Return and volatility properties: Stylized facts from the universe of cryptocurrencies and NFTs

被引:19
|
作者
Ghosh, Bikramaditya [1 ,2 ]
Bouri, Elie [3 ,4 ]
Wee, Jung Bum [4 ]
Zulfiqar, Noshaba [5 ]
机构
[1] Deemed Univ, Symbiosis Inst Business Management, Symbiosis Int, Bengaluru, India
[2] Harper Adams Univ, Edgmond, Newport TF10 8NB, Shrops, England
[3] Lebanese Amer Univ, Sch Business, Beirut, Lebanon
[4] Kyung Hee Univ, Coll Business, 26 Kyungheedae Ro, Seoul 02447, South Korea
[5] Univ Wah, Quaid Ave, Wah Cantt, Pakistan
关键词
Non -fungible token (NFT); Bitcoin and cryptocurrencies; Fat tails; GARCH-models; Asymmetric volatility; Long memory; BITCOIN; TAIL;
D O I
10.1016/j.ribaf.2023.101945
中图分类号
F8 [财政、金融];
学科分类号
0202 ;
摘要
Stylized facts of returns and volatility are an important approximation tool for empirical finance studies, especially in the area of young and new assets. In this paper, we examine the return and volatility properties of four non-fungible tokens (NFTs) and four cryptocurrencies from 24th January 2018-2nd August 2022. The results show the following: Firstly, the returns of both NFTs and cryptocurrencies have fat tails, with evidence of tail exponents following the inverse cubiclaw, along with clear persistence behavior. Secondly, all returns exhibit volatility clustering, albeit to varying degrees, and the detected absence of inverse volatility-asymmetry challenges the safe-haven property often documented for cryptocurrencies. Thirdly, return-based long-memory is slightly more intense than volatility-based long-memory, especially for NFTs, which demonstrate a predictability contesting market efficiency. These findings are generally consistent with previous findings on equities, implying that the return and volatility behavior of NFTs and cryptocurrencies is leaning towards that of traditional assets.
引用
收藏
页数:16
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