Publication Search Results
Exact matches for:
- Author = Chan JSK [web profile page]
1.
Wong SYK, Chan JSK, Azizi L
Steven Y K Wong, Jennifer S K Chan, Lamiae Azizi:
Quantifying neural network uncertainty under volatility clustering,
Neurocomputing,
614
(2025),
Article 128816 (14 pages).
2.
Usman F, Chan JSK, Markov UE, Wang Y, Dong AXD
Farha Usman, Jennifer S K Chan, Udi E Markov, Yang Wang and Alice X D Dong:
Claim Prediction and Premium Pricing for Telematics Auto Insurance Data Using Poisson Regression with Lasso Regularisation,
Risks,
12
(2024),
no. 137,
33 pages.
3.
Nitithumbundit T, Chan JSK
Thanakorn Nitithumbundit & Jennifer S K Chan:
Maximum leave-one-out likelihood method for the location parameter of variance gamma distribution with unbounded density,
Journal of Statistical Computation and Simulation,
93
(2023),
no. 15,
2642–2671.
4.
Wang JJJ, Chan JSK
Joanna J J Wang and Jennifer S K Chan:
Stochastic modelling of volatility and inter-relationships in the Australian electricity markets,
Communications in Statistics - Simulation and Computation,
52
(2023),
no. 8,
3877–3896.
5.
James N, Menzies M, Chan JSK
Nick James, Max Menzies and Jennifer Chan:
Semi-Metric Portfolio Optimization: A New Algorithm Reducing Simultaneous Asset Shocks,
Econometrics,
11 (Open Access)
(2023),
no. 1,
Article 8 (33 pages).
6.
Tan SK, Ng KH, Chan JSK
Shay Kee Tan, Kok Haur Ng and Jennifer So-Kuen Chan:
Predicting Returns, Volatilities and Correlations of Stock Indices Using Multivariate Conditional Autoregressive Range and Return Models,
Mathematics,
11
(2023),
no. 1,
24 pages.
7.
Usman F, Chan JSK
Farha Usman, Jennifer S K Chan:
New loss reserve models with persistence effects to forecast trapezoidal losses in run-off triangles,
Astin Bulletin (the Journal of the International Actuarial Association),
52
(2022),
no. 3,
877–920.
8.
Peters GW, Yan H, Chan JSK
Gareth W Peters, Hongxuan Yan and Jennifer Chan:
Model risk in mortality-linked contingent claims pricing,
Journal of Risk Model Validation,
16
(2022),
no. 3,
1–53.
9.
Nitithumbundit T, Chan JSK
Thanakorn Nitithumbundit, Jennifer S K Chan:
Covid-19 impact on Cryptocurrencies market using Multivariate Time Series Models,
Quarterly Review of Economics and Finance,
86
(2022),
365–375.
10.
Chan JSK, Choy STB, Makov U, Shamir A, Shapovalov V
Jennifer S K Chan, S T Boris Choy, Udi Makov, Ariel Shamir and Vered Shapovalov:
Variable Selection Algorithm for a Mixture of Poisson Regression for Handling Overdispersion in Claims Frequency Modeling Using Telematics Car Driving Data,
Risks,
10 (Open Access)
(2022),
no. 83,
10 pages.
11.
Wong SYK, Chan JSK, Azizi L, Xu RYD
Steven Y K Wong, Jennifer S K Chan, Lamiae Azizi, Richard Y D Xu:
Supervised temporal autoencoder for stock return time-series forecasting,
Proceedings - 2021 IEEE 45th Annual Computers, Software, and Applications Conference, COMPSAC 2021,
IEEE 45th Annual Computers, Software, and Applications Conference, COMPSAC 2021,
W K Chan, B Claycomb, H Takakura, J Yang, Y Teranishi, D Towey, S Segura, H Shahria, S Reisman, S I Ahamed (eds.),
IEEE,
USA,
(2021),
1735–1741.
ISBN 978-166542463-9.
12.
Peiris MS, Chan JSK, Jajo NK
Shelton Peiris, Jennifer Chan, Nethal Jajo:
A Quick Reference Guide to Beginners of Statistics and Data Science Using RStudio,
CV. Meugah Printindo,
Indonesia,
(2021),
276.
ISBN 978-623-97079-0-3.
13.
Nitithumbundit T, Chan JSK
Thanakorn Nitithumbundit, Jennifer S K Chan:
ECM Algorithm for Auto-Regressive Multivariate Skewed Variance Gamma Model with Unbounded Density,
Methodology and Computing in Applied Probability,
22
(2020),
no. 3,
1169–1191.
14.
Phillip A, Chan JSK, Peiris MS
Andrew Phillip, Jennifer Chan, Shelton Peiris:
On generalized bivariate student-t Gegenbauer long memory stochastic volatility models with leverage: Bayesian forecasting of cryptocurrencies with a focus on Bitcoin,
Econometrics and Statistics,
16
(2020),
69–90.
15.
James N, Menzies M, Azizi L, Chan JSK
Nick James, Max Menzies, Lamiae Azizi, Jennifer Chan:
Novel semi-metrics for multivariate change point analysis and anomaly detection,
Physica D: Nonlinear Phenomena,
412
(2020),
no. November 2020,
15 pages art. no. 132636..
16.
Yatigammana RP, Chan JSK, Gerlach R
R P Yatigammana, J S K Chan and R H Gerlach:
Forecasting trade durations via ACD models with mixture distributions,
Quantitative Finance,
19
(2019),
no. 12,
2051–2067.
MR4029351
17.
Chan JSK, Ng KH, Nitithumbundit T, Peiris MS
Jennifer So Kuen Chan, Kok-Haur Ng, Thanakorn Nitithumbundit, Shelton Peiris:
Efficient estimation of financial risk by regressing the quantiles of parametric distributions: An application to CARR models,
Studies in Nonlinear Dynamics & Econometrics,
23
(2019),
no. 2,
1–22.
MR3948450
18.
Chan JSK, Ng KH, Ragell R
Jennifer So-Kuen Chan, Kok-Haur Ng, Rachel Ragell:
Bayesian return forecasts using realised range and asymmetric CARR model with various distribution assumptions,
International Review of Economics & Finance,
61
(2019),
no. May 2019,
188–212.
19.
Phillip A, Chan JSK, Peiris MS
Andrew Phillip, Jennifer Chan, Shelton Peiris:
On long memory effects in the volatility measure of cryptocurrencies,
Finance Research Letters,
28
(2019),
95–100.
20.
Tan SK, Ng KH, Chan JSK, Mohamed I
Shay-Kee Tan, Kok-Haur Ng, Jennifer So-Kuen Chan, Ibrahim Mohamed:
Quantile range-based volatility measure for modelling and forecasting volatility using high frequency data,
North American Journal of Economics and Finance,
47
(2019),
537–551.
21.
Chan JSK, Choy STB, Makov UE, Landsman Z
J S K Chan, S T B Choy, U E Makov and Z Landsman:
Modelling Insurance Losses Using Contaminated Generalised Beta Type-Ii Distribution,
ASTIN Bulletin: The Journal of the IAA,
48
(2018),
no. 2,
871–904.
22.
Phillip A, Chan JSK, Peiris MS
Andrew Phillip, Chan Jennifer S.K., Peiris Shelton:
Bayesian estimation of Gegenbauer long memory processes with stochastic volatility: methods and applications,
Studies in Nonlinear Dynamics & Econometrics,
22
(2018),
no. 3,
1–29.
23.
Phillip A, Chan JSK, Peiris MS
Andrew Phillip, Jennifer S.K.Chan, Shelton Peiris:
A new look at Cryptocurrencies,
Economics Letters,
163
(2018),
6–9.
24.
Ng KH, Peiris MS, Chan JSK, Allen DE, Ng KH
Kok Haur Ng, Shelton Peiris, Jennifer So-kuen Chan, David Allen, Kooi Huat Ng:
Efficient modelling and forecasting with range based volatility models and its application,
North American Journal of Economics and Finance,
42
(2017),
448–460.
25.
Yatigammana RP, Choy STB, Chan JSK
Rasika P Yatigammana, S T Boris Choy and Jennifer S K Chan:
Autoregressive Conditional Duration Model with an Extended Weibull Error Distribution,
Studies in Computational Intelligence,
622
(2016),
no. January 2016,
83–107.
26.
Chan JSK
Jennifer S K Chan:
Bayesian informative dropout model for longitudinal binary data with random effects using conditional and joint modeling approaches,
Biometrical Journal,
58
(2016),
no. 3,
549–569.
MR3500560
27.
Choy STB, Chan JSK, Makov UE
S T Boris Choy, Jennifer S K Chan & Udi E Makov:
Robust Bayesian analysis of loss reserving data using scale mixtures distributions,
Journal of Applied Statistics,
43
(2016),
no. 3,
396–411.
MR3441544
28.
Chan JSK, Wan WY
Jennifer So Kuen Chan and Wai Yin Wan:
Bayesian analysis of Cannabis offences using generalized Poisson geometric process model with flexible dispersion,
Journal of Statistical Computation and Simulation,
86
(2016),
no. 16,
3315–3336.
MR3534582
29.
Chan JSK
Chan, J.S.K.:
Predicting loss reserves using quantile regression,
Journal of Data Science,
13
(2016),
127–156.
30.
Yatigammana RP, Choy STB, Chan JSK
Rasika P. Yatigammana, S.T. Boris Choy and Jennifer S.K. Chan:
Autoregressive Conditional Duration Model with an Extended Weibull Error Distribution,
Causal Inference in Econometrics,
Studies in Computational Intelligence 622,
Springer,
Switzerland,
(2016),
638.
ISBN 1860-949X.
31.
Dong AXD, Chan JSK, Peters GW
Alice X.D., Dong, Jennifer S.K. Chan and Gareth W. Peters:
Risk margin quantile function via parametric and non-parametric Bayesian approaches,
Astin Bulletin,
45
(2015),
no. 3,
503–550.
32.
Chan JSK
Jennifer S.K. Chan:
Analysis of Correlation Structures using Generalized Estimating Equation Approach for Longitudinal Binary Data,
Journal of Data Science,
12
(2014),
293–305.
33.
Chan JSK, Lam CPY, Choy B
JSK Chan, CPY Lam and Boris Choy:
An innovative financial time series model: The Geometric Process model,
Advances in Intelligent Systems and Computing,
251
(2014),
81–99.
34.
Chan JSK, Choy STB, Lam CPY
Jennifer S K Chan, S T Boris Choy and Connie P Y Lam:
Modeling Electricity Price Using A Threshold Conditional Autoregressive Geometric Process Jump Model,
Communications in Statistics -- Theory and Methods,
43
(2014),
no. 10 - 12,
2505–2515.
35.
Chan JSK, Wan WY, Yu PLH
J S K. Chan, W Y Wan and P L H Yu:
A Poisson geometric process approach for predicting drop-out and committed first-time blood donors,
Journal of Applied Statistics,
41
(2014),
no. 7,
1486–1503.
36.
Chan JSK, Wan WY
Chan, Jennifer So kuen and Wan, Wai Yin:
Multivariate generalized Poisson geometric process model with scale mixtures of normal distributions,
Journal of Multivariate Analysis,
127
(2014),
72–87.
37.
Jones CGA, Kemp RI, Chan JSK
Craig G.A. Jones, Richard I. Kemp and Jennifer S.K. Chan:
The relationship between delay discounting, judicial supervision and substance use among adult drug court clients,
Psychology, Public Policy, and Law,
19
(2013),
454–465.
38.
Dong AXD, Chan JSK
Dong, A.X.D and Chan, J.S.K.:
Bayesian analysis of loss reserving using dynamic models with generalized beta distribution,
Insurance: Mathematics and Economics,
53
(2013),
no. 3,
355–365.
39.
Wang JJJ, Choy STB, Chan JSK
Joanna J J Wang, S T Boris Choy & Jennifer S K Chan:
Modelling stochastic volatility using generalized t distribution,
Journal of Statistical Computation and Simulation,
83
(2013),
no. 2,
340–354.
40.
Rosner B, Peiris MS, Chan JSK, Marchev D
Rosner, B., Peiris, S., Chan, J., Marchev, D.:
MATH1015: Biostatistics,
Third Edition,
Cengage Learning,
Australia,
(2013),
296.
ISBN 978-0170257916.
41.
Chan JSK, Lam CPY, Yu PLH, Choy STB, Chen CWS
J S K Chan, C PY . Lam, P L H Yu, S T B Choy, C W S Chen:
A Bayesian conditional autoregressive geometric process model for range data,
Computational Statistics & Data Analysi,
56
(2012),
no. 11,
3006–3019.
MR2943877
42.
Chen CWS, Chan JSK, So MKP, Lee KKM
Cathy W S Chen, Jennifer S K Chan, Mike K P So, Kevin K M Lee:
Classification in segmented regression p,
Computational Statistics and Data Analysis,
55
(2011),
no. 7,
2276–2287.
43.
Wang JJJ, Choy STB, Chan JSK
Joanna J JWang, S T Boris Choy and Jennifer S K Chan:
Modelling stochastic volatility using generalized t distribution,
Journal of Statistical Computation and Simulation,
iFirst
(2011),
no. 2011,
1–15.
44.
Chen CWS, Chan JSK, Gerlach R, Hsieh WYL
Cathy W S Chen, Jennifer S K Chan, Richard Gerlach, William Y L Hsieh:
A comparison of estimators for regression models with change points,
Statistics and Computing,
21
(2011),
no. 3,
395–414.
45.
Chan JSK, Wan WY
Jennifer S K Chan, Wai Y Wan:
Bayesian approach to analysing longitudinal bivariate binary data with informative dropout,
Computational Statistics,
26
(2011),
no. 1,
121.
46.
Rosner B, Peiris MS, Chan JSK, Marchev D
Bernard Rosner, Shelton Peiris, Jennifer Chan, Dobrin Marchev:
Descriptive Statistics,
MATH 1015: Biostatistics,
CENGAGE Learning,
Australia,
(2011),
272.
ISBN 978-0170213349.
47.
Wang JJJ, Chan JSK, Choy STB
Wang, J.J.J., Chan, J.S.K. and Choy, S.T.B.:
Stochastic Volatility Models with Leverage and Heavy-tailed Distributions: A Bayesian Approach using Scale Mixtures,
Computational Statistics and Data Analysis,
55
(2011),
852–862.
48.
Wan WY, Chan JSK
Wan, W.Y. and Chan, J.S.K.:
Bayesian analysis of robust Poisson geometric process model using heavy-tailed distributions,
Computational Statistics and Data Analysis,
55
(2011),
687–702.
49.
Chan JSK, Leung DYP
Chan, J.S.K. and Leung, D.Y.P.:
Binary geometric process model for the modeling of longitudinal binary data with trend,
Computational Statistics,
25
(2010),
505–536.
50.
Wan WY, Chan JSK
W Y Wan and JSK Chan:
A new approach for handling longitudinal count data with zero-inflation and overdispersion: Poisson Geometric Process Model,
Biometrical Journal,
51
(2009),
no. 4,
556–570.
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