Cryptocurrencies and Tokens Lifetime Analysis from 2009 to 2021

Paul Gatabazi, Gaëtan Kabera, Jules Clement Mba, Edson Pindza and Sileshi Fanta Melesse
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Paul Gatabazi: Department of Mathematics and Applied Mathematics, Faculty of Sciences, University of Johannesburg, Johannesburg 2006, South Africa
Gaëtan Kabera: Department of Statistics, University of South Africa—UNISA, Pretoria 0003, South Africa
Edson Pindza: Department of Mathematics and Statistics, Tshwane University of Technology, Pretoria 0001, South Africa
Sileshi Fanta Melesse: School of Mathematics, Statistics and Computer Science, University of KwaZulu Natal, Pietermaritzburg 3209, South Africa

Economies, 2022, vol. 10, issue 3, 1-14

Abstract: The success of Bitcoin has spurred emergence of countless alternative coins with some of them shutting down only few weeks after their inception, thus disappearing with millions of dollars collected from enthusiast investors through initial coin offering (ICO) process. This has led investors from the general population to the institutional ones, to become skeptical in venturing in the cryptocurrency market, adding to its highly volatile characteristic. It is then of vital interest to investigate the life span of available coins and tokens, and to evaluate their level of survivability. This will make investors more knowledgeable and hence build their confidence in hazarding in the cryptocurrency market. Survival analysis approach is well suited to provide the needed information. In this study, we discuss the survival outcomes of coins and tokens from the first release of a cryptocurrency in 2009. Non-parametric methods of time-to-event analysis namely Aalen Additive Hazards Model (AAHM) trough counting and martingale processes, Cox Proportional Hazard Model (CPHM) are based on six covariates of interest. Proportional hazards assumption (PHA) is checked by assessing the Kaplan-Meier estimates of survival functions at the levels of each covariate. The results in different regression models display significant and non-significant covariates, relative risks and standard errors. Among the results, it was found that cryptocurrencies under standalone blockchain were at a relatively higher risk of collapsing. It was also found that the 2013–2017 cryptocurrencies release was at a high risk as compared to 2009–2013 release and that cryptocurrencies for which headquarters are known had the relatively better survival outcomes. This provides clear indicators to watch out for while selecting the coins or tokens in which to invest.

Keywords: cryptocurrency; blockchain; survival function; risk; weight; hazard ratio (search for similar items in EconPapers)
JEL-codes: E F I J O Q (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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