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Research of gender effect on funding success in peer-to-peer lending markets demonstrates that gender discrimination is a platform-specific phenomenon rather than a common feature. Can we get a similar conclusion about the relationship between gender and credit risk? How do gender differences affect default risk? We try to answer this question using the data of the largest peer-to-peer lending platform RenRenDai spanning from March 2016 to September 2016. In order to avoid the endogeneity problem, this paper first uses the instrumental variable method to conduct a baseline Probit model estimate connecting gender difference to the default rate with several borrowers’ individual characteristics under control. Then the original Probit model and a propensity score matching method aiming to eliminate the effects of divergent observable characteristics are applied to test the robustness of the outcome. Both the baseline estimation and the robustness test show that there is no significant gender effect on the probability of default, ceteris paribus. Therefore, borrowers’ gender is not a good screening device for the P2P lending platform to control the credit risk; other factors should be taken into account to reduce the non-performing loan rate. However, since this paper only investigates the situation of RenRenDai and the data we use is limited, we should be very careful to generalize our findings to other P2P lending platforms. More research on different P2P lending platforms in different regulatory regimes is in necessity

Research of influence of macroeconomic fluctuations on stock markets suggests different kinds of relationship between them. This paper aims to analyze the relationship between Shanghai Composite Index and China’s macroeconomic indexes applying cointegration method and different metrics of money supply: M1 and M2. The time period of data in this paper spans from Quarter 1, 1995 to Quarter 4, 2018. The Vector Error Correction Model (VECM) constituted suggests that: 1) there is a long-run equilibrium between these variables; 2) in the long run, despite of different measures of money supply, real GDP is negatively correlated with SCI, implicating a deviation of a stock market from real economy; 3) in the short run, no matter what measure of money supply we use, real GDP seems to have no significant effect on SCI, which again verifies the deviation of the stock market from real economy. The impulse response analysis suggests the totally opposite direction of effect that money supply and interest rate have on SCI in different specifications, and the forecast-error decomposition analysis indicates that SCI cannot fully reflect macroeconomic fluctuations once again.

Nonequilibrium molecular dynamics simulation (NEMD) was used to compute the viscosity of a pure polyol ester, −1 to 1010pentaerythritol tetrahexanoate (PEC6), for a broad range of strain rate (107 s s−1), temperature (258 K to 373 K), and pressure (0.1 MPa to 1 GPa). The Newtonian viscosity was obtained by fitting the viscosities at different strain rates to the Eyring model. The predicted Newtonian viscosities agree well with the experimental data with respect to temperature and pressure. The molecular dynamics simulation is pure prediction because it requires only the chemical structure as the input. Therefore, molecular dynamics can be especially useful in simulating those hypothetical molecules and those experimentally inaccessible conditions, which can reduce the cost and time of experimentation and facilitate the development of high-performance lubricants.