Python for Finance

Enroll in our Python for Finance course today! Learn to use various Python libraries such as QuantConnect to perform financial analysis and research.

 

 

Student rating

5.00 Out Of 17 Students

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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

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Course Content

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.

 

 

  • Python
  • Numpy
  • Pandas
  • Matplotlib
  • Financial Concepts with Python
    • Effective Market Hypothesis
    • Sharpe Ratio
    • Sortino Ratio
    • Modern Portfolio Theory
    • Capital Asset Pricing Method
  • Algorithmic Trading with Quantconnect
    • How to use Quantconnect
    • Buying and Selling Shares
    • Implementation of Custom Algorithms
    • Plotting
    • Future & Option Trading
    • Backtesting

 

 

Intermediate to experienced Python developers looking to work with financial time series data. Check out our Introduction to Python course if you’re new to Python programming.

 

 

Course Description

This Python for Finance course is for students familiar with python who want to learn how to use python for financial data and algorithmic trading. Core financial concepts and strategies, such as Modern Portfolio Theory paired with clean python code build a solid ground to implement trading algorithms on the Quantconnect platform with their Lean engine. Quantconnect offers large functionality for implementation, backtesting and deployment of custom algorithms for algorithmic trading.

 

 

What Students Are Saying

This course is very precise and very interesting, based on the concepts of finance. The course is suitable for beginners.nToo 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.

Artur Agababyan

great course - very good teacher and good knowledge about stock market

Anthony griffiths

I enjoy the smooth and easy way Jose presents the material

Michael Malgeri

Jose's teaching style is amazing! He does a great job breaking down what you need to learn and is very clear in his videos.

Marcos Garcia

Jose P courses always good. Want to learn about QuantConnect.

David Haertzen

I am in halfway of course and I must say I am very much satisfied.

Kumar Divyanshu

Have taking several courses and they are always well thought out with lots of understandable instructions.

Gregg Flora

- Very straight forward with Jupyter's main functionalities. Pandas and numpy libraries in depth using financial data. Well explained and pertinent financial concepts for managing portfolios

Nicolas Novikow

Jose is an excellent teacher, makes the concepts easy to understand and maybe most important groups the concepts in a logical way to allow the student to make progress.nThe course is not only on Python for trading but covers lots of basics of capital markets, that are important for a new comer or a good refresher for an old timer.

Savio Viana

It is not easy to be an instructor. And coming from a programming background it takes me a lot of effort to smoothly explain concepts. Jose conveys his message very thoroughly. Every lecture is well prepared in advance and very easy to follow. I feel the effort needed to come up with such as long and well designed course takes a huge amount of effort and dedication.

Dario Teodori
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Python Learning online
Course type
  • In-House
  • Self-Paced
Student rating

5.00

Course length

134 Lectures

22 Hours

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