Applied Sentiment Analysis – Trading & Forecasting
Learn to develop and back-test sentiment and technical models to forecast the trend of assets with real applications.
Note: 4.4/5 (75 notes) 2,168 students
Instructor(s): Sofien KAABAR, CFA
Last update: 2022-03-06
What you’ll learn
- Understand the COT report and its strength in predicting the market’s trend.
- Understand basic concepts of Descriptive Statistics and their implications in trading.
- Learn how to develop and use a COT model from scratch.
- Learn how to analyze markets using Technical Analysis.
- Learn how to combine both types of analyses to produce robust forecasts.
- Back-test step-by-step the advanced strategies presented through Python.
- Learn about other sentiment indicators (ISM PMI, VIX, Put/Call ratio, etc) and back-test other strategies.
- Very basic knowledge of the financial markets (we will do a recap to refresh it, just in case).
- Some basic concepts of Technical Analysis (It’s covered in case you’re just getting started).
- Motivation and Willingness to experiment with data analysis in excel.
- Some knowledge in Python is desired but not crucial.
It’s time Market Sentiment analysis got a proper step-by-step guide. Why stick only with Technical and Fundamental Analysis when you are trading the markets? Adding this powerful tool to your arsenal will greatly enhance your skills and undoubtedly improve your risk-adjusted returns.
Whether you are just beginning or you’re already an experimented user of market sentiment analysis wanting to discover new techniques in this exciting field, then search no more! this course is for you.
It is specifically designed to guide you from A-Z with a focus on intermediate/advanced concepts that you will find very interesting through different applications and most importantly stepping-stones upon which you can build your super model and combine it with other promising types of analyses!
The CFTC publishes a goldmine every week, which is known as the Commitments of Traders Report – COT – that gauges the pulse and the feeling of the big market participants (i.e. the market movers).
Properly understanding and analyzing this report will allow the user to forecast the trend of the chosen asset (FX, equities, commodities) for the following days, weeks, and even months.
This course is split into 4 main parts:
1. Introduction to Market Sentiment.
2. Framework and COT Data Analysis.
3. Advanced Concepts & Back-testing through Python.
4. Other Sentiment Strategies (Put-call ratio, Dark pool index, Gamma exposure index, etc).
This is an APPLIED course, meaning we will not spend too much time with the boring theoretical albeit necessary stuff. There will be occasional notes for every major section to help you refresh your knowledge as you progress in the course. I will constantly be updating the sections with new sentiment and technical methods / strategies. All of the documents and code are downloadable.
Disclaimer: We acknowledge that trading comes with risks, and therefore, we have to stress that success in this field comes with proper risk management. No model is perfect and the views expressed in this course are only based on market sentiment analysis and are for educational purposes only. Always do your homework and let no one affect your judgement unless objective data is presented.
If you have a question/complaint (or even two), you can contact me through the Q&A section.
Who this course is for
- Anyone wanting to discover how to analyze FX, equity, and commodities markets from a sentiment point of view.
- Professional and retail traders wanting to enlarge their toolkit.
- Long-term investors wanting to gauge the trends and the the pre-crisis periods.
- Researchers wanting to dive in deeper to develop more sophisticated sentiment models.
- Anyone curious about a lesser-known trading technique.
- INTRODUCTION TO MARKET SENTIMENT
- Getting Started
- The Different Types of Analyses
- Economic Intuition 101
- Conflicts & Model’s Choice Dilemma
- Important: Read FIRST
- Intuition of Market Sentiment
- Our Approach
- Downloading the COT Data Step-by-Step
- Handling the COT Charts
- Open Interest & Spreads
- Notes – Part 1 Recap
- FRAMEWORK AND DATA ANALYSIS
- Part 2: Quick Snapshot
- Introduction to Descriptive Statistics
- EURUSD Statistical Analysis Template
- The 3 Golden Rules
- How to get the Commodities’ COT values
- Application – Crude Oil
- Introduction to Behavioral Finance
- Behavioral Finance Extra Notes
- Notes – Part 2 Recap
- ADVANCED CONCEPTS & BACK-TESTING THROUGH PYTHON
- Part 3: Quick Snapshot
- Correlation Analysis
- Commercial Consumers | Soybeans
- Commercial Producers | USDCAD
- Other COT Components
- Cross Asset COT Technique
- Downloading Anaconda
- Getting Familiar with SPYDER
- Numpy and Pandas basics
- Performance Evaluation
- Strategy 1: Fixed-Barrier COT Back-testing
- Strategy 2: Variable-Barrier COT Back-testing
- COT Delta Intuition
- Application – Gold
- Strategy 3: COT Delta Back-testing
- Normalization Intuition
- Strategy 4: Normalization Back-testing
- Equity Sentiment COT
- COT | RSI Intuition
- Strategy 5: COT | RSI Silver
- Beware of Technical Analysis Traps: Back-testing the RSI
- Combining Technical & Sentiment Analysis
- Notes – Part 3 Recap
- OTHER SENTIMENT STRATEGIES
- Part 4: Quick Snapshot
- Downloading the GEX/DPI Data Step-By-Step
- Back-testing the GEX/DPI
- UMCSI – Intuition
- Application – Dollar Index
- ISM – Purchasing Manager’s Index
- Downloading the Put-Call ratio Data Step-By-Step
- Back-testing the Put-Call Ratio
- The VIX from another perspective
- A Discussion on Discretionary Trading
- Part 1 Documents
- Part 2 Documents
- Part 3 Documents
- Part 4 Documents
- UPDATE: New Put-Call Ratio Data
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