Starting a Quantitative Finance Notebook
Why I am using this site as a public notebook for quantitative finance.
Quantitative finance / Data science / AI research
Viet Hung Vu
I am a PhD candidate at Griffith University in Queensland, Australia, working across data science, AI research, and quantitative finance.
This site is my public research notebook for quantitative finance: backtesting, market data, forecasting, risk, portfolio construction, and the engineering habits that make research reproducible.
I am currently a Research Assistant with the IoT Cluster and Big Data Visualisation Lab at Griffith University, and a Teaching Assistant for Big Data Analysis and Data Wrangling and Visualization.
Focus
Areas I am studying, writing about, and turning into reproducible research notes.
Systematic research
Backtesting, signal evaluation, factor models, and portfolio construction.
Risk and forecasting
Volatility, drawdowns, stress testing, and model evaluation for financial data.
Research engineering
Data cleaning, machine learning pipelines, experiment design, and reporting.
Writing
Quantitative finance notes and research logs.
A Backtesting Checklist
A compact checklist for more careful strategy backtests.
Factor Models: A Study Plan
A short study plan for understanding factor models in quantitative finance.
Volatility and Risk Notes
Initial notes on volatility forecasting and risk measurement.
Market Data Cleaning Notes
Why data cleaning is a core part of quantitative research.