{"title":"Web3 中的风格化事实","authors":"A. Christian Silva, Shen-Ning Tung, Wwi-Ru Chen","doi":"arxiv-2408.07653","DOIUrl":null,"url":null,"abstract":"This paper presents a comprehensive statistical analysis of the Web3\necosystem, comparing various Web3 tokens with traditional financial assets\nacross multiple time scales. We examine probability distributions, tail\nbehaviors, and other key stylized facts of the returns for a diverse range of\ntokens, including decentralized exchanges, liquidity pools, and centralized\nexchanges. Despite functional differences, most tokens exhibit well-established\nempirical facts, including unconditional probability density of returns with\nheavy tails gradually becoming Gaussian and volatility clustering. Furthermore,\nwe compare assets traded on centralized (CEX) and decentralized (DEX)\nexchanges, finding that DEXs exhibit similar stylized facts despite different\ntrading mechanisms and often divergent long-term performance. We propose that\nthis similarity is attributable to arbitrageurs striving to maintain similar\ncentralized and decentralized prices. Our study contributes to a better\nunderstanding of the dynamics of Web3 tokens and the relationship between CEX\nand DEX markets, with important implications for risk management, pricing\nmodels, and portfolio construction in the rapidly evolving DeFi landscape.\nThese results add to the growing body of literature on cryptocurrency markets\nand provide insights that can guide the development of more accurate models for\nDeFi markets.","PeriodicalId":501139,"journal":{"name":"arXiv - QuantFin - Statistical Finance","volume":"33 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Stylized facts in Web3\",\"authors\":\"A. Christian Silva, Shen-Ning Tung, Wwi-Ru Chen\",\"doi\":\"arxiv-2408.07653\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper presents a comprehensive statistical analysis of the Web3\\necosystem, comparing various Web3 tokens with traditional financial assets\\nacross multiple time scales. We examine probability distributions, tail\\nbehaviors, and other key stylized facts of the returns for a diverse range of\\ntokens, including decentralized exchanges, liquidity pools, and centralized\\nexchanges. Despite functional differences, most tokens exhibit well-established\\nempirical facts, including unconditional probability density of returns with\\nheavy tails gradually becoming Gaussian and volatility clustering. Furthermore,\\nwe compare assets traded on centralized (CEX) and decentralized (DEX)\\nexchanges, finding that DEXs exhibit similar stylized facts despite different\\ntrading mechanisms and often divergent long-term performance. We propose that\\nthis similarity is attributable to arbitrageurs striving to maintain similar\\ncentralized and decentralized prices. Our study contributes to a better\\nunderstanding of the dynamics of Web3 tokens and the relationship between CEX\\nand DEX markets, with important implications for risk management, pricing\\nmodels, and portfolio construction in the rapidly evolving DeFi landscape.\\nThese results add to the growing body of literature on cryptocurrency markets\\nand provide insights that can guide the development of more accurate models for\\nDeFi markets.\",\"PeriodicalId\":501139,\"journal\":{\"name\":\"arXiv - QuantFin - Statistical Finance\",\"volume\":\"33 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-08-14\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"arXiv - QuantFin - Statistical Finance\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/arxiv-2408.07653\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"arXiv - QuantFin - Statistical Finance","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/arxiv-2408.07653","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
This paper presents a comprehensive statistical analysis of the Web3
ecosystem, comparing various Web3 tokens with traditional financial assets
across multiple time scales. We examine probability distributions, tail
behaviors, and other key stylized facts of the returns for a diverse range of
tokens, including decentralized exchanges, liquidity pools, and centralized
exchanges. Despite functional differences, most tokens exhibit well-established
empirical facts, including unconditional probability density of returns with
heavy tails gradually becoming Gaussian and volatility clustering. Furthermore,
we compare assets traded on centralized (CEX) and decentralized (DEX)
exchanges, finding that DEXs exhibit similar stylized facts despite different
trading mechanisms and often divergent long-term performance. We propose that
this similarity is attributable to arbitrageurs striving to maintain similar
centralized and decentralized prices. Our study contributes to a better
understanding of the dynamics of Web3 tokens and the relationship between CEX
and DEX markets, with important implications for risk management, pricing
models, and portfolio construction in the rapidly evolving DeFi landscape.
These results add to the growing body of literature on cryptocurrency markets
and provide insights that can guide the development of more accurate models for
DeFi markets.