NFT pazarının tanımlayıcı ve tahmine dayalı analizi

Non-fungible tokens (NFTs) are digital assets on a blockchain that have unique identi- fication codes and metadata that make them distinguishable from one another. NFTs can represent a wide range of digital assets, including game cards, artwork, and even real estate. Due to these characteristics, NFTs have gained a tremendous interest from people around the world, leading to huge returns on investment in the NFT market. However, there are only a few studies on the market in the literature. This paper examines various aspects of the NFT market to shed light on its dy- namics and wallet behaviors. First, a descriptive analysis of the market is performed to show its overall trend. The transactional behaviors of wallets are then analyzed, and a segmentation is made to gain a general understanding of the user portfolio. The buyers of a specific NFT collection (Bored Ape Yacht Club) are then studied by comparing them to the overall market, revealing differences in transactional tenden- cies and macro indicators. Finally, machine learning models are developed to predict the transactional behaviors of wallets. Our analysis has revealed that the growth of the NFT market is largely driven by new entrants to the market, but lately there has been a significant decrease in the number of new wallets entering the market. We have also found that the majority of wallets in the market have only one transaction and hold only one token, suggesting that these are users who are experimenting with the market. When we look at the Bored Ape Yacht Club sample, however, we see that these users are highly engaged with the market, with high trading frequencies and a diverse portfolio. Finally, our predictive models show that the transactional behaviors of wallets can be predicted, which opens up opportunities for optimization in various areas.