Research classified by Journal of Economic Literature (JEL) codes

1. Forecasting

2024

• Dr. Marc Ingo Wolter & Florian Bernardt & Jannik Daßler & Saskia Reuschel & Dr. Britta Stöver, 2024, "Klimafolgen und Anpassung – 2024," GWS Research Report Series, GWS - Institute of Economic Structures Research, number 24-2.
• Abdelaati Daouia & Simone A. Padoan & Gilles Stupfler, 2024, "Extreme expectile estimation for short-tailed data," Post-Print, HAL, number hal-04672516, DOI: 10.1016/j.jeconom.2024.105770.
• Rafael Branco & Alexandre Rubesam & Mauricio Zevallos, 2024, "Forecasting realized volatility: Does anything beat linear models?," Post-Print, HAL, number hal-04835657, Sep, DOI: 10.1016/j.jempfin.2024.101524.
• Amal Ben Hamida & Christian de Peretti & Lotfi Belkacem, 2024, "The link between abnormal numbers and price movements of financial securities: How does Benford’s law predict stock returns?," Post-Print, HAL, number hal-04875454, Oct, DOI: 10.1016/j.irfa.2024.103517.
• Michele Lenza & Inès Moutachaker & Joan Paredes, 2024, "Density forecasts of inflation: a quantile regression forest approach
  [Prévisions de densité de l'inflation : une approche par forêt de régressions quantile]," Working Papers, HAL, number hal-05329662, Jun.
• Kreye, Tom Jannik & Sibbertsen, Philipp, 2024, "Testing for a Forecast Accuracy Breakdown under Long Memory," Hannover Economic Papers (HEP), Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät, number dp-729, Nov.
• Tea Šestanović, 2024, "A Comprehensive Approach To Bitcoin Forecasting Using Neural Networks," Ekonomski pregled, Hrvatsko društvo ekonomista (Croatian Society of Economists), volume 75, issue 1, pages 62-85, DOI: 10.32910/ep.75.1.3.
• Sheybanivaziri, Samaneh & Le Dréau, Jérôme & Kazmi, Hussain, 2024, "Forecasting price spikes in day-ahead electricity markets: techniques, challenges, and the road ahead," Discussion Papers, Norwegian School of Economics, Department of Business and Management Science, number 2024/1, Jan.
• Narum, Benjamin S. & Berentsen, Geir D., 2024, "Joint Forecasting of Salmon Lice and Treatment Interventions in Aquaculture Operations," Discussion Papers, Norwegian School of Economics, Department of Business and Management Science, number 2024/7, May.
• Shchestyuk, Nataliya & Tyshchenkob, Sergii, 2024, "Subdiffusive option price model with Inverse Gaussian subordinator," Working Papers, Örebro University, School of Business, number 2024:1, Jan.
• Pettersson, Nicklas & Kelemen, Katalin, 2024, "Yet another case of Nordic exceptionalism?: A quantitative approach to an intra-Nordic and an international comparison of supreme courts’ constitutional reasoning," Working Papers, Örebro University, School of Business, number 2024:7, Aug.
• Bårdsen, Gunnar & Nymoen, Ragnar, 2024, "U.S. wage-price dynamics, before, during and after COVID-19, through the lens of an empirical econometric model," Memorandum, Oslo University, Department of Economics, number 1/2024, Jun.
• Kim Karlsson, Hyunjoo & Li, Yushu, 2024, "Investigation of Swedish krona exchange rate volatility by APARCH-Support Vector Regression," Working Papers in Economics and Statistics, Linnaeus University, School of Business and Economics, Department of Economics and Statistics, number 10/2024, Jun.
• HARA, Naoko & YAMAMOTO, Yohei, 2024, "Testing and Quantifying Economic Resilience," Discussion paper series, Hitotsubashi Institute for Advanced Study, Hitotsubashi University, number HIAS-E-142, Nov.
• Alison Baulos & Jorge Luis Garcia & James J. Heckman, 2024, "Perry Preschool at 50: What Lessons Should Be Drawn and Which Criticisms Ignored?," Working Papers, Human Capital and Economic Opportunity Working Group, number 2024-019, Nov.
• Berg, Gerard J. van den & Kunaschk, Max & Lang, Julia & Stephan, Gesine & Uhlendorff, Arne, 2024, "Predicting Re-Employment: Machine Learning Versus Assessments by Unemployed Workers and by Their Caseworkers," IAB-Discussion Paper, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany], number 202403, Feb, DOI: 10.48720/IAB.DP.2403.
• Bjarni G. Einarsson, 2024, "Online Monitoring of Policy Optimality," Economics, Department of Economics, Central bank of Iceland, number wp95, Apr.
• Agarwala, Matthew & Burke, Matt & Doherty-Bigara, Jennifer & Klusak, Patrycja & Mohaddes, Kamiar, 2024, "Climate Change and Sovereign Risk: A Regional Analysis for the Caribbean," IDB Publications (Working Papers), Inter-American Development Bank, number 13478, Apr, DOI: http://dx.doi.org/10.18235/0012885.
• Benítez, Miguel & Parrado, Eric, 2024, "Mirror, Mirror on the Wall: Which Jobs Will AI Replace After All?: A New Index of Occupational Exposure," IDB Publications (Working Papers), Inter-American Development Bank, number 13696, Aug, DOI: http://dx.doi.org/10.18235/0013125.
• Kaustubh & Soumya Bhadury & Saurabh Ghosh, 2024, "Reinvigorating GVA Nowcasting in the Post-pandemic Period: A Case Study for India," Bulletin of Monetary Economics and Banking, Bank Indonesia, volume 27, issue Spesial I, pages 95-130, February, DOI: https://doi.org/10.59091/2460-9196..
• Gabriel, Stefan & Kunst, Robert M., 2024, "Cointegrated portfolios and volatility modeling in the cryptocurrency market," IHS Working Paper Series, Institute for Advanced Studies, number 52, Mar.
• Cullen S. Hendrix, 2024, "The El Nino Southern Oscillation and Geopolitical Risk," Working Paper Series, Peterson Institute for International Economics, number WP24-14, May.
• Mahir Binici & Samuele Centorrino & Serhan Cevik & Gyowon Gwon, 2024, "Here Comes the Change: The Role of Global and Domestic Factors in Post-Pandemic Inflation in Europe," International Journal of Central Banking, International Journal of Central Banking, volume 20, issue 2, pages 237-290, April.
• Frank Schorfheide & Dongho Song, 2024, "Real-Time Forecasting with a (Standard) Mixed-Frequency VAR During a Pandemic," International Journal of Central Banking, International Journal of Central Banking, volume 20, issue 4, pages 275-320, October.
• Ferdinand Fichtner & Heike Joebges, 2024, "Stock market returns and GDP growth," IMK Studies, IMK at the Hans Boeckler Foundation, Macroeconomic Policy Institute, number 90-2024.
• Adrián F. Rossignolo, 2024, "Basel IV and the structural relationship between SA and IMA," Remef - Revista Mexicana de Economía y Finanzas Nueva Época REMEF (The Mexican Journal of Economics and Finance), Instituto Mexicano de Ejecutivos de Finanzas, IMEF, volume 19, issue 2, pages 1-37, Abril - J.
• Erwis Melchor Pérez & Moisés Emmanuel Ramírez Guzmán & Araceli Hernández Jiménez & Agustín Santiago Alvarado, 2024, "Predicción del riesgo crediticio a microfinanciera usando aprendizaje computacional," Remef - Revista Mexicana de Economía y Finanzas Nueva Época REMEF (The Mexican Journal of Economics and Finance), Instituto Mexicano de Ejecutivos de Finanzas, IMEF, volume 19, issue 4, pages 1-16, Octubre -.
• Helena Chuliá & Sabuhi Khalili & Jorge M. Uribe, 2024, "Monitoring time-varying systemic risk in sovereign debt and currency markets with generative AI," IREA Working Papers, University of Barcelona, Research Institute of Applied Economics, number 202402, Feb, revised Feb 2024.
• Adrián Fernandez-Perez & Marta Gómez-Puig & Simón Sosvilla-Rivero, 2025, "Examining the transmission of credit and liquidity risks: A network analysis for EMU sovereign debt markets," IREA Working Papers, University of Barcelona, Research Institute of Applied Economics, number 202504, Jan.
• Huo, Shutong & Feng, Derek & Gill, Thomas M. & Chen, Xi, 2024, "Childhood Circumstances and Health of American and Chinese Older Adults: A Machine Learning Evaluation of Inequality of Opportunity in Health," IZA Discussion Papers, IZA Network @ LISER, number 16764, Jan.
• Fiaschi, Davide & Tealdi, Cristina, 2024, "Let's Roll Back! The Challenging Task of Regulating Temporary Contracts," IZA Discussion Papers, IZA Network @ LISER, number 16777, Jan.
• Kumar, Pradeep & Nicodemo, Catia & Oreffice, Sonia & Quintana-Domeque, Climent, 2024, "Machine Learning and Multiple Abortions," IZA Discussion Papers, IZA Network @ LISER, number 17046, Jun.
• Hyee, Raphaela & Immervoll, Herwig & Fernandez, Rodrigo & Lee, Jongmi & Handscomb, Karl, 2024, "How Reliable Are Social Safety Nets in Situations of Acute Economic Need? Extended Estimates for 14 OECD Countries," IZA Discussion Papers, IZA Network @ LISER, number 17477, Nov.
• TORI Athina & GJECI Ardit & KUFO Andromahi, 2024, "Emerging from the Storm: Forecasting Bank Loan Quality in the Aftermath of COVID-19," European Journal of Interdisciplinary Studies, Bucharest Economic Academy, issue 01, March.
• Sandra Dreher & Sebastian Eichfelder & Felix Noth, 2024, "Does IFRS information on tax loss carryforwards and negative performance improve predictions of earnings and cash flows?," Journal of Business Economics, Springer, volume 94, issue 1, pages 1-39, January, DOI: 10.1007/s11573-023-01147-7.
• J. Peter Leo Deepak & Yavana Rani Subramanian & J. Josephine Lalitha & K. Vidhya, 2024, "Optimum Level of Currency Reserves: Investigation and Forecasting of Indian Rupee Using ARIMA Model," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), volume 20, issue 1, pages 137-150, August, DOI: 10.1007/s41549-023-00091-3.
• Maximilian Boeck & Massimiliano Marcellino & Michael Pfarrhofer & Tommaso Tornese, 2024, "Predicting Tail-Risks for the Italian Economy," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), volume 20, issue 3, pages 339-366, November, DOI: 10.1007/s41549-025-00106-1.
• Jörg Döpke & Tim Köhler & Lars Tegtmeier, 2024, "Are they worth it? – An evaluation of predictions for NBA ‘Fantasy Sports’," Journal of Economics and Finance, Springer;Academy of Economics and Finance, volume 48, issue 1, pages 142-165, March, DOI: 10.1007/s12197-023-09646-7.
• Isaac K. Ofori & Camara K. Obeng & Simplice A. Asongu, 2024, "What Really Drives Economic Growth in Sub-Saharan Africa? Evidence from the Lasso Regularization and Inferential Techniques," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), volume 15, issue 1, pages 144-179, March, DOI: 10.1007/s13132-022-01055-1.
• Dervis Kirikkaleli & Fusun Celebi Boz & Melike Torun, 2024, "Do Economic and Financial Stabilities Matter for Political Stability in Estonia?," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), volume 15, issue 3, pages 15202-15217, September, DOI: 10.1007/s13132-023-01662-6.
• Filip Lubinski, 2024, "Book review. J. Doyne Farmer, Making Sense of Chaos. A Better Economics for a Better World, Penguin (2024), pp. 364," Journal of Evolutionary Economics, Springer, volume 34, issue 4, pages 1013-1017, December, DOI: 10.1007/s00191-024-00876-4.
• Agnieszka Orwat-Acedańska, 2024, "Accuracy of small area mortality prediction methods: evidence from Poland," Journal of Population Research, Springer, volume 41, issue 1, pages 1-20, March, DOI: 10.1007/s12546-023-09326-7.
• Gavin Ooft & Sailesh Bhaghoe & Philip Hans Franses, 2024, "Forecasting Annual Inflation Using Weekly Money Supply," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), volume 22, issue 1, pages 25-43, March, DOI: 10.1007/s40953-023-00376-5.
• Kristian Jönsson, 2024, "Neighbor Weighting and Distance Metrics in Nearest Neighbor Nowcasting of Swedish GDP," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), volume 22, issue 4, pages 1077-1089, December, DOI: 10.1007/s40953-024-00400-2.
• Seyed Farshid Ghorashi & Maziyar Bahri & Atousa Goodarzi, 2024, "Developing and comparing machine learning approaches for predicting insurance penetration rates based on each country," Letters in Spatial and Resource Sciences, Springer, volume 17, issue 1, pages 1-29, December, DOI: 10.1007/s12076-024-00387-7.
• Claudia Ceci & Michele Bufalo & Giuseppe Orlando, 2024, "Modelling the industrial production of electric and gas utilities through the $$CIR^3$$ C I R 3 model," Mathematics and Financial Economics, Springer, number 1, January, DOI: 10.1007/s11579-023-00350-y.
• Giorgio Gnecco & Sara Landi & Massimo Riccaboni, 2024, "The emergence of social soft skill needs in the post COVID-19 era," Quality & Quantity: International Journal of Methodology, Springer, volume 58, issue 1, pages 647-680, February, DOI: 10.1007/s11135-023-01659-y.
• Afees Salisu & Sulaiman Salisu & Subair Salisu, 2024, "A news-based economic policy uncertainty index for Nigeria," Quality & Quantity: International Journal of Methodology, Springer, volume 58, issue 5, pages 4987-5002, October, DOI: 10.1007/s11135-024-01886-x.
• Chris Reimann, 2024, "Predicting financial crises: an evaluation of machine learning algorithms and model explainability for early warning systems," Review of Evolutionary Political Economy, Springer, volume 5, issue 1, pages 51-83, June, DOI: 10.1007/s43253-024-00114-4.
• Diego Fresoli, 2024, "Spanish GDP short-term point and density forecasting using a mixed-frequency dynamic factor model," SERIEs: Journal of the Spanish Economic Association, Springer;Spanish Economic Association, volume 15, issue 2, pages 145-177, June, DOI: 10.1007/s13209-024-00297-3.
• Philipp Wegmueller & Christian Glocker, 2024, "Capturing Swiss economic confidence," Swiss Journal of Economics and Statistics, Springer;Swiss Society of Economics and Statistics, volume 160, issue 1, pages 1-17, December, DOI: 10.1186/s41937-024-00120-7.
• Riadh Trabelsi, 2024, "Sources of macroeconomic fluctuations in Tunisia: a structural VAR approach," SN Business & Economics, Springer, volume 4, issue 10, pages 1-28, October, DOI: 10.1007/s43546-024-00717-3.
• M’bakob Gilles Brice & Mandeng ma Ntamack Jules, 2024, "Influence of psychological exchange rates (PER) on forex price formation: theory, empirical, and experimental evidence," SN Business & Economics, Springer, volume 4, issue 9, pages 1-53, September, DOI: 10.1007/s43546-024-00698-3.
• Kazım Berk Küçüklerli & Veysel Ulusoy, 2024, "Sentiment-Driven Exchange Rate Forecasting: Integrating Twitter Analysis with Economic Indicators," Journal of Applied Finance & Banking, SCIENPRESS Ltd, volume 14, issue 3, pages 1-4.
• Pål Boug & Håvard Hungnes & Takamitsu Kurita, 2024, "Getting Back on Track. Forecasting After Extreme Observations," Discussion Papers, Statistics Norway, Research Department, number 1018, Dec.
• Joana Katina & Joana Katina & Igor Katin & Igor Katin & Vera Komarova, 2024, "Cryptocurrency price forecasting: a comparative analysis of autoregressive and recurrent neural network models," Entrepreneurship and Sustainability Issues, VsI Entrepreneurship and Sustainability Center, volume 11, issue 4, pages 425-436, June, DOI: 10.9770/jesi.2024.11.4(26).
• Givi Bedianashvili & Murman Tsartsidze & Nino Mikeladze & Zviad Gabroshvili, 2024, "Human capital and economic growth under modern globalization," Entrepreneurship and Sustainability Issues, VsI Entrepreneurship and Sustainability Center, volume 12, issue 1, pages 268-289, September, DOI: 10.9770/jesi.2024.12.1(19).
• Yasin Mimir & Lorenzo Ricci, 2024, "Financial imbalances and macroeconomic tail risks: A structural regime-switching investigation," Working Papers, European Stability Mechanism, number 64, Nov, revised 15 Nov 2024.
• Luke Hartigan & Tom Rosewall, 2024, "Nowcasting Quarterly GDP Growth during the COVID-19 Crisis Using a Monthly Activity Indicator," Working Papers, University of Sydney, School of Economics, number 2024-15, Jul.
• Monica Billio & Roberto Casarin & Matteo Iacopini, 2024, "Bayesian Markov-Switching Tensor Regression for Time-Varying Networks," Journal of the American Statistical Association, Taylor & Francis Journals, volume 119, issue 545, pages 109-121, January, DOI: 10.1080/01621459.2022.2102502.
• Liu Yang & Kajal Lahiri & Adrian Pagan, 2024, "Getting the ROC into Sync," Journal of Business & Economic Statistics, Taylor & Francis Journals, volume 42, issue 1, pages 109-121, January, DOI: 10.1080/07350015.2022.2154778.
• James Morley & Trung Duc Tran & Benjamin Wong, 2024, "A Simple Correction for Misspecification in Trend-Cycle Decompositions with an Application to Estimating r," Journal of Business & Economic Statistics, Taylor & Francis Journals, volume 42, issue 2, pages 665-680, April, DOI: 10.1080/07350015.2023.2221974.
• Davide Delle Monache & Andrea De Polis & Ivan Petrella, 2024, "Modeling and Forecasting Macroeconomic Downside Risk," Journal of Business & Economic Statistics, Taylor & Francis Journals, volume 42, issue 3, pages 1010-1025, July, DOI: 10.1080/07350015.2023.2277171.
• David Ardia & Arnaud Dufays & Carlos Ordás Criado, 2024, "Linking Frequentist and Bayesian Change-Point Methods," Journal of Business & Economic Statistics, Taylor & Francis Journals, volume 42, issue 4, pages 1155-1168, October, DOI: 10.1080/07350015.2023.2293166.
• Todd E. Clark & Florian Huber & Gary Koop & Massimiliano Marcellino & Michael Pfarrhofer, 2024, "Investigating Growth-at-Risk Using a Multicountry Nonparametric Quantile Factor Model," Journal of Business & Economic Statistics, Taylor & Francis Journals, volume 42, issue 4, pages 1302-1317, October, DOI: 10.1080/07350015.2024.2310020.
• Raffaele Mattera & George Athanasopoulos & Rob Hyndman, 2024, "Improving out-of-sample forecasts of stock price indexes with forecast reconciliation and clustering," Quantitative Finance, Taylor & Francis Journals, volume 24, issue 11, pages 1641-1667, November, DOI: 10.1080/14697688.2024.2412687.
• Mihaela Simionescu & Nicolas Schneider & Beata Gavurova, 2024, "A Bayesian vector-autoregressive application with time-varying parameters on the monetary shocks–production network nexus," Journal of Applied Economics, Taylor & Francis Journals, volume 27, issue 1, pages 2395114-239, December, DOI: 10.1080/15140326.2024.2395114.
• Salih Zeki Atilgan & Tarik Aydogdu & Mehmet Selman Colak & Muhammed Hasan Yilmaz, 2024, "Anticipating Credit Developments with Regularization and Shrinkage Methods: Evidence for Turkish Banking Industry," Working Papers, Research and Monetary Policy Department, Central Bank of the Republic of Turkey, number 2402.
• Anne Opschoor & Dewi Peerlings & Luca Rossini & Andre Lucas, 2024, "Density Forecasting for Electricity Prices under Tail Heterogeneity with the t-Riesz Distribution," Tinbergen Institute Discussion Papers, Tinbergen Institute, number 24-049/III, Jul.
• Gabriele Mingoli, 2024, "Modeling Common Bubbles: A Mixed Causal Non-Causal Dynamic Factor Model," Tinbergen Institute Discussion Papers, Tinbergen Institute, number 24-072/III, Nov.
• Pierluigi Vallarino, 2024, "Dynamic kernel models," Tinbergen Institute Discussion Papers, Tinbergen Institute, number 24-082/III, Dec.
• Andrea Carriero & Todd E. Clark & Massimiliano Marcellino & Elmar Mertens, 2024, "Addressing COVID-19 Outliers in BVARs with Stochastic Volatility," The Review of Economics and Statistics, MIT Press, volume 106, issue 5, pages 1403-1417, September, DOI: 10.1162/rest_a_01213.
• Felix Haase, 2024, "Sum-of-the-Parts Revised: Economic Regimes and Flexible Probabilities," Research Papers in Economics, University of Trier, Department of Economics, number 2024-10.
• Fayssal Jamhamed & Franck Martin & Fabien Rondeau & Josué Thélissaint & Stéphane Tufféry, 2024, "Regime-Specific Dynamics and Informational Efficiency in Cryptomarkets: Evidence from Gaussian Mixture Models," Economics Working Paper Archive (University of Rennes & University of Caen), Center for Research in Economics and Management (CREM), University of Rennes, University of Caen and CNRS, number 2024-13, Dec.
• Tae-Hwy Lee & Tao Wang, 2024, "Estimation and Testing of Forecast Rationality with Many Moments," Working Papers, University of California at Riverside, Department of Economics, number 202412, Dec.
• Zacharias Psaradakis & Martin Sola & Francisco Rapetti & Patricio Yunis, 2024, "The Role of Consumer Sentiment in the Stock Market: A Multivariate Dynamic Mixture Model with Threshold Effects," Department of Economics Working Papers, Universidad Torcuato Di Tella, number 2024_01, Apr.
• Zacharias Psaradakis & Martin Sola & Nicola Spagnolo & Patricio Yunis, 2024, "Predictive Accuracy of Impulse Responses Estimated Using Local Projections and Vector Autoregressions," Department of Economics Working Papers, Universidad Torcuato Di Tella, number 2024_02, May.
• Amelie BARBIER-GAUCHARD & Emmanouil SOFIANOS, 2024, "Forecasting Public Debt in the Euro Area Using Machine Learning: Decision Tools for Financial Markets," Working Papers of BETA, Bureau d'Economie Théorique et Appliquée, UDS, Strasbourg, number 2024-47.
• Paula Barro, 2024, "Imputación de ingresos del hogar en la Encuesta de Uso del Tiempo de Uruguay 2021-2022. Documento metodológico," Documentos de Trabajo (working papers), Instituto de Economía - IECON, number 24-19, Dec.
• Elena G. Shershneva, 2024, "CAMELS parameters’ impact on the risk of losing financial stability: The case of Russian banks," Journal of New Economy, Ural State University of Economics, volume 25, issue 2, pages 130-152, July, DOI: 10.29141/2658-5081-2024-25-2-7.
• Valdemar J. Undji & Johannes P. S. Sheefeni, 2024, "A factor-based framework for stress-testing the Namibian banking sector," Journal of New Economy, Ural State University of Economics, volume 25, issue 3, pages 112-137, December, DOI: 10.29141/2658-5081-2024-25-3-6.
• HABIBI, Reza, 2024, "A Note On The Early Warning System Of Change Points: Combination Of Regime Switching And Threshold Models," Studii Financiare (Financial Studies), Centre of Financial and Monetary Research "Victor Slavescu", volume 28, issue 2, pages 6-18, June.
• ANGHEL, Bogdan Ionuț, 2024, "Predicting Stock Price Direction Of Eurozone Banks: Can Deep Learning Techniques Outperform Traditional Models?," Studii Financiare (Financial Studies), Centre of Financial and Monetary Research "Victor Slavescu", volume 28, issue 4, pages 29-42, December.
• Yordan Petkov, 2024, "Forecasting The Number Of Human Resources In The Organization Using Markov Chains," INTERNATIONAL SCIENTIFIC AND PRACTICAL CONFERENCE "HUMAN RESOURCE MANAGEMENT", University of Economics - Varna, issue 1, pages 80-88.
• Svetlana Todorova, 2024, "Hedonic Modelling of Real Estate Prices in Varna," Stroitelno predpriemachestvo i nedvizhima sobstvenost = Construction Entrepreneurship and Real Property, University of Economics Varna, issue 1, pages 65-79.
• Radojković Ivan D. & Radović Ognjen V. & Stevanović Kristina R., 2024, "Modeling the Volatility of Returns on Investment Units of Voluntary Pension Funds in Serbia," Economic Themes, Sciendo, volume 62, issue 4, pages 541-560, DOI: 10.2478/ethemes-2024-0029.
• Mirescu Lucian & Popescu Liviu, 2024, "Forecasts of Performance Indicators in the Health System Using the Arima Method," Journal of Social and Economic Statistics, Sciendo, volume 13, issue 1, pages 1-22, DOI: 10.2478/jses-2024-0005.
• Mirescu Lucian & Popescu Liviu, 2024, "Forecasts on the Evolution of Human Resources in the Health System in Romania Using the Arima Method," Timisoara Journal of Economics and Business, Sciendo, volume 17, issue 1, pages 65-112, DOI: 10.2478/tjeb-2024-0004.
• Naz Farah & Lutfullah Tooba & Zahra Kanwal, 2024, "COVID-19 and Seasonality in Monthly Returns: a Firm Level Analysis of PSX," Zagreb International Review of Economics and Business, Sciendo, volume 27, issue 1, pages 201-230, DOI: 10.2478/zireb-2024-0010.
• Bartosz Bieganowski & Robert Ślepaczuk, 2024, "Supervised Autoencoder MLP for Financial Time Series Forecasting," Working Papers, Faculty of Economic Sciences, University of Warsaw, number 2024-03.
• Kamil Kashif & Robert Ślepaczuk, 2024, "LSTM-ARIMA as a Hybrid Approach in Algorithmic Investment Strategies," Working Papers, Faculty of Economic Sciences, University of Warsaw, number 2024-07.
• Sugarbayar Enkhbayar & Robert Ślepaczuk, 2024, "Predictive modeling of foreign exchange trading signals using machine learning techniques," Working Papers, Faculty of Economic Sciences, University of Warsaw, number 2024-10.
• Maciej Wysocki & Robert Ślepaczuk, 2024, "Construction and Hedging of Equity Index Options Portfolios," Working Papers, Faculty of Economic Sciences, University of Warsaw, number 2024-14.
• Stanisław Łaniewski & Robert Ślepaczuk, 2024, "Enhancing literature review with NLP methods Algorithmic investment strategies case," Working Papers, Faculty of Economic Sciences, University of Warsaw, number 2024-16.
• Filip Stefaniuk & Robert Ślepaczuk, 2024, "The article investigates the usage of Informer architecture for building automated trading strategies for high frequency Bitcoin data. Three strategies using Informer model with different loss functions: Root Mean Squared Error (RMSE), Generalized Me," Working Papers, Faculty of Economic Sciences, University of Warsaw, number 2024-27.
• Vasily Astrov & Artem Kochnev & Vincent Stamer & Feodora Teti, 2024, "The Russian Economy Amidst the War and Sanctions," Russia Monitor, The Vienna Institute for International Economic Studies, wiiw, number 1, Jan.
• Sulkhan Chavleishvili & Simone Manganelli, 2024, "Forecasting and stress testing with quantile vector autoregression," Journal of Applied Econometrics, John Wiley & Sons, Ltd., volume 39, issue 1, pages 66-85, January, DOI: 10.1002/jae.3009.
• Jia Liu & John M. Maheu & Yong Song, 2024, "Identification and forecasting of bull and bear markets using multivariate returns," Journal of Applied Econometrics, John Wiley & Sons, Ltd., volume 39, issue 5, pages 723-745, August, DOI: 10.1002/jae.3048.
• James Mitchell & Aubrey Poon & Dan Zhu, 2024, "Constructing density forecasts from quantile regressions: Multimodality in macrofinancial dynamics," Journal of Applied Econometrics, John Wiley & Sons, Ltd., volume 39, issue 5, pages 790-812, August, DOI: 10.1002/jae.3049.
• Florian Huber & Gary Koop, 2024, "Fast and order‐invariant inference in Bayesian VARs with nonparametric shocks," Journal of Applied Econometrics, John Wiley & Sons, Ltd., volume 39, issue 7, pages 1301-1320, November, DOI: 10.1002/jae.3087.
• Matteo Bonato & Oguzhan Cepni & Rangan Gupta & Christian Pierdzioch, 2024, "Business applications and state‐level stock market realized volatility: A forecasting experiment," Journal of Forecasting, John Wiley & Sons, Ltd., volume 43, issue 2, pages 456-472, March, DOI: 10.1002/for.3042.
• Peter McAdam & Anders Warne, 2024, "Density forecast combinations: The real‐time dimension," Journal of Forecasting, John Wiley & Sons, Ltd., volume 43, issue 5, pages 1153-1172, August, DOI: 10.1002/for.3068.
• Pablo Pincheira Brown & Nicolás Hardy, 2024, "Correlation‐based tests of predictability," Journal of Forecasting, John Wiley & Sons, Ltd., volume 43, issue 6, pages 1835-1858, September, DOI: 10.1002/for.3081.
• Matteo Bonato & Oguzhan Cepni & Rangan Gupta & Christian Pierdzioch, 2024, "Forecasting the realized volatility of agricultural commodity prices: Does sentiment matter?," Journal of Forecasting, John Wiley & Sons, Ltd., volume 43, issue 6, pages 2088-2125, September, DOI: 10.1002/for.3106.
• Chenxing Li & John M. Maheu & Qiao Yang, 2024, "An infinite hidden Markov model with stochastic volatility," Journal of Forecasting, John Wiley & Sons, Ltd., volume 43, issue 6, pages 2187-2211, September, DOI: 10.1002/for.3123.
• Pablo Pincheira Brown & Nicolás Hardy, 2024, "The mean squared prediction error paradox," Journal of Forecasting, John Wiley & Sons, Ltd., volume 43, issue 6, pages 2298-2321, September, DOI: 10.1002/for.3129.
• Utkarsh Kumar & Wasim Ahmad & Gazi Salah Uddin, 2024, "Bayesian Markov switching model for BRICS currencies' exchange rates," Journal of Forecasting, John Wiley & Sons, Ltd., volume 43, issue 6, pages 2322-2340, September, DOI: 10.1002/for.3128.
• Jesus Crespo Cuaresma & Ines Fortin & Jaroslava Hlouskova & Michael Obersteiner, 2024, "Regime‐dependent commodity price dynamics: A predictive analysis," Journal of Forecasting, John Wiley & Sons, Ltd., volume 43, issue 7, pages 2822-2847, November, DOI: 10.1002/for.3152.
• Arabinda Basistha & Richard Startz, 2024, "Measuring persistent global economic factors with output, commodity price, and commodity currency data," Journal of Forecasting, John Wiley & Sons, Ltd., volume 43, issue 7, pages 2860-2885, November, DOI: 10.1002/for.3139.
• Andrea Carriero & Todd E. Clark & Massimiliano Marcellino, 2024, "Capturing Macro‐Economic Tail Risks with Bayesian Vector Autoregressions," Journal of Money, Credit and Banking, Blackwell Publishing, volume 56, issue 5, pages 1099-1127, August, DOI: 10.1111/jmcb.13121.
• William A. Barnett & Marcelle Chauvet & Danilo Leiva‐Leon & Liting Su, 2024, "The Credit‐Card‐Services Augmented Divisia Monetary Aggregates," Journal of Money, Credit and Banking, Blackwell Publishing, volume 56, issue 5, pages 1163-1202, August, DOI: 10.1111/jmcb.13088.
• Gergely Ganics & Barbara Rossi & Tatevik Sekhposyan, 2024, "From Fixed‐Event to Fixed‐Horizon Density Forecasts: Obtaining Measures of Multihorizon Uncertainty from Survey Density Forecasts," Journal of Money, Credit and Banking, Blackwell Publishing, volume 56, issue 7, pages 1675-1704, October, DOI: 10.1111/jmcb.13105.
• De Polis, Andrea & Melosi, Leonardo & Petrella, Ivan, 2024, "The Taming of the Skew : Asymmetric Inflation Risk and Monetary Policy," The Warwick Economics Research Paper Series (TWERPS), University of Warwick, Department of Economics, number 1530.
• Long Thanh Giang & Aiko Kikkawa & Donghyun Park, 2024, "Health Capacity to Work among Older Adults in Viet Nam," Asian Development Review (ADR), World Scientific Publishing Co. Pte. Ltd., volume 41, issue 01, pages 195-225, March, DOI: 10.1142/S0116110524400080.
• Rangan Gupta & Savanah Hall & Christian Pierdzioch, 2024, "Realized Stock Market Volatility of the United States: The Role of Employee Sentiment," Annals of Financial Economics (AFE), World Scientific Publishing Co. Pte. Ltd., volume 19, issue 02, pages 1-21, June, DOI: 10.1142/S2010495224500064.
• Jacobus Nel & Rangan Gupta & Mark E. Wohar & Christian Pierdzioch, 2024, "Climate Risks And Predictability Of Commodity Returns And Volatility: Evidence From Over 750 Years Of Data," Climate Change Economics (CCE), World Scientific Publishing Co. Pte. Ltd., volume 15, issue 04, pages 1-40, November, DOI: 10.1142/S2010007824500039.
• Nguyen Anh Phong & Phan Huy Tam & Nguyen Thanh Tung, 2024, "Identifying Fraud Financial Reports Based on Signs of Income Management Using Machine Learning Technology: The Case of Listed Companies in Vietnam," Journal of International Commerce, Economics and Policy (JICEP), World Scientific Publishing Co. Pte. Ltd., volume 15, issue 02, pages 1-16, June, DOI: 10.1142/S1793993324500133.
• Russell R Barton, 2024, "Predictive Analytics for Business using R," World Scientific Books, World Scientific Publishing Co. Pte. Ltd., number 13856, ISBN: ARRAY(0x6d876410).
• Granziera, Eleonora & Jalasjoki, Pirkka & Paloviita, Maritta, 2024, "The bias of the ECB inflation projections: A State-dependent analysis," Bank of Finland Research Discussion Papers, Bank of Finland, number 4/2024.
• Clark, Todd E. & Ganics, Gergely & Mertens, Elmar, 2024, "Constructing fan charts from the ragged edge of SPF forecasts," Discussion Papers, Deutsche Bundesbank, number 38/2024.
• Schnorrenberger, Richard & Schwind, Patrick & Wieland, Elisabeth, 2024, "Forecasting HICP package holidays with forward-looking booking data," Technical Papers, Deutsche Bundesbank, number 04/2024.
• Herbst, Tobias & Roling, Christoph, 2024, "A top-down loan-level stress test for banks' corporate credit risk: Application to risks from commercial real estate markets," Technical Papers, Deutsche Bundesbank, number 09/2024.
• Lux, Thomas, 2024, "Lack of identification of parameters in a simple behavioral macroeconomic model," Economics Working Papers, Christian-Albrechts-University of Kiel, Department of Economics, number 2024-02.
• Kronenberg, Philipp, 2024, "A High-Frequency GDP Indicator for Switzerland," EconStor Preprints, ZBW - Leibniz Information Centre for Economics, number 330303, DOI: 10.2139/ssrn.4875922.
• Huo, Shutong & Feng, Derek & Gill, Thomas M. & Chen, Xi, 2024, "Childhood Circumstances and Health of American and Chinese Older Adults: A Machine Learning Evaluation of Inequality of Opportunity in Health," GLO Discussion Paper Series, Global Labor Organization (GLO), number 1384.
• Greyling, Talita & Rossouw, Stephanié, 2024, "Development and validation of a real-time happiness index using Google TrendsTM," GLO Discussion Paper Series, Global Labor Organization (GLO), number 1493.
• Bantle, Melissa, 2024, "Screen for collusive behavior: A machine learning approach," Hohenheim Discussion Papers in Business, Economics and Social Sciences, University of Hohenheim, Faculty of Business, Economics and Social Sciences, number 01-2024.
• Paul, Joseph R. & Schaffer, Mark E., 2024, "An introduction to conformal inference for economists," Accountancy, Economics, and Finance Working Papers, Heriot-Watt University, Department of Accountancy, Economics, and Finance, number 2024-13.
• Holtemöller, Oliver & Kozyrev, Boris, 2024, "Forecasting economic activity using a neural network in uncertain times: Monte Carlo evidence and application to the German GDP," IWH Discussion Papers, Halle Institute for Economic Research (IWH), number 6/2024.
• Heinisch, Katja, 2024, "Step by step - A quarterly evaluation of EU Commission's GDP forecasts," IWH Discussion Papers, Halle Institute for Economic Research (IWH), number 22/2024.
• Deschermeier, Philipp, 2024, "IW-Bevölkerungsprognose: Eine Datengrundlage zur Gestaltung der Herausforderungen des demografischen Wandels auf Basis des Zensus 2022
  [IW population forecast 2024 - Essential data for meeting the challenges of demographic change on the basis of t," IW-Trends – Vierteljahresschrift zur empirischen Wirtschaftsforschung, Institut der deutschen Wirtschaft (IW) / German Economic Institute, volume 51, issue 3, pages 67-87, DOI: 10.2373/1864-810X.24-03-04.
• Foltas, Alexander, 2024, "Inefficient forecast narratives: A BERT-based approach," Working Papers, German Research Foundation's Priority Programme 1859 "Experience and Expectation. Historical Foundations of Economic Behaviour", Humboldt University Berlin, number 45, DOI: 10.18452/29133.
• Wolf, Elias & Montes-Galdón, Carlos & Paredes, Joan, 2024, "Conditional density forecasting: a tempered importance sampling approach," VfS Annual Conference 2024 (Berlin): Upcoming Labor Market Challenges, Verein für Socialpolitik / German Economic Association, number 302442.

2023

• Christian Lohmann & Steffen Möllenhoff & Thorsten Ohliger, 2023, "Nonlinear relationships in bankruptcy prediction and their effect on the profitability of bankruptcy prediction models," Journal of Business Economics, Springer, volume 93, issue 9, pages 1661-1690, November, DOI: 10.1007/s11573-022-01130-8.
• Tobias Götze & Marc Gürtler & Eileen Witowski, 2023, "Forecasting accuracy of machine learning and linear regression: evidence from the secondary CAT bond market," Journal of Business Economics, Springer, volume 93, issue 9, pages 1629-1660, November, DOI: 10.1007/s11573-023-01138-8.
• Kajal Lahiri & Cheng Yang, 2023, "ROC and PRC Approaches to Evaluate Recession Forecasts," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), volume 19, issue 2, pages 119-148, September, DOI: 10.1007/s41549-023-00082-4.
• Satoshi Urasawa, 2023, "The Usefulness of High-Frequency Alternative Data to Obtain Nowcasts for Japan’s GDP: Evidence from Credit Card Data," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), volume 19, issue 2, pages 191-211, September, DOI: 10.1007/s41549-023-00085-1.
• Klaus Abberger & Michael Graff & Oliver Müller & Boriss Siliverstovs, 2023, "Imputing Monthly Values for Quarterly Time Series: An Application Performed with Swiss Business Cycle Data," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), volume 19, issue 3, pages 241-273, November, DOI: 10.1007/s41549-023-00088-y.
• Saulius Jokubaitis & Dmitrij Celov, 2023, "Business Cycle Synchronization in the EU: A Regional-Sectoral Look through Soft-Clustering and Wavelet Decomposition," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), volume 19, issue 3, pages 311-371, November, DOI: 10.1007/s41549-023-00090-4.
• Javier Sánchez García & Salvador Cruz Rambaud, 2023, "Volatility spillovers between oil and financial markets during economic and financial crises: A dynamic approach," Journal of Economics and Finance, Springer;Academy of Economics and Finance, volume 47, issue 4, pages 1018-1040, December, DOI: 10.1007/s12197-023-09634-x.
• Mihaela Simionescu & Nicolas Schneider, 2023, "Monetary shocks and production network in the G7 countries," Journal of Economic Structures, Springer;Pan-Pacific Association of Input-Output Studies (PAPAIOS), volume 12, issue 1, pages 1-32, December, DOI: 10.1186/s40008-023-00313-y.
• Paul M. Torrens, 2023, "Agent models of customer journeys on retail high streets," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, volume 18, issue 1, pages 87-128, January, DOI: 10.1007/s11403-022-00350-z.
• Mustafa Yurtsever, 2023, "Unemployment rate forecasting: LSTM-GRU hybrid approach," Journal for Labour Market Research, Springer;Institute for Employment Research/ Institut für Arbeitsmarkt- und Berufsforschung (IAB), volume 57, issue 1, pages 1-9, December, DOI: 10.1186/s12651-023-00345-8.
• Zouheir Mighri & Raouf Jaziri, 2023, "Long-Memory, Asymmetry and Fat-Tailed GARCH Models in Value-at-Risk Estimation: Empirical Evidence from the Global Real Estate Markets," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), volume 21, issue 1, pages 41-97, March, DOI: 10.1007/s40953-022-00331-w.
• Rudrani Bhattacharya & Bornali Bhandari & Sudipto Mundle, 2023, "Nowcasting India’s Quarterly GDP Growth: A Factor-Augmented Time-Varying Coefficient Regression Model (FA-TVCRM)," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), volume 21, issue 1, pages 213-234, March, DOI: 10.1007/s40953-022-00335-6.
• Samuel F. Onipede & Nafiu A. Bashir & Jamaladeen Abubakar, 2023, "Small open economies and external shocks: an application of Bayesian global vector autoregression model," Quality & Quantity: International Journal of Methodology, Springer, volume 57, issue 2, pages 1673-1699, April, DOI: 10.1007/s11135-022-01423-8.
• Afees A. Salisu & Abdulsalam Abidemi Sikiru & Philip C. Omoke, 2023, "COVID-19 pandemic and financial innovations," Quality & Quantity: International Journal of Methodology, Springer, volume 57, issue 4, pages 3885-3904, August, DOI: 10.1007/s11135-022-01540-4.
• Matthias Breuer & Harm H. Schütt, 2023, "Accounting for uncertainty: an application of Bayesian methods to accruals models," Review of Accounting Studies, Springer, volume 28, issue 2, pages 726-768, June, DOI: 10.1007/s11142-021-09654-0.
• Krzysztof Rusek & Agnieszka Kleszcz & Albert Cabellos-Aparicio, 2023, "Bayesian inference of spatial and temporal relations in AI patents for EU countries," Scientometrics, Springer;Akadémiai Kiadó, volume 128, issue 6, pages 3313-3335, June, DOI: 10.1007/s11192-023-04699-1.
• Sylvia Kaufmann, 2023, "Covid-19 outbreak and beyond: a retrospect on the information content of short-time workers for GDP now- and forecasting," Swiss Journal of Economics and Statistics, Springer;Swiss Society of Economics and Statistics, volume 159, issue 1, pages 1-10, December, DOI: 10.1186/s41937-023-00106-x.
• Stavros Degiannakis, 2023, "The D-model for GDP nowcasting," Swiss Journal of Economics and Statistics, Springer;Swiss Society of Economics and Statistics, volume 159, issue 1, pages 1-33, December, DOI: 10.1186/s41937-023-00109-8.
• Peter Kugler & George Sheldon, 2023, "A monthly leading indicator of Swiss GDP growth based on Okun’s law," Swiss Journal of Economics and Statistics, Springer;Swiss Society of Economics and Statistics, volume 159, issue 1, pages 1-14, December, DOI: 10.1186/s41937-023-00115-w.
• Emmanuel O. Akande & Elijah O. Akanni & Oyedamola F. Taiwo & Jeremiah D. Joshua & Abel Anthony, 2023, "Predicting inflation component drivers in Nigeria: a stacked ensemble approach," SN Business & Economics, Springer, volume 3, issue 1, pages 1-32, January, DOI: 10.1007/s43546-022-00384-2.
• Pami Dua & Rajiv Ranjan & Deepika Goel, 2023, "Forecasting the INR/USD Exchange Rate: A BVAR Framework," Springer Books, Springer, chapter 0, in: Pami Dua, "Macroeconometric Methods", DOI: 10.1007/978-981-19-7592-9_8.
• Timothy Neal, 2023, "The Importance of External Weather Effects in Projecting the Economic Impacts of Climate Change," Discussion Papers, School of Economics, The University of New South Wales, number 2023-09, Jun.
• Clements, Adam & Vasnev, Andrey L., 2023, "Combining simple multivariate HAR-like models for portfolio construction," Working Papers, University of Sydney Business School, Discipline of Business Analytics, number BAWP-2023-03, Nov.
• Kajal Lahiri & Junyan Zhang & Yongchen Zhao, 2023, "Inefficiency in social security trust funds forecasts," Applied Economics Letters, Taylor & Francis Journals, volume 30, issue 10, pages 1353-1357, June, DOI: 10.1080/13504851.2022.2053649.
• Jiqian Wang & Rangan Gupta & Oğuzhan Çepni & Feng Ma, 2023, "Forecasting international REITs volatility: the role of oil-price uncertainty," The European Journal of Finance, Taylor & Francis Journals, volume 29, issue 14, pages 1579-1597, September, DOI: 10.1080/1351847X.2022.2137422.
• Rangan Gupta & Jacobus Nel & Christian Pierdzioch, 2023, "Investor Confidence and Forecastability of US Stock Market Realized Volatility: Evidence from Machine Learning," Journal of Behavioral Finance, Taylor & Francis Journals, volume 24, issue 1, pages 111-122, January, DOI: 10.1080/15427560.2021.1949719.
• Monica Billio & Roberto Casarin & Matteo Iacopini & Sylvia Kaufmann, 2023, "Bayesian Dynamic Tensor Regression," Journal of Business & Economic Statistics, Taylor & Francis Journals, volume 41, issue 2, pages 429-439, April, DOI: 10.1080/07350015.2022.2032721.
• Knut Are Aastveit & Jamie L. Cross & Herman K. van Dijk, 2023, "Quantifying Time-Varying Forecast Uncertainty and Risk for the Real Price of Oil," Journal of Business & Economic Statistics, Taylor & Francis Journals, volume 41, issue 2, pages 523-537, April, DOI: 10.1080/07350015.2022.2039159.
• Laurent Ferrara & Anna Simoni, 2023, "When are Google Data Useful to Nowcast GDP? An Approach via Preselection and Shrinkage," Journal of Business & Economic Statistics, Taylor & Francis Journals, volume 41, issue 4, pages 1188-1202, October, DOI: 10.1080/07350015.2022.2116025.
• Zhongchen Song & Tom Coupé, 2023, "Predicting Chinese consumption series with Baidu," Journal of Chinese Economic and Business Studies, Taylor & Francis Journals, volume 21, issue 3, pages 429-463, July, DOI: 10.1080/14765284.2022.2161175.
• Constantin Rudolf Salomo Bürgi, 2023, "How to deal with missing observations in surveys of professional forecasters," Journal of Applied Economics, Taylor & Francis Journals, volume 26, issue 1, pages 2185975-218, December, DOI: 10.1080/15140326.2023.2185975.
• Anna Gloria Billé & Alessio Tomelleri & Francesco Ravazzolo, 2023, "Forecasting regional GDPs: a comparison with spatial dynamic panel data models," Spatial Economic Analysis, Taylor & Francis Journals, volume 18, issue 4, pages 530-551, October, DOI: 10.1080/17421772.2023.2199034.
• Benjamin Monnery & Fran ois-Charles Wolff, 2023, "Is participatory democracy in line with social protest ? Evidence from the French Yellow Vests movement," TEPP Working Paper, TEPP, number 2023-07.
• Daan Opschoor & Dick van Dijk, 2023, "Slow Expectation-Maximization Convergence in Low-Noise Dynamic Factor Models," Tinbergen Institute Discussion Papers, Tinbergen Institute, number 23-018/III, Apr.
• Francisco Blasques & Siem Jan Koopman & Gabriele Mingoli, 2023, "Observation-Driven filters for Time- Series with Stochastic Trends and Mixed Causal Non-Causal Dynamics," Tinbergen Institute Discussion Papers, Tinbergen Institute, number 23-065/III, Oct, revised 01 Mar 2024.
• Gabriel Mathy & Yongchen Zhao, 2023, "Could Diffusion Indexes Have Forecasted the Great Depression?," Working Papers, Towson University, Department of Economics, number 2023-05, Sep, revised Sep 2023.
• Yongchen Zhao, 2023, "Uncertainty of Household Inflation Expectations: Reconciling Point and Density Forecasts," Working Papers, Towson University, Department of Economics, number 2023-09, Dec, revised Dec 2023.
• Travis J. Berge, 2023, "Time-Varying Uncertainty of the Federal Reserve's Output Gap Estimate," The Review of Economics and Statistics, MIT Press, volume 105, issue 5, pages 1191-1206, September, DOI: 10.1162/rest_a_01102.
• Abir HASSAN & Mahbubul Md. ALAM & Azmaine FAEIQUE, 2023, "Forecasting Monthly Inflation in Bangladesh: A Seasonal Autoregressive Moving Average (SARIMA) Approach," Journal of Economics and Financial Analysis, Tripal Publishing House, volume 7, issue 2, pages 25-43, DOI: 10.1991/jefa.v7i2.a61.
• Marco Del Negro & Marc P. Giannoni & Christina Patterson, 2023, "The Forward Guidance Puzzle," Journal of Political Economy Macroeconomics, University of Chicago Press, volume 1, issue 1, pages 43-79, DOI: 10.1086/724214.
• Jianghao Chu & Tae-Hwy Lee & Aman Ullah, 2023, "Asymmetric AdaBoost for High-dimensional Maximum Score Regression," Working Papers, University of California at Riverside, Department of Economics, number 202306, Aug.
• Tae-Hwy Lee & Tao Wang, 2023, "Estimation and Testing of Forecast Rationality with Many Moments," Working Papers, University of California at Riverside, Department of Economics, number 202307, Sep.
• Tae-Hwy Lee & Ekaterina Seregina & Yaojue Xu, 2023, "Elicitability and Encompassing for Volatility Forecasts by Bregman Functions," Working Papers, University of California at Riverside, Department of Economics, number 202311, Sep.
• Vladimir M. Markovic & Nikola Radivojevic & Tatjana Ivanovic & Slobodan Radisic & Nenad Novakovic, 2023, "The quantum harmonic oscillator expected shortfall model," Estudios de Economia, University of Chile, Department of Economics, volume 50, issue 2 Year 20, pages 233-261, December.
• Mihnea Constantinescu, 2023, "Sparse Warcasting," Working Papers, National Bank of Ukraine, number 01/2023, Jun.
• Alejo Estavillo & Gabriela Mordecki, 2023, "Nowcasting del PIB para Uruguay en base a un modelo de ecuaciones puente," Documentos de Trabajo (working papers), Instituto de Economía - IECON, number 23-26, Dec.
• Dietrich, Stephan & Malerba, Daniele & Gassmann, Franziska, 2023, "Predicting social assistance beneficiaries," MERIT Working Papers, United Nations University - Maastricht Economic and Social Research Institute on Innovation and Technology (MERIT), number 2023-007, Mar.
• Jaromir Hurnik & Vatcharin Sirimaneetham, 2023, "A long-term approach for analysing public debt sustainability: a case study of Mongolia," MPDD Working Paper Series, United Nations Economic and Social Commission for Asia and the Pacific (ESCAP), number WP/23/02, Dec.
• Lis Szymon & Chlebus Marcin, 2023, "Combining forecasts? Keep it simple," Central European Economic Journal, Sciendo, volume 10, issue 57, pages 343-370, January, DOI: 10.2478/ceej-2023-0020.
• Sabek Amine, 2023, "Unveiling the diverse efficacy of artificial neural networks and logistic regression: A comparative analysis in predicting financial distress," Croatian Review of Economic, Business and Social Statistics, Sciendo, volume 9, issue 1, pages 16-32, July, DOI: 10.2478/crebss-2023-0002.
• Berezka Kateryna & Kovalchuk Olha, 2023, "The Application of Association Rules to Detect the Effects of Vaccinations against Covid-19 in the EU-27. Preliminary Estimates," Econometrics. Advances in Applied Data Analysis, Sciendo, volume 27, issue 1, pages 1-16, March, DOI: 10.15611/eada.2023.1.01.
• Souto Hugo Gobato & Moradi Amir, 2023, "Forecasting realized volatility through financial turbulence and neural networks," Economics and Business Review, Sciendo, volume 9, issue 2, pages 133-159, April, DOI: 10.18559/ebr.2023.2.737.
• Mishra Akshay Kumar & Kumar Rahul & Bal Debi Prasad, 2023, "ESG Volatility Prediction Using GARCH and LSTM Models," Financial Internet Quarterly (formerly e-Finanse), Sciendo, volume 19, issue 4, pages 97-114, December, DOI: 10.2478/fiqf-2023-0029.
• Vasilev Julian & Sulova Snezhana, 2023, "An Approach for the In-Depth Data Analysis of the Marine Traffic of Independent Nearby Ports," Folia Oeconomica Stetinensia, Sciendo, volume 23, issue 2, pages 402-426, December, DOI: 10.2478/foli-2023-0038.
• Suleiman Ahmad Abubakar & Othman Mahmod & Daud Hanita & Abdullah Mohd Lazim & Kadir Evizal Abdul & Kane Ibrahim Lawal & Husin Abdullah, 2023, "Forecasting the Volatility of Real Residential Property Prices in Malaysia: A Comparison of Garch Models," Real Estate Management and Valuation, Sciendo, volume 31, issue 3, pages 20-31, September, DOI: 10.2478/remav-2023-0018.
• Ciocîrlan Cecilia & Zwak-Cantoriu Maria-Cristina & Stancea Andreea & Plăcintă Dimitrie-Daniel, 2023, "European Macroeconomic Dynamics on Financial Markets and Economic Policy: A Cross Country Study for Spillover Effects," Studia Universitatis Babeș-Bolyai Oeconomica, Sciendo, volume 68, issue 3, pages 40-63, December, DOI: 10.2478/subboec-2023-0014.
• Leo Krippner, 2023, "Estimating and Applying Autoregression Models Via Their Eigensystem Representation," Working Papers in Economics, University of Waikato, number 23/09, Dec.
• Maudud Hassan Uzzal & Robert Ślepaczuk, 2023, "The performance of time series forecasting based on classical and machine learning methods for S&P 500 index," Working Papers, Faculty of Economic Sciences, University of Warsaw, number 2023-05.
• Konrad Lewszyk & Piotr Wójcik, 2023, "Modelling Subjective Attractiveness," Working Papers, Faculty of Economic Sciences, University of Warsaw, number 2023-06.
• Karol Chojnacki & Robert Ślepaczuk, 2023, "This study compares well-known tools of technical analysis (Moving Average Crossover MAC) with Machine Learning based strategies (LSTM and XGBoost) and Ensembled Machine Learning Strategies (LSTM ensembled with XGBoost and MAC). All models were compa," Working Papers, Faculty of Economic Sciences, University of Warsaw, number 2023-15.
• Damian Ślusarczyk & Robert Ślepaczuk, 2023, "Optimal Markowitz Portfolio Using Returns Forecasted with Time Series and Machine Learning Models," Working Papers, Faculty of Economic Sciences, University of Warsaw, number 2023-17.
• Paweł Jakubowski & Robert Ślepaczuk & Franciszek Windorbski, 2023, "REnsembling ARIMAX Model in Algorithmic Investment Strategies on Commodities Market," Working Papers, Faculty of Economic Sciences, University of Warsaw, number 2023-20.
• Jakub Michańków & Paweł Sakowski & Robert Ślepaczuk, 2023, "Mean Absolute Directional Loss as a New Loss Function for Machine Learning Problems in Algorithmic Investment Strategies," Working Papers, Faculty of Economic Sciences, University of Warsaw, number 2023-23.
• Jakub Michańków & Paweł Sakowski & Robert Ślepaczuk, 2023, "Hedging Properties of Algorithmic Investment Strategies using Long Short-Term Memory and Time Series models for Equity Indices," Working Papers, Faculty of Economic Sciences, University of Warsaw, number 2023-25.
• Sahil Teymurzade & Robert Ślepaczuk, 2023, "Predicting DJIA, NASDAQ and NYSE index prices using ARIMA and VAR models," Working Papers, Faculty of Economic Sciences, University of Warsaw, number 2023-27.
• Amor Aniss Benmoussa, Reinhard Ellwanger, Stephen Snudden, 2023, "Carpe Diem: Can daily oil prices improve model-based forecasts of the real price of crude oil?," LCERPA Working Papers, Laurier Centre for Economic Research and Policy Analysis, number bm0141, Dec.
• Reinhard Ellwanger, Stephen Snudden, Lenin Arango-Castillo, 2023, "Seize the Last Day: Period-End-Point Sampling for Forecasts of Temporally Aggregated Data," LCERPA Working Papers, Laurier Centre for Economic Research and Policy Analysis, number bm0142, Dec.