG Lisa - Forecasting, uncertainty and risk; perspectives on clinical decision-making in preventive and curative medicine, pp. 659-666
  • BLOOMFIELD Katherine, WILLIAMS Terry, BOVIS Chris, MERALI Yasmin - Systemic risk in major public contracts, pp. 667-676
  • TALEB Nassim Nicholas - How much data do you need? An operational, pre-asymptotic metric for fat-tailedness, pp. 677-686
  • SPILIOTIS Evangelos, NIKOLOPOULOS Konstantinos, ASSIMAKOPOULOS Vassilios - Tales from tails: On the empirical distributions of forecasting errors and their implication to risk, pp. 687-698
  • KARMAKAR Madhusudan, PAUL Samit - Intraday portfolio risk management using VaR and CVaR:A CGARCH-EVT-Copula approach, pp. 699-709
Special Section: Sports Forecasting 
  • McHALE Ian, SWART Tim - Editorial: Forecasting in sports, pp. 710-711
  • ANGELINI Giovanni, DE ANGELIS Luca - Efficiency of online football betting markets, pp. 712-721
  • CORONA Francisco, FORREST David, TENA J.D., WIPER Michael - Bayesian forecasting of UEFA Champions League under alternative seeding regimes, pp. 722-732
  • ARAKI Kenji, HIROSE Yoshihiro, KOMAKI Fumiyasu - Paired comparison models with age effects modeled as piecewise quadratic splines, pp. 733-740
  • BABOOTA Rahul, KAUR Harleen - Predictive analysis and modelling football results using machine learning approach for English Premier League, pp. 741-755
  • KOVALCHIK Stephanie, REID Machar - A calibration method with dynamic updates for within-match forecasting of wins in tennis, pp. 756-766
  • MULHOLLAND Jason, JENSEN Shane T. - Optimizing the allocation of funds of an NFL team under the salary cap, pp. 767-775
  • MAYMIN Philip Z. - Wage against the machine: A generalized deep-learning market test of dataset value, pp. 776-782
  • HUBÁCÉK Ondřej, ŠOUREK Gustav, ŽELEZNÝ Filip - Exploiting sports-betting market using machine learning, pp. 783-796
  • KOOPMAN Siem Jan, LIT Rutger - Forecasting football match results in national league competitions using score-driven time series models, pp. 797-809
  • VAN REETH Daam - Forecasting Tour de France TV audiences: A multi-country analysis, pp. 810-821

  (résumés du n° 2/2019)  

Volume 35, n° 1, January-March 2019

  • TEMPORÃO Mickael, DUFRESNE Yannick, SAVOIE Justin, VAN DER LINDEN Clifton - Crowdsourcing the vote: New horizons in citizen forecasting, pp. 1-10
  • NOLTE Ingmar, NOLTE Sandra, POHLMEIER Winfried - What determines forecasters’ forecasting errors? pp. 11-24
  • BUSE Rebekka, SCHIENLE Melanie - Measuring connectedness of euro area sovereign risk, pp. 25-44
  • GÖTZ Thomas B., KNETSCH Thomas A. - Google data in bridge equation models for German GD, pp. 45-66
  • CUBADDA Gianluca, GUARDABASCIO Barbara - Representation, estimation and forecasting of the multivariate index-augmented autoregressive model, pp. 67-79
  • DEMETRESCU Matei, HOKE Sinem Hacıoğlu - Predictive regressions under asymmetric loss: Factor augmentation and model selection, pp. 80-99
  • BONEVA Lena, FAWCETT Nicholas, MASOLO Riccardo M., WALDRON Matt - Forecasting the UK economy: Alternative forecasting methodologies and the role of off-model information, pp. 100-120

Special Section: Supply chain forecasting; Guest Editors: Robert Fildes, John Boylan, Ram Ganeshan, Tonya Boone, Nada Sanders.

  • BOONE Tonya, BOYLAN John E., FILDES Robert, GANESHAN Ram, SANDERS Nada - Perspectives on supply chain forecasting, pp. 121-127
  • Contributing editors and referees for this Special Issue on Supply Chain Forecasting, p. 128
  • PHILLIPS Christina Jane, NIKOLOPOULOS Konstantinos - Forecast quality improvement with Action Research: A success story at PharmaCo, pp. 129-143
  • FILDES Robert, GOODWIN Paul, ÖNKAL Dilek - Use and misuse of information in supply chain forecasting of promotion effects, pp. 144-156
  • VILLEGAS Marco A., PEDREGAL Diego J. - Automatic selection of unobserved components models for supply chain forecasting, pp. 157-169
  • BOONE Tonya, GANESHAN Ram, JAIN Aditya, SANDERS Nada R. - Forecasting sales in the supply chain: Consumer analytics in the big data era, pp. 170-180
  • VAN DER AUWERAER Sarah, BOUTE Robert N., SYNTETOS Aris A. - Forecasting spare part demand with installed base information: A review, pp. 181-196
  • SCHAER Oliver, KOURENTZES Nikolaos, FILDES Robert - Demand forecasting with user-generated online information, pp. 197-212
  • YU Lean, ZHAO Yaqing, TANG Ling, YANG Zebin - Online big data-driven oil consumption forecasting with Google trends, pp. 213-223
  • PRAK Dennis, TEUNTER Ruud - A general method for addressing forecasting uncertainty in inventory models, pp. 224-238
  • TRAPERO Juan R., CARDÓS Manuel, KOURENTZES Nikolaos - Quantile forecast optimal combination to enhance safety stock estimation, pp. 239-250
  • PETROPOULOS Fotios, WANG Xun, DISNEY Stephen M. - The inventory performance of forecasting methods: Evidence from the M3 competition data, pp. 251-265

Special section: Prediction markets; Guest editors: Leighton Vaughan Williams, Johnnie E.V. Johnson, and Ming-Chien Sung.

  • WILLIAMS Leighton Vaughan, SUNG Ming-Chien, JOHNSON Johnnie - Prediction markets: Theory, evidence and applications, pp. 266-270
  • BERG Joyce E., RIETZ Thomas A. - Longshots, overconfidence and efficiency on the Iowa Electronic Market, pp. 271-287
  • BROWN Alasdair, YANG Fuyu - The wisdom of large and small crowds: Evidence from repeated natural experiments in sports bettin, pp. 288-296
  • TAI Chung-Ching, LIN Hung-Wen,CHIE Bin-Tzong, TUNG Chen-Yuan - Predicting the failures of prediction markets: A procedure of decision making using classification models, pp. 297-312
  • GRANT Andrew, JOHNSTONE David, KWON Oh Kang - The cost of capital in a prediction market, pp. 313-320
  • SPERB Luis Felipe Costa, SUNG Ming-Chien, JOHNSON Johnnie E.V., MA Tiejun - Keeping a weather eye on prediction markets: The influence of environmental conditions on forecasting accuracy, pp. 321-335
  • READE J. James, WILLIAMS Leighton Vaughan - Polls to probabilities: Comparing prediction markets and opinion polls, pp. 336-350
  • DI Chen, DIMITROV Stanko, HE Qi-Ming - Incentive compatibility in prediction markets: Costly actions and external incentives, pp. 351-370
  • AULD Tom, LINTON Oliver - The behaviour of betting and currency markets on the night of the EU referendum, pp. 371-389
  • LOHRMANN Christoph, LUUKKA Pasi - Classification of intraday S&P500 returns with a Random Forest, pp. 390-407
  • STRIJBIS Oliveris, ARNESEN Sveinung - Explaining variance in the accuracy of prediction markets, pp. 408-419
  • BROWN Alasdair, READE J. James, WILLIAMS Leighton Vaughan - When are prediction market prices most informative? pp. 420-428

 (résumés du n° 1/2019)

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