Predicting cryptocurrency defaults
Year of publication: |
2020
|
---|---|
Authors: | Grobys, Klaus ; Sapkota, Niranjan |
Published in: |
Applied economics. - New York, NY : Routledge, ISSN 1466-4283, ZDB-ID 1473581-7. - Vol. 52.2020, 46, p. 5060-5076
|
Subject: | Cryptocurrency | bitcoin | bankruptcy | default | credit risk | Insolvenz | Insolvency | Kreditrisiko | Credit risk | Virtuelle Währung | Virtual currency | Elektronisches Geld | Electronic money | Prognoseverfahren | Forecasting model | Kreditwürdigkeit | Credit rating | Welt | World |
-
Predicting Cryptocurrency Defaults
Sapkota, Niranjan, (2019)
-
Neural networks VS discriminant analysis in the assessment of default
Wójcicka, Aleksandra, (2017)
-
Capacity of neural networks and discriminant analysis in classifying potential debtors
Piasecki, Krzysztof, (2017)
- More ...
-
A fractal view on losses attributable to scams in the market for initial coin offerings
Grobys, Klaus, (2022)
-
Sapkota, Niranjan, (2019)
-
Grobys, Klaus, (2019)
- More ...