Draft:Julien Guyon
This draft lacks inline citations. Wikipedia's verifiability policy requires that all content be supported by reliable sources. We require inline citations (footnotes) to show which source supports which specific statement.
You must place an inline citation directly after:
Please edit your draft to support your statements with inline citations. Learn how to create inline citations in the:
Where to get help
How to improve a draft
You can also browse Wikipedia:Featured articles and Wikipedia:Good articles to find examples of Wikipedia's best writing on topics similar to your proposed article. Improving your odds of a speedy review To improve your odds of a faster review, tag your draft with relevant WikiProject tags using the button below. This will let reviewers know a new draft has been submitted in their area of interest. For instance, if you wrote about a female astronomer, you would want to add the Biography, Astronomy, and Women scientists tags. Editor resources
|  |
Comment: May be notable but draft gives no references to significant coverage (in-depth, analytical - not database entries, interviews, routine industry reporting) about Guyon in published reliable independent sources with reputations for accuracy and fact-checking. We cannot, for example, rely on Guyon's own CV, staff and editorial board profiles, or his own published work. The referencing needs to be improved so that - at a glance - a reader knows what publication or other source is being cited, who wrote it and when it was published. And, please, no more puffery. Paul W (talk) 14:15, 10 August 2026 (UTC)
Julien Guyon (born May 3, 1977) is a French-American applied mathematician, quantitative analyst, and academic, recognized for his contributions to financial mathematics and sports analytics.
Early life and education
[edit]Julien Guyon was born in France in 1977. After completing his preparatory classes at the Lycée Henri-IV, he graduated from École polytechnique in 2000. In 2003, he earned a master's degree in probability theory from Pierre and Marie Curie University[1] (now Sorbonne Université).
Guyon subsequently completed his PhD in Probability Theory and Statistics at the École nationale des ponts et chaussées, under the supervision of Jean-François Delmas. His dissertation, Probabilistic Modeling in Finance and Biology, received highest honors and was awarded the institution's Best 2006 PhD Thesis.[2]
Career and research
[edit]Finance
[edit]Guyon began as a quantitative researcher at Société Générale in Paris, where he focused on equity derivatives and volatility modeling.[citation needed] In 2012, he relocated to New York to join Bloomberg L.P. as a senior quantitative analyst, a position he held for a decade.[citation needed]
During his tenure in the industry, Guyon solved the holy grail of equity derivatives: the joint calibration of S&P 500 and VIX smiles,[3] and worked on path-dependent volatility, in particular the Guyon-Lekeufack volatility model, which earned him the 2025 Quant of the Year award from Risk magazine.[4] Other technical contributions include the particle method for smile calibration (with Pierre Henry-Labordère)[citation needed] and the Bergomi-Guyon expansion.[citation needed]
Academia
[edit]Guyon is currently a professor of applied mathematics at École nationale des ponts et chaussées (ENPC), Polytechnic Institute of Paris, a position he has held since September 2022.[citation needed] At ENPC, he holds the BNP Paribas Chair Futures of Quantitative Finance and conducts research at CERMICS.[citation needed] His teaching portfolio spans several world-class institutions.[citation needed]
Since 2015, he has been an adjunct professor at Columbia University,[5] where he teaches Nonlinear Option Pricing in the Mathematics of Finance MA program.
Additionally, he is a visiting associate professor at the New York University Tandon School of Engineering.[6] Previously, he held adjunct roles at the Courant Institute of Mathematical Sciences (NYU) and Baruch College.[citation needed] He has editorial roles with journals including Finance & Stochastics,[7] Quantitative Finance,[8] and SIAM Journal on Financial Mathematics.[citation needed]
Sports analytics
[edit]In sports analytics, Guyon has researched the fairness and design of major tournament structures. He has identified critical flaws in historical formats, such as biases in the 2014 FIFA World Cup draw, which led to a significant reform in 2018 where teams were allocated into pots based on world rankings,[9] and the risk of collusion in the initially planned 16-groups-of-three format for the 2026 FIFA World Cup – a study that won second prize at the 2021 MIT Sloan Sports Analytics Conference.[10]
Beyond FIFA, his suggestions have influenced UEFA tournament designs,[11] including the draw procedure of the league phase of the Champions League and a new knockout bracket for the Euro since 2020. His broader contributions include proposing Choose Your Opponent knockout formats to eliminate tanking incentives and publishing sports research in both academic journals and major international newspapers,[12] including The New York Times, The Times, Le Monde, and El País.
Honours and awards
[edit]- Quant of the Year (2025)
- Louis Bachelier Fellow (since 2021)
- MIT Sloan Sports Analytics Conference Research Award (2021)
References
[edit]- ↑ Julien Guyon's resume
- ↑ Cermics staff
- ↑ Guyon, Julien, "The Joint S&P 500/VIX Smile Calibration Puzzle Solved" (May 31, 2019). Risk, April 2020, Available at SSRN: https://ssrn.com/abstract=3397382 or http://dx.doi.org/10.2139/ssrn.3397382
- ↑ "Quant of the year: Julien Guyon - Risk.net". www.risk.net. 2024-11-26. Retrieved 2026-08-10.
- ↑ Columbia MAFN staff
- ↑ NYU Staff
- ↑ Finance & Stochastic editorial board
- ↑ Quantitive finance editorial board
- ↑ New York Times article by Julien Guyon - June 2014
- ↑ Research paper Sloan Sports conference
- ↑ Drawing and Scheduling the UEFA Champions League League Phase
- ↑ Choose your opponent: A new knockout design for hybrid tournaments
- provide significant coverage: discuss the person in detail, not brief mentions or interviews lacking independent analysis;
- are reliable: from reputable outlets with editorial oversight;
- are independent: not connected to the person, such as interviews, press releases, the subject's own website, or sponsored content.
Please add references that meet all three of these criteria. If none exist, the subject is not yet suitable for Wikipedia.