Python for Finance and Algorithmic Trading with QuantConnect
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English + srt | Duration: 112 lectures (20h 17m) | Size: 5.7 GB
Learn to use Python, Pandas, Matplotlib, and the QuantConnect Lean Engine to perform financial analysis and trading
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
Requirements
Basic Python Experience
Description
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)
Sharpe Ratio
Portfolio Allocation Optimization
Efficient Frontier and Markowitz Optimization
Types of Funds
Order Books
Short Selling
Capital Asset Pricing Model
Stock Splits and Dividends
Efficient Market Hypothesis
Algorithmic Trading with QuantConnect
Futures Trading
Options Trading
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.
Homepage
https://anonymz.com/?https://www.udemy.com/course/python-for-finance-and-algorithmic-trading-with-quantconnect/
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