Digital Art Index

The Digital Art Index (DAI) uses Hedonic regression models and discounting characteristics of NFT artwork in order to show the fundamental market movements of the NFT art market


Rise of NFT Art Sales and DAI:

Around the middle of 2020, NFT art sales surged, leading to the emergence of the Digital Art Index (DAI) in late 2020.

By mid-2021, DAI began to overshadow other art markets, indicating its growing prominence. After the midpoint of 2021, DAI has experienced sporadic spikes.

Despite the overall rise in NFT art sales, this did not directly correlate with market performance in terms of price or return.

Click on the Quantlet logo to see the code behind DAI

Click the Quantinar logo to learn more about DAI and NFT’s


What are NFTs? NFTs are digital tokens that provide proof of ownership and authenticity for assets.

What do they change? They bring a new and fast way of digital art trading, see for example collections such as CryptoPunks, Art Blocks.

NFT Art Market

  • Initial sale and price are determined by the creator
  • Most trades occur on platforms such as Opensea or Rarible
  • Subsequent transactions are traceable

Conventional Art Market

  • Creators in traditional art markets rely on dealers/galleries for sales
  • Art pieces’ prices are determined through valuation and negotiation


Market size: Market capitalization reached $41 billion (2021), a 30% increase from the Year Before


NFT Art Market Surge and Decline:

The market experienced a significant surge during the COVID-19 pandemic in 2020, followed by a subsequent decline in the fourth quarter of 2021

Other Segments of the Art Market witnessed heightened sales activity amid the pandemic. As we can see in the image on the left, there is a visible contrast with the fluctuating trends in the NFT art market


Volatility of price indices for heterogeneous goods with applications to the fine art market (2015)

Journal of Applied Econometrics

Bocart, F. Y., & Hafner, C. M.

代 DAI Digital Art Index: A robust price index for heterogeneous digital assets(2022)

Available at SSRN 4279412.

Lin, M. B., Wang, B., Bocart, F., Hafner, C. M., & Härdle, W. K.

Economic activity and painting performance(2002)

Working paper, Stern School of Business, New York University.

Mei, J., & Moses, M.