[data] Anonymous admission contribution

[YichengYang-Ethan]

Profile

• GPA: 3.94
• GRE: 334 (modeled Q170 / V164)
• University: US T10 (modeled as University of Pennsylvania — poster did not name school)
• Majors: Applied Mathematics + Economics (simplified; poster lists more STEM)
• International: yes
• Internships: Multiple quant / AM / brokerage (US & China); poster lists 8+ roles
• Research: Finance, math, earth sciences (conference publication mentioned)

Prediction Results

• Master of Science in Financial Engineering (New York University): 81% [71%-88%] — safety
• Master of Science in Quantitative and Computational Finance (Georgia Institute of Technology): 72% [37%-92%] — safety
• Master of Science in Mathematics in Finance (New York University): 70% [53%-82%] — target
• Master of Arts in Mathematics of Finance (Columbia University): 68% [53%-80%] — target
• Master of Science in Financial Mathematics (University of Chicago): 65% [53%-75%] — target
• Master of Science in Computational Finance (Carnegie Mellon University): 64% [54%-72%] — target
• Master of Financial Engineering (Cornell University): 64% [46%-78%] — target
• Master of Financial Engineering (University of California, Berkeley): 56% [32%-77%] — target
• Master of Science in Financial Engineering (Columbia University): 54% [45%-63%] — target
• Master in Asset Management (Yale University): 50% [28%-72%] — target
• MS in Financial Economics (Columbia University): 49% [18%-81%] — target
• Master of Finance (Massachusetts Institute of Technology): 41% [26%-59%] — target
• Master of Science in Mathematical and Computational Finance (Stanford University): 34% [22%-50%] — reach
• Master in Finance (Princeton University): 30% [13%-54%] — reach
• Master of Financial Engineering (Baruch College, City University of New York): 23% [8%-49%] — reach

Command: quantpath predict --profile profiles/data_contrib_near_grand_slam.yaml (GPBoost v2 — retrained 2026-04-02). 15 programs — 3 reach / 10 target / 2 safety.

Actual Outcomes

Accepted (then mostly declined by applicant)

• Master in Finance (Princeton University): accepted (scholarship)
• Master of Science in Computational Finance (Carnegie Mellon University): accepted (scholarship)
• Master of Finance (MIT): accepted
• Master in Asset Management (Yale SOM): accepted
• Master of Arts in Mathematics of Finance (Columbia University): accepted
• Master of Science in Financial Engineering (Columbia University): accepted
• Master of Science in Financial Mathematics (University of Chicago): accepted
• Oxford MCF, Cambridge Finance, JHU FinMath, Duke MEng Env, LBS, etc.: various accepted (not all in focused 15)

Rejected

• Stanford MS&E (Management Science & Engineering): rejected — not the same program as stanford-mcf in the table above

Model accuracy note

Compare stanford-mcf row only to Stanford MCF, not MS&E. Yale AM admit vs ~47% on yale-am. Multiple elite admits despite modest marginal P on several rows.

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Data contribution — “near grand slam” public post. profiles/data_contrib_near_grand_slam.yaml.