A multi-agent simulation of investment choice in the P2P lending market with bankruptcy risk. Issue 2 (4th March 2022)

• Record Type: Journal Article
• Authors: Liu, Jiajia; Dong, Jichang
• Is Part Of: Journal of simulation. Volume 16:Issue 2(2022)
• Page Start: 132
• Page End: 146
• Publication Date: 2022-03-04
• Subjects: Heterogeneous Investors Multi-Agent Model -- Simulation -- P2P Lending Platform -- Bankruptcy Risk -- Investment Choice; Operations research -- Periodicals; Mathematical models -- Periodicals; Simulation methods -- Periodicals; 511.805
• DOI: 10.1080/17477778.2020.1759386
• Languages: English
• ISSNs: 1747-7778

Abstract

ABSTRACT: A challenge for investors in P2P lending marketplaces is to find an effective allocation of their funds across different loans by assessing the widespread collapse of lending platforms and each loan's default risk. This paper investigates risk-averse/risk-tolerant/risk-neutral investors' and borrowers' transaction behaviours, as well as P2P lending platforms' operating mechanism. A Heterogeneous Investors Multi-Agent Model (HIMAM) is built to simulate agents' reactions to variance in platform's bankruptcy risk. This enables an assessment of changes in investors' average return rates and investment decisions. This study finds that platform bankruptcy risk influences total investment amounts and average return rates. The correlation between the transaction fee and total investment amount presents as an inverted U-shape. Furthermore, there is a negative correlation between two-part tariffs and both investors' average return rates and the number of investors. This is because two-part tariffs are dependent on investors' transaction volumes. High two-part tariffs increase investors' transaction costs. Additionally, considering bankruptcy and default risk, credit E are the most popular type of borrower because such borrower tradeoff higher risk for higher return; credits B and C are the least popular type of borrower.