Mehmet Caner
Mathematics · The Ohio State University
Publications
149
Citations
3,648
Est. group size
—
Recurring co-author estimate
Active years
60
Publishing since 1967
Mehmet Caner works at the intersection of statistics, econometrics, and finance, developing methods for analyzing large, high-dimensional datasets—such as estimating precision matrices and building investment portfolios when there are many assets or variables. Recent work incorporates machine learning and AI techniques (like Lasso, deep learning, and agentic AI screening) into financial modeling, with a focus on portfolio construction, risk estimation, and the reliability of these methods when used by or against strategic actors.
Publication output has fluctuated over the past decade with a dip around 2022-2023, but shows a sharp recent increase, especially projected for 2026.
Generated by claude-sonnet-5 from public bibliographic data · Jul 20, 2026
- Portfolio Analysis in High Dimensions with Tracking Error and Weight Constraints
Journal of the American Statistical Association · 2026
- A practitioner’s guide to AI+ML in portfolio investing
Econometric Reviews · 2026
- Portfolio Analysis in High Dimensions with Tracking Error and Weight Constraints
Figshare · 2026
- Portfolio Analysis in High Dimensions with Tracking Error and Weight Constraints
Figshare · 2026
- Designing Agentic AI-Based Screening for Portfolio Investment
arXiv (Cornell University) · 2026
- Designing Agentic AI-Based Screening for Portfolio Investment
arXiv (Cornell University) · 2026
- Model-Estimation-Free, Dense, and High Dimensional Consistent Precision Matrix Estimators
SSRN Electronic Journal · 2026
- Designing Agentic AI-Based Screening for Portfolio Investment
SSRN Electronic Journal · 2026
- Deep learning based residuals in non-linear factor models: Precision matrix estimation of returns with low signal-to-noise ratio
Journal of Econometrics · 2025
- Should Humans Lie to Machines? The Incentive Compatibility of Lasso and GLM Structured Sparsity Estimators
Journal of Business and Economic Statistics · 2024
- Should Humans Lie to Machines? The Incentive Compatibility of Lasso and GLM Structured Sparsity Estimators
SSRN Electronic Journal · 2024
- Portfolio Analysis in High Dimensions with TE and Weight Constraints
arXiv (Cornell University) · 2024
- Deep Learning Based Residuals in Non-Linear Factor Models: Precision Matrix Estimation of Returns with Low Signal-to-Noise Ratio
SSRN Electronic Journal · 2024
- Generalized linear models with structured sparsity estimators
Journal of Econometrics · 2023
- Supplementary Material for: The Clinical Manifestation of Immunosuppressive Therapy as a Tool to Improve Immune Monitoring in Renal Transplant Recipients
Figshare · 2023
- arXiv (Cornell University)×14
- Figshare×6
- SSRN Electronic Journal×6
- Journal of Econometrics×4
- Econometric Reviews×3
- Robert de Jong
Mathematics · The Ohio State University
- Juhyun Park
Mathematics · Indiana University
- Brandon Koch
Mathematics · The Ohio State University
- Anindya Bhadra
Mathematics · Purdue University West Lafayette
- Anirban Dasgupta
Mathematics · Purdue University West Lafayette
This profile was generated automatically from public scholarly data (OpenAlex). Group size and activity levels are estimates derived from co-authorship patterns.
Last updated Jul 19, 2026.
Claim or correct this profile