Research on Balance Strategy of Supervision and Incentive of P2P Lending Platform

The supervision of P2P lending platforms has always been a hot topic. However, if the government regulates the platform too strictly, it would restrain the subjective initiative of Internet financial innovation, and if the government overstimulates the platform, it might lead to systemic financial risks. From the perspective of government double objective optimization, this article sets a specific scene and analyzes the policy choice of supervision and incentive of P2P platform through game theory modeling and numerical simulation. Two schemes are offered, respectively, “First regulate and then motivate” and “First motivate and then regulate”. The results show that the government should first motivate and then regulate the P2P lending platforms, so as to achieve the government\u27s dual objective optimization and utility maximization. Moreover, the investment of supervision and incentive should be adjusted continuously with the development of the industry

Portfolio formation with preselection using deep learning from long-term financial data

Portfolio theory is an important foundation for portfolio management which is a well-studied subject yet not fully conquered territory. This paper proposes a mixed method consisting of long short-term memory networks and mean-variance model for optimal portfolio formation in conjunction with the asset preselection, in which long-term dependences of financial time-series data can be captured. The experiment uses a large volume of sample data from the UK Stock Exchange 100 Index between March 1994 and March 2019. In the first stage, long short-term memory networks are used to forecast the return of assets and select assets with higher potential returns. After comparing the outcomes of the long short-term memory networks against support vector machine, random forest, deep neural networks, and autoregressive integrated moving average model, we discover that long short-term memory networks are appropriate for financial time-series forecasting, to beat the other benchmark models by a very clear margin. In the second stage, based on selected assets with higher returns, the mean-variance model is applied for portfolio optimisation. The validation of this methodology is carried out by comparing the proposed model with the other five baseline strategies, to which the proposed model clearly outperforms others in terms of the cumulative return per year, Sharpe ratio per triennium as well as average return to the risk per month of each triennium. i.e. potential returns and risks

Risk Analysis of Re-displacement After Conservative Treatment of Pediatric Unstable Fractures of Middle and Distal Forearm

Background: Fractures of the middle and distal diaphysis of the forearm are common in children. Conservative treatment is effective in this regard. Some studies have discussed the risk factors and predictive indicators of re-displacement; however, the objects of the study are all fixed with tubular plaster or double sugar splint. Objectives: This study was performed to determine the risk factors of re-displacement after closed reduction and double splint plaster fixation of unstable pediatric fractures of the middle and distal diaphysis of the forearm. Methods: This retrospective study was conducted on 57 patients undergoing closed reduction and plaster fixation after unstable diaphyseal fractures of the middle and distal forearm in Wuxi Children's Hospital of Nanjing Medical University within May 2014 to May 2020. A total of 35 male and 22 female subjects aged 6 - 9 years (average: 7.3 years) participated in this study. They were followed up for more than 6 weeks after fracture healing. According to whether experiencing a secondary displacement within 2 weeks after the fracture, the subjects were divided into two groups, namely displacement, and non-displacement. Gender, age, double fracture, reduction quality, and plaster fixation type were analyzed as relevant, effective factors. Results: All 57 patients were followed up, and all fractures reached clinical healing standards at the last follow-up. Moreover, 20 and 37 cases were in the shift and non-shift groups, respectively. No statistically significant difference was reported in gender (c2 = 0.168; P = 0.780), age (t = 1.003; P = 0.217), double fracture (c2 = 0.021; P = 1), and plaster fixation type (c2 = 0.416; P = 0.699) between the two groups. The reduction quality (c2 = 7.480; P = 0.025) showed a statistically significant difference. Binary logistic regression analysis showed that reduction quality was a risk factor for fracture relocation providing a predictive value. Conclusions: Good reduction quality can reduce the risk of fracture displacement.</jats:p

E-book adoption behaviors through an online sharing platform

Purpose The purpose of this paper is to construct a multi-relational network for an online sharing platform in the age of the sharing economy, to identify the factors impacting users’ product adoption behavior and to predict consumers’ purchases of user-generated products on the platform. Design/methodology/approach The study conducted multi-relational network analyses of five different sub-networks in identifying influential factors for e-book adoption. Meanwhile, the study adopted machine learning methods with different classification algorithms and feature sets to predict users’ purchasing behaviors. Findings The authors found that an individual’s adoption of a product was correlated with his or her purchasing habits and collaboration with others on the online sharing platform. Through the inclusion of network features, the authors were able to build a predictive model that forecasted consumers’ purchases of user-generated e-books with reasonable accuracy. Research limitations/implications The interdisciplinary approach used in the study can serve as a good reference for identifying factors impacting the product adoption behavior of users in the online sharing platform, through employing different sociological and computational methods. Practical implications The outcome of the study has provided important managerial implications, especially for the design of social commerce platform in the age of the sharing economy. Social implications The authors verified the social influence impacting consumers’ product adoption behavior and shed light on the value of collaboration in the age of the sharing economy. Originality/value The study was the first to identify user-generated e-book adoption on an online sharing platform from a multi-relational network perspective. The idea and the approach supplied a new method of behavioral analysis in the context of a sharing economy. </jats:sec