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

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  • Jessica Foo
  • Lek-Heng Lim
  • Ken Sze-Wai Wong

Abstract

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.

Suggested Citation

  • Jessica Foo & Lek-Heng Lim & Ken Sze-Wai Wong, 2017. "Macroeconomics and FinTech: Uncovering Latent Macroeconomic Effects on Peer-to-Peer Lending," Papers 1710.11283, arXiv.org.
    • Handle: RePEc:arx:papers:1710.11283
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    References listed on IDEAS

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    1. Gourieroux, C & Monfort, A & Renault, E, 1993. "Indirect Inference," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 8(S), pages 85-118, Suppl. De.
    2. Ang, Andrew & Piazzesi, Monika, 2003. "A no-arbitrage vector autoregression of term structure dynamics with macroeconomic and latent variables," Journal of Monetary Economics, Elsevier, vol. 50(4), pages 745-787, May.
    3. Fama, Eugene F. & French, Kenneth R., 1993. "Common risk factors in the returns on stocks and bonds," Journal of Financial Economics, Elsevier, vol. 33(1), pages 3-56, February.
    4. Mikael C. Bergbrant & Patrick J. Kelly, 2016. "Macroeconomic Expectations and the Size, Value, and Momentum Factors," Financial Management, Financial Management Association International, vol. 45(4), pages 809-844, December.
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    Cited by:

    1. GUO, Jianfeng & LIU, Xiaojie & CUI, Changnan & GU, Fu, 2021. "Influence of nonspecific factors on the interest rate of online peer-to-peer microloans in China," Finance Research Letters, Elsevier, vol. 41(C).
    2. Kamilė Taujanskaitė & Eugenijus Milčius, 2022. "Accelerated Growth of Peer-to-Peer Lending and Its Impact on the Consumer Credit Market: Evidence from Lithuania," Economies, MDPI, vol. 10(9), pages 1-17, September.

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