Coining.ai

One of the newer players in the coin information ecosystem is coining.ai. Coining.ai is the product of three PHD’s in computer science from the University of Rochester. The Coining.ai (CA) system is comprised of several modules. The first section i want to discuss is the coining kit. It has some unique metrics worth your time as I describe below.

Coining kit is divided by the following areas:

  1. Coins
  2. Social
  3. Normalized Price
  4. Prospective Good Coins
  5. Prospective Alt Coins

Coins

The layout in the screen shot may remind you of other coin data sites but, is there a better way to represent coin data than in a table?  You can do the normal sorting of each field but let’s talk about the unique features.

Rank

Rank is not your normal run of the mill market cap sort. Instead it takes into account several factors; market cap, trading volume, and normalized price.

Normalized Price

This may be the most important factor here. Bitcoin has a limited supply of 21mm units. To get  a coins comparative value they take the market cap and spread (divide) it across the total supply of bitcoin which is 21 million. This compresses the market cap of an alt coin (usually billions of units) into bitcoins units (21 million). What you realize is if alt coins had the same total supply as BTC then you can draw further comparisons from things being the same unit size. It was critical for me to suspend my total supply arguments for this exercise to dive a little deeper.

 

Lets just take one example: Dragon or DRGN

  1. Market Cap is: $240,503,364
  2. Total Supply is: 433,494,437 DRGN
  3. Price in USD as of May 6th. 2018: $1.00

We can infer a few things here. The market cap on some exchanges is only based on circulating supply which seems to miss almost 200BB of coins in the case of DRGN.

Now, lets take the total supply market cap (433,494,437 x $1.00 = $433,494,437) . Now the market cap is much larger than the market cap displayed on many coin data sites. 

$433,494,437 (total MC) > $240,503,364 (circulating MC)

$433,494,437 (total MC) – $240,503,364 (circulating MC) = $192,991,073 (non circulating MC)

Now we have the total market cap, not the circulating market cap.  My gut here is this number is more relevant in terms of long term holds. The gap between the two numbers ($192,991,073) could also have a significant impact on a coins per unit value if a large amount  were to be released into the market suddenly. 

I digress, now taking the total market cap of $433,494,437 and fitting into BTC’s total supply number of 21,000,00. 

$433,494,437 / 21,000,000 = $20.64…

BTC at this time: $9,637.09

A few things I can take away from all of this. Normalized price only starts to make sense in the context of a sort column. That is where coining.ai really starts to shine. Although, dragon isn’t on the list  of high to low, we can see some things that jump out. Namely three coins in particular,  E-dinar, Solar Coin, and Veritaseum.

 

Rank

The normalized price can take on more context when we look at the rank column. Coins that are overvalued then start to appear with a negative rating. Conversely we should start to see coins that are undervalued when sorting from high to low as captured below:

 

 

Volume%

Lastly the other impact column is volume. Everything is based on BTC. So BTC volume is considered 100%. Everything then is a percentage of BTC’s volume to tell who the movers are. Price action tells part of the story but the volume lets us know where the big money has been and to act accordingly. Of note at the screen shot below is TrueChain, apparently the whales have been active…

 

For a more thorough description of how this metric operates you can see that here

For a very nice google spreadsheet on the topic of normalized price that can be seen here