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halim-quantlab/README.md

👋 Hi, I'm Wielly Halim

🚀 Aspiring Quantitative Researcher
🎓 Incoming NUS MQF Candidate
💻 Python & C++ for Financial Modeling
📍 Singapore

Welcome to halim-quantlab, where I explore quantitative finance through code and experimentation.
My goal is to build a strong foundation in financial engineering, stochastic modeling, and quantitative research.

💼 Interests

📊 Quantitative Finance & Asset Pricing

  • CAPM
  • Fama-French Factor Models (FF3 / FF5)

📈 Portfolio Optimization & Risk Management

  • Modern Portfolio Theory
  • Efficient Frontier
  • Value at Risk (VaR)

🔍 Financial Engineering

  • Derivatives Pricing
  • Stochastic Processes
  • Monte Carlo Simulation

💻 Computational Finance

  • Python for rapid prototyping
  • C++ for numerical performance
  • SQL for financial data analysis

🧠 Currently Learning

  • Monte Carlo methods for derivatives pricing
  • Variance reduction techniques (Antithetic Variates, Control Variates)
  • Stochastic calculus foundations
  • Financial machine learning for time series

🔬 Featured Projects

📘 Wilmott Quant Foundations

Implementation of concepts from Paul Wilmott – Introduces Quantitative Finance

Key features:

  • Forward pricing and arbitrage detection
  • Geometric Brownian Motion (GBM) simulation
  • Monte Carlo option pricing
  • Asian and European options
  • Black–Scholes analytical pricing
  • Greeks computation
  • Put–Call parity validation
  • Python and C++ implementations

📊 Fama-French Factor Models

Asset pricing analysis using Fama-French 3-Factor and 5-Factor models

Features:

  • Factor regression analysis
  • Portfolio construction
  • Visualization of factor exposures
  • Performance evaluation

📈 Portfolio Optimizer

Portfolio optimization using Modern Portfolio Theory

Features:

  • Efficient frontier computation
  • Portfolio risk-return comparison
  • Optimization using cvxpy
  • Market data via yfinance

📉 Monte Carlo Value at Risk

Risk modeling using Monte Carlo simulation.

Features:

  • Portfolio loss distribution simulation
  • VaR estimation
  • Jump diffusion modeling
  • Probabilistic risk visualization

🛠 Tools & Languages

Python
C++
NumPy / Pandas
Monte Carlo Simulation
Quantitative Modeling

🤝 Collaboration

I’m interested in collaborating on:

  • Quant research projects
  • Financial modeling tools
  • Open-source fintech libraries
  • Data-driven trading or risk models

📫 Contact

📧 Email
wiellyhalim92@gmail.com
wiellyhalim92@icloud.com

💼 LinkedIn
https://linkedin.com/in/wiellyhalim

⚡ This GitHub serves as a quant research lab documenting my learning journey toward becoming a quantitative researcher.

Pinned Loading

  1. option-pricing-engine-cpp option-pricing-engine-cpp Public

    Modular C++ option pricing engine with flexible inputs and support for multiple pricing models

    C++ 1

  2. portfolio-optimizer portfolio-optimizer Public

    A Python-based tool that applies Modern Portfolio Theory to optimize asset allocation.

    Jupyter Notebook 1

  3. fama-french-models fama-french-models Public

    A Python-based tool for building, evaluating, and comparing optimized portfolios using the Fama-French 3-Factor (FF3) and Fama-French 5-Factor (FF5) models.

    Jupyter Notebook 2

  4. VaR-MonteCarlo VaR-MonteCarlo Public

    Monte Carlo Value at Risk Simulator with jump diffusion model

    Jupyter Notebook 2

  5. stock-return-model stock-return-model Public

    Feature-engineered ML pipeline for stock return prediction using linear & logistic regression, with out-of-sample evaluation and backtesting. Demonstrates how weak financial signals can be translat…

    Jupyter Notebook 1