In this paper, we design and implement a web crawler system based on the Solana blockchain for the automated collection and analysis of market data for popular non-fungible tokens (NFTs) on the chain. Firstly, the basic information and transaction data of popular NFTs on the Solana chain are collected using the Selenium tool. Secondly, the transaction records of the Magic Eden trading market are thoroughly analyzed by combining them with the Scrapy framework to examine the price fluctuations and market trends of NFTs. In terms of data analysis, this paper employs time series analysis to examine the dynamics of the NFT market and seeks to identify potential price patterns. In addition, the risk and return of different NFTs are evaluated using the mean-variance optimization model, taking into account their characteristics, such as illiquidity and market volatility, to provide investors with data-driven portfolio recommendations. The experimental results show that the combination of crawler technology and financial analytics can effectively analyze NFT data on the Solana blockchain and provide timely market insights and investment strategies. This study provides a reference for further exploration in the field of digital currencies.

翻译：本文设计并实现了一个基于Solana区块链的网页爬虫系统，用于自动化收集和分析链上热门非同质化代币（NFT）的市场数据。首先，利用Selenium工具采集Solana链上热门NFT的基本信息与交易数据。其次，结合Scrapy框架对Magic Eden交易市场的交易记录进行深入分析，以考察NFT的价格波动与市场趋势。在数据分析方面，本文采用时间序列分析方法研究NFT市场的动态变化，并试图识别潜在的价格模式。此外，利用均值-方差优化模型评估不同NFT的风险与收益，同时考虑其非流动性和市场波动性等特征，为投资者提供数据驱动的投资组合建议。实验结果表明，爬虫技术与金融分析方法的结合能够有效分析Solana区块链上的NFT数据，并提供及时的市场洞察与投资策略。本研究为数字货币领域的进一步探索提供了参考。