Sara Biagini
- Finance top 5%
- Economics and Econometrics top 10%
- Management Science and Operations Research top 5%
- Demography
- General Decision Sciences
- Co-authors
- Marco FrittelliMustafa Ç. Pı̆narBruno BouchardMatheus R. GrasselliConstantinos KardarasMarcel NutzRama ContMihai Ŝırbu
- Topics
- Stochastic processes and financial applications (18 papers)Risk and Portfolio Optimization (14 papers)Economic theories and models (10 papers)
- Partner nations
- ItalyFranceUnited Kingdom
In The Last Decade
Sara Biagini
19 papers receiving 211 citations
Peers
Comparison fields: 5 of 20
- Finance 209
- Economics and Econometrics 145
- Management Science and Operations Research 141
- Demography 18
- General Decision Sciences 15
Countries citing papers authored by Sara Biagini
This map shows the geographic impact of Sara Biagini'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 Sara Biagini with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Sara Biagini more than expected).
Fields of papers citing papers by Sara Biagini
This network shows the impact of papers produced by Sara Biagini. 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 Sara Biagini. The network helps show where Sara Biagini may publish in the future.
Co-authorship network of co-authors of Sara Biagini
This figure shows the co-authorship network connecting the top 25 collaborators of Sara Biagini. A scholar is included among the top collaborators of Sara Biagini 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 Sara Biagini. Sara Biagini 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 | 7 | |
| 3 | 4 | |
| 4 | 1 | |
| 5 | 45 | |
| 6 | 30 | |
| 7 | 4 | |
| 8 | 1 | |
| 9 | ADMISSIBLE STRATEGIES IN SEMIMARTINGALE PORTFOLIO Selection | 9 |
| 10 | 6 | |
| 11 | 23 | |
| 12 | 6 | |
| 13 | Expected utility maximization: the dual approach | 5 |
| 14 | A note on investment opportunities when the credit line is infinite | 1 |
| 15 | 8 | |
| 16 | 6 | |
| 17 | 2 | |
| 18 | 14 | |
| 19 | 48 | |
| 20 | 16 |
About Sara Biagini
Sara Biagini is a scholar working on Finance, Management Science and Operations Research and General Decision Sciences, having authored 21 papers that have together received 239 indexed citations. Recurring topics across this work include Stochastic processes and financial applications (18 papers), Risk and Portfolio Optimization (14 papers) and Economic theories and models (10 papers). The work is most often cited by research in Finance (209 citations), Management Science and Operations Research (141 citations) and General Decision Sciences (15 citations). Sara Biagini has collaborated with scholars based in Italy, France and United Kingdom. Frequent co-authors include Marco Frittelli, Mustafa Ç. Pı̆nar, Bruno Bouchard, Matheus R. Grasselli, Constantinos Kardaras, Marcel Nutz, Rama Cont, Mihai Ŝırbu, Paolo Guasoni and Fausto Gozzi. Their work appears in journals such as Mathematical Finance, The Annals of Applied Probability and Finance and Stochastics.
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.