Analytics and Valuation
We construct a number of related indices that provide additional characterization for the behavior of the NFT market. Our research shows that prices in the related markets (the crypto tokens and equities that are related to NFT) may correlate with the NFT indices [1,2,3]. Moreover, we show that measures of attention have proven to be important for the behavior of such markets [1,3,4,8].
We construct an AVM (automated valuation model) that optimally combines information from the BLT indices and machine learning techniques to generate updated high-precision and reliable valuations of individual NFTs and NFT collections.
Bored Ape Yacht Club valuation
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Cool Cats valuation
Clone X valuation
Mutant Ape Yacht Club valuation
Pudgy Penguins valuation
We provide core analytics for the NFT market following our research .
Volatility and the Sharpe ratio are the key characteristics of the risk/return tradeoff of an asset.
The index-to-transactions indicator is an important valuation ratio that also has significant predictive power in the time-series. [1,7 ]
Momentum/reversal statistics is a key property of the behavior of the NFT index over time (see, ) and a key component of its predictability and of the predictability of crypto tokens (see also, [2,3,4,8]).
We calculate the time-varying exposure of the NFT markets to the related markets: NFT coins and stocks. This is a version of the classic CAPM methodology.
Trading gap and the repeat sale volume are measures of liquidity and the depth of the market.
The correlation heatmap summarizes the correlation of the NFT market with a variety of other markets and indicators.