Python for Finance and Algorithmic Trading with QuantConnect
Learn to use Python, Pandas, Matplotlib, and the QuantConnect Lean Engine to perform financial analysis and trading
4.82 (1917 reviews)
17 725
students
23 hours
content
May 2022
last update
$99.99
regular price
What you will 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
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Our Verdict
Python for Finance and Algorithmic Trading with QuantConnect is a comprehensive and engaging course that provides an in-depth look at Python libraries and financial analysis techniques. The course's main strength lies in the clear and concise teaching style, along with a thorough exploration of QuantConnect's capabilities. However, it falls short by not providing a full use case example and having outdated code snippets. Additionally, important derivatives trading topics are missing from the content. While this course still serves as an excellent starting point for learning about algorithmic trading, those interested in futures and options might need to look elsewhere.
What We Liked
- In-depth coverage of Python libraries and financial analysis techniques
- Excellent teaching style that's clear, concise, and engaging
- Thorough exploration of QuantConnect for backtesting and executing trade logic
- Well-structured course with straightforward explanations
Potential Drawbacks
- Lacks a full use case example using technical or fundamental analysis
- Some QuantConnect code in the videos is outdated
- Content for futures and options trading is not yet available in the course
- Exercises are spread far apart, making it difficult to retain information
Related Topics
4230404
udemy ID
08/08/2021
course created date
30/09/2021
course indexed date
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