Research classified by Journal of Economic Literature (JEL) codes

1. Forecasting

2025

• Felipe Roldán-Ferrín & Julián A. Parra-Polania, 2025, "Enhancing inflation nowcasting with online search data: a random forest application for Colombia," Borradores de Economia, Banco de la Republica de Colombia, number 1318, Jul, DOI: 10.32468/be.1318.
• César Anzola Bravo & Paola Poveda, 2025, "Forecasting Disaggregated Food Inflation Baskets in Colombia with an XGBoost Model," Borradores de Economia, Banco de la Republica de Colombia, number 1335, Dec, DOI: 10.32468/be.1335.
• Stéphane Lhuissier, 2025, "Assessing Asymmetric Macroeconomic Risk," Working papers, Banque de France, number 1004.
• Matteo Mogliani & Florens Odendahl, 2025, "Density Forecast Transformations," Working papers, Banque de France, number 1027.
• Alexander Kohlhas & Vladimir Asriyan, 2025, "The Macroeconomics of Data: Scale, Product Choice, and Pricing in the Information Age," Working Papers, Barcelona School of Economics, number 1486, Apr.
• Joshua Elias Fred A. Suero, 2025, "Developing a Standard Strategy for Time Series Forecasting Integrating Statistical and Machine Learning Techniques Using a Meta-Model Approach and its Application in Generating External Debt Projections," BSP Discussion Paper Series, Bangko Sentral ng Pilipinas, number 202503, Apr.
• Jorjin F. Godoy, 2025, "​Measuring the Systemic Risk Contribution of Philippine Industries and Conglomerate Groups​," BSP Discussion Paper Series, Bangko Sentral ng Pilipinas, number 202508, Aug.
• Harold Glenn A. Valera & Cymon Kayle Lubangco & Mark J. Holmes, 2025, "​​Does Repeated Cross-section Data Help Explain Consumer Inflation Expectations Revisions?," BSP Discussion Paper Series, Bangko Sentral ng Pilipinas, number 202514, Dec.
• Inaki Aldasoro & Peter Hördahl & Andreas Schrimpf & Sonya Zhu, 2025, "Predicting financial market stress with machine learning," BIS Working Papers, Bank for International Settlements, number 1250, Mar.
• Alberto Americo & Douglas Kiarelly Godoy de Araujo & Johannes Damp & Sjur Nilsen & Daniel Rees & Rafael Schmidt & Christian Schmieder, 2025, "Inflation cycles: evidence from international data," BIS Working Papers, Bank for International Settlements, number 1264, Apr.
• Anton Ilichov, 2025, "Problems of the efficiency of the functioning of the market of passenger transportation services in the conditions of the stateof war: identification and ways of overcoming," Economic Synergy, Higher Educational Institution Academician Yuriy Bugay International Scientific & Technical University, issue 1, pages 212-225, DOI: 10.53920/ES-2025-1-16.
• Elizaveta Volgina, 2025, "Forecasting Inflation Using News Indices," Russian Journal of Money and Finance, Bank of Russia, volume 84, issue 1, pages 26-59, March.
• Oleg Kryzhanovskiy & Anastasia Mogilat & Zhanna Shuvalova & Dmitry Gvozdev, 2025, "Using LSTM Neural Networks for Nowcasting and Forecasting GVA of Industrial Sectors," Russian Journal of Money and Finance, Bank of Russia, volume 84, issue 1, pages 93-104, March.
• Alexander Eliseev, 2025, "Nowcasting Russian GDP in a Mixed-Frequency DSGE Model with a Panel of Non-Modelled Variables," Russian Journal of Money and Finance, Bank of Russia, volume 84, issue 3, pages 63-93, September.
• Anastasia Pankratova, 2025, "Application of MF-PVAR Model for Nowcasting Gross Regional Products in Russia," Russian Journal of Money and Finance, Bank of Russia, volume 84, issue 4, pages 47-62, December.
• Urmat Dzhunkeev, 2025, "MOSES: Macroeconomic Forecasting with Models and Sentiment Synthesis," Russian Journal of Money and Finance, Bank of Russia, volume 84, issue 4, pages 63-84, December.
• Alexander Eliseev, 2025, "Nowcasting Russian GDP in a mixed-frequency DSGE model with a panel of non-modelled variables," Bank of Russia Working Paper Series, Bank of Russia, number wps145, Feb.
• Afees A. Salisu & Ahamuefula E. Ogbonna & Rangan Gupta & Sisa Shiba, 2025, "Energy Market Uncertainties and Gold Return Volatility: A GARCH–MIDAS Approach," Australian Economic Papers, Wiley Blackwell, volume 64, issue 3, pages 320-329, September, DOI: 10.1111/1467-8454.12396.
• Luke Hartigan & Tom Rosewall, 2025, "Nowcasting Quarterly GDP Growth During the COVID‐19 Crisis Using a Monthly Activity Indicator," The Economic Record, The Economic Society of Australia, volume 101, issue 335, pages 456-484, December, DOI: 10.1111/1475-4932.70000.
• Gunnar Bårdsen & Ragnar Nymoen, 2025, "U.S. Wage‐Price Dynamics, Before, During and After COVID‐19, Through the Lens of an Empirical Econometric Model," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, volume 87, issue 6, pages 1122-1145, December, DOI: 10.1111/obes.12686.
• Artur Silva Lopes, 2025, "Assessing Income Convergence with a Long‐run Forecasting Approach: Some New Results," Review of Income and Wealth, International Association for Research in Income and Wealth, volume 71, issue 1, February, DOI: 10.1111/roiw.12702.
• Dimitris Korobilis, 2025, "Learning from crises: A new class of time-varying parameter VARs with observable adaptation," Working Papers, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School, number No 09/2025, Dec.
• Yang, Zhang & Jianxiong Lin & Yihe Qian & Lianjie Shu, 2025, "Machine learning and financial inclusion: Evidence from credit risk assessment of small-business loans in China," Working Papers, University of Macau, Faculty of Business Administration, number 202532, Jun.
• Tom Doan, 2025, "MATHESON_STAVREV_EL2013: RATS programs to replicate Matheson-Stavrev(2013) non-linear state-space model," Statistical Software Components, Boston College Department of Economics, number RTZ00216, revised .
• Tom Doan, 2025, "SKALIN_TERASVIRTA_JAE1999: RATS program to replicate Skalin and Terasvirta(1999) STAR models and causality tests," Statistical Software Components, Boston College Department of Economics, number RTZ00230, revised .
• Tom Doan, 2025, "WEST_CHO_JOE1995: RATS program to replicate West and Cho(1995) analysis of GARCH models," Statistical Software Components, Boston College Department of Economics, number RTZ00233, revised .
• Marcus Buckmann & Galina Potjagailo & Philip Schnattinger, 2025, "Blockwise Boosted Inflation: Non-linear determinants of inflation using machine learning," Bank of England Staff Working Paper series, Bank of England, number 1143, Sep.
• Marcus Buckmann & Galina Potjagailo, 2025, "Infusing economically motivated structure into machine learning methods," Bank of England Staff Working Paper series, Bank of England, number 1144, Sep.
• Stavros Degiannakis & Eleftheria Kafousaki, 2025, "Disaggregating VIX," Working Papers, Bank of Greece, number 335, Jan, DOI: 10.52903/wp2025335.
• Stavros Degiannakis & Panagiotis Delis & George Filis & George Giannopoulos, 2025, "Trading VIX on volatility forecasts: another volatility puzzle?," Working Papers, Bank of Greece, number 336, Feb, DOI: 10.52903/wp2025336.
• Dimitrios Papaoikonomou, 2025, "Stochastic debt sustainability analysis: a methodological note," Working Papers, Bank of Greece, number 338, Mar, DOI: 10.52903/wp2025338.
• Panagiotis Delis & Stavros Degiannakis & George Filis, 2025, "Navigating crude oil volatility forecasts: assessing the contribution of geopolitical risk," Working Papers, Bank of Greece, number 342, May, DOI: 10.52903/wp2025342.
• Georgios Angelopoulos & Zacharias Bragoudakis & Dimitrios Dimitriou & Alexandros Tsioutsios, 2025, "A new proposal for forecasting inflation in the eurozone. A global model," Working Papers, Bank of Greece, number 350, Oct, DOI: 10.52903/wp2025350.
• Shunsuke Haba & Kimihiko Izawa & Yui Kishaba & Yusuke Takahashi & Shunichi Yoneyama, 2025, "Measuring Policy Effects since the Introduction of Quantitative and Qualitative Monetary Easing (QQE): An Analysis Using the Macroeconomic Model Q-JEM," Bank of Japan Working Paper Series, Bank of Japan, number 25-E-2, Feb.
• Ichiro Fukunaga & Yui Kishaba & Nao Shibata & Shunichi Yoneyama, 2025, "Uncertainty in the Formation of Inflation Expectations in Japan: An Analysis Using the Macroeconomic Model Q-JEM," Bank of Japan Working Paper Series, Bank of Japan, number 25-E-3, Feb.
• Klaus Adam & Pei Kuang & Shihan Xie, 2025, "Overconfidence in Private Information Explains Biases in Professional Forecasts," CRC TR 224 Discussion Paper Series, University of Bonn and University of Mannheim, Germany, number crctr224_2025_617, Jan.
• Orujov Samir & Elvira Victor & Poterie Audrey & Rajabov Farid & Septier Francois, 2025, "VS-LTGARCHX: A Flexible Variable Selection in Log-TGARCHX Models," Journal of Time Series Econometrics, De Gruyter, volume 17, issue 1, pages 1-34, DOI: 10.1515/jtse-2023-0035.
• Mattera Raffaele, 2025, "Forecasting High-Dimensional Portfolios," Journal of Time Series Econometrics, De Gruyter, volume 17, issue 1, pages 35-67, DOI: 10.1515/jtse-2023-0011.
• Herculano Miguel C. & Jacob Punnoose, 2025, "Financial Condition Indices in an Incomplete Data Environment," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, volume 29, issue 1, pages 19-38, DOI: 10.1515/snde-2022-0115.
• Gupta Rangan & Sun Xiaojin, 2025, "Time-Varying Parameter Four-Equation DSGE Model," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, volume 29, issue 2, pages 235-246, DOI: 10.1515/snde-2023-0010.
• Gkillas Konstantinos & Tantoula Maria & Tzagarakis Manolis, 2025, "Heterogeneity, Jumps and Co-Movements in Transmission of Volatility Spillovers Among Cryptocurrencies," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, volume 29, issue 5, pages 621-649, DOI: 10.1515/snde-2023-0088.
• Goulet Coulombe Philippe, 2025, "To Bag is to Prune," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, volume 29, issue 6, pages 669-697, DOI: 10.1515/snde-2023-0030.
• Hafner, C. M. & Linton, O. B. & Wang, L., 2025, "Multivariate AutoRegressive Smooth Liquidity (MARSLiQ)," Cambridge Working Papers in Economics, Faculty of Economics, University of Cambridge, number 2569, Oct.
• Bachmair, K. & Schmitz, N., 2025, "Forecasting Macro with Finance," Cambridge Working Papers in Economics, Faculty of Economics, University of Cambridge, number 2574, Nov.
• Congressional Budget Office, 2025, "The Accuracy of CBO’s Budget Projections for Fiscal Year 2024," Reports, Congressional Budget Office, number 60885, Jan.
• Congressional Budget Office, 2025, "CBO's Economic Forecasting Record: 2025 Update," Reports, Congressional Budget Office, number 61334, Jul.
• Maximilian Langer & Joshua Hassib & Lars P. Feld & Daniel Nientiedt, 2025, "Evaluating the Effects of the German Debt Brake: A Synthetic Control Approach," CESifo Working Paper Series, CESifo, number 11933.
• Christian Conrad & Zeno Enders & Gernot Müller, 2025, "Inflation Forecast Targeting Revisited," CESifo Working Paper Series, CESifo, number 12006.
• Stefan Sauer & Klaus Wohlrabe, 2025, "Explaining Business Sentiment: Insights from the ifo Business Survey," CESifo Working Paper Series, CESifo, number 12007.
• Bryan T. Kelly & Semyon Malamud & Emil Siriwardane & Hongyu Wu, 2025, "Behavioral Impulse Responses," Swiss Finance Institute Research Paper Series, Swiss Finance Institute, number 25-04, Jan.
• MD Nazmul Ahsan & Jean-Marie Dufour & Gabriel Rodriguez, 2025, "Modèles de volatilité stochastique à haute dimension: applications à l’incertitude macroéconomique au Québec et au Canada," CIRANO Project Reports, CIRANO, number 2025rp-19, Sep.
• Etienne Briand & Massimiliano Marcellino & Dalibor Stevanovic, 2025, "Inflation, Attention and Expectations," CIRANO Working Papers, CIRANO, number 2025s-01, Jan.
• Philippe Goulet Coulombe & Massimiliano Marcellino & Dalibor Stevanovic, 2025, "Panel Machine Learning with Mixed-Frequency Data: Monitoring State-Level Fiscal Variables," CIRANO Working Papers, CIRANO, number 2025s-15, May.
• Oxana Babecka Kucharcukova & Jan Bruha & Petr Sterba, 2025, "Web Reviews as a New Leading Indicator for Nowcasting Travel Expenditure in Balance of Payments Statistics," Working Papers, Czech National Bank, Research and Statistics Department, number 2025/13, Nov.
• Sona Benecka, 2025, "Forecasting Disaggregated Producer Prices: A Fusion of Machine Learning and Econometric Techniques," Working Papers, Czech National Bank, Research and Statistics Department, number 2025/2, Mar.
• Frantisek Brazdik & Karel Musil & Tomas Pokorny & Tomas Sestorad & Jaromir Tonner & Jan Zacek, 2025, "Upgrading the Czech National Bank's Core Forecasting Model g3+," Working Papers, Czech National Bank, Research and Statistics Department, number 2025/7, May.
• Juan Jos√© Rinc√≥n Brice√±o, 2025, "Colombian economic activity nowcasting: addressing nonlinearities and high dimensionality through machine-learning," Documentos CEDE, Universidad de los Andes, Facultad de Economía, CEDE, number 21388, Jun.
• Cimadomo, Jacopo & Giannone, Domenico & Lenza, Michele & Monti, Francesca & Sokol, Andrej, 2025, "Nowcasting with large Bayesian vector autoregressions," LIDAM Reprints CORE, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE), number 3331, Jan, DOI: https://doi.org/10.1016/j.jeconom.2.
• Chernov, Mikhail & Elenev, Vadim & Song, Dongho, 2025, "The Comovement of Voter Preferences: Insights from U.S. Presidential Election Prediction Markets Beyond Polls," CEPR Discussion Papers, Centre for Economic Policy Research, number 19836, Jan.
• Gonzalez-Casasus, Oriol & Schorfheide, Frank, 2025, "Misspecification-Robust Shrinkage and Selection for VAR Forecasts and IRFs," CEPR Discussion Papers, Centre for Economic Policy Research, number 19915, Feb.
• Hauzenberger, Niko & Marcellino, Massimiliano & Pfarrhofer, Michael & Stelzer, Anna, 2025, "Bayesian Nowcasting with Mixed Frequency Data Using Gaussian Processes," CEPR Discussion Papers, Centre for Economic Policy Research, number 19965, Feb.
• Gabaix, Xavier & Koijen, Ralph & Richmond, Robert & Yogo, Motohiro, 2025, "Asset Embeddings," CEPR Discussion Papers, Centre for Economic Policy Research, number 20082, Mar.
• Adrian, Tobias & Giannone, Domenico & Luciani, Matteo & West, Mike, 2025, "Scenario Synthesis and Macroeconomic Risk," CEPR Discussion Papers, Centre for Economic Policy Research, number 20219, May.
• Liu, Weifeng Larry & Mckibbin, Warwick, 2025, "Long-Term Projections of the World Economy," CEPR Discussion Papers, Centre for Economic Policy Research, number 20293, May.
• Aldasoro, Inaki & Hördahl, Peter & Schrimpf, Andreas & Zhu, Sonya, 2025, "Predicting Financial Market Stress with Machine Learning," CEPR Discussion Papers, Centre for Economic Policy Research, number 20439, Jul.
• Marcellino, Massimiliano & Pfarrhofer, Michael, 2025, "Nonparametric Mixed Frequency Monitoring Macro-at-Risk," CEPR Discussion Papers, Centre for Economic Policy Research, number 20442, Jul.
• Gorodnichenko, Yuriy & Vasudevan, Vittal, 2025, "Macroeconomic Expectations in a War," CEPR Discussion Papers, Centre for Economic Policy Research, number 20462, Jul.
• Conrad, Christian & Enders, Zeno & Müller, Gernot, 2025, "Inflation Forecast Targeting Revisited," CEPR Discussion Papers, Centre for Economic Policy Research, number 20467, Jul.
• Gargiulo, Valeria & Inoue, Atsushi & Rossi, Barbara, 2025, "A New Approach to Fiscal Multipliers: Time Variation and High Frequency Shocks," CEPR Discussion Papers, Centre for Economic Policy Research, number 20670, Sep.
• Chi, Ta-Chung & Fan, Ting-Han & Ghigliazza, Raffaele & Giannone, Domenico & Wang, Zixuan (Kevin), 2025, "Macroeconomic Forecasting and Machine Learning," CEPR Discussion Papers, Centre for Economic Policy Research, number 20727, Oct.
• Adam, Klaus & Kuang, Pei & Xie, Shihan, 2025, "Overconfidence in Private Information Explains Biases in Professional Forecasts," CEPR Discussion Papers, Centre for Economic Policy Research, number 20806, Nov.
• Oosterbeek, Hessel & Rozsos, Tina & van der Klaauw, Bas, 2025, "School Choice, School Switching, and Optimal Assignment," CEPR Discussion Papers, Centre for Economic Policy Research, number 20890, Dec.
• Hessel Oosterbeek & Tina Rozsos & Bas van der Klaauw, 2025, "School choice, school switching, and optimal assignment," RFBerlin Discussion Paper Series, ROCKWOOL Foundation Berlin (RFBerlin), number 25159, Dec.
• Marco Guerzoni & Luigi Riso & Maria Grazia Zoia, 2025, "Forecasting the Impact of Extreme Weather Events on Electricity Prices in Italy: A GARCH-MIDAS Approach with Enhanced Variable Selection," DISCE - Working Papers del Dipartimento di Politica Economica, Università Cattolica del Sacro Cuore, Dipartimenti e Istituti di Scienze Economiche (DISCE), number dipe0043, Jan.
• Guo, Hongfei & Marín Díazaraque, Juan Miguel & Veiga, Helena, 2025, "Learning Volatility:A Bayesian Neural Stochastic Framework," DES - Working Papers. Statistics and Econometrics. WS, Universidad Carlos III de Madrid. Departamento de Estadística, number 47944, Sep.
• Shirlee LICHTMAN-SADOT & Neta BNEHSHALOM-TIROSH & Eyal SHEINER, 2025, "Conflict, rockets, and birth outcomes: evidence from Israel's Operation Protective Edge," JODE - Journal of Demographic Economics, Cambridge University Press, volume 91, issue 1, pages 119-145, March, DOI: 10.1017/dem.2022.18.
• Tal BOGER, 2025, "Forecasting inflation in Iran by applying machine learning algorithms to PPP lag," Turkish Economic Review, EconSciences Journals, volume 12, issue 2, pages 68-82, June.
• Маргарита Шопова & Евгени Овчинников, 2025, "Автоматизирани Алгоритми За Идентификация На Arima Модели При Прогнозиране На Динамични Редове - Преглед На Литературата," Scientific Research Almanac, D. A. Tsenov Academy of Economics, Svishtov, Bulgaria, issue 33 Year 2, pages 117-148.
• Jelena Franjkovic & Ivana Fosic & Ana Zivkovic, 2025, "Application Of Machine Learning Algorithms in Predicting Customer Loyalty Towards Grocery Retailers," Business Management, D. A. Tsenov Academy of Economics, Svishtov, Bulgaria, issue 2 Year 20, pages 86-102.
• Daniel Graeber & Lorenz Meister & Carsten Schröder & Sabine Zinn, 2025, "Random Forests for Labor Market Analysis: Balancing Precision and Interpretability," SOEPpapers on Multidisciplinary Panel Data Research, DIW Berlin, The German Socio-Economic Panel (SOEP), number 1230.
• Robert-Paul Berben & Rajni Rasiawan & Jasper de Winter, 2025, "Forecasting Dutch inflation using machine learning methods," Working Papers, DNB, number 828, Feb.
• Pérignon, Christophe & Saurin, Sébastien & Sentenac, Flore & Digalakis Jr, Vassilis, 2025, "The Challenger: When Do New Data Sources Justify Switching Machine Learning Models?," HEC Research Papers Series, HEC Paris, number 1601, Dec, DOI: 10.2139/ssrn.5946174.
• Foroni, Claudia & Schroeder, Christofer, 2025, "Using corporate earnings calls to forecast euro area labour demand," Economic Bulletin Boxes, European Central Bank, volume 2.
• Figueres, Juan Manuel & Prieto, Barbara Montero & Scalone, Valerio & Hooft, James ’t & Ter Steege, Lucas & Vallotto, Clarissa, 2025, "A framework to assess the severity of adverse scenarios in EU-wide stress tests," Macroprudential Bulletin, European Central Bank, volume 32.
• Angelini, Elena & Darracq Pariès, Matthieu & Haertel, Thomas & Lalik, Magdalena & Aldama, Pierre & Brázdik, František & Damjanović, Milan & Fantino, Davide & Sanchez, Pablo Garcia & Guarda, Paolo & Ke, 2025, "The ESCB forecasting models: what are they and what are they good for?," Occasional Paper Series, European Central Bank, number 381, Dec.
• Petrella, Ivan & De Polis, Andrea & Melosi, Leonardo, 2025, "The taming of the skew: asymmetric inflation risk and monetary policy," Working Paper Series, European Central Bank, number 3028, Feb.
• Bańbura, Marta & Bobeica, Elena & Giammaria, Alessandro & Porqueddu, Mario & van Spronsen, Josha, 2025, "A new model to forecast energy inflation in the euro area," Working Paper Series, European Central Bank, number 3062, Jun.
• Klieber, Karin & Coulombe, Philippe Goulet, 2025, "Opening the black box of local projections," Working Paper Series, European Central Bank, number 3105, Aug.
• Saiz, Lorena & Magro, Manuel Medina, 2025, "What can newspaper articles reveal about the euro area economy?," Working Paper Series, European Central Bank, number 3122, Sep.
• Trebbi, Giovanni, 2025, "Inflation narratives and expectations," Working Paper Series, European Central Bank, number 3158, Dec.
• Togan, Aslı & Togan, Sübidey, 2025, "Reforming external debt governance in Turkey to reach external debt sustainability," Journal of Asian Economics, Elsevier, volume 101, issue C, DOI: 10.1016/j.asieco.2025.102020.
• Adachi, Yusuke & Ogawa, Hikaru & Tsubuku, Masafumi, 2025, "Regional employment during recessions and recoveries in Japan: A data-driven approach," Journal of Asian Economics, Elsevier, volume 98, issue C, DOI: 10.1016/j.asieco.2025.101917.
• Bitetto, Alessandro & Filomeni, Stefano & Modina, Michele, 2025, "Machine Learning for the Unlisted: Enhancing MSME Default Prediction with Public Market Signals," Journal of Corporate Finance, Elsevier, volume 94, issue C, DOI: 10.1016/j.jcorpfin.2025.102830.
• Zanetti Chini, Emilio, 2025, "Judgment can spur long memory," Journal of Economic Dynamics and Control, Elsevier, volume 170, issue C, DOI: 10.1016/j.jedc.2024.105005.
• Bao, Te & Dai, Yun & Duffy, John, 2025, "Least squares learning? Evidence from the laboratory," Journal of Economic Dynamics and Control, Elsevier, volume 172, issue C, DOI: 10.1016/j.jedc.2024.104980.
• Clements, Michael P. & Rich, Robert W. & Tracy, Joseph, 2025, "An Investigation into the Uncertainty Revision Process of Professional Forecasters," Journal of Economic Dynamics and Control, Elsevier, volume 173, issue C, DOI: 10.1016/j.jedc.2025.105060.
• Falconio, Andrea & Manganelli, Simone, 2025, "Financial conditions, business cycle fluctuations and growth-at-risk," Journal of Economic Dynamics and Control, Elsevier, volume 176, issue C, DOI: 10.1016/j.jedc.2025.105109.
• Barci, Giovanni, 2025, "The effects of monetary policy on macroeconomic downside risk: state-dependence matters," Journal of Economic Dynamics and Control, Elsevier, volume 180, issue C, DOI: 10.1016/j.jedc.2025.105201.
• Lian, Zeng & Chen, Liang & Tan, Hongru, 2025, "How NAFTA affected U.S. vehicle emissions: Demand growth and usage patterns," Economic Modelling, Elsevier, volume 143, issue C, DOI: 10.1016/j.econmod.2024.106961.
• Wang, Nianling & Wang, Qianchao & Li, Yong, 2025, "Estimation and forecast of carbon emission market volatility based on model averaging method," Economic Modelling, Elsevier, volume 143, issue C, DOI: 10.1016/j.econmod.2024.106976.
• Qiu, Yue & Qu, Shaoguang & Shi, Zhentao & Xie, Tian, 2025, "Predicting cryptocurrency volatility: The power of model clustering," Economic Modelling, Elsevier, volume 144, issue C, DOI: 10.1016/j.econmod.2024.106986.
• Kaustubh, Kaustubh & Ranjan, Abhishek, 2025, "A multi-factor GDP nowcast model for India," Economic Modelling, Elsevier, volume 147, issue C, DOI: 10.1016/j.econmod.2025.107053.
• Gillmann, Niels & Okhrin, Ostap, 2025, "Adaptive local VAR for dynamic economic policy uncertainty spillover," Economic Modelling, Elsevier, volume 148, issue C, DOI: 10.1016/j.econmod.2025.107079.
• Lefort, Fernando & Díaz, Fernando, 2025, "Analyzing price efficiency using machine learning generated price indices: The case of the Chilean used car market," Economic Modelling, Elsevier, volume 152, issue C, DOI: 10.1016/j.econmod.2025.107257.
• Lin, Wensheng & Wang, Xuewu, 2025, "Regime-dependent volatility spillover asymmetry in Shanghai and Hong Kong stock markets with forecasting and portfolio inferences," Economic Modelling, Elsevier, volume 152, issue C, DOI: 10.1016/j.econmod.2025.107268.
• Deng, Shangkun & Li, Yongqi & Zhu, Yingke & Wang, Bingsen & Ning, Hong & Yi, Siyu & Shimada, Tatsuro, 2025, "Financial distress warning and risk path analysis for Chinese listed companies: An interpretable machine learning approach," Economic Modelling, Elsevier, volume 152, issue C, DOI: 10.1016/j.econmod.2025.107288.
• Ma, Yong & Li, Shuaibing & Liu, Xiaojun, 2025, "Forecasting energy commodity returns: Can weak factors and nonlinearity help?," Economic Modelling, Elsevier, volume 153, issue C, DOI: 10.1016/j.econmod.2025.107295.
• Aguilar, Pablo & Vázquez, Jesús, 2025, "Multi-period Euler-equation learning and term structure," Economic Modelling, Elsevier, volume 153, issue C, DOI: 10.1016/j.econmod.2025.107346.
• Papenfuß, Patric & Schischke, Amelie & Rathgeber, Andreas, 2025, "Factors of predictive power for metal commodities," The North American Journal of Economics and Finance, Elsevier, volume 76, issue C, DOI: 10.1016/j.najef.2024.102309.
• Fernandez-Perez, Adrián & Gómez-Puig, Marta & Sosvilla-Rivero, Simón, 2025, "Examining the transmission of credit and liquidity risks: A network analysis for EMU sovereign debt markets," The North American Journal of Economics and Finance, Elsevier, volume 77, issue C, DOI: 10.1016/j.najef.2025.102407.
• Hu, Genhua & Ma, Xiaoqing & Zhu, Tingting, 2025, "Forecasting volatility of China’s crude oil futures based on hybrid ML-HAR-RV models," The North American Journal of Economics and Finance, Elsevier, volume 78, issue C, DOI: 10.1016/j.najef.2025.102428.
• Clements, Adam & Otero, Jesús, 2025, "Forecasting retail fuel prices with spatial interdependencies," Economics Letters, Elsevier, volume 247, issue C, DOI: 10.1016/j.econlet.2024.112128.
• Younker, James, 2025, "Calculating effective degrees of freedom for forecast combinations and ensemble models," Economics Letters, Elsevier, volume 247, issue C, DOI: 10.1016/j.econlet.2024.112137.
• Marcellino, Massimiliano & Pfarrhofer, Michael, 2025, "Nonparametric mixed frequency monitoring macro-at-risk," Economics Letters, Elsevier, volume 255, issue C, DOI: 10.1016/j.econlet.2025.112498.
• Seiler, Pascal, 2025, "Measuring economic sentiment from open-ended survey comments using large language models," Economics Letters, Elsevier, volume 256, issue C, DOI: 10.1016/j.econlet.2025.112622.
• Chen, Minghui & Hanauer, Matthias X. & Kalsbach, Tobias, 2025, "Model complexity and the performance of global versus regional models," Economics Letters, Elsevier, volume 257, issue C, DOI: 10.1016/j.econlet.2025.112641.
• Ghirelli, Corinna & Pérez, Javier J. & Santabárbara, Daniel, 2025, "Forecast errors and the sacrifice ratio of monetary policy in the euro area," Economics Letters, Elsevier, volume 257, issue C, DOI: 10.1016/j.econlet.2025.112678.
• Tu, Yundong & Zheng, Jinsha, 2025, "Consistent model selection for factor-augmented regression within hierarchical factor structures," Economics Letters, Elsevier, volume 257, issue C, DOI: 10.1016/j.econlet.2025.112697.

2024

• Do, Quang Hung, 2024, "Predicting Efficiency of Commercial Banks in Vietnam: A DEA and Machine Learning Approach," Advances in Decision Sciences, Asia University, Taiwan, volume 28, issue 4, pages 120-143.
• Nguyen Anh Phong & Phan Huy Tam & Ngo Phu Thanh, 2024, "Identifying Fraudulent Financial Reports: Verification Between the M-Score Model and the Auditor’s Opinion," Advances in Decision Sciences, Asia University, Taiwan, volume 28, issue 4, pages 23-45.
• Hyeongwoo Kim & Jisoo Son, 2024, "What Charge-Off Rates Are Predictable by Macroeconomic Latent Factors?," Auburn Economics Working Paper Series, Department of Economics, Auburn University, number auwp2024-01, Feb.
• Sarthak Behera & Hyeongwoo Kim & Soohyon Kim, 2024, "Predictive Power of U.S. Macroeconomic Factors for the Dollar/Won Real Exchange Rate," Auburn Economics Working Paper Series, Department of Economics, Auburn University, number auwp2024-02, Feb.
• Sedat Çerez & Abdullah Kürşat Merter & Yavuz Selim Balcıoğlu & Gökhan Özer, 2024, "Evaluation of Annual Reports by Text Analysis: An Application in Bist100 Index," Journal of Finance Letters (Maliye ve Finans Yazıları), Maliye ve Finans Yazıları Yayıncılık Ltd. Şti., volume 39, issue 121, pages 175-188, April, DOI: https://doi.org/10.33203/mfy.133848.
• Rodney Duffett & Rodica Milena Zaharia & Tudor Edu & Raluca Constantinescu & Costel Negricea, 2024, "Exploring the Antecedents of Artificial Intelligence Products’ Usage. The Case of Business Students," The AMFITEATRU ECONOMIC journal, Academy of Economic Studies - Bucharest, Romania, volume 26, issue 65, pages 106-106, February.
• Khulood Mohammed BaLashwar & Yuosuf Khalid Al-Hamar & Seyed-Ali Sadegh-Zadeh, 2024, "Optimizing Bank Stability Through MSME Loan Securitization: A Predictive and Prescriptive Analytics Approach," The African Finance Journal, Africagrowth Institute, volume 26, issue 2, pages 58-79.
• Bastianin, Andrea & Mirto, Elisabetta & Qin, Yan & Rossini, Luca, , "What drives the European carbon market? Macroeconomic factors and forecasts," FEEM Working Papers, Fondazione Eni Enrico Mattei (FEEM), number 339740, DOI: 10.22004/ag.econ.339740.
• Tomasz Serafin & Rafal Weron, 2024, "Loss functions in regression models: Impact on profits and risk in day-ahead electricity trading," WORking papers in Management Science (WORMS), Department of Operations Research and Business Intelligence, Wroclaw University of Science and Technology, number WORMS/24/03.
• Katarzyna Chec & Bartosz Uniejewski & Rafal Weron, 2024, "Extrapolating the long-term seasonal component of electricity prices for forecasting in the day-ahead market," WORking papers in Management Science (WORMS), Department of Operations Research and Business Intelligence, Wroclaw University of Science and Technology, number WORMS/24/04.
• İbrahim Tutar & Özge Orbey, 2024, "Start-up Değerlemesi: Yeni bir Yöntem Önerisi," Journal of Research in Economics, Politics & Finance, Ersan ERSOY, volume 9, issue 3, pages 549-574, DOI: 10.30784/epfad.1475685.
• Lucian MIRESCU & Ana-Maria Camelia POPESCU, 2024, "Analysis And Forecast Of The Employees In The Public And Private Health Systems In Romania," Management and Marketing Journal, University of Craiova, Faculty of Economics and Business Administration, volume 0, issue 1, pages 113-138, May.
• Liudmyla DOROKHOVA & Silvia BELOEVA & Nataliya VENELINOVA & Oleksandr DOROKHOV, 2024, "Consumer service modeling: the study of buyer’s queues in pharmacies," Access Journal, Access Press Publishing House, volume 5, issue 3, pages 511-525, July, DOI: 10.46656/access.2024.5.3(8).
• Evgeny V. Balatsky, Natalia A. Ekimova, 2024, "Identification of Economies of Scale in Regional-Industrial Production Complexes of Russia: Theoretical Foundations and Econometric Estimates," Journal of Applied Economic Research, Graduate School of Economics and Management, Ural Federal University, volume 23, issue 2, pages 394-421, DOI: https://doi.org/10.15826/vestnik.20.
• Elena G. Shershneva, Min Zhou Hao, 2024, "Russian Banks Financial Stability Loss Diagnostic: Multidimensional Logit-Model Approach," Journal of Applied Economic Research, Graduate School of Economics and Management, Ural Federal University, volume 23, issue 2, pages 476-498, DOI: https://doi.org/10.15826/vestnik.20.
• Algieri, Bernardina & Iania, Leonardo & Leccadito, Arturo, 2024, "Looking ahead: Forecasting total energy carbon dioxide emissions," LIDAM Reprints LFIN, Université catholique de Louvain, Louvain Finance (LFIN), number 2024007, Jan, DOI: https://doi.org/10.1016/j.cesys.202.
• Gabriel P. Mathy & Yongchen Zhao, 2024, "Could Diffusion Indexes Have Forecasted the Great Recession?," Working Papers, American University, Department of Economics, number 2024-03.
• Ozge Camalan & Sahika Gokmen & Sibel Atan, 2024, "Using Advanced Machine Learning Techniques to Predict the Sales Volume of Non-Fungible Tokens," World Journal of Applied Economics, WERI-World Economic Research Institute, volume 10, issue 1, pages 17-27, June, DOI: 10.22440/wjae.10.1.2.
• Merve Kılınç Yılmaz & Yusuf Şahin & Kenan Oğuzhan Oruç, 2024, "Price Forecasting of Feed Raw Materials Used in Dairy Farming: A Methodological Comparison," Alphanumeric Journal, Bahadir Fatih Yildirim, volume 12, issue 3, pages 249-280, December, DOI: https://doi.org/10.17093/alphanumer.
• Құратова Ақбөпе // Kuratova Akbope & Ускенбаев Азат // Uskenbayev Azat, 2024, "Подходы К Оценке Устойчивости Внешнего Сектора Казахстана," Working Papers, National Bank of Kazakhstan, number #2024-9.
• Konrad Raczkowski & Jarosław Klepacki, 2024, "Typologia metod prognozowania kursu walutowego," Ekonomista, Polskie Towarzystwo Ekonomiczne, issue 3, pages 350-366.
• Alberto Vindas-Quesada & Carlos Brenes-Soto & Adriana Sandí-Esquivel & Susan Jiménez-Montero, 2024, "Univariate inflation forecasts in Costa Rica: model evaluation and selection," Notas Técnicas, Banco Central de Costa Rica, number 2405, Oct.
• Inna S. Lola & Dmitry G. Asoskov, 2024, "Potential of business uncertainty indicators in forecasting economic activity: The case of Russia," Russian Journal of Economics, ARPHA Platform, volume 10, issue 4, pages 351-364, December, DOI: 10.32609/j.ruje.10.113578.
• Anna A. Maigur, 2024, "Machine learning algorithms for predicting unemployment duration in Russia," Russian Journal of Economics, ARPHA Platform, volume 10, issue 4, pages 365-384, December, DOI: 10.32609/j.ruje.10.128611.
• Takaaki Koike & Cathy W. S. Chen & Edward M. H. Lin, 2024, "Forecasting and Backtesting Gradient Allocations of Expected Shortfall," Papers, arXiv.org, number 2401.11701, Jan, revised Jun 2024.
• M. Hashem Pesaran & Ron P. Smith, 2024, "High-dimensional forecasting with known knowns and known unknowns," Papers, arXiv.org, number 2401.14582, Jan, revised Apr 2024.
• Davide Fiaschi & Cristina Tealdi, 2024, "Let's roll back! The challenging task of regulating temporary contracts," Papers, arXiv.org, number 2401.17971, Jan.
• Andrea Bastianin & Elisabetta Mirto & Yan Qin & Luca Rossini, 2024, "What drives the European carbon market? Macroeconomic factors and forecasts," Papers, arXiv.org, number 2402.04828, Feb, revised Feb 2024.
• Arnaud Dufays & Aristide Houndetoungan & Alain Coen, 2024, "Selective linear segmentation for detecting relevant parameter changes," Papers, arXiv.org, number 2402.05329, Feb.
• Jeff Dominitz & Charles F. Manski, 2024, "Comprehensive OOS Evaluation of Predictive Algorithms with Statistical Decision Theory," Papers, arXiv.org, number 2403.11016, Mar, revised Apr 2025.
• Bartosz Bieganowski & Robert Slepaczuk, 2024, "Supervised Autoencoder MLP for Financial Time Series Forecasting," Papers, arXiv.org, number 2404.01866, Apr, revised Jun 2024.
• Arkadiusz Lipiecki & Bartosz Uniejewski & Rafa{l} Weron, 2024, "Postprocessing of point predictions for probabilistic forecasting of day-ahead electricity prices: The benefits of using isotonic distributional regression," Papers, arXiv.org, number 2404.02270, Apr, revised Oct 2024.
• M. Hashem Pesaran & Andreas Pick & Allan Timmermann, 2024, "Forecasting with panel data: Estimation uncertainty versus parameter heterogeneity," Papers, arXiv.org, number 2404.11198, Apr, revised Jan 2026.
• Tony Chernis & Gary Koop & Emily Tallman & Mike West, 2024, "Decision synthesis in monetary policy," Papers, arXiv.org, number 2406.03321, Jun, revised Feb 2025.
• Kamil Kashif & Robert 'Slepaczuk, 2024, "LSTM-ARIMA as a Hybrid Approach in Algorithmic Investment Strategies," Papers, arXiv.org, number 2406.18206, Jun.
• Maciej Wysocki & Robert 'Slepaczuk, 2024, "Construction and Hedging of Equity Index Options Portfolios," Papers, arXiv.org, number 2407.13908, Jul.
• Jannik Kreye & Philipp Sibbertsen, 2024, "Testing for a Forecast Accuracy Breakdown under Long Memory," Papers, arXiv.org, number 2409.07087, Sep.
• Zhan Gao & Ji Hyung Lee & Ziwei Mei & Zhentao Shi, 2024, "LASSO Inference for High Dimensional Predictive Regressions," Papers, arXiv.org, number 2409.10030, Sep, revised Apr 2026.
• Laura Coroneo & Fabrizio Iacone, 2024, "Testing for equal predictive accuracy with strong dependence," Papers, arXiv.org, number 2409.12662, Sep.
• Matteo Mogliani & Florens Odendahl, 2024, "Density forecast transformations," Papers, arXiv.org, number 2412.06092, Dec.
• Kemal Kirtac & Guido Germano, 2024, "Sentiment trading with large language models," Papers, arXiv.org, number 2412.19245, Dec.
• Conrad, Christian & Lahiri, Kajal, 2024, "Heterogeneous Expectations among Professional Forecasters," Working Papers, University of Heidelberg, Department of Economics, number 0754, Oct.
• Xiao Li & Wenjun Xue & Kaimeng Zhang, 2024, "The Predictive Power of Monetary Policy on International Stock Market Returns-Evidence From TV-ARMAX Model," Asian Economics Letters, Asia-Pacific Applied Economics Association, volume 5, issue 2, pages 1-8, DOI: 2024/06/28.
• Xiaohang Ren & Kang Yuan & Lizhu Tao & Cheng Yan, 2024, "Carbon Prices Forecasting Using Group Information," Energy RESEARCH LETTERS, Asia-Pacific Applied Economics Association, volume 4, issue 4, pages 1-6, DOI: 2024/07/09.
• Massimiliano MARCELLINO & Michael PFARRHOFER, 2024, "Bayesian nonparametric methods for macroeconomic forecasting," BAFFI CAREFIN Working Papers, BAFFI CAREFIN, Centre for Applied Research on International Markets Banking Finance and Regulation, Universita' Bocconi, Milano, Italy, number 24224.
• Monia Magnani, 2024, "Does Macroeconomic Predictability Enhance the Economic Value of Hedge Funds to Risk-Averse Investors?," BAFFI CAREFIN Working Papers, BAFFI CAREFIN, Centre for Applied Research on International Markets Banking Finance and Regulation, Universita' Bocconi, Milano, Italy, number 24232.
• Etienne Briand & Massimiliano Marcellino & Dalibor Stevanovic, 2024, "Inflation, Attention and Expectations," Working Papers, Chair in macroeconomics and forecasting, University of Quebec in Montreal's School of Management, number 24-05, Dec, revised Dec 2024.
• Antoine Poulin-Moore & Kerem Tuzcuoglu, 2024, "Forecasting Recessions in Canada: An Autoregressive Probit Model Approach," Staff Working Papers, Bank of Canada, number 24-10, Mar, DOI: 10.34989/swp-2024-10.
• Tony Chernis & Gary Koop & Emily Tallman & Mike West, 2024, "Decision Synthesis in Monetary Policy," Staff Working Papers, Bank of Canada, number 24-30, Aug, DOI: 10.34989/swp-2024-30.
• Pablo Garcia & Pascal Jacquinot & Crt Lenarcic & Kostas Mavromatis & Niki Papadopoulou & Edgar Silgado-Gómez, 2024, "Green Transition in the euro area: Domestic and global factors," BCL working papers, Central Bank of Luxembourg, number 190, Sep.
• Furkan TURKOGLU & Eda GOCECEK & Yavuz YUMRUKUZ, 2024, "Predictive Abilities of Machine Learning and Deep Learning Approaches for Exchange Rate Prediction," Journal of BRSA Banking and Financial Markets, Banking Regulation and Supervision Agency, volume 18, issue 2, pages 186-210.
• Todd E. Clark & Gergely Ganics & Elmar Mertens, 2024, "Constructing fan charts from the ragged edge of SPF forecasts," Working Papers, Banco de España, number 2429, Sep, DOI: https://doi.org/10.53479/37597.
• Alicia Aguilar & Ricardo Gimeno, 2024, "Discrete Probability Forecasts: What to expect when you are expecting a monetary policy decision," Working Papers, Banco de España, number 2438, Oct, DOI: https://doi.org/10.53479/37893.
• Francesco Braggiotti & Nicola Chiarini & Giulio Dondi & Luciano Lavecchia & Valeria Lionetti & Juri Marcucci & Riccardo Russo, 2024, "Predicting buildings' EPC in Italy: a machine learning based-approach," Questioni di Economia e Finanza (Occasional Papers), Bank of Italy, Economic Research and International Relations Area, number 850, Jun.
• Davide Delle Monache & Claudia Pacella, 2024, "The drivers of inflation dynamics in Italy over the period 2021-2023," Questioni di Economia e Finanza (Occasional Papers), Bank of Italy, Economic Research and International Relations Area, number 873, Oct.
• Donato Ceci & Orest Prifti & Andrea Silvestrini, 2024, "Nowcasting Italian GDP growth: a Factor MIDAS approach," Temi di discussione (Economic working papers), Bank of Italy, Economic Research and International Relations Area, number 1446, Mar.
• Andrea Gazzani & Fabrizio Venditti & Giovanni Veronese, 2024, "Oil price shocks in real time," Temi di discussione (Economic working papers), Bank of Italy, Economic Research and International Relations Area, number 1448, Mar.
• Simon Freyaldenhoven & Christian B. Hansen & Jorge Pérez Pérez & Jesse M. Shapiro & Constantino Carreto, 2024, "Policy Effect Estimation and Visualization in Linear Panel Event-Study Designs: Introducing the xtevent Package," Working Papers, Banco de México, number 2024-09, Aug.
• Lenin Arango-Castillo & Francisco J. Martínez-Ramírez & María José Orraca, 2024, "Univariate Measures of Persistence: A Comparative Analysis," Working Papers, Banco de México, number 2024-11, Sep.
• Magnus Saß, 2024, "Detecting excessive credit growth: An approach based on structural counterfactuals," Berlin School of Economics Discussion Papers, Berlin School of Economics, number 0046, Aug, DOI: 10.48462/opus4-5591.
• Gary Cornwall & Marina Gindelsky, 2024, "Nowcasting Distributional National Accounts for the United States: A Machine Learning Approach," BEA Papers, Bureau of Economic Analysis, number 0130, Sep.
• Pınar Karadayı Ataş, 2024, "A Novel Hybrid Regression Model for Banking Loss Estimation," Bingol University Journal of Economics and Administrative Sciences, Bingol University, Faculty of Economics and Administrative Sciences, volume 8, issue 1, pages 91-105, June, DOI: https://doi.org/10.33399/biibfad.13.
• Ilia Chapyshev & Ansel Shaidullin, 2024, "Study of the Problem of Interoperability of the Bank of Russia's Digital Currency," Russian Journal of Money and Finance, Bank of Russia, volume 83, issue 1, pages 104-126, March.
• Anastasiia Pankratova, 2024, "Forecasting Key Macroeconomic Indicators Using DMA and DMS Methods," Russian Journal of Money and Finance, Bank of Russia, volume 83, issue 1, pages 32-52, March.
• Urmat Dzhunkeev, 2024, "Forecasting Inflation in Russia Using Gradient Boosting and Neural Networks," Russian Journal of Money and Finance, Bank of Russia, volume 83, issue 1, pages 53-76, March.
• Anastasia Mogilat & Oleg Kryzhanovskiy & Zhanna Shuvalova & Yaroslav Murashov, 2024, "DYFARUS: Dynamic Factor Model to Forecast GDP by Output Using Input-Output Tables," Russian Journal of Money and Finance, Bank of Russia, volume 83, issue 2, pages 3-25, June.
• Yury Perevyshin, 2024, "Analysts' Inflation Expectations vs Univariate Models of Inflation Forecasting in the Russian Economy," Russian Journal of Money and Finance, Bank of Russia, volume 83, issue 2, pages 54-76, June.
• Rodion Latypov & Elena Akhmedova & Egor Postolit & Marina Mikitchuk, 2024, "Bottom-up Inflation Forecasting Using Machine Learning Methods," Russian Journal of Money and Finance, Bank of Russia, volume 83, issue 3, pages 23-44, September.
• Alexandra Bozhechkova & Urmat Dzhunkeev, 2024, "CLARA and CARLSON: Combination of Ensemble and Neural Network Machine Learning Methods for GDP Forecasting," Russian Journal of Money and Finance, Bank of Russia, volume 83, issue 3, pages 45-69, September.
• Oguzhan Cepni & Rangan Gupta & Wenting Liao & Jun Ma, 2024, "Climate risks and forecastability of the weekly state‐level economic conditions of the United States," International Review of Finance, International Review of Finance Ltd., volume 24, issue 1, pages 154-162, March, DOI: 10.1111/irfi.12431.
• Leona Han Chen & Yijie Fei & Jun Yu, 2024, "Multivariate Stochastic Volatility Models based on Generalized Fisher Transformation," Working Papers, University of Macau, Faculty of Business Administration, number 202419, Oct.
• Fernando Eguren-Martin & Sevim Kösem & Guido Maia & Andrej Sokol, 2024, "Targeted financial conditions indices and growth-at-risk," Bank of England Staff Working Paper series, Bank of England, number 1084, Aug.
• Mehrabani Ali & Parsaeian Shahnaz & Ullah Aman, 2024, "Shrinkage Estimation and Forecasting in Dynamic Regression Models Under Structural Instability," Journal of Econometric Methods, De Gruyter, volume 13, issue 2, pages 251-279, DOI: 10.1515/jem-2023-0036.
• Prüser Jan, 2024, "Forecasting the Risk of Cryptocurrencies: Comparison and Combination of GARCH and Stochastic Volatility Models," Journal of Time Series Econometrics, De Gruyter, volume 16, issue 2, pages 83-108, DOI: 10.1515/jtse-2023-0039.
• Mohamed Riyath Mohamed Ismail & Aldabbous Nagham, 2024, "Long-Run Volatility Memory Dynamics and Inter-Market Linkages in GCC Equity Markets: Application of DCC-FIGARCH Models," Review of Middle East Economics and Finance, De Gruyter, volume 20, issue 3, pages 299-329, DOI: 10.1515/rmeef-2024-0018.
• Chernis Tony, 2024, "Combining Large Numbers of Density Predictions with Bayesian Predictive Synthesis," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, volume 28, issue 2, pages 293-317, April, DOI: 10.1515/snde-2022-0108.