International Journal of Forecasting
2017, Volume 33, Issue 2
- 337-344 A vector heterogeneous autoregressive index model for realized volatility measures
by Cubadda, Gianluca & Guardabascio, Barbara & Hecq, Alain
- 345-358 Visualising forecasting algorithm performance using time series instance spaces
by Kang, Yanfei & Hyndman, Rob J. & Smith-Miles, Kate
- 359-372 Evaluating multi-step system forecasts with relatively few forecast-error observations
by Hendry, David F. & Martinez, Andrew B.
- 373-389 Does realized volatility help bond yield density prediction?
by Shin, Minchul & Zhong, Molin
- 390-402 Now-casting the Japanese economy
by Bragoli, Daniela
- 403-415 Empowering cash managers to achieve cost savings by improving predictive accuracy
by Salas-Molina, Francisco & Martin, Francisco J. & Rodríguez-Aguilar, Juan A. & Serrà, Joan & Arcos, Josep Ll.
- 416-432 Density forecast evaluation in unstable environments
by González-Rivera, Gloria & Sun, Yingying
- 433-441 Structural forecasts for marketing data
by Allenby, Greg M.
- 442-457 Forecasting inflation: Phillips curve effects on services price measures
by Tallman, Ellis W. & Zaman, Saeed
- 458-466 A bivariate Weibull count model for forecasting association football scores
by Boshnakov, Georgi & Kharrat, Tarak & McHale, Ian G.
- 467-481 Forecasting elections at the constituency level: A correction–combination procedure
by Munzert, Simon
- 482-501 Adaptive models and heavy tails with an application to inflation forecasting
by Delle Monache, Davide & Petrella, Ivan
- 502-512 Forecasting compositional time series: A state space approach
by Snyder, Ralph D. & Ord, J. Keith & Koehler, Anne B. & McLaren, Keith R. & Beaumont, Adrian N.
- 513-522 Forecasting loss given default of bank loans with multi-stage model
by Tanoue, Yuta & Kawada, Akihiro & Yamashita, Satoshi
- 523-542 Economic forecasting in theory and practice: An interview with David F. Hendry
by Ericsson, Neil R.
- 543-559 How biased are U.S. government forecasts of the federal debt?
by Ericsson, Neil R.
- 560-562 Comment on “How Biased are US Government Forecasts of the Federal Debt?”
by Gamber, Edward N. & Liebner, Jeffrey P.
- 563-568 Interpreting estimates of forecast bias
by Ericsson, Neil R.
2017, Volume 33, Issue 1
- 1-10 Monte Carlo forecast evaluation with persistent data
by Khalaf, Lynda & Saunders, Charles J.
- 11-20 Quantile regression forecasts of inflation under model uncertainty
by Korobilis, Dimitris
- 21-47 A comparison of wavelet networks and genetic programming in the context of temperature derivatives
by Alexandridis, Antonis K. & Kampouridis, Michael & Cramer, Sam
- 48-60 Model Confidence Sets and forecast combination
by Samuels, Jon D. & Sekkel, Rodrigo M.
- 61-75 A mixed frequency approach to the forecasting of private consumption with ATM/POS data
by Duarte, Cláudia & Rodrigues, Paulo M.M. & Rua, António
- 76-89 A comparative assessment of alternative ex ante measures of inflation uncertainty
by Hartmann, Matthias & Herwartz, Helmut & Ulm, Maren
- 90-101 Modeling intra-seasonal heterogeneity in hourly advertising-response models: Do forecasts improve?
by Kiygi-Calli, Meltem & Weverbergh, Marcel & Franses, Philip Hans
- 102-120 Forecasting market returns: bagging or combining?
by Jordan, Steven J. & Vivian, Andrew & Wohar, Mark E.
- 121-131 Forecasting the Brazilian yield curve using forward-looking variables
by Vieira, Fausto & Fernandes, Marcelo & Chague, Fernando
- 132-152 Realized volatility forecasting of agricultural commodity futures using the HAR model with time-varying sparsity
by Tian, Fengping & Yang, Ke & Chen, Langnan
- 153-173 Forecasting GDP with global components: This time is different
by Bjørnland, Hilde C. & Ravazzolo, Francesco & Thorsrud, Leif Anders
- 174-184 Identifying business cycle turning points in real time with vector quantization
by Giusto, Andrea & Piger, Jeremy
- 185-198 Real-time nowcasting the US output gap: Singular spectrum analysis at work
by de Carvalho, Miguel & Rua, António
- 199-213 Forecasting stochastic processes using singular spectrum analysis: Aspects of the theory and application
by Khan, M. Atikur Rahman & Poskitt, D.S.
- 214-229 EXSSA: SSA-based reconstruction of time series via exponential smoothing of covariance eigenvalues
by Papailias, Fotis & Thomakos, Dimitrios
- 230-243 Use of expert knowledge to anticipate the future: Issues, analysis and directions
by Bolger, Fergus & Wright, George
- 244-253 Quantifiying blind spots and weak signals in executive judgment: A structured integration of expert judgment into the scenario development process
by Meissner, Philip & Brands, Christian & Wulf, Torsten
- 254-266 Augmenting the intuitive logics scenario planning method for a more comprehensive analysis of causation
by Derbyshire, James & Wright, George
- 267-279 I nvestigate D iscuss E stimate A ggregate for structured expert judgement
by Hanea, A.M. & McBride, M.F. & Burgman, M.A. & Wintle, B.C. & Fidler, F. & Flander, L. & Twardy, C.R. & Manning, B. & Mascaro, S.
- 280-297 Evaluating expert advice in forecasting: Users’ reactions to presumed vs. experienced credibility
by Önkal, Dilek & Sinan Gönül, M. & Goodwin, Paul & Thomson, Mary & Öz, Esra
- 298-313 Expertise, credibility of system forecasts and integration methods in judgmental demand forecasting
by Alvarado-Valencia, Jorge & Barrero, Lope H. & Önkal, Dilek & Dennerlein, Jack T.
- 314-324 Using a rolling training approach to improve judgmental extrapolations elicited from forecasters with technical knowledge
by Petropoulos, Fotios & Goodwin, Paul & Fildes, Robert
- 325-336 An investigation of dependence in expert judgement studies with multiple experts
by Wilson, Kevin J.
2016, Volume 32, Issue 4
- 1103-1119 A comparison of AdaBoost algorithms for time series forecast combination
by Barrow, Devon K. & Crone, Sven F.
- 1120-1137 Cross-validation aggregation for combining autoregressive neural network forecasts
by Barrow, Devon K. & Crone, Sven F.
- 1138-1150 What predicts US recessions?
by Liu, Weiling & Moench, Emanuel
- 1151-1161 Models for optimising the theta method and their relationship to state space models
by Fiorucci, Jose A. & Pellegrini, Tiago R. & Louzada, Francisco & Petropoulos, Fotios & Koehler, Anne B.
- 1162-1177 Testing for predictability in panels of any time series dimension
by Westerlund, Joakim & Narayan, Paresh
- 1178-1192 Does disagreement among oil price forecasters reflect volatility? Evidence from the ECB surveys
by Atalla, Tarek & Joutz, Fred & Pierru, Axel
- 1193-1207 Equity premium prediction: Are economic and technical indicators unstable?
by Baetje, Fabian & Menkhoff, Lukas
- 1208-1211 The forecastability quotient reconsidered
by Gardner, Everette Shaw & Acar, Yavuz
- 1212-1233 Investor attention to rounding as a salient forecast feature
by Athanasakou, Vasiliki & Simpson, Ana
- 1234-1246 Testing the historic tracking of climate models
by Beenstock, Michael & Reingewertz, Yaniv & Paldor, Nathan
- 1247-1255 A simple model for now-casting volatility series
by Breitung, Jörg & Hafner, Christian M.
- 1256-1267 Forecasting using sparse cointegration
by Wilms, Ines & Croux, Christophe
- 1268-1283 Modelling and trading the U.S. implied volatility indices. Evidence from the VIX, VXN and VXD indices
by Psaradellis, Ioannis & Sermpinis, Georgios
- 1284-1305 Forecasting and nowcasting economic growth in the euro area using factor models
by Hindrayanto, Irma & Koopman, Siem Jan & de Winter, Jasper
- 1306-1316 Modeling the impact of forecast-based regime switches on US inflation
by Bel, Koen & Paap, Richard
- 1317-1339 Global equity market volatility spillovers: A broader role for the United States
by Buncic, Daniel & Gisler, Katja I.M.
- 1340-1351 Constrained functional time series: Applications to the Italian gas market
by Canale, Antonio & Vantini, Simone
- 1352-1368 The role of spatial and temporal structure for residential rent predictions
by Füss, Roland & Koller, Jan A.
- 1369-1384 Nowcasting Turkish GDP and news decomposition
by Modugno, Michele & Soybilgen, Barış & Yazgan, Ege
- 1385-1402 Variational Bayes for assessment of dynamic quantile forecasts
by Gerlach, Richard & Abeywardana, Sachin
2016, Volume 32, Issue 3
- 585-597 Electric load forecasting with recency effect: A big data approach
by Wang, Pu & Liu, Bidong & Hong, Tao
- 598-613 The relationship between model complexity and forecasting performance for computer intelligence optimization in finance
by Ghandar, Adam & Michalewicz, Zbigniew & Zurbruegg, Ralf
- 614-628 Long-run restrictions and survey forecasts of output, consumption and investment
by Clements, Michael P.
- 629-649 A multilevel functional data method for forecasting population, with an application to the United Kingdom
by Shang, Han Lin & Smith, Peter W.F. & Bijak, Jakub & Wiśniowski, Arkadiusz
- 650-668 Getting the most out of macroeconomic information for predicting excess stock returns
by Çakmaklı, Cem & van Dijk, Dick
- 669-679 A new metric of absolute percentage error for intermittent demand forecasts
by Kim, Sungil & Kim, Heeyoung
- 680-694 Aggregate versus disaggregate information in dynamic factor models
by Alvarez, Rocio & Camacho, Maximo & Perez-Quiros, Gabriel
- 695-715 Combining nearest neighbor predictions and model-based predictions of realized variance: Does it pay?
by Andrada-Félix, Julián & Fernández-Rodríguez, Fernando & Fuertes, Ana-Maria
- 716-725 Time varying biases and the state of the economy
by Xie, Zixiong & Hsu, Shih-Hsun
- 726-735 Household forecasting: Preservation of age patterns
by Keilman, Nico
- 736-753 Nonlinear forecasting with many predictors using kernel ridge regression
by Exterkate, Peter & Groenen, Patrick J.F. & Heij, Christiaan & van Dijk, Dick
- 754-762 The forecast combination puzzle: A simple theoretical explanation
by Claeskens, Gerda & Magnus, Jan R. & Vasnev, Andrey L. & Wang, Wendun
- 763-787 Bayesian model averaging and principal component regression forecasts in a data rich environment
by Ouysse, Rachida
- 788-803 Evaluating predictive count data distributions in retail sales forecasting
by Kolassa, Stephan
- 804-817 Central banks’ forecasts and their bias: Evidence, effects and explanation
by Charemza, Wojciech & Ladley, Daniel
- 818-837 Density forecasting using Bayesian global vector autoregressions with stochastic volatility
by Huber, Florian
- 838-848 Forecasting food prices: The case of corn, soybeans and wheat
by Ahumada, H. & Cornejo, M.
- 849-864 Uncertainty in forecasting inflation and monetary policy design: Evidence from the laboratory
by Pfajfar, Damjan & Žakelj, Blaž
- 865-874 Modeling and forecasting call center arrivals: A literature survey and a case study
by Ibrahim, Rouba & Ye, Han & L’Ecuyer, Pierre & Shen, Haipeng
- 875-887 In-sample confidence bands and out-of-sample forecast bands for time-varying parameters in observation-driven models
by Blasques, Francisco & Koopman, Siem Jan & Łasak, Katarzyna & Lucas, André
- 896-913 Probabilistic energy forecasting: Global Energy Forecasting Competition 2014 and beyond
by Hong, Tao & Pinson, Pierre & Fan, Shu & Zareipour, Hamidreza & Troccoli, Alberto & Hyndman, Rob J.
- 914-938 Probabilistic electric load forecasting: A tutorial review
by Hong, Tao & Fan, Shu
- 939-947 A prediction interval for a function-valued forecast model: Application to load forecasting
by Antoniadis, Anestis & Brossat, Xavier & Cugliari, Jairo & Poggi, Jean-Michel
- 948-956 Probabilistic anomaly detection in natural gas time series data
by Akouemo, Hermine N. & Povinelli, Richard J.
- 957-965 Probabilistic forecasting of electricity spot prices using Factor Quantile Regression Averaging
by Maciejowska, Katarzyna & Nowotarski, Jakub & Weron, Rafał
- 966-980 Probabilistic forecasting of hourly electricity prices in the medium-term using spatial interpolation techniques
by Bello, Antonio & Reneses, Javier & Muñoz, Antonio & Delgadillo, Andrés
- 981-990 Short-term probabilistic forecasting of wind speed using stochastic differential equations
by Iversen, Emil B. & Morales, Juan M. & Møller, Jan K. & Madsen, Henrik
- 991-1004 Short-term density forecasting of wave energy using ARMA-GARCH models and kernel density estimation
by Jeon, Jooyoung & Taylor, James W.
- 1005-1011 GEFCom2014 probabilistic electric load forecasting using time series and semi-parametric regression models
by Dordonnat, V. & Pichavant, A. & Pierrot, A.
- 1012-1016 GEFCom2014 probabilistic electric load forecasting: An integrated solution with forecast combination and residual simulation
by Xie, Jingrui & Hong, Tao
- 1017-1022 A hybrid model of kernel density estimation and quantile regression for GEFCom2014 probabilistic load forecasting
by Haben, Stephen & Giasemidis, Georgios
- 1023-1028 Sequence of nonparametric models for GEFCom2014 probabilistic electric load forecasting
by Mangalova, Ekaterina & Shesterneva, Olesya
- 1029-1037 Lasso estimation for GEFCom2014 probabilistic electric load forecasting
by Ziel, Florian & Liu, Bidong
- 1038-1050 Additive models and robust aggregation for GEFCom2014 probabilistic electric load and electricity price forecasting
by Gaillard, Pierre & Goude, Yannig & Nedellec, Raphaël
- 1051-1056 A hybrid model for GEFCom2014 probabilistic electricity price forecasting
by Maciejowska, Katarzyna & Nowotarski, Jakub
- 1057-1060 Multilayer perceptron for GEFCom2014 probabilistic electricity price forecasting
by Dudek, Grzegorz
- 1061-1066 Probabilistic gradient boosting machines for GEFCom2014 wind forecasting
by Landry, Mark & Erlinger, Thomas P. & Patschke, David & Varrichio, Craig
- 1067-1073 K-nearest neighbors for GEFCom2014 probabilistic wind power forecasting
by Mangalova, Ekaterina & Shesterneva, Olesya
- 1074-1080 K-nearest neighbors and a kernel density estimator for GEFCom2014 probabilistic wind power forecasting
by Zhang, Yao & Wang, Jianxue
- 1081-1086 A semi-empirical approach using gradient boosting and k-nearest neighbors regression for GEFCom2014 probabilistic solar power forecasting
by Huang, Jing & Perry, Matthew
- 1087-1093 GEFCom2014: Probabilistic solar and wind power forecasting using a generalized additive tree ensemble approach
by Nagy, Gábor I. & Barta, Gergő & Kazi, Sándor & Borbély, Gyula & Simon, Gábor
- 1094-1102 A multiple quantile regression approach to the wind, solar, and price tracks of GEFCom2014
by Juban, Romain & Ohlsson, Henrik & Maasoumy, Mehdi & Poirier, Louis & Kolter, J. Zico
2016, Volume 32, Issue 2
- 233-242 Assessing macroeconomic forecasts for Japan under an asymmetric loss function
by Tsuchiya, Yoichi
- 243-256 Forecasting sales of new and existing products using consumer reviews: A random projections approach
by Schneider, Matthew J. & Gupta, Sachin
- 257-270 A comparison of MIDAS and bridge equations
by Schumacher, Christian
- 271-282 Using time-stamped survey responses to measure expectations at a daily frequency
by Mokinski, Frieder
- 283-292 Identification and real-time forecasting of Norwegian business cycles
by Aastveit, Knut Are & Jore, Anne Sofie & Ravazzolo, Francesco
- 293-302 Score-driven exponentially weighted moving averages and Value-at-Risk forecasting
by Lucas, André & Zhang, Xin
- 303-312 Bagging exponential smoothing methods using STL decomposition and Box–Cox transformation
by Bergmeir, Christoph & Hyndman, Rob J. & Benítez, José M.
- 313-323 Revisiting the relative forecast performances of Fed staff and private forecasters: A dynamic approach
by El-Shagi, Makram & Giesen, Sebastian & Jung, Alexander
- 324-343 A dynamic factor model of the yield curve components as a predictor of the economy
by Chauvet, Marcelle & Senyuz, Zeynep
- 344-357 Forecasting branded and generic pharmaceuticals
by Nikolopoulos, Konstantinos & Buxton, Samantha & Khammash, Marwan & Stern, Philip
- 358-373 Improving the reliability of real-time output gap estimates using survey forecasts
by Galimberti, Jaqueson K. & Moura, Marcelo L.
- 374-390 Forecasting global recessions in a GVAR model of actual and expected output
by Garratt, Anthony & Lee, Kevin & Shields, Kalvinder
- 391-397 A note on the estimation of optimal weights for density forecast combinations
by Pauwels, Laurent L. & Vasnev, Andrey L.
- 398-410 Low and high prices can improve volatility forecasts during periods of turmoil
by Fiszeder, Piotr & Perczak, Grzegorz
- 411-436 Forecasting and nowcasting real GDP: Comparing statistical models and subjective forecasts
by Jansen, W. Jos & Jin, Xiaowen & de Winter, Jasper M.
- 437-457 Volatility and quantile forecasts by realized stochastic volatility models with generalized hyperbolic distribution
by Takahashi, Makoto & Watanabe, Toshiaki & Omori, Yasuhiro
- 458-474 Finite sample weighting of recursive forecast errors
by Brooks, Chris & Burke, Simon P. & Stanescu, Silvia
- 475-501 Frontiers in VaR forecasting and backtesting
by Nieto, Maria Rosa & Ruiz, Esther
- 502-517 Multi-period-ahead forecasting with residual extrapolation and information sharing — Utilizing a multitude of retail series
by Gur Ali, Ozden & Pinar, Efe
- 518-526 Do asset price drops foreshadow recessions?
by Bluedorn, John C. & Decressin, Jörg & Terrones, Marco E.
- 527-547 On the predictability of model-free implied correlation
by Markopoulou, Chryssa & Skintzi, Vasiliki & Refenes, Apostolos
- 548-558 Betas and the myth of market neutrality
by Papageorgiou, Nicolas & Reeves, Jonathan J. & Xie, Xuan
- 559-570 Evaluating qualitative forecasts: The FOMC minutes, 2006–2010
by Stekler, Herman & Symington, Hilary
- 571-583 Eliciting GDP forecasts from the FOMC’s minutes around the financial crisis
by Ericsson, Neil R.
2016, Volume 32, Issue 1
- 1-9 Forecasting crude oil market volatility: A Markov switching multifractal volatility approach
by Wang, Yudong & Wu, Chongfeng & Yang, Li
- 10-19 Predicting Finnish economic activity using firm-level data
by Fornaro, Paolo
- 20-22 A note on the Mean Absolute Scaled Error
by Franses, Philip Hans
- 23-33 Herding behavior of business cycle forecasters
by Rülke, Jan-Christoph & Silgoner, Maria & Wörz, Julia
- 34-43 In-play forecasting of win probability in One-Day International cricket: A dynamic logistic regression model
by Asif, Muhammad & McHale, Ian G.
- 44-60 Order effects in judgmental forecasting
by Theocharis, Zoe & Harvey, Nigel
- 61-74 Combining forecasts from successive data vintages: An application to U.S. growth
by Götz, Thomas B. & Hecq, Alain & Urbain, Jean-Pierre
- 75-97 Can currency-based risk factors help forecast exchange rates?
by Ahmed, Shamim & Liu, Xiaoquan & Valente, Giorgio
- 98-111 Irregular leadership changes in 2014: Forecasts using ensemble, split-population duration models
by Beger, Andreas & Dorff, Cassy L. & Ward, Michael D.
- 112-120 A parsimonious explanation of observed biases when forecasting one’s own performance
by Meeran, Sheik & Goodwin, Paul & Yalabik, Baris
- 121-137 Multistep forecasting in the presence of location shifts
by Chevillon, Guillaume
- 138-153 Forecasting inflation using survey expectations and target inflation: Evidence for Brazil and Turkey
by Altug, Sumru & Çakmaklı, Cem
- 154-167 How accurate are professional forecasts in Asia? Evidence from ten countries
by Chen, Qiwei & Costantini, Mauro & Deschamps, Bruno
- 168-179 Forecasting annual lung and bronchus cancer deaths using individual survival times
by Jun, Duk Bin & Kim, Kyunghoon & Park, Myoung Hwan
- 180-202 Outlier detection in structural time series models: The indicator saturation approach
by Marczak, Martyna & Proietti, Tommaso
- 203-230 The time-varying leading properties of the high yield spread in the United States
by De Pace, Pierangelo & Weber, Kyle D.
2015, Volume 31, Issue 4
- 1009-1020 Real-time forecasting of the US federal government budget: A simple mixed frequency data regression approach
by Ghysels, Eric & Ozkan, Nazire
- 1021-1042 Nowcasting French GDP in real-time with surveys and “blocked” regressions: Combining forecasts or pooling information?
by Bec, Frédérique & Mogliani, Matteo
- 1043-1055 What affects the predictions of private forecasters? The role of central bank forecasts in Chile
by Pedersen, Michael
- 1056-1066 Forecasting long memory series subject to structural change: A two-stage approach
by Papailias, Fotis & Fruet Dias, Gustavo
- 1067-1095 Point and density forecasts for the euro area using Bayesian VARs
by Berg, Tim O. & Henzel, Steffen R.
- 1096-1103 Optimal combination of survey forecasts
by Conflitti, Cristina & De Mol, Christine & Giannone, Domenico
- 1105-1126 Forecasting in telecommunications and ICT—A review
by Meade, Nigel & Islam, Towhidul
- 1127-1137 Predicting internet commercial connectivity wars: The impact of trust and operators’ asymmetry
by D’Ignazio, Alessio & Giovannetti, Emanuele
- 1138-1152 Firm level innovation diffusion of 3G mobile connections in international context
by Islam, Towhidul & Meade, Nigel
- 1153-1158 The forecasting accuracy of models of post-award network deployment: An application of maximum score tests
by Madden, Gary & Mayer, Walter & Wu, Chen & Tran, Thien
- 1159-1170 The diffusion of mobile social networking: Exploring adoption externalities in four G7 countries
by Scaglione, Miriam & Giovannetti, Emanuele & Hamoudia, Mohsen
2015, Volume 31, Issue 3
- 587-597 Testing for multiple-period predictability between serially dependent time series
by Heaton, Chris
- 598-608 Forecasting zero-inflated price changes with a Markov switching mixture model for autoregressive and heteroscedastic time series
by Kömm, Holger & Küsters, Ulrich
- 609-619 Volatility forecasting: The role of lunch-break returns, overnight returns, trading volume and leverage effects
by Wang, Xunxiao & Wu, Chongfeng & Xu, Weidong
- 620-634 Forecasting realized volatility with changing average levels
by Gallo, Giampiero M. & Otranto, Edoardo
- 635-650 Option pricing with asymmetric heteroskedastic normal mixture models
by Rombouts, Jeroen V.K. & Stentoft, Lars
- 651-663 Forecasting the forecastability quotient for inventory management
by Hill, Arthur V. & Zhang, Weiyong & Burch, Gerald F.
- 664-679 Macroeconomic forecasting during the Great Recession: The return of non-linearity?
by Ferrara, Laurent & Marcellino, Massimiliano & Mogliani, Matteo
- 682-691 Macroeconomic forecasting and structural analysis through regularized reduced-rank regression
by Bernardini, Emmanuela & Cubadda, Gianluca
- 692-711 Markov-switching mixed-frequency VAR models
by Foroni, Claudia & Guérin, Pierre & Marcellino, Massimiliano
- 712-738 EuroMInd-C: A disaggregate monthly indicator of economic activity for the Euro area and member countries
by Grassi, Stefano & Proietti, Tommaso & Frale, Cecilia & Marcellino, Massimiliano & Mazzi, Gianluigi
- 739-756 Conditional forecasts and scenario analysis with vector autoregressions for large cross-sections
by Bańbura, Marta & Giannone, Domenico & Lenza, Michele
- 757-768 Forecasting with Bayesian multivariate vintage-based VARs
by Carriero, Andrea & Clements, Michael P. & Galvão, Ana Beatriz
- 769-781 Interpretation and use of sensitivity in econometrics, illustrated with forecast combinations
by Magnus, Jan R. & Vasnev, Andrey L.
- 782-798 Comparison of methods for constructing joint confidence bands for impulse response functions
by Lütkepohl, Helmut & Staszewska-Bystrova, Anna & Winker, Peter
- 799-814 Generalized autocontours: Evaluation of multivariate density models
by González-Rivera, Gloria & Sun, Yingying
- 815-833 Copula modelling of dependence in multivariate time series
by Smith, Michael Stanley
- 834-848 Bootstrap multi-step forecasts of non-Gaussian VAR models
by Fresoli, Diego & Ruiz, Esther & Pascual, Lorenzo
- 849-861 Selecting volatility forecasting models for portfolio allocation purposes
by Becker, R. & Clements, A.E. & Doolan, M.B. & Hurn, A.S.
- 862-875 Forecasting multivariate time series under present-value model short- and long-run co-movement restrictions
by Guillén, Osmani Teixeira & Hecq, Alain & Issler, João Victor & Saraiva, Diogo
- 876-894 Testing causality between two vectors in multivariate GARCH models
by Woźniak, Tomasz
- 898-909 Origins of Presidential poll aggregation: A perspective from 2004 to 2012
by Wang, Samuel S.-H.
- 910-915 A simple approach to projecting the electoral college
by Putnam, Joshua T.
- 916-929 The wisdom of crowds: Applying Condorcet’s jury theorem to forecasting US presidential elections
by Murr, Andreas E.
- 930-942 Calibrating ensemble forecasting models with sparse data in the social sciences
by Montgomery, Jacob M. & Hollenbach, Florian M. & Ward, Michael D.
- 943-951 Limitations of Ensemble Bayesian Model Averaging for forecasting social science problems
by Graefe, Andreas & Küchenhoff, Helmut & Stierle, Veronika & Riedl, Bernhard
- 952-964 Combining forecasts for elections: Accurate, relevant, and timely
by Rothschild, David
- 965-979 Under-performing, over-performing, or just performing? The limitations of fundamentals-based presidential election forecasting
by Lauderdale, Benjamin E. & Linzer, Drew
- 980-991 Forecasting elections with non-representative polls
by Wang, Wei & Rothschild, David & Goel, Sharad & Gelman, Andrew
- 992-1007 Can we vote with our tweet? On the perennial difficulty of election forecasting with social media
by Huberty, Mark
2015, Volume 31, Issue 2
- 223-237 Forecast combination with outlier protection
by Cheng, Gang & Yang, Yuhong
- 238-252 Do high-frequency financial data help forecast oil prices? The MIDAS touch at work
by Baumeister, Christiane & Guérin, Pierre & Kilian, Lutz
- 253-262 ROC-based model estimation for forecasting large changes in demand
by Schneider, Matthew J. & Gorr, Wilpen L.
- 263-275 Balance sheets of financial intermediaries: Do they forecast economic activity?
by Sekkel, Rodrigo M.
- 276-285 Forecasting residential investment in the United States
by Lunsford, Kurt G.
- 286-295 Weather station selection for electric load forecasting
by Hong, Tao & Wang, Pu & White, Laura
- 296-311 Modeling time-varying skewness via decomposition for out-of-sample forecast
by Liu, Xiaochun
- 312-324 How good are US government forecasts of the federal debt?
by Martinez, Andrew B.
- 325-348 Macroeconomic information, structural change, and the prediction of fiscal aggregates
by Carriero, Andrea & Mumtaz, Haroon & Theophilopoulou, Angeliki
- 349-363 Forecasting financial market activity using a semiparametric fractionally integrated Log-ACD
by Feng, Yuanhua & Zhou, Chen
- 364-390 Box office forecasting using machine learning algorithms based on SNS data
by Kim, Taegu & Hong, Jungsik & Kang, Pilsung
- 399-425 Some historical perspectives on the Bond-Stock Earnings Yield Model for crash prediction around the world
by Lleo, Sébastien & Ziemba, William T.
- 426-445 Using financial indicators to predict turning points in the business cycle: The case of the leading economic index for the United States
by Levanon, Gad & Manini, Jean-Claude & Ozyildirim, Ataman & Schaitkin, Brian & Tanchua, Jennelyn
- 446-453 A further analysis of the conference board’s new Leading Economic Index
by Lahiri, Kajal & Yang, Liu
- 454-472 Predictability and ‘good deals’ in currency markets
by Levich, Richard M. & Potì, Valerio
- 473-487 Pretesting for multi-step-ahead exchange rate forecasts with STAR models
by Enders, Walter & Pascalau, Razvan
- 488-500 Comparing the effectiveness of traditional vs. mechanized identification methods in post-sample forecasting for a macroeconomic Granger causality analysis
by Ye, Haichun & Ashley, Richard & Guerard, John