Algorithmic Trading Quantitative Analysis Using Python

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Tags: Quantitative Finance , Algorithmic Trading

Build fully automated trading system and Implement quantitative trading strategies using Python

Last updated 2022-01-10 | 4.5

- Algorithmic trading and quantitative analysis using python
- Carrying out both technical analysis and fundamental analysis programatically
- API trading

What you'll learn

Algorithmic trading and quantitative analysis using python
Carrying out both technical analysis and fundamental analysis programatically
API trading

* Requirements

* Intermediate level expertise in python
* high school level familiarity with mathematics and statistics
* Basic understanding of equity/forex trading

Description

Build a fully automated trading bot on a shoestring budget. Learn quantitative analysis of financial data using python. Automate steps like extracting data, performing technical and fundamental analysis, generating signals, backtesting, API integration etc. You will learn how to code and back test trading strategies using python. The course will also give an introduction to relevant python libraries required to perform quantitative analysis. The USP of this course is delving into API trading and familiarizing students with how to fully automate their trading strategies.


You can expect to gain the following skills from this course

  • Extracting daily and intraday data for free using APIs and web-scraping

  • Working with JSON data

  • Incorporating technical indicators using python

  • Performing thorough quantitative analysis of fundamental data

  • Value investing using quantitative methods

  • Visualization of time series data

  • Measuring the performance of your trading strategies

  • Incorporating and backtesting your strategies using python

  • API integration of your trading script

  • FXCM and OANDA API

  • Sentiment Analysis

Who this course is for:

  • traders looking to automate strategies and building automated trading stations, data scientists seeking to work with financial data, anyone curious about quantitative analysis

Course content

11 sections • 109 lectures

Introduction 7 lectures

What Is Covered in this Course? Preview 04:31

Course Prerequisites Preview 01:57

Is This For Me? Preview 01:39

How To Get Help Preview 02:42

Streaming Coding Lectures Preview 02:27

Anaconda Distribution Intro Preview 03:36

Creating Virtual Environment (Optional) Preview 09:58

Getting Data 13 lectures

Data Gathering Intro Preview 05:00

yfinance Overview Preview 07:32

yfinance - Getting Data for Multiple Stocks Preview 14:16

yahoofinancials Library and Parsing JSON Data Preview 10:28

yahoofinancials - Getting Data for Multiple Stocks Preview 13:51

Alpha Vantage Python Library Intro Preview 07:53

Alpha Vantage - Getting Data for Multiple Tickers Preview 16:48

Web Scraping Intro Preview 09:23

Important Note - Yahoo Finance Web Scraping Preview 00:20

Using Web Scraping to Extract Stock Fundamental Data - I Preview 16:02

Using Web Scraping to Extract Stock Fundamental Data - II Preview 23:43

Updated Web-Scraping Code - Yahoo-Finance Webpage Changes Preview 12:35

Other Free Data Resources Preview 00:30

Basic Data Handling and Operations 5 lectures

Handling NaN Values Preview 17:00

Basic Statistics - Familiarize Yourself With Your Data Preview 12:37

Rolling Operations - Data In Motion Preview 10:17

Visualization Basics - I Preview 13:03

Visualization Basics - II Preview 10:36

Technical Indicators 16 lectures

Introduction to Technical Indicators Preview 04:40

Introduction to Charting Preview 11:00

MACD Overview Preview 08:13

MACD Implementation in Python Preview 18:20

ATR and Bollinger Bands Overview Preview 09:39

ATR Implementation in Python Preview 11:56

Bollinger Bands Implementation in Python Preview 06:36

RSI Overview and Excel Implementation Preview 10:27

RSI Implementation in Python Preview 09:35

ADX Overview Preview 04:14

ADX Implementation in Excel Preview 12:46

ADX Implementation in Python Preview 10:31

Renko Overview Preview 07:31

Renko Implementation in Python Preview 11:37

TA-Lib Introduction Preview 04:23

TA-Lib Installation and Application Preview 17:53

Performance Measurement - KPIs 9 lectures

Introduction to Performance Measurement Preview 04:50

CAGR Overview Preview 03:04

CAGR Implementation in Python Preview 10:20

How to Measure Volatility Preview 03:45

Volatility Measures' Python Implementation Preview 02:57

Sharpe Ratio and Sortino Ratio Preview 04:26

Sharpe and Sortino in Python Preview 08:11

Maximum Drawdown and Calmar Ratio Preview 03:38

Maximum Drawdown and Calmar Ratio in Python Preview 08:12

Backtest Your Strategies 10 lectures

Why Should I Backtest My Strategies? Preview 06:53

Strategy I - Portfolio Rebalancing Preview 07:03

Strategy I in Python Preview 28:20

Strategy II - Resistance Breakout Preview 08:27

Strategy II in Python -I Preview 18:41

Strategy II in Python -II Preview 28:05

Strategy III - Renko and OBV Preview 04:34

Strategy III in Python Preview 21:24

Strategy IV - Renko and MACD Preview 05:19

Strategy IV in Python Preview 12:54

Value Investing 7 lectures

Value Investing Overview Preview 04:56

Introduction to Magic Formula Preview 06:02

Magic Formula Implementation in Python Preview 24:16

Updated Python Code - Yahoo-Finance Webpage Changes Preview 00:44

Introduction to Piotroski F-Score Preview 07:20

Piotroski F-Score Implementation in Python Preview 27:08

Updated Python Code - Yahoo-Finance Webpage Changes Preview 00:22

Building Automated Trading System on a Shoestring Budget 12 lectures

Automated/Algorithmic Trading Overview Preview 13:48

Using Time Module in Python Preview 12:44

FXCM Overview Preview 07:01

Introduction to FXCM Terminal Preview 12:34

FXCM API Preview 22:06

Building an Automated Trading System - part I Preview 08:08

Building an Automated Trading System - part II Preview 11:14

Building an Automated Trading System - part III Preview 11:23

Building an Automated Trading System - part IV Preview 10:50

OANDA Overview Preview 06:56

OANDA API Preview 25:57

SMA Crossover Strategy using OANDA API Preview 19:19

Bonus Section: Running Your Algorithms in Cloud 9 lectures

Why Cloud Preview 04:54

Launching AWS EC2 Instance Preview 19:57

Connecting To The EC2 Instance I Preview 15:11

Connecting To The EC2 Instance II Preview 07:48

Transferring Files to EC2 Instance Preview 12:11

Scheduling/Automating Your Scripts Using Crontab Preview 15:15

Keeping Track of Running Processes Preview 10:32

Using Screen Command with Crontab Preview 07:35

Shutting Down/Deleting EC2 Instance Preview 03:41

Bonus Section: Sentiment Analysis 14 lectures

Why Sentiment Analysis Preview 06:00

Sentiment Analysis - Intuition Preview 08:09

Natural Language Processing Basics Preview 17:16

Lexicon Based Sentiment Analysis Preview 06:36

VADER Introduction Preview 11:35

Textblob Introduction Preview 07:41

Building a Sentiment Analyzer using VADER - Part I Preview 10:35

Building a Sentiment Analyzer using VADER - Part II Preview 18:21

Machine Learning Based Sentiment Analysis Preview 13:59

ML Feature Matrix & TF-IDF Introduction Preview 09:50

Building ML Based Sentiment Analyzer - Part I Preview 03:16

Building a ML Based Sentiment Analyzer - Part II Preview 16:59

Building a ML Based Sentiment Analyzer - Part III Preview 06:31

Sentiment Analysis Application - Opportunities & Challenges Preview 04:56

Archived Lectures 7 lectures

Archived Lectures - Important Note Preview 00:31

Pandas Datareader Overview Preview 09:23

Getting Data Using Pandas Datareader Preview 11:40

OBV Overview and Excel Implementation Preview 06:36

OBV Implementation in Python Preview 03:07

Slope in a Chart Preview 04:12

Slope Implementation in Python Preview 23:03