Selection-Neglect in the NFT Bubble / Dong Huang, William N. Goetzmann.

Format:

Book

Author/Creator:

Huang, Dong.

Contributor:

National Bureau of Economic Research.

Goetzmann, William N.

Series:

Working Paper Series (National Bureau of Economic Research) no. w31498.

NBER working paper series no. w31498

Language:

English

Physical Description:

1 online resource: illustrations (black and white);

Place of Publication:

Cambridge, Mass. National Bureau of Economic Research 2023.

Summary:

Using transaction data from a large non-fungible token (NFT) trading platform, this paper examines how the behavioral bias of selection-neglect interacts with extrapolative beliefs, accelerating the boom and delaying the crash in the recent NFT bubble. We show that the price-volume relationship is consistent with extrapolative beliefs about increasing prices which were plausibly triggered by a macroeconomic shock. We test the hypothesis that agents prone to selection-neglect formed even more optimistic beliefs and traded more aggressively than their counterparts during the boom. When liquidity for NFTs declined, observed NFT prices were subject to severe selection bias due in part to seller loss aversion delaying the onset of the crash. Finally, we show that market participants with sophisticated bidding behavior were less subject to selection bias and performed better.

Notes:

Print version record

July 2023.