Great summary, surprising to see the volume of measurable wash trading is lower than I expected. Hermes_Corp raised some excellent points on the potential methodological pitfalls of the author’s approach, I agree that there is more to be learned on the practice through better knowledge of wash trading patterns in NFT markets.
One question I’m left with is how much overall impact these wash trades have on the market, beyond the individual transaction. For example, in collections that have received more wash trading, does the price effect extend to other NFTs that were not wash traded?
In other words, because of high psychological association between NFTs in a collection, is the effect more similar to “painting the tape” than wash trading alone? In that case, how does the effect impact the overall profit extraction of an identified wash trader in the dataset? Others have pointed out floor price manipulation, which seems like a highly relevant factor when considering the overall prevalence and impact of price manipulation tactics on the market.
I think it would be interesting to see this data categorized in terms of profit extraction (i.e closed loop trades ending with an external sale) and not just trading volume, in order to see how these trades distort the market. Given the large degree of inequality between the profitability of NFT traders, even a low relative percentage of manipulated trades may be responsible for an outsized degree of extraction from market participants.