New report, major update on short-term signal overview!

New report, major update on short-term signal overview!

The latest report introduces a major update on short-term signals!

This is request I received frequently from people using the regression tool, which offers more insight in shorter term movements in the crypto markets. The overview shows the top 5 increases and decreases of the following social media metrics:
• Largest increase/decrease in Twitter mentions
• Largest increase/decrease in Twitter Recipients
• Largest increase/decrease in Twitter Sentiment
• Largest increase/decrease in Reddit Subscribers
• Largest increase/decrease in Reddit Users Online
• Largest increase/decrease in Sentiment

Partial report is available below
20180210 Valuationreport_nc

Full report (15 EUR, new payment options added!)
https://sowl.co/X2iKs

New report and free Twitter implied market cap overview

New report and free Twitter implied market cap overview

A new report is available below. Also a (free) Twitter implied market capitalization overview is uploaded, of which the used metrics are part of the scorecard. This provides some intuition in to methodology used.

Partial report
20180124 Valuationreport_nc

Twitter implied market caps
Twitter Large account valuation

Full report (15 EUR, more payment options coming soon or send a mail to newsletter@altcoinanalytics.com to pay via crypto)
https://sowl.co/MN3Rl

Maybe unsurprisingly there is a clear relation between the number of Twitter (large account) mentions and market capitalization (see below for a scatter plot of all 200 top crypto currencies). For example, the number of mentions with respect to Bitcoin is about two times larger than Ethereum, whereas the market capitalization is also about twice as large. A regression shows that there is a clear linear relation for all cryptos. This relationship can be used to reverse engineer a hypothetical market cap (or price) based on a crypto’s Twitter mentions. Comparing this to the actual market cap then shows the deviation between actual value and hypothetical social media value.

Though there is obviously more to the value of a crypto than only its social media presence, it does offer some insight since there is clear linear relation.

The same logic is used for the scorecard, however there Z-scores are used to make differences more meaningful and make them more suitable for incorporating in the total scorecard. Also the applied metric (large account Twitter mentions) is only a small part of the overall score.