As traditional markets like equities continue to be influenced by various factors, crypto markets...
The world of cryptocurrency has witnessed extraordinary growth and attention this year, with Bitcoin posting a staggering 150%+ year-to-date return. As digital assets continue to gain popularity, a fascinating relationship has emerged between Twitter mentions and subsequent cryptocurrency stock prices. In this blog, we delve into the intricate details of this correlation and highlight the SV-Score—a standardized volume metric that plays a pivotal role in unraveling the dynamics between social media buzz and market movements.
The SV-Score, or Standardized Volume Score, is one of the many patented S-Factors offered by Context Analytics. This is a metric that gauges the level of social media attention a cryptocurrency receives on Twitter. Calculated by normalizing the number of mentions in the past 24 hours over the preceding 20 days for each coin, this score follows a normal distribution, allowing for a standardized comparison across different cryptocurrencies.
Our research methodology involves daily data collection, where we pull information on the top 100 market cap coins at the 23:59 timestamp. These coins represent the most liquid and commonly traded assets in the market. To analyze the impact of the SV-Score on subsequent asset prices, we categorize the top 100 coins into three groups, or tertiles, based on their SV-Score.
Dividing the top 100 coins daily into the following groups:
Tertile 1 (Low SV-Score): Coins with the least mentions relative to their normal volume.
Tertile 2 (Neutral SV-Score): Coins with normal levels of mentions relative to their normal volume.
Tertile 3 (High SV-Score): Coins with the highest mentions relative to their normal volume.
We traded with these portfolios for the previous 4 months by calculating equally weighted daily returns from coins within each portfolio. We compounded these returns through this time.
Over the past four months, our study reveals a compelling correlation between the SV-Score tertiles and subsequent cryptocurrency returns. The top tertile, comprising the most mentioned coins on Twitter, consistently outperforms the other groups. On the flip side, the bottom tertile, representing the least mentioned coins, lags below. The cumulative return for the top tertile exceeds that of the other groups, indicating a positive relationship between social media buzz and subsequent coin performance. The annualized return shows a similar pattern, with the top tertile consistently delivering superior results over the studied timeframe. Our analysis also displays a correlation between risk metrics and the SV-Score tertiles, further validating the impact of social media attention on market dynamics. Intriguingly, our study not only reveals the correlation between the SV-Score tertiles and subsequent returns but also showcases the ability of this strategy to outperform Bitcoin over the studied period. Despite Bitcoin’s impressive recent success, the top tertile, driven by heightened Twitter mentions, manages to surpass the performance of the highest market capitalization coin.
In conclusion, our research provides compelling evidence that the SV-Score of high-market-cap coins is correlated with subsequent coin movements. The top tertile, fueled by an influx of relative Twitter mentions, emerges as the standout performer, suggesting that in the world of cryptocurrency, no publicity on Twitter might indeed be bad publicity. As investors navigate this volatile market, understanding the role of social media in influencing price action becomes increasingly crucial. The SV-Score offers a valuable tool for market participants seeking to capitalize on the connection between online chatter and cryptocurrency returns. For more information on how sentiment from Context Analytics can be leveraged in the crypto world, click the button below or visit our website and schedule a meeting at www.contextanalytics-ai.com .
