Aidarkhan D. Zhubatkan

+852 4491 3027 · azhubatkan16@gmail.com · azhubatkan · idarkhanzh
Education
The University of Hong Kong September 2025 – Present
BSc Statistics & Minor in Mathematics Hong Kong SAR
Major GPA: 3.70 / 4.30
Awards: Finalist at the Web3 Trading Hackathon by Flow Traders and Jane Street (2025)
WorldQuant University September 2025 – January 2026
Applied AI Lab: Deep Learning for Computer Vision Remote
Work Experience
CASH Algo Finance Group June 2026 – Present
Quantitative Finance Intern Hong Kong
  • Working on attention factor model for statistical arbitrage on S&P 500.
The University of Hong Kong May 2026 – Present
Research Assistant, Department of Statistics Hong Kong SAR
  • Conducting research under Dr. Wat on financial risk analysis and insurance risk models.
Ernst & Young June 2025 – August 2025
Quantitative Analyst Intern Kazakhstan
  • Built equity-screening prototypes via factor transformations and ML classifiers, evaluated via sector-neutral backtests.
  • Automated analytics workflows with pandas/matplotlib, producing reproducible reporting dashboards.
  • 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 & Research
Multi-Strategy Algorithmic Trading Engine GitHub November 2025
  • Implemented multi-strategy 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).
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.
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.
  • Detrended non-stationary market series to isolate mean-reverting components and improve strategy entry precision.
  • Conducted an analysis into the stability of regression-based (Longstaff-Schwartz, Broadie-Andersen) non-linear option pricing algorithms in S&P 500 stocks.
IMC Prosperity 4 April 2026
Algorithmic Trading Competition  |  #7 in Hong Kong Worldwide
  • Applied ADF/KPSS and Hurst exponent to classify regimes and assign mean-reversion/momentum strategies per asset.
  • Built a symmetric mean-reversion market-maker with inventory skew, passive/aggressive order layering, and crash-protection flattening; implemented a trailing drawdown stop for trend-following positions.
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