Abstract
Since 2007, China’s first P2P (Internet financial point-to-point lending platform) was established, the Internet loan model officially entered the public vision. P2P grows explosively in the next few years and has it’s own place in the lending market. It is notable that the development of P2P industry is still imperfect and the number of P2P problem platforms is increasing every year, we pay attention to P2P interest rate in order to promote the continuous development of P2P industry. Since P2P industry has a little data as a new industry, so the Bayesian vector autoregressive model (BVAR) based on independent Minnesota-Wishart conjugate prior has been chosen to overcome the over-parameterized problem and the low estimation accuracy problem under the small sample condition. We found that the P2P interest rate has the dynamic link with itself in the last term. At last, we predict the P2P interest rate by MCMC of Gibbs sampling.
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This work was supported by National Natural Foundation of China (71171128).
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Lyu, W., Lyu, T. (2018). The Dynamic Relationship Analysis and Forecast of P2P Interest Rate—Based on Bayesian Vector Autoregressive Model. In: Li, X., Xu, X. (eds) Proceedings of the Fifth International Forum on Decision Sciences. Uncertainty and Operations Research. Springer, Singapore. https://doi.org/10.1007/978-981-10-7817-0_17
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DOI: https://doi.org/10.1007/978-981-10-7817-0_17
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