API Data Ingest Practice
BeginnerPull free market data APIs, handle rate limits, and normalize columns for later use.
Quant Labs
Explore interactive Python workbooks covering derivatives, factor research, portfolio construction, and stochastic simulation.
35 workbooks found
| # | Link | ||
|---|---|---|---|
| 1 | API Data Ingest Practice Pull free market data APIs, handle rate limits, and normalize columns for later use. | Beginner | Coming soon |
| 2 | ETF Backtest Starter Kit Follow guided steps to load ETF prices, build a simple strategy, and evaluate performance. | Beginner | Coming soon |
| 3 | Factor Screener Lite Screen stocks with size, value, and momentum signals using interactive widgets. | Beginner | Coming soon |
| 4 | Intro to Risk Metrics Walk through volatility, drawdown, and Sharpe ratio calculations using tidy helper functions. | Beginner | Coming soon |
| 5 | Loan Default Prediction with Gradient Boosting Train, calibrate, and explain boosted credit models with SHAP insights. | Beginner | Coming soon |
| 6 | Monte Carlo Scenario Simulator Model correlated paths, apply regime-dependent shocks, and visualize distribution shifts. | Beginner | Coming soon |
| 7 | Options Vocabulary Workbook Introduce options terminology, payoff diagrams, and small quizzes before diving deeper. | Beginner | Coming soon |
| 8 | Pandas Data Exploration Playground Practice cleaning, merging, and summarizing market datasets with step-by-step prompts. | Beginner | Coming soon |
| 9 | Python Fundamentals for Finance Review core Python syntax, functions, and libraries needed to follow the quant workbooks. | Beginner | Coming soon |
| 10 | Return Calculations 101 Compute simple, log, and cumulative returns with plenty of inline checks and visuals. | Beginner | Coming soon |
| 11 | Time Value of Money Drills Solve discounting and compounding exercises with instant feedback cells. | Beginner | Coming soon |
| 12 | Visualizing Distributions with Matplotlib Learn histograms, KDE plots, and annotations for financial return distributions. | Beginner | Coming soon |
Pull free market data APIs, handle rate limits, and normalize columns for later use.
Follow guided steps to load ETF prices, build a simple strategy, and evaluate performance.
Screen stocks with size, value, and momentum signals using interactive widgets.
Walk through volatility, drawdown, and Sharpe ratio calculations using tidy helper functions.
Train, calibrate, and explain boosted credit models with SHAP insights.
Model correlated paths, apply regime-dependent shocks, and visualize distribution shifts.
Introduce options terminology, payoff diagrams, and small quizzes before diving deeper.
Practice cleaning, merging, and summarizing market datasets with step-by-step prompts.
Review core Python syntax, functions, and libraries needed to follow the quant workbooks.
Compute simple, log, and cumulative returns with plenty of inline checks and visuals.
Solve discounting and compounding exercises with instant feedback cells.
Learn histograms, KDE plots, and annotations for financial return distributions.
These workbooks cover key quantitative finance topics including options pricing, portfolio optimization, risk analytics, and algorithmic trading. Each workbook includes step-by-step explanations and practical examples in Jupyter format.
Signed-in users can open beginner and intermediate workbooks directly in Google Colab or download the original `.ipynb` files.