Research classified by Journal of Economic Literature (JEL) codes

1. Forecasting

2026

• Martin McCarthy & Umberto Collodel & Prakash Loungani, 2026, "Real GDP Forecasts by International Organisations," RBA Research Discussion Papers, Reserve Bank of Australia, number rdp2026-05, Sep, DOI: 10.47688/rdp2026-05.
• Winkelried, Diego & Jason Cruz & Javier Torres, 2026, "Nowcasting GDP using data revisions in an emerging economy," Working Papers, Banco Central de Reserva del Perú, number 2026-003, Apr.
• Juan Tenorio & Heidi Alpiste & Jackelin Remón & Arian Segil, 2026, "An Artificial Trend Index for Private Consumption Using Google Trends," Working Papers, Banco Central de Reserva del Perú, number 2026-019, Jul.
• Annamária Lőrincz, 2026, "Dynamic Optimisation and Scenario Analysis of the Romanian Public Pension System," Zbornik radova Ekonomskog fakulteta u Rijeci/Proceedings of Rijeka Faculty of Economics, University of Rijeka, Faculty of Economics and Business, volume 44, issue 1, pages 129-160.
• Emek Aslı CİNEL & Ufuk YOLCU, 2026, "Türkiye’de İşsizlik ve İstihdam Oranlarının Ekonomik Büyüme Göstergeleriyle Öngörülmesi: İstatistiksel, Yapay Sinir Ağı ve Bulanık Modellerin Karşılaştırılması
  [Forecasting Unemployment and Employment Rates in Türkiye with Economic Growth Indicato," Business and Economics Research Journal, Bursa Uludag University, Faculty of Economics and Administrative Sciences, volume 17, issue 4, pages 587-618, October, DOI: 10.20409/berj.2026.513.
• Valdemar J. Undji & Johannes P.S. Sheefeni, 2026, "Determinants of Non-Performing Loans in Namibia," Economia Internazionale / International Economics, Camera di Commercio Industria Artigianato Agricoltura di Genova, volume 79, issue 2, pages 199-244, May, DOI: 10.65644/EIIE.079.02.0199.
• Julián Ramajo & Alejandro Ricci-Risquete & Geoffrey J.D Hewings, 2026, "Dinámica espaciotemporal en el crecimiento económico regional: un modelo empírico para las comunidades autónomas españolas
  [Spatio-temporal dynamics of regional economic growth: An empirical model for the Spanish Autonomous Communities]," INVESTIGACIONES REGIONALES - Journal of REGIONAL RESEARCH, Asociación Española de Ciencia Regional, volume 65, issue 65, pages 143-160, June, DOI: 10.38191/iirr-jorr.24.049.
• Hyunjun Song & Dojoon Park & Zoonky Lee & Yong Joo Kang, 2026, "Machine-Learning Based Default Prediction: The Role of External Audits and Financial Constraints," Journal of Economic Development, The Economic Research Institute, Chung-Ang University, volume 51, issue 2, pages 13-41, June, DOI: 10.35866/caujed.2026.51.2.002.
• Larissa Nawo, 2026, "Financial Conditions and U.S. Macro Tail Risk," Papers, Risk Management Research Platform, number 26-02, Oct.
• Hwee Kwan Chow & Jordan Lee, 2026, "Projecting Inflation Tail Risks in a Small Open Economy: Some Evidence from Singapore," Economics and Statistics Working Papers, Singapore Management University, School of Economics, number 04-2026, Feb.
• Mara Giua & Francesca Micocci & Giulia Valeria Sonzogno, 2026, "Enhancing Implementation SuccessinCohesion Policy. A Machine Learning Approach," Departmental Working Papers of Economics - University 'Roma Tre', Department of Economics - University Roma Tre, number 0289, Mar.
• Magdalena Cornejo & Walter Sosa Escudero, 2026, "Machine Learning and Shrinkage in Dynamic Panel Forecasting," Working Papers, Universidad de San Andres, Departamento de Economia, number 183, May, revised May 2026.
• Maciej Ryczkowski, 2026, "Evaluating the Methods of Estimating Total Hours Actually Worked: Insights from Labor Market Statistics," Gospodarka Narodowa. The Polish Journal of Economics, Warsaw School of Economics, issue 2, pages 22-49.
• Marcos Ross Fernandes, 2026, "Combining Combined Forecasts: a Network Approach," Working Papers, Department of Economics, University of São Paulo (FEA-USP), number 2026_23, Aug.
• Vitor Gentini & Marcio Issao Nakane, 2026, "NEWS IV: A model with news and implied volatility for enhanced volatility prediction," Working Papers, Department of Economics, University of São Paulo (FEA-USP), number 2026_25, Aug.
• Tu DQ Le & Son H Tran & Thanh Ngo & Hung D Bui, 2026, "Forecasting Vietnam Inflation Using Machine Learning Approaches: A Comprehensive Analysis," Advances in Decision Sciences, Asia University, Taiwan, volume 30, issue 1, pages 136-185.
• Jose Rizal & Nur Afandi & Gusman Juliadi & Indah Wahyuliani & Cinta Rizki Oktarina, 2026, "Forecasting the Appearance Frequency of Rafflesia arnoldii in Bengkulu, Indonesia, Using Discrete-valued Time Series Modeling," Advances in Decision Sciences, Asia University, Taiwan, volume 30, issue 2, pages 39-67, June.
• Mohamed Galal & Sherine Rady & Mostafa Aref, 2026, "Enhancement of Digital Credit Scoring in P2P Lending using a Robust Hybrid Voting–Stacking Ensemble Framework," Advances in Decision Sciences, Asia University, Taiwan, volume 30, issue 3, pages 145-183, September.
• Zourkata Meriem & Damene Ouahiba, 2026, "The Use of the Z-Score Indicator to Measure Financial Soundness and Stability in Islamic Banks (The Case of Al Salam Bank Algeria during the Period 2015–2024)," Finance, Accounting and Business Analysis, Academic Publishing UNWE, volume 8, issue 1, pages 117-134, June.
• Sarthak Behera & Hyeongwoo Kim & Soohyon Kim, 2026, "Asymmetric Roles of Macroeconomic Variables in the Real Exchange Rate: Insights from U.S.-Korea Data," Auburn Economics Working Paper Series, Department of Economics, Auburn University, number auwp2026-01, Jan.
• Kfir Eliaz & Ran Spiegler, 2026, "Monopolistic Data Dumping," American Economic Journal: Microeconomics, American Economic Association, volume 18, issue 4, pages 534-559, November, DOI: 10.1257/mic.20250260.
• Denis Kuster & Bojana Vukovic, 2026, "Enhancing Resilience of Small and Medium-Sized Enterprises in an Emerging Economy: Neural Network-Based Bankruptcy Prediction," The AMFITEATRU ECONOMIC journal, Academy of Economic Studies - Bucharest, Romania, volume 28, issue 72, pages 712-712, April.
• Casoli, Chiara & Lucchetti, Riccardo, 2026, "A rotated Dynamic Factor Model for the yield curve: squeezing out information when it matters," FEEM Working Papers, Fondazione Eni Enrico Mattei (FEEM), number 388985, Jan, DOI: 10.22004/ag.econ.388985.
• Katarzyna Chec & Bartosz Uniejewski & Rafal Weron, 2026, "From biased point forecasts of electricity demand to accurate predictive distributions: Using LASSO and GAMLSS," WORking papers in Management Science (WORMS), Department of Operations Research and Business Intelligence, Wroclaw University of Science and Technology, number WORMS/26/01.
• Cansu Çilingir Kara, 2026, "The Impact of R&D Intensity and Financial Slack on Company Performance: An Analysis of Companies with the Highest R&D Expenditure in Türkiye," Journal of Research in Economics, Politics & Finance, Ersan ERSOY, volume 10, issue 4, pages 1366-1381, DOI: 10.30784/epfad.1666691.
• Chiara Casoli & Riccardo Lucchetti, 2026, "A rotated Dynamic Factor Model for the yield curve: squeezing out information when it matters," Working Papers, Universita' Politecnica delle Marche (I), Dipartimento di Scienze Economiche e Sociali, number 503, Jan.
• Sara BOUGHANOU & Adil EL MARHOUM, 2026, "Signaux textuels multilingues et prévision de la volatilité réalisée : une approche hybride Transformer-HAR-X appliquée au S&P 500 et au MASI," International Journal of Accounting, Finance, Auditing, Management and Economics, Faculté d'Économie et de Gestion, Université Ibn Tofaïl de Kénitra, volume 7, issue 10, pages 109-132.
• Rahma MZOURI & Abdelkrim KANDROUCH, 2026, "Défaillance des entreprises : revue de littérature," International Journal of Accounting, Finance, Auditing, Management and Economics, Faculté d'Économie et de Gestion, Université Ibn Tofaïl de Kénitra, volume 7, issue 2, pages 645-670.
• Adil SLAMI-AMINE & Abdessamad DINE & Boujemaa ACHCHAB, 2026, "Typologie et taxonomie des modèles prédictifs monolithiques et hybrides d'intelligence artificielle et d'apprentissage automatique en finance : une architecture générationnelle intégrée," International Journal of Accounting, Finance, Auditing, Management and Economics, Faculté d'Économie et de Gestion, Université Ibn Tofaïl de Kénitra, volume 7, issue 6, pages 543-570.
• Adil SLAMI-AMINE & Abdessamad DINE & Boujemaa ACHCHAB, 2026, "Une typologie comparative des générations de modèles d'apprentissage automatique monolithiques et hybrides pour la prédiction financière : benchmark théorique face aux modèles économétriques traditionnels," International Journal of Accounting, Finance, Auditing, Management and Economics, Faculté d'Économie et de Gestion, Université Ibn Tofaïl de Kénitra, volume 7, issue 7, pages 174-200.
• Julien TEKASALA NLANDU, 2026, "Prédiction de faillite de l’industrie agroalimentaire de la ville de Kinshasa : application du modèle Z-score d’Edward Altman," International Journal of Accounting, Finance, Auditing, Management and Economics, Faculté d'Économie et de Gestion, Université Ibn Tofaïl de Kénitra, volume 7, issue 8, pages 774-784.
• Ахмет Алишер // Alisher Akhmet, 2026, "Прогнозирование ВВП Казахстана на основе динамической факторной модели с регуляризацией // Forecasting Kazakhstan’s GDP Based on a Dynamic Factor Model with Regularization," Working Papers, National Bank of Kazakhstan, number #2026-1.
• Esteban Sánchez-Gómez, 2026, "Machine Learning Methods for Multi-Horizon Inflation Forecasting: A Comparative Analysis for Costa Rica," Documentos de Trabajo, Banco Central de Costa Rica, number 2606, Aug.
• Susan Jiménez-Montero, 2026, "Short-term Inflation Forecasts as an Input for the Formulation of Monetary Policy," Ensayos de Política Económica, Banco Central de Costa Rica, number 2603, Jun.
• Ani Asoyan & Jared Laxton, 2026, "An Analytical Framework to Support a Prudent Risk Management Approach in Armenia," Working Papers, Central Bank of Armenia, number WP-2026-03, Sep.
• Joshua S. Gans, 2026, "Optimal Use of Preferences in Artificial Intelligence Algorithms," Papers, arXiv.org, number 2601.18732, Jan.
• Jiti Gao & Fei Liu & Bin Peng, 2026, "Inference for High-Dimensional Local Projection," Papers, arXiv.org, number 2602.10415, Feb.
• Hilde C. Bjornland & Nicolas Hardy & Dimitris Korobilis, 2026, "Forecasting Oil Prices Across the Distribution: A Quantile VAR Approach," Papers, arXiv.org, number 2604.12927, Apr.
• Dalibor Stevanovic, 2026, "Who Saw It Coming? Historical Experience and the 2021 Inflation Forecast Failure," Papers, arXiv.org, number 2604.14467, Apr.
• Tobias Adrian & Domenico Giannone & Matteo Luciani & Mike West, 2026, "Risks and Uncertainty in Monetary Policy," Papers, arXiv.org, number 2606.16708, Jun.
• Latif Zeynalli & Ramil Huseyn & Agil Asadov & Abdulrahim Dadashov, 2026, "Exploring The Nexus Between Emissions, Economic Growth, And Employment: Evidence From Azerbaijan," Economic Thought and Practice, Department of Economics and Business, University of Dubrovnik, volume 35, issue 1, pages 277-298, june, DOI: 10.17818/EMIP/2025/44.
• Tamkin Nuriyev & Aygun Garayeva & Gulzar Tahirova, 2026, "Construction and Forecasting of the Imported Food Price Index in Azerbaijan," Working Papers, Central Bank of Azerbaijan Republic, number 2601, Jan.
• Zakia Zafar & Tanweer Ul Islam, 2026, "Inflation Dynamics and Forecasting Performance in Developing Economies: A Cross-Country MIDAS Analysis," Journal of Economic Sciences, Federal Urdu University Islamabad, Department of Economics, volume 5, issue 1, pages 127-148, January-J, DOI: 10.55603/jes.v5i1.a8.
• Niko Hauzenberger Massimiliano Marcellino Michael Pfarrhofer Anna Stelzer, 2026, "Direct Gaussian Process Predictive Regressions with Mixed Frequency Data," BAFFI CAREFIN Working Papers, BAFFI CAREFIN, Centre for Applied Research on International Markets Banking Finance and Regulation, Universita' Bocconi, Milano, Italy, number 26265.
• Andrea Panozzo, Lorenzo Spadavecchia, Adam Mugume, Elizabeth Kasekende, Samuel Namwanja Musoke, Mariss Nakayaga, Deo Sande, Anita Mpagi, Nzima Ghislain, 2026, "Nowcasting GDP with Digital Payments: Evidence from Uganda," BAFFI CAREFIN Working Papers, BAFFI CAREFIN, Centre for Applied Research on International Markets Banking Finance and Regulation, Universita' Bocconi, Milano, Italy, number 26282.
• Andrea Gentilini, 2026, "Data Driven Compliance: A SBR solution for regulated entities," BAFFI CAREFIN Working Papers, BAFFI CAREFIN, Centre for Applied Research on International Markets Banking Finance and Regulation, Universita' Bocconi, Milano, Italy, number 26283.
• Dezdemona Gjylapi & Alketa Hyso & Filloreta Madani, 2026, "Forecasting Quarterly GDP Growth and the GDP Deflator in Albania under Data Scarcity: A Comparative Evaluation of Statistical and Machine Learning Models," Economic Studies journal, Bulgarian Academy of Sciences - Economic Research Institute, issue 6, pages 107-131.
• Dalibor Stevanovic, 2026, "Who Saw It Coming? Historical Experienceand the 2021 Inflation Forecast Failure," Working Papers, Chair in macroeconomics and forecasting, University of Quebec in Montreal's School of Management, number 26-02, Apr.
• Guanglan Zhou & Ziyi Wu, 2026, "A resilient model for trade volume forecasting under economic uncertainty: Addressing challenges in the global supply chain," E&M Economics and Management, Technical University of Liberec, Faculty of Economics, volume 29, issue 1, pages 207-224, March, DOI: 10.15240/tul/001/2026-1-013.
• Shahryar Ghorbani & Figen Yildirim & Ali Altug Bicer & Reza Rostamzadeh & Jonas Saparauskas, 2026, "Forecasting major currency exchange rates using long short-term memory networks: Evidence from multi-currency time series analysis," E&M Economics and Management, Technical University of Liberec, Faculty of Economics, volume 29, issue 2, pages 220-239, July, DOI: 10.15240/tul/001/2026-2-014.
• Alfonso Ugarte, 2026, "Panel Local Projections without Fixed-Effects: A Cumulative-Difference OLS Estimator," Working Papers, BBVA Bank, Economic Research Department, number 26/09, Jun.
• Sergio A. Lago Alves & Waldyr Dutra Areosa & Carlos Viana de Carvalho, 2026, "Beating the “pros” with a semi-structural model of their own inflation forecasts," Staff Working Papers, Bank of Canada, number 26-11, Mar, DOI: 10.34989/swp-2026-11.
• Gabriel Rodriguez Rondon & Jean-Marie Dufour & Md. Nazmul Ahsan, 2026, "Estimation and Inference for Stochastic Volatility Models with Heavy-Tailed Distributions," Staff Working Papers, Bank of Canada, number 26-8, Mar, DOI: 10.34989/swp-2026-8.
• Irma Alonso-Alvarez & Iván Kataryniuk & David López-Salido & Javier J. Pérez, 2026, "Geopolitical Oil-Supply Scenarios and Macroeconomic Risks: A Bayesian Toolkit for Policy Analysis," Occasional Papers, Banco de España, number 2616, Sep, DOI: https://doi.org/10.53479/44325.
• Andrea De Polis & Leonardo Melosi & Ivan Petrella, 2026, "The Taming of the Skew: Asymmetric Inflation Risk and Monetary Policy," Working Papers, Banco de España, number 2626, Sep, DOI: https://doi.org/10.53479/44247.
• Luca Bacco & Tiziana Laureti & Juri Marcucci & Luigi Palumbo & Daniele Sasso & Luca Vollero, 2026, "Nowcasting the Italian consumer price index using online prices and machine learning," Questioni di Economia e Finanza (Occasional Papers), Bank of Italy, Economic Research and International Relations Area, number 1026, Jun.
• Andrea Del Monaco & Luigi Longo & Juri Marcucci & Irene Tafani, 2026, "Reddit's 'pulse' on US inflation: forecasting with large language models," Questioni di Economia e Finanza (Occasional Papers), Bank of Italy, Economic Research and International Relations Area, number 1028, Jun.
• Michela Eugenia Pasetto, 2026, "A method for forecasting unquoted shares of non-financial corporations in the Italian financial accounts," Questioni di Economia e Finanza (Occasional Papers), Bank of Italy, Economic Research and International Relations Area, number 1037, Jul.
• Donato Ceci & Claudia Pacella & Fabrizio Venditti, 2026, "Consumption and saving in the euro area after COVID: a scenario analysis," Questioni di Economia e Finanza (Occasional Papers), Bank of Italy, Economic Research and International Relations Area, number 1047, Jul.
• Filippo Natoli & Sharath Sonti, 2026, "Overconfident forecasters and the impact of inflation information: evidence from a randomized survey experiment," Temi di discussione (Economic working papers), Bank of Italy, Economic Research and International Relations Area, number 1532, Apr.
• Rocío Clara A. Mora-Quiñones & Antonio José Orozco-Gallo & Dora Alicia Mora-Pérez, 2026, "Sentiment and Uncertainty Indices from economic news in Colombia," Borradores de Economia, Banco de la Republica de Colombia, number 1340, Jan, DOI: 10.32468/be.1340.
• Aarón Levi Garavito-Acosta & Wilmer Martinez-Rivera & Camilo González-Sabogal & Johanna Barbosa-Buitrago & Nathaly Vergel-Serrano, 2026, "Determinantes y pronóstico de la cuenta corriente para Colombia," Borradores de Economia, Banco de la Republica de Colombia, number 1360, Aug.
• Franky Juliano Galeano-Ramírez & Nicolás Martínez-Cortés & Hernán Dario Perdomo-Sánchez & Marlon Salazar, 2026, "Inflation Drivers in Colombia: A Hemisphere Neural Network Approach," Borradores de Economia, Banco de la Republica de Colombia, number 1370, Oct.
• Pedro Pablo Calderon-Camacho & Celina Gaitán-Maldonado & Nicolle Valentina Herrera-Pinto & Mario Andrés Ramos-Veloza, 2026, "Reading Between the Lines: A Quantitative Analysis of Colombia’s Central Bank Minutes," Borradores de Economia, Banco de la Republica de Colombia, number 1371, Oct.
• Aarón Levi Garavito-Acosta & Wilmer Martinez-Rivera & Juan José Ospina-Tejeiro & Edgar Caicedo-García, 2026, "Experimenting with Large Language Models for Inflation Forecasting in Colombia," Borradores de Economia, Banco de la Republica de Colombia, number 1375, Oct.
• Laura Mayoral & Hannes Mueller & Margherita Philipp & Christopher Rauh & Renato Vassallo, 2026, "Semantic Similarity Measures in Newspaper Text for Detecting and Predicting Disruptive Institutional Events," Working Papers, Barcelona School of Economics, number 1555, Jan.
• Laura Mayoral & Hannes Mueller & Christopher Rauh & Ben Seimon & Ramón Talvi Robledo, 2026, "Forecasting Forced Displacement Flows Using Machine Learning with Text Data," Working Papers, Barcelona School of Economics, number 1573, Apr.
• Doan Gia Bao Ngoc & Luu Minh Quan & Truong Thi Thanh Ha & Nguyen Duc Minh Tan & Phan Thi Minh Huyen & Tran Duy Thanh, 2026, "Building a new hybrid machine learning model for improvement insurance cross-sell prediction," Ho Chi Minh City Open University Journal of Science - Economics and Business Administration, Ho Chi Minh City Open University Journal of Science, Ho Chi Minh City Open University, volume 16, issue 1, pages 93-111, DOI: 10.46223/HCMCOUJS.econ.en.16.1.4306.
• Zhanna Shuvalova, 2026, "Forecasting Fixed Capital Investment with Patent Activity Indicators," Russian Journal of Money and Finance, Bank of Russia, volume 85, issue 2, pages 37-66, June.
• Danila Ovechkin, 2026, "Estimation and forecasting with a Nonlinear Phillips Curve based on heterogeneous sensitivity between economic activity and CPI components," Bank of Russia Working Paper Series, Bank of Russia, number wps161, Jan.
• Alexander Eliseev & Sergei Seleznev, 2026, "Fake Date Tests: Can We Trust In-sample Accuracy of LLMs in Macroeconomic Forecasting?," Bank of Russia Working Paper Series, Bank of Russia, number wps167, Mar.
• Oguzhan Cepni & Riza Demirer & Rangan Gupta & Christian Pierdzioch, 2026, "Political Geography and Stock Market Volatility: The Role of Political Alignment Across Sentiment Regimes," Scottish Journal of Political Economy, Scottish Economic Society, volume 73, issue 1, February, DOI: 10.1111/sjpe.70028.
• Yuriy Gorodnichenko & Vittal Vasudevan, 2026, "Macroeconomic Expectations in a War," Scottish Journal of Political Economy, Scottish Economic Society, volume 73, issue 3, July, DOI: 10.1111/sjpe.70064.
• Hilde C. Bjørnland & Nicolás Hardy & Dimitris Korobilis, 2026, "Forecasting Oil Prices Across the Distribution: A Quantile VAR Approach," Working Papers, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School, number No 03/2026, Apr.
• Nicolas Hardy & Dimitris Korobilis, 2026, "Generalized Bayesian Composite Quantile Regression with an Application to Equity Premium Forecasting," Working Papers, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School, number No 04/2026, Apr.
• Tom Doan, 2026, "MATHESONSTAVREVEL2013: RATS programs to replicate Matheson-Stavrev(2013) non-linear state-space model," Statistical Software Components, Boston College Department of Economics, number RTJ00054, revised .
• Panagiotis Delis & Georgios Kontogeorgos, 2026, "Outlier-robust evaluation of fixed-event macroeconomic survey expectations," Working Papers, Bank of Greece, number 356, Jan, DOI: 10.52903/wp2026356.
• Dimitrios P. Louzis, 2026, "Trend inflation and inflation expectations in high dimensional vector autoregressions," Working Papers, Bank of Greece, number 360, Mar, DOI: 10.52903/wp2026360.
• Zacharias Bragoudakis & Alexandros Karakitsios & Evangelia Kasimati, 2026, "Short-term inflation projections: Τhe new BOG’STIP model," Working Papers, Bank of Greece, number 363, Jun, DOI: 10.52903/wp2026363.
• Nonejad Nima, 2026, "Out-of-Sample Density Prediction of the End-of-Month Price of Crude Oil and the U.S. Economic Policy Uncertainty Index," Journal of Time Series Econometrics, De Gruyter, volume 18, issue 1, pages 1-47, DOI: 10.1515/jtse-2025-0007.
• Psaradakis Zacharias & Sola Martin & Spagnolo Nicola & Yunis Patricio, 2026, "Predictive Accuracy of Impulse Responses Estimated Using Local Projections and Vector Autoregressions," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, volume 30, issue 3, pages 431-441, DOI: 10.1515/snde-2024-0053.
• Liu Ruipeng & Segnon Mawuli & Gupta Rangan & Bouri Elie, 2026, "Conventional and Unconventional Monetary Policy Rate Uncertainty and Stock Market Volatility: A Forecasting Perspective," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, volume 30, issue 4, pages 595-619, DOI: 10.1515/snde-2024-0108.
• Leon-Gonzalez Roberto & Majoni Blessings, 2026, "Approximate Factor Models with a Common Multiplicative Factor for Stochastic Volatility," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, volume 30, issue 4, pages 649-678, DOI: 10.1515/snde-2024-0103.
• Abbara Omar & Zevallos Mauricio, 2026, "On the Estimation of Asymmetric Long Memory Stochastic Volatility Models," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, volume 30, issue 4, pages 847-867, DOI: 10.1515/snde-2024-0092.
• Adrian Gadient & Delia Haag & Nicolas Gygax, 2026, "Estimating Housing Costs in Switzerland Using Public Registers and Survey Data: A Machine Learning Approach," University of Bern Social Sciences Working Papers, University of Bern, Department of Social Sciences, number 63, Oct.
• Mayoral, L. & Mueller, H. & Philipp, M. & Rauh, C. & Vassallo, R., 2026, "Semantic Similarity Measures in Newspaper Text for Detecting and Predicting Disruptive Institutional Events," Cambridge Working Papers in Economics, Faculty of Economics, University of Cambridge, number 2609, Jan.
• Congressional Budget Office, 2026, "The Accuracy of CBO's Budget Projections for Fiscal Year 2025," Reports, Congressional Budget Office, number 61916, Jan.
• Xu, Yongdeng, 2026, "Learn the measure, estimate the moment: machine-learned drivers in dynamic conditional correlation models," Cardiff Economics Working Papers, Cardiff University, Cardiff Business School, Economics Section, number E2026/12, Sep.
• Karanasos, Menelaos & Xu, Yongdeng & Yfanti, Stavroula & Zopounidis, Constantin, 2026, "Enforcing an Admissible Parameter Space for Vector MEM: The Fundamental Role of Matrix Inequality Constraints," Cardiff Economics Working Papers, Cardiff University, Cardiff Business School, Economics Section, number E2026/3, Mar.
• Rouven Beiner & Bernd Süssmuth, 2026, "Monotonic Polynomial GARCH Models for Conditional Higher Moments," CESifo Working Paper Series, CESifo, number 12734.
• Veni Arakelia & Guglielmo Maria Caporale & Mirto M. Gasparinatou & Menelaos Karanasos, 2026, "Machine Learning and Liquidity Dynamics in European Stock Markets," CESifo Working Paper Series, CESifo, number 12829.
• Vegard H. Larsen & Leif Anders Thorsrud, 2026, "Zero-Shot Conditional Forecasting and the Information Content of Central Bank Paths," CESifo Working Paper Series, CESifo, number 12972.
• Jesús Fernández-Villaverde & Carlos Sanz, 2026, "Social Sorting and Political Cleavages: Evidence from 2.5 Million Electoral Candidates," CESifo Working Paper Series, CESifo, number 13005.
• Stephane Hallegatte, 2026, "Global Flood Risk in the 2026/27 El Niño: An Empirical Estimate from the Historical Relationship," CESifo Working Paper Series, CESifo, number 13043.
• José Alves & Clarisse Wagner, 2026, "The Two Sides of Sovereign Balance Sheets: How Much Do Government Financial Assets Tell Us About r − g?," CESifo Working Paper Series, CESifo, number 13080.
• Uluc Aysun & Melanie Guldi, 2026, "Revisiting exchange rate predictability: Can machine learning with theoretical filtering outperform canonical models?," Working Papers, University of Central Florida, Department of Economics, number 2026-01, Jan.
• Konstantinos N. Konstantakis & Olivier Scaillet & Nikolas Topaloglou & Panayotis G. Michaelides, 2026, "A Heterogeneous-Quantile Global VAR for Tail-Risk Transmission," Swiss Finance Institute Research Paper Series, Swiss Finance Institute, number 26-48, Jun.
• Yucheng Yang & Tao A. Zha, 2026, "Algorithm-Driven SVARs: Navigating the Wilderness of Big Data," Swiss Finance Institute Research Paper Series, Swiss Finance Institute, number 26-57, Aug.
• Dalibor Stevanovic, 2026, "Who Saw It Coming? Historical Experience and the 2021 Inflation Forecast Failure," CIRANO Working Papers, CIRANO, number 2026s-06, Apr.
• MD Nazmul Ahsan & Jean-Marie Dufour, 2026, "Practical estimation methods for high-dimensional multivariate stochastic volatility models," CIRANO Working Papers, CIRANO, number 2026s-20, Oct.
• Filip Blaha & Jan Botka & Josef Sveda & Ales Michl, 2026, "AI-Based Forecasting of Czech Inflation: Quantile Regression Forests with Dynamic Weights," Working Papers, Czech National Bank, Research and Statistics Department, number 2026/09, Apr.
• Juan Carlos Gutiérrez-Betancur, 2026, "Del tsunami al terremoto demográfico en Colombia," Documentos de Trabajo de Valor Público, Universidad EAFIT, number 023626.
• Carlos Palomino Selem & Ruth Milagros Delgado Yana, 2026, "Comparative analysis between traditional momentum and machine learning (random forest): evidence from the S&P 500 (2000-2024)," Revista Tendencias, Universidad de Narino, volume 27, issue 02, pages 32-61, July, DOI: 10.22267/rtend.26272.296.
• Ghezzi, Fabrizio & Timmermann, Allan & Yang, Max, 2026, "Gauging Hourly Economic Activity in Your Neighborhood," CEPR Discussion Papers, Centre for Economic Policy Research, number 21098, Jan.
• Hauzenberger, Niko & Marcellino, Massimiliano & Pfarrhofer, Michael & Stelzer, Anna, 2026, "Direct Gaussian Process Predictive Regressions with Mixed Frequency Data," CEPR Discussion Papers, Centre for Economic Policy Research, number 21214, Feb.
• Fernández-Villaverde, Jesús & Sanz, Carlos, 2026, "Social Sorting and Political Cleavages: Evidence from 2.5 Million Electoral Candidates," CEPR Discussion Papers, Centre for Economic Policy Research, number 21978, Sep.
• Guo, Hongfei & Marín, Juan Miguel & Veiga, Helena, 2026, "Target-Driven Bayesian Stacking of Realized and Implied Volatility Forecasts," DES - Working Papers. Statistics and Econometrics. WS, Universidad Carlos III de Madrid. Departamento de Estadística, number 49851, Apr.
• Guo, Hongfei & Marín, Juan Miguel & Veiga, Helena, 2026, "Diagnosing and Stabilizing Dynamic Correlations in Multivariate Stochastic Volatility Models," DES - Working Papers. Statistics and Econometrics. WS, Universidad Carlos III de Madrid. Departamento de Estadística, number 50561, Jul.
• Guo, Hongfei & Marín, Juan Miguel & Veiga, Helena, 2026, "Testing Whether Volatility Model Gains Persist: A Prespecified Holdout in Tail Risk Forecasting," DES - Working Papers. Statistics and Econometrics. WS, Universidad Carlos III de Madrid. Departamento de Estadística, number 50798, Sep.
• Çiğdem LAZOĞLU & Uğur KARABEY, 2026, "Evaluating the impact of stochastic interest rates and COVID-19 on financial performance under IFRS 17," JODE - Journal of Demographic Economics, Cambridge University Press, volume 92, issue 2, pages 277-296, June, DOI: 10.1017/dem.2024.25.
• Moench, Emanuel & Stein, Tobias, 2026, "Equity Premium Predictability over the Business Cycle," Journal of Financial and Quantitative Analysis, Cambridge University Press, volume 61, issue 3, pages 1216-1246, May.
• Nina Maria Brehl & Geraldine Dany-Knedlik & Laura Pagenhardt, 2026, "Nowcasting the Income Distribution," Discussion Papers of DIW Berlin, DIW Berlin, German Institute for Economic Research, number 2187.
• Valérie Mignon & Marc Joëts & Christophe Hurlin, 2026, "ZICO: A Credit Scoring Approach to Detecting Zombie Papers," EconomiX Working Papers, University of Paris Nanterre, EconomiX, number 2026-18.
• Eraslan, Sercan & Fabbri, Andrea & Saiz, Lorena, 2026, "Short-term forecasting of euro area economic activity in an uncertain world," Economic Bulletin Articles, European Central Bank, volume 8.
• Chahad, Mohammed & Mogliani, Matteo & Bańbura, Marta & Kulikov, Dmitry & Montes-Galdón, Carlos & Landau, Bettina & Meunier, Baptiste & Odendahl, Florens & Paredes, Joan & Sigwalt, Antoine & Theofilako, 2026, "Macro-at-Risk in the euro area Expert Group on Macro-at-Risk Time-Series Workstream," Occasional Paper Series, European Central Bank, number 396, Aug.
• Szörfi, Béla, 2026, "The factors behind output gap revisions," Occasional Paper Series, European Central Bank, number 399, Sep.
• Montes-Galdón, Carlos & Paredes, Joan & Wolf, Elias, 2026, "A robust approach to tilting: parametric relative entropy," Working Paper Series, European Central Bank, number 3200, Mar.
• Delgado-Téllez, Mar & Ceglar, Andrej & Spiteri, Sarah & Lebouteiller, Léonore & Vorderobermeier, Nicole, 2026, "Beat the heat, the role of heat waves and droughts in regional EU economies," Working Paper Series, European Central Bank, number 3248, Jun.
• Consolo, Agostino & Foroni, Claudia & Lissona, Claudio & Schroeder, Christofer, 2026, "Forecasting the euro area job vacancy rate with earnings calls data," Working Paper Series, European Central Bank, number 3269, Aug.
• Nocciola, Luca & Scaglioni, Samuele, 2026, "Learning probability of default and stress testing," Working Paper Series, European Central Bank, number 3277, Aug.
• Mertens, Elmar & Clark, Todd E., 2026, "Entropic tilting of forecasts to SPF histograms: analytics & applications," Working Paper Series, European Central Bank, number 3284, Sep.
• Fonseca, Luís & Martorana, Giulia & Schupp, Fabian & Trebbi, Giovanni, 2026, "Inflation narratives and risk premia," Working Paper Series, European Central Bank, number 3288, Sep.
• Schröder, Maximilian, 2026, "Multivariate uncertainty and distributional transmission," Working Paper Series, European Central Bank, number 3290, Sep.
• Montes-Galdón, Carlos, 2026, "Deep-π*: a neural network estimate of trend inflation," Working Paper Series, European Central Bank, number 3307, Nov.
• Jiang, Min & Shi, Jichuan & Zheng, Yukai & Zhou, Wei, 2026, "The role of alternative data in micro-enterprises’ credit risk assessment in China — Empirical evidence based on machine learning," Journal of Behavioral and Experimental Finance, Elsevier, volume 49, issue C, DOI: 10.1016/j.jbef.2026.101154.
• Mohanty, Subhransu Sekhar & Mohanty, Odette, 2026, "Harmonic resonance in asset pricing: An ontological framework of market behavior," Chaos, Solitons & Fractals, Elsevier, volume 212, issue P2, DOI: 10.1016/j.chaos.2026.118973.
• Mahler, Daniel Gerszon & Schoch, Marta & Lakner, Christoph & Nguyen, Minh Cong, 2026, "A parsimonious approach to predicting income distributions," Journal of Development Economics, Elsevier, volume 180, issue C, DOI: 10.1016/j.jdeveco.2025.103695.
• Yang, Zheng & Wu, Haocheng & Kuo, Biing-Shen & Ma, Yongkai, 2026, "Forecasting Chinese equity premium: A dimensionality reduction combination approach," Journal of Economic Dynamics and Control, Elsevier, volume 186, issue C, DOI: 10.1016/j.jedc.2026.105308.
• Labonne, Paul & Thorsrud, Leif Anders, 2026, "Risky news and credit market sentiment," Journal of Economic Dynamics and Control, Elsevier, volume 187, issue C, DOI: 10.1016/j.jedc.2026.105331.
• Chironna, Gianpiero & Orlando, Giuseppe, 2026, "Predicting bank defaults in Italy: A comparative analysis of conventional and machine learning approaches," Economic Analysis and Policy, Elsevier, volume 89, issue C, pages 788-833, DOI: 10.1016/j.eap.2025.12.002.
• De Rosa, Mauricio & Vilá, Joan, 2026, "Taxing the rich in Latin America: Effects of a wealth tax on revenue and distribution," Economic Analysis and Policy, Elsevier, volume 90, issue C, pages 1440-1466, DOI: 10.1016/j.eap.2026.02.016.
• Koppolu, Sarath Chandra & Hoeschle, Lisa & Maruejols, Lucie, 2026, "Potential for energy poverty reduction by error decomposition with machine learning," Economic Analysis and Policy, Elsevier, volume 90, issue C, pages 417-435, DOI: 10.1016/j.eap.2026.01.032.
• Goosen, Kasper & de Vette, Nander & Willem van den End, Jan, 2026, "The impact of uncertainty on economic tail risk: bank capital as mitigating factor," Economic Analysis and Policy, Elsevier, volume 91, issue C, pages 1469-1485, DOI: 10.1016/j.eap.2026.05.001.
• Yanotti, María B. & Navon, Yonatan & de Silva, Ashton & Angelopoulos, Sveta & Sinclair, Sarah, 2026, "The walking economy: Pedestrian counts as a real-time indicator of regional economic activity," Economic Analysis and Policy, Elsevier, volume 92, issue C, pages 641-662, DOI: 10.1016/j.eap.2026.06.032.
• Shah, Sayar Ahmad & Garg, Bhavesh, 2026, "Dynamics of exchange rate pass-through: The role of pricing strategies and economic shocks," Economic Modelling, Elsevier, volume 154, issue C, DOI: 10.1016/j.econmod.2025.107353.
• Raj, Prakash & Selvaraju, N., 2026, "Bitcoin volatility modeling with realized measures and jump dynamics," Economic Modelling, Elsevier, volume 160, issue C, DOI: 10.1016/j.econmod.2026.107615.
• Zeng, Tao & Wang, Kaixin & Fan, Yanjing & Liu, Xiaobin, 2026, "Systemic default probability and return predictability: Evidence from China," Economic Modelling, Elsevier, volume 160, issue C, DOI: 10.1016/j.econmod.2026.107617.
• Prüser, Jan & Blagov, Boris, 2026, "Improving inference and forecasting in VAR models using cross-sectional information," Economic Modelling, Elsevier, volume 160, issue C, DOI: 10.1016/j.econmod.2026.107618.
• Pan, Zhiyuan & Zhou, Yue & Huang, Chuwen, 2026, "The economic value of variable selection methods: Evidence from volatility forecasting," Economic Modelling, Elsevier, volume 163, issue C, DOI: 10.1016/j.econmod.2026.107739.
• Dallari, Pietro & Gattini, Luca, 2026, "How severe are euro area regulatory stress test scenarios? Evidence from a growth-at-risk framework," Economic Modelling, Elsevier, volume 164, issue C, DOI: 10.1016/j.econmod.2026.107782.
• Guerzoni, Marco & Riso, Luigi & Zoia, M. Grazia, 2026, "Extreme weather events as the main driver of electricity price volatility in Italy: A GARCH-MIDAS approach with machine learning-based variable selection," The North American Journal of Economics and Finance, Elsevier, volume 81, issue C, DOI: 10.1016/j.najef.2025.102512.
• Aslam, Adnan & Brahmana, Rayenda Khresna, 2026, "Systemic spillovers in high-growth private market sectors: determinants and portfolio implications," The North American Journal of Economics and Finance, Elsevier, volume 82, issue C, DOI: 10.1016/j.najef.2025.102579.
• Bonaccolto, Giovanni & Karmakar, Sayar & Bouri, Elie & Gupta, Rangan, 2026, "Spillover and predictability of volatility of 50 major cryptocurrencies: Evidence from a LASSO-regularized Quantile VAR," The North American Journal of Economics and Finance, Elsevier, volume 85, issue C, DOI: 10.1016/j.najef.2026.102668.
• Ghosh, Indranil & Alfaro-Cortés, Esteban & Gámez, Matías & García-Rubio, Noelia, 2026, "Predictive influence of Reddit sentiment on AI and tech moguls for digital financial assets: evidence from KAN and DES methodology," The North American Journal of Economics and Finance, Elsevier, volume 85, issue C, DOI: 10.1016/j.najef.2026.102672.
• Wang, Zhufeng & Wang, Lu, 2026, "Macroeconomic forecasting based on high-dimensional datasets: a smooth transition three pass regression filter model," The North American Journal of Economics and Finance, Elsevier, volume 86, issue C, DOI: 10.1016/j.najef.2026.102697.
• Garcia-Jorcano, Laura & Sanchis-Marco, Lidia, 2026, "Extreme climate and natural disaster risk in financial markets: A CoES approach," The North American Journal of Economics and Finance, Elsevier, volume 86, issue C, DOI: 10.1016/j.najef.2026.102700.
• Caldeira, João F. & Cordeiro, Werley C., 2026, "Decomposing nominal and real yield curves and inflation forecasting: Evidence from Brazil," Economics Letters, Elsevier, volume 258, issue C, DOI: 10.1016/j.econlet.2025.112712.
• Goulet Coulombe, Philippe & Klieber, Karin, 2026, "An adaptive moving average for macroeconomic monitoring," Economics Letters, Elsevier, volume 259, issue C, DOI: 10.1016/j.econlet.2025.112773.
• Quinlan, Rory & Pinheiro, Roberto, 2026, "BLS payroll revisions: Forecasting recessions," Economics Letters, Elsevier, volume 261, issue C, DOI: 10.1016/j.econlet.2026.112859.
• Morita, Hiroshi, 2026, "Forecasting GDP growth with stock returns: Time-series or cross-sectional information?," Economics Letters, Elsevier, volume 263, issue C, DOI: 10.1016/j.econlet.2026.112946.
• Zevallos, Mauricio & Rubesam, Alexandre, 2026, "Finite-sample properties of the Campbell and Thompson out-of-sample R2," Economics Letters, Elsevier, volume 265, issue C, DOI: 10.1016/j.econlet.2026.113011.
• Guidolin, Massimo & Ionta, Serena, 2026, "Predicting commodity returns with climate variables: Statistical loss functions vs. economic value," Economics Letters, Elsevier, volume 265, issue C, DOI: 10.1016/j.econlet.2026.113028.
• Stosik, Jan & Zaremba, Adam, 2026, "Short-term reversal persists globally—If properly measured," Economics Letters, Elsevier, volume 267, issue C, DOI: 10.1016/j.econlet.2026.113113.
• Chen, Sihan & Yang, Shenggang & Lan, Xiaomei, 2026, "Three horizon-specific drivers of gold prices with Iterated Dynamic Model Averaging," Economics Letters, Elsevier, volume 268, issue C, DOI: 10.1016/j.econlet.2026.113147.
• Shin, Minchul, 2026, "An auditable AI agent loop for empirical economics: A case study in forecast combination," Economics Letters, Elsevier, volume 268, issue C, DOI: 10.1016/j.econlet.2026.113164.
• Guo, Hongfei & Marín, J.M. & Veiga, Helena, 2026, "Target-driven Bayesian stacking of realised and implied volatility forecasts," Economics Letters, Elsevier, volume 268, issue C, DOI: 10.1016/j.econlet.2026.113166.
• Patton, Andrew J. & Zhang, Haozhe, 2026, "Bespoke realized volatility: Tailored measures of risk for volatility prediction," Journal of Econometrics, Elsevier, volume 254, issue PA, DOI: 10.1016/j.jeconom.2025.106122.
• Lunsford, Kurt G. & West, Kenneth D., 2026, "An empirical evaluation of some long-horizon macroeconomic forecasts," Journal of Econometrics, Elsevier, volume 255, issue C, DOI: 10.1016/j.jeconom.2026.106221.
• Gao, Zhan & Lee, Ji Hyung & Mei, Ziwei & Shi, Zhentao, 2026, "LASSO inference for high dimensional predictive regressions," Journal of Econometrics, Elsevier, volume 255, issue C, DOI: 10.1016/j.jeconom.2026.106240.
• Menzel, Konrad, 2026, "Transfer estimates for causal effects across heterogeneous sites," Journal of Econometrics, Elsevier, volume 255, issue C, DOI: 10.1016/j.jeconom.2026.106250.
• Kumbhakar, Subal C. & Mallick, Sushanta K., 2026, "Bayesian methods in economics and finance: A unified survey and taxonomy," Journal of Econometrics, Elsevier, volume 256, issue PB, DOI: 10.1016/j.jeconom.2026.106269.
• Sun, Yuying & Chen, Feng & Gao, Jiti, 2026, "Model averaging for time–varying vector autoregressions," Journal of Econometrics, Elsevier, volume 257, issue C, DOI: 10.1016/j.jeconom.2026.106308.
• Maddock, Luke & Nelson, Frank & Altringer, Levi & McKee, Sophie C., 2026, "Estimating the value of ecosystem services: A machine learning approach for Missouri wetlands," Ecosystem Services, Elsevier, volume 79, issue C, DOI: 10.1016/j.ecoser.2026.101849.
• Garcia, Pablo & Jacquinot, Pascal & Lenarčič, Črt & Mavromatis, Kostas & Papadopoulou, Niki & Silgado-Gómez, Edgar, 2026, "Green transition in the euro area: Domestic and global factors," European Economic Review, Elsevier, volume 182, issue C, DOI: 10.1016/j.euroecorev.2025.105206.
• Li, Mengheng & Mendieta-Muñoz, Ivan, 2026, "Unpacking trend inflation: Evidence from a factor correlated unobserved components model of sticky and flexible prices," European Economic Review, Elsevier, volume 187, issue C, DOI: 10.1016/j.euroecorev.2026.105377.
• Wang, Haibo, 2026, "Modeling bank systemic risk of emerging markets under geopolitical shocks: Empirical evidence from BRICS countries," Emerging Markets Review, Elsevier, volume 74, issue C, DOI: 10.1016/j.ememar.2026.101502.
• Bonato, Matteo & Gupta, Rangan & Pierdzioch, Christian, 2026, "Do shortages forecast aggregate and sectoral U.S. stock market realized variance? Evidence from a century of data," Journal of Empirical Finance, Elsevier, volume 86, issue C, DOI: 10.1016/j.jempfin.2026.101726.
• Babiak, Mykola & Baruník, Jozef, 2026, "Deep learning, predictability, and optimal portfolio returns," Journal of Empirical Finance, Elsevier, volume 87, issue C, DOI: 10.1016/j.jempfin.2026.101705.
• Cheng, Mingmian, 2026, "Sparse heterogeneous auto-regressive model for volatility forecasting," Journal of Empirical Finance, Elsevier, volume 87, issue C, DOI: 10.1016/j.jempfin.2026.101708.
• Li, Gang & Wang, Shuqi & Wei, K.C. John, 2026, "What drives retail investors’ overconfidence? The role of information acquisition costs," Journal of Empirical Finance, Elsevier, volume 87, issue C, DOI: 10.1016/j.jempfin.2026.101709.
• Jiao, Lei & Zhou, Qing (Clara), 2026, "Economic conditions and portfolio tail risk: A probability-weighted simulation approach," Journal of Empirical Finance, Elsevier, volume 87, issue C, DOI: 10.1016/j.jempfin.2026.101715.
• Rahimikia, Eghbal & Poon, Ser-Huang, 2026, "Machine learning for realised volatility forecasting," Journal of Empirical Finance, Elsevier, volume 88, issue C, DOI: 10.1016/j.jempfin.2026.101739.
• Nam, Kyungsik & Seo, Won-Ki, 2026, "Nonlinear temperature sensitivity of residential electricity demand: Evidence from a distributional regression approach," Energy Economics, Elsevier, volume 153, issue C, DOI: 10.1016/j.eneco.2025.109076.
• Ghelasi, Paul & Ziel, Florian, 2026, "A data-driven merit order: Learning a fundamental electricity price model," Energy Economics, Elsevier, volume 154, issue C, DOI: 10.1016/j.eneco.2025.109114.
• Garratt, Anthony & Petrella, Ivan & Zhang, Yunyi, 2026, "The predictive content of U.S. Energy Information Administration oil market forecasts," Energy Economics, Elsevier, volume 156, issue C, DOI: 10.1016/j.eneco.2026.109214.
• Das, Abhinav & Schlüter, Stephan & Schneider, Lorenz, 2026, "Regime-aware conditional neural processes with multi-criteria decision support for operational electricity price forecasting," Energy Economics, Elsevier, volume 157, issue C, DOI: 10.1016/j.eneco.2026.109233.
• Theile, Philipp, 2026, "The shape of U — On the structure of utility from electric vehicle charging," Energy Economics, Elsevier, volume 161, issue C, DOI: 10.1016/j.eneco.2026.109519.
• Proz, Jeremy & Huber, Martin & Marin, Ivan, 2026, "Machine learning for detecting collusion and capacity withholding in wholesale electricity markets," Energy Economics, Elsevier, volume 162, issue C, DOI: 10.1016/j.eneco.2026.109557.
• Zhang, Yuetong, 2026, "The dual burden of energy poverty and climate exposure," Energy Economics, Elsevier, volume 162, issue C, DOI: 10.1016/j.eneco.2026.109560.
• Hubert, Emma & Lolas, Dimitrios & Sircar, Ronnie, 2026, "Trading electrons: Predicting DART spread spikes in ISO electricity markets," Energy Economics, Elsevier, volume 162, issue C, DOI: 10.1016/j.eneco.2026.109590.
• Díaz-Díaz, Raimundo & Galiano, Aida & Martín-Álvarez, Juan Manuel & Barrientos-Marín, Jorge, 2026, "From policy to reality: Forecasting Spain's vehicle fleet trajectory toward 2030 climate targets," Energy Policy, Elsevier, volume 215, issue C, DOI: 10.1016/j.enpol.2026.115298.
• Yu, Deshui & Tang, Jiachen & Zhou, Mingtao, 2026, "Trade policy uncertainty and stock returns: A tale of two periods," International Review of Financial Analysis, Elsevier, volume 109, issue C, DOI: 10.1016/j.irfa.2025.104789.
• Klinkowska, Olga & Zadorozhna, Olha, 2026, "The yield curve strikes back: New evidence of its predictive power for economic activity and inflation," International Review of Financial Analysis, Elsevier, volume 113, issue C, DOI: 10.1016/j.irfa.2026.105128.
• Čech, František & Kočenda, Evžen, 2026, "Tail risk forecasting in the U.S. Treasury futures market," International Review of Financial Analysis, Elsevier, volume 118, issue C, DOI: 10.1016/j.irfa.2026.105329.
• Bao, Guanhao & Cui, Baisheng & Zhang, Zhen, 2026, "To what extent does monetary policy uncertainty affect inflation forecasting?," International Review of Financial Analysis, Elsevier, volume 118, issue C, DOI: 10.1016/j.irfa.2026.105334.
• Bonaccolto, Giovanni & Caporin, Massimiliano & Cepni, Oguzhan & Gupta, Rangan, 2026, "Forecasting realized volatility of state-level stock markets of the United States: The role of sentiment," International Review of Financial Analysis, Elsevier, volume 118, issue C, DOI: 10.1016/j.irfa.2026.105376.
• Li, Jupeng & Hou, Weijie & Zhang, Zongxin, 2026, "A coupled autoregressive extreme-value model for dynamic tail risk with risk spirals," Finance Research Letters, Elsevier, volume 105, issue C, DOI: 10.1016/j.frl.2026.110187.
• Sheng, Xin & Cepni, Oguzhan & Gupta, Rangan & Markovski, Minko, 2026, "Mixed frequency machine learning forecasting of the growth of real gross fixed capital formation in the United States: the role of extreme weather conditions," Finance Research Letters, Elsevier, volume 106, issue C, DOI: 10.1016/j.frl.2026.110271.
• Bonato, Matteo & Cepni, Oguzhan & Gupta, Rangan & Pierdzioch, Christian, 2026, "Credit standards: A new predictor of U.S. stock market realized volatility," Finance Research Letters, Elsevier, volume 106, issue C, DOI: 10.1016/j.frl.2026.110298.
• Lacombe, Donald J. & Yuan, Yuan & Qian, Pengyu, 2026, "A Bayesian Student-t specification for the MF2-GARCH model with applications in equity and crypto markets," Finance Research Letters, Elsevier, volume 107, issue C, DOI: 10.1016/j.frl.2026.110283.
• Wang, Chenguang & Yao, Kai & Liu, Jinpeng, 2026, "Salience, asymmetric effect and stock returns," Finance Research Letters, Elsevier, volume 107, issue C, DOI: 10.1016/j.frl.2026.110360.
• Huang, Junhui & Wu, Jianbin, 2026, "Do LLM-based overnight news indicators add value beyond A50 futures?," Finance Research Letters, Elsevier, volume 107, issue C, DOI: 10.1016/j.frl.2026.110367.
• Frydrych, Sylwia, 2026, "Transition risk and ESG materiality in credit rating downgrades: evidence from explainable machine learning," Finance Research Letters, Elsevier, volume 107, issue C, DOI: 10.1016/j.frl.2026.110408.
• Atak, Alev, 2026, "Volatility regime probabilities and the horizon profile of tail risk," Finance Research Letters, Elsevier, volume 108, issue C, DOI: 10.1016/j.frl.2026.110425.
• Su, Xiaoman & Qi, Shuyuan, 2026, "The compounding cost of price limits: A multi-period perspective on tail risk," Finance Research Letters, Elsevier, volume 108, issue C, DOI: 10.1016/j.frl.2026.110443.
• Rafizadeh, Nima, 2026, "Pricing scarcity: A machine learning test of water futures efficiency," Finance Research Letters, Elsevier, volume 108, issue C, DOI: 10.1016/j.frl.2026.110486.
• Yatawara, Anjana, 2026, "Good portfolios from bad forecasts: The anatomy of LLM volatility estimates," Finance Research Letters, Elsevier, volume 109, issue C, DOI: 10.1016/j.frl.2026.110572.
• Li, Xiaowei & Chen, Jian & Liu, Yangshu, 2026, "Option implied asymmetric correlation risk and stock returns," Finance Research Letters, Elsevier, volume 110, issue C, DOI: 10.1016/j.frl.2026.110575.
• Zhong, Yilin & Fu, Yuqi & Zhu, Sixuan, 2026, "Foundation models do not beat simple volatility benchmarks: Evidence from 5000 Chinese stocks," Finance Research Letters, Elsevier, volume 110, issue C, DOI: 10.1016/j.frl.2026.110606.
• Monteux, Manou & Arcuri, Maria Cristina & Gandolfi, Gino & Riani, Marco, 2026, "Transaction-based machine learning under restricted feature availability for short-term credit distress under a structural shock," Finance Research Letters, Elsevier, volume 111, issue C, DOI: 10.1016/j.frl.2026.110642.