Business
Finance
Algorithmic Trading
Algorithmic Trading & Quantitative Analysis Using Python
4.5 (1,232 ratings)
Course Ratings are calculated from individual students’ ratings and a variety of other signals, like age of rating and reliability, to ensure that they reflect course quality fairly and accurately.
9,439 students enrolled

Algorithmic Trading & Quantitative Analysis Using Python

Build fully automated trading system and Implement quantitative trading strategies using Python
Bestseller
4.5 (1,232 ratings)
Course Ratings are calculated from individual students’ ratings and a variety of other signals, like age of rating and reliability, to ensure that they reflect course quality fairly and accurately.
9,445 students enrolled
Created by Mayank Rasu
Last updated 7/2020
English
English [Auto], French [Auto]
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Algorithmic Trading & Quantitative Analysis Using Python
Current price: $34.99 Original price: $49.99 Discount: 30% off
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This course includes
  • 18 hours on-demand video
  • 4 articles
  • 15 downloadable resources
  • Full lifetime access
  • Access on mobile and TV
  • Certificate of Completion
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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
Featured review
Mellacheruvu Krishna Teja
Mellacheruvu Krishna Teja ( 4 courses, 2 reviews )
9 months ago
Highly recommended course for the people who wants to explore the finance with technology. The content was super cool and the instructor is really friendly, the way he explains the concepts is amazing. Thanks a lot Mayank!
Course content
Expand all 103 lectures 17:46:17
+ – Getting Data
12 lectures 02:18:01
Data Gathering Intro
05:00
yfinance Overview
07:32
yfinance - Getting Data for Multiple Stocks
14:16
yahoofinancials Library and Parsing JSON Data
10:28
yahoofinancials - Getting Data for Multiple Stocks
13:51
Alpha Vantage Python Library Intro
07:53
Alpha Vantage - Getting Data for Multiple Tickers
16:48
Web Scraping Intro
09:23
Using Web Scraping to Extract Stock Fundamental Data - I
16:02
Using Web Scraping to Extract Stock Fundamental Data - II
23:43
Updated Web-Scraping Code - Yahoo-Finance Webpage Changes
12:35
Other Free Data Resources
00:30
+ – Basic Data Handling and Operations
5 lectures 01:06:56
Handling NaN Values
17:00
Basic Statistics - Familiarize Yourself With Your Data
10:46
Rolling Operations - Data In Motion
15:01
Visualization Basics - I
10:18
Visualization Basics - II
13:51
+ – Technical Indicators
18 lectures 03:03:52
Introduction to Technical Indicators
09:11
MACD Overview
08:31
MACD Implementation in Python
11:10
ATR and Bollinger Bands Overview
06:08
ATR and Bollinger Bands Implementation in Python
14:00
RSI Overview and Excel Implementation
11:58
RSI Implementation in Python
11:27
ADX Overview
04:13
ADX Implementation in Excel
12:55
ADX Implementation in Python
13:41
OBV Overview and Excel Implementation
06:36
OBV Implementation in Python
03:07
Slope in a Chart
04:12
Slope Implementation in Python
23:03
Renko Overview
06:57
Renko Implementation in Python
14:27
TA-Lib Introduction
04:23
TA-Lib Installation and Application
17:53
+ – Performance Measurement - KPIs
9 lectures 52:25
Introduction to Performance Measurement
02:03
CAGR Overview
04:03
CAGR Implementation in Python
09:29
How to Measure Volatility
04:17
Volatility Measures' Python Implementation
02:27
Sharpe Ratio and Sortino Ratio
04:32
Sharpe and Sortino in Python
10:25
Maximum Drawdown and Calmar Ratio
03:58
Maximum Drawdown and Calmar Ratio in Python
11:11
+ – Backtest Your Strategies
9 lectures 02:03:41
Why Should I Backtest My Strategies?
06:53
Strategy I - Portfolio Rebalancing
07:03
Strategy I in Python
28:20
Strategy II - Resistance Breakout
08:27
Strategy II in Python
28:47
Strategy III - Renko and OBV
04:34
Strategy III in Python
21:24
Strategy IV - Renko and MACD
05:19
Strategy IV in Python
12:54
+ – Value Investing
7 lectures 01:10:16
Value Investing Overview
04:56
Introduction to Magic Formula
06:02
Magic Formula Implementation in Python
24:16
Updated Python Code - Yahoo-Finance Webpage Changes
00:17
Introduction to Piotroski F-Score
07:20
Piotroski F-Score Implementation in Python
27:08
Updated Python Code - Yahoo-Finance Webpage Changes
Preview 00:17
+ – Building Automated Trading System on a Shoestring Budget
12 lectures 02:42:00
Automated/Algorithmic Trading Overview
13:48
Using Time Module in Python
12:44
FXCM Overview
07:01
Introduction to FXCM Terminal
12:34
FXCM API
22:06
Building an Automated Trading System - part I
08:08
Building an Automated Trading System - part II
11:14
Building an Automated Trading System - part III
11:23
Building an Automated Trading System - part IV
10:50
OANDA Overview
06:56
OANDA API
25:57
SMA Crossover Strategy using OANDA API
19:19
+ – Bonus Section: Running Your Algorithms in Cloud
7 lectures 01:18:57
Why Cloud
04:54
Launching AWS EC2 Instance
19:57
Connecting To The EC2 Instance I
15:11
Connecting To The EC2 Instance II
07:48
Transferring Files to EC2 Instance
12:11
Scheduling/Automating Your Scripts Using Crontab
15:15
Shutting Down/Deleting EC2 Instance
03:41
+ – Bonus Section: Sentiment Analysis
14 lectures 02:21:44
Why Sentiment Analysis
06:00
Sentiment Analysis - Intuition
08:09
Natural Language Processing Basics
17:16
Lexicon Based Sentiment Analysis
06:36
VADER Introduction
11:35
Textblob Introduction
07:41
Building a Sentiment Analyzer using VADER - Part I
10:35
Building a Sentiment Analyzer using VADER - Part II
18:21
Machine Learning Based Sentiment Analysis
13:59
ML Feature Matrix & TF-IDF Introduction
09:50
Building ML Based Sentiment Analyzer - Part I
03:16
Building a ML Based Sentiment Analyzer - Part II
16:59
Building a ML Based Sentiment Analyzer - Part III
06:31
Sentiment Analysis Application - Opportunities & Challenges
04:56