Complete list
Buy the Rumour Sell the Event With Sentiment Analysis
Here, we see an interesting trading strategy that combines two elements: Buy the rumour sell the event, and sentiment analysis. If these sound like jargon to you, don’t worry – we're here to break it down in simple terms.
You will learn about the “Buy the Rumour Sell the event” strategy; you will understand the concept of sentiment analysis for trading and how we can combine the strategy with sentiment analysis. We backtested the buy the rumour sell the event with sentiment analysis strategy on Apple stock, and these were the results:
Strategy Performance
It is important to note that backtesting results do not guarantee future performance. The presented strategy results are intended solely for educational purposes and should not be interpreted as investment advice. A comprehensive evaluation of the strategy across multiple parameters is necessary to assess its effectiveness.
All the concepts covered in this post are taken from the Quantra course on News Sentiment Trading Strategies. You can preview the concepts taught in this course by clicking on the free preview button and going to Section 17 and Unit 11 of the course.
Note: The links in this tutorial will be accessible only after logging into quantra.quantinsti.com
What Is Buy the Rumour Sell the Event Strategy?
Well, it's a strategy where traders capitalise on market speculation and anticipation before a significant event. Picture this: whispers and rumours circulating about a big announcement, earnings report, or some game-changing development. Traders jump in, riding the wave of anticipation, only to exit when the actual event occurs and the market adjusts.
Here's a breakdown of the strategy:
Buy the Rumour:
- Traders identify a rumour or speculation that suggests a particular event or development is likely to occur in the future.
- Anticipating that the event will have a positive or negative impact on the price of a financial asset (such as a stock), they take a position in that asset.
Sell the Event:
- As the anticipated event approaches or takes place, the market reacts, and the price of the asset may change in response to the speculation.
- Once the event happens, traders may start to take profits by exiting their positions.
What Is Sentiment Analysis?
It's like reading the collective mood of the market. Think of it as the market's emotional barometer, giving you insights into whether traders are feeling positive (bullish) or negative (bearish) about a particular asset or the market in general.
Now, how do we tap into this collective mood swing? Sentiment analysis in trading harnesses the power of natural language processing and machine learning to sift through this vast ocean of data.
Take news, for instance. Positive news about a company's earnings or a breakthrough innovation can set a positive tone. On the flip side, negative news like regulatory issues or a slump in sales can cast a shadow. Sentiment analysis algorithms can scan through news articles, assigning a positive, negative, or neutral score to each piece, giving you a sense of the overall sentiment.
How to Perform Sentiment Analysis?
There are various approaches to perform sentiment analysis for trading like VADER (Valence Aware Dictionary and sEntiment Reasoner), Natural Language Processing (NLP), and Large Language Models (LLM).
- VADER: It is a rule-based sentiment analysis tool that uses a pre-built lexicon (dictionary) that assigns sentiment scores to words. Each word is given a polarity score (positive, negative, or neutral), and these scores are combined to calculate the overall sentiment of a sentence or document.
- NLP: NLP involves the use of computational models and algorithms to understand and interpret human language. NLP models learn patterns and relationships between words and sentiments during training and can then predict sentiment in new, unseen text.
- LLM: Language models are large-scale models pre-trained on vast amounts of diverse text data, enabling them to understand and generate human-like language. LLMs can be fine-tuned for sentiment analysis tasks. During fine-tuning, the model learns to associate input text with sentiment labels. The pre-trained knowledge helps the model capture the context, dependencies, and semantics of language.
The sentiment scores for the news headlines calculated using the above methods would look something like this:
|
Headline |
Sentiment Score |
|
Why Apple Stock Is Trading Lower Today |
-0.516 |
|
Apple Has 'Flex The Muscles Moment' With iPhone 15 |
0.762 |
|
Apple Event Fails To Impress Bulls |
-0.254 |
A positive score indicates a bullish sentiment, while a negative score indicates a bearish sentiment.
Buy the Rumour Sell the Event With Sentiment Analysis
Let’s say that there is an upcoming Apple event in a few days, and there are rumours that the company is about to announce record-breaking quarterly earnings. How can we take advantage of this? A sample strategy to trade this information can be:
Entry:
- Check if the current date is within 9 trading days before the event. If yes, then calculate the average sentiment score for the last 20 calendar days.
- If the average sentiment score is more than 0, which means that there is a positive sentiment, you would go long on Apple.
Exit:
There are two exit conditions:
- Exit the trade if the average sentiment score falls below 0 anytime after taking a long position.
- Exit on the day prior to the event.
In the above strategy, we are taking an average sentiment score for the last 20 days. This number is chosen arbitrarily. You can choose any other number of trading days for calculating the average sentiment score as per your preference.
In the above strategy, we are trading within 9 days before the event. But how do you decide this number? You can check the cumulative returns for various numbers of days over a historical period and see which number of days gives better returns.
Strategy Performance
It is important to note that backtesting results do not guarantee future performance. The presented strategy results are intended solely for educational purposes and should not be interpreted as investment advice. A comprehensive evaluation of the strategy across multiple parameters is necessary to assess its effectiveness.
The backtesting of buy the rumour sell the event with sentiment analysis strategy has been covered in detail along with the Python code in this unit of the News Sentiment Trading Strategies course. You need to take a Free Preview of the course by clicking on the green-coloured Free Preview button on the right corner of the screen next to the FAQs tab and go to Section 17 and Unit 11 of the course.
What to do next?
- Go to this course
- Click on
- Go through 10-15% of course content
Drop us your comments and queries on the community
IMPORTANT DISCLAIMER: This email is for educational purposes only and is not a solicitation or recommendation to buy or sell any securities. Investing in financial markets involves risks and you should seek the advice of a licensed financial advisor before making any investment decisions. Your investment decisions are solely your responsibility. The information provided is based on publicly available data and our own analysis, and we do not guarantee its accuracy or completeness. By no means is this communication sent as the licensed equity analysts or financial advisors and it should not be construed as professional advice or a recommendation to buy or sell any securities or any other kind of asset.
