Applied Mathematics · Quantitative Projects

Yeoh Yu Yong

Applied Mathematics student at Nanyang Technological University with strong skills in data analysis, financial modeling, and programming in Python and R. Experienced in developing trading strategies and working on quantitative projects. Seeking to apply my analytical and technical skills in finance or data-driven roles.

Portrait of Yeoh Yu Yong
Singapore · yeoh.yuyong@gmail.com · yeohyuyong.github.io

Selected Work

Projects

COVID-19 Impact Analysis on Singapore

R · Aug 2025 - Present

  • Developed a Dynamic Inoperability Input-Output Model (DIIM) using Singapore's IO tables in collaboration with DSO National Laboratories
  • Simulated sector interdependencies to model economic disruptions and identify key recovery priorities
  • Performed sensitivity analysis showing consistent sector loss rankings across varying lockdown durations

ML-Optimized Pairs Trading

Python, Bayesian Optimization, XGBoost · Jan 2025 - Apr 2025

  • Built a machine learning-based pairs trading strategy integrating Bayesian optimization and XGBoost forecasting
  • Selected cointegrated stock pairs and predicted next-day price spreads to inform trades
  • Outperformed benchmarks with a 19.81% return and Sharpe ratio of 2.53

HDB Price Prediction

R, Linear Regression, Tree-based Methods · Jan 2025 - Apr 2025

  • Evaluated multiple models including Linear Regression, Ridge/LASSO, Bagging, and Random Forest
  • Analyzed node count vs. deviance to tune tree-based approaches
  • Bagging achieved the lowest RMSE of 41,230.59

USD Twin Win Certificate Pricing & Risk

R, yfinance API · Aug 2024 - Nov 2024

  • Priced structured product using multidimensional GBM with variance reduction
  • Compared variance reduction techniques via simulated price paths
  • Empirical Martingale Correction to Control Variates yielded lowest RMSE of 18.41

Ensemble DL for Flower Classification

Python · Aug 2024 - Nov 2024

  • Built an ensemble of VGG16, VGG19, and DeiT models on Oxford Flowers 102
  • Implemented to improve accuracy over baseline SVM
  • Delivered 80.71% test accuracy vs 72.8% baseline

Professional

Experience

May 2025 - Aug 2025

Bioinformatics Intern

Agency for Science, Technology and Research (A*STAR) · Singapore

  • Addressed confounding bias in observational studies to improve statistical inference
  • Developed hybrid matching and weighting algorithm outperforming traditional propensity score matching and IPTW
  • Implemented the algorithm in R and tested across simulations with varying noise levels
  • Achieved lowest average mean squared error of 0.00890 versus baseline methods
Jan 2020 - Mar 2020

Research Assistant Intern

Red Dot Robotics · Singapore

  • Created airport-road video dataset to improve self-driving luggage transport vehicle accuracy
  • Annotated videos and converted labels into ground truth for CNN training
  • Trained a new model on airport-specific data, improving accuracy over street-trained baseline

Academic

Education

Aug 2022 - May 2026

Nanyang Technological University

BSc in Mathematical Sciences (Applied Math Track)

  • Current GPA: 4.81/5.00 (First Class Honours equivalent); Dean's List AY23/24 (Top 5% of cohort)
  • Relevant Courses: Stochastic Finance, Simulation Techniques in Finance, Quantitative Trading Strategies, Neural Networks and Deep Learning, Stochastic Processes, Financial Data Analysis and Applications
Jan 2014 - Dec 2019

Dunman High School

Singapore-Cambridge GCE Advanced Level

  • H2 Mathematics, H2 Further Mathematics, H2 Computing
  • Info-comm Club Executive Committee 2019

Toolbox

Skills

Programming Languages & Tools

Python Pandas NumPy Scikit-learn R ggplot2 caret

Quantitative Methods

Stochastic Calculus Monte Carlo Simulation Linear Algebra Optimization

Financial Modeling & Analysis

Derivatives Pricing Black-Scholes Binomial Trees Risk Management Hedging Strategies