Eminda Ishan De Silva, Gayithri Niluka Kuruppu, Sandun Dassanayake
{"title":"基于时变窗口的不可兑换代币(NFT)市场羊群检测","authors":"Eminda Ishan De Silva, Gayithri Niluka Kuruppu, Sandun Dassanayake","doi":"10.1108/cfri-05-2023-0118","DOIUrl":null,"url":null,"abstract":"<h3>Purpose</h3>\n<p>The non-fungible token (NFT) market had undergone dramatic growth and a sudden decline during 2021–2022. The market experienced a surge in prices in late 2021 and early 2022, with NFTs being sold at inflated prices. Despite this, by April 2022, the market underwent a correction, and the prices of NFTs returned to more reasonable levels. This can be a result of imitating the actions or judgments of a larger group, which is not systematically proven yet. Therefore, this study systematically investigates the applicability of herding behavior in the NFT market.</p><!--/ Abstract__block -->\n<h3>Design/methodology/approach</h3>\n<p>This research employs cross-sectional absolute deviation (CSAD) of returns and ordinary least squares (OLS) to test herding behavior with moving time windows of 10, 20 and 30 days based on the sales data collected from public interface of OpenSea between July 1, 2021 and June 30, 2022. Additionally, NFT-related keyword usage analysis is done for the detected herding periods.</p><!--/ Abstract__block -->\n<h3>Findings</h3>\n<p>As per the results of the data analyzed, herding behavior was evidenced using 10-, 20- and 30-day time windows from July 1, 2021 to June 30, 2022because of media movement. The findings revealed that this behavior was present and aligned with the overall behavior of the market.</p><!--/ Abstract__block -->\n<h3>Originality/value</h3>\n<p>This study introduces CSAD to examine herding behavior patterns within the NFT market. Complementing this method, keyword count-based analysis is employed to identify the underlying causes of herding behavior. Through this comprehensive approach, this study not only uncovers the roots of herding behavior but also offers an assessment of the time windows during which it occurs, considering the plausible socioeconomic contexts that influence these trends.</p><!--/ Abstract__block -->","PeriodicalId":44440,"journal":{"name":"China Finance Review International","volume":"64 1","pages":""},"PeriodicalIF":9.0000,"publicationDate":"2024-02-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Time-varying window-based herding detection in the non-fungible token (NFT) marketplace\",\"authors\":\"Eminda Ishan De Silva, Gayithri Niluka Kuruppu, Sandun Dassanayake\",\"doi\":\"10.1108/cfri-05-2023-0118\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<h3>Purpose</h3>\\n<p>The non-fungible token (NFT) market had undergone dramatic growth and a sudden decline during 2021–2022. The market experienced a surge in prices in late 2021 and early 2022, with NFTs being sold at inflated prices. Despite this, by April 2022, the market underwent a correction, and the prices of NFTs returned to more reasonable levels. This can be a result of imitating the actions or judgments of a larger group, which is not systematically proven yet. Therefore, this study systematically investigates the applicability of herding behavior in the NFT market.</p><!--/ Abstract__block -->\\n<h3>Design/methodology/approach</h3>\\n<p>This research employs cross-sectional absolute deviation (CSAD) of returns and ordinary least squares (OLS) to test herding behavior with moving time windows of 10, 20 and 30 days based on the sales data collected from public interface of OpenSea between July 1, 2021 and June 30, 2022. Additionally, NFT-related keyword usage analysis is done for the detected herding periods.</p><!--/ Abstract__block -->\\n<h3>Findings</h3>\\n<p>As per the results of the data analyzed, herding behavior was evidenced using 10-, 20- and 30-day time windows from July 1, 2021 to June 30, 2022because of media movement. The findings revealed that this behavior was present and aligned with the overall behavior of the market.</p><!--/ Abstract__block -->\\n<h3>Originality/value</h3>\\n<p>This study introduces CSAD to examine herding behavior patterns within the NFT market. Complementing this method, keyword count-based analysis is employed to identify the underlying causes of herding behavior. 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Time-varying window-based herding detection in the non-fungible token (NFT) marketplace
Purpose
The non-fungible token (NFT) market had undergone dramatic growth and a sudden decline during 2021–2022. The market experienced a surge in prices in late 2021 and early 2022, with NFTs being sold at inflated prices. Despite this, by April 2022, the market underwent a correction, and the prices of NFTs returned to more reasonable levels. This can be a result of imitating the actions or judgments of a larger group, which is not systematically proven yet. Therefore, this study systematically investigates the applicability of herding behavior in the NFT market.
Design/methodology/approach
This research employs cross-sectional absolute deviation (CSAD) of returns and ordinary least squares (OLS) to test herding behavior with moving time windows of 10, 20 and 30 days based on the sales data collected from public interface of OpenSea between July 1, 2021 and June 30, 2022. Additionally, NFT-related keyword usage analysis is done for the detected herding periods.
Findings
As per the results of the data analyzed, herding behavior was evidenced using 10-, 20- and 30-day time windows from July 1, 2021 to June 30, 2022because of media movement. The findings revealed that this behavior was present and aligned with the overall behavior of the market.
Originality/value
This study introduces CSAD to examine herding behavior patterns within the NFT market. Complementing this method, keyword count-based analysis is employed to identify the underlying causes of herding behavior. Through this comprehensive approach, this study not only uncovers the roots of herding behavior but also offers an assessment of the time windows during which it occurs, considering the plausible socioeconomic contexts that influence these trends.
期刊介绍:
China Finance Review International publishes original and high-quality theoretical and empirical articles focusing on financial and economic issues arising from China's reform, opening-up, economic development, and system transformation. The journal serves as a platform for exchange between Chinese finance scholars and international financial economists, covering a wide range of topics including monetary policy, banking, international trade and finance, corporate finance, asset pricing, market microstructure, corporate governance, incentive studies, fiscal policy, public management, and state-owned enterprise reform.