The University of Hong Kong
September 2025 — Present
Majors in Computer Science, Economics and Finance | Minor in Mathematics
Hong Kong SAR
Aidarkhan D. Zhubatkan
Education
WorldQuant University
August 2025 — December 2025
Applied AI Lab: Deep Learning in Computer Vision
Remote
Nazarbayev Intellectual Schools
September 2019 — June 2025
IGCSE Mathematics, Physics, and Computer Science
Kazakhstan
Work Experience
UpSwing
January 2026 — Present
Quantitative Research Intern
United States
- Engineered volatility-clustered features and applied time-decay walk-forward retraining to address regime instability.
- Built cross-venue statistical arbitrage models using OLS and deep learning to estimate event probabilities mispricing.
- Implemented volatility-scaled position sizing and PnL attribution to evaluate alpha contribution across regimes.
Ernst & Young
June 2025 — August 2025
Quantitative Analyst Intern
Kazakhstan
- Developed equity-screening prototypes using factor transformations and ML classifiers; evaluated factor efficacy via sector-neutral backtests and performance attribution.
- Automated analytics workflows with pandas/matplotlib, creating reproducible reporting dashboards and eliminating manual intervention in performance analysis.
- Conducted feature selection and statistical diagnostics to improve predictive strength and mitigate multicollinearity.
The Financial Monitoring Agency of the Republic of Kazakhstan
May 2024 — July 2024
Risk Management Intern
Kazakhstan
- Trained logistic regression and tree-based risk models, performing feature engineering on financial datasets.
- Engineered structured feature sets from regulatory datasets using SQL and pandas, enhancing model signal quality.
- Quantified capital impact under simulated macro shocks, analyzing risk metric sensitivity across stress scenarios.
Projects & Researches
Multi-Strategy Algorithmic Trading Engine
Github
November 2025
- Implemented multi-strat system (Donchian breakout, MA breakout, Fourier Transform, mean reversion), and added execution engine, signal router, dynamic position sizing, and full performance analytics (1.32 Sharpe & 114% return).
- Designed a vectorized Python backtesting engine with walk-forward validation and Monte-Carlo drawdown stress tests.
Bermudan Options Pricing
Github
December 2025
- Implemented discrete-time Bermudan pricing via backward induction (Longstaff–Schwartz, Broadie–Andersen), simulating Monte Carlo paths and estimating optimal early-exercise boundaries.
Probabilistic Modeling of Tournament Outcomes under Uncertainty
Github
April 2025
- Built a ridge-regularized logistic regression and ran 100,000-iteration Monte Carlo simulations for probabilistic outcome modeling and sensitivity analysis.
Extracurricular Activities
HKU Trading Group
September 2025 — Present
Quantitative Analyst
Hong Kong SAR
- Built cross-sectional OLS factor models with custom feature engineering and statistical validation.
- Conducting an analysis into the stability of regression-based (Longstaff-Schwartz, Broadie-Andersen) non-linear option pricing algorithms in S&P 500 stocks.
Additional Information
Languages: Kazakh & Russian (Native), English (Fluent), Hebrew & Spanish & Italian (Conversational)
Technical: Python (NumPy, pandas, statsmodels, scikit-learn, PyTorch), time-series analysis, stochastic processes (pricing)
Interests: Weightlifting, Ice-skating, Cryptography, Tutoring & Education, Sudoku, Poker