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Han Lin Shang

Personal Details

First Name:Han Lin
Middle Name:
Last Name:Shang
Suffix:
RePEc Short-ID:psh533
[This author has chosen not to make the email address public]
https://researchers.mq.edu.au/en/persons/hanlin-shang
Department of Actuarial Studies and Business Analytics Level 7, 4 Eastern Road, Macquarie University, NSW 2109, Australia
Terminal Degree:2010 Department of Econometrics and Business Statistics; Monash Business School; Monash University (from RePEc Genealogy)

Affiliation

Business School
Macquarie University

Sydney, Australia
https://www.mq.edu.au/macquarie-business-school
RePEc:edi:defmqau (more details at EDIRC)

Research output

as
Jump to: Working papers Articles

Working papers

  1. Degui Li & Runze Li & Han Lin Shang, 2023. "Detection and Estimation of Structural Breaks in High-Dimensional Functional Time Series," Papers 2304.07003, arXiv.org.
  2. Han Lin Shang & Fearghal Kearney, 2021. "Dynamic functional time-series forecasts of foreign exchange implied volatility surfaces," Papers 2107.14026, arXiv.org.
  3. Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.
  4. Rob J Hyndman & Yijun Zeng & Han Lin Shang, 2020. "Forecasting the Old-Age Dependency Ratio to Determine a Sustainable Pension Age," Monash Econometrics and Business Statistics Working Papers 31/20, Monash University, Department of Econometrics and Business Statistics.
  5. Fearghal Kearney & Han Lin Shang & Lisa Sheenan, 2019. "Implied volatility surface predictability: the case of commodity markets," Papers 1909.11009, arXiv.org.
  6. Han Lin Shang & Rob J Hyndman, 2016. "Grouped functional time series forecasting: An application to age-specific mortality rates," Monash Econometrics and Business Statistics Working Papers 4/16, Monash University, Department of Econometrics and Business Statistics.
  7. Xibin Zhang & Maxwell L. King & Han Lin Shang, 2013. "A sampling algorithm for bandwidth estimation in a nonparametric regression model with a flexible error density," Monash Econometrics and Business Statistics Working Papers 20/13, Monash University, Department of Econometrics and Business Statistics.
  8. Xibin Zhang & Maxwell L. King & Han Lin Shang, 2013. "Bayesian bandwidth selection for a nonparametric regession model with mixed types of regressors," Monash Econometrics and Business Statistics Working Papers 13/13, Monash University, Department of Econometrics and Business Statistics.
  9. Han Lin Shang, 2012. "Point and interval forecasts of age-specific fertility rates: a comparison of functional principal component methods," Monash Econometrics and Business Statistics Working Papers 10/12, Monash University, Department of Econometrics and Business Statistics.
  10. Han Lin Shang, 2011. "A survey of functional principal component analysis," Monash Econometrics and Business Statistics Working Papers 6/11, Monash University, Department of Econometrics and Business Statistics.
  11. Xibin Zhang & Maxwell L. King & Han Lin Shang, 2011. "Bayesian estimation of bandwidths for a nonparametric regression model with a flexible error density," Monash Econometrics and Business Statistics Working Papers 10/11, Monash University, Department of Econometrics and Business Statistics.
  12. Han Lin Shang, 2010. "Nonparametric modeling and forecasting electricity demand: an empirical study," Monash Econometrics and Business Statistics Working Papers 19/10, Monash University, Department of Econometrics and Business Statistics.
  13. Han Lin Shang & Rob J Hyndman & Heather Booth, 2010. "A comparison of ten principal component methods for forecasting mortality rates," Monash Econometrics and Business Statistics Working Papers 8/10, Monash University, Department of Econometrics and Business Statistics.
  14. Han Lin Shang & Rob J Hyndman, 2009. "Nonparametric time series forecasting with dynamic updating," Monash Econometrics and Business Statistics Working Papers 8/09, Monash University, Department of Econometrics and Business Statistics.
  15. Rob J. Hyndman & Han Lin Shang, 2008. "Rainbow plots, Bagplots and Boxplots for Functional Data," Monash Econometrics and Business Statistics Working Papers 9/08, Monash University, Department of Econometrics and Business Statistics.

Articles

  1. Sizhe Chen & Han Lin Shang & Yang Yang, 2025. "Is the age pension in Australia sustainable and fair? Evidence from forecasting the old-age dependency ratio using the Hamilton-Perry model," Journal of Population Research, Springer, vol. 42(1), pages 1-27, March.
  2. Yang, Yang & Shang, Han Lin & Raymer, James, 2024. "Forecasting Australian fertility by age, region, and birthplace," International Journal of Forecasting, Elsevier, vol. 40(2), pages 532-548.
  3. Shaokang Wang & Han Lin Shang & Leonie Tickle & Han Li, 2024. "Forecasting Age- and Sex-Specific Survival Functions: Application to Annuity Pricing," Risks, MDPI, vol. 12(7), pages 1-15, July.
  4. Dong Michelle & Bruhn Aaron & Shang Han Lin & Hui Francis, 2024. "Assessing the Impact of Climate Risk Stresses on Life Insurance Portfolios," Asia-Pacific Journal of Risk and Insurance, De Gruyter, vol. 18(1), pages 87-114, January.
  5. Han Lin Shang, 2024. "Bootstrapping Long-Run Covariance of Stationary Functional Time Series," Forecasting, MDPI, vol. 6(1), pages 1-14, February.
  6. Ufuk Beyaztas & Mujgan Tez & Han Lin Shang, 2024. "Robust scalar-on-function partial quantile regression," Journal of Applied Statistics, Taylor & Francis Journals, vol. 51(7), pages 1359-1377, May.
  7. Han Lin Shang & Kaiying Ji, 2023. "Forecasting intraday financial time series with sieve bootstrapping and dynamic updating," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(8), pages 1973-1988, December.
  8. Han Lin Shang, 2023. "Sieve bootstrapping the memory parameter in long-range dependent stationary functional time series," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 107(3), pages 421-441, September.
  9. Efstathios Paparoditis & Han Lin Shang, 2023. "Bootstrap Prediction Bands for Functional Time Series," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 118(542), pages 972-986, April.
  10. Muge Mutis & Ufuk Beyaztas & Gulhayat Golbasi Simsek & Han Lin Shang, 2023. "A robust scalar-on-function logistic regression for classification," Communications in Statistics - Theory and Methods, Taylor & Francis Journals, vol. 52(23), pages 8538-8554, December.
  11. Antonio Elías & Raúl Jiménez & Han Lin Shang, 2023. "Depth-based reconstruction method for incomplete functional data," Computational Statistics, Springer, vol. 38(3), pages 1507-1535, September.
  12. Shang, Han Lin & Haberman, Steven & Xu, Ruofan, 2022. "Multi-population modelling and forecasting life-table death counts," Insurance: Mathematics and Economics, Elsevier, vol. 106(C), pages 239-253.
  13. Han Lin Shang & Jiguo Cao & Peijun Sang, 2022. "Stopping time detection of wood panel compression: A functional time‐series approach," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 71(5), pages 1205-1224, November.
  14. Shang Han Lin & Zhang Xibin, 2022. "Bayesian bandwidth estimation for local linear fitting in nonparametric regression models," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 26(1), pages 55-71, February.
  15. Han Lin Shang & Ruofan Xu, 2022. "Change point detection for COVID-19 excess deaths in Belgium," Journal of Population Research, Springer, vol. 39(4), pages 557-565, December.
  16. Yang Yang & Han Lin Shang & Joel E. Cohen, 2022. "Temporal and spatial Taylor's law: Application to Japanese subnational mortality rates," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 185(4), pages 1979-2006, October.
  17. Ufuk Beyaztas & Han Lin Shang & Aylin Alin, 2022. "Function-on-Function Partial Quantile Regression," Journal of Agricultural, Biological and Environmental Statistics, Springer;The International Biometric Society;American Statistical Association, vol. 27(1), pages 149-174, March.
  18. Zhe Michelle Dong & Han Lin Shang & Aaron Bruhn, 2022. "Air Pollution and Mortality Impacts," Risks, MDPI, vol. 10(6), pages 1-21, June.
  19. Elías, Antonio & Jiménez, Raúl & Shang, Han Lin, 2022. "On projection methods for functional time series forecasting," Journal of Multivariate Analysis, Elsevier, vol. 189(C).
  20. Ufuk Beyaztas & Han Lin Shang, 2022. "Robust bootstrap prediction intervals for univariate and multivariate autoregressive time series models," Journal of Applied Statistics, Taylor & Francis Journals, vol. 49(5), pages 1179-1202, April.
  21. Ufuk Beyaztas & Hanlin Shang, 2022. "Machine-Learning-Based Functional Time Series Forecasting: Application to Age-Specific Mortality Rates," Forecasting, MDPI, vol. 4(1), pages 1-15, March.
  22. Petropoulos, Fotios & Apiletti, Daniele & Assimakopoulos, Vassilios & Babai, Mohamed Zied & Barrow, Devon K. & Ben Taieb, Souhaib & Bergmeir, Christoph & Bessa, Ricardo J. & Bijak, Jakub & Boylan, Joh, 2022. "Forecasting: theory and practice," International Journal of Forecasting, Elsevier, vol. 38(3), pages 705-871.
    • Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.
  23. Xin Huang & Han Lin Shang & David Pitt, 2022. "A model sufficiency test using permutation entropy," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(5), pages 1017-1036, August.
  24. Yang, Yang & Yang, Yanrong & Shang, Han Lin, 2022. "Feature extraction for functional time series: Theory and application to NIR spectroscopy data," Journal of Multivariate Analysis, Elsevier, vol. 189(C).
  25. Shang, Han Lin & Kearney, Fearghal, 2022. "Dynamic functional time-series forecasts of foreign exchange implied volatility surfaces," International Journal of Forecasting, Elsevier, vol. 38(3), pages 1025-1049.
  26. Degui Li & Peter M. Robinson & Han Lin Shang, 2021. "Local Whittle estimation of long‐range dependence for functional time series," Journal of Time Series Analysis, Wiley Blackwell, vol. 42(5-6), pages 685-695, September.
  27. Han Lin Shang & Yang Yang, 2021. "Forecasting Australian subnational age-specific mortality rates," Journal of Population Research, Springer, vol. 38(1), pages 1-24, March.
  28. Butler, Sunil & Kokoszka, Piotr & Miao, Hong & Shang, Han Lin, 2021. "Neural network prediction of crude oil futures using B-splines," Energy Economics, Elsevier, vol. 94(C).
  29. Ufuk Beyaztas & Han Lin Shang, 2021. "A partial least squares approach for function-on-function interaction regression," Computational Statistics, Springer, vol. 36(2), pages 911-939, June.
  30. Han Lin Shang & Kaiying Ji & Ufuk Beyaztas, 2021. "Granger causality of bivariate stationary curve time series," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(4), pages 626-635, July.
  31. Han Lin Shang, 2021. "Bayesian bandwidth estimation and semi-metric selection for a functional partial linear model with unknown error density," Journal of Applied Statistics, Taylor & Francis Journals, vol. 48(4), pages 583-604, March.
  32. Han Lin Shang, 2020. "Dynamic principal component regression for forecasting functional time series in a group structure," Scandinavian Actuarial Journal, Taylor & Francis Journals, vol. 2020(4), pages 307-322, April.
  33. Degui Li & Peter M. Robinson & Han Lin Shang, 2020. "Long-Range Dependent Curve Time Series," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 115(530), pages 957-971, April.
  34. Shang Han Lin, 2020. "A Comparison of Hurst Exponent Estimators in Long-range Dependent Curve Time Series," Journal of Time Series Econometrics, De Gruyter, vol. 12(1), pages 1-39, January.
  35. Fearghal Kearney & Han Lin Shang, 2020. "Uncovering predictability in the evolution of the WTI oil futures curve," European Financial Management, European Financial Management Association, vol. 26(1), pages 238-257, January.
  36. Shang, Han Lin & Haberman, Steven, 2020. "Forecasting age distribution of death counts: an application to annuity pricing," Annals of Actuarial Science, Cambridge University Press, vol. 14(1), pages 150-169, March.
  37. Shang, Han Lin & Haberman, Steven, 2020. "Forecasting Multiple Functional Time Series In A Group Structure: An Application To Mortality," ASTIN Bulletin, Cambridge University Press, vol. 50(2), pages 357-379, May.
  38. Han Lin Shang & Steven Haberman, 2020. "Retiree Mortality Forecasting: A Partial Age-Range or a Full Age-Range Model?," Risks, MDPI, vol. 8(3), pages 1-11, July.
  39. Gao, Yuan & Shang, Han Lin & Yang, Yanrong, 2019. "High-dimensional functional time series forecasting: An application to age-specific mortality rates," Journal of Multivariate Analysis, Elsevier, vol. 170(C), pages 232-243.
  40. Han Lin Shang & Yang Yang & Fearghal Kearney, 2019. "Intraday forecasts of a volatility index: functional time series methods with dynamic updating," Annals of Operations Research, Springer, vol. 282(1), pages 331-354, November.
  41. Kearney, Fearghal & Shang, Han Lin & Sheenan, Lisa, 2019. "Implied volatility surface predictability: The case of commodity markets," Journal of Banking & Finance, Elsevier, vol. 108(C).
  42. Francis K. C. Hui & C. You & H. L. Shang & Samuel Müller, 2019. "Semiparametric Regression Using Variational Approximations," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 114(528), pages 1765-1777, October.
  43. Han Lin Shang, 2019. "Visualizing rate of change: an application to age‐specific fertility rates," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 182(1), pages 249-262, January.
  44. Kokoszka, Piotr & Miao, Hong & Petersen, Alexander & Shang, Han Lin, 2019. "Forecasting of density functions with an application to cross-sectional and intraday returns," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1304-1317.
  45. Shang, Han Lin, 2019. "Dynamic Principal Component Regression: Application To Age-Specific Mortality Forecasting," ASTIN Bulletin, Cambridge University Press, vol. 49(3), pages 619-645, September.
  46. Han Lin Shang, 2017. "Reconciling Forecasts of Infant Mortality Rates at National and Sub-National Levels: Grouped Time-Series Methods," Population Research and Policy Review, Springer;Southern Demographic Association (SDA), vol. 36(1), pages 55-84, February.
  47. Han Lin Shang, 2017. "Forecasting intraday S&P 500 index returns: A functional time series approach," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 36(7), pages 741-755, November.
  48. Shang, Han Lin & Haberman, Steven, 2017. "Grouped multivariate and functional time series forecasting:An application to annuity pricing," Insurance: Mathematics and Economics, Elsevier, vol. 75(C), pages 166-179.
  49. Shang, Han Lin, 2017. "Functional time series forecasting with dynamic updating: An application to intraday particulate matter concentration," Econometrics and Statistics, Elsevier, vol. 1(C), pages 184-200.
  50. Gregory Rice & Han Lin Shang, 2017. "A Plug-in Bandwidth Selection Procedure for Long-Run Covariance Estimation with Stationary Functional Time Series," Journal of Time Series Analysis, Wiley Blackwell, vol. 38(4), pages 591-609, July.
  51. Philip T. Reiss & Jeff Goldsmith & Han Lin Shang & R. Todd Ogden, 2017. "Methods for Scalar-on-Function Regression," International Statistical Review, International Statistical Institute, vol. 85(2), pages 228-249, August.
  52. Yuan Gao & Han Lin Shang, 2017. "Multivariate Functional Time Series Forecasting: Application to Age-Specific Mortality Rates," Risks, MDPI, vol. 5(2), pages 1-18, March.
  53. Xibin Zhang & Maxwell L. King & Han Lin Shang, 2016. "Bayesian Bandwidth Selection for a Nonparametric Regression Model with Mixed Types of Regressors," Econometrics, MDPI, vol. 4(2), pages 1-27, April.
  54. Shang, Han Lin, 2016. "A Bayesian approach for determining the optimal semi-metric and bandwidth in scalar-on-function quantile regression with unknown error density and dependent functional data," Journal of Multivariate Analysis, Elsevier, vol. 146(C), pages 95-104.
  55. Shang, Han Lin & Smith, Peter W.F. & Bijak, Jakub & Wiśniowski, Arkadiusz, 2016. "A multilevel functional data method for forecasting population, with an application to the United Kingdom," International Journal of Forecasting, Elsevier, vol. 32(3), pages 629-649.
  56. Han Lin Shang, 2015. "Statistically tested comparisons of the accuracy of forecasting methods for age-specific and sex-specific mortality and life expectancy," Population Studies, Taylor & Francis Journals, vol. 69(3), pages 317-335, November.
  57. Han Lin Shang, 2014. "Bayesian bandwidth estimation for a functional nonparametric regression model with mixed types of regressors and unknown error density," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 26(3), pages 599-615, September.
  58. Han Shang, 2014. "Bayesian bandwidth estimation for a semi-functional partial linear regression model with unknown error density," Computational Statistics, Springer, vol. 29(3), pages 829-848, June.
  59. Zhang, Xibin & King, Maxwell L. & Shang, Han Lin, 2014. "A sampling algorithm for bandwidth estimation in a nonparametric regression model with a flexible error density," Computational Statistics & Data Analysis, Elsevier, vol. 78(C), pages 218-234.
  60. Han Shang, 2014. "A survey of functional principal component analysis," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 98(2), pages 121-142, April.
  61. Shang, Han Lin, 2013. "Bayesian bandwidth estimation for a nonparametric functional regression model with unknown error density," Computational Statistics & Data Analysis, Elsevier, vol. 67(C), pages 185-198.
  62. Han Lin Shang, 2013. "The BUGS book: a practical introduction to Bayesian analysis," Journal of Applied Statistics, Taylor & Francis Journals, vol. 40(12), pages 2774-2775, December.
  63. Han Lin Shang, 2013. "Functional time series approach for forecasting very short-term electricity demand," Journal of Applied Statistics, Taylor & Francis Journals, vol. 40(1), pages 152-168, January.
  64. Han Lin Shang, 2012. "Point and interval forecasts of age-specific life expectancies," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 27(21), pages 593-644.
  65. Han Lin Shang, 2012. "Graphics for statistics and data analysis with R," Journal of Applied Statistics, Taylor & Francis Journals, vol. 39(8), pages 1843-1844, August.
  66. Han Lin Shang, 2011. "Dynamic linear models with R," Journal of Applied Statistics, Taylor & Francis Journals, vol. 38(10), pages 2369-2370.
  67. Han Lin Shang, 2011. "Bayesian Nonparametrics," Journal of Applied Statistics, Taylor & Francis Journals, vol. 38(12), pages 2990-2990, December.
  68. Han Lin Shang & Heather Booth & Rob Hyndman, 2011. "Point and interval forecasts of mortality rates and life expectancy: A comparison of ten principal component methods," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 25(5), pages 173-214.
  69. Hyndman, Rob J. & Ahmed, Roman A. & Athanasopoulos, George & Shang, Han Lin, 2011. "Optimal combination forecasts for hierarchical time series," Computational Statistics & Data Analysis, Elsevier, vol. 55(9), pages 2579-2589, September.
  70. Shang, Han Lin & Hyndman, Rob.J., 2011. "Nonparametric time series forecasting with dynamic updating," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 81(7), pages 1310-1324.
  71. Han Lin Shang, 2011. "Non-Parametric Econometrics," Journal of Applied Statistics, Taylor & Francis Journals, vol. 38(12), pages 2992-2992, December.

More information

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Statistics

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Rankings

This author is among the top 5% authors according to these criteria:
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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 15 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-FOR: Forecasting (12) 2009-09-26 2010-05-02 2010-11-27 2011-09-05 2012-05-02 2013-06-30 2013-11-16 2016-04-04 2019-10-07 2020-10-12 2021-08-16 2022-03-21. Author is listed
  2. NEP-ECM: Econometrics (7) 2009-03-22 2009-09-26 2010-11-27 2011-06-18 2011-09-05 2013-11-16 2023-05-15. Author is listed
  3. NEP-ETS: Econometric Time Series (5) 2009-09-26 2011-06-18 2016-04-04 2021-08-16 2023-05-15. Author is listed
  4. NEP-AGE: Economics of Ageing (3) 2010-05-02 2016-04-04 2020-10-12
  5. NEP-RMG: Risk Management (3) 2011-09-05 2020-10-12 2021-08-16
  6. NEP-ORE: Operations Research (2) 2011-09-05 2020-10-12
  7. NEP-BAN: Banking (1) 2022-03-21
  8. NEP-CWA: Central and Western Asia (1) 2022-03-21
  9. NEP-DEM: Demographic Economics (1) 2012-05-02
  10. NEP-ENE: Energy Economics (1) 2010-11-27
  11. NEP-HEA: Health Economics (1) 2010-05-02
  12. NEP-ISF: Islamic Finance (1) 2021-08-16
  13. NEP-LAB: Labour Economics (1) 2016-04-04
  14. NEP-UPT: Utility Models and Prospect Theory (1) 2022-03-21

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