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Risk Prediction of Peer-to-Peer Lending Market by a LSTM Model with Macroeconomic Factor
9 references·0 citing·38 second hop
Risk Prediction of Peer-to-Peer Lending Market by a LSTM Model with Macroeconomic Factor (2020)Risk Prediction of Peer-to-Peer Lending M…Predicting repayment of borrows in peer‐to‐peer social lending with deep dense convolutional network (2019)Predicting repayment of borro…Overdue Prediction of Bank Loans Based on LSTM-SVM (2018)Overdue Prediction of Bank Lo…Loan evaluation in P2P lending based on Random Forest optimized by genetic algorithm with profit score (2018)Loan evaluation in P2P lendin…A Deep Learning Approach for Credit Scoring of Peer-to-Peer Lending Using Attention Mechanism LSTM (2018)A Deep Learning Approach for …Detrended fluctuation analysis of multivariate time series (2016)Detrended fluctuation analysi…Risk assessment in social lending via random forests (2015)Risk assessment in social len…Evaluating credit risk and loan performance in online Peer-to-Peer (P2P) lending (2014)Evaluating credit risk and lo…Okun's Law Does the Austrian unemployment-GDP relationship exhibit structural breaks? (2001)Okun's Law Does the Austrian …Vector autoregression and causality: a theoretical overview and simulation study (1994)Vector autoregression and cau…Credit scoring with a data mining approach based on support vector machines (2006)A benchmark of machine learning approaches for credit score prediction (2020)Fairness in Machine Learning (2020)What have we learnt from 10 years of fintech research? a scientometric analysis (2020)Co-Integration and Error Correction: Representation, Estimation, and Testing (1987)Statistical analysis of cointegration vectors (1988)Estimation and Hypothesis Testing of Cointegration Vectors in Gaussian Vector Autoregressive Models (1991)Export-led growth: a survey of the empirical literature and some non-causality results. Part 1 (2000)THE BANGLADESH DEVELOPMENT STUDIES (2009)Economic growth and energy consumption causal nexus viewed through a bootstrap rolling window (2010)The Market for "Lemons": Quality Uncertainty and the Market Mechanism (1970)Credit Rationing in Markets with Imperfect Information (1981)Judging Borrowers by the Company They Keep: Friendship Networks and Information Asymmetry in Online Peer-to-Peer Lending (2012)Study on a prediction of P2P network loan default based on the machine learning LightGBM and XGboost algorithms according to different high dimensional data cleaning (2018)The roles of alternative data and machine learning in fintech lending: Evidence from the LendingClub consumer platform (2019)Effect of trends on detrended fluctuation analysis (2001)Multifractal detrended fluctuation analysis of nonstationary time series (2002)Detrended Cross-Correlation Analysis: A New Method for Analyzing Two Nonstationary Time Series (2008)Neural network credit scoring models (2000)Credit rating analysis with support vector machines and neural networks: a market comparative study (2003)Benchmarking state-of-the-art classification algorithms for credit scoring: An update of research (2015)2-stage modified random forest model for credit risk assessment of P2P network lending to “Three Rurals” borrowers (2020)A novel tree-based dynamic heterogeneous ensemble method for credit scoring (2020)Artificial intelligence in E-Commerce: a bibliometric study and literature review (2022)A boosted decision tree approach using Bayesian hyper-parameter optimization for credit scoring (2017)Fake news detection using deep learning models: A novel approach (2019)Deep learning in finance and banking: A literature review and classification (2020)Online peer-to-peer lending: A review of the literature (2021)Big Data: A Survey (2014)Data-intensive applications, challenges, techniques and technologies: A survey on Big Data (2014)Deep learning applications and challenges in big data analytics (2015)Risk-return modelling in the p2p lending market: Trends, gaps, recommendations and future directions (2021)Multi-view representation learning with Kolmogorov-Smirnov to predict default based on imbalanced and complex dataset (2022)Credit scoring using multi-task Siamese neural network for improving prediction performance and stability (2024)Risk Prediction of Peer-to-Peer Lending Market by a LSTM Model with Macroeconomic FactorHow can we assess and evaluate the competitive advantage of a country’s human resource development system? (2012)The Great Recession and Okun's law (2017)Accuracy Comparison Between Feedforward Neural Network, Support Vector Machine and Boosting Ensembles for Financial Risk Evaluation (2025)
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References

  • 2014Evaluating credit risk and loan performance in online Peer-to-Peer (P2P) lending495 cited
  • 1994Vector autoregression and causality: a theoretical overview and simulation study404 cited
  • 2015Risk assessment in social lending via random forests398 cited
  • 2018A Deep Learning Approach for Credit Scoring of Peer-to-Peer Lending Using Attention Mechanism LSTM148 cited
  • 2018Loan evaluation in P2P lending based on Random Forest optimized by genetic algorithm with profit score110 cited
  • 2001Okun's Law Does the Austrian unemployment-GDP relationship exhibit structural breaks?57 cited
  • 2016Detrended fluctuation analysis of multivariate time series52 cited
  • 2019Predicting repayment of borrows in peer‐to‐peer social lending with deep dense convolutional network39 cited
  • 2018Overdue Prediction of Bank Loans Based on LSTM-SVM13 cited

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