Python for Financial Analysis and Algorithmic Trading

4.6 (13219)
MOOC
Payment
Learning paid
Language
English
Duration
17 hours course
Course by Udemy
$ 126.99
$ 126.99
What will you learn?
Use NumPy to quickly work with Numerical Data
Use Pandas for Analyze and Visualize Data
Use Matplotlib to create custom plots
Learn how to use statsmodels for Time Series Analysis
Calculate Financial Statistics, such as Daily Returns, Cumulative Returns, Volatility, etc..
Use Exponentially Weighted Moving Averages
Use ARIMA models on Time Series Data
Calculate the Sharpe Ratio
Optimize Portfolio Allocations
Understand the Capital Asset Pricing Model
Learn about the Efficient Market Hypothesis
Conduct algorithmic Trading on Quantopian
About the course

Welcome to Python for Financial Analysis and Algorithmic Trading! Are you interested in how people use Python to conduct rigorous financial analysis and pursue algorithmic trading, then this is the right course for you!

This course will guide you through everything you need to know to use Python for Finance and Algorithmic Trading! We'll start off by learning the fundamentals of Python, and then proceed to learn about the various core libraries used in the Py-Finance Ecosystem, including jupyter, numpy, pandas, matplotlib, statsmodels, zipline, Quantopian, and much more!

 We'll cover the following topics used by financial professionals:

  • Python Fundamentals
  • NumPy for High Speed Numerical Processing
  • Pandas for Efficient Data Analysis
  • Matplotlib for Data Visualization
  • Using pandas-datareader and Quandl for data ingestion
  • Pandas Time Series Analysis Techniques
  • Stock Returns Analysis
  • Cumulative Daily Returns
  • Volatility and Securities Risk
  • EWMA (Exponentially Weighted Moving Average)
  • Statsmodels
  • ETS (Error-Trend-Seasonality)
  • ARIMA (Auto-regressive Integrated Moving Averages)
  • Auto Correlation Plots and Partial Auto Correlation Plots
  • 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 Quantopian
  • Futures Trading
Program
Course Introduction
Let's go over the course!
Introduction to Course
Course Overview Lecture (DON'T SKIP THIS!)
Did you skip the last lecture? Please go back and view it!
Course FAQ
Course Materials and Set-up
Let's get you set-up!
Course Installation Help Notes
Course Installation Guide
Python Crash Course
Quick Review of Python if you need it!
Welcome to the Python Crash Course
Introduction to Crash Course
Python Crash Course Part One
Requirements
  • Some knowledge of programming (preferably Python)
  • Ability to Download Anaconda (Python) to your computer
  • Basic Statistics and Linear Algebra will be helpful
Lecturers
Jose Portilla
Jose Portilla
Head of Data Science, Pierian Data Inc.
Platform
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Udemy courses are suited to professional development. The platform is organized in such a way that it is experts themselves that decide the topic and when the course will start. All supporting documents are made available to you for lifetime access. On this platform, you can find a course on about any subject, and that is no exaggeration – from a tutorial on how to ride a motorcycle, to managing the financial markets. The language and the course format are established by the teacher. This is why it is important to read the information about the course carefully before parting with any money.
Rating
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