Python Best Courses

# Python for Financial Analysis and Algorithmic Trading Learn Financial Analysis ## Python for Financial Analysis and Algorithmic Trading Learn Financial Analysis

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

#### What you’ll learn

Python for Financial Analysis and Algorithmic Trading Learn Financial Analysis

• Use NumPy to quickly work with Numerical Data
• Learn how to 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)
• Basic Statistics and Linear Algebra will be helpful

#### Description

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 Jupiter, 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

#### Who this course is for: • […] Python for Financial Analysis […]

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