Working Paper: NBER ID: w31498
Authors: Dong Huang; William N. Goetzmann
Abstract: 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.
Keywords: NFT; selection neglect; behavioral finance; extrapolative beliefs; market bubble
JEL Codes: G1; G12; G14; G4; G40; G41
Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.
| Cause | Effect |
|---|---|
| macroeconomic shocks (F41) | rising prices (P22) |
| extrapolative beliefs (D84) | rising prices (P22) |
| selection neglect (C52) | optimistic beliefs (D84) |
| selection neglect (C52) | trading behavior (G41) |
| loss aversion (G41) | biased pricing (D40) |
| biased pricing (D40) | delayed market corrections (G14) |
| investor sophistication (G11) | less selection bias (C34) |
| investor sophistication (G11) | market performance (G14) |