Sentiment Arbitrage

Written By

Dan Buckley

Updated

Jun 3, 2024

Sentiment arbitrage is a trading strategy that exploits the difference in market sentiment between various groups of traders/investors, typically retail and professional traders.

By analyzing and predicting the sentiment, traders can decisions to capitalize on any discrepancies in market perceptions.

The wider the divergence, potentially the greater the opportunity.

Key Takeaways – Sentiment Arbitrage

Definition and Strategy

Sentiment arbitrage is a trading strategy that exploits the differences in market sentiment between retail and professional traders by analyzing and predicting sentiment to capitalize on market perception discrepancies.

Retail vs. Professional Sentiment

Retail traders often exhibit volatile and reactive sentiment influenced by news and social media, while professional traders rely far more on data-driven analysis, leading to more stable sentiment.

Implementation and Examples

Sentiment arbitrage involves:

collecting sentiment data

analyzing discrepancies, and

executing trades based on significant differences

This includes shorting stocks with overly bullish retail sentiment versus bearish professional sentiment, or buying stocks with overly bearish retail sentiment versus bullish professional sentiment.

Often Part of a Broader Strategy

Some traders might weight retail vs. institutional sentiment in their process, but it won’t be the whole strategy.

Understanding Sentiment

Sentiment refers to the overall attitude of investors towards a particular security or the market as a whole.

It is typically measured as bullish (positive) or bearish (negative) sentiment.

Retail vs. Professional Traders

Retail Traders

Retail traders are individual traders/investors who trade securities for personal accounts.

Their sentiment is often influenced by news, social media, and market trends.

Retail sentiment can be more volatile and reactive compared to professional traders.

Markets that have more retail presence tend to be more momentum-driven.

This is, for example, why the price dynamics of China’s stock market is momentum-driven compared to that of the US (where there’s more institutional ownership).

Professional Traders

Professional traders, such as hedge funds and institutional investors, have access to advanced software, extensive research, and market insights.

Their sentiment is typically more stable and based on analysis and data.

Sentiment Discrepancies

Why Sentiment Differs

Retail and professional traders often have different sources of information and levels of expertise.

Retail traders might follow popular trends and news, which can lead to herd behavior.

Professional traders rely on in-depth research and sophisticated models.

This divergence creates opportunities for sentiment arbitrage.

Exploiting Sentiment Discrepancies

By identifying when retail traders are overly optimistic or pessimistic compared to professional traders, sentiment arbitrageurs can take positions that benefit from the expected market correction.

For example, if retail sentiment is overly bullish while professional sentiment is bearish, an arbitrageur might short the security expecting a price drop.

Measuring Sentiment

Sentiment Analysis Tools

Sentiment analysis involves using tools and algorithms to gauge the market mood.

These tools analyze data from various sources, including news articles, social media posts, trading volumes, and price movements.

This is commonly done via some type of Natural Language Processing (NLP) algo.

Other sentiment indicators, such as the Bullish Percent Index (BPI) or the Fear and Greed Index, help in determining market sentiment.

Surveys are also commonly used, believing that what people think now could determine how things could be in the future.

Sources of Sentiment Data

Social Media and Forums

Platforms like Twitter, Reddit, and financial forums can be rich sources of retail sentiment.

Analyzing posts and discussions can provide insights into the prevailing mood among retail traders.

News and Media Analysis

Professional traders often rely on news outlets, financial reports, and economic indicators.

Sentiment analysis tools can process this information to derive sentiment scores for different securities or the market in general.

Comparing Sentiments

To perform sentiment arbitrage, traders compare sentiment data from retail sources with professional sentiment indicators.

Discrepancies between these data sets highlight potential arbitrage opportunities.

Implementing Sentiment Arbitrage

Steps to Follow

Data Collection – Gather sentiment data from both retail and professional sources.
Sentiment Analysis – Use NLP or other sentiment analysis tools to process and quantify the sentiment.
Identify Discrepancies – Compare the sentiment scores to identify significant differences.
Trade Execution – Develop and execute a trading strategy based on the identified sentiment discrepancies.

Risks and Considerations

Market Volatility – Sentiment can change quickly, and arbitrage strategies must be agile to adapt to these changes.
Data Accuracy – The quality of sentiment analysis depends on the accuracy and relevance of the data.
Behavioral Biases – Understanding the psychological factors influencing both retail and professional traders is important.

Systematically analyzing and exploiting the differences in sentiment between retail and professional traders can be a profitable strategy, but it requires some way to accurately determine the sentiment and some way to take advantage of it.

Let’s look at some trades involving sentiment arbitrage.

Example 1: Overly Bullish Retail Sentiment vs. Bearish Professional Sentiment

Scenario

Let’s say that retail sentiment is extremely bullish on a particular stock, XYZ Corp, driven by positive news and social media hype (e.g., lots of promises made by management of new innovation coming shortly).

But… professional sentiment is bearish, supported by fundamental analysis indicating that the stock is overvalued and in conjunction with subject matter experts harboring strong reservations about all the promises being made.

Trade Setup

Data Collection: Gather sentiment data:

Retail sentiment – Use social media monitoring tools (e.g., Twitter sentiment analysis, Reddit discussions) showing 80% positive mentions about XYZ Corp.
Professional sentiment – Analyze reports from institutional investors, hedge funds, and sentiment indicators showing 70% negative outlook.

Sentiment Analysis: Quantify the sentiment:

Let’s say it’s on a scale from -100 (very negative) to +100 (very bullish).

Retail sentiment score = +80
Professional sentiment score = -70

Identify Discrepancies: Note the significant discrepancy between retail and professional sentiments.

Trade Execution:

Short XYZ Corp stock based on the expectation that the price will drop as the hype dies down.

Trade Details

Stock: XYZ Corp
Short Position: 1,000 shares
Current Price: $50 per share
Short Sell Amount: 1,000 shares * $50 = $50,000
Stop Loss: Set at $60 per share (to limit potential losses) or buy a 55 call to protect against upside
Take Profit: Set at $30 per share (expected price drop)

Example 2: Overly Bearish Retail Sentiment vs. Bullish Professional Sentiment

Scenario

Let’s say that retail sentiment is very bearish on a particular stock, ABC Inc., due to recent bad press and negative social media trends.

However, professional sentiment is bullish, backed by strong growth prospects that aren’t widely perceived.

Trade Setup

Data Collection: Gather sentiment data:

Retail sentiment – Monitor forums and social media showing 75% negative mentions about ABC Inc.
Professional sentiment – Review analyst reports and institutional sentiment showing 65% positive outlook.

Sentiment Analysis: Quantify the sentiment:

Retail sentiment score = -75
Professional sentiment score = +65

Identify Discrepancies: Note the significant discrepancy between retail and professional sentiments.

Trade Execution:

Buy ABC Inc. stock based on the expectation that the price will rise as fundamentals win out.

Trade Details

Stock: ABC Inc.
Long Position: 1,500 shares
Current Price: $30 per share
Purchase Amount: 1,500 shares * $30 = $45,000
Stop Loss: Set at $25 per share (to limit potential losses)
Take Profit: Set at $40 per share (expected price rise)

Step-by-Step Process

Step 1: Data Collection

Use sentiment analysis tools to gather data from social media, forums, news outlets, and institutional reports.
Example – Use tools like Brandwatch, Sentiment.io, or custom algorithms to quantify sentiment scores.

Step 2: Sentiment Analysis

Calculate the sentiment score for both retail and professional traders.
Example – Aggregate the percentage of positive vs. negative mentions and convert them into a sentiment score.

Step 3: Identify Discrepancies

Compare the sentiment scores to identify significant differences indicating potential arbitrage opportunities.

Step 4: Trade Execution

Determine the trade direction (long or short) based on the sentiment discrepancy.
Place the trade using a brokerage platform with specified amounts, stop loss, and take profit levels.

Step 5: Monitoring and Adjustment

Continue to monitor the sentiment and overall market for its securities.
Adjust stop loss and take profit levels as necessary to manage risk and maximize returns.

Through these steps, sentiment arbitrage can be more systematically executed to exploit discrepancies between retail and professional trader sentiments.

FAQ – Sentiment Arbitrage

Does sentiment arbitrage always mean following the “smart money”?

Sentiment arbitrage doesn’t always mean strictly following the “smart money” (institutional traders/investors), although institutional money is generally more informed due to access to advanced software, research, and market insights that give an informational and analytical advantage.

Institutional investors often base their sentiment on analysis and data, making their sentiment typically more stable and reliable.

Nonetheless, retail momentum can be important, especially in the short term.

Retail traders, influenced by news, social media, and market trends, can drive significant price movements through collective actions, sometimes leading to dramatic short-term price spikes.

This was evident in cases like GameStop (GME), AMC Theaters (AMC), and Tesla (TSLA), where retail traders heavily influenced the stock prices.

For instance, the surge in GME and AMC stocks in early 2021 was largely driven by retail traders on platforms like Reddit, leading to rapid, large price increases. The stocks had relatively low market caps, which made them more susceptible to short squeezes higher.

Similarly, Tesla’s stock experienced significant volatility and rapid price growth fueled by retail enthusiasm and media coverage.

These stocks didn’t maintain their elevated prices in the long term, but the power of retail sentiment was undeniable on the way up.

Accordingly, sentiment arbitrageurs need to consider both institutional sentiment for long-term stability and retail sentiment for short-term opportunities.

Balancing these perspectives allows traders to exploit market discrepancies effectively – i.e., capitalizing on both informed institutional positions and the potent, albeit sometimes fleeting, influence of retail momentum.