Course Information
Registration period
Year-round Recruitment
Course Level
Study Mode
Duration
16 Hour(s) 38 Minute(s)
Language
English
Taught by
Jose Portilla, Pierian Training
Certificate
- Available
- *The delivery and distribution of the certificate are subject to the policies and arrangements of the course provider.
Rating
Course Overview
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!
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
Course Content
- 14 section(s)
- 120 lecture(s)
- Section 1 Course Introduction
- Section 2 Course Materials and Set-up
- Section 3 Python Crash Course
- Section 4 NumPy
- Section 5 General Pandas Overview
- Section 6 Visualization with Matplotlib and Pandas
- Section 7 Data Sources
- Section 8 Pandas with Time Series Data
- Section 9 Capstone Stock Market Analysis Project
- Section 10 Time Series Analysis
- Section 11 Python Finance Fundamentals
- Section 12 Basics of Algorithmic Trading with Quantopian and Zipline
- Section 13 Advanced Quantopian and Trading Algorithms
- Section 14 BONUS SECTION: THANK YOU!
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
Skills covered in this course
Reviews
-
NNavdeep Sharma
This is really very knowledgeable course. I have learnt so many things after doing this course. I am also saying it in my learning path for future reference.
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SShafi Chitrachedu
good
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AAashwini Patil
Nice Explanation with real time examples
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DDylan Ferrara
Very good background on Python practices for finance, yet many of the libraries/tools are outdated, requiring configurations. Instructor has a good rhythm in teaching these concepts.
