Research ArticleOpen AccessGoogle Scholar indexed
Forecasting Model of Automobile Loan Based on Conditional Expectation
- 1
- 2
- 3
Copy link · social · email
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.
KeywordsAutomobile LoanConditional ExpectationThroughout Probability Theory
- J. K. Dagsvik and G. Liu, “A Framework for Analyzing Rank-Ordered Data with Application to Automobile Demand,” Transportation Research Part A: Policy and Practice, Vol. 43, No. 1, 2009, pp. 1-12.
- J. Lee, Y. S. Cho, “Demand Forecasting of Diesel Passenger Car Considering Consumer Preference and Government Regulation in South Korea,” Transportation Research Part A: Policy and Practice, Vol. 43, No. 4, 2009, pp. 420-429.
- A. A. Dick, “Demand Estimation and Consumer Welfare in the Banking Industry,” Journal of Banking & Finance, Vol. 32, No. 8, 2008, pp. 1661-1676.
- W. J. den Haan, S. W. Sumner and G. M. Yamashiro, “Bank Loan Portfolios and the Monetary Transmission Mechanism,” Journal of Monetary Economics, Vol. 54, No. 3, 2007, pp. 904-924.
- L.-C. Chi, “How Have Banks Fared Following a Borrower’s Financial Distress,” Economic Modelling, Vol. 26, No. 2, 2009, pp. 480-488.
- Q. Wang, “Forecast and Analysis on the Prospect of China’s Consumer Car Loan,” Operations Research and Management Science, Vol. 11, No. 2, 2002, pp. 117-121.
- Q. Ye, “Improving on GM (1, 1) and Its Application in the Forecast of Bank Loan,” Mathematics in Practice and Theory, Vol. 38, No. 18, 2008, pp. 20-27.