Python for Finance and Algorithmic Trading with QuantConnect
What you'll learn
- Learn to use powerful Python libraries such as NumPy, Pandas, and Matplotlib
- Understand Modern Portfolio Theory
- Use Monte Carlo simulation techniques to optimize portfolio allocation
- Understand SciPy minimization algorithms to create optimized portfolio holdings
- Use and understand stock fundamentals data, such as CFC, Revenue, and EPS
- Calculate the Sharpe Ratio for any stock
- Understand cumulative returns and daily average returns in stocks
- Learn to use QuantConnect's LEAN engine for automated trading
- Learn about Bollinger Bands and other classic technical analysis
- Use algorithmic trading to trade derivative futures contracts
- Dive into understanding CAPM - Capital Asset Pricing Model
- Use fundamental stock company data to create rules based trading algorithms
- Learn about alternatives to the Sharpe Ratio, such as the Sortino Ratio
- Learn to read and understand a Backtest, including Probabilistic Sharpe Ratios
- Conduct Research on QuantConnect, including full universe stock selection screening
- Basic Python Experience
Welcome to the ultimate online course to go from zero to hero in Python for Finance, including Algorithmic Trading with LEAN Engine!
This course will guide you through everything you need to know to use Python for Finance and conducting Algorithmic Trading on the QuantConnect platform with the powerful LEAN engine!
This course is specifically design to connect core financial concepts to clear Python code. You will learn about in-demand real world skills that are highly sought after in the fintech ecosystem.
We'll cover the following topics used by financial professionals:
Python Crash Course Fundamentals
NumPy for High Speed Numerical Processing
Pandas for Efficient Data Analysis
Matplotlib for Data Visualization
Stock Returns Analysis
Cumulative Daily Returns
Volatility and Securities Risk
EWMA (Exponentially Weighted Moving Average)
Portfolio Allocation Optimization
Efficient Frontier and Markowitz Optimization
Types of Funds
Capital Asset Pricing Model
Stock Splits and Dividends
Efficient Market Hypothesis
Algorithmic Trading with QuantConnect
and much more!
Why choose this specific course to learn Python, Finance, and Algorithmic Trading?
This course starts by teaching you some of the most important and popular libraries in Python for Data Analysis and Visualization, includign NumPy, Pandas, and Matplotlib.
Each lecture includes a high quality HD video with clear instructions and relevant theory slides as well as a full Jupyter Notebook with explanatory code and text.
This course has complete coverage allowing you to actually implement your ideas as algorithms, other courses online never actually show you how to trade with your new knowledge!
Powerful online community with our QA Forums with thousands of students and dedicated Teaching Assistants, as well as student interaction on our Discord Server.
All of this comes with a 30-day money back guarantee, so you can try out the course absolutely risk free!
Who this course is for:
- Python developers interested in learning more about finance, markets, and algorithmic trading.
Jose Marcial Portilla has a BS and MS in Mechanical Engineering from Santa Clara University and years of experience as a professional instructor and trainer for Data Science, Machine Learning and Python Programming. He has publications and patents in various fields such as microfluidics, materials science, and data science. Over the course of his career he has developed a skill set in analyzing data and he hopes to use his experience in teaching and data science to help other people learn the power of programming, the ability to analyze data, and the skills needed to present the data in clear and beautiful visualizations. Currently he works as the Head of Data Science for Pierian Training and provides in-person data science and python programming training courses to employees working at top companies, including General Electric, Cigna, The New York Times, Credit Suisse, McKinsey and many more. Feel free to check out the website link to find out more information about training offerings.