Mayank Rasu – Algorithmic Trading & Quantitative Analysis Using Python (Download)
The financial markets operate 24/7, generating countless opportunities that manual trading simply cannot capture. Algorithmic trading eliminates emotional decision-making, executes trades at optimal moments, and allows you to backtest strategies before risking real capital. For traders, data scientists, and finance professionals, Python has become the industry-standard tool for quantitative analysis and automated trading systems.
Course Overview
“Algorithmic Trading & Quantitative Analysis Using Python” by instructor Mayank Rasu provides comprehensive training in building fully automated trading systems on a budget. This practical course teaches you to extract financial data, implement technical and fundamental analysis programmatically, backtest strategies, and deploy live trading bots through API integration.
What You’ll Learn
Data Acquisition and Processing
Master multiple methods for gathering financial data including yfinance and Alpha Vantage libraries for stock data, web scraping techniques using BeautifulSoup and Selenium, handling JSON data from APIs, and managing missing values and basic statistical operations.
Technical Analysis Implementation
Learn to code essential technical indicators from scratch: MACD, ATR, Bollinger Bands, RSI, ADX, and Renko charts. You’ll also explore the TA-Lib library for streamlined indicator implementation and create visualizations to analyze price movements and patterns.
Strategy Development and Backtesting
Develop and test four distinct trading strategies including portfolio rebalancing, resistance breakout systems, Renko with OBV indicators, and Renko with MACD combinations. You’ll measure performance using key metrics like CAGR, Sharpe ratio, Sortino ratio, maximum drawdown, and Calmar ratio.
Value Investing Techniques
Apply quantitative methods to fundamental analysis using the Magic Formula investing approach and Piotroski F-Score for identifying undervalued stocks with strong fundamentals.
You may also be interested in these courses:
- 365 Careers – Accounting Made Easy: A Quick Guide to Financial Accounting (Download)
- Mohsen Hassan – The Complete Foundation Stock Trading Course (Download)
Building Automated Trading Systems
Connect to trading platforms via MetaTrader5 Python API, place and manage orders programmatically, implement complete automated strategies, and deploy trading bots on AWS cloud infrastructure for 24/7 operation. Learn scheduling with crontab and process management for uninterrupted trading.
Advanced Topics
Explore sentiment analysis using VADER and TextBlob for lexicon-based approaches, plus machine learning methods with TF-IDF for analyzing market sentiment from news and social media.
Course Structure
The curriculum progresses from data handling fundamentals through advanced automation, with hands-on coding demonstrations and real-world strategy implementations. Archived sections cover additional platforms like FXCM and OANDA for expanded API trading options.
Who Should Enroll
This course is ideal for traders wanting to automate their strategies, data scientists interested in financial applications, Python developers exploring quantitative finance, and anyone seeking to build algorithmic trading systems affordably.
Basic Python knowledge and understanding of financial markets are recommended to maximize learning outcomes.
