Bernard Wong

696 total citations
44 papers, 435 citations indexed

About

Bernard Wong is a scholar working on Management Science and Operations Research, Demography and Finance. According to data from OpenAlex, Bernard Wong has authored 44 papers receiving a total of 435 indexed citations (citations by other indexed papers that have themselves been cited), including 35 papers in Management Science and Operations Research, 21 papers in Demography and 20 papers in Finance. Recurrent topics in Bernard Wong's work include Probability and Risk Models (32 papers), Insurance, Mortality, Demography, Risk Management (21 papers) and Stochastic processes and financial applications (13 papers). Bernard Wong is often cited by papers focused on Probability and Risk Models (32 papers), Insurance, Mortality, Demography, Risk Management (21 papers) and Stochastic processes and financial applications (13 papers). Bernard Wong collaborates with scholars based in Australia, Canada and United States. Bernard Wong's co-authors include Benjamin Avanzi, C. C. Heyde, Eric C.K. Cheung, Jae‐Kyung Woo, Greg Taylor, Phuong Anh Vu, Andrew E. B. Lim, José Luis Pérez, Kazutoshi Yamazaki and Pierre Lafaye de Micheaux and has published in prestigious journals such as European Journal of Operational Research, Journal of Mathematical Analysis and Applications and Journal of Applied Probability.

In The Last Decade

Bernard Wong

42 papers receiving 419 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Bernard Wong Australia 12 301 249 215 149 75 44 435
Jiwook Jang Australia 9 167 0.6× 197 0.8× 148 0.7× 112 0.8× 45 0.6× 36 372
Andrew Cheuk-Yin Ng Hong Kong 9 188 0.6× 194 0.8× 180 0.8× 94 0.6× 46 0.6× 22 350
Stefan Thonhauser Austria 9 401 1.3× 208 0.8× 311 1.4× 118 0.8× 97 1.3× 20 429
Masahiko Egami Japan 10 187 0.6× 237 1.0× 124 0.6× 130 0.9× 22 0.3× 34 341
Jae‐Kyung Woo Australia 11 403 1.3× 190 0.8× 243 1.1× 93 0.6× 204 2.7× 38 450
Manuel Morales Canada 9 217 0.7× 187 0.8× 137 0.6× 71 0.5× 67 0.9× 23 294
Giacomo Scandolo Italy 7 582 1.9× 463 1.9× 125 0.6× 302 2.0× 92 1.2× 14 735
Tiantian Mao China 14 335 1.1× 235 0.9× 79 0.4× 146 1.0× 147 2.0× 64 451
J. Haezendonck Belgium 10 331 1.1× 220 0.9× 209 1.0× 199 1.3× 62 0.8× 18 451
Hélène Cossette Canada 15 575 1.9× 339 1.4× 309 1.4× 188 1.3× 273 3.6× 41 718

Countries citing papers authored by Bernard Wong

Since Specialization
Citations

This map shows the geographic impact of Bernard Wong's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Bernard Wong with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Bernard Wong more than expected).

Fields of papers citing papers by Bernard Wong

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Bernard Wong. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Bernard Wong. The network helps show where Bernard Wong may publish in the future.

Co-authorship network of co-authors of Bernard Wong

This figure shows the co-authorship network connecting the top 25 collaborators of Bernard Wong. A scholar is included among the top collaborators of Bernard Wong based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Bernard Wong. Bernard Wong is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Avanzi, Benjamin, et al.. (2025). On the Evolution of Data Breach Reporting Patterns and Frequency in the United States: A Cross-State Analysis. North American Actuarial Journal. 29(4). 833–864.
2.
Avanzi, Benjamin, et al.. (2024). Machine Learning with High-Cardinality Categorical Features in Actuarial Applications. Astin Bulletin. 54(2). 213–238. 8 indexed citations
3.
Avanzi, Benjamin, et al.. (2022). Stochastic loss reserving with mixture density neural networks. Insurance Mathematics and Economics. 105. 144–174. 6 indexed citations
4.
Avanzi, Benjamin, et al.. (2021). A counterexample to the existence of a general central limit theorem for pairwise independent identically distributed random variables. Journal of Mathematical Analysis and Applications. 499(1). 124982–124982. 5 indexed citations
5.
Avanzi, Benjamin, et al.. (2021). Optimal periodic dividend strategies for spectrally negative Lévy processes with fixed transaction costs. Scandinavian Actuarial Journal. 2021(8). 645–670. 5 indexed citations
6.
Avanzi, Benjamin, et al.. (2021). On the modelling of multivariate counts with Cox processes and dependent shot noise intensities. Insurance Mathematics and Economics. 99. 9–24. 4 indexed citations
7.
Avanzi, Benjamin, G. B. Taylor, Phuong Anh Vu, & Bernard Wong. (2020). A multivariate evolutionary generalised linear model framework with adaptive estimation for claims reserving. Insurance Mathematics and Economics. 93. 50–71. 4 indexed citations
8.
Avanzi, Benjamin, Greg Taylor, & Bernard Wong. (2018). COMMON SHOCK MODELS FOR CLAIM ARRAYS. Astin Bulletin. 48(3). 1109–1136. 7 indexed citations
9.
Avanzi, Benjamin, et al.. (2018). How to proxy the unmodellable: Analysing granular insurance claims in the presence of unobservable or complex drivers. UNSWorks (University of New South Wales, Sydney, Australia). 1 indexed citations
10.
Avanzi, Benjamin, Lars Henriksen, & Bernard Wong. (2018). ON THE DISTRIBUTION OF THE EXCEDENTS OF FUNDS WITH ASSETS AND LIABILITIES IN PRESENCE OF SOLVENCY AND RECOVERY REQUIREMENTS. Astin Bulletin. 48(2). 647–672. 2 indexed citations
11.
Avanzi, Benjamin, et al.. (2016). Stochastic loss reserving with dependence: A flexible multivariate Tweedie approach. Insurance Mathematics and Economics. 71. 63–78. 17 indexed citations
12.
Avanzi, Benjamin, Greg Taylor, & Bernard Wong. (2016). CORRELATIONS BETWEEN INSURANCE LINES OF BUSINESS: AN ILLUSION OR A REAL PHENOMENON? SOME METHODOLOGICAL CONSIDERATIONS. Astin Bulletin. 46(2). 225–263. 12 indexed citations
13.
Avanzi, Benjamin, et al.. (2015). A Micro-Level Claim Count Model with Overdispersion and Reporting Delays. SSRN Electronic Journal. 12 indexed citations
14.
Avanzi, Benjamin, Greg Taylor, & Bernard Wong. (2015). Correlations between Insurance Lines of Business: An Illusion or a Real Phenomenon? Some Methodological Considerations. SSRN Electronic Journal. 1 indexed citations
15.
Avanzi, Benjamin, et al.. (2014). On optimal periodic dividend strategies in the dual model with diffusion. Insurance Mathematics and Economics. 55. 210–224. 36 indexed citations
16.
Wong, Bernard. (2014). On ‘A note on arbitrage, approximate arbitrage and the fundamental theorem of asset pricing’. Stochastics. 86(6). 1022–1022. 1 indexed citations
17.
Avanzi, Benjamin, et al.. (2011). Modelling Dependence in Insurance Claims Processes with Lévy Copulas. Astin Bulletin. 41(2). 575–609. 8 indexed citations
18.
Avanzi, Benjamin, et al.. (2011). Modelling Dependence in Insurance Claims Processes with Lévy Copulas. SSRN Electronic Journal. 3 indexed citations
19.
Lim, Andrew E. B. & Bernard Wong. (2009). A benchmarking approach to optimal asset allocation for insurers and pension funds. Insurance Mathematics and Economics. 46(2). 317–327. 10 indexed citations
20.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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