Quantitative Research
Factor research, macro regime analysis, and Python analytics
QUANTITATIVE EQUITY / SEOUL
Yeonghwi Yoo
Quantitative Equity Portfolio Manager
Systematic equity investor with experience across developed Europe, Japan, and emerging markets. I contribute across multi-factor research, benchmark-aware portfolio construction, implementation, risk oversight, and self-built Python analytics.
EXPERIENCE
Institutional investing, research, and markets.
A career spanning quantitative equity portfolio management, financial data, global markets research, and equity prop trading.
Portfolio Construction & Implementation
Benchmark-aware construction, rebalancing, and execution
Performance & Risk
Attribution, factor exposure monitoring, and portfolio review
Korea Investment Corporation
Seoul, South Korea
Manager, Quantitative Equity
Contribute to multi-factor equity portfolios across developed Europe and Japan, spanning factor research, benchmark-aware construction, rebalancing and execution, risk monitoring, and self-built Python analytics for attribution and portfolio review.
Associate, Quantitative Equity
Supported EM ex-Korea and China equity mandates through multi-factor research, thematic baskets and relative-value ideas, portfolio rebalancing, and implementation.
Solution Chapter AI Specialist
Shinhan AI
Seoul, South Korea
Served as a domain reviewer for macro and markets content in an internal finance-specialized GPT model.
Global Markets Research Trainee
Societe Generale
Seoul, South Korea
Distilled global macro and FICC research into daily briefs for the Seoul trading floor and institutional clients.
Equity Prop Desk Intern
Meritz Securities
Seoul, South Korea
Supported portfolio positioning through external research synthesis and produced an internal single-name equity research report.
INDEPENDENT WORK
Building, testing, learning.
One completed forecasting challenge and two public-data research projects in development. All are personal projects and unrelated to my employer.
XForecast Challenge @ KDD 2026
My first machine-learning competition, completed in five days with an AI-assisted development workflow. I forecast four-week price direction for 100 U.S. mega-cap stocks from news embeddings and price data, finishing 18th of 51 teams on a blind held-out year. The lasting lessons were signal restraint, validation judgment, and predefined acceptance criteria.
View competition ->Multi-Factor Research Across Markets
A public-data study of value, quality, momentum, and earnings-revision signals across developed and emerging equity markets, with attention to sector neutrality, signal decay, turnover, and implementation.
Pairs Trading Under Real-World Frictions
A market-neutral pairs-trading project covering pair formation, cointegration stability, regime changes, borrow and transaction costs, and out-of-sample validation.
SIDE PROJECT
Finance knowledge, turned into a working product.
An independent project that brings together finance-domain knowledge, communication, and end-to-end product execution.
The Street Speaks
A financial-English learning app built around the language used in earnings calls, markets, macro, quant, risk, and investment banking.
Built the product end to end, including curated learning decks, original reading materials, adaptive review, and card, quiz, listening, and writing modes.
- 2,000+
- Expressions
- 68
- Curated decks
- 4
- Practice modes
EDUCATION & CREDENTIALS
Training for the work.
Sogang University
B.A. in Economics, Magna Cum Laude
Econometrics & Mathematical Economics | Graduated February 2023- CFA Charterholder
- Financial Risk Manager (FRM), GARP
- ARPM Quant Bootcamp (2025)
- Investment Manager Certification (Korea)
- Python (pandas, NumPy) / SQL
- Axioma / Bloomberg PORT & MAC3
- SimCorp / Refinitiv Eikon
CONTACT