Research on Cost and Risk Co-minimization Model of Cross-border Logistics in Guangxi Based on Monte Carlo Approach

Cross-border e-commerce refers to a kind of international commercial activity in which trading entities belonging to different customs borders reach transactions, make payments and settlements through e-commerce platforms, and deliver commodities through cross-border logistics to complete the transactions. Based on the relevant components of cross-border logistics cost and risk, this paper applies Markowitz, Capital Asset Pricing Model (CAPM), Value at Risk Model (VaRM), and Creditmetrics model to measure the risk of cross-border logistics, respectively. Through the cost measurement of cross-border logistics losses, a simplified logistics risk cost minimization model is derived. The model is applied to Guangxi’s cross-border logistics company M. Monte Carlo simulation is used to estimate the risk and cost of its cross-border logistics, respectively, and the probability of IRR>13.246% is simulated to be 32.963%, which indicates that the probability of cross-border logistics results exceeding the IRR of 13.246% given in the economic analysis is 32.963%. It can be seen in the logistics cost estimation that the mean value of the monthly logistics cost estimation of Company M is 2764000.564 yuan, and the standard deviation is 15126.36321 yuan, and after 3000 simulation operations, the logistics cost estimation has a 95% probability of falling on the interval [2572000 yuan, 2964000 yuan]. In response to the results of the simulation operations, a logistics risk and cost control strategy is proposed that is consistent with the long-term development of M Company.