Yujun Lian

Personal Details

First Name:	Yujun
Middle Name:
Last Name:	Lian
Suffix:
RePEc Short-ID:	pli510
	https://lingnan.sysu.edu.cn/en/faculty/LianYujun
Terminal Degree:	2007 Jinhe Center for Economic Research (JCER); Xi'an Jiaotong University (from RePEc Genealogy)

Affiliation

Department of Finance
Lingnan (University) College
Sun Yat-Sen University

Guangzhou, China
http://lingnan.sysu.edu.cn/jiaoxue/csx.asp
RePEc:edi:dfsuncn (more details at EDIRC)

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

Sorry, no citations of working papers recorded.

Articles

1. Huang, Bihong & Lian, Yujun & Li, Wensu, 2016. "How far is Chinese left-behind parents' health left behind?," China Economic Review, Elsevier, vol. 37(C), pages 15-26.

   Cited by:

   1. Yosuke Inoue & Annie Green Howard & Bo Qin & Aki Yazawa & Andrew Stickley & Penny Gordon-Larsen, 2019. "The association between family members’ migration and cognitive function among people left behind in China," PLOS ONE, Public Library of Science, vol. 14(9), pages 1-11, September.
   2. Menghua Li & Yun Zhou & Xinjie Shi, 2021. "Who Will Care for Middle Aged and Elderly Parents in Rural China?," China & World Economy, Institute of World Economics and Politics, Chinese Academy of Social Sciences, vol. 29(2), pages 123-150, March.
   3. Kumar, Sneha, 2021. "Offspring's labor migration and its implications for elderly parents' emotional wellbeing in Indonesia," Social Science & Medicine, Elsevier, vol. 276(C).
   4. De Neve, Jan-Walter & Kawachi, Ichiro, 2017. "Spillovers between siblings and from offspring to parents are understudied: A review and future directions for research," Social Science & Medicine, Elsevier, vol. 183(C), pages 56-61.
   5. Tianxiang Li & Beibei Wu & Fujin Yi & Bin Wang & Tomas Baležentis, 2020. "What Happens to the Health of Elderly Parents When Adult Child Migration Splits Households? Evidence from Rural China," IJERPH, MDPI, vol. 17(5), pages 1-14, March.
   6. Agadjanian, Victor & Hayford, Sarah R. & Jansen, Natalie A., 2021. "Men's migration and women's mortality in rural Mozambique," Social Science & Medicine, Elsevier, vol. 270(C).
   7. Sha Cao & Dingde Xu & Yi Liu & Shaoquan Liu, 2019. "The Impact of Rural Labor Migration on Elderly Health from the Perspective of Gender Structure: A Case Study in Western China," Sustainability, MDPI, vol. 11(20), pages 1-18, October.
   8. Sarah Bridges & Lefan Liu, 2022. "The impact of child migration on the health and well‐being of parents left behind," Journal of International Development, John Wiley & Sons, Ltd., vol. 34(6), pages 1145-1164, August.
   9. Kesavayuth, Dusanee & Liang, Yufang & Zikos, Vasileios, 2018. "An active lifestyle and cognitive function: Evidence from China," The Journal of the Economics of Ageing, Elsevier, vol. 12(C), pages 183-191.

2. Shao, Xi-Dong & Lian, Yu-Jun & Yin, Lian-Qian, 2009. "Forecasting Value-at-Risk using high frequency data: The realized range model," Global Finance Journal, Elsevier, vol. 20(2), pages 128-136.

   Cited by:

   1. Stavros Degiannakis & Pamela Dent & Christos Floros, 2014. "A Monte Carlo Simulation Approach to Forecasting Multi-period Value-at-Risk and Expected Shortfall Using the FIGARCH-skT Specification," Manchester School, University of Manchester, vol. 82(1), pages 71-102, January.
      • Degiannakis, Stavros & Dent, Pamela & Floros, Christos, 2014. "A Monte Carlo Simulation Approach to Forecasting Multi-period Value-at-Risk and Expected Shortfall Using the FIGARCH-skT Specification," MPRA Paper 80431, University Library of Munich, Germany.
   2. Fuertes, Ana-Maria & Olmo, Jose, 2013. "Optimally harnessing inter-day and intra-day information for daily value-at-risk prediction," International Journal of Forecasting, Elsevier, vol. 29(1), pages 28-42.
   3. Ewald, Christian & Hadina, Jelena & Haugom, Erik & Lien, Gudbrand & Størdal, Ståle & Yahya, Muhammad, 2023. "Sample frequency robustness and accuracy in forecasting Value-at-Risk for Brent Crude Oil futures," Finance Research Letters, Elsevier, vol. 58(PA).
   4. Iacus, Stefano M. & Mercuri, Lorenzo & Rroji, Edit, 2017. "COGARCH(p, q): Simulation and Inference with the yuima Package," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 80(i04).
   5. Louzis, Dimitrios P. & Xanthopoulos-Sisinis, Spyros & Refenes, Apostolos P., 2011. "Are realized volatility models good candidates for alternative Value at Risk prediction strategies?," MPRA Paper 30364, University Library of Munich, Germany.
   6. Louzis, Dimitrios P. & Xanthopoulos-Sisinis, Spyros & Refenes, Apostolos P., 2011. "The role of high frequency intra-daily data, daily range and implied volatility in multi-period Value-at-Risk forecasting," MPRA Paper 35252, University Library of Munich, Germany.
      • Dimitrios P. Louzis & Spyros Xanthopoulos‐Sisinis & Apostolos P. Refenes, 2013. "The Role of High‐Frequency Intra‐daily Data, Daily Range and Implied Volatility in Multi‐period Value‐at‐Risk Forecasting," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 32(6), pages 561-576, September.
   7. Louzis, Dimitrios P. & Xanthopoulos-Sisinis, Spyros & Refenes, Apostolos P., 2014. "Realized volatility models and alternative Value-at-Risk prediction strategies," Economic Modelling, Elsevier, vol. 40(C), pages 101-116.
   8. Liu, Chun & Maheu, John M., 2012. "Intraday dynamics of volatility and duration: Evidence from Chinese stocks," Pacific-Basin Finance Journal, Elsevier, vol. 20(3), pages 329-348.
   9. Tan, Shay-Kee & Ng, Kok-Haur & Chan, Jennifer So-Kuen & Mohamed, Ibrahim, 2019. "Quantile range-based volatility measure for modelling and forecasting volatility using high frequency data," The North American Journal of Economics and Finance, Elsevier, vol. 47(C), pages 537-551.
   10. Thanakorn Nitithumbundit & Jennifer S. K. Chan, 2020. "ECM Algorithm for Auto-Regressive Multivariate Skewed Variance Gamma Model with Unbounded Density," Methodology and Computing in Applied Probability, Springer, vol. 22(3), pages 1169-1191, September.
   11. Degiannakis, Stavros & Floros, Christos & Dent, Pamela, 2013. "Forecasting value-at-risk and expected shortfall using fractionally integrated models of conditional volatility: International evidence," International Review of Financial Analysis, Elsevier, vol. 27(C), pages 21-33.
       • Degiannakis, Stavros & Floros, Christos & Dent, Pamela, 2013. "Forecasting Value-at-Risk and Expected Shortfall using Fractionally Integrated Models of Conditional Volatility: International Evidence," MPRA Paper 80433, University Library of Munich, Germany.
   12. Chun Liu & John M Maheu, 2010. "Intraday Dynamics of Volatility and Duration: Evidence from the Chinese Stock Market," Working Papers tecipa-401, University of Toronto, Department of Economics.
   13. Chan Jennifer So Kuen & Nitithumbundit Thanakorn & Peiris Shelton & Ng Kok-Haur, 2019. "Efficient estimation of financial risk by regressing the quantiles of parametric distributions: An application to CARR models," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 23(2), pages 1-22, April.

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