Research classified by Journal of Economic Literature (JEL) codes

1. Forecasting

2026

• Dimitris Anastasiou & Apostolos Katsafados & Christos Tzomakas, 2026, "Banks’ stock price crash risk prediction with textual analysis: a machine learning approach," Annals of Operations Research, Springer, volume 357, issue 1, pages 89-111, February, DOI: 10.1007/s10479-025-06567-y.
• Philippe Bertrand & Jean-luc Prigent, 2026, "On the performance of factor investing: an analysis based on constant mix and buy-and-hold strategies," Annals of Operations Research, Springer, volume 357, issue 1, pages 531-563, February, DOI: 10.1007/s10479-025-06644-2.
• Priscila Espinosa & Maria Teresa Balaguer-Coll & Jose M. Pavía & Emili Tortosa-Ausina, 2026, "Modelling regional economic resilience to climate disasters: A recovery forecasting framework illustrated by the 2024 Valencia floods," The Annals of Regional Science, Springer;Western Regional Science Association, volume 75, issue 3, pages 1-34, September, DOI: 10.1007/s00168-026-01548-w.
• Xiaoqing Luo, 2026, "When simplicity fails: forecasting Mainland Chinese tourist arrivals in Macao during structural breaks with a hybrid economic-search model," Asia-Pacific Journal of Regional Science, Springer, volume 10, issue 1, pages 1-31, March, DOI: 10.1007/s41685-026-00419-8.
• Ayben Koy & Semra Demir & Andaç Batur Çolak, 2026, "Google trend index as an investor sentiment proxy in cryptomarket: nonlinear relationships with cryptomarket and predicting bitcoin returns with machine learning approach," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, volume 34, issue 2, pages 575-595, June, DOI: 10.1007/s10100-025-01012-8.
• Vaibhav Gagneja & Mayank Gupta & Sanjay Batish & Poonam Saini & Sudesh Rani, 2026, "ES-LSTM: a hybrid model for accurate time series forecasting in financial markets," Digital Finance, Springer, volume 8, issue 1, pages 1-21, March, DOI: 10.1007/s42521-025-00173-0.
• Qizhao Chen & Hiroaki Kawashima, 2026, "Sentiment-aware stock price prediction with transformer and LLM-generated formulaic alpha," Digital Finance, Springer, volume 8, issue 2, pages 1-28, June, DOI: 10.1007/s42521-026-00176-5.
• Hoang Anh Nguyen & Nhat Hoang Bach, 2026, "QI-HRNN: a quantum-inspired hybrid framework for resilient currency forecasting under extreme market conditions," Digital Finance, Springer, volume 8, issue 2, pages 1-40, June, DOI: 10.1007/s42521-026-00189-0.
• Huyen Giang Thi Thu & Thang Viet Doan & Ha-Bang Ban & Tai Le Quy, 2026, "An experimental study on fairness-aware machine learning for credit scoring problems," Digital Finance, Springer, volume 8, issue 3, pages 1-26, September, DOI: 10.1007/s42521-026-00202-6.
• András Szeberényi & Mátyás Imre Kovács, 2026, "Fear, greed and bitcoin return distributions: evidence from digital asset market states," Digital Finance, Springer, volume 8, issue 3, pages 1-29, September, DOI: 10.1007/s42521-026-00218-y.
• Yuhang Li & Hyoung-Goo Kang & Myeongsu Choi, 2026, "Protocol liquidity, rule-based benchmarks, and USDT yield predictability in DeFi lending," Digital Finance, Springer, volume 8, issue 4, pages 1-26, December, DOI: 10.1007/s42521-026-00223-1.
• Carlos Baquero & Daniel Tinoco, 2026, "The naive–power law blend as a robust baseline for bitcoin price forecasting," Digital Finance, Springer, volume 8, issue 4, pages 1-39, December, DOI: 10.1007/s42521-026-00226-y.
• Ahmed S. Wafi & Sherif El-Halaby & Sameh Abd-ElMaksoud Aboul-Dahab, 2026, "Regime-dependent bitcoin volatility forecasting under alternative information sets: evidence from econometric, deep learning, and hybrid models," Digital Finance, Springer, volume 8, issue 4, pages 1-46, December, DOI: 10.1007/s42521-026-00229-9.
• Junda Wu & Qiqi Gu & Jian Yao & Jiajing Sun, 2026, "Defining and monitoring stablecoin depegging risk: a rolling downside-threshold framework," Digital Finance, Springer, volume 8, issue 4, pages 1-38, December, DOI: 10.1007/s42521-026-00232-0.
• Christos Tzomakas, 2026, "Monetary policy transmission and the yield curve: the role of external market factors against the backdrop of Brexit," Empirical Economics, Springer, volume 70, issue 1, pages 1-42, January, DOI: 10.1007/s00181-025-02874-2.
• Alena Skolkova, 2026, "Model averaging with ridge regularization," Empirical Economics, Springer, volume 70, issue 2, pages 1-19, February, DOI: 10.1007/s00181-025-02866-2.
• Elliot Beck & Michael Wolf, 2026, "Forecasting inflation with the hedged random forest," Empirical Economics, Springer, volume 70, issue 2, pages 1-36, February, DOI: 10.1007/s00181-025-02879-x.
• Visa Kuntze & Henri Nyberg & Samuel Rauhala, 2026, "Similarity-based path forecasting of US recession periods," Empirical Economics, Springer, volume 70, issue 3, pages 1-18, March, DOI: 10.1007/s00181-026-02893-7.
• Jan Willem Van den End, 2026, "Does uncertainty raise the probability of a recession?," Empirical Economics, Springer, volume 70, issue 6, pages 1-32, June, DOI: 10.1007/s00181-026-02914-5.
• Karsten Reichold, 2026, "Forecasting post-pandemic tourism demand: random forests and calendar variables," Empirical Economics, Springer, volume 71, issue 1, pages 1-39, July, DOI: 10.1007/s00181-026-02944-z.
• Haoxin Zhao & Kazeem O. Isah, 2026, "Understanding ESG-mediated climate risk impacts on corporate profits: sectoral dynamics and predictive evidence from an ADL–MIDAS framework," Empirical Economics, Springer, volume 71, issue 1, pages 1-36, July, DOI: 10.1007/s00181-026-02945-y.
• Pourya Valizadeh & Akash Issar & Henry L. Bryant & Bart L. Fischer & Rebecca Nemec Boehm, 2026, "Forecasting the path of SNAP spending using state-level panel data models," Empirical Economics, Springer, volume 71, issue 1, pages 1-73, July, DOI: 10.1007/s00181-026-02947-w.
• Seho Park & Kahyun Lee, 2026, "Predicting brand share after LOE in chronic disease market using machine learning," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), volume 27, issue 3, pages 699-714, April, DOI: 10.1007/s10198-025-01845-9.
• Jan Radovan & Igor Masten, 2026, "Hybrid expectations, financial frictions, and macroeconomic dynamics in a small open economy within a monetary union," Eurasian Economic Review, Springer;Eurasia Business and Economics Society, volume 16, issue 3, pages 1373-1457, September, DOI: 10.1007/s40822-025-00350-x.
• Arthur Jonath & Fred Khorasani & John O’Connell, 2026, "The consumer-to-producer temperature gradient predicts leading indicators: a new economic measurement based on physical principles and cause and effect," Financial Innovation, Springer;Southwestern University of Finance and Economics, volume 12, issue 1, pages 1-24, December, DOI: 10.1186/s40854-025-00805-9.
• Radmir Mishelevich Leushuis & Nicolai Petkov, 2026, "Advances in forecasting realized volatility: a review of methodologies," Financial Innovation, Springer;Southwestern University of Finance and Economics, volume 12, issue 1, pages 1-29, December, DOI: 10.1186/s40854-025-00809-5.
• Hugo Gobato Souto & Amir Moradi, 2026, "Enhancing financial risk management: a novel multivariate neural network approach for realized covariance matrix prediction," Financial Innovation, Springer;Southwestern University of Finance and Economics, volume 12, issue 1, pages 1-26, December, DOI: 10.1186/s40854-025-00816-6.
• Heng Xiong & Yuxuan Guo & Ričardas Zitikis, 2026, "Beyond no-claims discount: a learning-embedded telematics-driven pricing system for dynamic premium adjustments," Financial Innovation, Springer;Southwestern University of Finance and Economics, volume 12, issue 1, pages 1-38, December, DOI: 10.1186/s40854-026-00928-7.
• Baffour Osei & Abigail Boatemaa & Isaac Nyame & Gabriel Osei Forkuo, 2026, "Evaluating machine learning and econometric models for inflation forecasting: evidence from a Sub-Saharan African panel," Future Business Journal, Springer, volume 12, issue 1, pages 1-21, December, DOI: 10.1186/s43093-026-01003-4.
• Amit Kumar Singh & Monomita Nandy & Suman Lodh & Shivani Kalra, 2026, "Sector signals: machine learning insights into IPO pricing dynamics," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, volume 17, issue 11, pages 3245-3263, November, DOI: 10.1007/s13198-026-03155-6.
• Manish Choudhury & Amit Choudhury & Kaustav Dutta & Dhruba Das, 2026, "Inferential aspects of a Markovian queuing system with no waiting space," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, volume 17, issue 11, pages 3418-3455, November, DOI: 10.1007/s13198-026-03161-8.
• Ameneh Khadivar & Payvand Mirzaeian Khamseh & Raha Basraei & Shib Sankar Sana, 2026, "Enhancing the price estimation in consulting services using empirically developed ANN," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, volume 17, issue 9, pages 2619-2634, September, DOI: 10.1007/s13198-025-03094-8.
• Herbert Dawid & Dirk Kohlweyer & Melina Schleef & Christian Stummer & Frederik Tolkmitt, 2026, "Navigating uncertainty in the presence of negative word of mouth: how different consumer modes impact innovation diffusion," Journal of Business Economics, Springer, volume 96, issue 7, pages 847-874, September, DOI: 10.1007/s11573-026-01266-x.
• Bibiana Lanzilotta & Gabriela Mordecki & Pablo Tapie & Joaquín Torres Pérez, 2026, "Structural Breaks in Uncertainty and the Business Cycle in a Small and Open Economy," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), volume 22, issue 1, pages 1-28, April, DOI: 10.1007/s41549-025-00117-y.
• Afees A. Salisu & Abeeb O. Olaniran, 2026, "Energy market uncertainty and economic conditions at the global and U.S. State levels," Journal of Economics and Finance, Springer;Academy of Economics and Finance, volume 50, issue 1, pages 1-51, December, DOI: 10.1007/s12197-025-09739-5.
• Elie Bouri & Rangan Gupta & Asingamaanda Liphadzi & Christian Pierdzioch, 2026, "Forecasting the volatility of stock returns in the G7 countries over centuries: the role of climate risks," Journal of Economics and Finance, Springer;Academy of Economics and Finance, volume 50, issue 1, pages 1-32, December, DOI: 10.1007/s12197-026-09751-3.
• Marc Mukendi Mpanda, 2026, "A coupled realised real-time EGARCH model with filtered historical simulation," Journal of Economics and Finance, Springer;Academy of Economics and Finance, volume 50, issue 1, pages 1-40, December, DOI: 10.1007/s12197-026-09782-w.
• Fabio Gobbi & Sabrina Mulinacci, 2026, "Forecasting volatility in periods of financial turbulence: a new state-dependent model," Journal of Economics and Finance, Springer;Academy of Economics and Finance, volume 50, issue 1, pages 1-28, December, DOI: 10.1007/s12197-026-09794-6.
• Afees A. Salisu & Ahamuefula E. Ogbonna & Rangan Gupta & Luis A. Gil-Alana, 2026, "Supply disruptions and predictability of oil return volatility: a GARCH-MIDAS approach," Journal of Economics and Finance, Springer;Academy of Economics and Finance, volume 50, issue 1, pages 1-33, December, DOI: 10.1007/s12197-026-09796-4.
• Bilgehan Tekin, 2026, "Bitcoin as a Behavioral Bellwether: Unveiling the Bandwagon Effect and Investor Sensitivity in the NFT Landscape," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), volume 17, issue 2, pages 3714-3739, April, DOI: 10.1007/s13132-025-02788-5.
• Nandhini Sridhar & Saumitra Bhaduri, 2026, "Forecasting Likelihood and Severity of Recessions in India: A Machine Learning Approach," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), volume 24, issue 3, pages 595-627, September, DOI: 10.1007/s40953-026-00502-z.
• Ibnu Rubianto Santriawan Kuncoro & Agung Purnomo, 2026, "Exploring the Global Landscape of Digital Social Innovation in the Tourism Context: Understanding Trend Mapping and Projection Modeling," Springer Proceedings in Business and Economics, Springer, in: Vicky Katsoni, "Synergizing Management, Culture, and Arts for Tourism Development - Vol. 1", DOI: 10.1007/978-3-032-17545-8_16.
• Konstantinos Gkillas & Constantinos Halkiopoulos, 2026, "AI-Driven Smart Tourism: Leveraging Deep Learning and Financial Econometrics for Predictive Risk Management and Dynamic Destination Optimization," Springer Proceedings in Business and Economics, Springer, in: Vicky Katsoni, "Synergizing Management, Culture, and Arts for Tourism Development - Vol. 1", DOI: 10.1007/978-3-032-17545-8_17.
• Nikolina Christou & Vassiliki Karioti, 2026, "Forecasting Tourist Indicators in Greece: A Comparative Evaluation of Statistical and Deep Learning Models," Springer Proceedings in Business and Economics, Springer, in: Vicky Katsoni, "Synergizing Management, Culture, and Arts for Tourism Development - Vol. 1", DOI: 10.1007/978-3-032-17545-8_22.
• Tonmoy Chatterjee & Nilendu Chatterjee, 2026, "Digitalisation, skill development and sustainable economic growth: theories and empirics in the context of BRICS," Quality & Quantity: International Journal of Methodology, Springer, volume 60, issue 4, pages 11647-11680, August, DOI: 10.1007/s11135-025-02144-4.
• Tooraj Karimi & Mohamad Ahmadian, 2026, "Analyzing post-pandemic tourism recovery: a grey system theory approach with high-accuracy small-sample modeling," Quality & Quantity: International Journal of Methodology, Springer, volume 60, issue 4, pages 12525-12545, August, DOI: 10.1007/s11135-025-02460-9.
• Mohanan Moni & Sreeraj Venuraj & Biju Ajithakumari Vijayappan Nair & Darko B. Vuković & Adel Dalal, 2026, "A temporal-fusion-based speculation index: early-warning signals from trading activity," Quality & Quantity: International Journal of Methodology, Springer, volume 60, issue 4, pages 14019-14047, August, DOI: 10.1007/s11135-026-02764-4.
• Sadik Aden Dirir, 2026, "Predictive modeling of electric vehicle adoption in OECD nations: an empirical assessment," Quality & Quantity: International Journal of Methodology, Springer, volume 60, issue 5, pages 15855-15883, October, DOI: 10.1007/s11135-026-02805-y.
• Afees A. Salisu & Sheriff Badmus, 2026, "Can AI news improve the out-of-sample forecasts of risk premia and volatility in the U.S. stock market?," Quality & Quantity: International Journal of Methodology, Springer, volume 60, issue 5, pages 16125-16144, October, DOI: 10.1007/s11135-026-02816-9.
• Philipp Kronenberg, 2026, "A high-frequency GDP indicator for Switzerland," Swiss Journal of Economics and Statistics, Springer;Swiss Society of Economics and Statistics, volume 162, issue 1, pages 1-55, December, DOI: 10.1186/s41937-026-00157-w.
• Gourav Roy & Debashish Nath & Arifur Rahman, 2026, "Technical analysis and capital market predictability: an econometric–Machine Learning Investigation," SN Business & Economics, Springer, volume 6, issue 12, pages 1-24, December, DOI: 10.1007/s43546-026-01557-z.
• Sanjib Kumar Mishra & Sasmita Mishra & Rojalina Priyadarshini & Zefree Lazarus Mayaluri, 2026, "Explainable business intelligence for auditable vendor segmentation and payment-traceability monitoring in SAP cross-company check payments," SN Business & Economics, Springer, volume 6, issue 7, pages 1-33, July, DOI: 10.1007/s43546-026-01239-w.
• Mohd Redzuan Ahmad & Mohd Herwan Sulaiman, 2026, "Machine learning-based gold price forecasting: a bibliometric review of trends, methods, and future directions," SN Business & Economics, Springer, volume 6, issue 8, pages 1-38, August, DOI: 10.1007/s43546-026-01299-y.
• Francis Bismans, 2026, "Radical Uncertainty, Probability and Econometrics," Springer Books, Springer, chapter 36, in: Chicot Eboué, "The Palgrave Handbook of Public Debt and Policy Mix", DOI: 10.1007/978-3-032-12508-8_36.
• David J. C. Dinis, 2026, "Low Default Portfolios – From the Usefulness of Pluriannual Data to the Inconsistency of Multi period Estimation," Journal of Applied Finance & Banking, SCIENPRESS Ltd, volume 16, issue 4, pages 1-2.
• Rakshay Pawar, 2026, "Regime-Gated Tail Transfer: Reliable Cross-Industry Machine Learning for Value-at-Risk and Expected Shortfall," Journal of Applied Finance & Banking, SCIENPRESS Ltd, volume 16, issue 6, pages 1-3.
• Sukriti Khanal & Farhan Munir, 2026, "Artificial Intelligence in Financial Analytics: An Integrative Review of Financial Modeling, Forecasting, and Financial Controls," Journal of Applied Finance & Banking, SCIENPRESS Ltd, volume 16, issue 6, pages 1-6.
• Zhiyang Jia & Snorre Skagseth & Thor O. Thoresen & Trine E. Vattø, 2026, "Apractical framework for behavioral microsimulation using external evidence," Discussion Papers, Statistics Norway, Research Department, number 1034, Feb.
• Carlos Montes-Galdón & Joan Paredes & Elias Wolf, 2026, "A robust approach to tilting: parametric relative entropy," Working and Discussion Papers, Research Department, National Bank of Slovakia, number WP 2/2026, Feb.
• Hanjo Odendaal, 2026, "Animal spirits or political risk? Separating confidence channels in an emerging economy," Working Papers, Stellenbosch University, Department of Economics, number 08/2026.
• Sarthak S. Behera & Hyeongwoo Kim & Soohyon Kim, 2026, "Asymmetric Roles of Macroeconomic Variables in the Real Exchange Rate: Insights from U.S.-Korea Data," International Economic Journal, Taylor & Francis Journals, volume 40, issue 1, pages 84-113, January, DOI: 10.1080/10168737.2026.2613859.
• Kurt G. Lunsford & Kenneth D. West, 2026, "Random Walk Forecasts of Stationary Processes Have Low Bias," Journal of Business & Economic Statistics, Taylor & Francis Journals, volume 44, issue 2, pages 537-546, April, DOI: 10.1080/07350015.2025.2541724.
• Altug Aydemir & Ali Sevim, 2026, "Google Searches, House Prices and Transactions: Signs of Regime Dependence around Turkiye’s Monetary Tightening," Working Papers, Research and Monetary Policy Department, Central Bank of the Republic of Turkey, number 2619.
• Justus Holman & Yicong Lin & Andre Lucas & Anne Opschoor, 2026, "Joint Eigenvector and Eigenvalue Dynamics with an Application to Time-Varying Covariance Matrices," Tinbergen Institute Discussion Papers, Tinbergen Institute, number 26-060/III, Aug.
• Ayla Jungbluth & Johannes Lederer & Simon Trimborn, 2026, "Market-Informed Networks for Modeling and Forecast Evaluation of Financial Extremes," Tinbergen Institute Discussion Papers, Tinbergen Institute, number 26-070/III, Sep.
• Garratt Anthony & Petrella Ivan & Zhang Yunyi, 2026, "The Predictive Content of U.S. Energy Information Administration Oil Market Forecasts," Working papers, Department of Economics, Social Studies, Applied Mathematics and Statistics (Dipartimento di Scienze Economico-Sociali e Matematico-Statistiche), University of Torino, number 104, Mar.
• Pedro Isaac Chavez-Lopez & Tae-Hwy Lee, 2026, "Quantile-Covariance Three-Pass Regression Filter," Working Papers, University of California at Riverside, Department of Economics, number 202605, Aug.
• Tae-Hwy Lee & Daanish Padha, 2026, "Forecasting Using Supervised Factors and Idiosyncratic Elements," Working Papers, University of California at Riverside, Department of Economics, number 202607, Oct.
• ANGHEL, Bogdan Ionut & MARINOV, Georgi & DONOIU, Paul Cristian, 2026, "Market Regimes And Portfolio Allocation: Evidence From The Romanian Equity Market Using Hidden Markov Models And Xgboost," Studii Financiare (Financial Studies), Centre of Financial and Monetary Research "Victor Slavescu", volume 30, issue 2, pages 89-107, June, DOI: https://doi.org/10.65672/fs.2026.2..
• Yachou Najlae & Abahman Omar & Hakimi Khalid, 2026, "Designing an LSTM-Based Model for Financial Asset Forecasting Using Machine Learning," Central European Economic Journal, Paradigm, volume 13, issue 60, pages 1-23, DOI: 10.2478/ceej-2026-0001.
• Kumar Suresh & Ali Hyder, 2026, "Liquidity risk and liquidity timing in the cross-section of Indian equity mutual fund returns," Economics and Business Review, Paradigm, volume 12, issue 1, pages 105-133, DOI: 10.18559/ebr.2026.1.2746.
• Tatarczak Anna & Humeniuk Oleksandra, 2026, "Forecasting cryptocurrencies in turbulent times: Evidence on parsimony versus model complexity," Economics and Business Review, Paradigm, volume 12, issue 1, pages 135-158, DOI: 10.18559/ebr.2026.1.2652.
• Ochrymiuk Tymoteusz & Grabowski Kacper, 2026, "Economic Growth in the USA: Econometric Model and Forecast," Folia Oeconomica Stetinensia, Paradigm, volume 26, issue 1, pages 194-212, DOI: 10.2478/foli-2026-0010.
• Mielus Piotr, 2026, "Modelling the implied volatility – A case of EUR/PLN currency options," International Journal of Management and Economics, Warsaw School of Economics, Collegium of World Economy, volume 62, issue 1, pages 51-63, DOI: 10.2478/ijme-2026-0006.
• Cafieri Simona & Borrata Gianmarco, 2026, "AI Techniques for Survey Data Quality: Transformers and GANs," Journal of Social and Economic Statistics, Paradigm, volume 15, issue 1, pages 57-68, DOI: 10.2478/jses-2026-0005.
• Pham Thuy Tu, 2026, "Global Information Uncertainty and Real Estate Stock Valuation in Emerging Markets: an Integrated Behavioral - Theoretical and Machine Learning Framework," Real Estate Management and Valuation, Paradigm, volume 34, issue 1, pages 63-83, DOI: 10.2478/remav-2026-0006.
• Thanh Hang Hoang Thi & Pham Thuy Tu, 2026, "Bridging Predictive Power and Interpretability: A Hybrid Deep Learning Framework for Real Estate Performance Under Systemic Uncertainty," Real Estate Management and Valuation, Paradigm, volume 34, issue 3, pages 62-76, DOI: 10.2478/remav-2026-0025.
• Horák Jakub & Kučera Jiří, 2026, "Trends, Shocks and Predictions in the Price Development of Food-Grade Wheat," Studia Universitatis „Vasile Goldis” Arad – Economics Series, Paradigm, volume 36, issue 3, pages 128-165, DOI: 10.2478/sues-2026-0015.
• Boysen-Hogrefe Jens, 2026, "Leitartikel: Fiskalregeln und die Grenzen der Politikberatung," Wirtschaftsdienst, Paradigm, volume 106, issue 4, pages 230-231, DOI: 10.2478/wd-2026-0056.
• Harold Glenn A. Valera & Cymon Kayle Lubangco & Mark J. Holmes, 2026, "Does repeated cross-section data help explain consumer inflation expectations revisions?," Working Papers in Economics, University of Waikato, number 26/03, Feb.
• Kostiantyn Okhrimenko, 2026, "Painting Price: A Machine Learning Approach to Art Valuation. Proof of Concept and Market Structure Diagnosis," Working Papers, Faculty of Economic Sciences, University of Warsaw, number 2026-18.
• Anna Kurowska & Magdalena Grabowska & Maciej Świtała & Beata Osiewalska, 2026, "Same Constraints in Changing Times? A Machine-Learning Approach to Childbearing and Fertility Intentions in Poland during and after the COVID-19 Pandemic," Working Papers, Faculty of Economic Sciences, University of Warsaw, number 2026-32.
• Evangelos E. Ioannidis & Sofia‐Eirini Nikolakakou, 2026, "Modeling and Forecasting Stochastic Seasonality: Are Seasonal Autoregressive Integrated Moving Average Models Always the Best Choice?," Journal of Forecasting, John Wiley & Sons, Ltd., volume 45, issue 1, pages 316-334, January, DOI: 10.1002/for.70034.
• Jaroslava Hlouskova & Ines Fortin, 2026, "Regime‐Dependent Nowcasting of the Austrian Economy," Journal of Forecasting, John Wiley & Sons, Ltd., volume 45, issue 4, pages 2078-2101, July, DOI: 10.1002/for.70123.
• Emmanouil Sofianos & Thierry Betti & Theophilos Papadimitriou & Amélie Barbier‐Gauchard & Periklis Gogas, 2026, "Using DSGE and Machine Learning to Forecast Public Debt for France," Journal of Forecasting, John Wiley & Sons, Ltd., volume 45, issue 5, pages 2173-2185, August, DOI: 10.1002/for.70144.
• Georgios Angelopoulos & Zacharias Bragoudakis & Dimitrios Dimitriou & Alexandros Tsioutsios, 2026, "A New Proposal for Forecasting Inflation in the Eurozone: A Global Model," Journal of Forecasting, John Wiley & Sons, Ltd., volume 45, issue 5, pages 2393-2425, August, DOI: 10.1002/for.70135.
• Ruipeng Liu & Mawuli Segnon & Oguzhan Cepni & Rangan Gupta, 2026, "Forecasting Volatility of Commodity, Currency, and Stock Markets: Evidence From Markov‐Switching Multifractal Models," Journal of Forecasting, John Wiley & Sons, Ltd., volume 45, issue 6, pages 2905-2941, September, DOI: 10.1002/for.70145.
• Menzie Chinn & Baptiste Meunier & Sebastian Stumpner, 2026, "Nowcasting World Trade With Machine Learning: A Three‐Step Approach," Journal of Forecasting, John Wiley & Sons, Ltd., volume 45, issue 6, pages 2954-2968, September, DOI: 10.1002/for.70165.
• Afees A. Salisu & Ahamuefula E. Ogbonna & Rangan Gupta & Onur Polat, 2026, "Forecasting Natural Gas Futures Price Volatility of the United States: National Versus State‐Level Climate Concern Indexes," Journal of Futures Markets, John Wiley & Sons, Ltd., volume 46, issue 7, pages 1275-1297, July, DOI: 10.1002/fut.70108.
• M. Hashem Pesaran & Andreas Pick & Allan Timmermann, 2026, "Forecasting with panel data: Estimation uncertainty versus parameter heterogeneity," Quantitative Economics, Econometric Society, volume 17, issue 2, pages 342-393, May, DOI: 10.3982/QE2589.
• Jabeur Salhi & Ichrak Dridi & Oussama Gafrej, 2026, "Unlocking success in tech reward crowdfunding: A hybrid probit-machine learning approach with SHAP-driven feature analysis," International Journal of Financial Engineering (IJFE), World Scientific Publishing Co. Pte. Ltd., volume 13, issue 01, pages 1-43, March, DOI: 10.1142/S2424786326500027.
• Ichrak Dridi & Mohamed Malek Belhoula, 2026, "The moderating role of inflation targeting in stock market volatility drivers: Machine learning insights into macro-financial channels," International Journal of Financial Engineering (IJFE), World Scientific Publishing Co. Pte. Ltd., volume 13, issue 02, pages 1-36, June, DOI: 10.1142/S2424786326500180.
• Sabbor Hussain & Jo-Hui Chen & Dramane Thiombiano, 2026, "The impact of macroeconomic indicators on ETF: A grey relational analysis-machine learning approach," International Journal of Financial Engineering (IJFE), World Scientific Publishing Co. Pte. Ltd., volume 13, issue 03, pages 1-30, September, DOI: 10.1142/S2424786326500234.
• Anshul Agrawal & Sanjeev Kadam & Mohd Afjal, 2026, "Evaluating Predictive Robustness of Machine Learning Models During Black Swan Crises: Insights from Bitcoin Price Forecasting," Journal of International Commerce, Economics and Policy (JICEP), World Scientific Publishing Co. Pte. Ltd., volume 17, issue 02, pages 1-22, June, DOI: 10.1142/S1793993325500267.
• Tuyen Le Nam & Tam Phan Huy, 2026, "Corporate Financial Distress Prediction in Vietnam Using Calibrated and Explainable Machine Learning," Journal of International Commerce, Economics and Policy (JICEP), World Scientific Publishing Co. Pte. Ltd., volume 17, issue 03, pages 1-31, October, DOI: 10.1142/S1793993326500195.
• Qian Chen & Xiang Gao & Chen Chen & Shuairu Tian & Shigeyuki Hamori, 2026, "Macro Factor, Market Volatility, And Stock-Bond Correlation: A Dynamic Mixed Data Sampling Forecast," The Singapore Economic Review (SER), World Scientific Publishing Co. Pte. Ltd., volume 71, issue 07, pages 1907-1936, September, DOI: 10.1142/S021759082250028X.
• Langer, Maximilian & Hassib, Joshua & Feld, Lars P. & Nientiedt, Daniel, 2026, "Evaluating the effects of the German debt brake: A synthetic control approach," Freiburg Discussion Papers on Constitutional Economics, Walter Eucken Institut e.V., number 26/2.
• Verona, Fabio, 2026, "Forecasting inflation: The sum of the cycles outperforms the whole," Bank of Finland Research Discussion Papers, Bank of Finland, number 1/2026.
• Ollech, Daniel, 2026, "Selecting seasonal filters in X-13-ARIMA via cross-validation," Discussion Papers, Deutsche Bundesbank, number 16/2026, DOI: 10.71734/DP-2026-16.
• Boughabi, Houssam, 2026, "Fiscal and labour-market conditions and wage-income dynamics in Morocco: A Kaleckian-inspired reduced-form analysis," ZÖSS-Discussion Papers, University of Hamburg, Centre for Economic and Sociological Studies (CESS/ZÖSS), number 131.
• Fausch, Jürg & Frigg, Moreno & Ruenzi, Stefan & Weigert, Florian, 2026, "Machine learning mutual fund flows," CFR Working Papers, University of Cologne, Centre for Financial Research (CFR), number 26-03.
• Dallari, Pietro & Gattini, Luca, 2026, "How severe are European regulatory stress test scenarios? A probabilistic calibration for the euro area," EIB Working Papers, European Investment Bank (EIB), number 2026/01, DOI: 10.2867/0689043.
• Kronenberg, Philipp, 2026, "A high-frequency GDP indicator for Switzerland," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, volume 162, issue 1, pages 1-55, DOI: 10.1186/s41937-026-00157-w.
• Mirjalili, Seyed Hossein & Heydarian, Samira, 2026, "Predicting The Effectiveness of Monetary and Fiscal Policies Under Financial Sanction: A Machine Learning and SHAP Analysis," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, volume 21, issue 3, pages 411-446.
• Gondauri, Davit & Batiashvili, Mikheil, 2026, "Agentic Capital as a Productive Asset in the Agentic Economy: A Panel Econometric Analysis of Productivity Dynamics," EconStor Preprints, ZBW - Leibniz Information Centre for Economics, number 341306.
• Gondauri, Davit, 2026, "Global Hodge-Econometric Modeling of the World Economy: A Regional Benchmark Prototype for Topological Flow Decomposition, Systemic Circulation, Shock Transmission, and Macroeconomic Resilience," EconStor Preprints, ZBW - Leibniz Information Centre for Economics, number 341543.
• Yadav, Harsh & Goli, Srinivas, 2026, "Cultural Momentum, Demographic Divergence, and Population Prospects in India, 2100: Son Preference as a Structural Driver of Fertility and Long-Term Projections," EconStor Preprints, ZBW - Leibniz Information Centre for Economics, number 341571.
• Gondauri, Davit, 2026, "Navier-Stokes-Inspired Global Liquidity-Flow and Systemic-Stress Modelling: A Nondimensional Macro-Financial Stress-Testing Framework," EconStor Preprints, ZBW - Leibniz Information Centre for Economics, number 341616.
• Gondauri, Davit, 2026, "Global Perelman-Ricci-Poincare-Inspired Inequality Diagnostics: Curvature, Entropy and Graph-Topological Modelling of Macro-Regional Pressure and Smoothing Capacity," EconStor Preprints, ZBW - Leibniz Information Centre for Economics, number 341620.
• Gondauri, Davit, 2026, "Global Riemann-Zeta FPAS+ζ Inflation Forecasting: Layered Validation of a Hybrid Structural-Spectral Model for World Macroeconomic Pressure," EconStor Preprints, ZBW - Leibniz Information Centre for Economics, number 341672.
• Guest, Oliver & Steenkamp, Daan, 2026, "Is the rand at fair value?," EconStor Research Reports, ZBW - Leibniz Information Centre for Economics, number 336005.
• Schmal, Wolfgang Benedikt, 2026, "Was kostet das Deutschlandticket bis 2030? Eine szenariobasierte Analyse der VMK-Preisformel," FORMOE Working Papers, FORMOE - Forschungsforum Mobilitätsökonomik, number 2.
• Ewald, Anika & Puhani, Patrick A., 2026, "Does Pension Coverage Predict Fertility? International Evidence from OLS, Fixed Effects and Machine Learning Random Forests," GLO Discussion Paper Series, Global Labor Organization (GLO), number 1860.
• Schmitz, Luca, 2026, "Behind the curve: Reassessing inflation risks with a High-dimensional Distributional VAR (HiDVAR)," IMFS Working Paper Series, Goethe University Frankfurt, Institute for Monetary and Financial Stability (IMFS), number 245.
• Pita Marcet, Alicia & Schröder, Christian & Wolters, Maik H., 2026, "Improving inflation forecasting by modeling expectation de-anchoring in low-inflation periods," IMFS Working Paper Series, Goethe University Frankfurt, Institute for Monetary and Financial Stability (IMFS), number 246.
• Heinisch, Katja & van Norden, Simon & Wildi, Marc, 2026, "Smooth and persistent forecasts of German GDP: Balancing accuracy and stability," IWH Discussion Papers, Halle Institute for Economic Research (IWH), number 1/2026, DOI: 10.18717/dp99kr-7336.
• Drygalla, Andrej & Heinisch, Katja & Holtemöller, Oliver & Lindner, Axel & Schult, Christoph & Zeddies, Götz, 2026, "Einhaltung der EU-Fiskalregeln erfordert umfangreiche Konsolidierung: Mittelfristige Projektion der gesamtwirtschaftlichen Entwicklung und der öffentlichen Finanzen in Deutschland," IWH Policy Notes, Halle Institute for Economic Research (IWH), number 1/2026, DOI: 10.18717/pnb1fm-ja32.
• Blagov, Boris & Krause, Clara, 2026, "Does it add up? Reconciling forecasts and impulse responses for hierarchical macroeconomic data," Ruhr Economic Papers, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen, number 1224, DOI: 10.4419/96973409.
• Knüppel, Malte & Pavlova, Lora, 2026, "Survey design and professional forecasters: The case of uncertainty in the US SPF," ZEW Discussion Papers, ZEW - Leibniz Centre for European Economic Research, number 26-017.
• Bogdan Mirea & Giani-Ionel Gradinaru, 2026, "Ethics and bias in AI: a potential challenge to fair economic progress," Romanian Journal of Economics, Institute of National Economy, volume 62, issue 1(71), pages 99-110, June.
• José Alves & Clarisse Wagner, 2026, "The two sides of sovereign balance sheets: how much do government financial assets tell us about r - g?," Working Papers REM, ISEG - Lisbon School of Economics and Management, REM, Universidade de Lisboa, number 2026/0436, Oct.
• Giménez-Nadal, José Ignacio & Molina, José Alberto & Velilla, Jorge, 2026, "Who Shirks at Work? An Application of Machine Learning to Time Use Data," IZA Discussion Papers, IZA Network @ LISER, number 18432, Mar.
• Bruns, Daniel & Meier, Dennis & Thomsen, Stephan & Wolf, Felix, 2026, "Small-Area Projections of the General Practitioner Workforce in Germany: Supply, Demand and Workforce Gaps," IZA Discussion Papers, IZA Network @ LISER, number 18801, Jul.
• Mithila Chavan & Abhishek Garg, 2025, "Forecasting ENSO Impact on India’s Economic Indicators Using AI and Climate Data: A Cross-Model Evaluation," Journal of Global Economy, Research Centre for Social Sciences,Mumbai, India, volume 21, issue 4, pages 261-284, June.
• Mengnan Xu & Qifa Xu & Cuixia Jiang & Xingxuan Zhuo, 2026, "High-frequency Growth-at-Risk of China: the Role of Macro-financial Environment," Computational Economics, Springer;Society for Computational Economics, volume 67, issue 3, pages 1533-1570, March, DOI: 10.1007/s10614-025-10927-y.
• Bhanu Pratap & Amit Pawar & Shovon Sengupta, 2026, "Non-linear Phillips Curve for India: Evidence from Explainable Machine Learning," Computational Economics, Springer;Society for Computational Economics, volume 67, issue 3, pages 2301-2344, March, DOI: 10.1007/s10614-025-10942-z.
• Mengxi He & Daxiang Jin & Yaojie Zhang, 2026, "The Role of Lead-lag Effect in Predicting Crude Oil Futures Volatility: Empirical Evidence from China," Computational Economics, Springer;Society for Computational Economics, volume 67, issue 6, pages 5115-5137, June, DOI: 10.1007/s10614-025-11041-9.
• David Alaminos & M. Belén Salas-Compás & Estefanía Alaminos, 2026, "High-Frequency Trading, Short Squeeze and ARMA-GARCH-Fractal Neural Networks," Computational Economics, Springer;Society for Computational Economics, volume 68, issue 2, pages 1097-1154, August, DOI: 10.1007/s10614-025-11026-8.
• Wenxian Li & Kefei Han & Qi Zhang, 2026, "To Hybridize, or not To Hybridize: A Study on Hybrid Models for International Oil Prices Prediction," Computational Economics, Springer;Society for Computational Economics, volume 68, issue 6, pages 5217-5259, December, DOI: 10.1007/s10614-025-11226-2.
• Xiaoxian Duan & Kun Guo, 2026, "The Hybrid Multi-Scale Optimization Forecasting Model: a Novel Framework for High-Accuracy Prediction of Industrial Added Value Growth Rate," Computational Economics, Springer;Society for Computational Economics, volume 68, issue 6, pages 5075-5104, December, DOI: 10.1007/s10614-025-11228-0.
• Alok Arun & Sibanjan Mishra & Bibhuti Bhusan Mishra, 2026, "Cross impact of technology and finance on economic growth: evidence across globe," Economic Change and Restructuring, Springer, volume 59, issue 3, pages 1-35, June, DOI: 10.1007/s10644-026-10021-9.
• Kerim Keskin, 2026, "A game theory approach to football predictions," Public Choice, Springer, volume 206, issue 1, pages 241-261, January, DOI: 10.1007/s11127-025-01317-x.
• Wen-Chi Yeh & Bharat Sarath, 2026, "Earnings and price forecast with ARIMA and panel VAR time-series models," Review of Quantitative Finance and Accounting, Springer, volume 67, issue 3, pages 995-1046, October, DOI: 10.1007/s11156-025-01475-5.
• Iván Alejandro Vacio-Hernández, 2026, "A SARIMA Model Proposal with Intervention Variables for Forecasting Inflation in Mexico," Lecturas de Economía, Universidad de Antioquia, Departamento de Economía, issue 105, pages 151-192, DOI: 10.17533/udea.le.n105a359932.
• Foltas Alexander, 2026, "Inefficient Forecast Narratives: A BERT-Based Approach," Review of Economics, De Gruyter, volume 77, issue 1, pages 87-115, DOI: 10.1515/roe-2026-0013.
• Alice Treesa M & Dr. Arpita Choudhary, 2026, "Comparative Study of Machine Learning and Deep Learning Models for Short-Term Energy Consumption Prediction," Working Papers, Madras School of Economics,Chennai,India, number 2026-301, May.
• Jiti Gao & Fei Liu & Bin Peng, 2026, "Inference for High-Dimensional Local Projection," Monash Econometrics and Business Statistics Working Papers, Monash University, Department of Econometrics and Business Statistics, number 1/26.
• Nam Ho-Nguyen & Hossein Alipour & Anastasios Panagiotelis & George Athanasopoulos, 2026, "Optimal Forecast Reconciliation for Quantiles," Monash Econometrics and Business Statistics Working Papers, Monash University, Department of Econometrics and Business Statistics, number 4/26.
• Ewa Dziwok & Witold Szczepaniak, 2026, "Systemic risk and climate change: a joint impact of transition and physical climate risks on the Polish banking sector," Bank i Kredyt, Narodowy Bank Polski, volume 57, issue 1, pages 105-134.
• Ming Gu & David Hirshleifer & Siew Hong Teoh & Shijia Wu, 2026, "GIFfluence: A Visual Approach to Investor Sentiment and the Stock Market," NBER Working Papers, National Bureau of Economic Research, Inc, number 34636, Jan.
• Joshua S. Gans, 2026, "Optimal Use of Preferences in Artificial Intelligence Algorithms," NBER Working Papers, National Bureau of Economic Research, Inc, number 34780, Jan.
• Lauren Cohen & Yiwen Lu & Quoc H. Nguyen, 2026, "Mimicking Finance," NBER Working Papers, National Bureau of Economic Research, Inc, number 34849, Feb.
• Kurt G. Lunsford & Kenneth D. West, 2026, "An Empirical Evaluation of Some Long-Horizon Macroeconomic Forecasts," NBER Working Papers, National Bureau of Economic Research, Inc, number 34904, Feb.
• Lauren Cohen & Bo Li, 2026, "The Micro-Geography of Persuasion: Randomized Peer Exposure and Legislative Outcomes," NBER Working Papers, National Bureau of Economic Research, Inc, number 34925, Mar.
• Lin William Cong & Guanhao Feng & Jingyu He & Yuanzhi Wang, 2026, "Mosaics of Predictability," NBER Working Papers, National Bureau of Economic Research, Inc, number 35158, Apr.
• Peter Ganong & Avik Garg & Maximilian Kasy, 2026, "Literature Review and Evidence Aggregation: a Toolkit for Applied Micro," NBER Working Papers, National Bureau of Economic Research, Inc, number 35403, Jul.
• Victor Duarte & Julia Fonseca, 2026, "Self-Fulfilling Credit Scores," NBER Working Papers, National Bureau of Economic Research, Inc, number 35508, Jul.
• Jesús Fernández-Villaverde & Carlos Sanz, 2026, "Social Sorting and Political Cleavages: Evidence from 2.5 Million Electoral Candidates," NBER Working Papers, National Bureau of Economic Research, Inc, number 35820, Sep.
• Diane Coffey & Michael Geruso & Dean Spears & Sangita Vyas, 2026, "Does Fertility Stabilize At Low Levels? Evidence from Period, Cohort, and Subnational Data," NBER Working Papers, National Bureau of Economic Research, Inc, number 35824, Sep.
• Jin Huang & Diego Ferreras Garrucho & Yutong Xie & Walter M. Yuan & Qiaozhu Mei & Chen Lian & Jonathon Hazell, 2026, "HouseholdBench: Evaluating Large Language Models as Predictors of Household Economic Behavior," NBER Working Papers, National Bureau of Economic Research, Inc, number 35927, Oct.
• Samrajya Raj Acharya & Aayush Man Regmi & Kanhaiya Jha, 2026, "Exploring Trajectories of Government Bonds for Debt Planning Using Machine Learning Models," NRB Economic Review, Nepal Rastra Bank, Economic Research Department, volume 37, issue 1, pages 1-27, April.
• Adele Bergin & Luke Doyle & Stephen Millard, 2026, "The Macroeconomic Impact of Tariffs on Northern Ireland," National Institute of Economic and Social Research (NIESR) Discussion Papers, National Institute of Economic and Social Research, number 581, Jul.
• Peter Dixon, 2026, "Assessing Forecast Accuracy," National Institute of Economic and Social Research (NIESR) Discussion Papers, National Institute of Economic and Social Research, number 582, Aug.
• Stephen Millard, 2026, "Communicating Uncertainty in Macroeconomic Forecasts," National Institute of Economic and Social Research (NIESR) Discussion Papers, National Institute of Economic and Social Research, number 583, Aug.
• Stephen Millard, 2026, "Scenario Analysis as a Tool for Communicating Risks in Macroeconomic Forecasts," National Institute of Economic and Social Research (NIESR) Discussion Papers, National Institute of Economic and Social Research, number 584, Aug.
• National Institute of Economic and Social Research, 2026, "Box A: How Have the UK Economy and Our Forecasts Evolved Over 2025?," National Institute Economic Outlook, National Institute of Economic and Social Research, issue Winter, pages 21-23.
• National Institute of Economic and Social Research, 2026, "Box B: Communicating Uncertainty," National Institute Economic Outlook, National Institute of Economic and Social Research, issue Winter, pages 24-28.
• Yvan Guillemette, 2026, "Illustrating long-run fiscal challenges using the Long-Term Model," OECD Economics Department Working Papers, OECD Publishing, number 1877, Sep, DOI: 10.1787/421bf86f-en.
• Takashi Miyahara & Laura Betschka, 2026, "Can the Sahm rule indicator signal recession in OECD countries?," OECD Statistics Working Papers, OECD Publishing, number 2026/01, Mar, DOI: 10.1787/c15f9c28-en.
• Oecd, 2026, "Nowcasting the distribution of disposable income: A microsimulation framework enhanced by machine learning," OECD Papers on Well-being and Inequalities, OECD Publishing, number 41, Oct, DOI: 10.1787/b02cdd40-en.
• Albu Ana Octavia, 2026, "When Accurate Forecasts Still Produce Waste: Demand Shocks and Over-Forecasting Risk in Food Retail," Revista OEconomica, Romanian Society for Economic Science, Revista OEconomica, issue 01-2.
• Liu Jieni, 2026, "A Search-Then-Forecast Transformer Framework for Mid-Term Stock Price Prediction: An Empirical Case Study on the Chinese A-Share Market," Discussion Papers in Economics and Business, Osaka University, Graduate School of Economics, number 26-06, Apr.
• Yu Bai & Bin Peng & Shuping Shi & Wenying Yao, 2026, "Optimal Bandwidth Selection for Forecasting under Parameter Instability," Journal of Financial Econometrics, Oxford University Press, volume 24, issue 2, pages 1-001..
• Eusebiu Iordache, 2026, "Can Machine Learning Enhance Revenue Growth Forecasting in the Automotive Sector?," Ovidius University Annals, Economic Sciences Series, Ovidius University of Constantza, Faculty of Economic Sciences, volume 0, issue 1, pages 744-752, August.
• Didit B. Nugroho & Bambang Susanto & Faldy Tita & Takayuki Morimoto, 2026, "Real-time return extensions of realized GARCH models for improved risk management in asset markets," Journal of Asset Management, Palgrave Macmillan, volume 27, issue 2, pages 1-19, June, DOI: 10.1057/s41260-026-00452-4.
• Biju Ajithakumari Vijayappan Nair & Aghila Sasidharan & Arathy Chandralekha & Krishna Reddy, 2026, "Effect of ESG engagement on loan quality of banks: analysing non-performing loans in emerging economy banks," Journal of Banking Regulation, Palgrave Macmillan, volume 27, issue 3, pages 1-16, September, DOI: 10.1057/s41261-026-00345-x.
• Wojciech Starosta, 2026, "Calibrating credit risk parameters for climate stress testing," Risk Management, Palgrave Macmillan, volume 28, issue 1, pages 1-24, February, DOI: 10.1057/s41283-025-00189-1.
• Kazeem Ovanero Isah, 2026, "Assessing climate risk and resilience across stocks, ESG portfolios, and REITs: evidence from predictive modelling," Risk Management, Palgrave Macmillan, volume 28, issue 2, pages 1-19, May, DOI: 10.1057/s41283-026-00216-9.
• Zhixing Lin & Shuoyan Lin, 2026, "Volatility persistence across global equity markets: long-memory diagnostics versus horizon-specific VaR rankings," Risk Management, Palgrave Macmillan, volume 28, issue 4, pages 1-28, December, DOI: 10.1057/s41283-026-00247-2.
• Gabriel Rodriguez & Fiorela Liza & Miguel Ataurima Arellano, 2026, "Forecasting Value at Risk and Expected Shortfall in Equity Markets of High-Income and Latin American Countries," Documentos de Trabajo / Working Papers, Departamento de Economía - Pontificia Universidad Católica del Perú, number 2026-554, DOI: 10.18800/2079-8474.0554.
• Stephan Kaiser, 2026, "Business Model Change and Cash Flow Forecast Accuracy," Working Papers Dissertations, Paderborn University, Faculty of Business Administration and Economics, number 188, Nov.
• Jesús Fernández-Villaverde & Carlos Sanz, 2026, "Social Sorting and Political Cleavages: Evidence from 2.5 Million Electoral Candidates," PIER Working Paper Archive, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania, number 26-017, 09.
• Bahaa Aly, Tarek, 2026, "Global Economic Cycles Unveiled: A Hybrid TCN-HMM Approach for Regime Dynamics Across Eight Nations," MPRA Paper, University Library of Munich, Germany, number 127574, Jan.
• Kahambwe, Christ & Aidini, Christian & E.Loemba, Alexandre, 2026, "Intelligence artificielle et transformation de la relation croissance –emploi : une relecture empirique de la loi d’okun
  [Artificial Intelligence and the transformation of the growth–employment nexus: an empirical reappraisal of okun’s law]," MPRA Paper, University Library of Munich, Germany, number 127930, Jan, revised 2026.
• Larsen, Harry, 2026, "A Markov Model of the Learning Curve," MPRA Paper, University Library of Munich, Germany, number 128435, Mar.
• Fantazzini, Dean & Kurbatskii, Alexey, 2026, "Nowcasting and Forecasting Russian Regional CPI: Sparse Models and the Time-Varying Value of Online Data," MPRA Paper, University Library of Munich, Germany, number 128456.
• Kinel, Michal, 2026, "Robust Real-Time Macroeconomic Trend Extraction: A Gradient Boosting Approach," MPRA Paper, University Library of Munich, Germany, number 128473, Mar.
• Hardy, Nicolas & Korobilis, Dimitris, 2026, "Generalized Bayesian Composite Quantile Regression with an Application to Equity Premium Forecasting," MPRA Paper, University Library of Munich, Germany, number 128752, Apr.
• Labastidas, Esteban, 2026, "A Hybrid Early-Warning System for Inflation in an Emerging Market: Combining Econometric Models, an Agent-Based Decomposition with Heterogeneous Expectations, a Large Language Model, and a Multi-Output Agent Architecture," MPRA Paper, University Library of Munich, Germany, number 128779, Apr.
• boughabi, houssam, 2026, "Fiscal Regimes and Wage Formation: Learning Distributive Conflict in a Kaleckian Economy," MPRA Paper, University Library of Munich, Germany, number 128993, May.
• Nugawela, N.P. Gayan, 2026, "THE YIELD EQUILIBRIUM PROTOCOL: Architecting Revenue Governance and NOI Protection," MPRA Paper, University Library of Munich, Germany, number 129202, Apr.
• Buczak, Maciej, 2026, "The AMA method - analytical foundations of its failure," MPRA Paper, University Library of Munich, Germany, number 129937, Jun.
• Badreddine, Sadek, 2026, "Adaptive Economic Governance Under Nonstationarity: A State-Contingent Alternative to Fixed Ideological Policy," MPRA Paper, University Library of Munich, Germany, number 130393, Aug.
• Chakrawar, Onkar, 2026, "When does beta shrinkage help, and why does the leverage adjustment fail? Out-of-sample evidence from Indian equities," MPRA Paper, University Library of Munich, Germany, number 130509, Aug.
• Frank, Luis, 2026, "Comparación de métodos de regresión y reducción de dimensión para el nowcasting del EMAE
  [A Comparison of Regression and Dimensionality Reduction Methods for EMAE Nowcasting]," MPRA Paper, University Library of Munich, Germany, number 131074, Sep.
• Giovanni Bonaccolto & Massimiliano Caporin & Oguzhan Cepni & Rangan Gupta, 2026, "Forecasting Realized Volatility of State-Level Stock Markets of the United States: The Role of Sentiment," Working Papers, University of Pretoria, Department of Economics, number 202603, Feb.
• Matteo Bonato & Oguzhan Cepni & Rangan Gupta & Christian Pierdzioch, 2026, "Credit Standards: A New Predictor of U.S. Stock Market Realized Volatility," Working Papers, University of Pretoria, Department of Economics, number 202607, Mar.
• Onur Polat & Rangan Gupta & Dhanashree Somani & Sayar Karmakar, 2026, "Machine Learning Forecasting of U.S. Stock Market Volatility: The Role of Stock and Oil Bubbles," Working Papers, University of Pretoria, Department of Economics, number 202611, Apr.
• Talita Greyling & Rangan Gupta & Christian Pierdzioch, 2026, "Supply Bottlenecks and Sentiment in Europe: Some Evidence using Machine Learning," Working Papers, University of Pretoria, Department of Economics, number 202616, May.
• Onur Polat & Oguzhan Cepni & Riza Demirer & Rangan Gupta, 2026, "AI Revolution and Crash Risks in Technology Stocks," Working Papers, University of Pretoria, Department of Economics, number 202617, Jun.
• Afees A. Salisu & Ahamuefula E. Ogbonna & Rangan Gupta & Elie Bouri, 2026, "Price Conflict and US Stock Return Volatility Forecasting: Insights from over 150 Years with a Mixed-Frequency Framework," Working Papers, University of Pretoria, Department of Economics, number 202620, Aug.
• Khder Alakkari & Bushra Ali & Rangan Gupta, 2026, "Energy Transportation Uncertainty and Global Economic Activity: State-Dependent Evidence from Multivariate Quantile-on-Quantile Regressions," Working Papers, University of Pretoria, Department of Economics, number 202622, Aug.
• Oguzhan Cepni & Rangan Gupta, 2026, "Forecasting U.S. State Real GDP Growth with Panel Machine Learning and Mixed-Frequency Data," Working Papers, University of Pretoria, Department of Economics, number 202632, Oct.
• Onur Polat & Goodness C. Aye & Rangan Gupta & Samrat Goswami, 2026, "Aggregate versus Disaggregated Geopolitical Risks and Machine Learning Forecasting of Oil Market Volatility: Evidence from AI-Based Indexes," Working Papers, University of Pretoria, Department of Economics, number 202636, Oct.
• Ruipeng Liu & Christian Pierdzioch & Rangan Gupta & Elie Bouri, 2026, "Bank Runs and Gold-Price Returns and Volatility: Evidence from Centuries of Data," Working Papers, University of Pretoria, Department of Economics, number 202637, Oct.
• Piotr Mielus, 2026, "Volatility Modelling - What Drives Cee Currency Option Prices?," Prague Economic Papers, Prague University of Economics and Business, volume 2026, issue 1, pages 1-27, DOI: 10.18267/j.pep.906.
• Yang Yu & Yaping Gong & DooHwan Won & Atif Jahanger, 2026, "Regional Disparities in Drivers and Peaking Pathways of CO2 Emissions: Insights from Scenario Planning," Politická ekonomie, Prague University of Economics and Business, volume 2026, issue 1, pages 170-197, DOI: 10.18267/j.polek.1484.
• Milla Nyyssölä, 2026, "Ostovoiman kasvu ei kohdistu pienituloisimpiin ryhmiin. Reaalisten käytettävissä olevien tulojen kehitys Suomessa tulo- ja väestöryhmittäin vuoteen 2026 saakka," Analyses, Työn ja talouden tutkimus LABORE, Labour Institute for Economic Research LABORE, number 2026/9, Sep.
• Paulo Júlio, 2026, "Deep Learning Models in Central Bank Forecasting," Working Papers, Banco de Portugal, Economics and Research Department, number w202612.
• Luz Judith Rodríguez Esparza & Dolly Anabel Ortiz Lazcano, 2026, "A stochastic model to analyze the dynamics of poverty and social mobility in Mexico," EconoQuantum, Revista de Economia y Finanzas, Universidad de Guadalajara, Centro Universitario de Ciencias Economico Administrativas, Departamento de Metodos Cuantitativos y Maestria en Economia., volume 23, issue 1, pages 25-48, January-J.