This challenge was inspired by the online art platform DADA. DADA is an online place where people around the world create spontaneous visual conversations together, in spite of language, distance, nationality, or other artificial boundaries. On DADA, art is a means of communication, and its creative and collaborative nature fosters strong bonds between people. It’s a free and liberating experience. Trolling and bullying are organically neutralized. It is a place where strangers make art together without expecting remuneration, motivated not by extrinsic rewards like money or status but by intrinsic rewards such as the joy of making art, and a sense of autonomy, validation, self-development, belonging and a higher purpose.

Currently, DADA is translating into practice the concept of Invisible Economy. The Invisible Economy is the radical separation of art and the market. Blockchain technology allows the economy to be both invisible and transparent. It is invisible because it separates art making, code writing, art collecting, and general contributions from market transactions through different mechanisms. And it is transparent because all the transactions take place on the Ethereum blockchain where everyone can track them.

In this challenge we assume a crypto art marketplace with the following price scheme:

We define:

All prices are defined in USD with ETH/USD change rate of the day of the sale.

The data challenge is the following. Use the SuperRare marketplace to analyse how the overall gallery volume splits into its two components (artist volume and collector volume) as of today, in the past and in the future. In particular:

Concentration of volume among sellers and buyers

Gini index typically measures the extent to which the distribution of income among individuals within an economy deviates from a perfectly equal distribution. A Lorenz curve plots the cumulative percentages of total income received against the cumulative percentage of number of recipients, starting with the richest individual. The Gini index measures the area between the Lorenz curve and a hypothetical line of absolute equality, expressed as a percentage of the maximum area under the line. Thus a Gini index of 0 represents perfect equality, while an index of 100 implies perfect inequality. See the country ranking by Gini index.

The sale volume, that is the sum of all sale prices in USD (excluding fees and royalties), amounts to $4,390,159. Here we applied the Gini index to the share of sale volume received by sellers or spent by buyers.

Artist and collector volumes today

As of today, the total gallery volume on SuperRare (primary and secondary sales) is $3,875,307. Of this:

The artists are the ones who make the magic happen, so be respectful to all SuperRare artists even if you are not a fan of their work. SuperRare Community Guidelines

Moreover:

In summary, collectors re-sell at 1.68 times the price they buy; however, they sell far less often than artists (every 100 pieces they buy, they resell only 17 of them).

We hence observe an artist dominance, where the the volume earned by artists is far bigger than that gained by collectors. Substantially, the secondary market is still underdeveloped and collectors buy to hold. Of course, if eventually collectors will have weaker hands and sell more pieces, since the re-sale price is generally higher, these figures might change in favor of collectors.

The temporal evolution of artist dominance

I expect that the situation is the past is even more skewed towards artists, meaning the artists are earning a higher share of the gallery volume and hence the artist dominance is higher. Let’s check!

The artist dominance (red line) was quite stable and above 90% until October 2019, when it started to decline in favor of a rise of the collector share. Assuming that this trend continues, when are the shares earned by artists and collector break even? Let’s fit a linear regression model!

Predicting the artist dominance

The linear regression model has time (number of months) as independent variable and the share of volume earned by collectors as response (dependent) variable. It predicts the following linear model (\(R^2\): 0.88, p-value: \(1.382 \cdot 10^{-6}\)):

\[ \mathrm{collector\ share} = 0.095697 + 0.012497 \cdot \mathrm{month} \]

This means that, according to the fitted model, every month the collector volume increases of 1.25%. Hence we can predict that the collector volume share will be 0.5 and hence equal to the artist volume share in about 32 months from October 2019, or in 19 months (1 year and 7 months) from now, that is June, 2022. Is this scaring?

What if scenarios

When is going to be the break even between artist and collector volumes if we increase the royalty percentage?

Summing up

Limitations and discussion