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Forecasting crude oil prices with a large set of predictors: Can LASSO select powerful predictors?
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- Wang, Yudong & Hao, Xianfeng, 2023. "Forecasting the real prices of crude oil: What is the role of parameter instability?," Energy Economics, Elsevier, vol. 117(C).
- Zhang, Yaojie & He, Jiaxin & He, Mengxi & Li, Shaofang, 2023. "Geopolitical risk and stock market volatility: A global perspective," Finance Research Letters, Elsevier, vol. 53(C).
- Dai, Zhifeng & Kang, Jie & Hu, Yangli, 2021. "Efficient predictability of oil price: The role of number of IPOs and U.S. dollar index," Resources Policy, Elsevier, vol. 74(C).
- Mengxi He & Xianfeng Hao & Yaojie Zhang & Fanyi Meng, 2021. "Forecasting stock return volatility using a robust regression model," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(8), pages 1463-1478, December.
- Yan, Xiang & Bai, Jiancheng & Li, Xiafei & Chen, Zhonglu, 2022. "Can dimensional reduction technology make better use of the information of uncertainty indices when predicting volatility of Chinese crude oil futures?," Resources Policy, Elsevier, vol. 75(C).
- Liu, Shan & Li, Ziwei, 2023. "Macroeconomic attention and oil futures volatility prediction," Finance Research Letters, Elsevier, vol. 57(C).
- Lv, Wendai & Wu, Qian, 2022. "Global economic conditions index and oil price predictability," Finance Research Letters, Elsevier, vol. 48(C).
- Liu, Yang & Han, Liyan & Xu, Yang, 2021. "The impact of geopolitical uncertainty on energy volatility," International Review of Financial Analysis, Elsevier, vol. 75(C).
- Ciner, Cetin, 2021. "Stock return predictability in the time of COVID-19," Finance Research Letters, Elsevier, vol. 38(C).
- Guo, Lili & Huang, Xinya & Li, Yanjiao & Li, Houjian, 2023. "Forecasting crude oil futures price using machine learning methods: Evidence from China," Energy Economics, Elsevier, vol. 127(PA).
- He, Mengxi & Zhang, Yaojie, 2022. "Climate policy uncertainty and the stock return predictability of the oil industry," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 81(C).
- Zhang, Zhikai & Wang, Yudong & Xiao, Jihong & Zhang, Yaojie, 2023. "Not all geopolitical shocks are alike: Identifying price dynamics in the crude oil market under tensions," Resources Policy, Elsevier, vol. 80(C).
- Zhang, Jiaming & Guo, Songlin & Dou, Bin & Xie, Bingyuan, 2023. "Evidence of the internationalization of China's crude oil futures: Asymmetric linkages to global financial risks," Energy Economics, Elsevier, vol. 127(PA).
- Xiao, Jihong & Wang, Yudong, 2022. "Macroeconomic uncertainty, speculation, and energy futures returns: Evidence from a quantile regression," Energy, Elsevier, vol. 241(C).
- Lu, Xinjie & Ma, Feng & Wang, Tianyang & Wen, Fenghua, 2023. "International stock market volatility: A data-rich environment based on oil shocks," Journal of Economic Behavior & Organization, Elsevier, vol. 214(C), pages 184-215.
- Xi Zhang & Xu Wu & Linlin Zhang & Zhonglu Chen, 2022. "The Evaluation of Mean-Detrended Cross-Correlation Analysis Portfolio Strategy for Multiple risk Assets," Evaluation Review, , vol. 46(2), pages 138-164, April.
- Yi, Yongsheng & He, Mengxi & Zhang, Yaojie, 2022. "Out-of-sample prediction of Bitcoin realized volatility: Do other cryptocurrencies help?," The North American Journal of Economics and Finance, Elsevier, vol. 62(C).
- Ma, Feng & Cao, Jiawei, 2023. "The Chinese equity premium predictability: Evidence from a long historical data," Finance Research Letters, Elsevier, vol. 53(C).
- Ma, Feng & Wang, Jiqian & Wahab, M.I.M. & Ma, Yuanhui, 2023. "Stock market volatility predictability in a data-rich world: A new insight," International Journal of Forecasting, Elsevier, vol. 39(4), pages 1804-1819.
- Shi, Xunpeng & Wang, Keying & Cheong, Tsun Se & Zhang, Hongwu, 2020. "Prioritizing driving factors of household carbon emissions: An application of the LASSO model with survey data," Energy Economics, Elsevier, vol. 92(C).
- Qingxiang Han & Mengxi He & Yaojie Zhang & Muhammad Umar, 2023. "Default return spread: A powerful predictor of crude oil price returns," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(7), pages 1786-1804, November.
- Zhang, Lixia & Luo, Qin & Guo, Xiaozhu & Umar, Muhammad, 2022. "Medium-term and long-term volatility forecasts for EUA futures with country-specific economic policy uncertainty indices," Resources Policy, Elsevier, vol. 77(C).
- Xing, Li-Min & Zhang, Yue-Jun, 2022. "Forecasting crude oil prices with shrinkage methods: Can nonconvex penalty and Huber loss help?," Energy Economics, Elsevier, vol. 110(C).
- Chao Liang & Yan Li & Feng Ma & Yaojie Zhang, 2022. "Forecasting international equity market volatility: A new approach," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(7), pages 1433-1457, November.
- Wen, Chufu & Zhu, Haoyang & Dai, Zhifeng, 2023. "Forecasting commodity prices returns: The role of partial least squares approach," Energy Economics, Elsevier, vol. 125(C).
- Lycheva, Maria & Mironenkov, Alexey & Kurbatskii, Alexey & Fantazzini, Dean, 2022.
"Forecasting oil prices with penalized regressions, variance risk premia and Google data,"
Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 68, pages 28-49.
- Fantazzini, Dean & Kurbatskii, Alexey & Mironenkov, Alexey & Lycheva, Maria, 2022. "Forecasting oil prices with penalized regressions, variance risk premia and Google data," MPRA Paper 118239, University Library of Munich, Germany.
- Lyu, Zhichong & Ma, Feng & Zhang, Jixiang, 2023. "Oil futures volatility prediction: Bagging or combination?," International Review of Economics & Finance, Elsevier, vol. 87(C), pages 457-467.
- Afees A. Salisu & Rangan Gupta & Elie Bouri & Qiang Ji, 2022. "Mixed‐frequency forecasting of crude oil volatility based on the information content of global economic conditions," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(1), pages 134-157, January.
- Zhang, Yaojie & Wang, Yudong, 2023. "Forecasting crude oil futures market returns: A principal component analysis combination approach," International Journal of Forecasting, Elsevier, vol. 39(2), pages 659-673.
- Conlon, Thomas & Cotter, John & Eyiah-Donkor, Emmanuel, 2022.
"The illusion of oil return predictability: The choice of data matters!,"
Journal of Banking & Finance, Elsevier, vol. 134(C).
- Thomas Conlon & John Cotter & Emmanuel Eyiah-Donkor, 2022. "The illusion of oil return predictability: The choice of data matters!," Post-Print hal-03519860, HAL.
- Dai, Zhifeng & Zhu, Haoyang, 2023. "Dynamic risk spillover among crude oil, economic policy uncertainty and Chinese financial sectors," International Review of Economics & Finance, Elsevier, vol. 83(C), pages 421-450.
- Li, Xiafei & Liao, Yin & Lu, Xinjie & Ma, Feng, 2022. "An oil futures volatility forecast perspective on the selection of high-frequency jump tests," Energy Economics, Elsevier, vol. 116(C).
- Wen, Danyan & Liu, Li & Wang, Yudong & Zhang, Yaojie, 2022. "Forecasting crude oil market returns: Enhanced moving average technical indicators," Resources Policy, Elsevier, vol. 76(C).
- Yaojie Zhang & Yudong Wang & Feng Ma, 2021. "Forecasting US stock market volatility: How to use international volatility information," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(5), pages 733-768, August.
- Donghua Wang & Tianhui Fang, 2022. "Forecasting Crude Oil Prices with a WT-FNN Model," Energies, MDPI, vol. 15(6), pages 1-21, March.
- Zhifeng Dai & Tingyu Li & Mi Yang, 2022. "Forecasting stock return volatility: The role of shrinkage approaches in a data‐rich environment," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(5), pages 980-996, August.
- Zhang, Yaojie & Wahab, M.I.M. & Wang, Yudong, 2023. "Forecasting crude oil market volatility using variable selection and common factor," International Journal of Forecasting, Elsevier, vol. 39(1), pages 486-502.
- Cheng, Xian & Wu, Peng & Liao, Stephen Shaoyi & Wang, Xuelian, 2023. "An integrated model for crude oil forecasting: Causality assessment and technical efficiency," Energy Economics, Elsevier, vol. 117(C).
- Wang, Jiqian & Ma, Feng & Bouri, Elie & Zhong, Juandan, 2022. "Volatility of clean energy and natural gas, uncertainty indices, and global economic conditions," Energy Economics, Elsevier, vol. 108(C).
- Lv, Wendai & Qi, Jipeng, 2022. "Stock market return predictability: A combination forecast perspective," International Review of Financial Analysis, Elsevier, vol. 84(C).
- Guo, Xiaozhu & Huang, Dengshi & Li, Xiafei & Liang, Chao, 2023. "Are categorical EPU indices predictable for carbon futures volatility? Evidence from the machine learning method," International Review of Economics & Finance, Elsevier, vol. 83(C), pages 672-693.
- Luo, Jiawen & Klein, Tony & Walther, Thomas & Ji, Qiang, 2021. "Forecasting Realized Volatility of Crude Oil Futures Prices based on Machine Learning," QBS Working Paper Series 2021/04, Queen's University Belfast, Queen's Business School.
- Zhang, Yaojie & He, Mengxi & Liao, Cunfei & Wang, Yudong, 2023. "Climate risk exposure and the cross-section of Chinese stock returns," Finance Research Letters, Elsevier, vol. 55(PB).
- Tian, Guangning & Peng, Yuchao & Meng, Yuhao, 2023. "Forecasting crude oil prices in the COVID-19 era: Can machine learn better?," Energy Economics, Elsevier, vol. 125(C).
- Rao, Congjun & Zhang, Yue & Wen, Jianghui & Xiao, Xinping & Goh, Mark, 2023. "Energy demand forecasting in China: A support vector regression-compositional data second exponential smoothing model," Energy, Elsevier, vol. 263(PC).
- Jiang, Zhe & Zhang, Lin & Zhang, Lingling & Wen, Bo, 2022. "Investor sentiment and machine learning: Predicting the price of China's crude oil futures market," Energy, Elsevier, vol. 247(C).
- Huang, Yisu & Xu, Weiju & Huang, Dengshi & Zhao, Chenchen, 2023. "Chinese crude oil futures volatility and sustainability: An uncertainty indices perspective," Resources Policy, Elsevier, vol. 80(C).
- Liu, Guangqiang & Guo, Xiaozhu, 2022. "Forecasting stock market volatility using commodity futures volatility information," Resources Policy, Elsevier, vol. 75(C).
- Un, Kuok Sin & Ausloos, Marcel, 2022. "Equity premium prediction: Taking into account the role of long, even asymmetric, swings in stock market behavior," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 608(P1).
- Lu, Xinjie & Ma, Feng & Wang, Jiqian & Zhu, Bo, 2021. "Oil shocks and stock market volatility: New evidence," Energy Economics, Elsevier, vol. 103(C).
- Xu, Yongan & Duong, Duy & Xu, Hualong, 2023. "Attention! Predicting crude oil prices from the perspective of extreme weather," Finance Research Letters, Elsevier, vol. 57(C).
- Liang, Chao & Xu, Yongan & Wang, Jianqiong & Yang, Mo, 2022. "Whether dimensionality reduction techniques can improve the ability of sentiment proxies to predict stock market returns," International Review of Financial Analysis, Elsevier, vol. 82(C).
- Lu, Xinjie & Ma, Feng & Xu, Jin & Zhang, Zehui, 2022. "Oil futures volatility predictability: New evidence based on machine learning models11All the authors contribute to the paper equally," International Review of Financial Analysis, Elsevier, vol. 83(C).
- Dai, Zhifeng & Kang, Jie, 2021. "Bond yield and crude oil prices predictability," Energy Economics, Elsevier, vol. 97(C).
- Zhang, Zhikai & He, Mengxi & Zhang, Yaojie & Wang, Yudong, 2022. "Geopolitical risk trends and crude oil price predictability," Energy, Elsevier, vol. 258(C).
- Xiao, Jihong & Wang, Yudong, 2021. "Investor attention and oil market volatility: Does economic policy uncertainty matter?," Energy Economics, Elsevier, vol. 97(C).
- Mengxi He & Yudong Wang & Yaojie Zhang, 2023. "The predictability of iron ore futures prices: A product‐material lead–lag effect," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 43(9), pages 1289-1304, September.
- Plakandaras, Vasilios & Ji, Qiang, 2022. "Intrinsic decompositions in gold forecasting," Journal of Commodity Markets, Elsevier, vol. 28(C).
- Ma, Feng & Lu, Xinjie & Liu, Jia & Huang, Dengshi, 2022. "Macroeconomic attention and stock market return predictability," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 79(C).
- Zhang, Yue-Jun & Li, Zhao-Chen, 2021. "Forecasting the stock returns of Chinese oil companies: Can investor attention help?," International Review of Economics & Finance, Elsevier, vol. 76(C), pages 531-555.
- Jiqian Wang & Feng Ma & Elie Bouri & Yangli Guo, 2023. "Which factors drive Bitcoin volatility: Macroeconomic, technical, or both?," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(4), pages 970-988, July.
- Kais Tissaoui & Ilyes Abidi & Nadia Azibi & Mariem Nsaibi, 2024. "Spillover Effects between Crude Oil Returns and Uncertainty: New Evidence from Time-Frequency Domain Approaches," Energies, MDPI, vol. 17(2), pages 1-24, January.
- Zeng, Qing & Lu, Xinjie & Dong, Dayong & Li, Pan, 2022. "Category-specific EPU indices, macroeconomic variables and stock market return predictability," International Review of Financial Analysis, Elsevier, vol. 84(C).
- Likun Lei & Yaojie Zhang & Yu Wei & Yi Zhang, 2021. "Forecasting the volatility of Chinese stock market: An international volatility index," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(1), pages 1336-1350, January.
- Zhang, Yaojie & He, Mengxi & Wen, Danyan & Wang, Yudong, 2023. "Forecasting crude oil price returns: Can nonlinearity help?," Energy, Elsevier, vol. 262(PB).
- Liang, Chao & Ma, Feng & Li, Ziyang & Li, Yan, 2020. "Which types of commodity price information are more useful for predicting US stock market volatility?," Economic Modelling, Elsevier, vol. 93(C), pages 642-650.
- He, Huizi & Sun, Mei & Li, Xiuming & Mensah, Isaac Adjei, 2022. "A novel crude oil price trend prediction method: Machine learning classification algorithm based on multi-modal data features," Energy, Elsevier, vol. 244(PA).
- Caglayan, Mustafa & Pham, Tho & Talavera, Oleksandr & Xiong, Xiong, 2020. "Asset mispricing in peer-to-peer loan secondary markets," Journal of Corporate Finance, Elsevier, vol. 65(C).
- Sun, Chuanwang & Min, Jialin & Sun, Jiacheng & Gong, Xu, 2023. "The role of China's crude oil futures in world oil futures market and China's financial market," Energy Economics, Elsevier, vol. 120(C).
- 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, vol. 55(PA).
- Song, Yixuan & He, Mengxi & Wang, Yudong & Zhang, Yaojie, 2022. "Forecasting crude oil market volatility: A newspaper-based predictor regarding petroleum market volatility," Resources Policy, Elsevier, vol. 79(C).
- He, Mengxi & Zhang, Yaojie & Wen, Danyan & Wang, Yudong, 2021. "Forecasting crude oil prices: A scaled PCA approach," Energy Economics, Elsevier, vol. 97(C).
- Yaojie Zhang & Mengxi He & Danyan Wen & Yudong Wang, 2022. "Forecasting Bitcoin volatility: A new insight from the threshold regression model," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(3), pages 633-652, April.
- Zhang, Ditian & Tang, Pan, 2023. "Forecasting European Union allowances futures: The role of technical indicators," Energy, Elsevier, vol. 270(C).
- Chao Liang & Feng Ma & Lu Wang & Qing Zeng, 2021. "The information content of uncertainty indices for natural gas futures volatility forecasting," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(7), pages 1310-1324, November.
- Kim, Jang Ho & Han, Jiwoon & Kang, Taehyeon & Fabozzi, Frank J., 2023. "A machine learning approach for comparing the largest firm effect," Emerging Markets Review, Elsevier, vol. 54(C).
- Jiawen Luo & Qun Zhang, 2024. "Air pollution, weather factors, and realized volatility forecasts of agricultural commodity futures," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 44(2), pages 151-217, February.
- Xinjie Lu & Feng Ma & Jiqian Wang & Jing Liu, 2022. "Forecasting oil futures realized range‐based volatility with jumps, leverage effect, and regime switching: New evidence from MIDAS models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(4), pages 853-868, July.
- Li, Xiafei & Liang, Chao & Chen, Zhonglu & Umar, Muhammad, 2022. "Forecasting crude oil volatility with uncertainty indicators: New evidence," Energy Economics, Elsevier, vol. 108(C).
- Chao Liang & Yongan Xu & Zhonglu Chen & Xiafei Li, 2023. "Forecasting China's stock market volatility with shrinkage method: Can Adaptive Lasso select stronger predictors from numerous predictors?," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 28(4), pages 3689-3699, October.
- Yaojie Zhang & Mengxi He & Yuqi Zhao & Xianfeng Hao, 2023. "Predicting stock realized variance based on an asymmetric robust regression approach," Bulletin of Economic Research, Wiley Blackwell, vol. 75(4), pages 1022-1047, October.
- Niu, Zibo & Wang, Chenlu & Zhang, Hongwei, 2023. "Forecasting stock market volatility with various geopolitical risks categories: New evidence from machine learning models," International Review of Financial Analysis, Elsevier, vol. 89(C).
- Dai, Zhifeng & Dong, Xiaodi & Kang, Jie & Hong, Lianying, 2020. "Forecasting stock market returns: New technical indicators and two-step economic constraint method," The North American Journal of Economics and Finance, Elsevier, vol. 53(C).
- Chao Liang & Yu Wei & Likun Lei & Feng Ma, 2022. "Global equity market volatility forecasting: New evidence," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(1), pages 594-609, January.
- Xiao, Jihong & Wen, Fenghua & He, Zhifang, 2023. "Impact of geopolitical risks on investor attention and speculation in the oil market: Evidence from nonlinear and time-varying analysis," Energy, Elsevier, vol. 267(C).
- Lu, Fei & Ma, Feng & Li, Pan & Huang, Dengshi, 2022. "Natural gas volatility predictability in a data-rich world," International Review of Financial Analysis, Elsevier, vol. 83(C).
- Chen, Zhonglu & Ye, Yong & Li, Xiafei, 2022. "Forecasting China's crude oil futures volatility: New evidence from the MIDAS-RV model and COVID-19 pandemic," Resources Policy, Elsevier, vol. 75(C).
- Xu, Yongan & Liang, Chao & Li, Yan & Huynh, Toan L.D., 2022. "News sentiment and stock return: Evidence from managers’ news coverages," Finance Research Letters, Elsevier, vol. 48(C).
- Wen, Danyan & Wang, Yudong & Zhang, Yaojie, 2021. "Intraday return predictability in China’s crude oil futures market: New evidence from a unique trading mechanism," Economic Modelling, Elsevier, vol. 96(C), pages 209-219.
- Wang, Jiqian & He, Xiaofeng & Ma, Feng & Li, Pan, 2022. "Uncertainty and oil volatility: Evidence from shrinkage method," Resources Policy, Elsevier, vol. 75(C).
- Ayşe Özmen, 2023. "Sparse regression modeling for short- and long‐term natural gas demand prediction," Annals of Operations Research, Springer, vol. 322(2), pages 921-946, March.
- 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, vol. 119(C).
- Wang, Jiqian & Guo, Xiaozhu & Tan, Xueping & Chevallier, Julien & Ma, Feng, 2023. "Which exogenous driver is informative in forecasting European carbon volatility: Bond, commodity, stock or uncertainty?," Energy Economics, Elsevier, vol. 117(C).
- Niu, Zibo & Liu, Yuanyuan & Gao, Wang & Zhang, Hongwei, 2021. "The role of coronavirus news in the volatility forecasting of crude oil futures markets: Evidence from China," Resources Policy, Elsevier, vol. 73(C).
- 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, vol. 84(C), pages 358-368.
- Yu, Dan & Chen, Chuang & Wang, Yudong & Zhang, Yaojie, 2023. "Hedging pressure momentum and the predictability of oil futures returns," Economic Modelling, Elsevier, vol. 121(C).
- Zhang, Yaojie & Lei, Likun & Wei, Yu, 2020. "Forecasting the Chinese stock market volatility with international market volatilities: The role of regime switching," The North American Journal of Economics and Finance, Elsevier, vol. 52(C).
- Li, Houjian & Huang, Xinya & Guo, Lili, 2023. "Extreme risk dependence and time-varying spillover between crude oil, commodity market and inflation in China," Energy Economics, Elsevier, vol. 127(PB).
- Yumin Li & Ruiqi Yang & Xiaoman Wang & Jiaming Zhu & Nan Song, 2023. "Carbon Price Combination Forecasting Model Based on Lasso Regression and Optimal Integration," Sustainability, MDPI, vol. 15(12), pages 1-26, June.
- Jin, Daxiang & He, Mengxi & Xing, Lu & Zhang, Yaojie, 2022. "Forecasting China's crude oil futures volatility: How to dig out the information of other energy futures volatilities?," Resources Policy, Elsevier, vol. 78(C).
- Wang, Lu & Ma, Feng & Hao, Jianyang & Gao, Xinxin, 2021. "Forecasting crude oil volatility with geopolitical risk: Do time-varying switching probabilities play a role?," International Review of Financial Analysis, Elsevier, vol. 76(C).
- Chen, Zhonglu & Liang, Chao & Umar, Muhammad, 2021. "Is investor sentiment stronger than VIX and uncertainty indices in predicting energy volatility?," Resources Policy, Elsevier, vol. 74(C).
- Huang, Yisu & Ma, Feng & Bouri, Elie & Huang, Dengshi, 2023. "A comprehensive investigation on the predictive power of economic policy uncertainty from non-U.S. countries for U.S. stock market returns," International Review of Financial Analysis, Elsevier, vol. 87(C).
- Wang, Jiqian & Huang, Yisu & Ma, Feng & Chevallier, Julien, 2020. "Does high-frequency crude oil futures data contain useful information for predicting volatility in the US stock market? New evidence," Energy Economics, Elsevier, vol. 91(C).
- Li Yao & He Ni, 2023. "Prediction of patent grant and interpreting the key determinants: an application of interpretable machine learning approach," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(9), pages 4933-4969, September.
- Xiao, Jihong & Wang, Yudong, 2022. "Good oil volatility, bad oil volatility, and stock return predictability," International Review of Economics & Finance, Elsevier, vol. 80(C), pages 953-966.
- Silva, Diego S. & Yamashita, Gabrielli Harumi & Cortimiglia, Marcelo Nogueira & Brust-Renck, Priscila G. & ten Caten, Carla Schwengber, 2022. "Are we ready to assess digital readiness? Exploring digital implications for social progress from the Network Readiness Index," Technology in Society, Elsevier, vol. 68(C).
- Liang, Chao & Tang, Linchun & Li, Yan & Wei, Yu, 2020. "Which sentiment index is more informative to forecast stock market volatility? Evidence from China," International Review of Financial Analysis, Elsevier, vol. 71(C).
- Yan Wang & Tong Lin, 2023. "A Novel Deterministic Probabilistic Forecasting Framework for Gold Price with a New Pandemic Index Based on Quantile Regression Deep Learning and Multi-Objective Optimization," Mathematics, MDPI, vol. 12(1), pages 1-21, December.
- Dai, Zhifeng & Kang, Jie & Wen, Fenghua, 2021. "Predicting stock returns: A risk measurement perspective," International Review of Financial Analysis, Elsevier, vol. 74(C).
- Zheng, Yan & Zhou, Min & Wen, Fenghua, 2021. "Asymmetric effects of oil shocks on carbon allowance price: Evidence from China," Energy Economics, Elsevier, vol. 97(C).
- Nonejad, Nima, 2021. "Predicting the return on the spot price of crude oil out-of-sample by conditioning on news-based uncertainty measures: Some new empirical results," Energy Economics, Elsevier, vol. 104(C).
- Lu, Xinjie & Lang, Qiaoqi, 2023. "Categorial economic policy uncertainty indices or Twitter-based uncertainty indices? Evidence from Chinese stock market," Finance Research Letters, Elsevier, vol. 55(PB).
- Sobti, Neharika & Sehgal, Sanjay & Ilango, Balakrishnan, 2021. "How do macroeconomic news surprises affect round-the-clock price discovery of gold?," International Review of Financial Analysis, Elsevier, vol. 78(C).
- Li, Xiafei & Guo, Qiang & Liang, Chao & Umar, Muhammad, 2023. "Forecasting gold volatility with geopolitical risk indices," Research in International Business and Finance, Elsevier, vol. 64(C).
- Yuntong Liu & Yu Wei & Yi Liu & Wenjuan Li, 2020. "Forecasting Oil Price by Hierarchical Shrinkage in Dynamic Parameter Models," Discrete Dynamics in Nature and Society, Hindawi, vol. 2020, pages 1-12, December.