Background:
Korean national, Certified Tax Accountant (CPA-equivalent in Korea) with 2.5 years of professional experience in taxation and accounting.
Currently operating an independent tax advisory practice while transitioning into quantitative finance and risk management.
Education:
Recommendation Letters:
Pursue an MFE to bridge taxation, data science, and quantitative risk management.
My long-term objective is to work in systematic risk analysis or portfolio strategy development at a hedge fund or asset management firm.
Target Programs
Based on my profile, which U.S. MFE programs do I have a realistic chance of getting into?
Korean national, Certified Tax Accountant (CPA-equivalent in Korea) with 2.5 years of professional experience in taxation and accounting.
Currently operating an independent tax advisory practice while transitioning into quantitative finance and risk management.
Education:
- B.S. in Software Engineering, regional national university in South Korea (Top 15–20 nationwide)
GPA: 4.3 / 4.5 (≈ 3.85 / 4.0) - Relevant coursework: Calculus I–II, Linear Algebra, Probability & Statistics, Optimization, Numerical Methods, Stochastic Processes, Data Structures, Algorithms, Machine Learning, Financial Computing
- TOEFL: 108
- GRE: 335 (Q170, V165, AWA 4.0)
- CFA Level I (passed)
- Licensed Tax Accountant (2.5 years): advised over 100 SME clients, focusing on tax optimization and portfolio-based wealth management.
- Developed automated tax reporting tools using Python to enhance efficiency and data accuracy.
- Exposure to portfolio analytics, cash-flow modeling, and financial risk evaluation through client advisory work.
- Futures & FX Momentum Strategy (Live-traded for 9 months)
- Developed multi-factor momentum signals across global futures and FX data.
- Integrated volatility filters and risk-parity weighting for position sizing.
- Targeted Sharpe ratio > 1.5, currently validating live results.
- Option Pricing Library (Python + C++)
- Implemented Monte Carlo, PDE, and Heston model solvers for derivative pricing.
- Computed Greeks, performed calibration, and benchmarked performance across methods.
- Portfolio Risk Optimization Model (In Progress)
- Building a fixed-income + covered-call ETF structure (e.g., 96% U.S. Treasuries + 4% option overlay) to generate stable income under low-volatility conditions.
Recommendation Letters:
- 1 from a Korean PhD professor (academic/research-focused)
- 1 from a U.S. PhD professor (strong recommendation related to quant research work)
Pursue an MFE to bridge taxation, data science, and quantitative risk management.
My long-term objective is to work in systematic risk analysis or portfolio strategy development at a hedge fund or asset management firm.
Target Programs
- UC Berkeley MFE
- Columbia MFE
- CMU MSCF
- NYU Courant MFE
- UChicago FinMath
- Cornell MFE
- Georgia Tech QCF
- My undergraduate institution is not top-tier, which might be a disadvantage.
- Limited formal experience in quantitative finance roles.
- Need to further strengthen my applied quant profile through projects before applications.
Based on my profile, which U.S. MFE programs do I have a realistic chance of getting into?