A multi-objective instance-based decision support system for investment recommendation in peer-to-peer lending

Babaei, Golnoosh; Bamdad, Shahrooz

doi:10.1016/j.eswa.2020.113278

Cited by 42 publications

(19 citation statements)

References 47 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Similarly, the internet is integrated into various traditional industries, such as elderly care [ 4 ], government services [ 5 ], education [ 6 ], and finance [ 7 ]. According to “The 45th China Statistical Report on Internet Development”, released by the China Internet Network Information Center [ 8 ], internet users over 50 years old reached 16.9% of the population as of March 2020.…”

Section: Introductionmentioning

confidence: 99%

Impact of Internet Use on Elderly Health: Empirical Study Based on Chinese General Social Survey (CGSS) Data

Wang

Liang

2020

Healthcare

View full text Add to dashboard Cite

In the current era, the rapid spread of Internet technology has combined with various traditional industries; this provides new research perspectives and solutions for current problems, such as those in the elderly care industry. Elderly health is an important social problem in various countries, and governments have turned to the internet for new methods and better solutions. However, internet-use behavior has a certain influence on the elderly’s health status. This study investigates the effects of internet use on the elderly’s physical health, mental health, and self-rated health, along with the moderating role of individual cognitive ability in the above relationship. This study uses data from the Chinese General Social Survey (CGSS) in 2012 and 2015 as samples for analysis via the hierarchical regression method. The sample is from China and had 2821 and 3185 valid respondents in 2012 and 2015, respectively. Results show that internet use significantly affects the physical and mental health of the elderly and does not significantly affect self-rated health. In addition, individual cognitive ability plays a negative moderating role between internet use and physical and mental health. Finally, on the basis of results analysis and discussion, this study provides new recommendations to achieve targeted health improvements.

show abstract

Section: Introductionmentioning

confidence: 99%

Impact of Internet Use on Elderly Health: Empirical Study Based on Chinese General Social Survey (CGSS) Data

Wang

Liang

2020

Healthcare

View full text Add to dashboard Cite

show abstract

“…The first general assumption (and simplification) concerns the parameters σ ij . All the papers in the literature applying portfolio optimization in P2P lending consider the values σ ij to be zero when i ≠ j (Babaei & Bamdad, 2020a). This can be attributed to the assumption of negligible correlation between individual loan applications in the P2P market.…”

Section: Background and Literature Reviewmentioning

confidence: 99%

“…The aforementioned multi‐objective formulation can rarely be found in the literature; the main reason for this is that the algorithmic and computational requirements of these types of problems are significantly higher than similar single‐objective formulations. The only recent example attempting to formulate and solve a multi‐objective formulation was presented by Babaei and Bamdad (2020a), in which they utilized one of the most widely used evolutionary algorithm procedures, NSGA2. The authors found that the solution to the multi‐objective formulation offered a solution with lower return and risk than with a profit‐scoring model.…”

Section: Background and Literature Reviewmentioning

confidence: 99%

Data‐driven optimization of peer‐to‐peer lending portfolios based on the expected value framework

Byanjankar

Mezei

Heikkilä

2021

Intell Sys Acc Fin Mgmt

View full text Add to dashboard Cite

In recent years, peer‐to‐peer (P2P) lending has been gaining popularity amongst borrowers and individual investors. This can mainly be attributed to the easy and quick access to loans and the higher possible returns. However, the risk involved in these investments is considerable, and for most investors, being nonprofessionals, this increases the complexity and the importance of investment decisions. In this study, we focus on generating optimal investment decisions to lenders for selecting loans. We treat the loan selection process in P2P lending as a portfolio optimization problem, with the aim being to select a set of loans that provide a required return while minimizing risk. In the process, we use internal rate of return as the measure of return. As the starting point of the model, we use machine‐learning algorithms to predict the default probabilities and calculate expected values for the loans based on historical data. Afterwards, we calculate the distance between loans using (i) default probabilities and, as a novel step, (ii) expected value. In the calculations, we utilize kernel functions to obtain similarity weights of loans as the input of the optimization models. Two optimization models are tested and compared on data from the popular P2P platform Lending Club. The results show that using the expected‐value framework yields higher return.

show abstract

“…Equations (4-5) define a multiobjective optimization problem, which can usually be solved via the genetic algorithm [16,17], ant colony algorithm [18], particle swarm optimization algorithm [19] or simulated annealing algorithm [20]. In this paper, one of the most widely used multiobjective optimization methods, namely, non-dominated sorting genetic algorithm II (NSGA-II), is used to solve the noninferior solution set of the problem.…”

Section: Identification Of the Pareto Boundarymentioning

confidence: 99%

A Negotiation Pricing Model for Innovation Services Based on the Multiobjective Genetic Algorithm

Zhou¹,

Li²,

Zhang³

2020

Preprint

View full text Add to dashboard Cite

Service pricing is a bottleneck in the development of innovation services, as it is the issue of most concern between the suppliers and demanders. In this paper, a negotiation pricing model that is based on the multiobjective genetic algorithm is developed for innovation service pricing. Regarding the service pricing process as a multiobjective problem, the objective functions, which include the service price, service efficiency, and service quality, for suppliers and demanders are constructed. As the solution of a multiobjective problem is typically a series of alternatives, another negotiation process is necessary for determining the final decision. A learning strategy is adopted during the negotiation process to simulate reality. Finally, the model is implemented for an innovation service transaction, the objective of which is to identify the optimal price plan. The results demonstrate that the model can provide quantitative decision support for the pricing of an innovation service and ultimately yield a win-win result for both the supplier and demander of the innovation service. Furthermore, the influence of the parameters during the negotiation process is analyzed in detail. The effects of the learning strategy on accelerating the negotiation process, as well as the chosen of reasonable parameters are given.

show abstract

A multi-objective instance-based decision support system for investment recommendation in peer-to-peer lending

Cited by 42 publications

References 47 publications

Impact of Internet Use on Elderly Health: Empirical Study Based on Chinese General Social Survey (CGSS) Data

Impact of Internet Use on Elderly Health: Empirical Study Based on Chinese General Social Survey (CGSS) Data

Data‐driven optimization of peer‐to‐peer lending portfolios based on the expected value framework

A Negotiation Pricing Model for Innovation Services Based on the Multiobjective Genetic Algorithm

Contact Info

Product

Resources

About