Data for: Forecasting Peer-to-Peer Platform Default Rate with LSTM Neural Network

Name: Data for: Forecasting Peer-to-Peer Platform Default Rate with LSTM Neural Network
Creator: Long yue Liang
Published: 2021-04-26T16:12:07.102Z
Keywords: Machine Learning Algorithm

Liang, Long yue

doi:10.17632/24c58vd88r.1

Data for: Forecasting Peer-to-Peer Platform Default Rate with LSTM Neural Network

Published: 26 April 2021| Version 1 | DOI: 10.17632/24c58vd88r.1

Contributor:

Long yue Liang

Description

This study adopts borrower data disclosed by US P2P lending platform Lending Club as data source, ranges from 2008 to 2015, since most of the loans issued in this period have been already paid off. We first calculate the average default rate of the monthly fresh loans as the dependent variable, then shift one to four delayed period of this average default as independent variables.

Data for: Forecasting Peer-to-Peer Platform Default Rate with LSTM Neural Network

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