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Determinants of default in the bitcoin lending market. The case of Bitbond platform

Noreikaite, Gabriele LU and Ambrazaite, Ausra Almante (2017) NEKN02 20171
Department of Economics
Abstract
This paper studies the bitcoin lending market and the factors explaining loans defaults. No financial intermediation implies that investors are faced directly with the credit risk. This increases information asymmetry at the cost of the lenders, so bitcoin lending platforms try to reduce this negative effect by providing information about the borrowers and their loan requests. Credit grade and interest rate are assigned by the platform, which are the main variables of the interest. This study has been conducted on the largest active bitcoin lending platform Bitbond covering 2013-2017 period with overall (N=1449) loans outstanding. Correlation analysis and univariate means tests have been used to analyse the data, while logistic regressions... (More)
This paper studies the bitcoin lending market and the factors explaining loans defaults. No financial intermediation implies that investors are faced directly with the credit risk. This increases information asymmetry at the cost of the lenders, so bitcoin lending platforms try to reduce this negative effect by providing information about the borrowers and their loan requests. Credit grade and interest rate are assigned by the platform, which are the main variables of the interest. This study has been conducted on the largest active bitcoin lending platform Bitbond covering 2013-2017 period with overall (N=1449) loans outstanding. Correlation analysis and univariate means tests have been used to analyse the data, while logistic regressions have been used for predicting default. Factors explaining default are loan amount, loan term and purpose of working capital, as well as industry of education and transportation and the total number of identifications. The interest rate assigned is the most predictive factor of the default followed by the grade, though other additional variables still improve the accuracy of the models. This paper contributes to the current literature since it is the first, to the best of our knowledge, analysing the bitcoin lending market. (Less)
Please use this url to cite or link to this publication:
author
Noreikaite, Gabriele LU and Ambrazaite, Ausra Almante
supervisor
organization
course
NEKN02 20171
year
type
H1 - Master's Degree (One Year)
subject
keywords
bitcoin, peer-to-peer lending, bitcoin lending, default, credit grade
language
English
id
8910358
date added to LUP
2017-06-13 15:19:16
date last changed
2017-06-13 15:19:16
@misc{8910358,
  abstract     = {{This paper studies the bitcoin lending market and the factors explaining loans defaults. No financial intermediation implies that investors are faced directly with the credit risk. This increases information asymmetry at the cost of the lenders, so bitcoin lending platforms try to reduce this negative effect by providing information about the borrowers and their loan requests. Credit grade and interest rate are assigned by the platform, which are the main variables of the interest. This study has been conducted on the largest active bitcoin lending platform Bitbond covering 2013-2017 period with overall (N=1449) loans outstanding. Correlation analysis and univariate means tests have been used to analyse the data, while logistic regressions have been used for predicting default. Factors explaining default are loan amount, loan term and purpose of working capital, as well as industry of education and transportation and the total number of identifications. The interest rate assigned is the most predictive factor of the default followed by the grade, though other additional variables still improve the accuracy of the models. This paper contributes to the current literature since it is the first, to the best of our knowledge, analysing the bitcoin lending market.}},
  author       = {{Noreikaite, Gabriele and Ambrazaite, Ausra Almante}},
  language     = {{eng}},
  note         = {{Student Paper}},
  title        = {{Determinants of default in the bitcoin lending market. The case of Bitbond platform}},
  year         = {{2017}},
}