Moyo, S.Mphephu, N.Maakgetlwa, Saleme Shoky2022-09-202022-09-202022-07-15Maakgetlwa, S. S. (2022) Multi-objective Loan Portfolio Optimization in Peer-to-Peer Lending Markets using Machine-Learning Techniques. University of Venda. South Africa.<http://hdl.handle.net/11602/2299>.http://hdl.handle.net/11602/2299MSc (Mathematics)Department of Mathematical and Computational SciencesPortfolio optimization problems in the Peer-to-Peer lending Platforms involve selecting good loan applications (less risky) from various potential borrowers. Such loans have lower level of risk in terms of funding and earning higher returns. The aim of this study is to find ways to maximize returns and minimize the risks associated with the investment. It becomes more complicated to optimally allocate weights to the loan application when there is an increased number of applications for funding. This study focused on devising techniques which can be used to optimally select portfolios of loan applications for funding with desired returns on the investment. Harry Markowitz pioneered the Modern Portfolio theory also known as Meanvariance theory to construct a portfolio but the theory failed since it was built on unrealistic assumptions in terms of real life situations. This study explored and compared the meanvariance theory and other machine learning methods to construct a portfolio of loans from peer-to-peer lending market in order to be able to recommend the best approach to achieving high returns with minimum risk. The study employed the evolutionary algorithms (Particle Swarm Optimization and Genetic Algorithm) and the Reinforcement learning algorithm1 online resource (vii, 45 leaves) ; color illustrationsenUniversity of VendaCalibration,UCTDGeneticAlgorithmMachine LearningReinforcement LearningOptimizationPortfolio OptimizationParticle Swarm Optimization332.3LoansFinancial institutionsLenders of las resortBanks and Banking, CentralIndividual investorsRisksInvestment -- Decision makingDissertationMaakgetlwa SS. Multi-objective Loan Portfolio Optimization in Peer-to-Peer Lending Markets using Machine-Learning Techniques. []. , 2022 [cited yyyy month dd]. Available from: http://hdl.handle.net/11602/2299Maakgetlwa, S. S. (2022). <i>Multi-objective Loan Portfolio Optimization in Peer-to-Peer Lending Markets using Machine-Learning Techniques</i>. (). . Retrieved from http://hdl.handle.net/11602/2299Maakgetlwa, Saleme Shoky. <i>"Multi-objective Loan Portfolio Optimization in Peer-to-Peer Lending Markets using Machine-Learning Techniques."</i> ., , 2022. http://hdl.handle.net/11602/2299TY - Dissertation AU - Maakgetlwa, Saleme Shoky AB - Portfolio optimization problems in the Peer-to-Peer lending Platforms involve selecting good loan applications (less risky) from various potential borrowers. Such loans have lower level of risk in terms of funding and earning higher returns. The aim of this study is to find ways to maximize returns and minimize the risks associated with the investment. It becomes more complicated to optimally allocate weights to the loan application when there is an increased number of applications for funding. This study focused on devising techniques which can be used to optimally select portfolios of loan applications for funding with desired returns on the investment. Harry Markowitz pioneered the Modern Portfolio theory also known as Meanvariance theory to construct a portfolio but the theory failed since it was built on unrealistic assumptions in terms of real life situations. This study explored and compared the meanvariance theory and other machine learning methods to construct a portfolio of loans from peer-to-peer lending market in order to be able to recommend the best approach to achieving high returns with minimum risk. The study employed the evolutionary algorithms (Particle Swarm Optimization and Genetic Algorithm) and the Reinforcement learning algorithm DA - 2022-07-15 DB - ResearchSpace DP - Univen KW - Calibration, KW - Genetic KW - Algorithm KW - Machine Learning KW - Reinforcement Learning KW - Optimization KW - Portfolio Optimization KW - Particle Swarm Optimization LK - https://univendspace.univen.ac.za PY - 2022 T1 - Multi-objective Loan Portfolio Optimization in Peer-to-Peer Lending Markets using Machine-Learning Techniques TI - Multi-objective Loan Portfolio Optimization in Peer-to-Peer Lending Markets using Machine-Learning Techniques UR - http://hdl.handle.net/11602/2299 ER -