The ‘Algorithmic Trading & Quantitative Analysis Using Python’ course will teach you to build fully automated trading system and Implement quantitative trading strategies using Python. In this course, 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 course delves into API trading and familiarizes you with how to fully automate your trading strategies. The course is usually available for INR 2,799 on Udemy but you can click on the link and get the ‘Algorithmic Trading & Quantitative Analysis Using Python’ for INR 499.
Who all can opt for this course?
- Anyone interested in quantitative analysis, including traders wishing to develop automated trading stations and automate their trading techniques
Course Highlights
| Key Highlights | Details |
|---|---|
| Registration Link | Apply Now! |
| Price | INR 499 ( |
| Duration | 19.5 Hours |
| Rating | 4.5/5 |
| Student Enrollment | 28,792 students |
| Instructor | Mayank Rasu https://www.linkedin.com/in/mayankrasu |
| Topics Covered | Web Sraping, API, Automated Trading System, JSON |
| Course Level | Advanced |
| Total Student Reviews | 3,417 |
Learning Outcomes
- Python-based quantitative analysis and algorithmic trading
- Execution of both technical analysis and fundamental analysis
- Trading API
Course Content
| S.No. | Module (Duration) | Topics |
|---|---|---|
| 1. | Introduction (24 minutes) | What Is Covered in this Course? |
| Course Prerequisites | ||
| Is This For Me? | ||
| How To Get Help | ||
| Anaconda Distribution Intro | ||
| Creating Virtual Environment (Optional) | ||
| 2. | Getting Data (01 hour 16 minutes) | Data Gathering Intro |
| yfinance Overview | ||
| yfinance – Getting Data for Multiple Stocks | ||
| yahoofinancials Library and Parsing JSON Data | ||
| yahoofinancials – Getting Data for Multiple Stocks | ||
| Alpha Vantage Python Library Intro | ||
| Alpha Vantage – Getting Data for Multiple Tickers | ||
| Other Free Data Resources | ||
| 3. | Web Scraping to Extract Financial Data (01 hour 11 minutes) | Web Scraping Vs API Based Data Extraction |
| HTML Intro | ||
| Web Scraping Financial Data Using Python – I | ||
| Web Scraping Financial Data Using Python – II | ||
| Web Scraping Financial Data Using Python – III | ||
| 4. | Basic Data Handling and Operations (01 hour 03 minutes) | Handling NaN Values |
| Basic Statistics – Familiarize Yourself With Your Data | ||
| Rolling Operations – Data In Motion | ||
| Visualization Basics – I | ||
| Visualization Basics – II | ||
| 5. | Technical Indicators (02 hours 39 minutes) | Introduction to Technical Indicators |
| Introduction to Charting | ||
| MACD Overview | ||
| MACD Implementation in Python | ||
| ATR and Bollinger Bands Overview | ||
| ATR Implementation in Python | ||
| Bollinger Bands Implementation in Python | ||
| RSI Overview and Excel Implementation | ||
| RSI Implementation in Python | ||
| ADX Overview | ||
| ADX Implementation in Excel | ||
| ADX Implementation in Python | ||
| Renko Overview | ||
| Renko Implementation in Python | ||
| TA-Lib Introduction | ||
| TA-Lib Installation and Application | ||
| 6. | Performance Measurement – KPIs (49 minutes) | Introduction to Performance Measurement |
| CAGR Overview | ||
| CAGR Implementation in Python | ||
| How to Measure Volatility | ||
| Volatility Measures’ Python Implementation | ||
| Sharpe Ratio and Sortino Ratio | ||
| Sharpe and Sortino in Python | ||
| Maximum Drawdown and Calmar Ratio | ||
| Maximum Drawdown and Calmar Ratio in Python | ||
| 7. | Backtest Your Strategies (02 hours 21 minutes) | Why Should I Backtest My Strategies? |
| Strategy I – Portfolio Rebalancing | ||
| Strategy I in Python | ||
| Strategy II – Resistance Breakout | ||
| Strategy II in Python -I | ||
| Strategy II in Python -II | ||
| Strategy III – Renko and OBV | ||
| Strategy III in Python | ||
| Strategy IV – Renko and MACD | ||
| Strategy IV in Python | ||
| 8. | Value Investing (01 hour 10 minutes) | Value Investing Overview |
| Introduction to Magic Formula | ||
| Magic Formula Implementation in Python | ||
| Updated Python Code – Yahoo-Finance Webpage Changes | ||
| Introduction to Piotroski F-Score | ||
| Piotroski F-Score Implementation in Python | ||
| Updated Python Code – Yahoo-Finance Webpage Changes | ||
| 9. | Building Automated Trading System on a Shoestring Budget (02 hours 42 minutes) | Automated/Algorithmic Trading Overview |
| Using Time Module in Python | ||
| FXCM Overview | ||
| Introduction to FXCM Terminal | ||
| FXCM API | ||
| Building an Automated Trading System – part I | ||
| Building an Automated Trading System – part II | ||
| Building an Automated Trading System – part III | ||
| Building an Automated Trading System – part IV | ||
| OANDA Overview | ||
| OANDA API | ||
| SMA Crossover Strategy using OANDA API | ||
| 10. | Bonus Section: Running Your Algorithms in Cloud (01 hour 37 minutes) | Why Cloud |
| Launching AWS EC2 Instance | ||
| Connecting To The EC2 Instance I | ||
| Connecting To The EC2 Instance II | ||
| Transferring Files to EC2 Instance | ||
| Scheduling/Automating Your Scripts Using Crontab | ||
| Keeping Track of Running Processes | ||
| Using Screen Command with Crontab | ||
| Shutting Down/Deleting EC2 Instance | ||
| 11. | Bonus Section: Sentiment Analysis (02 hours 21 minutes) | Why Sentiment Analysis |
| Sentiment Analysis – Intuition | ||
| Natural Language Processing Basics | ||
| Lexicon Based Sentiment Analysis | ||
| VADER Introduction | ||
| Textblob Introduction | ||
| Building a Sentiment Analyzer using VADER – Part I | ||
| Building a Sentiment Analyzer using VADER – Part II | ||
| Machine Learning Based Sentiment Analysis | ||
| ML Feature Matrix & TF-IDF Introduction | ||
| Building ML Based Sentiment Analyzer – Part I | ||
| Building a ML Based Sentiment Analyzer – Part II | ||
| Building a ML Based Sentiment Analyzer – Part III | ||
| Sentiment Analysis Application – Opportunities & Challenges | ||
| 12. | Archived Lectures (02 hours 00 minutes) | Archived Lectures – Important Note |
| Pandas Datareader Overview | ||
| Getting Data Using Pandas Datareader | ||
| OBV Overview and Excel Implementation | ||
| OBV Implementation in Python | ||
| Slope in a Chart | ||
| Slope Implementation in Python | ||
| Web Scraping Intro | ||
| Important Note – Yahoo Finance Web Scraping | ||
| Using Web Scraping to Extract Stock Fundamental Data – I | ||
| Using Web Scraping to Extract Stock Fundamental Data – II | ||
| Updated Web-Scraping Code – Yahoo-Finance Webpage Changes |
Resources Required
- Python proficiency at the intermediate level
- Knowledge of mathematics and statistics at the high school level
- Basic knowledge in FX and stock trading
Featured Review
Vikram B G (5/5) : Awesome course for the people who are looking forward to understanding algorithmic trading. I was impressed with the way the course was designed starting from the basics of python to introducing the machine learning concepts in trading. I will try to build on the knowledge this course gave me and become a successful trader. And finally, thank you MAYANK
Pros
- Dan Treacher (5/5) : All the code is kept up to date, and the explanations are excellent.
- Federico Borin (5/5) : very happy about the clarity of the explanations and the recommended tools.
- Rahul Agarwal (5/5) : This Course is Great..and the Mayank has excellently explained each part.
- Charles Demontigny (5/5) : Very good course! It helps you create an end-to-end automated trading plateform.
Cons
- Kavan Motazedi (1/5) : The course is outdated and the code won’t work as it’s supposed to because of that, delivery is not good, and the instructor is also sniffing a lot.
- Tushar Dwivedi (2/5) : I have done at least 50+ courses on Udemy, and trust me, none of them had this issue.
- Sean Family (1/5) : The screen / board the instructor is using is extremely hard to see.
- Tushar Dwivedi (2/5) : It’s because you have used normal (even smaller) font size while capturing your screen with some software, which recorded video in really terrible resolution, even if it claims 1080p.
About the Author
The instructor of this course is Mayank Rasu who is a Experienced Quant Researcher and Educator. With 4.6 Instructor Rating and 7,092 Reviews on Udemy, Instructor offers 9 Courses and has taught 47,544 Students so far.
- Mayank Rasu has written and released best-selling courses and books on technology and money
- He is passionate about making seemingly hard subjects like algorithmic trading, machine learning, and artificial intelligence understandable to students with no expertise in technology or finance
- In the fields of quantitative analysis and risk management, he has more than ten years of experience working with major international investment banks
- Mayank Rasu’s professional experience has solidified his conviction that he should constantly consider the qualitative parts of his work when making data-driven decisions
- Mayank Rasu studied engineering for his undergraduate degree and have an MBA and MFE
- Mayank Rasu consider himself to be a lifelong learner, and he greatly value the chance to impart his knowledge to others
Comparison Table
| Parameters | Algorithmic Trading & Quantitative Analysis Using Python | Algorithmic Trading using Interactive Broker’s Python API | Quantitative Finance & Algorithmic Trading in Python |
|---|---|---|---|
| Offers | INR 499 ( | INR 455 ( | INR 455 ( |
| Duration | 19.5 hours | 12 hours | 15 hours |
| Rating | 4.5/5 | 4.6 /5 | 4.6 /5 |
| Student Enrollments | 28,792 | 7,321 | 12,410 |
| Instructors | Mayank Rasu | Mayank Rasu | Holczer Balazs |
| Register Here | Apply Now! | Apply Now! | Apply Now! |
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