Research classified by Journal of Economic Literature (JEL) codes

2024

• 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.
• Rivera-Alonso, David & Iglesias, Emma M., 2024, "Is the Chinese crude oil spot price a good hedging tool for other crude oil prices, and in special for the main Russian oil benchmarks and during international sanctions?," Resources Policy, Elsevier, volume 90, issue C, DOI: 10.1016/j.resourpol.2024.104778.
• Sen, Chitrakalpa & Chakrabarti, Gagari, 2024, "Beyond the glitter: An empirical assessment of the true risk and hedging role of precious metals," Resources Policy, Elsevier, volume 96, issue C, DOI: 10.1016/j.resourpol.2024.105238.
• Wu, Xinyu & Qian, Jia & Zhao, Xiaohan, 2024, "Forecasting Chinese stock market volatility with option-implied risk aversion: Evidence from extended realized EGARCH-MIDAS approach," Pacific-Basin Finance Journal, Elsevier, volume 83, issue C, DOI: 10.1016/j.pacfin.2023.102245.
• Park, Dojoon & Hahn, Jaehoon & Eom, Young Ho, 2024, "Predicting the equity premium with financial ratios: A comprehensive look over a long period in Korea," Pacific-Basin Finance Journal, Elsevier, volume 84, issue C, DOI: 10.1016/j.pacfin.2024.102320.
• Deng, Shangkun & Luo, Qunfang & Zhu, Yingke & Ning, Hong & Shimada, Tatsuro, 2024, "Financial risk forewarning with an interpretable ensemble learning approach: An empirical analysis based on Chinese listed companies," Pacific-Basin Finance Journal, Elsevier, volume 85, issue C, DOI: 10.1016/j.pacfin.2024.102393.
• Le, Cao Hoang Anh & Shan, Yaowen & Taylor, Stephen, 2024, "International economic policy uncertainty and analysts' earnings forecasts," Pacific-Basin Finance Journal, Elsevier, volume 85, issue C, DOI: 10.1016/j.pacfin.2024.102403.
• Tang, Wenjin & Bu, Hui & Ji, Yuqiong & Li, Zhongfei, 2024, "Market uncertainty and information content in complex seasonality of prices," Pacific-Basin Finance Journal, Elsevier, volume 86, issue C, DOI: 10.1016/j.pacfin.2024.102430.
• Wu, Xinyu & Zhao, An & Wang, Yuyao & Han, Yang, 2024, "Forecasting Chinese stock market volatility with high-frequency intraday and current return information," Pacific-Basin Finance Journal, Elsevier, volume 86, issue C, DOI: 10.1016/j.pacfin.2024.102458.
• Zhong, Hao & He, Xiaoxiao & Li, Yuqi, 2024, "Is there a time-series momentum effect in the Asian crude oil futures market?," Pacific-Basin Finance Journal, Elsevier, volume 86, issue C, DOI: 10.1016/j.pacfin.2024.102472.
• Salisu, Afees A. & Ogbonna, Ahamuefula E. & Gupta, Rangan & Bouri, Elie, 2024, "Energy-related uncertainty and international stock market volatility," The Quarterly Review of Economics and Finance, Elsevier, volume 95, issue C, pages 280-293, DOI: 10.1016/j.qref.2024.04.005.
• Atance, David & Serna, Gregorio, 2024, "Time-varying expected returns, conditional skewness and Bitcoin return predictability," The Quarterly Review of Economics and Finance, Elsevier, volume 96, issue C, DOI: 10.1016/j.qref.2024.101868.
• Huang, Alex YiHou, 2024, "Mechanisms of overpricing: An investigation on momentum crashes," International Review of Economics & Finance, Elsevier, volume 89, issue PA, pages 118-142, DOI: 10.1016/j.iref.2023.07.059.
• Luo, Tao & Sun, Huaping & Zhang, Lixia & Bai, Jiancheng, 2024, "Do the dynamics of macroeconomic attention drive the yen/dollar exchange market volatility?," International Review of Economics & Finance, Elsevier, volume 89, issue PB, pages 597-611, DOI: 10.1016/j.iref.2023.09.012.
• Li, Xiaodan & Gong, Xue & Ge, Futing & Huang, Jingjing, 2024, "Forecasting stock volatility using pseudo-out-of-sample information," International Review of Economics & Finance, Elsevier, volume 90, issue C, pages 123-135, DOI: 10.1016/j.iref.2023.11.014.
• Peterburgsky, Stanley, 2024, "Size, value and volatility," International Review of Economics & Finance, Elsevier, volume 91, issue C, pages 752-763, DOI: 10.1016/j.iref.2024.01.038.
• Huang, Mu-Nan & Lee, Han-Hsing, 2024, "Inter-industry network and credit risk," International Review of Economics & Finance, Elsevier, volume 92, issue C, pages 598-625, DOI: 10.1016/j.iref.2024.02.044.
• Nasreen, Samia & Tiwari, Aviral Kumar & Goodell, John W. & Tedeschi, Marco, 2024, "Asymmetric and frequency-domain spillover effects among industrial metals, precious metals, and energy futures markets," International Review of Economics & Finance, Elsevier, volume 93, issue PA, pages 1556-1592, DOI: 10.1016/j.iref.2024.04.010.
• Garcia-Jorcano, Laura & Sanchis-Marco, Lidia, 2024, "Forecasting the effect of extreme sea-level rise on financial market risk," International Review of Economics & Finance, Elsevier, volume 93, issue PB, pages 1-27, DOI: 10.1016/j.iref.2024.03.079.
• Sato, Ayano & Nakata, Hayato & Percy, Jay, 2024, "Time-variant safe haven currencies," International Review of Economics & Finance, Elsevier, volume 93, issue PB, pages 316-328, DOI: 10.1016/j.iref.2024.04.015.
• Li, Zhao-Chen & Xie, Chi & Wang, Gang-Jin & Zhu, You & Zeng, Zhi-Jian & Gong, Jue, 2024, "Forecasting global stock market volatilities: A shrinkage heterogeneous autoregressive (HAR) model with a large cross-market predictor set," International Review of Economics & Finance, Elsevier, volume 93, issue PB, pages 673-711, DOI: 10.1016/j.iref.2024.05.008.
• Deprez, Niek & Frömmel, Michael, 2024, "Are simple technical trading rules profitable in bitcoin markets?," International Review of Economics & Finance, Elsevier, volume 93, issue PB, pages 858-874, DOI: 10.1016/j.iref.2024.05.003.
• Abdelaziz Eissa, Mohamed & Al Refai, Hisham, 2024, "Context-dependent responses to geopolitical risk in Middle Eastern and African stock markets: An asymmetric volatility spillover study," International Review of Economics & Finance, Elsevier, volume 94, issue C, DOI: 10.1016/j.iref.2024.103402.
• Patra, Saswat, 2024, "An empirical analysis of the volume-volatility nexus in crude oil markets under structural breaks: Implications for forecasting," International Review of Economics & Finance, Elsevier, volume 94, issue C, DOI: 10.1016/j.iref.2024.103434.
• He, Mengxi & Wen, Danyan & Xing, Lu & Zhang, Yaojie, 2024, "Industry volatility concentration and the predictability of aggregate stock market volatility," International Review of Economics & Finance, Elsevier, volume 95, issue C, DOI: 10.1016/j.iref.2024.103488.
• Zhang, Xincheng & Wu, Shaojiang, 2024, "Natural resources and sustainable development: Evidence from the dynamic correlation between crude oil and gold market," International Review of Economics & Finance, Elsevier, volume 96, issue PB, DOI: 10.1016/j.iref.2024.103665.
• Aspris, Angelo & Malloch, Hamish & Svec, Jiri, 2024, "Option implied dividends and the market risk premium," International Review of Economics & Finance, Elsevier, volume 96, issue PB, DOI: 10.1016/j.iref.2024.103675.
• Liu, Qiming & Liu, Zhenya & Moussa, Faten & Mu, Yuhao, 2024, "International capital flow in a period of high inflation: The case of China," Research in International Business and Finance, Elsevier, volume 67, issue PB, DOI: 10.1016/j.ribaf.2023.102070.
• Hoque, Ariful & Le, Thi & Hasan, Morshadul & Abedin, Mohammad Zoynul, 2024, "Does market efficiency matter for Shanghai 50 ETF index options?," Research in International Business and Finance, Elsevier, volume 67, issue PB, DOI: 10.1016/j.ribaf.2023.102129.
• Esparcia, Carlos & López, Raquel, 2024, "Performance of crypto-Forex portfolios based on intraday data," Research in International Business and Finance, Elsevier, volume 69, issue C, DOI: 10.1016/j.ribaf.2024.102217.
• Pan, Zhigang & Bai, Zhihong & Xing, Xiaochao & Wang, Zhufeng, 2024, "US inflation and global commodity prices: Asymmetric interdependence," Research in International Business and Finance, Elsevier, volume 69, issue C, DOI: 10.1016/j.ribaf.2024.102245.
• Xing, Jin & Chi, Guotai & Pan, Ancheng, 2024, "Instance-dependent misclassification cost-sensitive learning for default prediction," Research in International Business and Finance, Elsevier, volume 69, issue C, DOI: 10.1016/j.ribaf.2024.102265.
• Yang, Jinyu & Xia, Guoen & Dong, Dayong, 2024, "Placebo in the random walk of stock price: Momentum effect of corporate site visits," Research in International Business and Finance, Elsevier, volume 70, issue PB, DOI: 10.1016/j.ribaf.2024.102383.
• Ahmed, Mohamed Shaker & El-Masry, Ahmed A. & Al-Maghyereh, Aktham I. & Kumar, Satish, 2024, "Cryptocurrency volatility: A review, synthesis, and research agenda," Research in International Business and Finance, Elsevier, volume 71, issue C, DOI: 10.1016/j.ribaf.2024.102472.
• Wang, Jingya & Taylor, Alex P., 2024, "Predicting consumption-wealth ratio changes and stock market returns," Research in International Business and Finance, Elsevier, volume 71, issue C, DOI: 10.1016/j.ribaf.2024.102474.
• Anwer, Zaheer & Khan, Muhammad Arif & Hassan, M. Kabir & Singh, Manjeet Kaur Harnek, 2024, "Assessing dynamic co-movement of news based uncertainty indices and distance-to -default of global FinTech firms," Research in International Business and Finance, Elsevier, volume 71, issue C, DOI: 10.1016/j.ribaf.2024.102476.
• Esparcia, Carlos & Díaz, Antonio, 2024, "The football world upside down: Traditional equities as an alternative for the new fan tokens? A portfolio optimization study," Research in International Business and Finance, Elsevier, volume 71, issue C, DOI: 10.1016/j.ribaf.2024.102496.
• Brum-Civelli, Conrado & Fried-Gindel, Alejandro & Garcia-Hiernaux, Alfredo, 2024, "IFCI-SA: International financial conditions index for South American economies," Research in International Business and Finance, Elsevier, volume 72, issue PA, DOI: 10.1016/j.ribaf.2024.102507.
• Fu, Fanjie & Fang, Jing & Yang, Mei & Yao, Shujie, 2024, "Institutional investor horizons and stock price crash risk," Research in International Business and Finance, Elsevier, volume 72, issue PA, DOI: 10.1016/j.ribaf.2024.102509.
• Galbraith, James K., 2024, "La medicina medieval de la economía ortodoxa contra la inflación," El Trimestre Económico, Fondo de Cultura Económica, volume 91, issue 362, pages 409-414, abril-jun, DOI: https://doi.org/10.20430/ete.v91i36.
• Stiglitz, Joseph E., 2024, "Neoliberalismo, economía keynesiana y la respuesta a la inflación actual," El Trimestre Económico, Fondo de Cultura Económica, volume 91, issue 363, pages 707-749, julio-sep, DOI: https://doi.org/10.20430/ete.v91i36.
• Ziwen Gao & Steven F. Lehrer & Tian Xie & Xinyu Zhang, 2024, "Averaging Heterogeneous Autoregression Models with Heteroskedastic Errors: Theory and an Application to Cryptocurrency Volatility Forecasting," Advances in Econometrics, Emerald Group Publishing Limited, "Essays in Honor of Subal Kumbhakar", DOI: 10.1108/S0731-905320240000046006.
• Stiven Agusta & Fuad Rakhman & Jogiyanto Hartono Mustakini & Singgih Wijayana, 2024, "Enhancing the accuracy of stock return movement prediction in Indonesia through recent fundamental value incorporation in multilayer perceptron," Asian Journal of Accounting Research, Emerald Group Publishing Limited, volume 9, issue 4, pages 358-377, July, DOI: 10.1108/AJAR-01-2024-0006.
• Ting He & Kenneth Zheng, 2024, "Rational expectations tests on financial analysts’ cash flow forecasts," International Journal of Managerial Finance, Emerald Group Publishing Limited, volume 21, issue 2, pages 606-638, November, DOI: 10.1108/IJMF-03-2024-0162.
• Amritkant Mishra & Ajit Kumar Dash, 2024, "Return volatility of Asian stock exchanges; a GARCH DCC analysis with reference of Bitcoin and global crude oil price movement," Journal of Chinese Economic and Foreign Trade Studies, Emerald Group Publishing Limited, volume 17, issue 1, pages 29-48, May, DOI: 10.1108/JCEFTS-01-2024-0009.
• Trung Hai Le, 2024, "Forecasting value-at-risk and expected shortfall in emerging market: does forecast combination help?," Journal of Risk Finance, Emerald Group Publishing Limited, volume 25, issue 1, pages 160-177, January, DOI: 10.1108/JRF-06-2023-0137.
• Rama K. Malladi & Theodore P. Byrne & Pallavi Malladi, 2024, "Integrating corporate social responsibility with financial outcomes: stock performance of firms hiring US veterans during COVID-19," Review of Behavioral Finance, Emerald Group Publishing Limited, volume 17, issue 1, pages 39-63, September, DOI: 10.1108/RBF-11-2023-0294.
• Demetri Tsanacas, 2024, "Extreme Weather Patterns and Risk Assessment Strategies in the Banking Industry: A Survey," International Journal of Finance, Insurance and Risk Management, International Journal of Finance, Insurance and Risk Management, volume 14, issue 1, pages 3-11.
• Jaroslaw Klepacki, 2024, "Co-variance in Action: Analyzing the Impact of EUR/USD Exchange Rate Changes on Polish Zloty (PLN) Valuation (2019–2022) as a Predictive Tool in Forex Markets," European Research Studies Journal, European Research Studies Journal, volume 0, issue 2, pages 952-966.
• Bernard Kokczynski & Dorota Witkowska & Blazej Socha, 2024, "Predicting Bankruptcy: Insights from Polish Non-Public Companies (2019–2022)," European Research Studies Journal, European Research Studies Journal, volume 0, issue Special A, pages 252-264.
• Susana Calao & José I. Jarne & David Wroblewski, 2024, "Earnings Forecasts Accuracy: International Evidence of the Impact of the Covid-19 Pandemic," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, volume 74, issue 4, pages 473-499, October.
• Karel Janda & Mathieu Petit, 2024, "Analyzing Decision-Making in Deep-Q Reinforcement Learning for Trading: A Case Study on Tesla Company and its Supply Chain," Working Papers IES, Charles University Prague, Faculty of Social Sciences, Institute of Economic Studies, number 2024/40, Nov, revised Nov 2024.
• Jens H. E. Christensen & Mark M. Spiegel, 2024, "Inflation Expectations, Liquidity Premia and Global Spillovers in Japanese Bond Markets," Working Paper Series, Federal Reserve Bank of San Francisco, number 2024-12, Jul, DOI: 10.24148/wp2024-12.
• Alexander E. Abramov & Maria I. Chernova, 2024, "IPO of Russian Companies: Theory, Indicators, Trends and Prospects," Finansovyj žhurnal — Financial Journal, Financial Research Institute, Moscow 125375, Russia, issue 6, pages 42-60, December, DOI: 10.31107/2075-1990-2024-6-42-60.
• Nicoleta Valentina Florea & Gabriel Croitoru & Georgiana Radu (Cârstea) & Daria Florea, 2024, "The Analysis of the Impact of Digital Product Innovation and Human Resources Specialists on Intention to Use Artificial Intelligence in Financial Banking System," Journal of Financial Studies, Institute of Financial Studies, volume 16, issue 9, pages 96-110, May, DOI: 10.55654/JFS.2024.9.16.07.
• Dean Fantazzini, 2024, "Adaptive Conformal Inference for Computing Market Risk Measures: An Analysis with Four Thousand Crypto-Assets," JRFM, MDPI, volume 17, issue 6, pages 1-44, June.
• Diego Alejandro Martínez Cruz & Philip Rory Symington Alzate, 2024, "Robust Assessment of External Vulnerabilities in an Emerging Market During Stress Scenarios," IHEID Working Papers, Economics Section, The Graduate Institute of International Studies, number 15-2024, Jul.