Python for Financial Analysis and Algorithmic Trading

Python for Financial Analysis and Algorithmic Trading

Python for Financial Analysis and Algorithmic Trading. Learn numpy , pandas , matplotlib , quantopian , finance , and more for algorithmic trading with Python!

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!

Python for Financial Analysis and Algorithmic Trading Description

Requirements

  • Some knowledge of programming (preferably Python)
  • Ability to Download Anaconda (Python) to your computer
  • Basic Statistics and Linear Algebra will be helpful

Python for Finance Investment Fundamentals & Data Analytics Course

What you’ll 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

Who this course is for:

  • Someone familiar with Python who wants to learn about Financial Analysis!

Python for Financial Analysis and Algorithmic Trading Free Download

Google Drive (Public)

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Content From: https://www.udemy.com/course/python-for-finance-and-trading-algorithms/

2 Comments

  1. Elow August 23, 2020
    • hauvuhdvn August 23, 2020

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