Kasper Johansson
Office:
Packard 243
350 Serra Mall
Stanford, CA 94305
I’m a PhD student in Prof. Stephen Boyd’s group at Stanford. My current research is on convex optimization applied to quantitative finance. Prior to joining Stanford I was a research fellow at Harvard, and prior to that a research intern at Caltech. I received a BSc in Physics and an MSc in Machine Learning, both from KTH Royal Institute of Technology in Stockholm, Sweden.
news
Jun 11, 2024 | We published slides illustrating several uses of Convex Optimization in Quantitative Finance . |
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Jun 8, 2024 | We published a preprint of our manuscript A Markowitz Approach to Managing a Dynamic Basket of Moving-Band Statistical Arbitrages . |
Mar 21, 2024 | I presented our work on covariance prediction in finance at the Fidelity Investments seminar series. The slides are available here. |
Dec 24, 2023 | We published a preprint of our manuscript Markowitz Portfolio Construction at Seventy. A software package is available on GitHub. |
Dec 9, 2023 | We published a preprint of our manuscript Finding Moving-Band Statistical Arbitrages via Convex-Concave Optimization. |
Sep 18, 2023 | I (successfully) completed my PhD qualifying exam. My slides are available here. |
Jul 11, 2023 | We published a preprint of our manuscript A Simple Method for Predicting Covariance Matrices of Financial Returns. (Now published in Foundations and Trends in Econometrics, 2023.) A software package is available on GitHub. |
selected publications
2024
- Convex Optimization in Quantitative Finance2024Working Slides, Stanford University
- A Markowitz Approach to Managing a Dynamic Basket of Moving-Band Statistical Arbitrages2024Working Paper, Stanford University
- Markowitz Portfolio Construction at SeventyJournal of Portfolio Management, Harry Markowitz Special Issue, 2024
2023
- Finding Moving-Band Statistical Arbitrages via Convex-Concave Optimization2023Working Paper, Stanford University
- A Simple Method for Predicting Covariance Matrices of Financial ReturnsFoundations and Trends® in Econometrics, 2023