Repository navigation
v1.2.0 - Standard Release
Utils-main: Quantitative Finance & Python Utilities (v1.2.0)
Welcome to Utils-main, a comprehensive, beginner-friendly toolkit for learning and practicing quantitative finance, data analysis, coding, and financial engineering in Python!
🚀 What is This Repo?
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
📦 What's Inside?
All folders are independent, so you can learn or build projects one topic at a time!
🐍 Python Basics (Level 1)
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
🏗️ Data Structures (Level 2)
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
🚀 Advanced Python (Level 3)
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
📊 Quantitative Methods (Math & Stats)
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
💰 Finance Utilities & Simulators
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
🌐 Data & Connectivity
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
🔧 Utility Libraries (NEW in v1.2.0)
Comprehensive utility collections organized by category:
-
🔧 UTILS - Data Processing — Data validation, string manipulation, and cleaning
data_validation_utils.py— Email, phone, stock symbol validation, sanitizationstring_utils.py— Case conversion, truncation, currency formatting, slug generation
-
⚙️ UTILS - System Utilities — File operations and configuration management
file_io_utils.py— JSON/CSV operations, backup, file managementconfig_utils.py— Configuration loading, dot notation access, environment variables
-
🧮 UTILS - Core Utilities — Mathematical and date/time foundations
datetime_utils.py— Trading days, market hours, timestamp operationsmath_utils.py— Financial calculations, CAGR, moving averages, regression
-
💼 UTILS - Portfolio Management — Portfolio analysis and risk metrics
portfolio_utils.py— Portfolio valuation, allocation, rebalancing, diversificationrisk_utils.py— VaR, drawdown, Sharpe/Sortino ratios, stress testing, correlations
-
📊 UTILS - Market Data — Data processing and API integration
market_data_utils.py— Returns, outliers, sentiment analysis, data validationapi_utils.py— HTTP requests, retry logic, API key management, error handling
📚 Learning Platform
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
🎯 Who Is This For?
- 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
🛠️ Getting Started
- Clone this repo:
git clone https://github.com/MeridianAlgo/Learn-Quant - Install Python 3.8+ and required packages:
pip install numpy pandas scipy matplotlib requests
- Explore any folder, read the README, and run the Python script for live examples
- Visit the
Documentation/folder for guided paths and exercises
🆕 What's New in v1.2.0
- 🔧 5 New Utility Libraries: Comprehensive utility collections organized by category
- 📊 Enhanced Portfolio Tools: Advanced portfolio management and risk analysis utilities
- 🌐 Market Data Processing: Professional-grade data validation and API integration
- ⚙️ System Integration: Robust file I/O and configuration management
- 🧮 Core Mathematical Functions: Financial calculations and date/time utilities
- 📚 Improved Documentation: Each utility includes comprehensive README and examples
🌱 Contributing
- 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 v1.2.0
25 files added, 5,720+ lines of new utility code
Made with ❤️ by MeridianAlgo