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Sung Y. Park

Citations

Many of the citations below have been collected in an experimental project, CitEc, where a more detailed citation analysis can be found. These are citations from works listed in RePEc that could be analyzed mechanically. So far, only a minority of all works could be analyzed. See under "Corrections" how you can help improve the citation analysis.

Working papers

  1. Chong, Terence Tai Leung & Ding, Haoyuan & Park, Sung Y, 2014. "Nonlinear Dependence between Stock and Real Estate Markets in China," MPRA Paper 57774, University Library of Munich, Germany.

    Cited by:

    1. Haoyuan Ding & Yuying Jin & Cong Qin & Jiezhou Ying, 2020. "Tail Causality between Crude Oil Price and RMB Exchange Rate," China & World Economy, Institute of World Economics and Politics, Chinese Academy of Social Sciences, vol. 28(3), pages 116-134, May.
    2. Kyritsis, Evangelos & Andersson, Jonas, 2019. "Causality in Quantiles and Dynamic Relations in Energy Markets," Working Papers 116, VATT Institute for Economic Research.
    3. Khalid Almeshal & Nader Naifar, 2016. "A quantile regression approach and nonlinear analysis with Archimedean copulas to explain the movements of residential real estate prices," Afro-Asian Journal of Finance and Accounting, Inderscience Enterprises Ltd, vol. 6(4), pages 374-395.
    4. Cellmer Radosław & Bełej Mirosław & Cichulska Aneta, 2019. "Identification of Cause-and-Effect Relationships in the Real Estate Market Using the VAR Model and the Granger Test," Real Estate Management and Valuation, Sciendo, vol. 27(4), pages 85-95, December.
    5. Bahmani-Oskooee, Mohsen & Ghodsi, Seyed Hesam, 2018. "Asymmetric causality between the U.S. housing market and its stock market: Evidence from state level data," The Journal of Economic Asymmetries, Elsevier, vol. 18(C), pages 1-1.
    6. Effiong, Ekpeno L., 2016. "Nonlinear Dependence between Stock Prices and Exchange Rate in Nigeria," MPRA Paper 74336, University Library of Munich, Germany.
    7. Xia, Tongshui & Yao, Chen-Xi & Geng, Jiang-Bo, 2020. "Dynamic and frequency-domain spillover among economic policy uncertainty, stock and housing markets in China," International Review of Financial Analysis, Elsevier, vol. 67(C).
    8. Kyritsis, Evangelos & Andersson, Jonas, 2019. "Causality in quantiles and dynamic relations in energy markets: (De)tails matter," Energy Policy, Elsevier, vol. 133(C).
    9. Chi-Wei Su & Xiao-Cui Yin & Hsu-Ling Chang & Hai-Gang Zhou, 2019. "Are the stock and real estate markets integrated in China?," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 14(4), pages 741-760, December.
    10. Bahmani-Oskooee, Mohsen & Wu, Tsung-Pao, 2018. "Housing prices and real effective exchange rates in 18 OECD countries: A bootstrap multivariate panel Granger causality," Economic Analysis and Policy, Elsevier, vol. 60(C), pages 119-126.
    11. Albulescu, C.T. & Bouri, E. & Tiwari, A.K. & Roubaud, D., 2020. "Quantile causality between banking stock and real estate securities returns in the US," The Quarterly Review of Economics and Finance, Elsevier, vol. 78(C), pages 251-260.
    12. Korhan Gokmenoglu & Siamand Hesami, 2019. "Real estate prices and stock market in Germany: analysis based on hedonic price index," International Journal of Housing Markets and Analysis, Emerald Group Publishing Limited, vol. 12(4), pages 687-707, April.
    13. Mehmet Balcilar & Rangan Gupta & Duc Khuong Nguyen & Mark E. Wohar, 2018. "Causal effects of the United States and Japan on Pacific-Rim stock markets: nonparametric quantile causality approach," Applied Economics, Taylor & Francis Journals, vol. 50(53), pages 5712-5727, November.
    14. Xiangyu Chen & Jittima Tongurai, 2021. "The Relationship Between China’s Real Estate Market and Industrial Metals Futures Market: Evidence from Non-price Measures of the Real Estate Market," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 28(4), pages 527-561, December.
    15. Shi, Guangping & Liu, Xiaoxing & Zhang, Xu, 2017. "Time-varying causality between stock and housing markets in China," Finance Research Letters, Elsevier, vol. 22(C), pages 227-232.
    16. Rakesh K. Bissoondeeal & Leonidas Tsiaras, 2023. "Investigating the Links between UK House Prices and Share Prices with Copulas," The Journal of Real Estate Finance and Economics, Springer, vol. 67(3), pages 423-452, October.
    17. Stephanos Papadamou & Νikolaos A. Kyriazis & Panayiotis G. Tzeremes, 2020. "US non-linear causal effects on global equity indices in Normal times versus unconventional eras," International Economics and Economic Policy, Springer, vol. 17(2), pages 381-407, May.
    18. Mohsen Bahmani-Oskooee & Seyed Hesam Ghodsi, 2019. "On the Link between Value of the Dollar and Housing Production in the U.S.: Evidence from State Level Data," International Real Estate Review, Global Social Science Institute, vol. 22(2), pages 231-274.
    19. Lin, Wen-Yuan & Tsai, I-Chun, 2019. "Trader differences in Shanghai’s A-share and B-share markets: Effects on interaction with the Shanghai housing market," Journal of Asian Economics, Elsevier, vol. 64(C), pages 1-1.
    20. Feng-Li Lin & Mei-Chih Wang & Hsien-Hung Kung, 2020. "Housing and Stock Market Nexus in the US," European Research Studies Journal, European Research Studies Journal, vol. 0(3), pages 114-130.
    21. Hao, Jing & He, Feng, 2018. "Univariate dependence among sectors in Chinese stock market and systemic risk implication," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 510(C), pages 355-364.
    22. Su, Chi-Wei & Huang, Shi-Wen & Qin, Meng & Umar, Muhammad, 2021. "Does crude oil price stimulate economic policy uncertainty in BRICS?," Pacific-Basin Finance Journal, Elsevier, vol. 66(C).
    23. Mohsen Bahmani-Oskooee & Seyed Hesam Ghodsi, 2018. "Link between Housing and Stock Markets: Evidence from OECD Using Asymmetry Analysis," International Real Estate Review, Global Social Science Institute, vol. 21(4), pages 447-471.
    24. Pedro Coelho & Luís Gomes & Patrícia Ramos, 2023. "Asymmetric Wealth Effect between US Stock Markets and US Housing Market and European Stock Markets: Evidences from TAR and MTAR," Risks, MDPI, vol. 11(7), pages 1-14, July.

  2. Ying Fang & Sung Y. Park & Jinfeng Zhang, 2013. "A Simple Spatial Dependence Test Robust to Local and Distributional Misspecifications," Working Papers 2013-10-14, Wang Yanan Institute for Studies in Economics (WISE), Xiamen University.

    Cited by:

    1. Malabika Koley & Anil K. Bera, 2022. "Testing for spatial dependence in a spatial autoregressive (SAR) model in the presence of endogenous regressors," Journal of Spatial Econometrics, Springer, vol. 3(1), pages 1-46, December.

  3. Rui Fan & Ying Fang & Sung Y. Park, 2013. "Resource Abundance and Economic Growth in China," Working Papers 2013-10-14, Wang Yanan Institute for Studies in Economics (WISE), Xiamen University.

    Cited by:

    1. Charlier, Christophe & Guillou, Sarah, 2014. "Distortion Effects of Export Quota Policy: an Analysis of the China - Raw Materials Dispute," Climate Change and Sustainable Development 186732, Fondazione Eni Enrico Mattei (FEEM).
    2. Xiaoyu Li & Lan Xu, 2021. "Human development associated with environmental quality in China," PLOS ONE, Public Library of Science, vol. 16(2), pages 1-21, February.
    3. Wu, Linfei & Sun, Liwen & Qi, Peixiao & Ren, Xiangwei & Sun, Xiaoting, 2021. "Energy endowment, industrial structure upgrading, and CO2 emissions in China: Revisiting resource curse in the context of carbon emissions," Resources Policy, Elsevier, vol. 74(C).
    4. Zuo, Na & Zhong, Hua, 2020. "Can resource policy reverse the resource curse? Evidence from China," Resources Policy, Elsevier, vol. 68(C).
    5. He, Xiaoping & Mou, Dunguo, 2020. "Impacts of mineral resources: Evidence from county economies in China," Energy Policy, Elsevier, vol. 136(C).
    6. Jiang, Chun & Zhang, Yadi & Kamran, Hafiz Waqas & Afshan, Sahar, 2021. "Understanding the dynamics of the resource curse and financial development in China? A novel evidence based on QARDL model," Resources Policy, Elsevier, vol. 72(C).
    7. Cheng, Zhonghua & Li, Lianshui & Liu, Jun, 2020. "Natural resource abundance, resource industry dependence and economic green growth in China," Resources Policy, Elsevier, vol. 68(C).
    8. Cheng Peng & Dianzhuang Feng & Hai Long, 2022. "Assessing the Contribution of Natural Gas Exploitation to the Local Economic Growth in China," Energies, MDPI, vol. 15(16), pages 1-17, August.
    9. Hilmawan, Rian & Clark, Jeremy, 2019. "An investigation of the resource curse in Indonesia," Resources Policy, Elsevier, vol. 64(C).
    10. Shahbaz, Muhammad & Ahmed, Khalid & Tiwari, Aviral Kumar & Jiao, Zhilun, 2019. "Resource Curse Hypothesis and Role of Oil Prices in USA," MPRA Paper 96633, University Library of Munich, Germany, revised 14 Oct 2019.
    11. Xu, Xiaoliang & Xu, Xuefen & Chen, Qian & Che, Ying, 2015. "The impact on regional “resource curse” by coal resource tax reform in China—A dynamic CGE appraisal," Resources Policy, Elsevier, vol. 45(C), pages 277-289.
    12. Abdul Rahim Ridzuan & Mohd Shahidan Shaari & Anita Rosli & Abdul Rahim Md Jamil & Siswantini Siswantini & Arsiyanti Lestari & Shahsuzan Zakaria, 2021. "The Nexus between Economic Growth and Natural Resource Abundance in Selected ASEAN countries before Pandemic Covid-19," International Journal of Energy Economics and Policy, Econjournals, vol. 11(2), pages 281-292.
    13. Rian Hilmawan & Jeremy Clark, 2018. "Resource Dependence and the Causes of Local Economic Growth: An Empirical Investigation," Working Papers in Economics 18/12, University of Canterbury, Department of Economics and Finance.
    14. Magali Dauvin & David Guerreiro, 2016. "The Paradox of Plenty: A Meta-Analysis," EconomiX Working Papers 2016-14, University of Paris Nanterre, EconomiX.
    15. Adabor, Opoku, 2023. "The effect of financial development on natural gas resource rent in Ghana," Resources Policy, Elsevier, vol. 83(C).
    16. Alssadek, Marwan & Benhin, James, 2023. "Natural resource curse: A literature survey and comparative assessment of regional groupings of oil-rich countries," Resources Policy, Elsevier, vol. 84(C).
    17. Zuo, Na & Zhong, Hua, 2019. "The Effect of Resource Wealth on Regional Economic Development in China," 2019 Annual Meeting, July 21-23, Atlanta, Georgia 291114, Agricultural and Applied Economics Association.
    18. Magali Dauvin & David Guerreiro, 2016. "The Paradox of Plenty: A Meta-Analysis," Working Papers hal-04141596, HAL.
    19. Ai, Hongshan & Tan, Xiaoqing & Zhou, Shengwen & Liu, Wen, 2023. "The impact of supportive policy for resource-exhausted cities on carbon emission: Evidence from China," Resources Policy, Elsevier, vol. 85(PB).
    20. Kan Ji & Jan Magnus & Wendun Wang, 2014. "Natural Resources, Institutional Quality, and Economic Growth in China," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 57(3), pages 323-343, March.
    21. Cheng, Zhonghua & Li, Xiang & Wang, Meixiao, 2021. "Resource curse and green economic growth," Resources Policy, Elsevier, vol. 74(C).
    22. Nasiru Inuwa & Sagir Adamu & Mohammed Bello Sani & Abubakar Muhammad Saidu, 2022. "Resource Curse Hypothesis in GCC Member Countries: Evidence from Seemingly Unrelated Regression," Biophysical Economics and Resource Quality, Springer, vol. 7(4), pages 1-10, December.
    23. Hui Hu & Weijun Ran & Yuchen Wei & Xiang Li, 2020. "Do Energy Resource Curse and Heterogeneous Curse Exist in Provinces? Evidence from China," Energies, MDPI, vol. 13(17), pages 1-26, August.
    24. Zhou, Shuai & Qian, Yudan & Farmanesh, Panteha, 2022. "The economic cost of environmental laws: Volatility transmission mechanism and remedies," Resources Policy, Elsevier, vol. 79(C).
    25. Xu, Hangtian & Nakajima, Kentaro, 2013. "The Role of Coal Mine Regulation in Regional Development," PRIMCED Discussion Paper Series 45, Institute of Economic Research, Hitotsubashi University.
    26. Mamoudou Camara, 2023. "Bauxite mining and economic growth in Guinea over the period 1986–2020: empirical evidence from ARDL and NARDL approaches," Mineral Economics, Springer;Raw Materials Group (RMG);Luleå University of Technology, vol. 36(1), pages 157-179, January.
    27. Ahmad, Fayyaz & Draz, Muhammad Umar & Chang, Wei-Yew & Yang, Su-Chang & Su, Lijuan, 2021. "More than the resource curse: Exploring the nexus of natural resource abundance and environmental quality in northwestern China," Resources Policy, Elsevier, vol. 70(C).

Articles

  1. Yan, Zhimin & Park, Sung Y., 2023. "Does high-speed rail reduce local CO2 emissions in China? A counterfactual approach," Energy Policy, Elsevier, vol. 173(C).

    Cited by:

    1. Chen, Yu & Zhao, Changyi & Chen, Shan & Chen, Wenqing & Wan, Kunyang & Wei, Jia, 2023. "Riding the green rails: Exploring the nexus between high-speed trains, green innovation, and carbon emissions," Energy, Elsevier, vol. 282(C).

  2. Myeong Jun Kim & Tram T. H. Nguyen & Sung Y. Park, 2022. "Relationship between household income and socio-political capital in rural Vietnam: a panel quantile regression approach," Applied Economics Letters, Taylor & Francis Journals, vol. 29(10), pages 932-938, June.

    Cited by:

    1. Chen, Huihui & Li, Peng & Li, Qinghai, 2023. "The impact of science and technology services on agricultural income of rural household: An investigation based on the three northeastern provinces of China," Technological Forecasting and Social Change, Elsevier, vol. 191(C).

  3. Kim, Myeong Jun & Canh, Nguyen Phuc & Park, Sung Y., 2021. "Causal relationship among cryptocurrencies: A conditional quantile approach," Finance Research Letters, Elsevier, vol. 42(C).

    Cited by:

    1. Timoth'ee Fabre & Ioane Muni Toke, 2024. "Neural Hawkes: Non-Parametric Estimation in High Dimension and Causality Analysis in Cryptocurrency Markets," Papers 2401.09361, arXiv.org, revised Jan 2024.
    2. Fang, Sheng & Cao, Guangxi & Egan, Paul, 2023. "Forecasting and backtesting systemic risk in the cryptocurrency market," Finance Research Letters, Elsevier, vol. 54(C).

  4. Joo, Young C. & Park, Sung Y., 2021. "The impact of oil price volatility on stock markets: Evidences from oil-importing countries," Energy Economics, Elsevier, vol. 101(C).

    Cited by:

    1. Xiao, Jihong & Chen, Xian & Li, Yang & Wen, Fenghua, 2022. "Oil price uncertainty and stock price crash risk: Evidence from China," Energy Economics, Elsevier, vol. 112(C).
    2. Katarzyna Kuziak & Joanna Górka, 2023. "Dependence Analysis for the Energy Sector Based on Energy ETFs," Energies, MDPI, vol. 16(3), pages 1-30, January.
    3. Sohag, Kazi & Hassan, M. Kabir & Kalina, Irina & Mariev, Oleg, 2023. "The relative response of Russian National Wealth Fund to oil demand, supply and risk shocks," Energy Economics, Elsevier, vol. 123(C).
    4. Wang, Yanlong & Li, Haixia & Altuntaş, Mehmet, 2022. "Volatility in natural resources commodity prices: Evaluating volatility in oil and gas rents," Resources Policy, Elsevier, vol. 77(C).
    5. Liu, Feng & Xu, Jie & Ai, Chunrong, 2023. "Heterogeneous impacts of oil prices on China's stock market: Based on a new decomposition method," Energy, Elsevier, vol. 268(C).
    6. Ziadat, Salem Adel & McMillan, David G. & Herbst, Patrick, 2022. "Oil shocks and equity returns during bull and bear markets: The case of oil importing and exporting nations," Resources Policy, Elsevier, vol. 75(C).
    7. Kuang, Wei, 2023. "The equity-oil hedge: A comparison between volatility and alternative risk frameworks," Energy, Elsevier, vol. 271(C).
    8. Li, Chenchen & Wang, Yudong & Wu, Chongfeng, 2022. "Oil implied volatility and expected stock returns along the worldwide supply chain," Energy Economics, Elsevier, vol. 114(C).
    9. Breen, John David & Hu, Liang, 2021. "The predictive content of oil price and volatility: New evidence on exchange rate forecasting," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 75(C).
    10. Wen Chang, Hao & Chang, Tsangyao, 2023. "How oil price and exchange rate affect stock price in China using Bayesian Quantile_on_Quantile with GARCH approach," The North American Journal of Economics and Finance, Elsevier, vol. 64(C).
    11. Cui xiaozhong, & Yen-Ku, Kuo & Maneengam, Apichit & Cong, Phan The & Quynh, Nguyen Ngoc & Ageli, Mohammed Moosa & Wisetsri, Worakamol, 2022. "Covid-19 and oil and gold price volatilities: Evidence from China market," Resources Policy, Elsevier, vol. 79(C).
    12. Xiuwen Chen, 2023. "Are the shocks of EPU, VIX, and GPR indexes on the oil-stock nexus alike? A time-frequency analysis," Applied Economics, Taylor & Francis Journals, vol. 55(48), pages 5637-5652, October.
    13. Zhang, Chuanguo & Mou, Xinjie & Ye, Shuping, 2022. "How do dynamic jumps in global crude oil prices impact China's industrial sector?," Energy, Elsevier, vol. 249(C).
    14. Zhang, Chuanguo & Shang, Hongli, 2023. "Asymmetry effect of oil price shocks and the lagging effect of oil price jumps: Evidence from China's automobile markets," Energy Policy, Elsevier, vol. 172(C).
    15. Yang, Baochen & Song, Xinyu, 2023. "Does oil price uncertainty matter in firm innovation? Evidence from China," International Review of Financial Analysis, Elsevier, vol. 88(C).
    16. Min Hong & Xiaolei Wang & Zhenghui Li, 2022. "Will Oil Price Volatility Cause Market Panic?," Energies, MDPI, vol. 15(13), pages 1-17, June.
    17. Song, Xinyu & Yang, Baochen, 2022. "Oil price uncertainty, corporate governance and firm performance," International Review of Economics & Finance, Elsevier, vol. 80(C), pages 469-487.
    18. Haykir, Ozkan & Yagli, Ibrahim & Aktekin Gok, Emine Dilara & Budak, Hilal, 2022. "Oil price explosivity and stock return: Do sector and firm size matter?," Resources Policy, Elsevier, vol. 78(C).
    19. Wang, Xiangning & Huang, Qian & Zhang, Shuguang, 2023. "Effects of macroeconomic factors on stock prices for BRICS using the variational mode decomposition and quantile method," The North American Journal of Economics and Finance, Elsevier, vol. 67(C).

  5. Myeong Jun Kim & Sung Y. Park, 2019. "Do gender and age impact the time‐varying Okun's law? Evidence from South Korea," Pacific Economic Review, Wiley Blackwell, vol. 24(5), pages 672-685, December.

    Cited by:

    1. Mindaugas Butkus & Laura Dargenyte-Kacilevièiene & Kristina Matuzevièiute & Janina Šeputiene & Dovile Rupliene, 2023. "Age- and Gender-specific Output-employment Relationship across Economic Sectors," Journal of Economics / Ekonomicky casopis, Institute of Economic Research, Slovak Academy of Sciences, vol. 71(1), pages 3-22, January.

  6. Haiqi Li & Ying Liu & Sung Y. Park, 2018. "Time‐Varying Investor Herding in Chinese Stock Markets," International Review of Finance, International Review of Finance Ltd., vol. 18(4), pages 717-726, December.

    Cited by:

    1. Bao, Te & Ma, Mengzhong & Wen, Yonggang, 2023. "Herding in the non-fungible token (NFT) market," Journal of Behavioral and Experimental Finance, Elsevier, vol. 39(C).
    2. Fu, Jingxue & Wu, Lan, 2021. "Regime-switching herd behavior: Novel evidence from the Chinese A-share market," Finance Research Letters, Elsevier, vol. 39(C).
    3. Oi-Ping Chong & A.N. Bany-Ariffin & Annuar Md Nassir & Junaina Muhammad, 2019. "An Empirical Study of Herding Behaviour in China’s A-Share and B-Share Markets: Evidence of Bidirectional Herding Activities," Capital Markets Review, Malaysian Finance Association, vol. 27(2), pages 37-57.
    4. Hui HONG & Shulin XU & Chien-Chiang LEE, 2020. "Investor Herding in the China Stock Market: An Examination of ChiNext," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(4), pages 47-61, December.

  7. Song, Wonho & Park, Sung Y. & Ryu, Doojin, 2018. "Dynamic conditional relationships between developed and emerging markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 507(C), pages 534-543.

    Cited by:

    1. Jieun Lee & Doojin Ryu, 2019. "The impacts of public news announcements on intraday implied volatility dynamics," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 39(6), pages 656-685, June.
    2. Dohyun CHUN & Hoon CHO & Doojin RYU, 2018. "Macroeconomic Structural Changes in a Leading Emerging Market: The Effects of the Asian Financial Crisis," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(2), pages 22-42, December.
    3. Lee, Jaeram & Lee, Geul & Ryu, Doojin, 2018. "Difference in the intraday return-volume relationships of spots and futures: A quantile regression approach," Economics Discussion Papers 2018-68, Kiel Institute for the World Economy (IfW Kiel).
    4. Biao Guo & Qian Han & Jufang Liang & Doojin Ryu & Jinyoung Yu, 2020. "Sovereign Credit Spread Spillovers in Asia," Sustainability, MDPI, vol. 12(4), pages 1-14, February.
    5. Chun, Dohyun & Cho, Hoon & Ryu, Doojin, 2020. "Economic indicators and stock market volatility in an emerging economy," Economic Systems, Elsevier, vol. 44(2).
    6. Chun, Dohyun & Cho, Hoon & Ryu, Doojin, 2019. "Forecasting the KOSPI200 spot volatility using various volatility measures," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 514(C), pages 156-166.
    7. Sang Ik Seok & Hoon Cho & Chanhi Park & Doojin Ryu, 2019. "Do Overnight Returns Truly Measure Firm-Specific Investor Sentiment in the KOSPI Market?," Sustainability, MDPI, vol. 11(13), pages 1-14, July.
    8. Jung Park, Yuen & Kutan, Ali M. & Ryu, Doojin, 2019. "The impacts of overseas market shocks on the CDS-option basis," The North American Journal of Economics and Finance, Elsevier, vol. 47(C), pages 622-636.
    9. Daehyeon PARK & Doojin RYU, 2021. "Forecasting Stock Market Dynamics using Bidirectional Long Short-Term Memory," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(2), pages 22-34, June.
    10. Lee, Jieun & Ryu, Doojin, 2019. "How does FX liquidity affect the relationship between foreign ownership and stock liquidity?," Emerging Markets Review, Elsevier, vol. 39(C), pages 101-119.
    11. Daehyeon Park & Jiyeon Park & Doojin Ryu, 2020. "Volatility Spillovers between Equity and Green Bond Markets," Sustainability, MDPI, vol. 12(9), pages 1-12, May.

  8. Haiqi Li & Sung Y. Park, 2018. "Testing for a unit root in a nonlinear quantile autoregression framework," Econometric Reviews, Taylor & Francis Journals, vol. 37(8), pages 867-892, September.

    Cited by:

    1. Mohsen Bahmani‐Oskooee & Tsangyao Chang & Farhang Niroomand & Omid Ranjbar, 2020. "Fourier nonlinear quantile unit root test and PPP in Africa," Bulletin of Economic Research, Wiley Blackwell, vol. 72(4), pages 451-481, October.
    2. Yuan, Di & Li, Sufang & Li, Rong & Zhang, Feipeng, 2022. "Economic policy uncertainty, oil and stock markets in BRIC: Evidence from quantiles analysis," Energy Economics, Elsevier, vol. 110(C).
    3. Yi‐Ting Peng & Tsangyao Chang & Omid Ranjbar, 2022. "Analyzing the degree of persistence of economic policy uncertainty using linear and non‐linear fourier quantile unit root tests," Manchester School, University of Manchester, vol. 90(4), pages 453-471, July.
    4. Yang, Yang & Zhao, Zhao, 2020. "Quantile nonlinear unit root test with covariates and an application to the PPP hypothesis," Economic Modelling, Elsevier, vol. 93(C), pages 728-736.
    5. Nazlioglu, Saban & Kucukkaplan, Ilhan & Kilic, Emre & Altuntas, Mehmet, 2022. "Financial market integration of emerging markets: Heavy tails, structural shifts, nonlinearity, and asymmetric persistence," Research in International Business and Finance, Elsevier, vol. 62(C).
    6. Badri Narayan Rath & Vaseem Akram, 2021. "Popularity of Unit Root Tests - A Review," Asian Economics Letters, Asia-Pacific Applied Economics Association, vol. 2(4), pages 1-5.
    7. Li, Haiqi & Zheng, Chaowen, 2018. "Unit root quantile autoregression testing with smooth structural changes," Finance Research Letters, Elsevier, vol. 25(C), pages 83-89.
    8. Badri Narayan Rath & Vaseem Akram, 2022. "Popularity of Unit Root Tests - A Review," Asian Economics Letters, Asia-Pacific Applied Economics Association, vol. 2(4), pages 1-5.
    9. Yang, Jisheng & Wei, Jinbao & Cai, Biqing, 2022. "Quantile unit root inference for panel data with common shocks," Economics Letters, Elsevier, vol. 219(C).

  9. Park, Sung Y. & Ryu, Doojin & Song, Jeongseok, 2017. "The dynamic conditional relationship between stock market returns and implied volatility," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 482(C), pages 638-648.

    Cited by:

    1. Hyein Shim & Maria H. Kim & Doojin Ryu, 2017. "Effects of intraday weather changes on asset returns and volatilities," Zbornik radova Ekonomskog fakulteta u Rijeci/Proceedings of Rijeka Faculty of Economics, University of Rijeka, Faculty of Economics and Business, vol. 35(2), pages 301-330.
    2. Pan, Zhiyuan & Liu, Li, 2018. "Forecasting stock return volatility: A comparison between the roles of short-term and long-term leverage effects," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 492(C), pages 168-180.
    3. Dohyun CHUN & Hoon CHO & Doojin RYU, 2018. "Macroeconomic Structural Changes in a Leading Emerging Market: The Effects of the Asian Financial Crisis," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(2), pages 22-42, December.
    4. Doojin RYU & Hyein SHIM, 2017. "Intraday Dynamics of Asset Returns, Trading Activities, and Implied Volatilities: A Trivariate GARCH Framework," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(2), pages 45-61, June.
    5. Song, Wonho & Park, Sung Y. & Ryu, Doojin, 2018. "Dynamic conditional relationships between developed and emerging markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 507(C), pages 534-543.
    6. Chun, Dohyun & Cho, Hoon & Ryu, Doojin, 2020. "Economic indicators and stock market volatility in an emerging economy," Economic Systems, Elsevier, vol. 44(2).
    7. Chun, Dohyun & Cho, Hoon & Ryu, Doojin, 2019. "Forecasting the KOSPI200 spot volatility using various volatility measures," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 514(C), pages 156-166.
    8. Zhuang, Chunjuan, 2018. "Improving performance of exchange rate momentum strategy using volatility information," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 510(C), pages 741-753.
    9. Daehyeon PARK & Doojin RYU, 2021. "Forecasting Stock Market Dynamics using Bidirectional Long Short-Term Memory," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(2), pages 22-34, June.
    10. Daehyeon Park & Jiyeon Park & Doojin Ryu, 2020. "Volatility Spillovers between Equity and Green Bond Markets," Sustainability, MDPI, vol. 12(9), pages 1-12, May.

  10. Joo, Young C. & Park, Sung Y., 2017. "Oil prices and stock markets: Does the effect of uncertainty change over time?," Energy Economics, Elsevier, vol. 61(C), pages 42-51.

    Cited by:

    1. Nadal, Raquel & Szklo, Alexandre & Lucena, André, 2017. "Time-varying impacts of demand and supply oil shocks on correlations between crude oil prices and stock markets indices," Research in International Business and Finance, Elsevier, vol. 42(C), pages 1011-1020.
    2. Degiannakis, Stavros & Filis, George & Arora, Vipin, 2018. "Oil Prices and Stock Markets: A Review of the Theory and Empirical Evidence," MPRA Paper 96270, University Library of Munich, Germany.
    3. Yufeng Chen & Wenqi Li & Xi Jin, 2018. "Volatility Spillovers between Crude Oil Prices and New Energy Stock Price in China," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(2), pages 43-62, December.
    4. Ahmed, Walid M.A., 2018. "On the interdependence of natural gas and stock markets under structural breaks," The Quarterly Review of Economics and Finance, Elsevier, vol. 67(C), pages 149-161.
    5. Alexey Mikhaylov & Ishaq M. Bhatti & Hasan Dinçer & Serhat Yüksel, 2024. "Integrated decision recommendation system using iteration-enhanced collaborative filtering, golden cut bipolar for analyzing the risk-based oil market spillovers," Computational Economics, Springer;Society for Computational Economics, vol. 63(1), pages 305-338, January.
    6. Ahmed, Walid M.A., 2019. "Islamic and conventional equity markets: Two sides of the same coin, or not?," The Quarterly Review of Economics and Finance, Elsevier, vol. 72(C), pages 191-205.
    7. Liu, Zhenhua & Tseng, Hui-Kuan & Wu, Jy S. & Ding, Zhihua, 2020. "Implied volatility relationships between crude oil and the U.S. stock markets: Dynamic correlation and spillover effects," Resources Policy, Elsevier, vol. 66(C).
    8. Tunc, Ahmet & Kocoglu, Mustafa & Aslan, Alper, 2022. "Time-varying characteristics of the simultaneous interactions between economic uncertainty, international oil prices and GDP: A novel approach for Germany," Resources Policy, Elsevier, vol. 77(C).
    9. Vesarach Aumeboonsuke, 2021. "Commodity Prices and the Stock Market in Thailand," International Journal of Energy Economics and Policy, Econjournals, vol. 11(1), pages 34-40.
    10. Belhassine, Olfa & Karamti, Chiraz, 2021. "Volatility spillovers and hedging effectiveness between oil and stock markets: Evidence from a wavelet-based and structural breaks analysis," Energy Economics, Elsevier, vol. 102(C).
    11. Kyritsis, Evangelos & Serletis, Apostolos, 2017. "The Zero Lower Bound and Market Spillovers: Evidence from the G7 and Norway," Discussion Papers 2017/7, Norwegian School of Economics, Department of Business and Management Science.
    12. Bechir Raggad & Elie Bouri, 2023. "Quantile Dependence between Crude Oil Returns and Implied Volatility: Evidence from Parametric and Nonparametric Tests," Mathematics, MDPI, vol. 11(3), pages 1-23, January.
    13. Shi Chen & Wolfgang Karl Hardle & Brenda L'opez Cabrera, 2020. "Regularization Approach for Network Modeling of German Power Derivative Market," Papers 2009.09739, arXiv.org.
    14. Mushtaq Hussain Khan & Junaid Ahmed & Mazhar Mughal, 2020. "Oil Price Volatility and Stock Returns: Evidence from Three Oil-price Wars," PIDE-Working Papers 2020:22, Pakistan Institute of Development Economics.
    15. You, Wanhai & Guo, Yawei & Zhu, Huiming & Tang, Yong, 2017. "Oil price shocks, economic policy uncertainty and industry stock returns in China: Asymmetric effects with quantile regression," Energy Economics, Elsevier, vol. 68(C), pages 1-18.
    16. Zhifang He & Jiaqi Chen & Fangzhao Zhou & Guoqing Zhang & Fenghua Wen, 2022. "Oil price uncertainty and the risk‐return relation in stock markets: Evidence from oil‐importing and oil‐exporting countries," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(1), pages 1154-1172, January.
    17. Mohamad Husam Helmi & A. Nazif Catik & Begum Yurteri Kosedagli & Gul Serife Huyuguzel Kisla & Coskun Akdeniz, 2023. "The Effects of Energy Prices on Oil-Gas Sectoral Stock Returns for BRIC Countries: Evidence from Space State Models," International Journal of Energy Economics and Policy, Econjournals, vol. 13(6), pages 430-440, November.
    18. Khan, Muhammad Asif & Khan, Farhad & Sharif, Arshian & Suleman, Muhammad Tahir, 2023. "Dynamic linkages between Islamic equity indices, oil prices, gold prices, and news-based uncertainty: New insights from partial and multiple wavelet coherence," Resources Policy, Elsevier, vol. 80(C).
    19. Carlos Medel, 2017. "Geopolitical Tensions, OPEC News, and Oil Price: A Granger Causality Analysis," Working Papers Central Bank of Chile 805, Central Bank of Chile.
    20. Yin, Libo & Feng, Jiabao & Liu, Li & Wang, Yudong, 2019. "It's not that important: The negligible effect of oil market uncertainty," International Review of Economics & Finance, Elsevier, vol. 60(C), pages 62-84.
    21. Zhenhua Liu & Zhihua Ding & Tao Lv & Jy S. Wu & Wei Qiang, 2019. "Financial factors affecting oil price change and oil-stock interactions: a review and future perspectives," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 95(1), pages 207-225, January.
    22. Salah A. Nusair & Jamal A. Al-Khasawneh, 2023. "Changes in oil price and economic policy uncertainty and the G7 stock returns: evidence from asymmetric quantile regression analysis," Economic Change and Restructuring, Springer, vol. 56(3), pages 1849-1893, June.
    23. Kuang, Wei, 2023. "The equity-oil hedge: A comparison between volatility and alternative risk frameworks," Energy, Elsevier, vol. 271(C).
    24. Antonakakis, Nikolaos & Gupta, Rangan & Kollias, Christos & Papadamou, Stephanos, 2017. "Geopolitical risks and the oil-stock nexus over 1899–2016," Finance Research Letters, Elsevier, vol. 23(C), pages 165-173.
    25. Badeeb, Ramez Abubakr & Lean, Hooi Hooi, 2018. "Asymmetric impact of oil price on Islamic sectoral stocks," Energy Economics, Elsevier, vol. 71(C), pages 128-139.
    26. Salah A. Nusair & Jamal A. Al-Khasawneh, 2018. "Oil price shocks and stock market returns of the GCC countries: empirical evidence from quantile regression analysis," Economic Change and Restructuring, Springer, vol. 51(4), pages 339-372, November.
    27. Mensi, Walid & Selmi, Refk & Al-Yahyaee, Khamis Hamed, 2020. "Switching dependence and systemic risk between crude oil and U.S. Islamic and conventional equity markets: A new evidence," Resources Policy, Elsevier, vol. 69(C).
    28. Hou, Yang & Li, Steven & Wen, Fenghua, 2019. "Time-varying volatility spillover between Chinese fuel oil and stock index futures markets based on a DCC-GARCH model with a semi-nonparametric approach," Energy Economics, Elsevier, vol. 83(C), pages 119-143.
    29. Li, Cong & Lin, Shiwei & Sun, Yihan & Afshan, Sahar & Yaqoob, Tanzeela, 2022. "The asymmetric effect of oil price, news-based uncertainty, and COVID-19 pandemic on equity market," Resources Policy, Elsevier, vol. 77(C).
    30. Huang, Jionghao & Li, Ziruo & Xia, Xiaohua, 2021. "Network diffusion of international oil volatility risk in China's stock market: Quantile interconnectedness modelling and shock decomposition analysis," International Review of Economics & Finance, Elsevier, vol. 76(C), pages 1-39.
    31. Huang, Shupei & An, Haizhong & Huang, Xuan & Wang, Yue, 2018. "Do all sectors respond to oil price shocks simultaneously?," Applied Energy, Elsevier, vol. 227(C), pages 393-402.
    32. Ahmed, Walid M.A., 2020. "Corruption and equity market performance: International comparative evidence," Pacific-Basin Finance Journal, Elsevier, vol. 60(C).
    33. Liang, Xuedong & Luo, Peng & Li, Xiaoyan & Wang, Xia & Shu, Lingli, 2023. "Crude oil price prediction using deep reinforcement learning," Resources Policy, Elsevier, vol. 81(C).
    34. Mensi, Walid & Reboredo, Juan C. & Ugolini, Andrea, 2021. "Price-switching spillovers between gold, oil, and stock markets: Evidence from the USA and China during the COVID-19 pandemic," Resources Policy, Elsevier, vol. 73(C).
    35. Mohammad Enamul Hoque & Soo-Wah Low & Mohd Azlan Shah Zaidi, 2020. "The Effects of Oil and Gas Risk Factors on Malaysian Oil and Gas Stock Returns: Do They Vary?," Energies, MDPI, vol. 13(15), pages 1-22, July.
    36. Tian, Maoxi & Alshater, Muneer M. & Yoon, Seong-Min, 2022. "Dynamic risk spillovers from oil to stock markets: Fresh evidence from GARCH copula quantile regression-based CoVaR model," Energy Economics, Elsevier, vol. 115(C).
    37. Gutierrez, Juan P. & Vianna, Andre C., 2020. "Price effects of steel commodities on worldwide stock market returns," The North American Journal of Economics and Finance, Elsevier, vol. 51(C).
    38. Hashmi, Shabir Mohsin & Chang, Bisharat Hussain & Bhutto, Niaz Ahmed, 2021. "Asymmetric effect of oil prices on stock market prices: New evidence from oil-exporting and oil-importing countries," Resources Policy, Elsevier, vol. 70(C).
    39. Begüm Yurteri Kösedağlı & Gül Huyugüzel Kışla & A. Nazif Çatık, 2021. "The time-varying effects of oil prices on oil–gas stock returns of the fragile five countries," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 7(1), pages 1-22, December.
    40. Caporale, Guglielmo Maria & Çatık, Abdurrahman Nazif & Huyuguzel Kısla, Gul Serife & Helmi, Mohamad Husam & Akdeniz, Coşkun, 2022. "Oil prices and sectoral stock returns in the BRICS-T countries: A time-varying approach," Resources Policy, Elsevier, vol. 79(C).
    41. Corbet, Shaen & Hou, Yang (Greg) & Hu, Yang & Oxley, Les, 2021. "An analysis of investor behaviour and information flows surrounding the negative WTI oil price futures event," Energy Economics, Elsevier, vol. 104(C).
    42. Mushtaq Hussain Khan & Junaid Ahmed & Mazhar Mughal, 2022. "Dependence between oil price changes and sectoral stock returns in Pakistan: Evidence from a quantile regression approach," Energy & Environment, , vol. 33(2), pages 315-331, March.
    43. Mensi, Walid & Rehman, Mobeen Ur & Al-Yahyaee, Khamis Hamed & Vo, Xuan Vinh, 2023. "Frequency dependence between oil futures and international stock markets and the role of gold, bonds, and uncertainty indices: Evidence from partial and multivariate wavelet approaches," Resources Policy, Elsevier, vol. 80(C).
    44. Chang, Bisharat Hussain & Sharif, Arshian & Aman, Ameenullah & Suki, Norazah Mohd & Salman, Asma & Khan, Syed Abdul Rehman, 2020. "The asymmetric effects of oil price on sectoral Islamic stocks: New evidence from quantile-on-quantile regression approach," Resources Policy, Elsevier, vol. 65(C).

  11. Ma, Wei & Li, Haiqi & Park, Sung Y., 2017. "Empirical conditional quantile test for purchasing power parity: Evidence from East Asian countries," International Review of Economics & Finance, Elsevier, vol. 49(C), pages 211-222.

    Cited by:

    1. Oladunjoye Opeyemi Nathaniel, 2019. "Validity of Purchasing Power Parity (PPP) Hypothesis in the Ecowas (1980–2017)," Emerging Economy Studies, International Management Institute, vol. 5(2), pages 141-156, November.
    2. Kai-Hua WANG & Chi-Wei SU & Hsu-Ling CHANG & Ji MA & Cristina IOVU, 2017. "Purchasing Power Parity In China: An Empirical Investigation Based On Bootstrap Rollingwindow Test," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(4), pages 166-181, December.
    3. Chen, Rongda & Wang, Shengnan & Jin, Chenglu & Yu, Jingjing & Zhang, Xinyu & Zhang, Shuonan, 2023. "Comovements between multidimensional investor sentiment and returns on internet financial products," International Review of Financial Analysis, Elsevier, vol. 85(C).
    4. Lee, Yi-Lung & Ranjbar, Omid & Jahangard, Fateme & Chang, Tsangyao, 2020. "Analyzing slowdown and meltdowns in the African countries: New evidence using Fourier quantile unit root test," International Review of Economics & Finance, Elsevier, vol. 65(C), pages 187-198.
    5. Li, Haiqi & Zheng, Chaowen, 2018. "Unit root quantile autoregression testing with smooth structural changes," Finance Research Letters, Elsevier, vol. 25(C), pages 83-89.
    6. S. M. Woahid Murad & Mohammad Amzad Hossain, 2018. "The ASEAN experience of the purchasing power parity theory," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 4(1), pages 1-10, December.
    7. Hendriks, Johannes Jurgens & Bonga-Bonga, Lumengo, 2022. "Testing for the purchasing power parity (PPP) hypothesis between South Africa and its main trading partners: application of the quantile approach," MPRA Paper 112915, University Library of Munich, Germany.

  12. Haiqi Li & Yu Guo & Sung Y. Park, 2017. "Asymmetric Relationship between Investors' Sentiment and Stock Returns: Evidence from a Quantile Non†causality Test," International Review of Finance, International Review of Finance Ltd., vol. 17(4), pages 617-626, December.

    Cited by:

    1. Yong Jiang & Zhongbao Zhou, 2018. "Does the time horizon of the return predictive effect of investor sentiment vary with stock characteristics? A Granger causality analysis in the frequency domain," Papers 1803.02962, arXiv.org.
    2. Hela Namouri & Fredj Jawadi & Zied Ftiti & Néjib Hachicha, 2018. "Threshold effect in the relationship between investor sentiment and stock market returns: a PSTR specification," Applied Economics, Taylor & Francis Journals, vol. 50(5), pages 559-573, January.
    3. Raquel M. Gaspar & Xu Jiaming, 2023. "Consumer Confidence and Stock Markets' Returns," Working Papers REM 2023/0292, ISEG - Lisbon School of Economics and Management, REM, Universidade de Lisboa.
    4. Gizelle D. Willows & Daniel W. Richards, 2023. "Buy and buy again: The impact of unique reference points on (re)purchase decisions," International Review of Finance, International Review of Finance Ltd., vol. 23(2), pages 301-316, June.
    5. Jiang, Yong & Ren, Yi-Shuai & Narayan, Seema & Ma, Chao-Qun & Yang, Xiao-Guang, 2022. "Heterogeneity dependence between oil prices and exchange rate: Evidence from a parametric test of Granger causality in quantiles," The North American Journal of Economics and Finance, Elsevier, vol. 62(C).
    6. Ahmed, Bouteska, 2020. "Understanding the impact of investor sentiment on the price formation process: A review of the conduct of American stock markets," The Journal of Economic Asymmetries, Elsevier, vol. 22(C).
    7. Yousra Trichilli & Mouna Abdelhédi & Mouna Boujelbène Abbes, 2020. "The thermal optimal path model: Does Google search queries help to predict dynamic relationship between investor’s sentiment and indexes returns?," Journal of Asset Management, Palgrave Macmillan, vol. 21(3), pages 261-279, May.
    8. Naeem, Muhammad Abubakr & Farid, Saqib & Faruk, Balli & Shahzad, Syed Jawad Hussain, 2020. "Can happiness predict future volatility in stock markets?," Research in International Business and Finance, Elsevier, vol. 54(C).
    9. Golab, Anna & Bannigidadmath, Deepa & Pham, Thach Ngoc & Thuraisamy, Kannan, 2022. "Economic policy uncertainty and industry return predictability – Evidence from the UK," International Review of Economics & Finance, Elsevier, vol. 82(C), pages 433-447.
    10. Emre Cevik & Buket Kirci Altinkeski & Emrah Ismail Cevik & Sel Dibooglu, 2022. "Investor sentiments and stock markets during the COVID-19 pandemic," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 8(1), pages 1-34, December.
    11. Zorio-Grima, Ana & Merello, Paloma, 2020. "Consumer confidence: Causality links with subjective and objective information sources," Technological Forecasting and Social Change, Elsevier, vol. 150(C).
    12. Pham, Linh & Cepni, Oguzhan, 2022. "Extreme directional spillovers between investor attention and green bond markets," International Review of Economics & Finance, Elsevier, vol. 80(C), pages 186-210.

  13. Li, Haiqi & Zhong, Wanling & Park, Sung Y., 2016. "Generalized cross-spectral test for nonlinear Granger causality with applications to money–output and price–volume relations," Economic Modelling, Elsevier, vol. 52(PB), pages 661-671.

    Cited by:

    1. Balcilar, Mehmet & Bouri, Elie & Gupta, Rangan & Roubaud, David, 2017. "Can volume predict Bitcoin returns and volatility? A quantiles-based approach," Economic Modelling, Elsevier, vol. 64(C), pages 74-81.
    2. Mehmet Balcilar & Elie Bouri & Rangan Gupta & David Roubaud, 2016. "Can Volume Predict Bitcoin Returns and Volatility? A Nonparametric Causality-in-Quantiles Approach," Working Papers 201662, University of Pretoria, Department of Economics.
    3. Kao, Yu-Sheng & Zhao, Kai & Chuang, Hwei-Lin & Ku, Yu-Cheng, 2024. "The asymmetric relationships between the Bitcoin futures’ return, volatility, and trading volume," International Review of Economics & Finance, Elsevier, vol. 89(PA), pages 524-542.
    4. Park, Sung Y. & Ryu, Doojin & Song, Jeongseok, 2017. "The dynamic conditional relationship between stock market returns and implied volatility," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 482(C), pages 638-648.
    5. Kobana Abukari & Tov Assogbavi, 2019. "Price-Volume Granger Causality Tests in the Egyptian Stock Exchange (EGX)," Accounting and Finance Research, Sciedu Press, vol. 8(3), pages 1-48, August.

  14. Bera Anil K. & Galvao Antonio F. & Montes-Rojas Gabriel V. & Park Sung Y., 2016. "Asymmetric Laplace Regression: Maximum Likelihood, Maximum Entropy and Quantile Regression," Journal of Econometric Methods, De Gruyter, vol. 5(1), pages 79-101, January.

    Cited by:

    1. Bernstein, David H. & Parmeter, Christopher F. & Tsionas, Mike G., 2023. "On the performance of the United States nuclear power sector: A Bayesian approach," Energy Economics, Elsevier, vol. 125(C).
    2. Javier Alejo & Antonio F. Galvao & Julian Martinez-Iriarte & Gabriel Montes-Rojas, 2023. "Unconditional Quantile Partial Effects via Conditional Quantile Regression," Papers 2301.07241, arXiv.org, revised Dec 2023.
    3. Bajgiran, Amirsaman H. & Mardikoraem, Mahsa & Soofi, Ehsan S., 2021. "Maximum entropy distributions with quantile information," European Journal of Operational Research, Elsevier, vol. 290(1), pages 196-209.
    4. Ren, Xiaohang & Lu, Zudi & Cheng, Cheng & Shi, Yukun & Shen, Jian, 2019. "On dynamic linkages of the state natural gas markets in the USA: Evidence from an empirical spatio-temporal network quantile analysis," Energy Economics, Elsevier, vol. 80(C), pages 234-252.
    5. Hyung-Gun Kim & Kwong-Chin Hung & Sung Park, 2015. "Determinants of Housing Prices in Hong Kong: A Box-Cox Quantile Regression Approach," The Journal of Real Estate Finance and Economics, Springer, vol. 50(2), pages 270-287, February.
    6. Cheng Cheng & Xiaohang Ren & Zhen Wang & Yukun Shi, 2018. "The Impacts of Non-Fossil Energy, Economic Growth, Energy Consumption, and Oil Price on Carbon Intensity: Evidence from a Panel Quantile Regression Analysis of EU 28," Sustainability, MDPI, vol. 10(11), pages 1-20, November.
    7. Davidmac O. Ekeocha & Jonathan E. Ogbuabor & Oliver E. Ogbonna & Anthony Orji, 2023. "Economic policy uncertainty, governance institutions and economic performance in Africa: are there regional differences?," Economic Change and Restructuring, Springer, vol. 56(3), pages 1367-1431, June.
    8. Chen, Hongrui, 2023. "Energy innovations, natural resource abundance, urbanization, and environmental sustainability in the post-covid era. Does environmental regulation matter?," Resources Policy, Elsevier, vol. 85(PB).
    9. Gyamfi, Bright Akwasi & Bein, Murad A. & Udemba, Edmund Ntom & Bekun, Festus Victor, 2021. "Investigating the pollution haven hypothesis in oil and non-oil sub-Saharan Africa countries: Evidence from quantile regression technique," Resources Policy, Elsevier, vol. 73(C).
    10. Melike E. Bildirici & Rui Alexandre Castanho & Fazıl Kayıkçı & Sema Yılmaz Genç, 2022. "ICT, Energy Intensity, and CO 2 Emission Nexus," Energies, MDPI, vol. 15(13), pages 1-15, June.
    11. Volkan Han & Oguz Ocal & Alper Aslan, 2023. "A revisit to the relationship between globalization and income inequality: are levels of development really paramount?," Quality & Quantity: International Journal of Methodology, Springer, vol. 57(1), pages 973-990, February.
    12. Yuxiao Jiang & Xinyu Han & Ning Qiu & Mengbing Du & Liang Zhao, 2023. "Identifying Urban–Rural Disparities and Associated Factors in the Prevalence of Disabilities in Tianjin, China," Land, MDPI, vol. 12(8), pages 1-20, July.
    13. Xu, Bin & Lin, Boqiang, 2016. "A quantile regression analysis of China's provincial CO2 emissions: Where does the difference lie?," Energy Policy, Elsevier, vol. 98(C), pages 328-342.
    14. Ellen Thio & MeiXuen Tan & Liang Li & Muhammad Salman & Xingle Long & Huaping Sun & Bangzhu Zhu, 2022. "The estimation of influencing factors for carbon emissions based on EKC hypothesis and STIRPAT model: Evidence from top 10 countries," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 24(9), pages 11226-11259, September.
    15. Alfredo Cartone & Paolo Postiglione, 2016. "Modelli spaziali di regressione quantilica per l?analisi della convergenza economica regionale," RIVISTA DI ECONOMIA E STATISTICA DEL TERRITORIO, FrancoAngeli Editore, vol. 2016(3), pages 28-48.
    16. de Castro, Luciano & Galvao, Antonio F. & Montes-Rojas, Gabriel, 2020. "Quantile selection in non-linear GMM quantile models," Economics Letters, Elsevier, vol. 195(C).

  15. Kim, Myeong Jun & Park, Sung Y., 2016. "Optimal conditional hedge ratio: A simple shrinkage estimation approach," Journal of Empirical Finance, Elsevier, vol. 38(PA), pages 139-156.

    Cited by:

    1. Yang (Greg) Hou & Mark Holmes, 2020. "Do higher order moments of return distribution provide better decisions in minimum-variance hedging? Evidence from US stock index futures," Australian Journal of Management, Australian School of Business, vol. 45(2), pages 240-265, May.
    2. Corbet, Shaen & Hou, Yang (Greg) & Hu, Yang & Oxley, Les, 2022. "The influence of the COVID-19 pandemic on the hedging functionality of Chinese financial markets," Research in International Business and Finance, Elsevier, vol. 59(C).
    3. Hou, Yang & Holmes, Mark, 2017. "On the effects of static and autoregressive conditional higher order moments on dynamic optimal hedging," MPRA Paper 82000, University Library of Munich, Germany.
    4. K. Abhaya Kumar & Prakash Pinto & Iqbal Thonse Hawaldar & K. G. Ramesh, 2021. "Can Crude Oil Futures be the Good Hedging Tool for Tyre Equities? Evidence from India," International Journal of Energy Economics and Policy, Econjournals, vol. 11(6), pages 523-537.

  16. Li, Haiqi & Kim, Myeong Jun & Park, Sung Y., 2016. "Nonlinear relationship between crude oil price and net futures positions: A dynamic conditional distribution approach," International Review of Financial Analysis, Elsevier, vol. 44(C), pages 217-225.

    Cited by:

    1. Dedi, Valentina & Mandilaras, Alex, 2022. "Trader positions and the price of oil in the futures market," International Review of Economics & Finance, Elsevier, vol. 82(C), pages 448-460.
    2. Babalos, Vassilios & Balcilar, Mehmet, 2017. "Does institutional trading drive commodities prices away from their fundamentals: Evidence from a nonparametric causality-in-quantiles test," Finance Research Letters, Elsevier, vol. 21(C), pages 126-131.

  17. Ding, Haoyuan & Kim, Hyung-Gun & Park, Sung Y., 2016. "Crude oil and stock markets: Causal relationships in tails?," Energy Economics, Elsevier, vol. 59(C), pages 58-69.

    Cited by:

    1. Haoyuan Ding & Yuying Jin & Cong Qin & Jiezhou Ying, 2020. "Tail Causality between Crude Oil Price and RMB Exchange Rate," China & World Economy, Institute of World Economics and Politics, Chinese Academy of Social Sciences, vol. 28(3), pages 116-134, May.
    2. Mensi, Walid & Hammoudeh, Shawkat & Shahzad, Syed Jawad Hussain & Shahbaz, Muhammad, 2017. "Modeling systemic risk and dependence structure between oil and stock markets using a variational mode decomposition-based copula method," Journal of Banking & Finance, Elsevier, vol. 75(C), pages 258-279.
    3. Jose Eduardo Gomez-Gonzalez & Jorge Hirs-Garzon, 2017. "Uncovering the time-varying nature of causality between oil prices and stock market returns: A multi-country study," Borradores de Economia 1009, Banco de la Republica de Colombia.
    4. Misund, Bard, 2016. "Common and Fundamental Risk Factors in Shareholder Returns of Norwegian Salmon Producing Companies," UiS Working Papers in Economics and Finance 2016/17, University of Stavanger.
    5. Escribano, Ana & Koczar, Monika W. & Jareño, Francisco & Esparcia, Carlos, 2023. "Shock transmission between crude oil prices and stock markets," Resources Policy, Elsevier, vol. 83(C).
    6. Suresh Kumar & Ankit Kumar & Gurcharan Singh, 2023. "Causal relationship among international crude oil, gold, exchange rate, and stock market: Fresh evidence from NARDL testing approach," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 28(1), pages 47-57, January.
    7. Reboredo, Juan C. & Ugolini, Andrea, 2017. "Quantile causality between gold commodity and gold stock prices," Resources Policy, Elsevier, vol. 53(C), pages 56-63.
    8. Nadal, Raquel & Szklo, Alexandre & Lucena, André, 2017. "Time-varying impacts of demand and supply oil shocks on correlations between crude oil prices and stock markets indices," Research in International Business and Finance, Elsevier, vol. 42(C), pages 1011-1020.
    9. Pal, Debdatta & Mitra, Subrata K., 2019. "Oil price and automobile stock return co-movement: A wavelet coherence analysis," Economic Modelling, Elsevier, vol. 76(C), pages 172-181.
    10. Degiannakis, Stavros & Filis, George & Arora, Vipin, 2018. "Oil Prices and Stock Markets: A Review of the Theory and Empirical Evidence," MPRA Paper 96270, University Library of Munich, Germany.
    11. Hussain, Saiful Izzuan & Nur-Firyal, R. & Ruza, Nadiah, 2022. "Linkage transitions between oil and the stock markets of countries with the highest COVID-19 cases," Journal of Commodity Markets, Elsevier, vol. 28(C).
    12. Mokni, Khaled & Ajmi, Ahdi Noomen, 2021. "Cryptocurrencies vs. US dollar: Evidence from causality in quantiles analysis," Economic Analysis and Policy, Elsevier, vol. 69(C), pages 238-252.
    13. Jiang, Yong & Ren, Yi-Shuai & Narayan, Seema & Ma, Chao-Qun & Yang, Xiao-Guang, 2022. "Heterogeneity dependence between oil prices and exchange rate: Evidence from a parametric test of Granger causality in quantiles," The North American Journal of Economics and Finance, Elsevier, vol. 62(C).
    14. Qin Zhang & Jin Boon Wong, 2023. "The influence of oil price uncertainty on stock liquidity," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 43(2), pages 141-167, February.
    15. Gomez-Gonzalez, Jose E. & Hirs-Garzón, Jorge & Sanín-Restrepo, Sebastián, 2021. "Dynamic relations between oil and stock markets: Volatility spillovers, networks and causality," International Economics, Elsevier, vol. 165(C), pages 37-50.
    16. Leong, Soon Heng, 2021. "Global crude oil and the Chinese oil-intensive sectors: A comprehensive causality study," Energy Economics, Elsevier, vol. 103(C).
    17. Ramzi Benkraiem & Thi Hong Van Hoang & Amine Lahiani & Anthony Miloudi, 2018. "Crude oil and equity markets in major European countries: New evidence," Post-Print hal-01914607, HAL.
    18. Alexopoulos, Thomas A., 2018. "To trust or not to trust? A comparative study of conventional and clean energy exchange-traded funds," Energy Economics, Elsevier, vol. 72(C), pages 97-107.
    19. Liu, Zhenhua & Shi, Xunpeng & Zhai, Pengxiang & Wu, Shan & Ding, Zhihua & Zhou, Yuqin, 2021. "Tail risk connectedness in the oil-stock nexus: Evidence from a novel quantile spillover approach," Resources Policy, Elsevier, vol. 74(C).
    20. Troster, Victor & Bouri, Elie & Roubaud, David, 2019. "A quantile regression analysis of flights-to-safety with implied volatilities," Resources Policy, Elsevier, vol. 62(C), pages 482-495.
    21. Kyritsis, Evangelos & Serletis, Apostolos, 2017. "The Zero Lower Bound and Market Spillovers: Evidence from the G7 and Norway," Discussion Papers 2017/7, Norwegian School of Economics, Department of Business and Management Science.
    22. Stavros Stavroyiannis, 2022. "Cointegration and ARDL specification between the Dubai crude oil and the US natural gas market," Papers 2206.03278, arXiv.org.
    23. Jin Boon Wong, 2021. "Stock market reactions to different types of oil shocks: Evidence from China," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 41(2), pages 179-193, February.
    24. Fang, Sheng & Egan, Paul, 2018. "Measuring contagion effects between crude oil and Chinese stock market sectors," The Quarterly Review of Economics and Finance, Elsevier, vol. 68(C), pages 31-38.
    25. Jing Hao & Feng He & Feng Ma & Tong Fu, 2023. "Trading around the clock: Revisit volatility spillover between crude oil and equity markets in different trading sessions," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 43(6), pages 771-791, June.
    26. Liu, Xiang-dong & Pan, Fei & Cai, Wen-li & Peng, Rui, 2020. "Correlation and risk measurement modeling: A Markov-switching mixed Clayton copula approach," Reliability Engineering and System Safety, Elsevier, vol. 197(C).
    27. Salisu, Afees A. & Isah, Kazeem O., 2017. "Revisiting the oil price and stock market nexus: A nonlinear Panel ARDL approach," Economic Modelling, Elsevier, vol. 66(C), pages 258-271.
    28. Xiao, Di & Wang, Jun, 2020. "Dynamic complexity and causality of crude oil and major stock markets," Energy, Elsevier, vol. 193(C).
    29. Peng, Cheng & Zhu, Huiming & Guo, Yawei & Chen, Xiuyun, 2018. "Risk spillover of international crude oil to China's firms: Evidence from granger causality across quantile," Energy Economics, Elsevier, vol. 72(C), pages 188-199.
    30. Bianchi, Robert J. & Fan, John Hua & Todorova, Neda, 2020. "Financialization and de-financialization of commodity futures: A quantile regression approach," International Review of Financial Analysis, Elsevier, vol. 68(C).
    31. Adekunle, Wasiu & Bagudo, Abubakar M. & Odumosu, Monsuru & Inuolaji, Suraj B., 2020. "Predicting stock returns using crude oil prices: A firm level analysis of Nigeria's oil and gas sector," Resources Policy, Elsevier, vol. 68(C).
    32. Bajo-Buenestado, Raúl, 2018. "Relationship-specificity, incomplete contracts, and the pattern of trade: A comment on the role of natural resources," Energy Economics, Elsevier, vol. 75(C), pages 410-422.
    33. Lin, Ling & Kuang, Yuanpei & Jiang, Yong & Su, Xianfang, 2019. "Assessing risk contagion among the Brent crude oil market, London gold market and stock markets: Evidence based on a new wavelet decomposition approach," The North American Journal of Economics and Finance, Elsevier, vol. 50(C).
    34. Wen, Danyan & Wang, Gang-Jin & Ma, Chaoqun & Wang, Yudong, 2019. "Risk spillovers between oil and stock markets: A VAR for VaR analysis," Energy Economics, Elsevier, vol. 80(C), pages 524-535.
    35. Gomez-Gonzalez, Jose Eduardo & Hirs-Garzon, Jorge & Uribe, Jorge M., 2020. "Spillovers beyond the variance: exploring the natural gas and oil higher order risk linkages with the global financial markets," Working papers 46, Red Investigadores de Economía.
    36. Zhao, Zhao & Wen, Huwei & Li, Ke, 2021. "Identifying bubbles and the contagion effect between oil and stock markets: New evidence from China," Economic Modelling, Elsevier, vol. 94(C), pages 780-788.
    37. Hadhri, Sinda, 2021. "The nexus, downside risk and asset allocation between oil and Islamic stock markets: A cross-country analysis," Energy Economics, Elsevier, vol. 101(C).
    38. Ahmed A. Elamer & Bassam A. Elbialy & Kholoud A. Alsaab & Mohamed A. Khashan, 2022. "The Impact of COVID-19 on the Relationship between Non-Renewable Energy and Saudi Stock Market Sectors Using Wavelet Coherence Approach and Neural Networks," Sustainability, MDPI, vol. 14(21), pages 1-24, November.
    39. Gomez-Gonzalez, Jose E. & Hirs-Garzon, Jorge & Gamboa-Arbelaez, Juliana, 2020. "Dynamic relations between oil and stock market returns: A multi-country study," The North American Journal of Economics and Finance, Elsevier, vol. 51(C).
    40. Fenech, Jean-Pierre & Vosgha, Hamed, 2019. "Oil price and Gulf Corporation Council stock indices: New evidence from time-varying copula models," Economic Modelling, Elsevier, vol. 77(C), pages 81-91.
    41. Mensi, Walid & Vo, Xuan Vinh & Kang, Sang Hoon, 2022. "COVID-19 pandemic’s impact on intraday volatility spillover between oil, gold, and stock markets," Economic Analysis and Policy, Elsevier, vol. 74(C), pages 702-715.
    42. Jammazi, Rania & Ferrer, Román & Jareño, Francisco & Shahzad, Syed Jawad Hussain, 2017. "Time-varying causality between crude oil and stock markets: What can we learn from a multiscale perspective?," International Review of Economics & Finance, Elsevier, vol. 49(C), pages 453-483.
    43. Mensi, Walid & Selmi, Refk & Al-Yahyaee, Khamis Hamed, 2020. "Switching dependence and systemic risk between crude oil and U.S. Islamic and conventional equity markets: A new evidence," Resources Policy, Elsevier, vol. 69(C).
    44. Chen, Qitong & Zhu, Huiming & Yu, Dongwei & Hau, Liya, 2022. "How does investor attention matter for crude oil prices and returns? Evidence from time-frequency quantile causality analysis," The North American Journal of Economics and Finance, Elsevier, vol. 59(C).
    45. Sheng Fang & Paul Egan, 2021. "Tail dependence between oil prices and China's A‐shares: Evidence from firm‐level data," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(1), pages 1469-1487, January.
    46. Hassan, Kamrul & Hoque, Ariful & Gasbarro, Dominic, 2019. "Separating BRIC using Islamic stocks and crude oil: dynamic conditional correlation and volatility spillover analysis," Energy Economics, Elsevier, vol. 80(C), pages 950-969.
    47. Naeem, Muhammad Abubakr & Mbarki, Imen & Shahzad, Syed Jawad Hussain, 2021. "Predictive role of online investor sentiment for cryptocurrency market: Evidence from happiness and fears," International Review of Economics & Finance, Elsevier, vol. 73(C), pages 496-514.
    48. Stoupos, Nikolaos & Kiohos, Apostolos, 2021. "Energy commodities and advanced stock markets: A post-crisis approach," Resources Policy, Elsevier, vol. 70(C).
    49. Jiang, Yong & Wang, Gang-Jin & Ma, Chaoqun & Yang, Xiaoguang, 2021. "Do credit conditions matter for the impact of oil price shocks on stock returns? Evidence from a structural threshold VAR model," International Review of Economics & Finance, Elsevier, vol. 72(C), pages 1-15.
    50. Adams, Zeno & Collot, Solène & Kartsakli, Maria, 2020. "Have commodities become a financial asset? Evidence from ten years of Financialization," Energy Economics, Elsevier, vol. 89(C).
    51. Hassan, Kamrul & Hoque, Ariful & Wali, Muammer & Gasbarro, Dominic, 2020. "Islamic stocks, conventional stocks, and crude oil: Directional volatility spillover analysis in BRICS," Energy Economics, Elsevier, vol. 92(C).
    52. Jin Boon Wong & Qin Zhang, 2020. "Impact of international energy prices on China's industries," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 40(5), pages 722-748, May.
    53. Stephanos Papadamou & Νikolaos A. Kyriazis & Panayiotis G. Tzeremes, 2020. "US non-linear causal effects on global equity indices in Normal times versus unconventional eras," International Economics and Economic Policy, Springer, vol. 17(2), pages 381-407, May.
    54. Yin, Libo & Feng, Jiabao, 2019. "Can investors attention on oil markets predict stock returns?," The North American Journal of Economics and Finance, Elsevier, vol. 48(C), pages 786-800.
    55. Tim Friedhoff & Cam-Duc Au & Philippe Krahnhof, 2023. "Analysis of the Impact of Orthogonalized Brent Oil Price Shocks on the Returns of Dependent Industries in Times of the Russian War," MUNI ECON Working Papers 2023-04, Masaryk University.
    56. Mokni, Khaled & Mansouri, Faysal, 2017. "Conditional dependence between international stock markets: A long memory GARCH-copula model approach," Journal of Multinational Financial Management, Elsevier, vol. 42, pages 116-131.
    57. Misund, Bård, 2018. "Common and fundamental risk factors in shareholder returns of Norwegian salmon producing companies," Journal of Commodity Markets, Elsevier, vol. 12(C), pages 19-30.
    58. Mensi, Walid & Rehman, Mobeen Ur & Al-Yahyaee, Khamis Hamed & Vo, Xuan Vinh, 2023. "Frequency dependence between oil futures and international stock markets and the role of gold, bonds, and uncertainty indices: Evidence from partial and multivariate wavelet approaches," Resources Policy, Elsevier, vol. 80(C).

  18. Rui Fan & Haiqi Li & Sung Y. Park, 2016. "Estimation and Hedging Effectiveness of Time‐Varying Hedge Ratio: Nonparametric Approaches," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 36(10), pages 968-991, October.

    Cited by:

    1. Caporin, Massimiliano & Malik, Farooq, 2020. "Do structural breaks in volatility cause spurious volatility transmission?," Journal of Empirical Finance, Elsevier, vol. 55(C), pages 60-82.
    2. Farooq Malik, 2022. "Volatility spillover among sector equity returns under structural breaks," Review of Quantitative Finance and Accounting, Springer, vol. 58(3), pages 1063-1080, April.
    3. Corbet, Shaen & Hou, Yang (Greg) & Hu, Yang & Oxley, Les, 2022. "The influence of the COVID-19 pandemic on the hedging functionality of Chinese financial markets," Research in International Business and Finance, Elsevier, vol. 59(C).
    4. Pan, Zhiyuan & Xiao, Dongli & Dong, Qingma & Liu, Li, 2022. "Structural breaks, macroeconomic fundamentals and cross hedge ratio," Finance Research Letters, Elsevier, vol. 47(PA).
    5. Kim, Myeong Jun & Park, Sung Y., 2016. "Optimal conditional hedge ratio: A simple shrinkage estimation approach," Journal of Empirical Finance, Elsevier, vol. 38(PA), pages 139-156.
    6. Ikram Jebabli & David Roubaud, 2018. "Time-varying efficiency in food and energy markets: Evidence and implications," Post-Print hal-02330557, HAL.
    7. You‐How Go & Jia‐Jun Teo & Kam Fong Chan, 2023. "The effectiveness of crude oil futures hedging during infectious disease outbreaks in the 21st century," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 43(11), pages 1559-1575, November.
    8. Bai, Yujuan & Pan, Zhiyuan & Liu, Li, 2019. "Improving futures hedging performance using option information: Evidence from the S&P 500 index," Finance Research Letters, Elsevier, vol. 28(C), pages 112-117.
    9. Li Liu & Zhiyuan Pan & Yudong Wang, 2021. "What can we learn from the return predictability over the business cycle?," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(1), pages 108-131, January.

  19. Sung Y. Park & Sang Hyuck Kim, 2016. "Determinants of systematic risk in the US Restaurant industry," Tourism Economics, , vol. 22(3), pages 621-628, June.

    Cited by:

    1. Madhusmita Bhadra & Doyeon Kim, 2023. "Income elasticity of demand and stock market beta," International Finance, Wiley Blackwell, vol. 26(2), pages 225-240, August.

  20. Li, Haiqi & Kim, Hyung-Gun & Park, Sung Y., 2015. "The role of financial speculation in the energy future markets: A new time-varying coefficient approach," Economic Modelling, Elsevier, vol. 51(C), pages 112-122.

    Cited by:

    1. Wu, Nan & Wen, Fenghua & Gong, Xu, 2022. "Marionettes behind co-movement of commodity prices: Roles of speculative and hedging activities," Energy Economics, Elsevier, vol. 115(C).
    2. Narayan, Paresh Kumar & Phan, Dinh Hoang Bach & Thuraisamy, Kannan & Westerlund, Joakim, 2016. "Price discovery and asset pricing," Pacific-Basin Finance Journal, Elsevier, vol. 40(PA), pages 224-235.
    3. Juan Ignacio Guzmán & Enrique Silva, 2018. "Copper price determination: fundamentals versus non-fundamentals," Mineral Economics, Springer;Raw Materials Group (RMG);Luleå University of Technology, vol. 31(3), pages 283-300, October.
    4. Zhu, Xuehong & Zhang, Hongwei & Zhong, Meirui, 2017. "Volatility forecasting using high frequency data: The role of after-hours information and leverage effects," Resources Policy, Elsevier, vol. 54(C), pages 58-70.
    5. Yanhong Feng & Xiaolei Wang & Shuanglian Chen & Yanqiong Liu, 2022. "Impact of Oil Financialization on Oil Price Fluctuation: A Perspective of Heterogeneity," Energies, MDPI, vol. 15(12), pages 1-20, June.
    6. Chen, Rongda & Wang, Shengnan & Ye, Mengya & Jin, Chenglu & Ren, He & Chen, Shu, 2022. "Cross-Market Investor Sentiment of Energy Futures and Return Comovements," Finance Research Letters, Elsevier, vol. 49(C).

  21. Myeong Jun Kim & Sung Y. Park & Sang Young Jei, 2015. "An empirical test for Okun's law using a smooth time-varying parameter approach: evidence from East Asian countries," Applied Economics Letters, Taylor & Francis Journals, vol. 22(10), pages 788-795, July.

    Cited by:

    1. Kim, Jun & Yoon, Jong Cheol & Jei, Sang Young, 2020. "An empirical analysis of Okun’s laws in ASEAN using time-varying parameter model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 540(C).
    2. Asma Raies, 2023. "Sustainable Employment in Developing and Emerging Countries: Testing Augmented Okun’s Law in Light of Institutional Quality," Sustainability, MDPI, vol. 15(4), pages 1-13, February.
    3. Myeong Jun Kim & Stanley I. M. Ko & Sung Y. Park, 2021. "On time and frequency-varying Okun’s coefficient: a new approach based on ensemble empirical mode decomposition," Empirical Economics, Springer, vol. 61(3), pages 1151-1188, September.

  22. Hyung-Gun Kim & Kwong-Chin Hung & Sung Park, 2015. "Determinants of Housing Prices in Hong Kong: A Box-Cox Quantile Regression Approach," The Journal of Real Estate Finance and Economics, Springer, vol. 50(2), pages 270-287, February.

    Cited by:

    1. Ming Li & Guojun Zhang & Yunliang Chen & Chunshan Zhou, 2019. "Evaluation of Residential Housing Prices on the Internet: Data Pitfalls," Complexity, Hindawi, vol. 2019, pages 1-15, February.
    2. Wilmar Alexander Cabrera-Rodríguez & Juan Sebastián Mariño-Montaña & Carlos Andrés Quicazán-Moreno, 2019. "Modelos hedónicos con efectos espaciales: una aproximación al cálculo de índices de precios de vivienda para Bogotá," Borradores de Economia 1072, Banco de la Republica de Colombia.
    3. Heiko Kirchhain & Jan Mutl & Joachim Zietz, 2020. "The Impact of Exogenous Shocks on House Prices: the Case of the Volkswagen Emissions Scandal," The Journal of Real Estate Finance and Economics, Springer, vol. 60(4), pages 587-610, May.
    4. Cupal Martin & Sedlačík Marek & Michálek Jaroslav, 2019. "The Assessment of a Building’s insurable Value using Multivariate Statistics: The Case of the Czech Republic," Real Estate Management and Valuation, Sciendo, vol. 27(3), pages 81-96, September.
    5. Alan T. K. Wan & Shangyu Xie & Yong Zhou, "undated". "A varying coefficient approach to estimating hedonic housing price functions and their quantiles," GRU Working Paper Series GRU_2016_003, City University of Hong Kong, Department of Economics and Finance, Global Research Unit.
    6. Antonio Nesticò & Marianna La Marca, 2020. "Urban Real Estate Values and Ecosystem Disservices: An Estimate Model Based on Regression Analysis," Sustainability, MDPI, vol. 12(16), pages 1-15, August.

  23. Ding, Haoyuan & Chong, Terence Tai-leung & Park, Sung Y., 2014. "Nonlinear dependence between stock and real estate markets in China," Economics Letters, Elsevier, vol. 124(3), pages 526-529.
    See citations under working paper version above.
  24. Ding, Haoyuan & Kim, Hyung-Gun & Park, Sung Y., 2014. "Do net positions in the futures market cause spot prices of crude oil?," Economic Modelling, Elsevier, vol. 41(C), pages 177-190.

    Cited by:

    1. Haoyuan Ding & Yuying Jin & Cong Qin & Jiezhou Ying, 2020. "Tail Causality between Crude Oil Price and RMB Exchange Rate," China & World Economy, Institute of World Economics and Politics, Chinese Academy of Social Sciences, vol. 28(3), pages 116-134, May.
    2. Dedi, Valentina & Mandilaras, Alex, 2022. "Trader positions and the price of oil in the futures market," International Review of Economics & Finance, Elsevier, vol. 82(C), pages 448-460.
    3. Li, Haiqi & Zhong, Wanling & Park, Sung Y., 2016. "Generalized cross-spectral test for nonlinear Granger causality with applications to money–output and price–volume relations," Economic Modelling, Elsevier, vol. 52(PB), pages 661-671.
    4. Jena, Sangram Keshari & Tiwari, Aviral Kumar & Hammoudeh, Shawkat & Roubaud, David, 2019. "Distributional predictability between commodity spot and futures: Evidence from nonparametric causality-in-quantiles tests," Energy Economics, Elsevier, vol. 78(C), pages 615-628.
    5. Li, Xin & Ma, Jian & Wang, Shouyang & Zhang, Xun, 2015. "How does Google search affect trader positions and crude oil prices?," Economic Modelling, Elsevier, vol. 49(C), pages 162-171.
    6. Li, Haiqi & Kim, Myeong Jun & Park, Sung Y., 2016. "Nonlinear relationship between crude oil price and net futures positions: A dynamic conditional distribution approach," International Review of Financial Analysis, Elsevier, vol. 44(C), pages 217-225.
    7. Zhifang He & Fangzhao Zhou, 2018. "Time-varying and asymmetric effects of the oil-specific demand shock on investor sentiment," PLOS ONE, Public Library of Science, vol. 13(8), pages 1-18, August.
    8. Yanhong Feng & Xiaolei Wang & Shuanglian Chen & Yanqiong Liu, 2022. "Impact of Oil Financialization on Oil Price Fluctuation: A Perspective of Heterogeneity," Energies, MDPI, vol. 15(12), pages 1-20, June.
    9. Nicolau, Mihaela & Palomba, Giulio, 2015. "Dynamic relationships between spot and futures prices. The case of energy and gold commodities," Resources Policy, Elsevier, vol. 45(C), pages 130-143.
    10. Li, Haiqi & Kim, Hyung-Gun & Park, Sung Y., 2015. "The role of financial speculation in the energy future markets: A new time-varying coefficient approach," Economic Modelling, Elsevier, vol. 51(C), pages 112-122.
    11. Miroslava Zavadska & Lucía Morales & Joseph Coughlan, 2018. "The Lead–Lag Relationship between Oil Futures and Spot Prices—A Literature Review," IJFS, MDPI, vol. 6(4), pages 1-22, October.
    12. Xie, Xiaoyu & Zhu, Heliang, 2021. "The role of gold futures in mitigating the impact of economic uncertainty on spot prices: Evidence from China," Research in International Business and Finance, Elsevier, vol. 56(C).

  25. Fang, Ying & Park, Sung Y. & Zhang, Jinfeng, 2014. "A simple spatial dependence test robust to local and distributional misspecifications," Economics Letters, Elsevier, vol. 124(2), pages 203-206.
    See citations under working paper version above.
  26. Ko, Stanley I.M. & Park, Sung Y., 2013. "Multivariate density forecast evaluation: A modified approach," International Journal of Forecasting, Elsevier, vol. 29(3), pages 431-441.

    Cited by:

    1. Knüppel, Malte & Krüger, Fabian & Pohle, Marc-Oliver, 2022. "Score-based calibration testing for multivariate forecast distributions," Discussion Papers 50/2022, Deutsche Bundesbank.
    2. Gaglianone, Wagner Piazza & Marins, Jaqueline Terra Moura, 2017. "Evaluation of exchange rate point and density forecasts: An application to Brazil," International Journal of Forecasting, Elsevier, vol. 33(3), pages 707-728.
    3. Jonas Dovern & Hans Manner, 2018. "Order Invariant Tests for Proper Calibration of Multivariate Density Forecasts," CESifo Working Paper Series 7023, CESifo.
    4. Dovern, Jonas & Manner, Hans, 2016. "Robust Evaluation of Multivariate Density Forecasts," VfS Annual Conference 2016 (Augsburg): Demographic Change 145547, Verein für Socialpolitik / German Economic Association.
    5. Wagner Piazza Gaglianone & Jaqueline Terra Moura Marins, 2014. "Risk Assessment of the Brazilian FX Rate," Working Papers Series 344, Central Bank of Brazil, Research Department.
    6. Matthieu Garcin & Jules Klein & Sana Laaribi, 2020. "Estimation of time-varying kernel densities and chronology of the impact of COVID-19 on financial markets," Papers 2007.09043, arXiv.org, revised Mar 2022.
    7. Matthieu Garcin & Jules Klein & Sana Laaribi, 2022. "Estimation of time-varying kernel densities and chronology of the impact of COVID-19 on financial markets," Working Papers hal-02901988, HAL.
    8. Dovern, Jonas & Manner, Hans, 2016. "Order Invariant Evaluation of Multivariate Density Forecasts," Working Papers 0608, University of Heidelberg, Department of Economics.

  27. Antonio F. Galvao JR. & Gabriel Montes-Rojas & Sung Y. Park, 2013. "Quantile Autoregressive Distributed Lag Model with an Application to House Price Returns," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 75(2), pages 307-321, April.

    Cited by:

    1. Eric Ghysels & Leonardo Iania & Jonas Striaukas, 2018. "Quantile-based Inflation Risk Models," Working Paper Research 349, National Bank of Belgium.
    2. Gaglianone, Wagner Piazza & Guillén, Osmani Teixeira de Carvalho & Figueiredo, Francisco Marcos Rodrigues, 2018. "Estimating inflation persistence by quantile autoregression with quantile-specific unit roots," Economic Modelling, Elsevier, vol. 73(C), pages 407-430.
    3. Xu, Xiu & Wang, Weining & Shin, Yongcheol, 2020. "Dynamic Spatial Network Quantile Autoregression," IRTG 1792 Discussion Papers 2020-024, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    4. Uwe Hassler & Paulo M.M. Rodrigues & Antonio Rubia, 2016. "Quantile Regression for Long Memory Testing: A Case of Realized Volatility," Journal of Financial Econometrics, Oxford University Press, vol. 14(4), pages 693-724.
    5. Haroon Mumtaz & Paolo Surico, 2015. "The Transmission Mechanism In Good And Bad Times," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 56(4), pages 1237-1260, November.
    6. Nicholas Apergis, 2023. "Forecasting energy prices: Quantile‐based risk models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(1), pages 17-33, January.
    7. Christis Katsouris, 2023. "Limit Theory under Network Dependence and Nonstationarity," Papers 2308.01418, arXiv.org, revised Aug 2023.
    8. Debdatta Pal & Subrata K. Mitra, 2017. "Diesel and soybean price relationship in the USA: evidence from a quantile autoregressive distributed lag model," Empirical Economics, Springer, vol. 52(4), pages 1609-1626, June.
    9. Lijuan Huo & Tae-Hwan Kim & Yunmi Kim, 2013. "Testing for Autocorrelation in Quantile Regression Models," Working papers 2013rwp-54, Yonsei University, Yonsei Economics Research Institute.
    10. Emmanuel Uche & Lionel Effiom, 2021. "Oil price, exchange rate and stock price in Nigeria: Fresh insights based on quantile ARDL model," ECONOMICS AND POLICY OF ENERGY AND THE ENVIRONMENT, FrancoAngeli Editore, vol. 2021(1), pages 59-79.
    11. Yuyan Wang & Akhgar Ghassabian & Bo Gu & Yelena Afanasyeva & Yiwei Li & Leonardo Trasande & Mengling Liu, 2023. "Semiparametric distributed lag quantile regression for modeling time‐dependent exposure mixtures," Biometrics, The International Biometric Society, vol. 79(3), pages 2619-2632, September.
    12. Wagner Piazza Gaglianone & Osmani Teixeira de Carvalho Guillén & Francisco Marcos Rodrigues Figueiredo, 2015. "Local Unit Root and Inflationary Inertia in Brazil," Working Papers Series 406, Central Bank of Brazil, Research Department.
    13. Janda, Karel & Kravec, Peter, 2022. "VECM Modelling of the Price Dynamics for Fuels, Agricultural Commodities and Biofuels," EconStor Preprints 259404, ZBW - Leibniz Information Centre for Economics.
    14. Liu Xiaochun & Luger Richard, 2018. "Markov-switching quantile autoregression: a Gibbs sampling approach," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 22(2), pages 1, April.
    15. Nicholas Apergis, 2022. "Evaluating tail risks for the U.S. economic policy uncertainty," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(4), pages 3971-3989, October.
    16. Marques, André M. & Lima, Gilberto Tadeu, 2022. "Testing for Granger causality in quantiles between the wage share in income and productive capacity utilization," Structural Change and Economic Dynamics, Elsevier, vol. 62(C), pages 290-312.
    17. Xu, Qifa & Niu, Xufeng & Jiang, Cuixia & Huang, Xue, 2015. "The Phillips curve in the US: A nonlinear quantile regression approach," Economic Modelling, Elsevier, vol. 49(C), pages 186-197.
    18. Tae-Hwan Kim & Dong Jin Lee & Paul Mizen, 2020. "Impulse Response Analysis in Conditional Quantile Models and an Application to Monetary Policy," Working papers 2020rwp-164, Yonsei University, Yonsei Economics Research Institute.
    19. Lee, Chien-Chiang & Lee, Cheng-Feng & Lee, Chi-Chuan, 2014. "Asymmetric dynamics in REIT prices: Further evidence based on quantile regression analysis," Economic Modelling, Elsevier, vol. 42(C), pages 29-37.
    20. Linas Jurksas & Arvydas Paskevicius, 2017. "The Relationship Between Macroeconomy And Asset Prices: Long Run Causality Evidence From Lithuania," Organizations and Markets in Emerging Economies, Faculty of Economics, Vilnius University, vol. 8(1).
    21. Ding, Haoyuan & Kim, Hyung-Gun & Park, Sung Y., 2016. "Crude oil and stock markets: Causal relationships in tails?," Energy Economics, Elsevier, vol. 59(C), pages 58-69.
    22. Yunmi Kim & Lijuan Huo & Tae-Hwan Kim, 2020. "Dealing with Markov-Switching Parameters in Quantile Regression Models," Working papers 2020rwp-166, Yonsei University, Yonsei Economics Research Institute.
    23. Guodong Li & Yang Li & Chih-Ling Tsai, 2015. "Quantile Correlations and Quantile Autoregressive Modeling," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 110(509), pages 246-261, March.
    24. Jack Fosten & Daniel Gutknecht & Marc-Oliver Pohle, 2023. "Testing Quantile Forecast Optimality," Papers 2302.02747, arXiv.org, revised Oct 2023.
    25. Debdatta PAL & Subrata Kumar MITRA, 2015. "Impact of price realization on India's tea export: Evidence from Quantile Autoregressive Distributed Lag Model," Agricultural Economics, Czech Academy of Agricultural Sciences, vol. 61(9), pages 422-428.
    26. Zhu, Hui-Ming & Li, ZhaoLai & You, WanHai & Zeng, Zhaofa, 2015. "Revisiting the asymmetric dynamic dependence of stock returns: Evidence from a quantile autoregression model," International Review of Financial Analysis, Elsevier, vol. 40(C), pages 142-153.
    27. Montes-Rojas, Gabriel, 2017. "Reduced form vector directional quantiles," Journal of Multivariate Analysis, Elsevier, vol. 158(C), pages 20-30.
    28. Martins, Luis F., 2021. "The US debt–growth nexus along the business cycle," The North American Journal of Economics and Finance, Elsevier, vol. 58(C).

  28. Fan, Rui & Fang, Ying & Park, Sung Y., 2012. "Resource abundance and economic growth in China," China Economic Review, Elsevier, vol. 23(3), pages 704-719.
    See citations under working paper version above.
  29. Zuo, Haomiao & Park, Sung Y., 2011. "Money demand in China and time-varying cointegration," China Economic Review, Elsevier, vol. 22(3), pages 330-343, September.

    Cited by:

    1. Chen, Xiaohong & Wohlfarth, Paul & Smith, Ron P., 2021. "China's money demand in a cointegrating vector error correction model," Journal of Asian Economics, Elsevier, vol. 75(C).
    2. Nidhal Mgadmi & Helmi Hamdi & Houssem Rachdi, 2016. "Non-Linear Modelling of Money Demand in Tunisia: Evidence from the STAR Model," Economics Bulletin, AccessEcon, vol. 36(4), pages 1975-1985.
    3. Delatte, Anne-Laure & Fouguau, Julien & Holz, Carsten A., 2011. "Explaining money demand in China during the transition from a centrally planned to a market-based monetary system," BOFIT Discussion Papers 27/2011, Bank of Finland Institute for Emerging Economies (BOFIT).
    4. Feng-Li Lin & Wen-Yi Chen, 2020. "Did the Consumption Voucher Scheme Stimulate the Economy? Evidence from Smooth Time-Varying Cointegration Analysis," Sustainability, MDPI, vol. 12(12), pages 1-16, June.
    5. Rudra P. Pradhan & Mak B. Arvin & Neville R. Norman & John H. Hall, 2014. "The dynamics of banking sector and stock market maturity and the performance of Asian economies," Journal of Economic and Administrative Sciences, Emerald Group Publishing Limited, vol. 30(1), pages 16-44, May.
    6. Miller, Stephen M. & Martins, Luis Filipe & Gupta, Rangan, 2019. "A Time-Varying Approach Of The Us Welfare Cost Of Inflation," Macroeconomic Dynamics, Cambridge University Press, vol. 23(2), pages 775-797, March.
    7. Wan, Jianjun & Lee, Chien-Chiang, 2023. "Corporate investment and the dilemma of the monetary policy: Evidence from China," Economic Analysis and Policy, Elsevier, vol. 78(C), pages 106-121.
    8. Chen-Huan Shieh & Shou-Hsiang Liu & Chung-Ching Lee, 2017. "How Stable is the Money Demand in Taiwan?," International Journal of Economics and Financial Research, Academic Research Publishing Group, vol. 3(5), pages 54-64, 05-2017.
    9. Jingfei Wu & Mohsen Bahmani-Oskooee & Tsangyao Chang, 2018. "Revisiting purchasing power parity in G6 countries: an application of smooth time-varying cointegration approach," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 45(1), pages 187-196, February.
    10. Neto, David, 2014. "The FMLS-based CUSUM statistic for testing the null of smooth time-varying cointegration in the presence of a structural break," Economics Letters, Elsevier, vol. 125(2), pages 208-211.
    11. Martin Falk & Xiang Lin, 2018. "Income elasticity of overnight stays over seven decades," Tourism Economics, , vol. 24(8), pages 1015-1028, December.
    12. Zhan, Minghua & Wang, Lijun & Zhan, Shuwei & Lu, Yao, 2023. "Does digital finance change the stability of money demand function? Evidence from China," Journal of Asian Economics, Elsevier, vol. 88(C).
    13. Jeyhun I. Mikayilov & Fakhri J. Hasanov & Marzio Galeotti, 2018. "Decoupling of C02 Emissions and GDP: A Time-Varying Cointegration Approach," IEFE Working Papers 101, IEFE, Center for Research on Energy and Environmental Economics and Policy, Universita' Bocconi, Milano, Italy.
    14. Delatte, Anne-Laure & Holz, Carsten, 2013. "Understanding Money Demand in the Transition from a Centrally Planned to a Market Economy," CEPR Discussion Papers 9721, C.E.P.R. Discussion Papers.
    15. César Carrera & Jairo Flores, 2017. "Modelling and forecasting money demand: divide and conquer," Working Papers 91, Peruvian Economic Association.
    16. You, Kefei & Sarantis, Nicholas, 2012. "A twelve-area model for the equilibrium Chinese Yuan/US dollar nominal exchange rate," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 22(1), pages 151-170.
    17. Singh, Sunny Kumar, 2016. "Currency demand stability in the presence of seasonality and endogenous financial innovation: Evidence from India," MPRA Paper 71552, University Library of Munich, Germany.

  30. Haiqi Li & Sung Yong Park & Joo Hwan Seo, 2011. "Quantile Elasticity of International Tourism Demand for South Korea Using the Quantile Autoregressive Distributed Lag Model," Tourism Economics, , vol. 17(5), pages 997-1015, October.

    Cited by:

    1. Bernd Süssmuth & Ulrich Woitek, 2013. "Estimating Dynamic Asymmetries in Demand at the Munich Oktoberfest," Tourism Economics, , vol. 19(3), pages 653-674, June.
    2. Jian-Wu Bi & Tian-Yu Han & Yanbo Yao, 2024. "Collaborative forecasting of tourism demand for multiple tourist attractions with spatial dependence: A combined deep learning model," Tourism Economics, , vol. 30(2), pages 361-388, March.

  31. Sung Yong Park & Sang Young Jei, 2010. "Determinants of volatility on international tourism demand for South Korea: an empirical note," Applied Economics Letters, Taylor & Francis Journals, vol. 17(3), pages 217-223, February.

    Cited by:

    1. Seymur Ağazade & Egemen Güneş Tükenmez & Merve Uzun, 2023. "Is the volatility of international tourism revenues affected by tourism source market structure? An empirical analysis of Turkey," Tourism Economics, , vol. 29(2), pages 291-304, March.
    2. Wai Hong Kan Tsui & Faruk Balli, 2017. "International arrivals forecasting for Australian airports and the impact of tourism marketing expenditure," Tourism Economics, , vol. 23(2), pages 403-428, March.

  32. Park, Sung Y. & Zhao, Guochang, 2010. "An estimation of U.S. gasoline demand: A smooth time-varying cointegration approach," Energy Economics, Elsevier, vol. 32(1), pages 110-120, January.

    Cited by:

    1. Jeyhun I. Mikayilov & Shahriyar Mukhtarov & Jeyhun Mammadov, 2020. "Gasoline Demand Elasticities at the Backdrop of Lower Oil Prices: Fuel-Subsidizing Country Case," Energies, MDPI, vol. 13(24), pages 1-18, December.
    2. Jeyhun I. Mikayilov & Shahriyar Mukhtarov & Hasan Dinçer & Serhat Yüksel & Rıdvan Aydın, 2020. "Elasticity Analysis of Fossil Energy Sources for Sustainable Economies: A Case of Gasoline Consumption in Turkey," Energies, MDPI, vol. 13(3), pages 1-15, February.
    3. Liddle, Brantley & Hasanov, Fakhri J. & Parker, Steven, 2022. "Your mileage may vary: Have road-fuel demand elasticities changed over time in middle-income countries?," Transportation Research Part A: Policy and Practice, Elsevier, vol. 165(C), pages 38-53.
    4. Lin, Boqiang & Xie, Chunping, 2013. "Estimation on oil demand and oil saving potential of China's road transport sector," Energy Policy, Elsevier, vol. 61(C), pages 472-482.
    5. Liddle, Brantley, 2023. "Is timing everything? Assessing the evidence on whether energy/electricity demand elasticities are time-varying," Energy Economics, Elsevier, vol. 124(C).
    6. A. Talha Yalta, 2013. "The Dynamics of Road Energy Demand and Illegal Fuel Activity in Turkey: A Rolling Window Analysis," Working Papers 1304, TOBB University of Economics and Technology, Department of Economics, revised Jul 2013.
    7. Feng-Li Lin & Wen-Yi Chen, 2020. "Did the Consumption Voucher Scheme Stimulate the Economy? Evidence from Smooth Time-Varying Cointegration Analysis," Sustainability, MDPI, vol. 12(12), pages 1-16, June.
    8. Yalta, A. Talha & Yalta, A. Yasemin, 2016. "The dynamics of fuel demand and illegal fuel activity in Turkey," Energy Economics, Elsevier, vol. 54(C), pages 144-158.
    9. Boqiang Lin & Zihan Zhang & Fei Ge, 2017. "Energy Conservation in China’s Cement Industry," Sustainability, MDPI, vol. 9(4), pages 1-17, April.
    10. Liddle, Brantley & Parker, Steven, 2022. "One more for the road: Reconsidering whether OECD gasoline income and price elasticities have changed over time," Energy Economics, Elsevier, vol. 114(C).
    11. Gao, Jiti & Peng, Bin & Smyth, Russell, 2021. "On income and price elasticities for energy demand: A panel data study," Energy Economics, Elsevier, vol. 96(C).
    12. Muller, Adrian & Åsa, Löfgren & Thomas, Sterner, 2011. "Decoupling: Is there a Separate Contribution from Environmental Taxation," Working Papers in Economics 486, University of Gothenburg, Department of Economics.
    13. Yu, Lean & Ma, Yueming & Ma, Mengyao, 2021. "An effective rolling decomposition-ensemble model for gasoline consumption forecasting," Energy, Elsevier, vol. 222(C).
    14. Chen, Wen-Yi, 2020. "The welfare effect of co-payment adjustments on emergency department visits in medical centers: Evidence from Taiwan," Health Policy, Elsevier, vol. 124(11), pages 1192-1199.
    15. Yoosoon Chang & Yongok Choi & Chang Sik Kim & J. Isaac Miller & Joon Y. Park, 2024. "Common Trends and Country Specific Heterogeneities in Long-Run World Energy Consumption," CAMA Working Papers 2024-04, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    16. Chang, Yoosoon & Kim, Chang Sik & Miller, J. Isaac & Park, Joon Y. & Park, Sungkeun, 2016. "A new approach to modeling the effects of temperature fluctuations on monthly electricity demand," Energy Economics, Elsevier, vol. 60(C), pages 206-216.
    17. Lin, Boqiang & Du, Zhili, 2017. "Promoting energy conservation in China's metallurgy industry," Energy Policy, Elsevier, vol. 104(C), pages 285-294.
    18. Kakali Kanjilal & Sajal Ghosh, 2018. "Revisiting income and price elasticity of gasoline demand in India: new evidence from cointegration tests," Empirical Economics, Springer, vol. 55(4), pages 1869-1888, December.
    19. Wittmann, Nadine, 2014. "Regulating gasoline retail markets: The case of Germany," Economics Discussion Papers 2014-17, Kiel Institute for the World Economy (IfW Kiel).
    20. Chang, Yoosoon & Kim, Chang Sik & Miller, J. Isaac & Park, Joon Y. & Park, Sungkeun, 2014. "Time-varying Long-run Income and Output Elasticities of Electricity Demand with an Application to Korea," Energy Economics, Elsevier, vol. 46(C), pages 334-347.
    21. Zhang, Yichi & Wang, Qiao & Tian, Tian & Yang, Yuan, 2022. "Volatility in natural resources, economic performance, and public administration quality: Evidence from COVID-19," Resources Policy, Elsevier, vol. 76(C).
    22. Lemoine, Derek M., 2013. "Escape from Third-Best: Rating Emissions for Intensity Standards," 2014 Allied Social Sciences Association (ASSA) Annual Meeting, January 3-5, 2014, Philadelphia, PA 161656, Agricultural and Applied Economics Association.
    23. Eleyan, Mohammed I.Abu & Çatık, Abdurrahman Nazif & Balcılar, Mehmet & Ballı, Esra, 2021. "Are long-run income and price elasticities of oil demand time-varying? New evidence from BRICS countries," Energy, Elsevier, vol. 229(C).
    24. Polbin, Andrey & Skrobotov, Anton, 2022. "On decrease in oil price elasticity of GDP and investment in Russia," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 66, pages 5-24.
    25. Byung Min Soon & Wyatt Thompson, 2020. "Japanese beef trade impact from BSE using a time‐varying Armington model," Agribusiness, John Wiley & Sons, Ltd., vol. 36(3), pages 385-401, June.
    26. Yoosoon Chang & Chang Sik Kim & J. Isaac Miller & Joon Y. Park & Sungkeun Park, 2014. "Time-varying Long-run Income and Output Elasticities of Electricity Demand," Working Papers 1409, Department of Economics, University of Missouri.
    27. Ghoddusi, Hamed & Morovati, Mohammad & Rafizadeh, Nima, 2022. "Dynamics of fuel demand elasticity: Evidence from Iranian subsidy reforms," Energy Economics, Elsevier, vol. 110(C).
    28. Zuo, Haomiao & Park, Sung Y., 2011. "Money demand in China and time-varying cointegration," China Economic Review, Elsevier, vol. 22(3), pages 330-343, September.
    29. Liddle, Brantley & Smyth, Russell & Zhang, Xibin, 2020. "Time-varying income and price elasticities for energy demand: Evidence from a middle-income panel," Energy Economics, Elsevier, vol. 86(C).
    30. Lin, Boqiang & Long, Houyin, 2014. "Promoting carbon emissions reduction in China's chemical process industry," Energy, Elsevier, vol. 77(C), pages 822-830.
    31. Türkekul, Berna & UnakItan, Gökhan, 2011. "A co-integration analysis of the price and income elasticities of energy demand in Turkish agriculture," Energy Policy, Elsevier, vol. 39(5), pages 2416-2423, May.
    32. Salisu, Afees A. & Ayinde, Taofeek O., 2016. "Modeling energy demand: Some emerging issues," Renewable and Sustainable Energy Reviews, Elsevier, vol. 54(C), pages 1470-1480.
    33. Ederington, Louis H. & Fernando, Chitru S. & Lee, Thomas K. & Linn, Scott C. & Zhang, Huiming, 2021. "The relation between petroleum product prices and crude oil prices," Energy Economics, Elsevier, vol. 94(C).
    34. Arisoy, Ibrahim & Ozturk, Ilhan, 2014. "Estimating industrial and residential electricity demand in Turkey: A time varying parameter approach," Energy, Elsevier, vol. 66(C), pages 959-964.
    35. Neto, David, 2014. "The FMLS-based CUSUM statistic for testing the null of smooth time-varying cointegration in the presence of a structural break," Economics Letters, Elsevier, vol. 125(2), pages 208-211.
    36. Martin Falk & Xiang Lin, 2018. "Income elasticity of overnight stays over seven decades," Tourism Economics, , vol. 24(8), pages 1015-1028, December.
    37. Siskos, Pelopidas & Capros, Pantelis & De Vita, Alessia, 2015. "CO2 and energy efficiency car standards in the EU in the context of a decarbonisation strategy: A model-based policy assessment," Energy Policy, Elsevier, vol. 84(C), pages 22-34.
    38. Laurence Levin & Matthew S. Lewis & Frank A. Wolak, 2016. "High Frequency Evidence on the Demand for Gasoline," NBER Working Papers 22345, National Bureau of Economic Research, Inc.
    39. Hou, Yang & Li, Steven & Wen, Fenghua, 2019. "Time-varying volatility spillover between Chinese fuel oil and stock index futures markets based on a DCC-GARCH model with a semi-nonparametric approach," Energy Economics, Elsevier, vol. 83(C), pages 119-143.
    40. Fei, Rilong & Lin, Boqiang, 2017. "Estimates of energy demand and energy saving potential in China's agricultural sector," Energy, Elsevier, vol. 135(C), pages 865-875.
    41. Dumortier, Jerome & Zhang, Fengxiu & Marron, John, 2017. "State and federal fuel taxes: The road ahead for U.S. infrastructure funding," Transport Policy, Elsevier, vol. 53(C), pages 39-49.
    42. Zhang, Shaohe & Shinwari, Riazullah & Zhao, Shikuan & Dagestani, Abd Alwahed, 2023. "Energy transition, geopolitical risk, and natural resources extraction: A novel perspective of energy transition and resources extraction," Resources Policy, Elsevier, vol. 83(C).
    43. Ozturk, Ilhan & Arisoy, Ibrahim, 2016. "An estimation of crude oil import demand in Turkey: Evidence from time-varying parameters approach," Energy Policy, Elsevier, vol. 99(C), pages 174-179.
    44. Debnath, Kumar Biswajit & Mourshed, Monjur, 2018. "Forecasting methods in energy planning models," Renewable and Sustainable Energy Reviews, Elsevier, vol. 88(C), pages 297-325.
    45. Soohyeon Kim & Surim Oh, 2020. "Impact of US Shale Gas on the Vertical and Horizontal Dynamics of Ethylene Price," Energies, MDPI, vol. 13(17), pages 1-12, August.
    46. de Freitas, Luciano Charlita & Kaneko, Shinji, 2011. "Ethanol demand under the flex-fuel technology regime in Brazil," Energy Economics, Elsevier, vol. 33(6), pages 1146-1154.
    47. Nishida, Mitsukuni & Remer, Marc, 2018. "Lowering consumer search costs can lead to higher prices," Economics Letters, Elsevier, vol. 162(C), pages 1-4.
    48. Melo, Patricia C. & Ramli, Ahmad Razi, 2014. "Estimating fuel demand elasticities to evaluate CO2 emissions: Panel data evidence for the Lisbon Metropolitan Area," Transportation Research Part A: Policy and Practice, Elsevier, vol. 67(C), pages 30-46.
    49. Neto, David, 2012. "Testing and estimating time-varying elasticities of Swiss gasoline demand," Energy Economics, Elsevier, vol. 34(6), pages 1755-1762.
    50. Adewuyi, Adeolu O., 2016. "Determinants of import demand for non-renewable energy (petroleum) products: Empirical evidence from Nigeria," Energy Policy, Elsevier, vol. 95(C), pages 73-93.
    51. Kyoung-Min Lim & Myunghwan Kim & Chang Seob Kim & Seung-Hoon Yoo, 2012. "Short-Run and Long-Run Elasticities of Diesel Demand in Korea," Energies, MDPI, vol. 5(12), pages 1-10, November.
    52. Lin, Boqiang & Long, Houyin, 2014. "How to promote energy conservation in China’s chemical industry," Energy Policy, Elsevier, vol. 73(C), pages 93-102.
    53. Joo, Young C. & Park, Sung Y., 2017. "Oil prices and stock markets: Does the effect of uncertainty change over time?," Energy Economics, Elsevier, vol. 61(C), pages 42-51.
    54. Wang, Banban & Wei, Jie & Tan, Xiujie & Su, Bin, 2021. "The sectorally heterogeneous and time-varying price elasticities of energy demand in China," Energy Economics, Elsevier, vol. 102(C).
    55. David Neto, 2015. "Testing for and dating structural break in smooth time-varying cointegration parameters, with an application to retail gasoline price and crude oil price long-run relationship," Empirical Economics, Springer, vol. 49(3), pages 909-928, November.
    56. Dilaver, Zafer & Hunt, Lester C., 2021. "Modelling U.S. gasoline demand: A structural time series analysis with asymmetric price responses," Energy Policy, Elsevier, vol. 156(C).
    57. David P. Byrne & Nicolas de Roos, 2019. "Learning to Coordinate: A Study in Retail Gasoline," American Economic Review, American Economic Association, vol. 109(2), pages 591-619, February.
    58. Besma Talbi & Duc Khuong Nguyen, 2014. "An Empirical Analysis of Energy Demand in Tunisia," Economics Bulletin, AccessEcon, vol. 34(1), pages 452-458.
    59. Katarzyna Leszkiewicz-Kędzior, 2011. "Modelling Fuel Prices. An I(1) Analysis," Central European Journal of Economic Modelling and Econometrics, Central European Journal of Economic Modelling and Econometrics, vol. 3(2), pages 75-95, June.
    60. Giuliodori, David & Rodriguez, Alejandro, 2015. "Analysis of the stainless steel market in the EU, China and US using co-integration and VECM," Resources Policy, Elsevier, vol. 44(C), pages 12-24.
    61. Carlos Frederico A. Uchoa & Cleiton S. de Jesus & Leonardo C. B. Cardoso, 2021. "The asymmetric pattern of fuel demand in Brazil," Economics Bulletin, AccessEcon, vol. 41(1), pages 155-160.
    62. Dean Hyslop & Trinh Le & David Maré & Lynn Riggs & Nic Watson, 2023. "Domestic transport charges: Estimation of transport-related elasticities," Working Papers 23_10, Motu Economic and Public Policy Research.
    63. Jeyhun Mikayilov & Fred Joutz & Fakhri Hasanov, 2019. "Gasoline Demand in Saudi Arabia: Are the Price and Income Elasticities Constant?," Discussion Papers ks--2019-dp81, King Abdullah Petroleum Studies and Research Center.

  33. Sung Yong Park & Sang Young Jei, 2010. "Estimation and hedging effectiveness of time‐varying hedge ratio: Flexible bivariate garch approaches," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 30(1), pages 71-99, January.

    Cited by:

    1. Yang (Greg) Hou & Mark Holmes, 2020. "Do higher order moments of return distribution provide better decisions in minimum-variance hedging? Evidence from US stock index futures," Australian Journal of Management, Australian School of Business, vol. 45(2), pages 240-265, May.
    2. Karali, Berna, 2012. "Do USDA Announcements Affect Comovements Across Commodity Futures Returns?," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 37(1), pages 1-21, April.
    3. Hou, Yang (Greg) & Li, Steven, 2020. "Volatility and skewness spillover between stock index and stock index futures markets during a crash period: New evidence from China," International Review of Economics & Finance, Elsevier, vol. 66(C), pages 166-188.
    4. Ubukata, Masato & Watanabe, Toshiaki, 2015. "Evaluating the performance of futures hedging using multivariate realized volatility," Journal of the Japanese and International Economies, Elsevier, vol. 38(C), pages 148-171.
    5. Hu, Yang & Hou, Yang Greg & Oxley, Les, 2020. "What role do futures markets play in Bitcoin pricing? Causality, cointegration and price discovery from a time-varying perspective?," International Review of Financial Analysis, Elsevier, vol. 72(C).
    6. Marco Lau & Yongyang Su & Na Tan & Zhe Zhang, 2014. "Hedging China’s energy oil market risks," Eurasian Economic Review, Springer;Eurasia Business and Economics Society, vol. 4(1), pages 99-112, June.
    7. Ubukata, Masato, 2018. "Dynamic hedging performance and downside risk: Evidence from Nikkei index futures," International Review of Economics & Finance, Elsevier, vol. 58(C), pages 270-281.
    8. Corbet, Shaen & Hou, Yang (Greg) & Hu, Yang & Oxley, Les, 2022. "The influence of the COVID-19 pandemic on the hedging functionality of Chinese financial markets," Research in International Business and Finance, Elsevier, vol. 59(C).
    9. Hou, Yang & Li, Steven, 2017. "Time-Varying Price Discovery and Autoregressive Loading Factors: Evidence from S&P 500 Cash and E-Mini Futures Markets," MPRA Paper 81999, University Library of Munich, Germany.
    10. Dejan Živkov & Petra Balaban & Boris Kuzman, 2021. "How to combine precious metals with corn in a risk-minimizing two-asset portfolio?," Agricultural Economics, Czech Academy of Agricultural Sciences, vol. 67(2), pages 60-69.
    11. Kunlapath Sukcharoen & Hankyeung Choi & David J. Leatham, 2015. "Optimal gasoline hedging strategies using futures contracts and exchange-traded funds," Applied Economics, Taylor & Francis Journals, vol. 47(32), pages 3482-3498, July.
    12. Pan, Zhiyuan & Xiao, Dongli & Dong, Qingma & Liu, Li, 2022. "Structural breaks, macroeconomic fundamentals and cross hedge ratio," Finance Research Letters, Elsevier, vol. 47(PA).
    13. Hou, Yang & Li, Steven, 2013. "Hedging performance of Chinese stock index futures: An empirical analysis using wavelet analysis and flexible bivariate GARCH approaches," Pacific-Basin Finance Journal, Elsevier, vol. 24(C), pages 109-131.
    14. Lai, Yu-Sheng, 2022. "Improving hedging performance by using high–low range," Finance Research Letters, Elsevier, vol. 48(C).
    15. Yang Hu & Yang (Greg) Hou & Les Oxley, 2019. "Spot and Futures Prices of Bitcoin: Causality, Cointegration and Price Discovery from a Time-Varying Perspective," Working Papers in Economics 19/13, University of Waikato.
    16. Ya-Chi Huang & Chueh-Yung Tsao, 2018. "Evolutionary Frequency and Forecasting Accuracy: Simulations Based on an Agent-Based Artificial Stock Market," Computational Economics, Springer;Society for Computational Economics, vol. 52(1), pages 79-104, June.
    17. Mun, Kyung-Chun, 2016. "Hedging bank market risk with futures and forwards," The Quarterly Review of Economics and Finance, Elsevier, vol. 61(C), pages 112-125.
    18. Aragó, Vicent & Salvador, Enrique, 2011. "Sudden changes in variance and time varying hedge ratios," European Journal of Operational Research, Elsevier, vol. 215(2), pages 393-403, December.
    19. Kao, Wei-Shun & Lin, Chu-Hsiung & Changchien, Chang-Cheng & Wu, Chien-Hui, 2017. "Return distribution, leverage effect and spot-futures spread on the hedging effectiveness," Finance Research Letters, Elsevier, vol. 22(C), pages 158-162.
    20. Hou, Yang & Holmes, Mark, 2017. "On the effects of static and autoregressive conditional higher order moments on dynamic optimal hedging," MPRA Paper 82000, University Library of Munich, Germany.
    21. Hou, Yang & Li, Steven & Wen, Fenghua, 2019. "Time-varying volatility spillover between Chinese fuel oil and stock index futures markets based on a DCC-GARCH model with a semi-nonparametric approach," Energy Economics, Elsevier, vol. 83(C), pages 119-143.
    22. Kim, Myeong Jun & Park, Sung Y., 2016. "Optimal conditional hedge ratio: A simple shrinkage estimation approach," Journal of Empirical Finance, Elsevier, vol. 38(PA), pages 139-156.
    23. Su, Yongyang & Lau, Chi Keung Marco & Tan, Na, 2013. "Hedging China’s Energy Oil Market Risks," MPRA Paper 47134, University Library of Munich, Germany.
    24. Hou, Yang & Nartea, Gilbert, 2017. "Price Discovery in the Stock Index Futures Market: Evidence from the Chinese stock market crash," MPRA Paper 81995, University Library of Munich, Germany.
    25. Yang Hou & Steven Li & Fenghua Wen, 2021. "Time-varying information share and autoregressive loading factors: evidence from S&P 500 cash and E-mini futures markets," Review of Quantitative Finance and Accounting, Springer, vol. 57(1), pages 91-110, July.
    26. Yu-Sheng Lai, 2018. "Dynamic hedging with futures: a copula-based GARCH model with high-frequency data," Review of Derivatives Research, Springer, vol. 21(3), pages 307-329, October.
    27. Yu‐Sheng Lai, 2022. "Use of high‐frequency data to evaluate the performance of dynamic hedging strategies," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 42(1), pages 104-124, January.
    28. Jing-Yi Lai, 2012. "An empirical study of the impact of skewness and kurtosis on hedging decisions," Quantitative Finance, Taylor & Francis Journals, vol. 12(12), pages 1827-1837, December.
    29. Chiou-Wei, Song-Zan & Chen, Sheng-Hung & Zhu, Zhen, 2020. "Natural gas price, market fundamentals and hedging effectiveness," The Quarterly Review of Economics and Finance, Elsevier, vol. 78(C), pages 321-337.
    30. Spencer, Simon & Bredin, Don & Conlon, Thomas, 2018. "Energy and agricultural commodities revealed through hedging characteristics: Evidence from developing and mature markets," Journal of Commodity Markets, Elsevier, vol. 9(C), pages 1-20.
    31. Kotkatvuori-Örnberg, Juha, 2016. "Dynamic conditional copula correlation and optimal hedge ratios with currency futures," International Review of Financial Analysis, Elsevier, vol. 47(C), pages 60-69.

  34. Joo Hwan Seo & Sung Yong Park & Soyoung Boo, 2010. "Interrelationships among Korean Outbound Tourism Demand: Granger Causality Analysis," Tourism Economics, , vol. 16(3), pages 597-610, September.

    Cited by:

    1. Tsui, Wai Hong Kan & Fu, Xiaowen & Yin, Chuanzhong & Zhang, Huaxin, 2021. "Hong Kong's aviation and tourism growth - An empirical investigation," Journal of Air Transport Management, Elsevier, vol. 93(C).
    2. Oscar Claveria, 2017. "“What really matters is the economic performance: Positioning tourist destinations by means of perceptual maps," IREA Working Papers 201713, University of Barcelona, Research Institute of Applied Economics, revised Jun 2017.
    3. Chia-Yu Yeh & Kang Ernest Liu, 2019. "Modeling Household Participation Decisions Between Domestic And International Trips By Semi-Nonparametric Regressions," The Singapore Economic Review (SER), World Scientific Publishing Co. Pte. Ltd., vol. 64(01), pages 191-211, March.
    4. Cao, Zheng & Li, Gang & Song, Haiyan, 2017. "Modelling the interdependence of tourism demand: The global vector autoregressive approach," Annals of Tourism Research, Elsevier, vol. 67(C), pages 1-13.
    5. Kristen Corrie & Natalie Stoeckl & Taha Chaiechi, 2013. "Tourism and Economic Growth in Australia: An Empirical Investigation of Causal Links," Tourism Economics, , vol. 19(6), pages 1317-1344, December.
    6. Mehmet Balcilar & Sahar Aghazadeh & George N Ike, 2021. "Modelling the employment, income and price elasticities of outbound tourism demand in OECD countries," Tourism Economics, , vol. 27(5), pages 971-990, August.

  35. Park, Sung Y. & Bera, Anil K., 2009. "Maximum entropy autoregressive conditional heteroskedasticity model," Journal of Econometrics, Elsevier, vol. 150(2), pages 219-230, June.

    Cited by:

    1. Jorge Antunes & Rangan Gupta & Zinnia Mukherjee & Peter Wanke, 2022. "Information entropy, continuous improvement, and US energy performance: a novel stochastic-entropic analysis for ideal solutions (SEA-IS)," Annals of Operations Research, Springer, vol. 313(1), pages 289-318, June.
    2. Vilkkumaa, Eeva & Liesiö, Juuso & Salo, Ahti, 2014. "Optimal strategies for selecting project portfolios using uncertain value estimates," European Journal of Operational Research, Elsevier, vol. 233(3), pages 772-783.
    3. Gersbach, Hans & Liu, Yulin & Tischhauser, Martin, 2018. "Versatile Forward Guidance: Escaping or Switching?," CEPR Discussion Papers 12559, C.E.P.R. Discussion Papers.
    4. Tack, Jesse, 2013. "A Nested Test for Common Yield Distributions with Applications to U.S. Corn," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 38(1), pages 1-14, April.
    5. Salman A Rahman & Sheila K West & Harran Mkocha & Beatriz Munoz & Travis C Porco & Jeremy D Keenan & Thomas M Lietman, 2015. "The Distribution of Ocular Chlamydia Prevalence across Tanzanian Communities Where Trachoma Is Declining," PLOS Neglected Tropical Diseases, Public Library of Science, vol. 9(3), pages 1-8, March.
    6. Sung Y. Park & Anil K. Bera, 2018. "Information theoretic approaches to income density estimation with an application to the U.S. income data," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 16(4), pages 461-486, December.
    7. Corry Bedwell & Ryan Guttridge, 2019. "Modern Asset Theory: A Framework for Successful Active Management," Papers 1903.09683, arXiv.org.
    8. Carol Alexander & José María Sarabia, 2012. "Quantile Uncertainty and Value‐at‐Risk Model Risk," Risk Analysis, John Wiley & Sons, vol. 32(8), pages 1293-1308, August.
    9. Usta, Ilhan & Kantar, Yeliz Mert, 2011. "On the performance of the flexible maximum entropy distributions within partially adaptive estimation," Computational Statistics & Data Analysis, Elsevier, vol. 55(6), pages 2172-2182, June.
    10. Sylvia J. Soltyk & Felix Chan, 2023. "Modeling time‐varying higher‐order conditional moments: A survey," Journal of Economic Surveys, Wiley Blackwell, vol. 37(1), pages 33-57, February.
    11. Kiche J & Oscar Ngesa & George Orwa, 2019. "On Generalized Gamma Distribution and Its Application to Survival Data," International Journal of Statistics and Probability, Canadian Center of Science and Education, vol. 8(5), pages 85-102, September.
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    13. Anil K. Bera & Antonio F. Galvao Jr. & Gabriel V. Montes-Rojas & Sung Y. Park, 2014. "Which Quantile is the Most Informative? Maximum Likelihood, Maximum Entropy and Quantile Regression," World Scientific Book Chapters, in: Kaddour Hadri & William Mikhail (ed.), Econometric Methods and Their Applications in Finance, Macro and Related Fields, chapter 7, pages 167-199, World Scientific Publishing Co. Pte. Ltd..
    14. Klein, Ingo, 2017. "(Generalized) maximum cumulative direct, paired, and residual Φ entropy principle," FAU Discussion Papers in Economics 25/2017, Friedrich-Alexander University Erlangen-Nuremberg, Institute for Economics.
    15. Sung Y. Park & Sang Hyuck Kim, 2016. "Determinants of systematic risk in the US Restaurant industry," Tourism Economics, , vol. 22(3), pages 621-628, June.
    16. Vladimir Zdorovenin & Jacques Pézier, 2011. "Does Information Content of Option Prices Add Value for Asset Allocation?," ICMA Centre Discussion Papers in Finance icma-dp2011-03, Henley Business School, University of Reading.
    17. Domenico Di Gangi & Fabrizio Lillo & Davide Pirino, 2015. "Assessing systemic risk due to fire sales spillover through maximum entropy network reconstruction," Papers 1509.00607, arXiv.org, revised Jul 2018.
    18. Namaki, A. & Koohi Lai, Z. & Jafari, G.R. & Raei, R. & Tehrani, R., 2013. "Comparing emerging and mature markets during times of crises: A non-extensive statistical approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(14), pages 3039-3044.
    19. Carol Alexander & Jose Maria Sarabia, 2010. "Endogenizing Model Risk to Quantile Estimates," ICMA Centre Discussion Papers in Finance icma-dp2010-07, Henley Business School, University of Reading.
    20. Chen, Yi-Ting, 2012. "A simple approach to standardized-residuals-based higher-moment tests," Journal of Empirical Finance, Elsevier, vol. 19(4), pages 427-453.
    21. Di Gangi, Domenico & Lillo, Fabrizio & Pirino, Davide, 2018. "Assessing systemic risk due to fire sales spillover through maximum entropy network reconstruction," Journal of Economic Dynamics and Control, Elsevier, vol. 94(C), pages 117-141.
    22. Bera Anil K. & Galvao Antonio F. & Montes-Rojas Gabriel V. & Park Sung Y., 2016. "Asymmetric Laplace Regression: Maximum Likelihood, Maximum Entropy and Quantile Regression," Journal of Econometric Methods, De Gruyter, vol. 5(1), pages 79-101, January.

  36. Anil Bera & Sung Park, 2008. "Optimal Portfolio Diversification Using the Maximum Entropy Principle," Econometric Reviews, Taylor & Francis Journals, vol. 27(4-6), pages 484-512.

    Cited by:

    1. Sarah Perrin & Thierry Roncalli, 2019. "Machine Learning Optimization Algorithms & Portfolio Allocation," Papers 1909.10233, arXiv.org.
    2. Nathan Lassance & Frédéric Vrins, 2019. "Minimum Rényi entropy portfolios," LIDAM Reprints CORE 3062, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    3. Lee Tae-Hwy & Wang He & Xi Zhou & Zhang Ru, 2023. "Density Forecast of Financial Returns Using Decomposition and Maximum Entropy," Journal of Econometric Methods, De Gruyter, vol. 12(1), pages 57-83, January.
    4. Nicola Giuseppe Castellano & Roy Cerqueti & Bruno Maria Franceschetti, 2021. "Evaluating risks-based communities of Mafia companies: a complex networks perspective," Review of Quantitative Finance and Accounting, Springer, vol. 57(4), pages 1463-1486, November.
    5. David E. Allen & Michael McAleer & Robert Powell & Abhay K. Singh, 2013. "A Non-Parametric and Entropy Based Analysis of the Relationship between the VIX and S&P 500," Tinbergen Institute Discussion Papers 13-018/III, Tinbergen Institute.
    6. David E. Allen & Michael McAleer & Abhay K. Singh, 2016. "An entropy based analysis of the relationship between the DOW JONES Index and the TRNA Sentiment series," Documentos de Trabajo del ICAE 2017-01, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.
    7. Amritansu Ray & Sanat Kumar Majumder, 2018. "Multi objective mean–variance–skewness model with Burg’s entropy and fuzzy return for portfolio optimization," OPSEARCH, Springer;Operational Research Society of India, vol. 55(1), pages 107-133, March.
    8. Mariana Mazzucato & Gregor Semieniuk, 2016. "Financing Renewable Energy: Who is Financing What and Why it Matters," SPRU Working Paper Series 2016-12, SPRU - Science Policy Research Unit, University of Sussex Business School.
    9. Yue, Wei & Wang, Yuping, 2017. "A new fuzzy multi-objective higher order moment portfolio selection model for diversified portfolios," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 465(C), pages 124-140.
    10. Abdulnasser Hatemi-J & Mohamed Ali Hajji & Youssef El-Khatib, 2019. "Exact Solution for the Portfolio Diversification Problem Based on Maximizing the Risk Adjusted Return," Papers 1903.01082, arXiv.org.
    11. Będowska-Sójka, Barbara & Kliber, Agata, 2021. "Information content of liquidity and volatility measures," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 563(C).
    12. Ponta, Linda & Carbone, Anna, 2018. "Information measure for financial time series: Quantifying short-term market heterogeneity," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 510(C), pages 132-144.
    13. Lassance, Nathan & Vrins, Frédéric, 2023. "Portfolio selection: A target-distribution approach," European Journal of Operational Research, Elsevier, vol. 310(1), pages 302-314.
    14. Kang, Yan-li & Tian, Jing-Song & Chen, Chen & Zhao, Gui-Yu & Li, Yuan-fu & Wei, Yu, 2021. "Entropy based robust portfolio," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 583(C).
    15. Argimiro Arratia & Henryk Gzyl & Silvia Mayoral, 2022. "Tracking a Well Diversified Portfolio with Maximum Entropy in the Mean," Mathematics, MDPI, vol. 10(4), pages 1-14, February.
    16. Frahm, Gabriel & Wiechers, Christof, 2011. "On the diversification of portfolios of risky assets," Discussion Papers in Econometrics and Statistics 2/11, University of Cologne, Institute of Econometrics and Statistics.
    17. Gilles Boevi Koumou, 2020. "Diversification and portfolio theory: a review," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 34(3), pages 267-312, September.
    18. Máté, Gabriell & Néda, Zoltán, 2016. "The advantage of inhomogeneity — Lessons from a noise driven linearized dynamical system," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 445(C), pages 310-317.
    19. Prateek Sharma & Vipul, 2018. "Improving portfolio diversification: Identifying the right baskets for putting your eggs," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 39(6), pages 698-711, September.
    20. Deng, Xue & Chen, Jiaxing & Wang, Xu & Geng, Fengting, 2022. "Non-dominated sorting genetic algorithm-II for possibilistic mean-semiabsolute deviation-Yager entropy portfolio model with complex real-world constraints," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 202(C), pages 59-78.
    21. Billio, Monica & Casarin, Roberto & Costola, Michele & Pasqualini, Andrea, 2016. "An entropy-based early warning indicator for systemic risk," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 45(C), pages 42-59.
    22. Rodríguez, Yeny E. & Gómez, Juan M. & Contreras, Javier, 2021. "Diversified behavioral portfolio as an alternative to Modern Portfolio Theory," The North American Journal of Economics and Finance, Elsevier, vol. 58(C).
    23. Sahamkhadam, Maziar & Stephan, Andreas & Östermark, Ralf, 2022. "Copula-based Black–Litterman portfolio optimization," European Journal of Operational Research, Elsevier, vol. 297(3), pages 1055-1070.
    24. Yunker, James A. & Melkumian, Alla A., 2010. "The effect of capital wealth on optimal diversification: Evidence from the Survey of Consumer Finances," The Quarterly Review of Economics and Finance, Elsevier, vol. 50(1), pages 90-98, February.
    25. Claudiu Vinte & Ion Smeureanu & Titus-Felix Furtuna & Marcel Ausloos, 2022. "An Intrinsic Entropy Model for Exchange-Traded Securities," Papers 2205.01386, arXiv.org.
    26. Thorsten Poddig & Albina Unger, 2012. "On the robustness of risk-based asset allocations," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 26(3), pages 369-401, September.
    27. Gianni Pola, 2016. "On entropy and portfolio diversification," Journal of Asset Management, Palgrave Macmillan, vol. 17(4), pages 218-228, July.
    28. Joo, Young C. & Park, Sung Y., 2021. "Optimal portfolio selection using a simple double-shrinkage selection rule," Finance Research Letters, Elsevier, vol. 43(C).
    29. Contreras, Javier & Rodríguez, Yeny E. & Sosa, Aníbal, 2017. "Construction of an efficient portfolio of power purchase decisions based on risk-diversification tradeoff," Energy Economics, Elsevier, vol. 64(C), pages 286-297.
    30. Francesco Cesarone & Manuel L. Martino & Fabio Tardella, 2023. "Mean-Variance-VaR portfolios: MIQP formulation and performance analysis," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 45(3), pages 1043-1069, September.
    31. Vasyl Golosnoy & Benno Hildebrandt & Steffen Köhler, 2019. "Modeling and Forecasting Realized Portfolio Diversification Benefits," JRFM, MDPI, vol. 12(3), pages 1-16, July.
    32. Akhter Mohiuddin Rather & V. N. Sastry & Arun Agarwal, 2017. "Stock market prediction and Portfolio selection models: a survey," OPSEARCH, Springer;Operational Research Society of India, vol. 54(3), pages 558-579, September.
    33. Kin‐Yip Ho & Kun Tracy Wang & Wanbin Walter Wang, 2023. "A novel approach to portfolio selection using news volume and sentiment," International Review of Finance, International Review of Finance Ltd., vol. 23(4), pages 903-917, December.
    34. Silva, Thuener & Pinheiro, Plácido Rogério & Poggi, Marcus, 2017. "A more human-like portfolio optimization approach," European Journal of Operational Research, Elsevier, vol. 256(1), pages 252-260.
    35. Paolo Capelli & Federica Ielasi & Angeloantonio Russo, 2021. "Forecasting volatility by integrating financial risk with environmental, social, and governance risk," Corporate Social Responsibility and Environmental Management, John Wiley & Sons, vol. 28(5), pages 1483-1495, September.
    36. Thomas, Nisha Mary & Kashiramka, Smita & Yadav, Surendra Singh & Paul, Justin, 2022. "Role of emerging markets vis-à-vis frontier markets in improving portfolio diversification benefits," International Review of Economics & Finance, Elsevier, vol. 78(C), pages 95-121.
    37. Ponta, Linda & Murialdo, Pietro & Carbone, Anna, 2021. "Information measure for long-range correlated time series: Quantifying horizon dependence in financial markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 570(C).
    38. Henryk Gzyl & Alfredo Rios, 2018. "Which portfolio is better? A discussion of several possible comparison criteria," Papers 1805.06345, arXiv.org, revised Jun 2022.
    39. Capelli, Paolo & Ielasi, Federica & Russo, Angeloantonio, 2023. "Integrating ESG risks into value-at-risk," Finance Research Letters, Elsevier, vol. 55(PA).
    40. Marielle Jong, 2018. "Portfolio optimisation in an uncertain world," Journal of Asset Management, Palgrave Macmillan, vol. 19(4), pages 216-221, July.
    41. Francesco Cesarone & Rosella Giacometti & Manuel Luis Martino & Fabio Tardella, 2023. "A return-diversification approach to portfolio selection," Papers 2312.09707, arXiv.org.
    42. Prateek SHARMA, 2017. "Economic value of portfolio diversification: Evidence from international multi-asset portfolios," Theoretical and Applied Economics, Asociatia Generala a Economistilor din Romania - AGER, vol. 0(4(613), W), pages 33-42, Winter.

Chapters

  1. Anil K. Bera & Antonio F. Galvao Jr. & Gabriel V. Montes-Rojas & Sung Y. Park, 2014. "Which Quantile is the Most Informative? Maximum Likelihood, Maximum Entropy and Quantile Regression," World Scientific Book Chapters, in: Kaddour Hadri & William Mikhail (ed.), Econometric Methods and Their Applications in Finance, Macro and Related Fields, chapter 7, pages 167-199, World Scientific Publishing Co. Pte. Ltd..

    Cited by:

    1. Friedson, Andrew I. & Kniesner, Thomas J., 2011. "Losers and Losers: Some Demographics of Medical Malpractice Tort Reforms," IZA Discussion Papers 5921, Institute of Labor Economics (IZA).

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