چکیده مقاله
Valuing non fungible tokens NFTs challenging due to their unique nature and the extreme volatility of NFT markets Conventional price prediction approaches often rely on static analyses that fail to capture and model the temporal dependencies inherent in market behavior This study addresses that research gap by introducing and evaluating dynamic models for NFT price prediction, using the Bored Ape Yacht Club BAYC collection as a case study Leveraging a comprehensive dataset that combines intrinsic token attributes, rarity scores, trade volumes, and prior sale prices, together with cryptocurrency market indicators Ethereum and Bitcoin represented as temporal features, we develop machine learning models that explicitly exploit temporal structures to forecast prices Using time series based machine learning models, we capture sequential market patterns and conduct out of sample forecasts Results show that the dynamic approach significantly outperforms static baselines, yielding prediction errors below 10% The findings underscore the necessity of incorporating temporal dynamics into NFT market analysis to achieve both higher predictive accuracy and deeper behavioral insights
کلیدواژهها
نویسندگان
Ali Fadaei Tafreshi
Master's degree graduate, Faculty of Industrial Engineering, Sharif University of Technology, Tehran, Islamic Republic of Iran
Maryam Rezapourniari
Assistant Professor, Faculty of Industrial Engineering, Sharif University of Technology, Tehran, Islamic Republic of Iran
Reza Amiryaghoubi
Master's degree graduate, Faculty of Industrial Engineering, Amirkabir University of Technology, Tehran, Islamic Republic of Iran
Ali Asadi
Master's degree graduate, Faculty of Industrial Engineering, Sharif University of Technology, Tehran, Islamic Republic of Iran
شیوه ارجاع
Fadaei Tafreshi, Ali and Rezapourniari, Maryam and Amiryaghoubi, Reza and Asadi, Ali,1404,Dynamic NFT Price Prediction: Incorporating Temporal Features into Machine Learning Models (BAYC Case Study),11th International Conference on Industrial and System Engineering,Mashhad
ارائهشده در
مجموعه مقالات یازدهمین کنفرانس بین المللی مهندسی صنایع و سیستم ها2 مهر 1404 · مشهد