Art market information can be mined from historical data on trades of an artwork, if available. We assume a general setting in which artworks are created by artists while collectors can directly buy the artwork at the set price or make an offer (a bid) for it. Sold artworks remain tradable on the secondary market. The focus of our rating system is on artworks; different units like artists, collectors, and even entire galleries are collections of artworks and can be assessed in terms of the artworks they contain. In this setting, there are two major signals of market success for an artwork:

The method

We used the following metrics to assess the bid and sale history of an artwork:

For example, suppose the bid and sale history of an artwork is as follows:

  1. bid of 1 from A
  2. bid of 2 from B
  3. bid of 3 from A
  4. bid of 4 from B
  5. bid of 5 from C
  6. sale for 5 to C
  7. bid of 6 from A
  8. sale for 6 to A

Here, collector A is willing to pay 6 (their largest bid) for the artwork, collector B would pay 4, and collector C would spend 5. Hence, the sum of largest bids on the artwork is \(\beta = 6 + 4 + 5 = 15\) and represents a sort of open interest for the piece. The total number of bids is \(\gamma = 6\) and the number of different bidders is \(\delta = 3\) (A, B and C). The sum of all sales is \(\alpha = 5 + 6 = 11\).

We thus define an artwork rating \(\rho\) for an artwork \(t\) as a weighted average of the above four metrics after normalization:

\[ \rho(t) = \frac{1}{3} \cdot \frac{\alpha(t)}{\max(\alpha)} + \frac{1}{3} \cdot \frac{\beta(t)}{\max(\beta)} + \frac{1}{6} \cdot \frac{\gamma(t)}{\max(\gamma)} + \frac{1}{6} \cdot \frac{\delta(t)}{\max(\delta)} \]

Given a collection of artworks \(S\), we further define the cumulative rating \(\sigma\) of \(S\) as:

\[\sigma = \sum_{t \in S} \rho(t)\] and the average rating \(\mu\) of \(S\) as:

\[\mu = \frac{\sigma}{|S|}\] where \(|S|\) is the number of elements of \(S\). Notice that \(\sigma\) depends on the size of the collection \(S\) while \(\mu\) is size-independant.

An important caveat is how to assess the actual price of sales and bids. Since digital artworks are mainly traded in crypto currencies (mainly Ether, the coin of Ethereum blockchain), and these coins are not stable (they show large variance of the historical prices), we decided to use the price expressed in fiat money (dollars) at the exchange rate of the time of the bid or sale.

The rating method for artworks

We applied our method to the entire collection of SuperRare crypto art gallery (data from 5th April 2018 to 2nd November 2020). We first computed the artwork rating \(\rho\) for all artworks of the collection.

Top-20 artworks
rank name artist rating sale volume bid volume bids bidders id link
1 Rebirth of Venus NA 0.851 88085 305085 35 21 16297 click
2 AI Generated Nude Portrait #1 videodrome 0.592 123544 128735 13 10 1 click
3 The Innovator’s Dinner fewocious 0.521 0 175847 39 26 13670 click
4 AI Generated Nude Portrait #5 videodrome 0.440 122620 14663 10 8 65 click
5 AI Generated Nude Portrait #3 videodrome 0.430 101898 103053 4 4 3 click
6 Hurt Feelings fewocious 0.340 8834 54200 31 20 13907 click
7 Latent Space of Landscape Paintings #1 videodrome 0.322 798 130129 21 14 135 click
8 Elephant Dreams rac 0.312 25962 68554 20 13 14316 click
9 Möbius Knot pak 0.307 44352 102169 12 4 16428 click
10 shutdown –reboot NA 0.281 24529 68196 23 7 16647 click
11 AI Generated Nude Portrait #7 Frame #175 videodrome 0.279 4929 3361 32 20 365 click
12 CYBERSNEAKER rtfktstudios 0.271 11442 53936 28 10 14504 click
13 Dharma Dragon android_jones 0.234 21425 45401 15 10 14834 click
14 High Functioning killeracid 0.228 0 6129 27 17 47 click
15 AI Generated Nude Portrait #7 Frame #153 videodrome 0.228 2155 7780 39 8 343 click
16 “One of Us” Variation 1 mattkane 0.220 1464 3984 40 7 5051 click
17 UAP - Unidentified Art Phenomenon coldie 0.217 19138 50647 14 8 9343 click
18 DystoPunk 3D coldie 0.216 6505 33712 28 7 7168 click
19 The Frame pak 0.216 14577 57641 18 6 11958 click
20 Roarrr!! suryanto 0.215 5907 25062 29 8 16768 click

The rating method for artists

Then we assessed artists by the artworks they created. Here, we have two choices. We can assess an artist using the cumulative rating of all artworks tokenized by the artist. This choice, however, favors the most productive artists. Since tokenization is (almost) free when you are a white-listed artist on a gallery, we do not make this choice. The second possibility is to assess an artist using the mean of the ratings of all artworks they created. However, different artists create at different rates (there are artists that tokenize a new piece each day and others that mint one new artwork every month) and, moreover, they have different histories (some have long been active in the space while others just landed there). It turns out that the collections of artworks created by the artists are very heterogeneous in size. It is not statistically sound to compare means over samples of sizes that differ largely. Hence, we adopted a top-n-min-k approach. Given numbers \(k\) and \(n\) with \(k \geq n \geq 1\):

  1. we select only artists that created at least \(k\) pieces;
  2. for them we select the best \(n\) artworks according to the artwork rating \(\rho\);
  3. finally, we rate an artist using the mean rating of the \(n\) selected artworks.

A high value for \(n\) favors artists with a long activity history; on the other hand, a small value for \(n\) is inclusive with respect to artists with a short activity history, including emerging ones. We set \(n = k = 20\).

Top-20 artists that created at least 20 artworks
rank artist rating SuperRare OpenSea
1 videodrome 0.16023 click click
2 pak 0.15819 click click
3 hackatao 0.12173 click click
4 coldie 0.10124 click click
5 xcopy 0.10065 click click
6 twistedvacancyart 0.07987 click click
7 glasscrane 0.07905 click click
8 osinachi 0.07820 click click
9 alotta_money 0.07669 click click
10 jenisu 0.07319 click click
11 frenetikvoid 0.07235 click click
12 osiris 0.07175 click click
13 gric 0.07008 click click
14 missalsimpson 0.06871 click click
15 carlosmarcialt 0.06592 click click
16 mattkane 0.06502 click click
17 suryanto 0.06495 click click
18 goldweard 0.06347 click click
19 sveneberwein 0.06344 click click
20 _totemical 0.06192 click click

The rating method for collectors

We finally assessed collectors with the same method, considering the collection of artworks they acquired and setting \(n = k = 50\).

Top-20 collectors that collected at least 50 artworks
rank collector rating SuperRare OpenSea
1 thevault 0.08081 click click
2 moca 0.07945 click click
3 ethsquiat 0.07201 click click
4 moderats 0.07124 click click
5 maxstealth 0.06683 click click
6 basileus 0.06555 click click
7 gltr 0.05753 click click
8 tokenangels 0.05520 click click
9 randaartvault 0.05332 click click
10 0x123456789 0.05287 click click
11 coldie 0.05140 click click
12 matrix 0.05022 click click
13 blockchainbrett 0.05011 click click
14 momuscollection_sr 0.04886 click click
15 jedscryogenicstorage 0.04666 click click
16 bitbuzz 0.04553 click click
17 deej 0.04524 click click
18 mantaxrartvault 0.04320 click click
19 NA 0.04293 click click
20 zonted 0.04043 click click