  Leasing is a popular channel to market new cars. Pricing a leasing contract
is complicated because the leasing rate embodies an expectation of the residual
value of the car after contract expiration. To aid lessors in their pricing
decisions, the paper develops resale price forecasting models. A peculiarity of
the leasing business is that forecast errors entail different costs.
Identifying effective ways to address this characteristic is the main objective
of the paper. More specifically, the paper contributes to the literature
through i) consolidating and integrating previous work in forecasting with
asymmetric cost of error functions, ii) systematically evaluating previous
approaches and comparing them to a new approach, and iii) demonstrating that
forecasting with asymmetric cost of error functions enhances the quality of
decision support in car leasing. For example, under the assumption that the
costs of overestimating resale prices is twice that of the opposite error,
incorporating corresponding cost asymmetry into forecast model development
reduces decision costs by about eight percent, compared to a standard
forecasting model. Higher asymmetry produces even larger improvements.
