MarketPsych Analytics for Cryptocurrencies

Using a patented natural language processing engine, MarketPsych Analytics transforms unstructured text from thousands of curated news and social media sources into structured scores for over 1,000 cryptocurrencies. The data dates back to 2009, is point-in-time, and covers 28 languages. It has been cited in over 100 academic papers on cryptocurrencies:

“Our findings indicate that social media sentiment significantly predicts crypto returns…”
~ Canayaz, Cao, Nguyen, and Wang.

The data is published in minutely, hourly, and daily frequencies. It is ideal for quant trading, risk management, and display applications.

Detects and classifies over 4,000 crypto-relevant events (e.g., “fraud reported,” “code hacked,” “regulatory crackdown”).

The data is delivered via dashboard or API minutely (60-second), hourly, or daily.

4,000+ global sources scanned, with each score linked back to the original source reference.

Media types are processed independently, allowing users to track news and social media commentary separately.

Our NLP engine filters and scores relevant references to each asset. Data includes time-series of crypto-native themes that impact digital asset investors:

Quantitative research shows that sentiment drives cryptocurrency returns. In the example that follows, we select the top 10 cryptocurrencies by Buzz and rank them by their average social media sentiment over the prior 30 days. The strategy then buys the two most positively perceived cryptocurrencies and holds them over the following month. In the equity curve plot, we assume no transaction costs, and the blue equity curve depicts the growth of $1 invested in these top two cryptocurrencies by sentiment while the orange line depicts the growth of $1 invested in Bitcoin over the same period.

Identify trending cryptocurrencies and uncover insights using our interactive heatmaps.

This sentiment data gives clients a unique edge:

- Quant Trading: Deploy AI and machine learning strategies to anticipate swings in sentiment

- Risk Management: Hedge positions as investor enthusiasm wanes, project perceptions shift, or threats increase

Academic and internal research, including Python notebooks, is available with a trial or subscription.

Media sentiment often leads prices at major turning points. Sentiment moving averages help identify tops and bottoms, improving timing for risk-on/risk-off decisions.

Engaging tools and graphics – shown here from the WebApp – provide clients with actionable insights, such as the top Sentiment cryptocurrencies in the Screener depicted below.

- Investment Research & Idea Generation: Identify trending coins and innovative technologies early

- Display: Brokerages and websites allow users to explore and research the data via widgets

Free trials available. Contact us at: [email protected]