# Dsc2008 Assignment

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Dsc2008 Assignment
1. Introduction
The Vehicle Quota System (VQS) was implemented in May ‘90 by the Land Transport Authority of Singapore (LTA) to curb the rapidly increasing vehicle population growth. The VQS allocates a fixed number of Certificates of Entitlement (COE) available for competitive bidding during the bidding exercises conducted bi-monthly3. This report studies the factors affecting the monthly prices of COE in Category B and considers the best model to forecast future COE prices.
(1-Feb-09, \$689)
)

(1-Feb-09, \$689)
)

Fig 1.1 shows a gentle decline in prices from 15 Mar ‘02 to 15 Jan ’09, and an increasing trend afterwards. Irregularities in the overall trend are due to external factors such as the consumer demand for cars and the overall state of the economy. | Fig 1.3 | | Date | COE Price | Lag1 | 1-Jan-09 | \$3,089 | \$2,656 | 15-Jan-09 | \$200 | | 1-Feb-09 | \$689 | | 15-Feb-09 | \$4,889 | \$3,089 |
(15-Jan-09, \$200)

(15-Jan-09, \$200)

After a regression analysis of COE Prices against Time, the percentage error between actual and fitted values in Fig 1.2 reveals 2 outliers in the dataset (as circled) that occur on 15 Jan and 1 Feb ‘09. Corresponding values falling on these dates were removed from the data set to ensure forecast accuracy. This results in a discrepancy in Lag1 prices as shown in Fig 1.3. By definition, the Lag1 Price of a current period should be the actual Price of its immediate previous period. However, the original Lag1 Price on 15 Feb ‘09 is now \$3089 instead of \$689, due to the omission of the outliers. To avoid this, we may replace the 2 outlying prices using a centered moving average model, which is based on the existing prices before 15 January 2009 and after 1 February 2009. However, this method is biased in assuming that the prices at those points are going to follow the same trend. 2. Analysis and Forecasts of EXPLANATORY Variables
Running a Multiple Regression (MR) of Price against Bids, Quota, Bid Ratio, and

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