Lawrence J. Jin
- Finance top 1%
- Economics and Econometrics top 1%
- Accounting top 5%
- General Economics, Econometrics and Finance top 5%
- Management Science and Operations Research top 5%
- Co-authors
- Nicholas BarberisRobin GreenwoodAndrei ShleiferZhi DaXing HuangCary FrydmanJonathan E. IngersollSamuel Hanson
- Topics
- Financial Markets and Investment Strategies (14 papers)Complex Systems and Time Series Analysis (5 papers)Experimental Behavioral Economics Studies (4 papers)
- Partner nations
- United StatesUnited KingdomChina
In The Last Decade
Lawrence J. Jin
16 papers receiving 1.0k citations
Hit Papers
Peers
Comparison fields: 5 of 51
- Finance 821
- Economics and Econometrics 688
- Accounting 268
- General Economics, Econometrics and Finance 158
- Management Science and Operations Research 156
Countries citing papers authored by Lawrence J. Jin
This map shows the geographic impact of Lawrence J. Jin'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 Lawrence J. Jin with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Lawrence J. Jin more than expected).
Fields of papers citing papers by Lawrence J. Jin
This network shows the impact of papers produced by Lawrence J. Jin. 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 Lawrence J. Jin. The network helps show where Lawrence J. Jin may publish in the future.
Co-authorship network of co-authors of Lawrence J. Jin
This figure shows the co-authorship network connecting the top 25 collaborators of Lawrence J. Jin. A scholar is included among the top collaborators of Lawrence J. Jin 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 Lawrence J. Jin. Lawrence J. Jin is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 1 | |
| 3 | 0 | |
| 4 | 1 | |
| 5 | 50 | |
| 6 | 69 | |
| 7 | 62 | |
| 8 | 7 | |
| 9 | 102 | |
| 10 | 7 | |
| 11 | 9 | |
| 12 | 42 | |
| 13 | Extrapolation and bubblesbreakdown → | 239 |
| 14 | 8 | |
| 15 | A Model of Credit Market Sentiment | 16 |
| 16 | 15 | |
| 17 | X-CAPM: An extrapolative capital asset pricing modelbreakdown → | 395 |
| 18 | 39 |
About Lawrence J. Jin
Lawrence J. Jin is a scholar working on General Decision Sciences, Finance and Safety Research, having authored 18 papers that have together received 1.1k indexed citations. Recurring topics across this work include Financial Markets and Investment Strategies (14 papers), Complex Systems and Time Series Analysis (5 papers) and Experimental Behavioral Economics Studies (4 papers). The work is most often cited by research in Finance (821 citations), General Decision Sciences (150 citations) and Economics and Econometrics (688 citations). Lawrence J. Jin has collaborated with scholars based in United States, United Kingdom and China. Frequent co-authors include Nicholas Barberis, Robin Greenwood, Andrei Shleifer, Zhi Da, Xing Huang, Cary Frydman, Jonathan E. Ingersoll, Samuel Hanson, Baolian Wang and Cameron Peng. Their work appears in journals such as The Journal of Finance, Journal of Financial Economics and The Quarterly Journal of Economics.
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.