Welcome to Utils-main, a comprehensive, beginner-friendly toolkit for learning and practicing quantitative finance, data analysis, coding, and financial engineering in Python!
A curated, growing collection of Python modules and reference material to help you:
- Understand core quant finance concepts (risk, return, valuation, options, portfolios, data)
- Practice with realistic scenarios or DIY finance scripts
- Learn Python basics and data structures from scratch
- Tinker with news and sentiment analysis, logging, AI, and more
- Learn by doing—every tool is deeply commented and fully readable by learners new to finance and coding
All folders are independent, so you can learn or build projects one topic at a time!
UTILS - Python Basics - Numbers/— Integers, floats, decimals, and financial mathUTILS - Python Basics - Strings/— Text processing and formattingUTILS - Python Basics - Control Flow/— If/else, loops, and comprehensionsUTILS - Python Basics - Functions/— Modular code, args/kwargs, and lambda functions
UTILS - Data Structures - Lists/— Sequences and array-like operationsUTILS - Data Structures - Dictionaries/— Key-value mappings and lookupsUTILS - Data Structures - Tuples and Sets/— Immutable records and unique collectionsUTILS - Data Structures - Arrays/— Introduction to NumPy arrays
UTILS - Advanced Python - OOP/— Classes, objects, inheritance, and trading systemsUTILS - Advanced Python - Error Handling/— Try/except, logging, and robust codeUTILS - Advanced Python - Decorators and Generators/— Efficient pipelines and function wrappers
UTILS - Quantitative Methods - Statistics/— Descriptive stats, distributions, and hypothesis testingUTILS - Quantitative Methods - Linear Algebra/— Matrices, eigenvalues, and portfolio mathUTILS - Quantitative Methods - Regression Analysis/— Beta calculation, factor models, and predictionUTILS - Quantitative Methods - Optimization/— Portfolio optimization, curve fitting, and root findingUTILS - Quantitative Methods - Stochastic Processes/— Brownian motion, GBM, and mean reversionUTILS - Quantitative Methods - TVM/— Time Value of Money (NPV, IRR, Annuities)UTILS - Quantitative Methods - Time Series/— ARIMA, GARCH, and trend analysis
UTILS - Sharpe and Sortino Ratio/— Measure risk-adjusted returnsUTILS - CAPM/— Asset pricing with Capital Asset Pricing ModelUTILS - Value at Risk (VaR)/— Gauge risk of loss on any investmentUTILS - Black-Scholes Option Pricing/— Price call & put optionsUTILS - Monte Carlo Portfolio Simulator/— Simulate many investment futuresUTILS - Bond Price and Yield/— Price bonds & estimate YTMUTILS - Discounted Cash Flow (DCF)/— Value projects/stocks with DCFUTILS - Portfolio Optimizer/— Find the best asset mix using MPTUTILS - Risk Metrics/— Volatility, drawdown, skew, kurtosis, and moreUTILS - Technical Indicators/— Compute trading/analysis indicatorsUTILS - Options Chain Simulator/— Simulate option chainsUTILS - Order Execution Simulator/— Model execution and slippageUTILS - Portfolio Tracker/— Track investment values over timeUTILS - Dividend Tracker/— Track, analyze, and project dividend incomeUTILS - Economic Calendar/— Access & analyze economic events
UTILS - Historical Data/— Fetch and parse price data from APIsUTILS - News Fetching/— Collect financial, trending or relevant newsUTILS - Sentiment Analysis on News/— Analyze news sentiment with PythonUTILS - Currency Converter/— Convert currencies and analyze ratesUTILS - Websocket Connection/— Real-time data, eg. from exchangesUTILS - Logging/— Professional and educational logging (Python & JS)UTILS - AI Development/— Templates for basic AI/chatbots in Python/JS
UTILS - Learning Platform/— Extendable Python learning hubDocumentation/— Learning paths, tutorials, reference, examples, quizzes, and extra resourcestests/— Example and reference tests for practicing and validating code
- Absolute beginners to Python or finance (comments explain all math & code)
- Tinkerers wanting to simulate, value, or analyze investments in plain code
- Anyone wanting a practical, realistic finance or coding codebase for reference, study, or projects
- Clone this repo:
git clone https://github.com/MeridianAlgo/Learn-Quant - Install Python 3.8+ and required packages:
pip install numpy pandas scipy matplotlib
- Explore any folder, read the README, and run the Python script for live examples
- Visit the
Documentation/folder for guided paths and exercises
- See something missing? Want to add modules, improve docs, or fix code? PRs welcome—this project is designed to grow for all learners!
Learn-Quant v1.1.0
Made with ❤️ by MeridianAlgo