基于总资本价值最大化的P2P网络借贷投资建议

Yanchao Tan, Xiaolin Zheng, Mengying Zhu, Chaohui Wang, Z. Zhu, Lifeng Yu
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引用次数: 3

摘要

投资推荐在p2p网络借贷中起着关键作用,帮助投资者选择合适的产品。但是,没有考虑到货币的时间价值,这是不符合常识的。本文建立了三个关于货币时间价值的模型,以帮助投资者利用固定资本实现收益最大化。具体而言,第一个建议模型是货币时间价值预测(TVM)模型,旨在计算每个上市公司的货币时间价值,同时考虑上市公司融资时间和流量风险的影响。然后,通过预测违约风险,利用投资收益预测模型对上市公司的投资收益进行评估。最后,我们运用总资本价值最大化(Total Capital Value Maximization, TCVM)模型,结合回合时间和数据大小,得到top-N推荐。实际数据收集的实验结果表明,该建议模型在收益和有效性方面都优于传统方法。
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Investment Recommendation with Total Capital Value Maximization in Online P2P Lending
Investment recommendation plays a key role to online peer-to-peer lending, which help investors choose proper products. However, time value of money has not been considered, which is not in line with common sense. In this paper, we develop three models concerning about time value of money to help investor to maximize their benefits with fixed capital. Specifically, the first proposal model is Time Value of Money Prediction (TVM), aiming to calculate time value of money for each listing and taking into account of both effects of listing's financing time and flow risk. Then, investment profits of listings are assessed with Investment Profits Prediction (IP) model by predicting default risk. Finally, we apply Total Capital Value Maximization (TCVM) model to obtain the top-N recommendation by incorporating the round of time and data size. Experiment results carried on a real data collection reveal that the proposal models outperform traditional methods in terms of profits and contain effectiveness.
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