Research classified by Journal of Economic Literature (JEL) codes

2023

• Mutambara Tatenda Emmanuel & Nyatanga Phocenah & McCullough Kerry, 2023, "The Impact of Working Capital and Macroeconomic Variables on the Profitability of Listed Industrial Firms in South Africa," International Journal of Economics and Financial Issues, International Journal of Economics and Financial Issues, volume 13, issue 5, pages 32-42, September.
• Kolawole Ibrahim Gbolahan, 2023, "An Empirical Investigation of Bitcoin Hedging Capabilities against Inflation using VECM: The Case of United States, Eurozone, Philippines, Ukraine, Canada, India, and Nigeria," International Journal of Economics and Financial Issues, International Journal of Economics and Financial Issues, volume 13, issue 6, pages 91-100, November.
• Ayi Ahadiat & Fajrin Satria Dwi Kesumah & Rialdi Azhar & Febryan Kusuma Wisnu, 2023, "Strategic Decision-Making on Mining Sector Company Stock Prices and Economic Variable (State Space Model Application)," International Journal of Energy Economics and Policy, International Journal of Energy Economics and Policy, volume 13, issue 3, pages 177-184, May.
• Mehdi Abid, 2023, "How Does Renewable Energy Consumption Affect Environmental Quality in Saudi Arabia? Evidence from Quantile Regressions," International Journal of Energy Economics and Policy, International Journal of Energy Economics and Policy, volume 13, issue 4, pages 574-578, July.
• Vogl, Markus, 2023, "Hurst exponent dynamics of S&P 500 returns: Implications for market efficiency, long memory, multifractality and financial crises predictability by application of a nonlinear dynamics analysis framework," Chaos, Solitons & Fractals, Elsevier, volume 166, issue C, DOI: 10.1016/j.chaos.2022.112884.
• Forte, Santiago & Lovreta, Lidija, 2023, "Credit default swaps, the leverage effect, and cross-sectional predictability of equity and firm asset volatility," Journal of Corporate Finance, Elsevier, volume 79, issue C, DOI: 10.1016/j.jcorpfin.2022.102347.
• Chen, Jian & Tang, Guohao & Yao, Jiaquan & Zhou, Guofu, 2023, "Employee sentiment and stock returns," Journal of Economic Dynamics and Control, Elsevier, volume 149, issue C, DOI: 10.1016/j.jedc.2023.104636.
• Skavysh, Vladimir & Priazhkina, Sofia & Guala, Diego & Bromley, Thomas R., 2023, "Quantum monte carlo for economics: Stress testing and macroeconomic deep learning," Journal of Economic Dynamics and Control, Elsevier, volume 153, issue C, DOI: 10.1016/j.jedc.2023.104680.
• Tumala, Mohammed M. & Salisu, Afees A. & Gambo, Ali I., 2023, "Disentangled oil shocks and stock market volatility in Nigeria and South Africa: A GARCH-MIDAS approach," Economic Analysis and Policy, Elsevier, volume 78, issue C, pages 707-717, DOI: 10.1016/j.eap.2023.04.009.
• Li, Zhicheng & Chen, Xinyun & Xing, Haipeng, 2023, "A multifactor regime-switching model for inter-trade durations in the high-frequency limit order market," Economic Modelling, Elsevier, volume 118, issue C, DOI: 10.1016/j.econmod.2022.106082.
• Yu, Deshui & Huang, Difang & Chen, Li & Li, Luyang, 2023, "Forecasting dividend growth: The role of adjusted earnings yield," Economic Modelling, Elsevier, volume 120, issue C, DOI: 10.1016/j.econmod.2022.106188.
• Zhao, Shangwei & Xie, Tian & Ai, Xin & Yang, Guangren & Zhang, Xinyu, 2023, "Correcting sample selection bias with model averaging for consumer demand forecasting," Economic Modelling, Elsevier, volume 123, issue C, DOI: 10.1016/j.econmod.2023.106275.
• Tan, Xilong & Tao, Yubo, 2023, "Trend-based forecast of cryptocurrency returns," Economic Modelling, Elsevier, volume 124, issue C, DOI: 10.1016/j.econmod.2023.106323.
• Bucci, Andrea & Palomba, Giulio & Rossi, Eduardo, 2023, "The role of uncertainty in forecasting volatility comovements across stock markets," Economic Modelling, Elsevier, volume 125, issue C, DOI: 10.1016/j.econmod.2023.106309.
• Díaz, Antonio & Esparcia, Carlos & Huélamo, Diego, 2023, "Stablecoins as a tool to mitigate the downside risk of cryptocurrency portfolios," The North American Journal of Economics and Finance, Elsevier, volume 64, issue C, DOI: 10.1016/j.najef.2022.101838.
• Garg, Jyoti & Karmakar, Madhusudan & Paul, Samit, 2023, "A study on equity home bias using vine copula approach," The North American Journal of Economics and Finance, Elsevier, volume 64, issue C, DOI: 10.1016/j.najef.2022.101860.
• Procasky, William J. & Yin, Anwen, 2023, "Identifying the true nature of price discovery and cross-market informational flow in the investment grade CDS and equity markets," The North American Journal of Economics and Finance, Elsevier, volume 64, issue C, DOI: 10.1016/j.najef.2022.101877.
• Alexakis, Christos & Chantziaras, Antonios & Economou, Fotini & Eleftheriou, Konstantinos & Grose, Christos, 2023, "Animal Behavior in Capital markets: Herding formation dynamics, trading volume, and the role of COVID-19 pandemic," The North American Journal of Economics and Finance, Elsevier, volume 67, issue C, DOI: 10.1016/j.najef.2023.101946.
• Caiado, Jorge & Lúcio, Francisco, 2023, "Stock market forecasting accuracy of asymmetric GARCH models during the COVID-19 pandemic," The North American Journal of Economics and Finance, Elsevier, volume 68, issue C, DOI: 10.1016/j.najef.2023.101971.
• Wang, Yide & Chen, Zan & Ji, Xiaodong, 2023, "Cross-market information transmission and stock market volatility prediction," The North American Journal of Economics and Finance, Elsevier, volume 68, issue C, DOI: 10.1016/j.najef.2023.101977.
• Yu, Deshui & Chen, Li & Li, Luyang, 2023, "Time-varying predictability of the long horizon equity premium based on semiparametric regressions," Economics Letters, Elsevier, volume 224, issue C, DOI: 10.1016/j.econlet.2023.111033.
• Ardakani, Omid M., 2023, "Capturing information in extreme events," Economics Letters, Elsevier, volume 231, issue C, DOI: 10.1016/j.econlet.2023.111301.
• Gribisch, Bastian & Hartkopf, Jan Patrick, 2023, "Modeling realized covariance measures with heterogeneous liquidity: A generalized matrix-variate Wishart state-space model," Journal of Econometrics, Elsevier, volume 235, issue 1, pages 43-64, DOI: 10.1016/j.jeconom.2022.01.007.
• Abadir, Karim M. & Luati, Alessandra & Paruolo, Paolo, 2023, "GARCH density and functional forecasts," Journal of Econometrics, Elsevier, volume 235, issue 2, pages 470-483, DOI: 10.1016/j.jeconom.2022.04.010.
• Kole, Erik & van Dijk, Dick, 2023, "Moments, shocks and spillovers in Markov-switching VAR models," Journal of Econometrics, Elsevier, volume 236, issue 2, DOI: 10.1016/j.jeconom.2023.105474.
• Andersen, Torben G. & Li, Yingying & Todorov, Viktor & Zhou, Bo, 2023, "Volatility measurement with pockets of extreme return persistence," Journal of Econometrics, Elsevier, volume 237, issue 2, DOI: 10.1016/j.jeconom.2020.11.005.
• Odendahl, Florens & Rossi, Barbara & Sekhposyan, Tatevik, 2023, "Evaluating forecast performance with state dependence," Journal of Econometrics, Elsevier, volume 237, issue 2, DOI: 10.1016/j.jeconom.2021.07.015.
• Berrisch, Jonathan & Ziel, Florian, 2023, "CRPS learning," Journal of Econometrics, Elsevier, volume 237, issue 2, DOI: 10.1016/j.jeconom.2021.11.008.
• Demetrescu, Matei & Georgiev, Iliyan & Rodrigues, Paulo M.M. & Taylor, A.M. Robert, 2023, "Extensions to IVX methods of inference for return predictability," Journal of Econometrics, Elsevier, volume 237, issue 2, DOI: 10.1016/j.jeconom.2022.02.007.
• Demetrescu, Matei & Rodrigues, Paulo M.M. & Taylor, A.M. Robert, 2023, "Transformed regression-based long-horizon predictability tests," Journal of Econometrics, Elsevier, volume 237, issue 2, DOI: 10.1016/j.jeconom.2022.06.006.
• Cheng, Mingmian & Liao, Yuan & Yang, Xiye, 2023, "Uniform predictive inference for factor models with instrumental and idiosyncratic betas," Journal of Econometrics, Elsevier, volume 237, issue 2, DOI: 10.1016/j.jeconom.2022.11.007.
• Bakalli, Gaetan & Guerrier, Stéphane & Scaillet, Olivier, 2023, "A penalized two-pass regression to predict stock returns with time-varying risk premia," Journal of Econometrics, Elsevier, volume 237, issue 2, DOI: 10.1016/j.jeconom.2022.12.004.
• Huang, Dashan & Jiang, Fuwei & Li, Kunpeng & Tong, Guoshi & Zhou, Guofu, 2023, "Are bond returns predictable with real-time macro data?," Journal of Econometrics, Elsevier, volume 237, issue 2, DOI: 10.1016/j.jeconom.2022.09.008.
• Umlandt, Dennis, 2023, "Score-driven asset pricing: Predicting time-varying risk premia based on cross-sectional model performance," Journal of Econometrics, Elsevier, volume 237, issue 2, DOI: 10.1016/j.jeconom.2023.05.007.
• Hallin, Marc & Trucíos, Carlos, 2023, "Forecasting value-at-risk and expected shortfall in large portfolios: A general dynamic factor model approach," Econometrics and Statistics, Elsevier, volume 27, issue C, pages 1-15, DOI: 10.1016/j.ecosta.2021.04.006.
• Li, Zhiyong & Li, Aimin & Bellotti, Anthony & Yao, Xiao, 2023, "The profitability of online loans: A competing risks analysis on default and prepayment," European Journal of Operational Research, Elsevier, volume 306, issue 2, pages 968-985, DOI: 10.1016/j.ejor.2022.08.013.
• Wasiuzzaman, Shaista & Muhd Azwan, Ayu Nadhirah & Hj Nordin, Aina Nazurah, 2023, "Analysis of the performance of Islamic gold-backed cryptocurrencies during the bear market of 2020," Emerging Markets Review, Elsevier, volume 54, issue C, DOI: 10.1016/j.ememar.2022.100920.
• Stoupos, Nikolaos & Nikas, Christos & Kiohos, Apostolos, 2023, "Turkey: From a thriving economic past towards a rugged future? - An empirical analysis on the Turkish financial markets," Emerging Markets Review, Elsevier, volume 54, issue C, DOI: 10.1016/j.ememar.2022.100992.
• Hanauer, Matthias X. & Kalsbach, Tobias, 2023, "Machine learning and the cross-section of emerging market stock returns," Emerging Markets Review, Elsevier, volume 55, issue C, DOI: 10.1016/j.ememar.2023.101022.
• Bu, Ruijun & Hizmeri, Rodrigo & Izzeldin, Marwan & Murphy, Anthony & Tsionas, Mike, 2023, "The contribution of jump signs and activity to forecasting stock price volatility," Journal of Empirical Finance, Elsevier, volume 70, issue C, pages 144-164, DOI: 10.1016/j.jempfin.2022.12.001.
• Wang, Yunqi & Zhou, Ti, 2023, "Out-of-sample equity premium prediction: The role of option-implied constraints," Journal of Empirical Finance, Elsevier, volume 70, issue C, pages 199-226, DOI: 10.1016/j.jempfin.2022.12.004.
• Han, Seung-Oh & Huh, Sahn-Wook & Park, Jeayoung, 2023, "Detecting jumps amidst prevalent zero returns: Evidence from the U.S. Treasury securities," Journal of Empirical Finance, Elsevier, volume 70, issue C, pages 276-307, DOI: 10.1016/j.jempfin.2022.12.006.
• Nonejad, Nima, 2023, "Conditional out-of-sample predictability of aggregate equity returns and aggregate equity return volatility using economic variables," Journal of Empirical Finance, Elsevier, volume 70, issue C, pages 91-122, DOI: 10.1016/j.jempfin.2022.11.009.
• Ferrer Fernández, María & Henry, Ólan & Pybis, Sam & Stamatogiannis, Michalis P., 2023, "Can we forecast better in periods of low uncertainty? The role of technical indicators," Journal of Empirical Finance, Elsevier, volume 71, issue C, pages 1-12, DOI: 10.1016/j.jempfin.2022.12.014.
• Chan, Ka Kei & Kolokolova, Olga & Lin, Ming-Tsung & Poon, Ser-Huang, 2023, "Price convergence between credit default swap and put option: New evidence," Journal of Empirical Finance, Elsevier, volume 72, issue C, pages 188-213, DOI: 10.1016/j.jempfin.2023.03.008.
• Brennan, M.J. & Taylor, Alex P., 2023, "Expected returns and risk in the stock market," Journal of Empirical Finance, Elsevier, volume 72, issue C, pages 276-300, DOI: 10.1016/j.jempfin.2023.03.002.
• Lee, Cheol Woo & Kang, Kyu Ho, 2023, "Estimating and testing skewness in a stochastic volatility model," Journal of Empirical Finance, Elsevier, volume 72, issue C, pages 445-467, DOI: 10.1016/j.jempfin.2023.04.009.
• Liu, Zhenya & Lu, Shanglin & Li, Bo & Wang, Shixuan, 2023, "Time series momentum and reversal: Intraday information from realized semivariance," Journal of Empirical Finance, Elsevier, volume 72, issue C, pages 54-77, DOI: 10.1016/j.jempfin.2023.03.001.
• Tong, Chen & Huang, Zhuo & Wang, Tianyi & Zhang, Cong, 2023, "The effects of economic uncertainty on financial volatility: A comprehensive investigation," Journal of Empirical Finance, Elsevier, volume 73, issue C, pages 369-389, DOI: 10.1016/j.jempfin.2023.08.004.
• Wang, Keli & Liu, Xiaoquan & Ye, Wuyi, 2023, "Intraday VaR: A copula-based approach," Journal of Empirical Finance, Elsevier, volume 74, issue C, DOI: 10.1016/j.jempfin.2023.101419.
• Souropanis, Ioannis & Vivian, Andrew, 2023, "Forecasting realized volatility with wavelet decomposition," Journal of Empirical Finance, Elsevier, volume 74, issue C, DOI: 10.1016/j.jempfin.2023.101432.
• Rad, Hossein & Low, Rand Kwong Yew & Miffre, Joëlle & Faff, Robert, 2023, "The commodity risk premium and neural networks," Journal of Empirical Finance, Elsevier, volume 74, issue C, DOI: 10.1016/j.jempfin.2023.101433.
• Qu, Hui & Li, Guo, 2023, "Multi-perspective investor attention and oil futures volatility forecasting," Energy Economics, Elsevier, volume 119, issue C, DOI: 10.1016/j.eneco.2023.106531.
• Gong, Xue & Ye, Xin & Zhang, Weiguo & Zhang, Yue, 2023, "Predicting energy futures high-frequency volatility using technical indicators: The role of interaction," Energy Economics, Elsevier, volume 119, issue C, DOI: 10.1016/j.eneco.2023.106533.
• Li, Jingpeng & Umar, Muhammad & Huo, Jiale, 2023, "The spillover effect between Chinese crude oil futures market and Chinese green energy stock market," Energy Economics, Elsevier, volume 119, issue C, DOI: 10.1016/j.eneco.2023.106568.
• Sohag, Kazi & Hassan, M. Kabir & Bakhteyev, Stepan & Mariev, Oleg, 2023, "Do green and dirty investments hedge each other?," Energy Economics, Elsevier, volume 120, issue C, DOI: 10.1016/j.eneco.2023.106573.
• Abdollahi, Hooman, 2023, "Oil price volatility and new evidence from news and Twitter," Energy Economics, Elsevier, volume 122, issue C, DOI: 10.1016/j.eneco.2023.106711.
• Akhtaruzzaman, Md & Banerjee, Ameet Kumar & Boubaker, Sabri & Moussa, Faten, 2023, "Does green improve portfolio optimisation?," Energy Economics, Elsevier, volume 124, issue C, DOI: 10.1016/j.eneco.2023.106831.
• Tian, Guangning & Peng, Yuchao & Meng, Yuhao, 2023, "Forecasting crude oil prices in the COVID-19 era: Can machine learn better?," Energy Economics, Elsevier, volume 125, issue C, DOI: 10.1016/j.eneco.2023.106788.
• Thakur, Jagruti & Hesamzadeh, Mohammad Reza & Date, Paresh & Bunn, Derek, 2023, "Pricing and hedging wind power prediction risk with binary option contracts," Energy Economics, Elsevier, volume 126, issue C, DOI: 10.1016/j.eneco.2023.106960.
• Nonejad, Nima, 2023, "Modeling the out-of-sample predictive relationship between equity premium, returns on the price of crude oil and economic policy uncertainty using multivariate time-varying dimension models," Energy Economics, Elsevier, volume 126, issue C, DOI: 10.1016/j.eneco.2023.106964.
• Esparcia, Carlos & Diaz, Antonio & Alonso, Daniel, 2023, "How important is green awareness in energy investment decisions? An environmentally-based rebalancing portfolio study," Energy Economics, Elsevier, volume 128, issue C, DOI: 10.1016/j.eneco.2023.107174.
• Zhang, Yaojie & He, Mengxi & Wen, Danyan & Wang, Yudong, 2023, "Forecasting crude oil price returns: Can nonlinearity help?," Energy, Elsevier, volume 262, issue PB, DOI: 10.1016/j.energy.2022.125589.
• Nguyen, Quyen & Diaz-Rainey, Ivan & Kuruppuarachchi, Duminda & McCarten, Matthew & Tan, Eric K.M., 2023, "Climate transition risk in U.S. loan portfolios: Are all banks the same?," International Review of Financial Analysis, Elsevier, volume 85, issue C, DOI: 10.1016/j.irfa.2022.102401.
• Nguyen, Quyen & Diaz-Rainey, Ivan & Kuruppuarachchi, Duminda, 2023, "In search of climate distress risk," International Review of Financial Analysis, Elsevier, volume 85, issue C, DOI: 10.1016/j.irfa.2022.102444.
• Liu, Jinjing, 2023, "A novel downside beta and expected stock returns," International Review of Financial Analysis, Elsevier, volume 85, issue C, DOI: 10.1016/j.irfa.2022.102455.
• Li, Zhao-Chen & Xie, Chi & Zeng, Zhi-Jian & Wang, Gang-Jin & Zhang, Ting, 2023, "Forecasting global stock market volatilities in an uncertain world," International Review of Financial Analysis, Elsevier, volume 85, issue C, DOI: 10.1016/j.irfa.2022.102463.
• Zhang, Ning & Su, Xiaoman & Qi, Shuyuan, 2023, "An empirical investigation of multiperiod tail risk forecasting models," International Review of Financial Analysis, Elsevier, volume 86, issue C, DOI: 10.1016/j.irfa.2023.102498.
• Abakah, Emmanuel Joel Aikins & Nasreen, Samia & Tiwari, Aviral Kumar & Lee, Chien-Chiang, 2023, "U.S. leveraged loan and debt markets: Implications for optimal portfolio and hedging," International Review of Financial Analysis, Elsevier, volume 87, issue C, DOI: 10.1016/j.irfa.2023.102514.
• Ghosh, Indranil & Alfaro-Cortés, Esteban & Gámez, Matías & García-Rubio, Noelia, 2023, "Prediction and interpretation of daily NFT and DeFi prices dynamics: Inspection through ensemble machine learning & XAI," International Review of Financial Analysis, Elsevier, volume 87, issue C, DOI: 10.1016/j.irfa.2023.102558.
• Zaevski, Tsvetelin S. & Nedeltchev, Dragomir C., 2023, "From BASEL III to BASEL IV and beyond: Expected shortfall and expectile risk measures," International Review of Financial Analysis, Elsevier, volume 87, issue C, DOI: 10.1016/j.irfa.2023.102645.
• Ammari, Aymen & Chebbi, Kaouther & Ben Arfa, Nouha, 2023, "How does the COVID-19 pandemic shape the relationship between Twitter sentiment and stock liquidity of US firms?," International Review of Financial Analysis, Elsevier, volume 88, issue C, DOI: 10.1016/j.irfa.2023.102633.
• Bouazizi, Tarek & Galariotis, Emilios & Guesmi, Khaled & Makrychoriti, Panagiota, 2023, "Investigating the nature of interaction between crypto-currency and commodity markets," International Review of Financial Analysis, Elsevier, volume 88, issue C, DOI: 10.1016/j.irfa.2023.102690.
• Zhang, Zehua & Zhao, Ran, 2023, "Good volatility, bad volatility, and the cross section of cryptocurrency returns," International Review of Financial Analysis, Elsevier, volume 89, issue C, DOI: 10.1016/j.irfa.2023.102712.
• Gao, Jun & Gao, Xiang & Gu, Chen, 2023, "Forecasting European stock volatility: The role of the UK," International Review of Financial Analysis, Elsevier, volume 89, issue C, DOI: 10.1016/j.irfa.2023.102728.
• Gourdel, Régis & Sydow, Matthias, 2023, "Non-banks contagion and the uneven mitigation of climate risk," International Review of Financial Analysis, Elsevier, volume 89, issue C, DOI: 10.1016/j.irfa.2023.102739.
• Basse, Tobias & Desmyter, Steven & Saft, Danilo & Wegener, Christoph, 2023, "Leading indicators for the US housing market: New empirical evidence and thoughts about implications for risk managers and ESG investors," International Review of Financial Analysis, Elsevier, volume 89, issue C, DOI: 10.1016/j.irfa.2023.102765.
• Zhao, Qi & Xu, Weijun & Ji, Yucheng, 2023, "Predicting financial distress of Chinese listed companies using machine learning: To what extent does textual disclosure matter?," International Review of Financial Analysis, Elsevier, volume 89, issue C, DOI: 10.1016/j.irfa.2023.102770.
• Proelss, Juliane & Sévigny, Stéphane & Schweizer, Denis, 2023, "GameFi: The perfect symbiosis of blockchain, tokens, DeFi, and NFTs?," International Review of Financial Analysis, Elsevier, volume 90, issue C, DOI: 10.1016/j.irfa.2023.102916.
• Procasky, William J. & Yin, Anwen, 2023, "The impact of COVID-19 on the relative market efficiency and forecasting ability of credit derivative and equity markets," International Review of Financial Analysis, Elsevier, volume 90, issue C, DOI: 10.1016/j.irfa.2023.102926.
• Zakamulin, Valeriy & Giner, Javier, 2023, "Optimal trend-following with transaction costs," International Review of Financial Analysis, Elsevier, volume 90, issue C, DOI: 10.1016/j.irfa.2023.102928.
• Yu, Jize & Zhang, Li & Peng, Lijuan & Wu, Rui, 2023, "Which component of air quality index drives stock price volatility in China: a decomposition-based forecasting method," Finance Research Letters, Elsevier, volume 51, issue C, DOI: 10.1016/j.frl.2022.103406.
• Ghosh, Indranil & Alfaro-Cortés, Esteban & Gámez, Matías & García, Noelia, 2023, "Do travel uncertainty and invasion rhetoric spur Metaverse financial asset? – Gauging the role of media influence," Finance Research Letters, Elsevier, volume 51, issue C, DOI: 10.1016/j.frl.2022.103434.
• Yamani, Ehab, 2023, "The informational role of fund flow in the profitable predictability of mutual funds," Finance Research Letters, Elsevier, volume 51, issue C, DOI: 10.1016/j.frl.2022.103445.
• Li, Xingyi & Gan, Kai & Zhou, Qi, 2023, "Dynamic volatility connectedness among cryptocurrencies and China's financial assets in standard times and during the COVID-19 pandemic," Finance Research Letters, Elsevier, volume 51, issue C, DOI: 10.1016/j.frl.2022.103476.
• Díaz-Mendoza, Ana Carmen & Pardo, Ángel, 2023, "Water and traditional asset classes," Finance Research Letters, Elsevier, volume 52, issue C, DOI: 10.1016/j.frl.2022.103394.
• Berrisch, Jonathan & Pappert, Sven & Ziel, Florian & Arsova, Antonia, 2023, "Modeling volatility and dependence of European carbon and energy prices," Finance Research Letters, Elsevier, volume 52, issue C, DOI: 10.1016/j.frl.2022.103503.
• Xie, Yutang & Cao, Yujia & Li, Xiaotao, 2023, "The importance of trade policy uncertainty to energy consumption in a changing world," Finance Research Letters, Elsevier, volume 52, issue C, DOI: 10.1016/j.frl.2022.103566.
• Bouteska, Ahmed & Büyükoğlu, Burak & Ekşi, Ibrahim Halil, 2023, "How effective are banking regulations on banking performance and risk? Evidence from selected European countries," Finance Research Letters, Elsevier, volume 53, issue C, DOI: 10.1016/j.frl.2022.103604.
• Soria, Jorge & Moya, Jorge & Mohazab, Amin, 2023, "Optimal mining in proof-of-work blockchain protocols," Finance Research Letters, Elsevier, volume 53, issue C, DOI: 10.1016/j.frl.2022.103610.
• García, Javier Sánchez & Rambaud, Salvador Cruz, 2023, "Macrofinancial determinants of volatility transmission in a network of European sovereign debt markets," Finance Research Letters, Elsevier, volume 53, issue C, DOI: 10.1016/j.frl.2023.103635.
• Cheng, Tingting & Jiang, Shan & Zhao, Albert Bo & Jia, Zhimin, 2023, "Complete subset averaging methods in corporate bond return prediction," Finance Research Letters, Elsevier, volume 54, issue C, DOI: 10.1016/j.frl.2023.103727.
• Wilson, Linus, 2023, "Profitable timing of the stock market with the senior loan officer survey," Finance Research Letters, Elsevier, volume 54, issue C, DOI: 10.1016/j.frl.2023.103733.
• Yang, Xinyao & Liu, Zhaoyi & Li, Tao, 2023, "Individual investors’ dividend tax reform and stock price crash risk," Finance Research Letters, Elsevier, volume 54, issue C, DOI: 10.1016/j.frl.2023.103746.
• Kiss, Tamás & Kladívko, Kamil & Silfverberg, Oliwer & Österholm, Pär, 2023, "Market participants or the random walk – who forecasts better? Evidence from micro-level survey data," Finance Research Letters, Elsevier, volume 54, issue C, DOI: 10.1016/j.frl.2023.103752.
• Chen, Qihao & Huang, Zhuo & Liang, Fang, 2023, "Measuring systemic risk with high-frequency data: A realized GARCH approach," Finance Research Letters, Elsevier, volume 54, issue C, DOI: 10.1016/j.frl.2023.103753.
• Berger, Theo, 2023, "Explainable artificial intelligence and economic panel data: A study on volatility spillover along the supply chains," Finance Research Letters, Elsevier, volume 54, issue C, DOI: 10.1016/j.frl.2023.103757.
• Ham, Hyuna & Ryu, Doojin & Webb, Robert I. & Yu, Jinyoung, 2023, "How do investors react to overnight returns? Evidence from Korea," Finance Research Letters, Elsevier, volume 54, issue C, DOI: 10.1016/j.frl.2023.103779.
• Mueller, Lukas & Bartel, Merlin & Schiereck, Dirk, 2023, "Europe's gone “right” – A comparative study of stock market reactions to populist success in Sweden and Italy," Finance Research Letters, Elsevier, volume 55, issue PA, DOI: 10.1016/j.frl.2023.103829.
• Kawakami, Tabito, 2023, "Quantile prediction for Bitcoin returns using financial assets’ realized measures," Finance Research Letters, Elsevier, volume 55, issue PA, DOI: 10.1016/j.frl.2023.103843.
• Gao, Shang & Zhang, Zhikai & Wang, Yudong & Zhang, Yaojie, 2023, "Forecasting stock market volatility: The sum of the parts is more than the whole," Finance Research Letters, Elsevier, volume 55, issue PA, DOI: 10.1016/j.frl.2023.103849.
• Huynh, Nhan & Phan, Hoa, 2023, "Emotions in the crypto market: Do photos really speak?," Finance Research Letters, Elsevier, volume 55, issue PB, DOI: 10.1016/j.frl.2023.103945.
• Chang, Danting & Li, Feng, 2023, "Uncovering the information content in abnormal institutional visits," Finance Research Letters, Elsevier, volume 55, issue PB, DOI: 10.1016/j.frl.2023.103988.
• Wang, Cindy S.H. & Fan, Rui & Xie, Yiqiang, 2023, "Market systemic risk, predictability and macroeconomics news," Finance Research Letters, Elsevier, volume 56, issue C, DOI: 10.1016/j.frl.2023.104102.
• Wu, Xinyu & Zhao, An & Cheng, Tengfei, 2023, "A Real-Time GARCH-MIDAS model," Finance Research Letters, Elsevier, volume 56, issue C, DOI: 10.1016/j.frl.2023.104103.
• Hartkopf, Jan Patrick & Reh, Laura, 2023, "Challenging golden standards in EWMA smoothing parameter calibration based on realized covariance measures," Finance Research Letters, Elsevier, volume 56, issue C, DOI: 10.1016/j.frl.2023.104129.
• Verner, Robert & Tkáč, Michal, 2023, "On the predictability of bonds," Finance Research Letters, Elsevier, volume 57, issue C, DOI: 10.1016/j.frl.2023.104181.
• Gao, Wei & Ju, Ming & Yang, Tongyang, 2023, "Severe weather and peer-to-peer farmers’ loan default predictions: Evidence from machine learning analysis," Finance Research Letters, Elsevier, volume 58, issue PA, DOI: 10.1016/j.frl.2023.104287.
• Neururer, Thaddeus, 2023, "Variance risk premiums and aging firms," Finance Research Letters, Elsevier, volume 58, issue PA, DOI: 10.1016/j.frl.2023.104312.
• He, Mengxi & Shen, Lihua & Zhang, Yaojie & Zhang, Yi, 2023, "Predicting cryptocurrency returns for real-world investments: A daily updated and accessible predictor," Finance Research Letters, Elsevier, volume 58, issue PA, DOI: 10.1016/j.frl.2023.104406.
• Braun, Declan & Han, Yue & Wang, Heng Emily, 2023, "The application of feed forward neural networks to merger arbitrage: A return-based analysis," Finance Research Letters, Elsevier, volume 58, issue PB, DOI: 10.1016/j.frl.2023.104391.
• Zhang, Zhihao, 2023, "Are climate risks helpful for understanding inflation in BRICS countries?," Finance Research Letters, Elsevier, volume 58, issue PB, DOI: 10.1016/j.frl.2023.104441.
• Luo, Tao & Zhang, Lixia & Sun, Huaping & Bai, Jiancheng, 2023, "Enhancing exchange rate volatility prediction accuracy: Assessing the influence of different indices on the USD/CNY exchange rate," Finance Research Letters, Elsevier, volume 58, issue PB, DOI: 10.1016/j.frl.2023.104483.
• Shu, Qi & Xiong, Heng & Jiang, Wenjun & Mamon, Rogemar, 2023, "A novel perspective on forecasting non-ferrous metals’ volatility: Integrating deep learning techniques with econometric models," Finance Research Letters, Elsevier, volume 58, issue PC, DOI: 10.1016/j.frl.2023.104482.
• Zhao, Chencheng & Yuan, Xianghui & Long, Jun & Jin, Liwei & Guan, Bowen, 2023, "Financial indicators analysis using machine learning: Evidence from Chinese stock market," Finance Research Letters, Elsevier, volume 58, issue PD, DOI: 10.1016/j.frl.2023.104590.
• Zhang, Junyu & Ruan, Xinfeng & Zhang, Jin E., 2023, "Do short-term market swings improve realized volatility forecasts?," Finance Research Letters, Elsevier, volume 58, issue PD, DOI: 10.1016/j.frl.2023.104629.
• Díaz, Antonio & Esparcia, Carlos & Huélamo, Diego, 2023, "Unveiling the diversification capabilities of carbon markets in NFT portfolios," Finance Research Letters, Elsevier, volume 58, issue PD, DOI: 10.1016/j.frl.2023.104632.
• Faias, José Afonso, 2023, "Predicting the equity risk premium using the smooth cross-sectional tail risk: The importance of correlation," Journal of Financial Markets, Elsevier, volume 63, issue C, DOI: 10.1016/j.finmar.2022.100769.
• Alexandridis, Antonios K. & Apergis, Iraklis & Panopoulou, Ekaterini & Voukelatos, Nikolaos, 2023, "Equity premium prediction: The role of information from the options market," Journal of Financial Markets, Elsevier, volume 64, issue C, DOI: 10.1016/j.finmar.2022.100801.
• Angelidis, Timotheos & Tessaromatis, Nikolaos, 2023, "The disappearing profitability of volatility-managed equity factors," Journal of Financial Markets, Elsevier, volume 65, issue C, DOI: 10.1016/j.finmar.2023.100857.
• Bonato, Matteo & Cepni, Oguzhan & Gupta, Rangan & Pierdzioch, Christian, 2023, "Climate risks and state-level stock market realized volatility," Journal of Financial Markets, Elsevier, volume 66, issue C, DOI: 10.1016/j.finmar.2023.100854.
• Dichtl, Hubert & Drobetz, Wolfgang & Otto, Tizian, 2023, "Forecasting Stock Market Crashes via Machine Learning," Journal of Financial Stability, Elsevier, volume 65, issue C, DOI: 10.1016/j.jfs.2022.101099.
• Zeng, Hui & Marshall, Ben R. & Nguyen, Nhut H. & Visaltanachoti, Nuttawat, 2023, "Technical indicators and cross-sectional expected returns," Global Finance Journal, Elsevier, volume 56, issue C, DOI: 10.1016/j.gfj.2022.100781.
• Chun, Dohyun & Cho, Hoon & Ryu, Doojin, 2023, "Discovering the drivers of stock market volatility in a data-rich world," Journal of International Financial Markets, Institutions and Money, Elsevier, volume 82, issue C, DOI: 10.1016/j.intfin.2022.101684.
• Dai, Yingtong & Harris, Richard D.F., 2023, "Average tail risk and aggregate stock returns," Journal of International Financial Markets, Institutions and Money, Elsevier, volume 82, issue C, DOI: 10.1016/j.intfin.2022.101699.
• Hertrich, Daniel, 2023, "Carry and conditional value at risk trend: Capturing the short-, intermediate-, and long-term trends of left-tail risk forecasts," Journal of International Financial Markets, Institutions and Money, Elsevier, volume 82, issue C, DOI: 10.1016/j.intfin.2022.101710.
• Grobys, Klaus, 2023, "A multifractal model of asset (in)variances," Journal of International Financial Markets, Institutions and Money, Elsevier, volume 85, issue C, DOI: 10.1016/j.intfin.2023.101767.
• Esparcia, Carlos & Escribano, Ana & Jareño, Francisco, 2023, "Did cryptomarket chaos unleash Silvergate's bankruptcy? investigating the high-frequency volatility and connectedness behind the collapse," Journal of International Financial Markets, Institutions and Money, Elsevier, volume 89, issue C, DOI: 10.1016/j.intfin.2023.101851.
• Fortin, Alain-Philippe & Simonato, Jean-Guy & Dionne, Georges, 2023, "Forecasting expected shortfall: Should we use a multivariate model for stock market factors?," International Journal of Forecasting, Elsevier, volume 39, issue 1, pages 314-331, DOI: 10.1016/j.ijforecast.2021.11.010.
• Haase, Felix & Neuenkirch, Matthias, 2023, "Predictability of bull and bear markets: A new look at forecasting stock market regimes (and returns) in the US," International Journal of Forecasting, Elsevier, volume 39, issue 2, pages 587-605, DOI: 10.1016/j.ijforecast.2022.01.004.
• Bauwens, Luc & Xu, Yongdeng, 2023, "DCC- and DECO-HEAVY: Multivariate GARCH models based on realized variances and correlations," International Journal of Forecasting, Elsevier, volume 39, issue 2, pages 938-955, DOI: 10.1016/j.ijforecast.2022.03.005.
• Wiersema, Garbrand & Kleinnijenhuis, Alissa M. & Wetzer, Thom & Farmer, J. Doyne, 2023, "Scenario-free analysis of financial stability with interacting contagion channels," Journal of Banking & Finance, Elsevier, volume 146, issue C, DOI: 10.1016/j.jbankfin.2022.106684.
• Jacobs, Kris & Li, Bingxin, 2023, "Option Returns, Risk Premiums, and Demand Pressure in Energy Markets," Journal of Banking & Finance, Elsevier, volume 146, issue C, DOI: 10.1016/j.jbankfin.2022.106687.
• Guo, Laite, 2023, "Two faces of the size effect," Journal of Banking & Finance, Elsevier, volume 146, issue C, DOI: 10.1016/j.jbankfin.2022.106708.
• Caglayan, Mustafa O. & Lawrence, Edward & Reyes-Peña, Robinson, 2023, "Hot potatoes: Underpricing of stocks following extreme negative returns," Journal of Banking & Finance, Elsevier, volume 149, issue C, DOI: 10.1016/j.jbankfin.2023.106757.
• Krivorotov, George, 2023, "Machine learning-based profit modeling for credit card underwriting - implications for credit risk," Journal of Banking & Finance, Elsevier, volume 149, issue C, DOI: 10.1016/j.jbankfin.2023.106785.
• El Ghoul, Sadok & Guedhami, Omrane & Wei, Zuobao & Zhu, Yicheng, 2023, "Does public corruption affect analyst forecast quality?," Journal of Banking & Finance, Elsevier, volume 154, issue C, DOI: 10.1016/j.jbankfin.2023.106860.
• Asgharian, Hossein & Christiansen, Charlotte & Hou, Ai Jun, 2023, "The effect of uncertainty on stock market volatility and correlation," Journal of Banking & Finance, Elsevier, volume 154, issue C, DOI: 10.1016/j.jbankfin.2023.106929.
• Elkamhi, Redouane & Jo, Chanik, 2023, "Asset holders’ consumption risk and tests of conditional CCAPM," Journal of Financial Economics, Elsevier, volume 148, issue 3, pages 220-244, DOI: 10.1016/j.jfineco.2023.04.002.
• Kaniel, Ron & Lin, Zihan & Pelger, Markus & Van Nieuwerburgh, Stijn, 2023, "Machine-learning the skill of mutual fund managers," Journal of Financial Economics, Elsevier, volume 150, issue 1, pages 94-138, DOI: 10.1016/j.jfineco.2023.07.004.
• Bandi, Federico M. & Bretscher, Lorenzo & Tamoni, Andrea, 2023, "Return predictability with endogenous growth," Journal of Financial Economics, Elsevier, volume 150, issue 3, DOI: 10.1016/j.jfineco.2023.103724.
• DeMiguel, Victor & Gil-Bazo, Javier & Nogales, Francisco J. & Santos, André A.P., 2023, "Machine learning and fund characteristics help to select mutual funds with positive alpha," Journal of Financial Economics, Elsevier, volume 150, issue 3, DOI: 10.1016/j.jfineco.2023.103737.
• Christensen, Jens H.E. & Spiegel, Mark M., 2023, "Central bank credibility during COVID-19: Evidence from Japan," Journal of International Money and Finance, Elsevier, volume 131, issue C, DOI: 10.1016/j.jimonfin.2022.102788.
• Boucher, C. & Jasinski, A. & Tokpavi, S., 2023, "Conditional mean reversion of financial ratios and the predictability of returns," Journal of International Money and Finance, Elsevier, volume 137, issue C, DOI: 10.1016/j.jimonfin.2023.102907.
• Cotter, John & Eyiah-Donkor, Emmanuel & Potì, Valerio, 2023, "Commodity futures return predictability and intertemporal asset pricing," Journal of Commodity Markets, Elsevier, volume 31, issue C, DOI: 10.1016/j.jcomm.2022.100289.
• Rice, Gregory & Wirjanto, Tony & Zhao, Yuqian, 2023, "Exploring volatility of crude oil intraday return curves: A functional GARCH-X model," Journal of Commodity Markets, Elsevier, volume 32, issue C, DOI: 10.1016/j.jcomm.2023.100361.
• Orlowski, Lucjan T., 2023, "How susceptible is the European financial stability to economic policy uncertainty?," Journal of Policy Modeling, Elsevier, volume 45, issue 4, pages 864-875, DOI: 10.1016/j.jpolmod.2023.07.011.
• Aloui, Riadh & Ben Jabeur, Sami & Rezgui, Hichem & Ben Arfi, Wissal, 2023, "Geopolitical risk and commodity future returns: Fresh insights from dynamic copula conditional value-at-risk approach," Resources Policy, Elsevier, volume 85, issue PB, DOI: 10.1016/j.resourpol.2023.103873.
• Hardy, Nicolás & Ferreira, Tiago & Quinteros, Maria J. & Magner, Nicolás S., 2023, "“Watch your tone!”: Forecasting mining industry commodity prices with financial report tone," Resources Policy, Elsevier, volume 86, issue PA, DOI: 10.1016/j.resourpol.2023.104251.
• Teplova, Tamara & Sokolova, Tatiana & Kissa, David, 2023, "Revealing stock liquidity determinants by means of explainable AI: The role of ESG before and during the COVID-19 pandemic," Resources Policy, Elsevier, volume 86, issue PB, DOI: 10.1016/j.resourpol.2023.104253.
• Liu, Yang, 2023, "Government debt and risk premia," Journal of Monetary Economics, Elsevier, volume 136, issue C, pages 18-34, DOI: 10.1016/j.jmoneco.2023.01.009.
• Li, Ang & Liu, Mark & Sheather, Simon, 2023, "Predicting stock splits using ensemble machine learning and SMOTE oversampling," Pacific-Basin Finance Journal, Elsevier, volume 78, issue C, DOI: 10.1016/j.pacfin.2023.101948.
• Xu, Yongan & Liang, Chao & Wang, Jianqiong, 2023, "Financial stress and returns predictability: Fresh evidence from China," Pacific-Basin Finance Journal, Elsevier, volume 78, issue C, DOI: 10.1016/j.pacfin.2023.101980.
• Chen, Zhiyu & Xu, Yun & Wang, Yu, 2023, "Can convertible bond trading predict stock returns? Evidence from China," Pacific-Basin Finance Journal, Elsevier, volume 79, issue C, DOI: 10.1016/j.pacfin.2023.102026.
• Lu, Yueliang (Jacques) & Tian, Weidong, 2023, "An on-line machine learning return prediction," Pacific-Basin Finance Journal, Elsevier, volume 79, issue C, DOI: 10.1016/j.pacfin.2023.102049.
• Limkriangkrai, Manapon & Chai, Daniel & Zheng, Gaoping, 2023, "Market intraday momentum: APAC evidence," Pacific-Basin Finance Journal, Elsevier, volume 80, issue C, DOI: 10.1016/j.pacfin.2023.102086.
• Guidolin, Massimo & Wang, Kai, 2023, "The empirical performance of option implied volatility surface-driven optimal portfolios," Physica A: Statistical Mechanics and its Applications, Elsevier, volume 618, issue C, DOI: 10.1016/j.physa.2023.128496.
• Serna, Gregorio, 2023, "On the predictive ability of conditional market skewness," The Quarterly Review of Economics and Finance, Elsevier, volume 91, issue C, pages 186-191, DOI: 10.1016/j.qref.2022.11.001.
• Bouteska, Ahmed & Sharif, Taimur & Abedin, Mohammad Zoynul, 2023, "Volatility spillovers and other dynamics between cryptocurrencies and the energy and bond markets," The Quarterly Review of Economics and Finance, Elsevier, volume 92, issue C, pages 1-13, DOI: 10.1016/j.qref.2023.07.008.
• Gould, John & Yang, Joey W. & Singh, Ranjodh & Yeo, Ben, 2023, "The seasonality of lottery-like stock returns," International Review of Economics & Finance, Elsevier, volume 83, issue C, pages 383-400, DOI: 10.1016/j.iref.2022.09.004.
• Hong, Yanran & Yu, Jize & Su, Yuquan & Wang, Lu, 2023, "Southern oscillation: Great value of its trends for forecasting crude oil spot price volatility," International Review of Economics & Finance, Elsevier, volume 84, issue C, pages 358-368, DOI: 10.1016/j.iref.2022.11.023.
• Chen, Zhonglu & Zhang, Li & Weng, Chen, 2023, "Does climate policy uncertainty affect Chinese stock market volatility?," International Review of Economics & Finance, Elsevier, volume 84, issue C, pages 369-381, DOI: 10.1016/j.iref.2022.11.030.
• Li, Zepei & Huang, Haizhen, 2023, "Challenges for volatility forecasts of US fossil energy spot markets during the COVID-19 crisis," International Review of Economics & Finance, Elsevier, volume 86, issue C, pages 31-45, DOI: 10.1016/j.iref.2023.02.004.
• Hoang, Lai T. & Baur, Dirk G., 2023, "Cryptocurrencies are not immune to coronavirus: Evidence from investor fear," International Review of Economics & Finance, Elsevier, volume 88, issue C, pages 1444-1463, DOI: 10.1016/j.iref.2023.06.018.
• Song, Yixuan & He, Mengxi & Wang, Yudong & Zhang, Yaojie, 2023, "Forecasting crude oil prices: A reduced-rank approach," International Review of Economics & Finance, Elsevier, volume 88, issue C, pages 698-711, DOI: 10.1016/j.iref.2023.07.001.
• Orte, Francisco & Mira, José & Sánchez, María Jesús & Solana, Pablo, 2023, "A random forest-based model for crypto asset forecasts in futures markets with out-of-sample prediction," Research in International Business and Finance, Elsevier, volume 64, issue C, DOI: 10.1016/j.ribaf.2022.101829.
• Zhang, Qun & Zhang, Peihui & Liu, Hao, 2023, "Does expected idiosyncratic skewness of firms' profit predict the cross-section of stock returns? Evidence from China," Research in International Business and Finance, Elsevier, volume 64, issue C, DOI: 10.1016/j.ribaf.2022.101839.
• Zhou, Yang & Xie, Chi & Wang, Gang-Jin & Zhu, You & Uddin, Gazi Salah, 2023, "Analysing and forecasting co-movement between innovative and traditional financial assets based on complex network and machine learning," Research in International Business and Finance, Elsevier, volume 64, issue C, DOI: 10.1016/j.ribaf.2022.101846.
• Li, Xiafei & Guo, Qiang & Liang, Chao & Umar, Muhammad, 2023, "Forecasting gold volatility with geopolitical risk indices," Research in International Business and Finance, Elsevier, volume 64, issue C, DOI: 10.1016/j.ribaf.2022.101857.
• Liu, Yujun & Li, Zhongfei & Nekhili, Ramzi & Sultan, Jahangir, 2023, "Forecasting cryptocurrency returns with machine learning," Research in International Business and Finance, Elsevier, volume 64, issue C, DOI: 10.1016/j.ribaf.2023.101905.
• González, Marta Ramos & Ureña, Antonio Partal & Fernández-Aguado, Pilar Gómez, 2023, "Forecasting for regulatory credit loss derived from the COVID-19 pandemic: A machine learning approach," Research in International Business and Finance, Elsevier, volume 64, issue C, DOI: 10.1016/j.ribaf.2023.101907.
• He, Mengxi & Wang, Yudong & Zeng, Qing & Zhang, Yaojie, 2023, "Forecasting aggregate stock market volatility with industry volatilities: The role of spillover index," Research in International Business and Finance, Elsevier, volume 65, issue C, DOI: 10.1016/j.ribaf.2023.101983.
• Mtiraoui, Amine & Boubaker, Heni & BelKacem, Lotfi, 2023, "A hybrid approach for forecasting bitcoin series," Research in International Business and Finance, Elsevier, volume 66, issue C, DOI: 10.1016/j.ribaf.2023.102011.
• Duan, Kun & Wang, Rui & Chen, Shun & Ge, Lei, 2023, "Exploring the predictability of attention mechanism with LSTM: Evidence from EU carbon futures prices," Research in International Business and Finance, Elsevier, volume 66, issue C, DOI: 10.1016/j.ribaf.2023.102020.
• Grudniewicz, Jan & Ślepaczuk, Robert, 2023, "Application of machine learning in algorithmic investment strategies on global stock markets," Research in International Business and Finance, Elsevier, volume 66, issue C, DOI: 10.1016/j.ribaf.2023.102052.
• Li, Zhao-Chen & Xie, Chi & Wang, Gang-Jin & Zhu, You & Long, Jian-You & Zhou, Yang, 2023, "Forecasting stock market volatility under parameter and model uncertainty," Research in International Business and Finance, Elsevier, volume 66, issue C, DOI: 10.1016/j.ribaf.2023.102084.
• Abakah, Emmanuel Joel Aikins & Tiwari, Aviral Kumar & Ghosh, Sudeshna & Doğan, Buhari, 2023, "Dynamic effect of Bitcoin, fintech and artificial intelligence stocks on eco-friendly assets, Islamic stocks and conventional financial markets: Another look using quantile-based approaches," Technological Forecasting and Social Change, Elsevier, volume 192, issue C, DOI: 10.1016/j.techfore.2023.122566.
• Gary Moore & Marc William Simpson, 2023, "Which sustainable growth rate is best at forecasting actual growth?," American Journal of Business, Emerald Group Publishing Limited, volume 38, issue 4, pages 173-192, June, DOI: 10.1108/AJB-12-2022-0196.
• Valeriia Baklanova & Aleksei Kurkin & Tamara Teplova, 2023, "Investor sentiment and the NFT hype index: to buy or not to buy?," China Finance Review International, Emerald Group Publishing Limited, volume 14, issue 3, pages 522-548, December, DOI: 10.1108/CFRI-06-2023-0175.
• Rim El Khoury & Walid Mensi & Muneer M. Alshater & Sanghoon Kang, 2023, "Extreme risk spillovers and hedging strategies between Indonesia sectorial stocks and commodity markets," International Journal of Emerging Markets, Emerald Group Publishing Limited, volume 20, issue 1, pages 428-467, April, DOI: 10.1108/IJOEM-11-2022-1721.
• Norzalina Ahmad & Hazrul Shahiri & Safwan Mohd Nor & Mukhriz Izraf Azman Aziz, 2023, "Connectedness analysis of price return index among Malaysian economic sectors," International Journal of Islamic and Middle Eastern Finance and Management, Emerald Group Publishing Limited, volume 16, issue 4, pages 856-872, February, DOI: 10.1108/IMEFM-11-2021-0454.
• Taufik Faturohman & David Christian, 2023, "Predictive Blend: Fundamental Indexing with Markowitz Mean Variance Portfolio in Indonesia Stock Exchange," International Symposia in Economic Theory and Econometrics, Emerald Group Publishing Limited, "Comparative Analysis of Trade and Finance in Emerging Economies", DOI: 10.1108/S1571-038620230000031013.
• Ari Prasetyo & Taufik Faturohman, 2023, "Financial Distress and Financial Performance Analysis of Highway Companies Before and During the COVID-19 Pandemic: Evidence from Indonesia Stock Exchange," International Symposia in Economic Theory and Econometrics, Emerald Group Publishing Limited, "Comparative Analysis of Trade and Finance in Emerging Economies", DOI: 10.1108/S1571-038620230000031021.
• Isti Yuli Ismawati & Taufik Faturohman, 2023, "Credit Risk Scoring Model for Consumer Financing: Logistic Regression Method," International Symposia in Economic Theory and Econometrics, Emerald Group Publishing Limited, "Comparative Analysis of Trade and Finance in Emerging Economies", DOI: 10.1108/S1571-038620230000031023.
• Amit Pandey & Anil Kumar Sharma, 2023, "Indian institutional investor's portfolio concentration decision: skill and performance," Journal of Advances in Management Research, Emerald Group Publishing Limited, volume 21, issue 1, pages 66-95, December, DOI: 10.1108/JAMR-05-2023-0134.
• Özgür İcan & Taha Buğra Çelik, 2023, "Weak-form market efficiency and corruption: a cross-country comparative analysis," Journal of Capital Markets Studies, Emerald Group Publishing Limited, volume 7, issue 1, pages 72-90, April, DOI: 10.1108/JCMS-12-2022-0046.
• Cheol-Won Yang, 2023, "Investment strategy via analyst report text mining," Journal of Derivatives and Quantitative Studies: 선물연구, Emerald Group Publishing Limited, volume 31, issue 2, pages 98-120, March, DOI: 10.1108/JDQS-09-2022-0022.
• Victoria Cherkasova & Elena Fedorova & Igor Stepnov, 2023, "Market reaction to firms' investments in CSR projects," Journal of Economics, Finance and Administrative Science, Emerald Group Publishing Limited, volume 28, issue 55, pages 44-59, March, DOI: 10.1108/JEFAS-08-2021-0150.
• Youssef El-Khatib & Abdulnasser Hatemi-J, 2023, "On a regime switching illiquid high volatile prediction model for cryptocurrencies," Journal of Economic Studies, Emerald Group Publishing Limited, volume 51, issue 2, pages 485-498, July, DOI: 10.1108/JES-03-2023-0134.
• Rajyalakshmi Kandukuri, 2023, "An analysis of stockbroking frauds and regulatory action in India," Journal of Financial Crime, Emerald Group Publishing Limited, volume 31, issue 4, pages 1037-1046, June, DOI: 10.1108/JFC-04-2023-0076.
• Nader Trabelsi, 2023, "Global hidden factors predicting financial distress in Gulf Arab states: a quantile–time–frequency analysis," Journal of Financial Economic Policy, Emerald Group Publishing Limited, volume 15, issue 4/5, pages 284-312, May, DOI: 10.1108/JFEP-01-2023-0010.
• Syed Alamdar Ali Shah & Bayu Arie Fianto & Batool Imtiaz & Raditya Sukmana & Rafiatul Adlin Hj Mohd Ruslan, 2023, "Shariah review of Brownian motion of Islamic stock market elements: establishing the benchmarks of Islamic econophysics," Journal of Islamic Accounting and Business Research, Emerald Group Publishing Limited, volume 14, issue 8, pages 1182-1194, January, DOI: 10.1108/JIABR-07-2022-0181.
• Vladimir Dmitrievich Milovidov, 2023, "Redefining investors' goals in the post–normal world," Journal of Risk Finance, Emerald Group Publishing Limited, volume 24, issue 3, pages 371-385, March, DOI: 10.1108/JRF-07-2022-0191.
• Ikhlaas Gurrib & Firuz Kamalov & Olga Starkova & Elgilani Eltahir Elshareif & Davide Contu, 2023, "Drivers of the next-minute Bitcoin price using sparse regressions," Studies in Economics and Finance, Emerald Group Publishing Limited, volume 41, issue 2, pages 410-431, October, DOI: 10.1108/SEF-04-2023-0182.
• Justyna Bogolebska, 2023, "Catering Theory of Dividend Policy in Polish Listed Companies," European Research Studies Journal, European Research Studies Journal, volume 0, issue 2, pages 197-208.
• Chronopoulos, Ilias & Raftapostolos, Aristeidis & Kapetanios, George, 2023, "Forecasting Value-at-Risk using deep neural network quantile regression," Essex Finance Centre Working Papers, University of Essex, Essex Business School, number 34837, Feb.
• Hung-Hsi Huang & Yi-Ru Lin, 2023, "Forecasting VIX with Stock and Oil Prices," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, volume 73, issue 1, pages 24-55, January.
• Pablo Pincheira-Brown & Nicolás Hardy & Cristobal Henrriquez & Ignacio Tapia & Andrea Bentancor, 2023, "Forecasting Base Metal Prices with an International Stock Index," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, volume 73, issue 3, pages 277-302, October.
• Kiwoong Byun & Baeho Kim & Dong Hwan Oh, 2023, "Systemic Credit Risk Premium: Insights from Credit Derivatives Markets," Finance and Economics Discussion Series, Board of Governors of the Federal Reserve System (U.S.), number 2023-055r1, Aug, revised 04 Aug 2025, DOI: 10.17016/FEDS.2023.055r1.