Bryan Lim

2.2k total citations · 1 hit paper
11 papers, 1.1k citations indexed

About

Bryan Lim is a scholar working on Finance, Economics and Econometrics and Accounting. According to data from OpenAlex, Bryan Lim has authored 11 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Finance, 5 papers in Economics and Econometrics and 4 papers in Accounting. Recurrent topics in Bryan Lim's work include Financial Markets and Investment Strategies (7 papers), Corporate Finance and Governance (4 papers) and Complex Systems and Time Series Analysis (3 papers). Bryan Lim is often cited by papers focused on Financial Markets and Investment Strategies (7 papers), Corporate Finance and Governance (4 papers) and Complex Systems and Time Series Analysis (3 papers). Bryan Lim collaborates with scholars based in Australia, United Kingdom and United States. Bryan Lim's co-authors include Stefan Zohren, Patrick Verwijmeren, Bruce D. Grundy, Mihaela van der Schaar, Jia‐Guo Wang, Ahmed M. Alaa and Stephen Roberts and has published in prestigious journals such as Journal of Financial Economics, Journal of Banking & Finance and Philosophical Transactions of the Royal Society A Mathematical Physical and Engineering Sciences.

In The Last Decade

Bryan Lim

11 papers receiving 1.1k citations

Hit Papers

Time-series forecasting with deep learning: a survey 2021 2026 2022 2024 2021 250 500 750

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Bryan Lim Australia 8 304 276 266 207 205 11 1.1k
Lijuan Cao China 12 663 2.2× 906 3.3× 212 0.8× 481 2.3× 180 0.9× 25 1.9k
Sima Siami‐Namini United States 10 423 1.4× 382 1.4× 244 0.9× 476 2.3× 51 0.2× 34 1.9k
Achilleas Zapranis Greece 18 262 0.9× 297 1.1× 76 0.3× 155 0.7× 193 0.9× 38 968
David Elizondo United Kingdom 20 719 2.4× 89 0.3× 124 0.5× 211 1.0× 66 0.3× 84 1.5k
Thomas Fischer Germany 7 287 0.9× 1.1k 3.9× 165 0.6× 470 2.3× 426 2.1× 16 1.6k
Jozef Zurada United States 19 320 1.1× 116 0.4× 125 0.5× 89 0.4× 35 0.2× 74 1.1k
Wei Bao China 9 153 0.5× 498 1.8× 125 0.5× 270 1.3× 153 0.7× 25 922
Tim Verdonck Belgium 16 295 1.0× 161 0.6× 96 0.4× 35 0.2× 97 0.5× 80 1.3k
Vijay Menon India 11 249 0.8× 761 2.8× 171 0.6× 391 1.9× 215 1.0× 39 1.2k
Christopher Krauß Germany 9 314 1.0× 1.3k 4.8× 186 0.7× 554 2.7× 668 3.3× 14 2.0k

Countries citing papers authored by Bryan Lim

Since Specialization
Citations

This map shows the geographic impact of Bryan Lim'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 Bryan Lim with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Bryan Lim more than expected).

Fields of papers citing papers by Bryan Lim

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Bryan Lim. 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 Bryan Lim. The network helps show where Bryan Lim may publish in the future.

Co-authorship network of co-authors of Bryan Lim

This figure shows the co-authorship network connecting the top 25 collaborators of Bryan Lim. A scholar is included among the top collaborators of Bryan Lim 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 Bryan Lim. Bryan Lim is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

11 of 11 papers shown
1.
Lim, Bryan, et al.. (2023). The value of growth: Changes in profitability and future stock returns. Journal of Banking & Finance. 158. 107036–107036. 2 indexed citations
2.
Lim, Bryan, et al.. (2022). Enhancing Cross-Sectional Currency Strategies by Context-Aware Learning to Rank with Self-Attention. 4(3). 89–107. 7 indexed citations
3.
Lim, Bryan & Stefan Zohren. (2021). Time-series forecasting with deep learning: a survey. Philosophical Transactions of the Royal Society A Mathematical Physical and Engineering Sciences. 379(2194). 20200209–20200209. 874 indexed citations breakdown →
4.
Lim, Bryan & Mihaela van der Schaar. (2018). Disease-Atlas: Navigating Disease Trajectories using Deep Learning. 137–160. 10 indexed citations
5.
Lim, Bryan, Ahmed M. Alaa, & Mihaela van der Schaar. (2018). Forecasting Treatment Responses Over Time Using Recurrent Marginal Structural Networks. 31. 7483–7493. 35 indexed citations
6.
Lim, Bryan, et al.. (2018). Time-series momentum in nearly 100 years of stock returns. Journal of Banking & Finance. 97. 283–296. 43 indexed citations
7.
Grundy, Bruce D., Bryan Lim, & Patrick Verwijmeren. (2012). Do option markets undo restrictions on short sales? Evidence from the 2008 short-sale ban. Journal of Financial Economics. 106(2). 331–348. 110 indexed citations
8.
Lim, Bryan. (2011). Short-sale constraints and price bubbles. Journal of Banking & Finance. 35(9). 2443–2453. 9 indexed citations
9.
Lim, Bryan, et al.. (2010). The performance and impact of stock picks mentioned on ‘Mad Money’. Applied Financial Economics. 20(14). 1113–1124. 8 indexed citations
10.
Grundy, Bruce D., Bryan Lim, & Patrick Verwijmeren. (2010). Do Option Markets Undo Restrictions on Short Sales? Evidence from the 2008 Short-Sale Ban. SSRN Electronic Journal. 32 indexed citations
11.
Lim, Bryan, et al.. (2008). The Performance and Impact of Stock Picks Mentioned on 'Mad Money'. SSRN Electronic Journal. 2 indexed citations

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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