Research classified by Journal of Economic Literature (JEL) codes

2024

• Svetoslav Borisov, 2024, "Bitcoin – Hedge or Speculative Asset: Analysis of Its Role and Nature," Economic Studies journal, Bulgarian Academy of Sciences - Economic Research Institute, issue 5, pages 148-170.
• 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.
• Arturo Pablo Macías Fernández & Ignacio de la Peña Leal, 2024, "Sensibilidad a los tipos de interés soberanos de la cartera de colateral elegible para los préstamos de política monetaria," Occasional Papers, Banco de España, number 2417, May, DOI: https://doi.org/10.53479/36612.
• 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.
• Javier Gil-Bazo & Alexander Kempf & Raffaele Santioni, 2024, "Geographic shareholder dispersion and mutual fund flow risk," Temi di discussione (Economic working papers), Bank of Italy, Economic Research and International Relations Area, number 1461, Jul.
• Fredy Gamboa-Estrada & José Vicente Romero, 2024, "Geopolitical Risk and Emerging Markets Sovereign Risk Premia," Borradores de Economia, Banco de la Republica de Colombia, number 1282, Sep, DOI: 10.32468/be.1282.
• Martha López & Eduardo Sarmiento Gómez, 2024, "Collateral, output growth, mortgage spread volatility and subsidies in Colombia," Borradores de Economia, Banco de la Republica de Colombia, number 1287, Nov, DOI: 10.32468/be.1287.
• Martha López & Eduardo Sarmiento Gómez, 2024, "Collateral, output growth, mortgage spread volatility and subsidies in Colombia," Borradores de Economia, Banco de la Republica de Colombia, number 1287x, Nov, DOI: 10.32468/be.1287.
• Raffaele Santioni & Javier Gil-Bazo, 2024, "Geographic Shareholder Dispersion and Mutual Fund Flow Risk," Working Papers, Barcelona School of Economics, number 1440, Apr.
• Juan R. Hernández, 2024, "Covered interest parity: a forecasting approach to estimate the neutral band," BIS Working Papers, Bank for International Settlements, number 1206, Aug.
• Phạm Thu Hương & Hoàng Mạnh Hùng & Lê Đạt Chí, 2024, "Ứng dụng mô hình F-SCORE cho chiến lược đầu tư cổ phiếu tại Sở Giao dịch Chứng khoán Thành phố Hồ Chí Minh," TẠP CHÍ KHOA HỌC ĐẠI HỌC MỞ THÀNH PHỐ HỒ CHÍ MINH - KINH TẾ VÀ QUẢN TRỊ KINH DOANH, HO CHI MINH CITY OPEN UNIVERSITY JOURNAL OF SCIENCE, HO CHI MINH CITY OPEN UNIVERSITY, volume 19, issue 5, pages 46-58, DOI: 10.46223/HCMCOUJS.econ.vi.19.5.2968.
• Olivier Dessaint & Thierry Foucault & Laurent Fresard, 2024, "Does Alternative Data Improve Financial Forecasting? The Horizon Effect," Journal of Finance, American Finance Association, volume 79, issue 3, pages 2237-2287, June, DOI: 10.1111/jofi.13323.
• Akihito Yoneyama & Akitaka Tsuchiya & Noritaka Fukuma, 2024, "Changes in Risk Perceptions on Yen Interest Rates and Exchange Rates Observed in Options Markets: Developments in Implied Probability Distributions amid Rate Hikes in the United States and Europe from 2022 to 2023," Bank of Japan Review Series, Bank of Japan, number 24-E-8, Aug.
• 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.
• Liu Jinan & Serletis Apostolos, 2024, "Volatility and dependence in cryptocurrency and financial markets: a copula approach," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, volume 28, issue 1, pages 119-149, February, DOI: 10.1515/snde-2022-0029.
• Baruník Jozef & Fišer Pavel, 2024, "Co-Jumping of Treasury Yield Curve Rates," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, volume 28, issue 3, pages 481-506, DOI: 10.1515/snde-2022-0091.
• Roberto Marfe & Julien Penasse, 2024, "Measuring Macroeconomic Tail Risk," Carlo Alberto Notebooks, Collegio Carlo Alberto, number 715 JEL Classification: E.
• Xu, Yongdeng, 2024, "Extended multivariate EGARCH model: A model for zero†return and negative spillovers," Cardiff Economics Working Papers, Cardiff University, Cardiff Business School, Economics Section, number E2024/24, Dec.
• Briac Turquet & Pierre Bajgrowicz & O. Scaillet, 2024, "Mean Reversion Trading on the Naphtha Crack," Swiss Finance Institute Research Paper Series, Swiss Finance Institute, number 24-101, Nov.
• Markus Leippold & Michal Svaton, 2024, "Scheduling Processes and Inference of Scheduled Events From Price Data," Swiss Finance Institute Research Paper Series, Swiss Finance Institute, number 24-12, Jan.
• Soros Chitsiripanich & Marc S. Paolella & Pawel Polak & Patrick S. Walker, 2024, "Smoothing Out Momentum and Reversal," Swiss Finance Institute Research Paper Series, Swiss Finance Institute, number 24-47, Sep.
• Aysun Can Turetken & Markus Leippold, 2024, "Battle of Transformers: Adversarial Attacks on Financial Sentiment Models," Swiss Finance Institute Research Paper Series, Swiss Finance Institute, number 24-59, Nov.
• Matthias R. Fengler & Jeannine Polivka, 2024, "Structural Volatility Impulse Response Analysis," Swiss Finance Institute Research Paper Series, Swiss Finance Institute, number 24-63, Nov.
• Yicheng Wang & Didier Sornette & Ke Wu & Sandro Claudio Lera, 2024, "Dynamic Influence Networks Self-Organize Towards Sub-Critical Financial Instabilities," Swiss Finance Institute Research Paper Series, Swiss Finance Institute, number 24-77, Oct.
• Erdinc Akyildirim & Matteo Gambara & Josef Teichmann & Syang Zhou, 2024, "Randomized Signature Methods in Optimal Portfolio Selection," Swiss Finance Institute Research Paper Series, Swiss Finance Institute, number 24-79, Jan.
• Francisco Peñaranda & Enrique Sentana, 2024, "Portfolio management with big data," Working Papers, CEMFI, number wp2024_2411, Jun.
• V. Candila & O. Cepni & G. M. Gallo & R. Gupta, 2024, "Influence of Local and Global Economic Policy Uncertainty on the volatility of US state-level equity returns: Evidence from a GARCH-MIDAS approach with Shrinkage and Cluster Analysis," Working Paper CRENoS, Centre for North South Economic Research, University of Cagliari and Sassari, Sardinia, number 202414.
• Carlos Castro-Iragorri & Fabio G√≥mez & Nancy Quiceno, 2024, "Worst-Case Higher Moment Risk Measure: Addressing Distributional Shifts and Procyclicality," Documentos de Trabajo, Universidad del Rosario, number 21048, Feb.
• López Martha & Sarmiento Gómez Eduardo, 2023, "Excess Asset Returns Predictability in an Emerging Economy: The Case of Colombia," Revista de Economía del Rosario, Universidad del Rosario, volume 26, issue 2, pages 1-29.
• Héctor Javier Bendezú-Jiménez & Mauro Jesús Camacho Gadea, 2024, "Impact of Commodity Price Fluctuations on the Peruvian Stock Market (2010-2019)
  [Impacto de la variación del precio de los commodities sobre el mercado de valores peruano (2010-2019)]," Revista de Economía del Rosario, Universidad del Rosario, volume 27, issue 2, pages 1-26, DOI: 10.12804/revistas.urosario.edu.co/e.
• Bekaert, Geert & Xu, Nancy & Ye, Tiange, 2024, "Forecasting International Stock Market Variances," CEPR Discussion Papers, C.E.P.R. Discussion Papers, number 19121, May.
• Penaranda, Francisco & Sentana, Enrique, 2024, "Portfolio management with big data," CEPR Discussion Papers, C.E.P.R. Discussion Papers, number 19314, Jul.
• Julen Iglesias Tejedor, 2024, "Creación de una cartera de inversión que venza la inflación atendiendo a criterios ESG gestionada mediante machine learning," Revista de Economía y Finanzas (REyF), Asociación Cuadernos de Economía, volume 2, issue 5, pages 79-100, Mayo.
• Algieri, Bernardina & Iania, Leonardo & Leccadito, Arturo & Meloni, Giulia, 2024, "Message in a bottle: Forecasting wine prices," Journal of Wine Economics, Cambridge University Press, volume 19, issue 1, pages 64-91, February.
• Soumya Ranjan SETHI & Dushyant Ashok MAHADIK, 2024, "Spotting Trouble Before It Starts: Has Financial Distress Prediction Evolved During 1985–2022," Applied Econometrics and International Development, Euro-American Association of Economic Development, volume 24, issue 1, pages 181-206.
• Soumya Ranjan Sethi & Dushyant Ashok Mahadik & Rajkiran V. Bilolikar, 2024, "Exploring Trends and Advancements in Financial Distress Prediction Research: A Bibliometric Study," International Journal of Economics and Financial Issues, Econjournals, volume 14, issue 1, pages 164-179, January.
• Lamine Diane & Pradeep Brijlal, 2024, "Forecasting Stock Market Realized Volatility using Random Forest and Artificial Neural Network in South Africa," International Journal of Economics and Financial Issues, Econjournals, volume 14, issue 2, pages 5-14, March.
• Emily Groenewald & Gary Van Vuuren, 2024, "Visualisation of Mahalanobis Distances for Trivariate JOINT Distributions," International Journal of Economics and Financial Issues, Econjournals, volume 14, issue 2, pages 203-206, March.
• Christos Christodoulou-Volos & Dikaios Tserkezos, 2024, "The Impact of COVID-19 on the Cypriot Stock Market Dynamics," International Journal of Economics and Financial Issues, Econjournals, volume 14, issue 4, pages 214-221, July.
• Olufemi Peter Alawode & Helen Nwobodo & Afolake Ogunfowora & Alao Olubunmi & Chimeruo Victory Onyeka-Iheme, 2024, "Financial Re-Engineering and Customer Performance of Poultry Business in Nigeria," International Journal of Economics and Financial Issues, Econjournals, volume 14, issue 6, pages 164-173, October.
• Arif Çilek & Onur SeyranlıoÄŸlu, 2024, "Portfolio Optimization with Entropy-CRITIC-IDDWS- PROMETHEE Model in BIST Retail Trade Sector," International Journal of Economics and Financial Issues, Econjournals, volume 14, issue 6, pages 23-35, October.
• Christos Christodoulou-Volos & Dikaios Tserkezos, 2024, "The Impact of COVID-19 and Structural Market Changes on the Greek Stock Market: An Empirical Analysis," International Journal of Economics and Financial Issues, Econjournals, volume 14, issue 6, pages 320-326, October.
• Salokhiddin Avazkhodjaev & Nont Dhiensiri & Farkhod Mukhamedov, 2024, "Does Green Energy Investment Effects on Islamic and Conventional Stock Markets? New Evidence from Advanced Economies," International Journal of Energy Economics and Policy, Econjournals, volume 14, issue 1, pages 592-602, January.
• Bharat Kumar Meher & Abhishek Anand & Sunil Kumar & Ramona Birau & Manohar Sing, 2024, "Effectiveness of Random Forest Model in Predicting Stock Prices of Solar Energy Companies in India," International Journal of Energy Economics and Policy, Econjournals, volume 14, issue 2, pages 426-434, March.
• Mirzat Ullah & Kazi Sohag & Farrukh Nawaz & Oleg Mariev & Umar Kayani & Igor Mayburov & Svetlana Doroshenko, 2024, "Impact of Oil Price Shocks on Crypto and Conventional Financial Assets during Financial Crises: Evidence from the Russian Financial Market," International Journal of Energy Economics and Policy, Econjournals, volume 14, issue 4, pages 472-483, July.
• Faruk Dayi & Ali Cilesiz & Mustafa Yucel, 2024, "Strategic Management of Clean Energy Investments: Financial Performance Insights by Using BWM-based VIKOR and TOPSIS Methods," International Journal of Energy Economics and Policy, Econjournals, volume 14, issue 5, pages 566-574, September.
• Salokhiddin Avazkhodjaev & Nont Dhiensiri & Eshmurod Rakhimov, 2024, "Effects of Crude Oil Price Uncertainty on Fossil Fuel Production, Clean Energy Consumption, and Output Growth: An Empirical Study of the U.S," International Journal of Energy Economics and Policy, Econjournals, volume 14, issue 6, pages 371-383, November.
• Farrukh Nawaz & Mrestyal Khan & Umar Kayani & Indry Aristianto Pradipta & Aulia Luqman Aziz, 2024, "Impact of Volatility Spillovers upon Electric Utilities during the Russia-Ukraine Conflict," International Journal of Energy Economics and Policy, Econjournals, volume 14, issue 6, pages 597-604, November.
• Yu, Xing & Li, Yanyan & Zhao, Qian, 2024, "Research on optimization strategy of futures hedging dependent on market state," Applied Energy, Elsevier, volume 373, issue C, DOI: 10.1016/j.apenergy.2024.123885.
• Díaz, Antonio & Escribano, Ana & Esparcia, Carlos, 2024, "Sustainable risk preferences on asset allocation: a higher order optimal portfolio study," Journal of Behavioral and Experimental Finance, Elsevier, volume 41, issue C, DOI: 10.1016/j.jbef.2024.100887.
• Hoang, Lai & Vo, Duc Hong, 2024, "Google search and cross-section of cryptocurrency returns and trading activities," Journal of Behavioral and Experimental Finance, Elsevier, volume 44, issue C, DOI: 10.1016/j.jbef.2024.100991.
• Fu, Renhui & Ma, Chen & Zeng, Yamin & Zhang, Junsheng, 2024, "Determinants and consequences of sales/production report issuance," The British Accounting Review, Elsevier, volume 56, issue 5, DOI: 10.1016/j.bar.2023.101266.
• Gu, Zhenjiang & Lu, Louise Yi & Yu, Yangxin, 2024, "CEO equity incentive duration and expected crash risk," The British Accounting Review, Elsevier, volume 56, issue 6, DOI: 10.1016/j.bar.2023.101265.
• Wang, Liyao, 2024, "Partisan conflict and corporate credit spreads: The role of political connection," Journal of Corporate Finance, Elsevier, volume 84, issue C, DOI: 10.1016/j.jcorpfin.2023.102526.
• Tu, Xueyong & Li, Bin, 2024, "Robust portfolio selection with smart return prediction," Economic Modelling, Elsevier, volume 135, issue C, DOI: 10.1016/j.econmod.2024.106719.
• Seo, Myung Hwan & Koo, Bonsoo & Yang, Yangzhuoran Fin, 2024, "Nonlinear dynamics of Kimchi premium," Economic Modelling, Elsevier, volume 135, issue C, DOI: 10.1016/j.econmod.2024.106726.
• Fiszeder, Piotr & Małecka, Marta & Molnár, Peter, 2024, "Robust estimation of the range-based GARCH model: Forecasting volatility, value at risk and expected shortfall of cryptocurrencies," Economic Modelling, Elsevier, volume 141, issue C, DOI: 10.1016/j.econmod.2024.106887.
• Dufera, Tamirat Temesgen, 2024, "Fractional Brownian motion in option pricing and dynamic delta hedging: Experimental simulations," The North American Journal of Economics and Finance, Elsevier, volume 69, issue PB, DOI: 10.1016/j.najef.2023.102017.
• Jiang, Yifu & Olmo, Jose & Atwi, Majed, 2024, "Dynamic robust portfolio selection under market distress," The North American Journal of Economics and Finance, Elsevier, volume 69, issue PB, DOI: 10.1016/j.najef.2023.102037.
• Ji, Hongyun & Zhang, Han, 2024, "Application of the LPPL model in the identification and measurement of structural bubbles in the Chinese stock market," The North American Journal of Economics and Finance, Elsevier, volume 70, issue C, DOI: 10.1016/j.najef.2023.102060.
• Wang, Jia & Wang, Xinyi & Wang, Xu, 2024, "International oil shocks and the volatility forecasting of Chinese stock market based on machine learning combination models," The North American Journal of Economics and Finance, Elsevier, volume 70, issue C, DOI: 10.1016/j.najef.2023.102065.
• Aslam, Faheem & Hunjra, Ahmed Imran & Memon, Bilal Ahmed & Zhang, Mingda, 2024, "Interplay of multifractal dynamics between shadow policy rates and energy markets," The North American Journal of Economics and Finance, Elsevier, volume 71, issue C, DOI: 10.1016/j.najef.2024.102085.
• Tang, Pan & Tang, Tiantian & Lu, Chennuo, 2024, "Predicting systemic financial risk with interpretable machine learning," The North American Journal of Economics and Finance, Elsevier, volume 71, issue C, DOI: 10.1016/j.najef.2024.102088.
• Joo, Young C. & Park, Sung Y., 2024, "Hedging Bitcoin with commodity futures: An analysis with copper, gas, gold, and crude oil futures," The North American Journal of Economics and Finance, Elsevier, volume 72, issue C, DOI: 10.1016/j.najef.2024.102127.
• Herrera, Rodrigo & Piña, Marco, 2024, "Market risk modeling with option-implied covariances and score-driven dynamics," The North American Journal of Economics and Finance, Elsevier, volume 72, issue C, DOI: 10.1016/j.najef.2024.102136.
• Cai, Yi & Tang, Zhenpeng & Chen, Ying, 2024, "Can real-time investor sentiment help predict the high-frequency stock returns? Evidence from a mixed-frequency-rolling decomposition forecasting method," The North American Journal of Economics and Finance, Elsevier, volume 72, issue C, DOI: 10.1016/j.najef.2024.102147.
• Tang, Pan & Xu, Wei & Wang, Haosen, 2024, "Network-Based prediction of financial cross-sector risk spillover in China: A deep learning approach," The North American Journal of Economics and Finance, Elsevier, volume 72, issue C, DOI: 10.1016/j.najef.2024.102151.
• Kao, Yu-Sheng & Day, Min-Yuh & Chou, Ke-Hsin, 2024, "A comparison of bitcoin futures return and return volatility based on news sentiment contemporaneously or lead-lag," The North American Journal of Economics and Finance, Elsevier, volume 72, issue C, DOI: 10.1016/j.najef.2024.102159.
• Xu, Yuhong & Zhao, Xinyao, 2024, "How does node centrality in a financial network affect asset price prediction?," The North American Journal of Economics and Finance, Elsevier, volume 73, issue C, DOI: 10.1016/j.najef.2024.102163.
• Maki, Daiki, 2024, "Evaluation of volatility spillovers for asymmetric realized covariance," The North American Journal of Economics and Finance, Elsevier, volume 73, issue C, DOI: 10.1016/j.najef.2024.102177.
• Go, You-How & Lau, Wee-Yeap, 2024, "Terms of trade or market power? Further evidence from dynamic spillovers in return and volatility between Malaysian crude palm oil and foreign exchange markets," The North American Journal of Economics and Finance, Elsevier, volume 73, issue C, DOI: 10.1016/j.najef.2024.102178.
• Yang, Jinyu & Dong, Dayong & Cao, Jiawei, 2024, "Seemingly manipulated anomaly: Evidence from corporate site visits," The North American Journal of Economics and Finance, Elsevier, volume 73, issue C, DOI: 10.1016/j.najef.2024.102185.
• Sanford, Anthony, 2024, "Information content of option prices: Comparing analyst forecasts to option-based forecasts," The North American Journal of Economics and Finance, Elsevier, volume 73, issue C, DOI: 10.1016/j.najef.2024.102197.
• Tzeng, Kae-Yih & Su, Yi-Kai, 2024, "Can U.S. macroeconomic indicators forecast cryptocurrency volatility?," The North American Journal of Economics and Finance, Elsevier, volume 74, issue C, DOI: 10.1016/j.najef.2024.102224.
• Chen, Yan & Zhang, Lei & Zhang, Feipeng, 2024, "Forecasting crude oil volatility and stock volatility: New evidence from the quantile autoregressive model," The North American Journal of Economics and Finance, Elsevier, volume 74, issue C, DOI: 10.1016/j.najef.2024.102235.
• Li, Zhimin & Zhu, Weidong & Wu, Yong & Wu, Zihao, 2024, "Research on information fusion of security analysts’ stock recommendations based on two-dimensional D-S evidence theory," The North American Journal of Economics and Finance, Elsevier, volume 74, issue C, DOI: 10.1016/j.najef.2024.102261.
• Fieberg, Christian & Metko, Daniel & Zaremba, Adam, 2024, "Cross-country factor momentum," Economics Letters, Elsevier, volume 235, issue C, DOI: 10.1016/j.econlet.2024.111552.
• Zeng, Sipeng & Li, Yingmei Esme, 2024, "Braveheart: On the divergence of recommendations between normal and star analysts," Economics Letters, Elsevier, volume 240, issue C, DOI: 10.1016/j.econlet.2024.111765.
• Doan, Bao & Jayasuriya, Dulani & Lee, John B. & Reeves, Jonathan J., 2024, "Cryptocurrency systematic risk dynamics," Economics Letters, Elsevier, volume 241, issue C, DOI: 10.1016/j.econlet.2024.111788.
• Jahan-Pavar, Mohammad R. & Lang, William J., 2024, "Which daily equity returns improve output forecasts?," Economics Letters, Elsevier, volume 243, issue C, DOI: 10.1016/j.econlet.2024.111897.
• Harel, Arie & Harpaz, Giora, 2024, "Why stock analysts may make wrong predictions?," Economics Letters, Elsevier, volume 244, issue C, DOI: 10.1016/j.econlet.2024.111956.
• Krieg, Kimberly S. & Siagian, Ferdinand & Wu, Juan, 2024, "Does analyst forecast informativeness affect managers’ financial reporting incentives?," Economics Letters, Elsevier, volume 244, issue C, DOI: 10.1016/j.econlet.2024.111995.
• Ding, Yi & Li, Yingying & Liu, Guoli & Zheng, Xinghua, 2024, "Stock co-jump networks," Journal of Econometrics, Elsevier, volume 239, issue 2, DOI: 10.1016/j.jeconom.2023.01.026.
• Dierkes, Maik & Hollstein, Fabian & Prokopczuk, Marcel & Würsig, Christoph Matthias, 2024, "Measuring tail risk," Journal of Econometrics, Elsevier, volume 241, issue 2, DOI: 10.1016/j.jeconom.2024.105769.
• Takahashi, Makoto & Watanabe, Toshiaki & Omori, Yasuhiro, 2024, "Forecasting Daily Volatility of Stock Price Index Using Daily Returns and Realized Volatility," Econometrics and Statistics, Elsevier, volume 32, issue C, pages 34-56, DOI: 10.1016/j.ecosta.2021.08.002.
• Zsurkis, Gabriel & Nicolau, João & Rodrigues, Paulo M.M., 2024, "First passage times in portfolio optimization: A novel nonparametric approach," European Journal of Operational Research, Elsevier, volume 312, issue 3, pages 1074-1085, DOI: 10.1016/j.ejor.2023.07.044.
• Fu, Fanjie & Fang, Jing & Zhang, Fan & Yao, Shujie & Ou, Jinghua, 2024, "CEOs' hometown connections and corporate risk-taking: Evidence from China," Emerging Markets Review, Elsevier, volume 60, issue C, DOI: 10.1016/j.ememar.2024.101129.
• Candia, Claudio & Herrera, Rodrigo, 2024, "An empirical review of dynamic extreme value models for forecasting value at risk, expected shortfall and expectile," Journal of Empirical Finance, Elsevier, volume 77, issue C, DOI: 10.1016/j.jempfin.2024.101488.
• Yin, Ximing & Yang, Ge, 2024, "Instantaneous volatility of the yield curve, variance risk premium and bond return predictability," Journal of Empirical Finance, Elsevier, volume 77, issue C, DOI: 10.1016/j.jempfin.2024.101490.
• Jiang, Fuwei & Kang, Jie & Meng, Lingchao, 2024, "Certainty of uncertainty for asset pricing," Journal of Empirical Finance, Elsevier, volume 78, issue C, DOI: 10.1016/j.jempfin.2024.101501.
• Barroso, Pedro & Maio, Paulo, 2024, "The risk–return tradeoff among equity factors," Journal of Empirical Finance, Elsevier, volume 78, issue C, DOI: 10.1016/j.jempfin.2024.101518.
• Xu, Hongyi & Katselas, Dean & Drienko, Jo, 2024, "A portfolio-level, sum-of-the-parts approach to return predictability," Journal of Empirical Finance, Elsevier, volume 78, issue C, DOI: 10.1016/j.jempfin.2024.101525.
• Trimborn, Simon & Peng, Hanqiu & Chen, Ying, 2024, "Influencer detection meets network autoregression — Influential regions in the bitcoin blockchain," Journal of Empirical Finance, Elsevier, volume 78, issue C, DOI: 10.1016/j.jempfin.2024.101529.
• Peng, Yueqian & Shi, Li & Shi, Xiaojun & Tan, Songtao, 2024, "Tone or term: Machine-learning text analysis, featured vocabulary extraction, and evidence from bond pricing in China," Journal of Empirical Finance, Elsevier, volume 78, issue C, DOI: 10.1016/j.jempfin.2024.101534.
• Watanabe, Toshiaki & Nakajima, Jouchi, 2024, "High-frequency realized stochastic volatility model," Journal of Empirical Finance, Elsevier, volume 79, issue C, DOI: 10.1016/j.jempfin.2024.101559.
• Syuhada, Khreshna & Hakim, Arief & Suprijanto, Djoko, 2024, "Assessing systemic risk and connectedness among dirty and clean energy markets from the quantile and expectile perspectives," Energy Economics, Elsevier, volume 129, issue C, DOI: 10.1016/j.eneco.2023.107261.
• Zheng, Li & Sun, Yuying & Wang, Shouyang, 2024, "A novel interval-based hybrid framework for crude oil price forecasting and trading," Energy Economics, Elsevier, volume 130, issue C, DOI: 10.1016/j.eneco.2023.107266.
• Zadeh, Omid Razavi & Romagnoli, Silvia, 2024, "Financing sustainable energy transition with algorithmic energy tokens," Energy Economics, Elsevier, volume 132, issue C, DOI: 10.1016/j.eneco.2024.107420.
• Lyócsa, Štefan & Todorova, Neda, 2024, "Forecasting of clean energy market volatility: The role of oil and the technology sector," Energy Economics, Elsevier, volume 132, issue C, DOI: 10.1016/j.eneco.2024.107451.
• Haas, Christian & Budin, Constantin & d’Arcy, Anne, 2024, "How to select oil price prediction models — The effect of statistical and financial performance metrics and sentiment scores," Energy Economics, Elsevier, volume 133, issue C, DOI: 10.1016/j.eneco.2024.107466.
• Zhang, Zhikai & Wang, Yudong & Zhang, Yaojie & Wang, Qunwei, 2024, "Forecasting carbon prices under diversified attention: A dynamic model averaging approach with common factors," Energy Economics, Elsevier, volume 133, issue C, DOI: 10.1016/j.eneco.2024.107537.
• Fu, Tong & Huang, Dasen & Feng, Lingbing & Tang, Xiaoping, 2024, "More is better? The impact of predictor choice on the INE oil futures volatility forecasting," Energy Economics, Elsevier, volume 134, issue C, DOI: 10.1016/j.eneco.2024.107540.
• Pan, Zhiyuan & Zhong, Hao & Wang, Yudong & Huang, Juan, 2024, "Forecasting oil futures returns with news," Energy Economics, Elsevier, volume 134, issue C, DOI: 10.1016/j.eneco.2024.107606.
• Nygaard, Knut & Sørensen, Lars Qvigstad, 2024, "Betting on war? Oil prices, stock returns, and extreme geopolitical events," Energy Economics, Elsevier, volume 136, issue C, DOI: 10.1016/j.eneco.2024.107659.
• Barbosa, Maria de Fatima & Street, Alexandre & Fanzeres, Bruno, 2024, "A Tailored Derivative Instrument to Mitigate the Price-and-Quantity Risk Faced by Wind Power Companies," Energy Economics, Elsevier, volume 136, issue C, DOI: 10.1016/j.eneco.2024.107676.
• Kliber, Agata & Będowska-Sójka, Barbara, 2024, "Proof-of-work versus proof-of-stake coins as possible hedges against green and dirty energy," Energy Economics, Elsevier, volume 138, issue C, DOI: 10.1016/j.eneco.2024.107820.
• Basher, Syed Abul & Sadorsky, Perry, 2024, "Do climate change risks affect the systemic risk between the stocks of clean energy, electric vehicles, and critical minerals? Analysis under changing market conditions," Energy Economics, Elsevier, volume 138, issue C, DOI: 10.1016/j.eneco.2024.107832.
• Ouyang, Zisheng & Lu, Min & Ouyang, Zhongzhe & Zhou, Xuewei & Wang, Ren, 2024, "A novel integrated method for improving the forecasting accuracy of crude oil: ESMD-CFastICA-BiLSTM-Attention," Energy Economics, Elsevier, volume 138, issue C, DOI: 10.1016/j.eneco.2024.107851.
• Tian, Guangning & Peng, Yuchao & Du, Huancheng & Meng, Yuhao, 2024, "Forecasting crude oil returns in different degrees of ambiguity: Why machine learn better?," Energy Economics, Elsevier, volume 139, issue C, DOI: 10.1016/j.eneco.2024.107867.
• Sánchez-García, Javier & Mattera, Raffaele & Cruz-Rambaud, Salvador & Cerqueti, Roy, 2024, "Measuring financial stability in the presence of energy shocks," Energy Economics, Elsevier, volume 139, issue C, DOI: 10.1016/j.eneco.2024.107922.
• Zhao, Yuan & Gong, Xue & Zhang, Weiguo & Xu, Weijun, 2024, "Forecasting carbon futures returns using feature selection and Markov chain with sample distribution," Energy Economics, Elsevier, volume 140, issue C, DOI: 10.1016/j.eneco.2024.107962.
• Lyócsa, Štefan & Todorova, Neda, 2024, "What drives the uranium sector risk? The role of attention, economic and geopolitical uncertainty," Energy Economics, Elsevier, volume 140, issue C, DOI: 10.1016/j.eneco.2024.107980.
• Gong, Xue & Lai, Ping & He, Mengxi & Wen, Danyan, 2024, "Climate risk and energy futures high frequency volatility prediction," Energy, Elsevier, volume 307, issue C, DOI: 10.1016/j.energy.2024.132466.
• He, Mengxi & Zhang, Zhikai & Zhang, Yaojie, 2024, "Forecasting crude oil prices with global ocean temperatures," Energy, Elsevier, volume 311, issue C, DOI: 10.1016/j.energy.2024.133341.
• Trabelsi, Nader & Umar, Zaghum & Dogah, Kingsley E. & Vo, Xuan Vinh, 2024, "Are investment grade Sukuks decoupled from the conventional yield curve?," International Review of Financial Analysis, Elsevier, volume 91, issue C, DOI: 10.1016/j.irfa.2023.102981.
• Zeng, Hongjun & Abedin, Mohammad Zoynul & Zhou, Xiangjing & Lu, Ran, 2024, "Measuring the extreme linkages and time-frequency co-movements among artificial intelligence and clean energy indices," International Review of Financial Analysis, Elsevier, volume 92, issue C, DOI: 10.1016/j.irfa.2024.103073.
• Wang, Yuejing & Ye, Wuyi & Jiang, Ying & Liu, Xiaoquan, 2024, "Volatility prediction for the energy sector with economic determinants: Evidence from a hybrid model," International Review of Financial Analysis, Elsevier, volume 92, issue C, DOI: 10.1016/j.irfa.2024.103094.
• Qiu, Zhiguo & Lazar, Emese & Nakata, Keiichi, 2024, "VaR and ES forecasting via recurrent neural network-based stateful models," International Review of Financial Analysis, Elsevier, volume 92, issue C, DOI: 10.1016/j.irfa.2024.103102.
• Lang, Chunlin & Xu, Danyang & Corbet, Shaen & Hu, Yang & Goodell, John W., 2024, "Global financial risk and market connectedness: An empirical analysis of COVOL and major financial markets," International Review of Financial Analysis, Elsevier, volume 93, issue C, DOI: 10.1016/j.irfa.2024.103152.
• Ahmed, Mohamed Shaker & Elnahass, Marwa, 2024, "Being famous matters: Evidence from cash flow volatility," International Review of Financial Analysis, Elsevier, volume 93, issue C, DOI: 10.1016/j.irfa.2024.103165.
• Karim, Sitara & Shafiullah, Muhammad & Naeem, Muhammad Abubakr, 2024, "When one domino falls, others follow: A machine learning analysis of extreme risk spillovers in developed stock markets," International Review of Financial Analysis, Elsevier, volume 93, issue C, DOI: 10.1016/j.irfa.2024.103202.
• Parnes, Dror & Gormus, Alper, 2024, "Prescreening bank failures with K-means clustering: Pros and cons," International Review of Financial Analysis, Elsevier, volume 93, issue C, DOI: 10.1016/j.irfa.2024.103222.
• Cakici, Nusret & Shahzad, Syed Jawad Hussain & Będowska-Sójka, Barbara & Zaremba, Adam, 2024, "Machine learning and the cross-section of cryptocurrency returns," International Review of Financial Analysis, Elsevier, volume 94, issue C, DOI: 10.1016/j.irfa.2024.103244.
• Guo, Yongzhen & Wang, Yinghuan, 2024, "It is a small world: The effect of analyst-media school ties on analyst performance," International Review of Financial Analysis, Elsevier, volume 94, issue C, DOI: 10.1016/j.irfa.2024.103250.
• Ben Ameur, Hachmi & Ftiti, Zied & Louhichi, Waël & Yousfi, Mohamed, 2024, "Do green investments improve portfolio diversification? Evidence from mean conditional value-at-risk optimization," International Review of Financial Analysis, Elsevier, volume 94, issue C, DOI: 10.1016/j.irfa.2024.103255.
• Esparcia, Carlos & Escribano, Ana & Jareño, Francisco, 2024, "Assessing the crypto market stability after the FTX collapse: A study of high frequency volatility and connectedness," International Review of Financial Analysis, Elsevier, volume 94, issue C, DOI: 10.1016/j.irfa.2024.103287.
• Suzuki, Masataka, 2024, "A consumption-based term structure model of bonds and equity," International Review of Financial Analysis, Elsevier, volume 94, issue C, DOI: 10.1016/j.irfa.2024.103310.
• Huang, Yujun, 2024, "Do ESG ETFs provide downside risk protection during Covid-19? Evidence from forecast combination models," International Review of Financial Analysis, Elsevier, volume 94, issue C, DOI: 10.1016/j.irfa.2024.103320.
• Biondo, Alessio Emanuele & Mazzarino, Laura & Pluchino, Alessandro, 2024, "Trading strategies and Financial Performances: A simulation approach," International Review of Financial Analysis, Elsevier, volume 95, issue PB, DOI: 10.1016/j.irfa.2024.103426.
• Dainelli, Francesco & Bet, Gianmarco & Fabrizi, Eugenio, 2024, "The financial health of a company and the risk of its default: Back to the future," International Review of Financial Analysis, Elsevier, volume 95, issue PB, DOI: 10.1016/j.irfa.2024.103449.
• Peng, Yaohao & de Moraes Souza, João Gabriel, 2024, "Chaos, overfitting and equilibrium: To what extent can machine learning beat the financial market?," International Review of Financial Analysis, Elsevier, volume 95, issue PB, DOI: 10.1016/j.irfa.2024.103474.
• Fallah, Mir Feiz & Pourmansouri, Rezvan & Ahmadpour, Bahador, 2024, "Presenting a new deep learning-based method with the incorporation of error effects to predict certain cryptocurrencies," International Review of Financial Analysis, Elsevier, volume 95, issue PC, DOI: 10.1016/j.irfa.2024.103466.
• Moffo, Ahmadou Mustapha Fonton, 2024, "A machine learning approach in stress testing US bank holding companies," International Review of Financial Analysis, Elsevier, volume 95, issue PC, DOI: 10.1016/j.irfa.2024.103476.
• Ben Hamida, Amal & de Peretti, Christian & Belkacem, Lotfi, 2024, "The link between abnormal numbers and price movements of financial securities: How does Benford’s law predict stock returns?," International Review of Financial Analysis, Elsevier, volume 95, issue PC, DOI: 10.1016/j.irfa.2024.103517.
• Cakici, Nusret & Zaremba, Adam, 2024, "What drives stock returns across countries? Insights from machine learning models," International Review of Financial Analysis, Elsevier, volume 96, issue PA, DOI: 10.1016/j.irfa.2024.103569.
• Ardakani, Omid M., 2024, "Portfolio optimization with transfer entropy constraints," International Review of Financial Analysis, Elsevier, volume 96, issue PA, DOI: 10.1016/j.irfa.2024.103644.
• Gong, Xue & Xu, Weijun & Li, Xiaodan & Gong, Xue, 2024, "Presidential economic approval rating and global foreign exchange market volatility," International Review of Financial Analysis, Elsevier, volume 96, issue PB, DOI: 10.1016/j.irfa.2024.103584.
• Schlosky, Minh Tam Tammy & Karadas, Serkan & Stivers, Adam, 2024, "Forecasting U.S. Stock Returns Conditional on Geopolitical Risk and Business Cycles," International Review of Financial Analysis, Elsevier, volume 96, issue PB, DOI: 10.1016/j.irfa.2024.103707.
• Banerjee, Ameet Kumar & Sensoy, Ahmet & Goodell, John W. & Mahapatra, Biplab, 2024, "Impact of media hype and fake news on commodity futures prices: A deep learning approach over the COVID-19 period," Finance Research Letters, Elsevier, volume 59, issue C, DOI: 10.1016/j.frl.2023.104658.
• Pelster, Matthias & Val, Joel, 2024, "Can ChatGPT assist in picking stocks?," Finance Research Letters, Elsevier, volume 59, issue C, DOI: 10.1016/j.frl.2023.104786.
• Lalwani, Vaibhav, 2024, "Incorporating green assets in equity portfolios," Finance Research Letters, Elsevier, volume 59, issue C, DOI: 10.1016/j.frl.2023.104815.
• Wang, Peiwen & Huang, Guanglin, 2024, "Measuring systemic risk contribution: A higher-order moment augmented approach," Finance Research Letters, Elsevier, volume 59, issue C, DOI: 10.1016/j.frl.2023.104833.
• Gould, John & Sun, Zhiyue & Yang, Joey W., 2024, "ETF MAX and MIN effects," Finance Research Letters, Elsevier, volume 60, issue C, DOI: 10.1016/j.frl.2023.104835.
• Kwon, Ji Ho & Sohn, Bumjean, 2024, "The ICAPM and empirical pricing factors: A simulation study," Finance Research Letters, Elsevier, volume 60, issue C, DOI: 10.1016/j.frl.2023.104836.
• Stein, Roberto, 2024, "More than meets the eye: On the relationship between skewness and expected returns," Finance Research Letters, Elsevier, volume 60, issue C, DOI: 10.1016/j.frl.2023.104876.
• Zhang, Xiaoyun & Guo, Qiang, 2024, "How useful are energy-related uncertainty for oil price volatility forecasting?," Finance Research Letters, Elsevier, volume 60, issue C, DOI: 10.1016/j.frl.2023.104953.
• Biktimirov, Ernest N. & Sokolyk, Tatyana & Ayanso, Anteneh, 2024, "What is behind housing sentiment?," Finance Research Letters, Elsevier, volume 60, issue C, DOI: 10.1016/j.frl.2023.104966.
• Guinea, Laurentiu & Pérez, Rafaela & Ruiz, Jesús, 2024, "Asymmetric effects of financial volatility and volatility-of-volatility shocks on the energy mix," Finance Research Letters, Elsevier, volume 61, issue C, DOI: 10.1016/j.frl.2023.104938.
• Taussig, Roi D., 2024, "Pension expenses, risk, and implications for stock returns," Finance Research Letters, Elsevier, volume 61, issue C, DOI: 10.1016/j.frl.2024.105016.
• Liu, Dinggao & Chen, Kaijie & Cai, Yi & Tang, Zhenpeng, 2024, "Interpretable EU ETS Phase 4 prices forecasting based on deep generative data augmentation approach," Finance Research Letters, Elsevier, volume 61, issue C, DOI: 10.1016/j.frl.2024.105038.
• Li, Pan & Chen, Kecai & Zhu, Xiaoneng, 2024, "Extreme Sentiment and Jumps in Analyst Forecast Dispersion," Finance Research Letters, Elsevier, volume 62, issue PA, DOI: 10.1016/j.frl.2024.105113.
• Bock, J. & Geissel, S., 2024, "Evolution of stock market efficiency in Europe: Evidence from measuring periods of inefficiency," Finance Research Letters, Elsevier, volume 62, issue PA, DOI: 10.1016/j.frl.2024.105129.
• Albers, Stefan & Kestner, Lars N., 2024, "The daily rise and fall of the VIX1D: Causes and solutions of its overnight bias," Finance Research Letters, Elsevier, volume 62, issue PA, DOI: 10.1016/j.frl.2024.105186.
• Kirtac, Kemal & Germano, Guido, 2024, "Sentiment trading with large language models," Finance Research Letters, Elsevier, volume 62, issue PB, DOI: 10.1016/j.frl.2024.105227.
• Ouyang, Minhua & Xiao, Hailian, 2024, "Tail risk spillovers among Chinese stock market sectors," Finance Research Letters, Elsevier, volume 62, issue PB, DOI: 10.1016/j.frl.2024.105233.
• Obrimah, Oghenovo A., 2024, "A parsimonious analytically specified general equilibrium structure that spans discount rates," Finance Research Letters, Elsevier, volume 62, issue PB, DOI: 10.1016/j.frl.2024.105252.
• Li, Wei & Zhang, Junchao & Cao, Xiangye & Han, Wei, 2024, "Is the prediction of precious metal market volatility influenced by internet searches regarding uncertainty?," Finance Research Letters, Elsevier, volume 62, issue PB, DOI: 10.1016/j.frl.2024.105269.
• Li, Xiaodan & Gong, Xue & Xing, Lu, 2024, "The impact of presidential economic approval rating on stock volatility: An industrial perspective," Finance Research Letters, Elsevier, volume 63, issue C, DOI: 10.1016/j.frl.2024.105326.
• Jing, Zhongbo & Li, Qin & Zhao, Hongyi & Zhao, Yang, 2024, "Predicting stock price crash risk in China: A modified graph WaveNet model," Finance Research Letters, Elsevier, volume 64, issue C, DOI: 10.1016/j.frl.2024.105468.
• Castro-Iragorri, Carlos & Gómez, Fabio & Quiceno, Nancy, 2024, "Worst-case higher moment risk measure: Addressing distributional shifts and procyclicality," Finance Research Letters, Elsevier, volume 65, issue C, DOI: 10.1016/j.frl.2024.105580.
• Ma, Feng & Lyu, Zhichong & Li, Haibo, 2024, "Can ChatGPT predict Chinese equity premiums?," Finance Research Letters, Elsevier, volume 65, issue C, DOI: 10.1016/j.frl.2024.105631.
• Zhang, Yu & Zhao, Mengxiang, 2024, "Picking funds in China," Finance Research Letters, Elsevier, volume 67, issue PA, DOI: 10.1016/j.frl.2024.105817.
• Göncü, Ahmet & Kuzubaş, Tolga U. & Saltoğlu, Burak, 2024, "Predicting oil prices: A comparative analysis of machine learning and image recognition algorithms for trend prediction," Finance Research Letters, Elsevier, volume 67, issue PB, DOI: 10.1016/j.frl.2024.105874.
• Wang, Wenhao & Zhang, Qingyi & An, Pengda & Cai, Feifei, 2024, "Momentum and reversal strategies with low uncertainty," Finance Research Letters, Elsevier, volume 68, issue C, DOI: 10.1016/j.frl.2024.105970.
• Liu, Li, 2024, "Economic uncertainty and time-varying return predictability," Finance Research Letters, Elsevier, volume 68, issue C, DOI: 10.1016/j.frl.2024.106025.
• He, Yun & Li, Wei & Tan, Xiaofen & Wang, Yufan, 2024, "The time-varying interaction of northbound capital flows and stock market performance in China," Finance Research Letters, Elsevier, volume 69, issue PA, DOI: 10.1016/j.frl.2024.106076.
• Bouri, Elie & Gupta, Rangan & Pierdzioch, Christian & Polat, Onur, 2024, "Forecasting U.S. recessions using over 150 years of data: Stock-market moments versus oil-market moments," Finance Research Letters, Elsevier, volume 69, issue PB, DOI: 10.1016/j.frl.2024.106179.
• Zhang, Li & Wang, Lu & Nguyen, Thong Trung & Ren, Ruiyi, 2024, "Volatility forecasting of clean energy ETF using GARCH-MIDAS with neural network model," Finance Research Letters, Elsevier, volume 70, issue C, DOI: 10.1016/j.frl.2024.106286.
• Bojaj, Martin M. & Aharon, David Y., 2024, "Financial measures and banking crisis: New evidence," Finance Research Letters, Elsevier, volume 70, issue C, DOI: 10.1016/j.frl.2024.106326.
• Jiang, Fuwei & Ma, Tian & Zhu, Feifei, 2024, "Fundamental characteristics, machine learning, and stock price crash risk," Journal of Financial Markets, Elsevier, volume 69, issue C, DOI: 10.1016/j.finmar.2024.100908.
• Carro, Adrian & Stupariu, Patricia, 2024, "Uncertainty, non-linear contagion and the credit quality channel: An application to the Spanish interbank market," Journal of Financial Stability, Elsevier, volume 71, issue C, DOI: 10.1016/j.jfs.2024.101226.
• Siebenbrunner, Christoph & Hafner-Guth, Martin & Spitzer, Ralph & Trappl, Stefan, 2024, "Assessing the systemic risk impact of bank bail-ins," Journal of Financial Stability, Elsevier, volume 71, issue C, DOI: 10.1016/j.jfs.2024.101229.
• Gambacorta, Leonardo & Huang, Yiping & Qiu, Han & Wang, Jingyi, 2024, "How do machine learning and non-traditional data affect credit scoring? New evidence from a Chinese fintech firm," Journal of Financial Stability, Elsevier, volume 73, issue C, DOI: 10.1016/j.jfs.2024.101284.
• Kim, Hyeongwoo & Son, Jisoo, 2024, "What charge-off rates are predictable by macroeconomic latent factors?," Journal of Financial Stability, Elsevier, volume 74, issue C, DOI: 10.1016/j.jfs.2024.101301.
• Christopoulos, Andreas D. & Barratt, Joshua G. & Ilut, Daniel C., 2024, "Synthetic cap rate indices (1991-Covid era)," Global Finance Journal, Elsevier, volume 60, issue C, DOI: 10.1016/j.gfj.2024.100961.
• Jiang, Yifu & Olmo, Jose & Atwi, Majed, 2024, "Deep reinforcement learning for portfolio selection," Global Finance Journal, Elsevier, volume 62, issue C, DOI: 10.1016/j.gfj.2024.101016.
• Ghaemi Asl, Mahdi & Ben Jabeur, Sami & Hosseini, Seyedeh Sana & Tajmir Riahi, Hamed, 2024, "Fintech's impact on conventional and Islamic sustainable equities: Short- and long-term contributions of the digital financial ecosystem," Global Finance Journal, Elsevier, volume 62, issue C, DOI: 10.1016/j.gfj.2024.101022.
• Siburg, Karl Friedrich & Strothmann, Christopher & Weiß, Gregor, 2024, "Comparing and quantifying tail dependence," Insurance: Mathematics and Economics, Elsevier, volume 118, issue C, pages 95-103, DOI: 10.1016/j.insmatheco.2024.06.006.
• Zhao, Xiaojuan & Wang, Ye & Liu, Weiyi, 2024, "Someone like you: Lottery-like preference and the cross-section of expected returns in the cryptocurrency market," Journal of International Financial Markets, Institutions and Money, Elsevier, volume 91, issue C, DOI: 10.1016/j.intfin.2024.101957.
• Bas, Tugba & Malki, Issam & Sivaprasad, Sheeja, 2024, "Connectedness between central bank digital currency index, financial stability and digital assets," Journal of International Financial Markets, Institutions and Money, Elsevier, volume 92, issue C, DOI: 10.1016/j.intfin.2024.101981.
• Poli, Federica & Rossi, Simone & Borroni, Mariarosa, 2024, "Fall of dwarfs: micro and macroeconomic determinants of the disappearance of European small banks," Journal of International Financial Markets, Institutions and Money, Elsevier, volume 96, issue C, DOI: 10.1016/j.intfin.2024.102042.
• Huang, Zih-Chun & Sangiorgi, Ivan & Urquhart, Andrew, 2024, "Forecasting Bitcoin volatility using machine learning techniques," Journal of International Financial Markets, Institutions and Money, Elsevier, volume 97, issue C, DOI: 10.1016/j.intfin.2024.102064.
• Poutré, Cédric & Dionne, Georges & Yergeau, Gabriel, 2024, "The profitability of lead–lag arbitrage at high frequency," International Journal of Forecasting, Elsevier, volume 40, issue 3, pages 1002-1021, DOI: 10.1016/j.ijforecast.2023.09.001.
• Berrisch, Jonathan & Ziel, Florian, 2024, "Multivariate probabilistic CRPS learning with an application to day-ahead electricity prices," International Journal of Forecasting, Elsevier, volume 40, issue 4, pages 1568-1586, DOI: 10.1016/j.ijforecast.2024.01.005.
• Call, Andrew C. & Hribar, Paul & Skinner, Douglas J. & Volant, David, 2024, "Corporate managers’ perspectives on forward-looking guidance: Survey evidence," Journal of Accounting and Economics, Elsevier, volume 78, issue 2, DOI: 10.1016/j.jacceco.2024.101731.
• Fritzsch, Simon & Timphus, Maike & Weiß, Gregor, 2024, "Marginals versus copulas: Which account for more model risk in multivariate risk forecasting?," Journal of Banking & Finance, Elsevier, volume 158, issue C, DOI: 10.1016/j.jbankfin.2023.107035.
• Cheng, Hang & Guo, Hui & Shi, Yongdong, 2024, "Multifactor conditional equity premium model: Evidence from China's stock market," Journal of Banking & Finance, Elsevier, volume 161, issue C, DOI: 10.1016/j.jbankfin.2024.107117.
• Bao, Te & Füllbrunn, Sascha & Pei, Jiaoying & Zong, Jichuan, 2024, "Reading the market? Expectation coordination and theory of mind," Journal of Economic Behavior & Organization, Elsevier, volume 219, issue C, pages 510-527, DOI: 10.1016/j.jebo.2024.01.018.
• Zhang, Li & Liang, Chao & Huynh, Luu Duc Toan & Wang, Lu & Damette, Olivier, 2024, "Measuring the impact of climate risk on renewable energy stock volatility: A case study of G20 economies," Journal of Economic Behavior & Organization, Elsevier, volume 223, issue C, pages 168-184, DOI: 10.1016/j.jebo.2024.05.005.
• Marfè, Roberto & Pénasse, Julien, 2024, "Measuring macroeconomic tail risk," Journal of Financial Economics, Elsevier, volume 156, issue C, DOI: 10.1016/j.jfineco.2024.103838.
• Cao, Sean & Jiang, Wei & Wang, Junbo & Yang, Baozhong, 2024, "From Man vs. Machine to Man + Machine: The art and AI of stock analyses," Journal of Financial Economics, Elsevier, volume 160, issue C, DOI: 10.1016/j.jfineco.2024.103910.
• Biktimirov, Ernest N. & Sokolyk, Tatyana & Ayanso, Anteneh, 2024, "Unpacking the relation between media sentiment and house prices: A topic modeling approach," Journal of Housing Economics, Elsevier, volume 66, issue C, DOI: 10.1016/j.jhe.2024.102025.
• Bei, Zeyun & Lin, Juan & Zhou, Yinggang, 2024, "No safe haven, only diversification and contagion — Intraday evidence around the COVID-19 pandemic," Journal of International Money and Finance, Elsevier, volume 143, issue C, DOI: 10.1016/j.jimonfin.2024.103069.
• Lazar, Emese & Pan, Jingqi & Wang, Shixuan, 2024, "On the estimation of Value-at-Risk and Expected Shortfall at extreme levels," Journal of Commodity Markets, Elsevier, volume 34, issue C, DOI: 10.1016/j.jcomm.2024.100391.
• Ma, Tian & Li, Ganghui & Zhang, Huajing, 2024, "Stock return predictability using economic narrative: Evidence from energy sectors," Journal of Commodity Markets, Elsevier, volume 35, issue C, DOI: 10.1016/j.jcomm.2024.100418.
• Ma, Yong & Zhou, Mingtao & Li, Shuaibing, 2024, "Weathering market swings: Does climate risk matter for agricultural commodity price predictability?," Journal of Commodity Markets, Elsevier, volume 36, issue C, DOI: 10.1016/j.jcomm.2024.100423.
• Mousavi, Mohammad Mahdi & Gozgor, Giray & Acheampong, Albert, 2024, "Do oil market shocks affect financial distress? Evidence from firm-level global data," Journal of Commodity Markets, Elsevier, volume 36, issue C, DOI: 10.1016/j.jcomm.2024.100436.
• Ewald, Christian Oliver & Li, Yaoyu, 2024, "The role of news sentiment in salmon price prediction using deep learning," Journal of Commodity Markets, Elsevier, volume 36, issue C, DOI: 10.1016/j.jcomm.2024.100438.
• Li, Kaixin & Zhang, Zhikai & Wang, Yudong & Zhang, Yaojie, 2024, "Forecasting crude oil returns with oil-related industry ESG indices," Journal of Commodity Markets, Elsevier, volume 36, issue C, DOI: 10.1016/j.jcomm.2024.100444.
• Tse, Tiffany Tsz Kwan & Hanaki, Nobuyuki & Mao, Bolin, 2024, "Beware the performance of an algorithm before relying on it: Evidence from a stock price forecasting experiment," Journal of Economic Psychology, Elsevier, volume 102, issue C, DOI: 10.1016/j.joep.2024.102727.