This is a good example of a stable pricing model . We already reported on this case in July 2010. The model for Xilinx (NASDAQ:XLNX) is defined by the index of communication (CO-CUUR0000SAE2) and that of information and information processing (INF-CUUR0000SAE21). The former CPI component leads the share price by 4 months and the latter one leads by 11 months. From our past experience, the larger is the lag the more unreliable is the model, but this specific model has been valid since 2008.
These defining components provide the best fit model, i.e. the lowermost RMS residual error, between August 2009 and December 2010. The best-fit 2-C model for XLNX(t) is as follows:
XLNX(t) = -3.57*CO(t-4) + 4.21*INF(t-4) +1.88(t-2000) – 55.32
The predicted curve in Figure 2 leads the observed price by 4 months with the residual error of $1.89 for the period between July 2003 and December 2010. The model accurately predicts the share price in the past and foresees increasing price in the first quarter of 2011.
Figure 2. Observed and predicted XLNX share prices.
Figure 3. Residual error of the model. Mean residual error is 0 with standard deviation of $1.89. The largest errors were observed in 2004 and 2009.
1. Kitov, I. (2010). Deterministic mechanics