Macroeconomics and FinTech: Uncovering Latent Macroeconomic Effects on Peer-to-Peer Lending

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Tác giả: Jessica Foo, Lek-Heng Lim, Ken Sze-Wai Wong

Ngôn ngữ: eng

Ký hiệu phân loại: 609.17 Historical, geographic, persons treatment

Thông tin xuất bản: 2017

Mô tả vật lý:

Bộ sưu tập: Báo, Tạp chí

ID: 161635

Peer-to-peer (P2P) lending is a fast growing financial technology (FinTech) trend that is displacing traditional retail banking. Studies on P2P lending have focused on predicting individual interest rates or default probabilities. However, the relationship between aggregated P2P interest rates and the general economy will be of interest to investors and borrowers as the P2P credit market matures. We show that the variation in P2P interest rates across grade types are determined by three macroeconomic latent factors formed by Canonical Correlation Analysis (CCA) - macro default, investor uncertainty, and the fundamental value of the market. However, the variation in P2P interest rates across term types cannot be explained by the general economy.
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