Finally, the study confirms that the sellers of used cars possess informational advantages over market research agencies, which enable them to forecast resale prices more accurately. Second, the empirical results demonstrate the presence of heterogeneity in resale price forecasting and identify methods that can automatically overcome its detrimental effect on the forecast accuracy. It is also shown that the use of linear regression, the prevailing method in previous work, should be avoided.

First, a comparative analysis of alternative prediction methods provides evidence that random forest regression is particularly effective for resale price forecasting. An empirical study is performed to explore the contributions of different degrees of freedom in the modeling process to the forecast accuracy. The paper investigates statistical models for forecasting the resale prices of used cars. The proposed solution has already been deployed by a private company within its data analytics services since (1) an interpretable descriptive model of the main factors/parameters and corresponding weights affecting the residual value is provided and (2) the experimental results confirmed the promising outcomes of the proposed data-driven methodology. The proposed approach has been evaluated on a large set of real-world heavy trucks to demonstrate its effectiveness in correctly assessing the real status of wear and residual value at the end of leasing contracts, to provide a few and quantitative insights through an informative, interactive and user-friendly dashboard to make a proper decision on the next business strategies to be adopted. A huge amount of telematics data characterizing the actual usage of commercial vehicles is jointly analyzed with different external conditions (e.g., altimetry), affecting the truck’s performance to estimate the devaluation of the vehicle at the buy-back. This paper presents a data-driven and unsupervised methodology to provide a descriptive model assessing the residual value estimates of heavy trucks subject to buy-back. Recommend terms for leases that cover the costs of aging and mileage.In a context of deep transformation of the entire automotive industry, starting from pervasive and native connectivity, commercial vehicles (heavy, light, and buses) are generating and transmitting much more data than passenger cars, with a much higher expected value, motivated by the higher costs of the vehicles and their added-value related businesses, such as logistics, freight, and transportation management. (f) Does this model meet the conditions for using the MRM as the basis for inference? (g) Build confidence intervals for the partial effects of age and mileage. (e) Fit the appropriate multiple regression model. Do the relationships appear straight enough to permit using multiple regressions with these variables?

Explain why this similarity avoids some of the problems that we have when looking at a cross-section of different types of cars (such as nonlinear patterns or different variances). (c) The cars are all late-model cars in the same series. (b) Explain why we should use a multiple regression to estimate the effects of age and mileage simultaneously, rather than use two simple regression models. (a) Why does a manufacturer need to estimate the residual value of a leased car in order to determine annual payments on the lease? We’ll use data on the resale prices of used BMW cars gathered online. It seems as though the cost of a lease ought to take both duration and use into account. An older car that’s in great condition might be worth more than a newer car that’s been heavily driven. Another factor that affects the residual value is the type of use. The term of the lease, say 2 or 3 years, has to cover the cost of the ageing of the car. Customers expect to pay less for older cars, on average. What else matters? Certainly the age of the car affects its residual value. Let’s also assume that we’re looking at cars that have not been damaged in an accident. Let’s take this off the table by limiting our attention to a particular type of car. How should we estimate the residual value of a car? The residual value depends on how much the car was worth originally, such as the manufacturer’s list price. The residual value of a leased car is the value of this car in the used-car market, also known as the previously owned car market.

A different answer considers the so-called residual value of the car at the end of the lease. 4M Residual Car values When car dealers lease a car, how do they decide what to charge? One answer, if you’ve got a lot of unpopular cars to move, is to charge whatever it takes to get the cars off the lot.

Residual value of a car