Python for Finance and Algorithmic Trading with QuantConnect
Original price was: $84.99.$14.99Current price is: $14.99.
What you’ll learn
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Learn to use powerful Python libraries such as NumPy, Pandas, and Matplotlib
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Understand Modern Portfolio Theory
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Use Monte Carlo simulation techniques to optimize portfolio allocation
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Understand SciPy minimization algorithms to create optimized portfolio holdings
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Use and understand stock fundamentals data, such as CFC, Revenue, and EPS
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Calculate the Sharpe Ratio for any stock
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Understand cumulative returns and daily average returns in stocks
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Learn to use QuantConnect’s LEAN engine for automated trading
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Learn about Bollinger Bands and other classic technical analysis
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Use algorithmic trading to trade derivative futures contracts
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Dive into understanding CAPM – Capital Asset Pricing Model
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Use fundamental stock company data to create rules based trading algorithms
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Learn about alternatives to the Sharpe Ratio, such as the Sortino Ratio
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Learn to read and understand a Backtest, including Probabilistic Sharpe Ratios
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Conduct Research on QuantConnect, including full universe stock selection screening
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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:
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Python Crash Course Fundamentals
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NumPy for High Speed Numerical Processing
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Pandas for Efficient Data Analysis
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Matplotlib for Data Visualization
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Stock Returns Analysis
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Cumulative Daily Returns
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Volatility and Securities Risk
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EWMA (Exponentially Weighted Moving Average)
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Sharpe Ratio
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Portfolio Allocation Optimization
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Efficient Frontier and Markowitz Optimization
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Types of Funds
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Order Books
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Short Selling
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Capital Asset Pricing Model
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Stock Splits and Dividends
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Efficient Market Hypothesis
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Algorithmic Trading with QuantConnect
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Futures Trading
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Options Trading
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and much more!
Why choose this specific course to learn Python, Finance, and Algorithmic Trading?
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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.
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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.
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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!
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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.
10 reviews for Python for Finance and Algorithmic Trading with QuantConnect
Add a review
Original price was: $84.99.$14.99Current price is: $14.99.
Daniel Razumov –
I like the way Jose teaching the material, I am getting a good understanding of the topics that we are going thought (which is good), however I just wish there were more examples of strategies, researches and work technics for Quanconnect. There was very little exercises at the last section of the course …. it was promised that I will feel comfortable to create any strategy in QQ once finish the material, but clearly that not the case, defiantly not there yet unfortunately . It feels like the course was stopped in the middle at the most important part
Sebastian Teo –
Mostly focus on basic use of QuantConnect with simple and easy to follow python coding.
Jacobo Pérez Schwartz –
Excellent course, as expected from Jose Portilla. Loved that his python refreshes are not the same in every course, I learn a bit in each of those. Amazing teacher, great knowledge and explanations. I was hoping to see arbitrages. Thanks!!!
Artur Agababyan –
This course is very precise and very interesting, based on the concepts of finance. The course is suitable for beginners.
Too bad QuantConnect does not allow you to analyze the European markets (CAC 40, DAX 40, etc.). If other similar platforms exist for European markets can you add them as for alternative data sources, please.
Riccardo Manazza –
That was an abrupt ending to the course, there was no ,Where do we go from here.
I learned a lot!! wish there was a connection between the first part and second part of the course how to use machine learning and algorithm.
I want to thank Jose for putting together another amazing and easy to follow course
Miguel Pallás –
Sections 2-7 are really good. However, I think the capstone project in Section 8 could have been more thorough.
I am halfway through Section 9. The leap in difficulty is noticeable and I am not following as smoothly as in the previous sections. Maybe more practice exercises and more detailed notes would help. Having said that, it is also a student’s duty to go the extra mile and look for resources if they feel they are lagging behind. Cheers!
Massimo Pascucci –
Amazing Content! Very informative and hopefully applicable. I love this course, but really just wish at some points the instruction was a little bit slower. The concepts are pretty technical and further explanation at a slower pace would have been helpful.
Allen Lin –
Coming into this course from an internship at a quantitative hedgefund, I can say there were a ton of shortcuts I could’ve used that I wasn’t aware of. Honestly one of the best classes I’ve taken so far online!
Ronald van Ravensberg –
A bit to much focus on using QuantConnect in stead of general explanation of the concepts (buting, selling equaties, backtesting and using data to research stocks and testing the strategies.
The first part was a very good explaintion of how to use pandas, matplotlib and numpy. The second part felt like a manual for QuantConnect. Still a usefull course but could be better.
Andrés Felipe Tello Urrea –
The financial terms are easy to understand and come always with a practical application of them, that make’s the course just what I need