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Content
2021, Volume 37, Issue 1
- 360-377 Preventing rather than punishing: An early warning model of malfeasance in public procurement
by Gallego, Jorge & Rivero, Gonzalo & Martínez, Juan
- 378-387 Expert forecasting with and without uncertainty quantification and weighting: What do the data say?
by Cooke, Roger M. & Marti, Deniz & Mazzuchi, Thomas
- 388-427 Recurrent Neural Networks for Time Series Forecasting: Current status and future directions
by Hewamalage, Hansika & Bergmeir, Christoph & Bandara, Kasun
- 428-444 Forecasting recovery rates on non-performing loans with machine learning
by Bellotti, Anthony & Brigo, Damiano & Gambetti, Paolo & Vrins, Frédéric
2020, Volume 36, Issue 4
- 1193-1210 Probabilistic forecasting in day-ahead electricity markets: Simulating peak and off-peak prices
by Muniain, Peru & Ziel, Florian
- 1211-1227 Forecasting using heterogeneous panels with cross-sectional dependence
by Akgun, Oguzhan & Pirotte, Alain & Urga, Giovanni
- 1228-1240 On the statistical differences between binary forecasts and real-world payoffs
by Taleb, Nassim Nicholas
- 1241-1251 Agustín Maravall: An interview with the International Journal of Forecasting
by Peña, Daniel
- 1252-1259 Data revisions to German national accounts: Are initial releases good nowcasts?
by Strohsal, Till & Wolf, Elias
- 1260-1289 Statistical learning and exchange rate forecasting
by Colombo, Emilio & Pelagatti, Matteo
- 1290-1300 Investigating the inefficiency of the CBO’s budgetary projections
by Arai, Natsuki
- 1301-1317 Forecasting volatility with time-varying leverage and volatility of volatility effects
by Catania, Leopoldo & Proietti, Tommaso
- 1318-1328 Stochastic volatility models with ARMA innovations: An application to G7 inflation forecasts
by Zhang, Bo & Chan, Joshua C.C. & Cross, Jamie L.
- 1329-1341 Extension of the Elo rating system to margin of victory
by Kovalchik, Stephanie
- 1342-1361 Demand forecasting under fill rate constraints—The case of re-order points
by Bruzda, Joanna
- 1362-1379 Forecasting value at risk and expected shortfall with mixed data sampling
by Le, Trung H.
- 1380-1388 A strategic predictive distribution for tests of probabilistic calibration
by Taylor, James W.
- 1389-1406 Automatic Interpretable Retail forecasting with promotional scenarios
by Gür Ali, Özden & Gürlek, Ragıp
- 1407-1419 A two-stage model to forecast elections in new democracies
by Bunker, Kenneth
- 1420-1438 Daily retail demand forecasting using machine learning with emphasis on calendric special days
by Huber, Jakob & Stuckenschmidt, Heiner
- 1439-1453 Do macroeconomic forecasters use macroeconomics to forecast?
by Casey, Eddie
- 1454-1475 Forecasting global equity market volatilities
by Zhang, Yaojie & Ma, Feng & Liao, Yin
- 1478-1487 A textual analysis of Bank of England growth forecasts
by Jones, Jacob T. & Sinclair, Tara M. & Stekler, Herman O.
- 1488-1500 Forecasting and forecast narratives: The Bank of England Inflation Reports
by Clements, Michael P. & Reade, J. James
- 1501-1516 Forecasting with news sentiment: Evidence with UK newspapers
by Rambaccussing, Dooruj & Kwiatkowski, Andrzej
- 1517-1530 Linking words in economic discourse: Implications for macroeconomic forecasts
by Aromi, J. Daniel
- 1531-1540 GDP forecasts: Informational asymmetry of the SPF and FOMC minutes
by Bespalova, Olga
- 1541-1562 The role of text-extracted investor sentiment in Chinese stock price prediction with the enhancement of deep learning
by Li, Yelin & Bu, Hui & Li, Jiahong & Wu, Junjie
- 1563-1578 Incorporating textual information in customer churn prediction models based on a convolutional neural network
by De Caigny, Arno & Coussement, Kristof & De Bock, Koen W. & Lessmann, Stefan
2020, Volume 36, Issue 3
- 739-760 Forecasting third-party mobile payments with implications for customer flow prediction
by Ma, Shaohui & Fildes, Robert
- 761-780 Bias corrections for exponentially transformed forecasts: Are they worth the effort?
by Demetrescu, Matei & Golosnoy, Vasyl & Titova, Anna
- 781-799 Realized volatility forecast with the Bayesian random compressed multivariate HAR model
by Luo, Jiawen & Chen, Langnan
- 800-813 An information-theoretic approach for forecasting interval-valued SP500 daily returns
by Buansing, T.S. Tuang & Golan, Amos & Ullah, Aman
- 814-828 Forecasting the urban skyline with extreme value theory
by Auerbach, Jonathan & Wan, Phyllis
- 829-850 Predicting ordinary and severe recessions with a three-state Markov-switching dynamic factor model
by Carstensen, Kai & Heinrich, Markus & Reif, Magnus & Wolters, Maik H.
- 851-872 A three-frequency dynamic factor model for nowcasting Canadian provincial GDP growth
by Chernis, Tony & Cheung, Calista & Velasco, Gabriella
- 873-891 A Model Confidence Set approach to the combination of multivariate volatility forecasts
by Amendola, Alessandra & Braione, Manuela & Candila, Vincenzo & Storti, Giuseppe
- 892-898 Election forecasts: Cracking the Danish case
by Nadeau, Richard & Lewis-Beck, Michael S.
- 899-915 Macroeconomic forecasting with large Bayesian VARs: Global-local priors and the illusion of sparsity
by Cross, Jamie L. & Hou, Chenghan & Poon, Aubrey
- 916-932 A profitable model for predicting the over/under market in football
by Wheatcroft, Edward
- 933-948 Forecasting volatility and co-volatility of crude oil and gold futures: Effects of leverage, jumps, spillovers, and geopolitical risks
by Asai, Manabu & Gupta, Rangan & McAleer, Michael
- 949-962 Election forecasting: Too far out?
by Jennings, Will & Lewis-Beck, Michael & Wlezien, Christopher
- 963-973 Are GDP forecasts optimal? Evidence on European countries
by Giovannelli, Alessandro & Pericoli, Filippo Maria
- 974-986 Comparing the forecasting performances of linear models for electricity prices with high RES penetration
by Gianfreda, Angelica & Ravazzolo, Francesco & Rossini, Luca
- 987-1002 Measuring public opinion via digital footprints
by Cerina, Roberto & Duch, Raymond
- 1003-1022 Predicting LGD distributions with mixed continuous and discrete ordinal outcomes
by Hwang, Ruey-Ching & Chu, Chih-Kang & Yu, Kaizhi
- 1023-1038 Forecasting value at risk with intra-day return curves
by Rice, Gregory & Wirjanto, Tony & Zhao, Yuqian
- 1039-1056 Predicting default risk under asymmetric binary link functions
by Dendramis, Y. & Tzavalis, E. & Varthalitis, P. & Athanasiou, E.
- 1057-1072 Forecasting risk measures using intraday data in a generalized autoregressive score framework
by Lazar, Emese & Xue, Xiaohan
- 1073-1091 Bayesian loss given default estimation for European sovereign bonds
by Jobst, Rainer & Kellner, Ralf & Rösch, Daniel
- 1092-1113 Predicting bank insolvencies using machine learning techniques
by Petropoulos, Anastasios & Siakoulis, Vasilis & Stavroulakis, Evangelos & Vlachogiannakis, Nikolaos E.
- 1116-1127 Efficient big data model selection with applications to fraud detection
by Vaughan, Gregory
- 1128-1137 Brexit: Tracking and disentangling the sentiment towards leaving the EU
by de Carvalho, Miguel & Martos, Gabriel
- 1138-1148 Spatio-temporal modeling of yellow taxi demands in New York City using generalized STAR models
by Safikhani, Abolfazl & Kamga, Camille & Mudigonda, Sandeep & Faghih, Sabiheh Sadat & Moghimi, Bahman
- 1149-1162 Quantile forecasting with mixed-frequency data
by Lima, Luiz Renato & Meng, Fanning & Godeiro, Lucas
- 1163-1172 Can Google search data help predict macroeconomic series?
by Niesert, Robin F. & Oorschot, Jochem A. & Veldhuisen, Christian P. & Brons, Kester & Lange, Rutger-Jan
- 1173-1180 Nowcasting in real time using popularity priors
by Monokroussos, George & Zhao, Yongchen
- 1181-1191 DeepAR: Probabilistic forecasting with autoregressive recurrent networks
by Salinas, David & Flunkert, Valentin & Gasthaus, Jan & Januschowski, Tim
2020, Volume 36, Issue 2
- 232-247 Forecasting inflation with online prices
by Aparicio, Diego & Bertolotto, Manuel I.
- 248-266 Predicting loss given default in leasing: A closer look at models and variable selection
by Kaposty, Florian & Kriebel, Johannes & Löderbusch, Matthias
- 267-291 Macroeconomic forecasting using approximate factor models with outliers
by Chou, Ray Yeutien & Yen, Tso-Jung & Yen, Yu-Min
- 292-309 Forecasting bulk prices of Bordeaux wines using leading indicators
by Paroissien, Emmanuel
- 310-323 Probabilistic energy forecasting using the nearest neighbors quantile filter and quantile regression
by González Ordiano, Jorge Ángel & Gröll, Lutz & Mikut, Ralf & Hagenmeyer, Veit
- 324-333 Temperature anomaly detection for electric load forecasting
by Sobhani, Masoud & Hong, Tao & Martin, Claude
- 334-357 The impact of sentiment and attention measures on stock market volatility
by Audrino, Francesco & Sigrist, Fabio & Ballinari, Daniele
- 358-372 High-frequency credit spread information and macroeconomic forecast revision
by Deschamps, Bruno & Ioannidis, Christos & Ka, Kook
- 373-398 Combining survey long-run forecasts and nowcasts with BVAR forecasts using relative entropy
by Tallman, Ellis W. & Zaman, Saeed
- 399-413 Model-based pre-election polling for national and sub-national outcomes in the US and UK
by Lauderdale, Benjamin E. & Bailey, Delia & Blumenau, Jack & Rivers, Douglas
- 414-427 Forecasting election results by studying brand importance in online news
by Fronzetti Colladon, Andrea
- 428-441 Forecast combinations for value at risk and expected shortfall
by Taylor, James W.
- 442-465 Forecasting from others’ experience: Bayesian estimation of the generalized Bass model
by Ramírez-Hassan, Andrés & Montoya-Blandón, Santiago
- 466-479 Probabilistic electricity price forecasting with NARX networks: Combine point or probabilistic forecasts?
by Marcjasz, Grzegorz & Uniejewski, Bartosz & Weron, Rafał
- 480-488 Crime prediction by data-driven Green’s function method
by Kajita, Mami & Kajita, Seiji
- 489-506 Semi-parametric dynamic asymmetric Laplace models for tail risk forecasting, incorporating realized measures
by Gerlach, Richard & Wang, Chao
- 507-514 Improved recession dating using stock market volatility
by Huang, Yu-Fan & Startz, Richard
- 515-530 Probabilistic wind forecasting up to three months ahead using ensemble predictions for geopotential height
by Alonzo, Bastien & Tankov, Peter & Drobinski, Philippe & Plougonven, Riwal
- 531-551 Comparing density forecasts in a risk management context
by Diks, Cees & Fang, Hao
- 552-569 Probabilistic forecasting of heterogeneous consumer transaction–sales time series
by Berry, Lindsay R. & Helman, Paul & West, Mike
- 570-587 Oil price shocks and economic growth: The volatility link
by Maheu, John M. & Song, Yong & Yang, Qiao
- 588-606 An empirical investigation of water consumption forecasting methods
by Karamaziotis, Panagiotis I. & Raptis, Achilleas & Nikolopoulos, Konstantinos & Litsiou, Konstantia & Assimakopoulos, Vassilis
- 607-627 Five dimensions of the uncertainty–disagreement linkage
by Glas, Alexander
- 628-645 Trading and non-trading period realized market volatility: Does it matter for forecasting the volatility of US stocks?
by Lyócsa, Štefan & Todorova, Neda
- 646-665 A functional time series analysis of forward curves derived from commodity futures
by Horváth, Lajos & Liu, Zhenya & Rice, Gregory & Wang, Shixuan
- 666-683 Forecasting commodity prices out-of-sample: Can technical indicators help?
by Wang, Yudong & Liu, Li & Wu, Chongfeng
- 684-694 Forecasting stock price volatility: New evidence from the GARCH-MIDAS model
by Wang, Lu & Ma, Feng & Liu, Jing & Yang, Lin
- 695-712 Rethinking weather station selection for electric load forecasting using genetic algorithms
by Moreno-Carbonell, Santiago & Sánchez-Úbeda, Eugenio F. & Muñoz, Antonio
- 713-722 Are betting returns a useful measure of accuracy in (sports) forecasting?
by Wunderlich, Fabian & Memmert, Daniel
- 723-737 The term structure of volatility predictability
by Li, Xingyi & Zakamulin, Valeriy
2020, Volume 36, Issue 1
- 7-14 A brief history of forecasting competitions
by Hyndman, Rob J.
- 15-28 Forecasting in social settings: The state of the art
by Makridakis, Spyros & Hyndman, Rob J. & Petropoulos, Fotios
- 37-53 Are forecasting competitions data representative of the reality?
by Spiliotis, Evangelos & Kouloumos, Andreas & Assimakopoulos, Vassilios & Makridakis, Spyros
- 54-74 The M4 Competition: 100,000 time series and 61 forecasting methods
by Makridakis, Spyros & Spiliotis, Evangelos & Assimakopoulos, Vassilios
- 75-85 A hybrid method of exponential smoothing and recurrent neural networks for time series forecasting
by Smyl, Slawek
- 86-92 FFORMA: Feature-based forecast model averaging
by Montero-Manso, Pablo & Athanasopoulos, George & Hyndman, Rob J. & Talagala, Thiyanga S.
- 93-97 Weighted ensemble of statistical models
by Pawlikowski, Maciej & Chorowska, Agata
- 98-104 A combination-based forecasting method for the M4-competition
by Jaganathan, Srihari & Prakash, P.K.S.
- 105-109 GROEC: Combination method via Generalized Rolling Origin Evaluation
by Fiorucci, Jose Augusto & Louzada, Francisco
- 110-115 A simple combination of univariate models
by Petropoulos, Fotios & Svetunkov, Ivan
- 116-120 Fast and accurate yearly time series forecasting with forecast combinations
by Shaub, David
- 121-128 Correlated daily time series and forecasting in the M4 competition
by Ingel, Anti & Shahroudi, Novin & Kängsepp, Markus & Tättar, Andre & Komisarenko, Viacheslav & Kull, Meelis
- 129-134 Card forecasts for M4
by Doornik, Jurgen A. & Castle, Jennifer L. & Hendry, David F.
- 135-141 Forecasting the M4 competition weekly data: Forecast Pro’s winning approach
by Darin, Sarah Goodrich & Stellwagen, Eric
2019, Volume 35, Issue 4
- 1193-1210 Forecasting returns in the VIX futures market
by Taylor, Nick
- 1211-1225 A SHARP model of bid–ask spread forecasts
by Cattivelli, Luca & Pirino, Davide
- 1226-1239 A comprehensive evaluation of macroeconomic forecasting methods
by Carriero, Andrea & Galvão, Ana Beatriz & Kapetanios, George
- 1240-1249 Do forecasters target first or later releases of national accounts data?
by Clements, Michael P.
- 1250-1262 Forecasting and trading on the VIX futures market: A neural network approach based on open to close returns and coincident indicators
by Ballestra, Luca Vincenzo & Guizzardi, Andrea & Palladini, Fabio
- 1263-1272 Monthly forecasting of GDP with mixed-frequency multivariate singular spectrum analysis
by Hassani, Hossein & Rua, António & Silva, Emmanuel Sirimal & Thomakos, Dimitrios
- 1273-1287 Ordinal-response GARCH models for transaction data: A forecasting exercise
by Dimitrakopoulos, Stefanos & Tsionas, Mike
- 1288-1303 A hybrid machine learning model for forecasting a billing period’s peak electric load days
by Saxena, Harshit & Aponte, Omar & McConky, Katie T.
- 1304-1317 Forecasting of density functions with an application to cross-sectional and intraday returns
by Kokoszka, Piotr & Miao, Hong & Petersen, Alexander & Shang, Han Lin
- 1318-1331 A novel cluster HAR-type model for forecasting realized volatility
by Yao, Xingzhi & Izzeldin, Marwan & Li, Zhenxiong
- 1332-1355 Heterogeneous component multiplicative error models for forecasting trading volumes
by Naimoli, Antonio & Storti, Giuseppe
- 1356-1369 Adaptive learning forecasting, with applications in forecasting agricultural prices
by Kyriazi, Foteini & Thomakos, Dimitrios D. & Guerard, John B.
- 1370-1386 Questioning the news about economic growth: Sparse forecasting using thousands of news-based sentiment values
by Ardia, David & Bluteau, Keven & Boudt, Kris
- 1389-1399 Global energy forecasting competition 2017: Hierarchical probabilistic load forecasting
by Hong, Tao & Xie, Jingrui & Black, Jonathan
- 1400-1408 Quantile regression for the qualifying match of GEFCom2017 probabilistic load forecasting
by Ziel, Florian
- 1409-1423 Neural networks for GEFCom2017 probabilistic load forecasting
by Dimoulkas, I. & Mazidi, P. & Herre, L.
- 1424-1431 Machine learning methods for GEFCom2017 probabilistic load forecasting
by Smyl, Slawek & Hua, N. Grace
- 1432-1438 An ensemble approach to GEFCom2017 probabilistic load forecasting
by Landgraf, Andrew J.
- 1439-1450 Reconciled boosted models for GEFCom2017 hierarchical probabilistic load forecasting
by Roach, Cameron
- 1451-1459 Data visualization and forecast combination for probabilistic load forecasting in GEFCom2017 final match
by de Hoog, Julian & Abdulla, Khalid
- 1460-1468 Data preprocessing and quantile regression for probabilistic load forecasting in the GEFCom2017 final match
by Kanda, Isao & Veguillas, J.M. Quintana
- 1469-1484 Short term load forecasting and the effect of temperature at the low voltage level
by Haben, Stephen & Giasemidis, Georgios & Ziel, Florian & Arora, Siddharth
- 1485-1498 Online adaptive lasso estimation in vector autoregressive models for high dimensional wind power forecasting
by Messner, Jakob W. & Pinson, Pierre
- 1499-1519 Operational solar forecasting for the real-time market
by Yang, Dazhi & Wu, Elynn & Kleissl, Jan
- 1520-1532 On the importance of the long-term seasonal component in day-ahead electricity price forecasting with NARX neural networks
by Marcjasz, Grzegorz & Uniejewski, Bartosz & Weron, Rafał
- 1533-1547 Understanding intraday electricity markets: Variable selection and very short-term price forecasting using LASSO
by Uniejewski, Bartosz & Marcjasz, Grzegorz & Weron, Rafał
- 1548-1560 Text-based crude oil price forecasting: A deep learning approach
by Li, Xuerong & Shang, Wei & Wang, Shouyang
- 1564-1582 Gauging the uncertainty of the economic outlook using historical forecasting errors: The Federal Reserve’s approach
by Reifschneider, David & Tulip, Peter
- 1583-1595 Fiscal Surprises at the FOMC
by Croushore, Dean & van Norden, Simon
- 1596-1612 A new approach for detecting shifts in forecast accuracy
by Chiu, Ching-Wai (Jeremy) & Hayes, Simon & Kapetanios, George & Theodoridis, Konstantinos
- 1613-1626 Asymmetry in unemployment rate forecast errors
by Galbraith, John W. & van Norden, Simon
- 1627-1635 Evaluating the conditionality of judgmental forecasts
by Berge, Travis J. & Chang, Andrew C. & Sinha, Nitish R.
- 1636-1657 Predicting relative forecasting performance: An empirical investigation
by Granziera, Eleonora & Sekhposyan, Tatevik
- 1658-1668 Mind the gap: A multi-country BVAR benchmark for the Eurosystem projections
by Angelini, Elena & Lalik, Magdalena & Lenza, Michele & Paredes, Joan
- 1669-1678 Forecasting the UK economy with a medium-scale Bayesian VAR
by Domit, Sílvia & Monti, Francesca & Sokol, Andrej
- 1679-1691 Machine learning for regularized survey forecast combination: Partially-egalitarian LASSO and its derivatives
by Diebold, Francis X. & Shin, Minchul
- 1692-1707 Forecasting economic activity with mixed frequency BVARs
by Brave, Scott A. & Butters, R. Andrew & Justiniano, Alejandro
- 1708-1724 Financial nowcasts and their usefulness in macroeconomic forecasting
by Knotek, Edward S. & Zaman, Saeed
- 1725-1734 Macroeconomic news and market reaction: Surprise indexes meet nowcasting
by Caruso, Alberto
- 1735-1747 Forecasting economic time series using score-driven dynamic models with mixed-data sampling
by Gorgi, Paolo & Koopman, Siem Jan & Li, Mengheng
- 1748-1769 Assessing the uncertainty in central banks’ inflation outlooks
by Knüppel, Malte & Schultefrankenfeld, Guido
- 1770-1789 DSGE forecasts of the lost recovery
by Cai, Michael & Del Negro, Marco & Giannoni, Marc P. & Gupta, Abhi & Li, Pearl & Moszkowski, Erica
- 1790-1799 Residential investment and recession predictability
by Aastveit, Knut Are & Anundsen, André K. & Herstad, Eyo I.
- 1800-1813 Implied volatility term structure and exchange rate predictability
by Ornelas, José Renato Haas & Mauad, Roberto Baltieri
- 1814-1828 Forecasting GDP growth with NIPA aggregates: In search of core GDP
by Garciga, Christian & Knotek II, Edward S.
2019, Volume 35, Issue 3
- 823-835 Forecasting dynamic return distributions based on ordered binary choice
by Anatolyev, Stanislav & Baruník, Jozef
- 836-847 Forecasting Bitcoin risk measures: A robust approach
by Trucíos, Carlos
- 848-867 Recession forecasting using Bayesian classification
by Davig, Troy & Hall, Aaron Smalter
- 868-877 Accuracy of German federal election forecasts, 2013 & 2017
by Graefe, Andreas
- 878-890 Unrestricted and controlled identification of loss functions: Possibility and impossibility results
by Lieli, Robert P. & Stinchcombe, Maxwell B. & Grolmusz, Viola M.
- 891-909 Semiparametric quantile averaging in the presence of high-dimensional predictors
by De Gooijer, Jan G. & Zerom, Dawit
- 910-926 Robust optimization of forecast combinations
by Post, Thierry & Karabatı, Selçuk & Arvanitis, Stelios
- 929-947 International propagation of shocks: A dynamic factor model using survey forecasts
by Lahiri, Kajal & Zhao, Yongchen
- 948-966 Growth in stress
by González-Rivera, Gloria & Maldonado, Javier & Ruiz, Esther
- 967-979 The measurement and transmission of macroeconomic uncertainty: Evidence from the U.S. and BRIC countries
by Liu, Yang & Sheng, Xuguang Simon
- 980-993 Inflation expectations in India: Learning from household tendency surveys
by Das, Abhiman & Lahiri, Kajal & Zhao, Yongchen
- 994-1007 Quasi ex-ante inflation forecast uncertainty
by Charemza, Wojciech & Díaz, Carlos & Makarova, Svetlana
- 1008-1031 New perspectives on forecasting inflation in emerging market economies: An empirical assessment
by Duncan, Roberto & Martínez-García, Enrique
- 1042-1059 Bagged neural networks for forecasting Polish (low) inflation
by Szafranek, Karol
- 1060-1071 Forecasting inflation in Latin America with core measures
by Pincheira-Brown, Pablo & Selaive, Jorge & Nolazco, Jose Luis
- 1072-1084 The trilemma between accuracy, timeliness and smoothness in real-time signal extraction
by Wildi, Marc & McElroy, Tucker S.
- 1085-1099 Medium term growth forecasts: Experts vs. simple models
by Aromí, J. Daniel
- 1100-1107 Anomalies in macroeconomic prediction errors–evidence from Chilean private forecasters
by Pedersen, Michael
- 1108-1117 Characteristics and implications of Chinese macroeconomic data revisions
by Sinclair, Tara M.
- 1118-1130 Can media and text analytics provide insights into labour market conditions in China?
by Bailliu, Jeannine & Han, Xinfen & Kruger, Mark & Liu, Yu-Hsien & Thanabalasingam, Sri
- 1131-1142 Do IMF forecasts respect Okun’s law? Evidence for advanced and developing economies
by An, Zidong & Ball, Laurence & Jalles, Joao & Loungani, Prakash
- 1143-1159 Forecasts in times of crises
by Eicher, Theo S. & Kuenzel, David J. & Papageorgiou, Chris & Christofides, Charis
- 1160-1174 Financial information and macroeconomic forecasts
by Chen, Sophia & Ranciere, Romain
- 1175-1185 Assessing the accuracy of electricity production forecasts in developing countries
by Steinbuks, Jevgenijs
- 1186-1192 Some observations on forecasting and policy
by Wright, Jonathan H.
2019, Volume 35, Issue 2
- 429-442 Forecasting the exchange rate using nonlinear Taylor rule based models
by Wang, Rudan & Morley, Bruce & Stamatogiannis, Michalis P.
- 443-457 Forecasting U.S. money growth using economic uncertainty measures and regularisation techniques
by Tarassow, Artur
- 458-473 Threshold cointegration in international exchange rates:A Bayesian approach
by Huber, Florian & Zörner, Thomas O.
- 474-484 Combining forecasts: Performance and coherence
by Thomson, Mary E. & Pollock, Andrew C. & Önkal, Dilek & Gönül, M. Sinan
- 485-501 Forecasting cryptocurrencies under model and parameter instability
by Catania, Leopoldo & Grassi, Stefano & Ravazzolo, Francesco
- 502-520 Long-term forecasting of fuel demand at theater entry points
by Lobo, Benjamin J. & Brown, Donald E. & Grazaitis, Peter J.
- 521-539 Approximate Bayesian forecasting
by Frazier, David T. & Maneesoonthorn, Worapree & Martin, Gael M. & McCabe, Brendan P.M.
- 540-554 Testing out-of-sample portfolio performance
by Kazak, Ekaterina & Pohlmeier, Winfried
- 555-572 Nowcasting and forecasting GDP in emerging markets using global financial and macroeconomic diffusion indexes
by Cepni, Oguzhan & Güney, I. Ethem & Swanson, Norman R.
- 573-579 Interpreting the skill score form of forecast performance metrics
by Wheatcroft, Edward
- 580-600 Euro area real-time density forecasting with financial or labor market frictions
by McAdam, Peter & Warne, Anders
- 601-615 Combining wavelet decomposition with machine learning to forecast gold returns
by Risse, Marian
- 616-633 Macroeconomic forecasting for Australia using a large number of predictors
by Panagiotelis, Anastasios & Athanasopoulos, George & Hyndman, Rob J. & Jiang, Bin & Vahid, Farshid
- 634-640 A generalized non-linear forecasting model for limited overs international cricket
by Asif, M. & McHale, I.G.
- 644-658 Forecasting unknown-unknowns by boosting the risk radar within the risk intelligent organisation
by Marshall, Alasdair & Ojiako, Udechukwu & Wang, Victoria & Lin, Fenfang & Chipulu, Maxwell
- 659-666 Forecasting, uncertainty and risk; perspectives on clinical decision-making in preventive and curative medicine
by Makridakis, Spyros & Kirkham, Richard & Wakefield, Ann & Papadaki, Maria & Kirkham, Joanne & Long, Lisa
- 667-676 Systemic risk in major public contracts
by Bloomfield, Katherine & Williams, Terry & Bovis, Chris & Merali, Yasmin
- 677-686 How much data do you need? An operational, pre-asymptotic metric for fat-tailedness
by Taleb, Nassim Nicholas
- 687-698 Tales from tails: On the empirical distributions of forecasting errors and their implication to risk
by Spiliotis, Evangelos & Nikolopoulos, Konstantinos & Assimakopoulos, Vassilios
- 699-709 Intraday portfolio risk management using VaR and CVaR:A CGARCH-EVT-Copula approach
by Karmakar, Madhusudan & Paul, Samit
- 712-721 Efficiency of online football betting markets
by Angelini, Giovanni & De Angelis, Luca
- 722-732 Bayesian forecasting of UEFA Champions League under alternative seeding regimes
by Corona, Francisco & Forrest, David & Tena, J.D. & Wiper, Michael
- 733-740 Paired comparison models with age effects modeled as piecewise quadratic splines
by Araki, Kenji & Hirose, Yoshihiro & Komaki, Fumiyasu
- 741-755 Predictive analysis and modelling football results using machine learning approach for English Premier League
by Baboota, Rahul & Kaur, Harleen
- 756-766 A calibration method with dynamic updates for within-match forecasting of wins in tennis
by Kovalchik, Stephanie & Reid, Machar
- 767-775 Optimizing the allocation of funds of an NFL team under the salary cap
by Mulholland, Jason & Jensen, Shane T.
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