Analysis of the Hedging Rate of Used Cars in Beijing by Linear Regression Model

Abstract

The hedging rate for used cars is a very important index that measures the ratio of how much a car can be sold after driving multiple years out of the price when it was bought. It measures the popularity of the cars in used-car market. The higher the hedging rate for a used car always makes the car more popular in the market. As a result, it is crucial to make an accurate prediction of the hedging rate. This paper selects 12 basic indices for 1500 used cars in Beijing based on a popular used-car website in China to predict which factors have an influence on the hedging rate. By using linear regression model and comparing the p-value of each index with 0.05, 5 indices that have less significance on the hedging rate are eliminated, which are fuel consumption, maximum capacity, environmental protection standard, luggage capacity, and number of transfers. The result shows that the hedging rate has a positive relationship with swept volume, seats, and maximum speed, while it has a negative relationship with registration time, mileage, maximum horsepower, and doors.