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S.T. Boris Choy

Personal Details

First Name:S.T. Boris
Middle Name:
Last Name:Choy
Suffix:
RePEc Short-ID:pch752
http://www.econ.usyd.edu.au/staff/borisc

Affiliation

Discipline of Business Analytics
Business School
University of Sydney

Sydney, Australia
http://sydney.edu.au/business/business_analytics

: + 61 2 9351 6584
+ 61 2 9351 6409
Sydney, NSW 2006
RePEc:edi:dxusyau (more details at EDIRC)

Research output

as
Jump to: Working papers Articles

Working papers

  1. Jennifer Chan & Boris Choy & Udi Makov, 2007. "Robust Bayesian Analysis of Loss Reserves Data Using the Generalized-t Distribution," Research Paper Series 196, Quantitative Finance Research Centre, University of Technology, Sydney.

Articles

  1. Wang, Joanna J.J. & Chan, Jennifer S.K. & Choy, S.T. Boris, 2011. "Stochastic volatility models with leverage and heavy-tailed distributions: A Bayesian approach using scale mixtures," Computational Statistics & Data Analysis, Elsevier, pages 852-862.
  2. Chan, Jennifer S.K. & Leung, Doris Y.P. & Boris Choy, S.T. & Wan, Wai Y., 2009. "Nonignorable dropout models for longitudinal binary data with random effects: An application of Monte Carlo approximation through the Gibbs output," Computational Statistics & Data Analysis, Elsevier, pages 4530-4545.
  3. Choy, S. T. Boris & Walker, Stephen G., 2003. "The extended exponential power distribution and Bayesian robustness," Statistics & Probability Letters, Elsevier, pages 227-232.
  4. S. Choy & A. Smith, 1997. "Hierarchical models with scale mixtures of normal distributions," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 6(1), pages 205-221, June.

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. Jennifer Chan & Boris Choy & Udi Makov, 2007. "Robust Bayesian Analysis of Loss Reserves Data Using the Generalized-t Distribution," Research Paper Series 196, Quantitative Finance Research Centre, University of Technology, Sydney.

    Cited by:

    1. Boratyńska, Agata, 2017. "Robust Bayesian estimation and prediction of reserves in exponential model with quadratic variance function," Insurance: Mathematics and Economics, Elsevier, vol. 76(C), pages 135-140.
    2. Wan, Wai-Yin & Chan, Jennifer So-Kuen, 2011. "Bayesian analysis of robust Poisson geometric process model using heavy-tailed distributions," Computational Statistics & Data Analysis, Elsevier, pages 687-702.
    3. Dong, A.X.D. & Chan, J.S.K., 2013. "Bayesian analysis of loss reserving using dynamic models with generalized beta distribution," Insurance: Mathematics and Economics, Elsevier, vol. 53(2), pages 355-365.
    4. Alice X. D. Dong & Jennifer S. K. Chan & Gareth W. Peters, 2014. "Risk Margin Quantile Function Via Parametric and Non-Parametric Bayesian Quantile Regression," Papers 1402.2492, arXiv.org.
    5. Gareth W. Peters & Wilson Y. Chen & Richard H. Gerlach, 2016. "Estimating Quantile Families of Loss Distributions for Non-Life Insurance Modelling via L-moments," Papers 1603.01041, arXiv.org.
    6. Gareth W. Peters & Wilson Ye Chen & Richard H. Gerlach, 2016. "Estimating Quantile Families of Loss Distributions for Non-Life Insurance Modelling via L-Moments," Risks, MDPI, Open Access Journal, vol. 4(2), pages 1-41, May.

Articles

  1. Wang, Joanna J.J. & Chan, Jennifer S.K. & Choy, S.T. Boris, 2011. "Stochastic volatility models with leverage and heavy-tailed distributions: A Bayesian approach using scale mixtures," Computational Statistics & Data Analysis, Elsevier, pages 852-862.

    Cited by:

    1. Sujay Mukhoti & Pritam Ranjan, 2016. "Mean-correction and Higher Order Moments for a Stochastic Volatility Model with Correlated Errors," Papers 1605.02418, arXiv.org.
    2. Lopes Moreira Da Veiga, María Helena & Ruiz Ortega, Esther & Mao, Xiuping, 2013. "One for all : nesting asymmetric stochastic volatility models," DES - Working Papers. Statistics and Econometrics. WS ws131110, Universidad Carlos III de Madrid. Departamento de Estadística.
    3. Tsiotas, Georgios, 2012. "On generalised asymmetric stochastic volatility models," Computational Statistics & Data Analysis, Elsevier, pages 151-172.
    4. Jerzy P. Rydlewski & Ma{l}gorzata Snarska, 2012. "On Geometric Ergodicity of Skewed - SVCHARME models," Papers 1209.1544, arXiv.org.
    5. Yong Li & Tao Zeng & Jun Yu, 2012. "Robust Deviance Information Criterion for Latent Variable Models," Working Papers 30-2012, Singapore Management University, School of Economics.
    6. Shirota, Shinichiro & Hizu, Takayuki & Omori, Yasuhiro, 2014. "Realized stochastic volatility with leverage and long memory," Computational Statistics & Data Analysis, Elsevier, pages 618-641.
    7. Ying Wang & Sai Tsang Boris Choy & Hoi Ying Wong, 2016. "Bayesian Option Pricing Framework with Stochastic Volatility for FX Data," Risks, MDPI, Open Access Journal, vol. 4(4), pages 1-12, December.
    8. Lopes Moreira Da Veiga, María Helena & Ruiz Ortega, Esther & Mao, Xiuping, 2014. "Score driven asymmetric stochastic volatility models," DES - Working Papers. Statistics and Econometrics. WS ws142618, Universidad Carlos III de Madrid. Departamento de Estadística.
    9. Joshua C C Chan & Cody Y L Hsiao, 2013. "Estimation of Stochastic Volatility Models with Heavy Tails and Serial Dependence," CAMA Working Papers 2013-74, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    10. Kastner, Gregor & Frühwirth-Schnatter, Sylvia, 2014. "Ancillarity-sufficiency interweaving strategy (ASIS) for boosting MCMC estimation of stochastic volatility models," Computational Statistics & Data Analysis, Elsevier, pages 408-423.
    11. Stojanović, Vladica S. & Popović, Biljana Č. & Milovanović, Gradimir V., 2016. "The Split-SV model," Computational Statistics & Data Analysis, Elsevier, pages 560-581.
    12. Patricia Lengua & Cristian Bayes & Gabriel Rodríguez, 2015. " A Stochastic Volatility Model with GH Skew Student’s t-Distribution: Application to Latin-American Stock Returns," Documentos de Trabajo / Working Papers 2015-405, Departamento de Economía - Pontificia Universidad Católica del Perú.
    13. Nakajima Jouchi, 2013. "Stochastic volatility model with regime-switching skewness in heavy-tailed errors for exchange rate returns," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 17(5), pages 499-520, December.
    14. Wang, Joanna J.J., 2012. "On asymmetric generalised t stochastic volatility models," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 82(11), pages 2079-2095.

  2. Choy, S. T. Boris & Walker, Stephen G., 2003. "The extended exponential power distribution and Bayesian robustness," Statistics & Probability Letters, Elsevier, pages 227-232.

    Cited by:

    1. Tumlinson, Samuel E., 2015. "On the non-existence of maximum likelihood estimates for the extended exponential power distribution and its generalizations," Statistics & Probability Letters, Elsevier, pages 111-114.
    2. Sandro Sapio, 2012. "Modeling the distribution of day-ahead electricity returns: a comparison," Quantitative Finance, Taylor & Francis Journals, vol. 12(12), pages 1935-1949, December.
    3. Wan, Wai-Yin & Chan, Jennifer So-Kuen, 2011. "Bayesian analysis of robust Poisson geometric process model using heavy-tailed distributions," Computational Statistics & Data Analysis, Elsevier, pages 687-702.
    4. Fung, Thomas & Seneta, Eugene, 2008. "A characterisation of scale mixtures of the uniform distribution," Statistics & Probability Letters, Elsevier, pages 2883-2888.

  3. S. Choy & A. Smith, 1997. "Hierarchical models with scale mixtures of normal distributions," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 6(1), pages 205-221, June.

    Cited by:

    1. Choy, S. T. Boris & Walker, Stephen G., 2003. "The extended exponential power distribution and Bayesian robustness," Statistics & Probability Letters, Elsevier, pages 227-232.
    2. Chan, Jennifer S.K. & Leung, Doris Y.P. & Boris Choy, S.T. & Wan, Wai Y., 2009. "Nonignorable dropout models for longitudinal binary data with random effects: An application of Monte Carlo approximation through the Gibbs output," Computational Statistics & Data Analysis, Elsevier, pages 4530-4545.
    3. Wang, Joanna J.J. & Chan, Jennifer S.K. & Choy, S.T. Boris, 2011. "Stochastic volatility models with leverage and heavy-tailed distributions: A Bayesian approach using scale mixtures," Computational Statistics & Data Analysis, Elsevier, pages 852-862.
    4. Wan, Wai-Yin & Chan, Jennifer So-Kuen, 2011. "Bayesian analysis of robust Poisson geometric process model using heavy-tailed distributions," Computational Statistics & Data Analysis, Elsevier, pages 687-702.
    5. Marín, J.M. & Rodríguez-Bernal, M.T., 2012. "Multiple hypothesis testing and clustering with mixtures of non-central t-distributions applied in microarray data analysis," Computational Statistics & Data Analysis, Elsevier, pages 1898-1907.
    6. Chan, Jennifer S.K. & Kuk, Anthony Y.C. & Yam, Carrie H.K., 2005. "Monte Carlo approximation through Gibbs output in generalized linear mixed models," Journal of Multivariate Analysis, Elsevier, vol. 94(2), pages 300-312, June.
    7. Chan, Jennifer So Kuen & Wan, Wai Yin, 2014. "Multivariate generalized Poisson geometric process model with scale mixtures of normal distributions," Journal of Multivariate Analysis, Elsevier, vol. 127(C), pages 72-87.
    8. Rodríguez Bernal, M. T. & Marín Díazaraque, Juan Miguel, 2010. "Multiple hypothesis testing and clustering with mixtures of non-central t-distributions applied in microarray data analysis," DES - Working Papers. Statistics and Econometrics. WS ws104427, Universidad Carlos III de Madrid. Departamento de Estadística.
    9. Chan, J.S.K. & Lam, C.P.Y. & Yu, P.L.H. & Choy, S.T.B. & Chen, C.W.S., 2012. "A Bayesian conditional autoregressive geometric process model for range data," Computational Statistics & Data Analysis, Elsevier, pages 3006-3019.

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 1 paper 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-ECM: Econometrics (1) 2007-06-30
  2. NEP-ETS: Econometric Time Series (1) 2007-06-30
  3. NEP-FOR: Forecasting (1) 2007-06-30
  4. NEP-RMG: Risk Management (1) 2007-06-30

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