Python For Financial Analysis And Algorithmic Trading

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Learn numpy , pandas , matplotlib , quantopian , finance , and more for algorithmic trading with Python!

What you’ll learn in Python For Financial Analysis

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

Requirements

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

Description

Welcome to Python for Financial Analysis and 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 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: