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Liyuan Chen

Personal Details

First Name:Liyuan
Middle Name:
Last Name:Chen
Suffix:
RePEc Short-ID:pch1751

Affiliation

Department of Economics and Related Studies
University of York

York, United Kingdom
http://www.york.ac.uk/economics/
RePEc:edi:deyoruk (more details at EDIRC)

Research output

as
Jump to: Working papers

Working papers

  1. Liyuan Chen & Paola Zerilli & Christopher F Baum, 2018. "Leverage effects and stochastic volatility in spot oil returns: A Bayesian approach with VaR and CVaR applications," Boston College Working Papers in Economics 953, Boston College Department of Economics.
  2. Christopher F Baum & Paola Zerilli & Liyuan Chen, 2018. "Stochastic volatility, jumps and leverage in energy and stock markets: evidence from high frequency data," Boston College Working Papers in Economics 952, Boston College Department of Economics, revised 29 May 2019.

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. Liyuan Chen & Paola Zerilli & Christopher F Baum, 2018. "Leverage effects and stochastic volatility in spot oil returns: A Bayesian approach with VaR and CVaR applications," Boston College Working Papers in Economics 953, Boston College Department of Economics.

    Cited by:

    1. Zi‐Yi Guo, 2020. "Stochastic multifactor models in risk management of energy futures," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 40(12), pages 1918-1934, December.
    2. Virbickaite, Audrone & Nguyen, Hoang & Tran, Minh-Ngoc, 2023. "Bayesian Predictive Distributions of Oil Returns Using Mixed Data Sampling Volatility Models," Working Papers 2023:7, Örebro University, School of Business.
    3. Jo-Hui & Chen & Sabbor Hussain, 2022. "Jump Dynamics and Leverage Effect: Evidences from Energy Exchange Traded Fund (ETFs)," Journal of Applied Finance & Banking, SCIENPRESS Ltd, vol. 12(6), pages 1-7.
    4. Wang, Delu & Tong, Xian & Wang, Yadong, 2020. "An early risk warning system for Outward Foreign Direct Investment in Mineral Resource-based enterprises using multi-classifiers fusion," Resources Policy, Elsevier, vol. 66(C).
    5. Zhang, Yue-Jun & Bouri, Elie & Gupta, Rangan & Ma, Shu-Jiao, 2021. "Risk spillover between Bitcoin and conventional financial markets: An expectile-based approach," The North American Journal of Economics and Finance, Elsevier, vol. 55(C).
    6. Tiwari, Aviral Kumar & Sharma, Gagan Deep & Rao, Amar & Hossain, Mohammad Razib & Dev, Dhairya, 2024. "Unraveling the crystal ball: Machine learning models for crude oil and natural gas volatility forecasting," Energy Economics, Elsevier, vol. 134(C).
    7. Kuntadi, Cris, 2022. "Effective energy commodity risk management on Indonesia," Resources Policy, Elsevier, vol. 78(C).
    8. Baum, Christopher F. & Zerilli, Paola & Chen, Liyuan, 2021. "Stochastic volatility, jumps and leverage in energy and stock markets: Evidence from high frequency data," Energy Economics, Elsevier, vol. 93(C).
    9. Jun Dong & Yaoyu Zhang & Yuanyuan Wang & Yao Liu, 2021. "A Two-Stage Optimal Dispatching Model for Micro Energy Grid Considering the Dual Goals of Economy and Environmental Protection under CVaR," Sustainability, MDPI, vol. 13(18), pages 1-28, September.
    10. Pablo Cansado-Bravo & Carlos Rodríguez-Monroy, 2018. "Persistence of Oil Prices in Gas Import Prices and the Resilience of the Oil-Indexation Mechanism. The Case of Spanish Gas Import Prices," Energies, MDPI, vol. 11(12), pages 1-17, December.
    11. Virbickaitė, Audronė & Ausín, M. Concepción & Galeano, Pedro, 2020. "Copula stochastic volatility in oil returns: Approximate Bayesian computation with volatility prediction," Energy Economics, Elsevier, vol. 92(C).
    12. Jose Arreola Hernandez & Sang Hoon Kang & Seong‐Min Yoon, 2022. "Nonlinear spillover and portfolio allocation characteristics of energy equity sectors: Evidence from the United States and Canada," Review of International Economics, Wiley Blackwell, vol. 30(1), pages 1-33, February.

  2. Christopher F Baum & Paola Zerilli & Liyuan Chen, 2018. "Stochastic volatility, jumps and leverage in energy and stock markets: evidence from high frequency data," Boston College Working Papers in Economics 952, Boston College Department of Economics, revised 29 May 2019.

    Cited by:

    1. Shen, Yiran & Liu, Chang & Sun, Xiaolei & Guo, Kun, 2023. "Investor sentiment and the Chinese new energy stock market: A risk–return perspective," International Review of Economics & Finance, Elsevier, vol. 84(C), pages 395-408.
    2. George P. Papaioannou & Christos Dikaiakos & Akylas C. Stratigakos & Panos C. Papageorgiou & Konstantinos F. Krommydas, 2019. "Testing the Efficiency of Electricity Markets Using a New Composite Measure Based on Nonlinear TS Tools," Energies, MDPI, vol. 12(4), pages 1-30, February.
    3. Jo-Hui & Chen & Sabbor Hussain, 2022. "Jump Dynamics and Leverage Effect: Evidences from Energy Exchange Traded Fund (ETFs)," Journal of Applied Finance & Banking, SCIENPRESS Ltd, vol. 12(6), pages 1-7.
    4. Alfredo Trespalacios & Lina M. Cortés & Javier Perote, 2019. "Modeling the electricity spot price with switching regime semi-nonparametric distributions," Documentos de Trabajo de Valor Público 17618, Universidad EAFIT.
    5. Xinjie Lu & Feng Ma & Jiqian Wang & Jing Liu, 2022. "Forecasting oil futures realized range‐based volatility with jumps, leverage effect, and regime switching: New evidence from MIDAS models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(4), pages 853-868, July.
    6. Shen, Lihua & Lu, Xinjie & Luu Duc Huynh, Toan & Liang, Chao, 2023. "Air quality index and the Chinese stock market volatility: Evidence from both market and sector indices," International Review of Economics & Finance, Elsevier, vol. 84(C), pages 224-239.

More information

Research fields, statistics, top rankings, if available.

Statistics

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Co-authorship network on CollEc

NEP Fields

NEP is an announcement service for new working papers, with a weekly report in each of many fields. This author has had 2 papers announced in NEP. These are the fields, ordered by number of announcements, along with their dates. If the author is listed in the directory of specialists for this field, a link is also provided.
  1. NEP-ENE: Energy Economics (2) 2018-06-25 2018-07-09. Author is listed
  2. NEP-ORE: Operations Research (2) 2018-06-25 2018-07-09. Author is listed
  3. NEP-RMG: Risk Management (2) 2018-06-25 2018-07-09. Author is listed
  4. NEP-FOR: Forecasting (1) 2018-06-25. Author is listed
  5. NEP-KNM: Knowledge Management and Knowledge Economy (1) 2018-07-09. Author is listed

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