Prototyping to address cognitive gaps in Distributed Ledger investments

Tian Wei, Han Wu and Michael Dowling

Finance Research Letters, 2024, vol. 70, issue C

Abstract: The Distributed Ledger Technology (DLT)-based ecosystem enhances transparency and efficiency in financial transactions through decentralized verification. However, its complexity, market volatility, and evolving regulations create cognitive uncertainties among investors, leading to the potential for biased decisions. We contribute towards understanding the specific categorizing cognitive processes investors use based on textual machine learning from a dataset centred around 669 DLT companies. Our findings particularly show that investor decisions on new entrants tend to be based on a prototyping approach which means they are significantly influenced by the perceived unambiguity and financial reputation of the company's category. Overall, our study offers significant new data-driven understanding of investment behaviors in the DLT ecosystem.

Keywords: DLT; Distributed ledger; Categorization; Cognitive bias; Investment; Machine learning (search for similar items in EconPapers)
JEL-codes: G11 G41 (search for similar items in EconPapers)
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:eee:finlet:v:70:y:2024:i:c:s1544612324013382

DOI: 10.1016/j.frl.2024.106309

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