Abstract
A double forecasting model based on conditional expectation was proposed through probability distribution of demand of automobile loan. The demand of automobile loan is the sum of all compound variables which indicated that automobile loan was credited to customer occurring in a certain period of time. Probability distribution of automobile loan was acquired using throughout probability theory. In view of such a fact, demand of automobile loan can be viewed as an conditional mathematic expectation. The forecasting model is proposed using growing function. Theoretical analysis and Case study shows that model based on conditional expectation is better than other model available with respect to forecasting demand of automobile loan.
Highlights
In China, the rapid increase in the demand for private cars is an important and sensitive issue
A double forecasting model based on conditional expectation was proposed through probability distribution of demand of automobile loan
Probability distribution of automobile loan was acquired using throughout probability theory
Summary
In China, the rapid increase in the demand for private cars is an important and sensitive issue. Dagsvik and Gang Liu developed a general random utility framework for analyzing data on individuals’ rank-orderings They show that in the case with three alternatives one can express the probability of a particular rank-ordering as a simple function of first choice probabilities. Their framework is applied to specify and estimate models of household demand for conventional gasoline cars and alternative fuel vehicles in Shanghai based on rank-ordered data obtained from a stated preference survey [1]. Wouter J. den Haan et al investigated the portfolio behavior of bank loans following a monetary tightening and noted that real estate and consumer loans sharply decrease, while commercial and industrial (C & I) loans increase. He proposed an innovative application by providing an empirical exposition of the receiver operating characteristic curve analysis and by presenting the results of the model’s performance in reliability and robustness [5]
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