NFT market manipulation is bigger than its famous member. Wash trading gets the headlines, and my paper measures it directly, but thin bilateral markets with public tapes invite a whole repertoire of moves. This page is the field taxonomy: each technique, the economics that make it work, and the evidence trail it leaves.
1. Wash trading
Self-dealing to manufacture activity, either to advertise a collection or to farm rewards that pay per unit of volume. The evidence says the second motive dominated in NFT markets: fake volume tracked trade-to-earn incentives rather than luring genuine buyers. Start with the explainer, the NFT-specific data, and the LooksRare case study.
2. Floor price management
A collection's floor, its cheapest live listing, is its de facto price. Managing it is cheap in both directions: delist or self-buy the cheapest items to raise it, or cascade low listings to crush it before accumulating. Because a single actor can hold many tokens in a thin collection, the floor is closer to a poster than a price. Watch the custody chains of floor-setting listings; round trips back to funding parents give the game away.
3. Bid supports and phantom depth
Standing bids just under the floor simulate demand depth, reassuring buyers that exit liquidity exists. When the bids are the seller's own capital, the support is decoration that can vanish the moment it is tested. The equity-market ancestor is layering; the NFT version is cruder because identities are free.
4. Sweep-and-relist momentum games
Buying a visible tranche of a collection in one transaction, the sweep, prints a burst of volume and social proof, often amplified by trackers that broadcast whale activity. The manipulator relists into the attention. Distinguishing genuine conviction sweeps from theatre requires the funding and disposal analysis covered on the detection page.
5. Insider activity
Trading ahead of non-public information: upcoming marketplace features, collection listings, reveal outcomes. The best-known enforcement in the sector involved front-running featured placements on a major marketplace, charged as wire fraud, which matters legally: fraud theories do not wait for asset-classification debates, as the legality page explains.
Why the taxonomy matters
Each technique corrupts a different signal: wash trading corrupts volume, floor games corrupt price, bid supports corrupt depth, sweeps corrupt flow, insiders corrupt information itself. Defences follow the same map. Statistics that resist self-dealing, covered under fake trading volume, neutralise the first two. Funding-graph surveillance handles the middle. Only governance fixes the last. The general lesson from the research is unglamorous: markets get the integrity their measurement and incentive design pay for, and NFT markets paid for very little of it in their formative years.