In the previous post, we described the pricing model for ConocoPhillips shares as based on the concept of stock dependence on consumer price index. He we apply the model to Exxon Mobil (XOM). As for COP, we will track the performance of the model and compare observed and predicted prices.
Since March 18, the readings of the headline CPI and its components for February 2010 are available (we retrieve all CPI data from http://www.bls.gov/data). Here we update our model for XOM as one of selected stocks from the S&P 500 list.
Exxon Mobil provides an example of a company, which share price has been leading defining components of the CPI. As always, the model is seeking those two CPI components from a large number of pre-selected ones, which minimize the difference between observed (monthly closing price adjusted for dividends and splits) and predicted prices for the period between July 2003 and February 2010. The original model [2-4] included only nine top CPI subcategories and that obtained in [1] - 34 different CPI indices. Currently, the set of CPI components is extended to 92. This is not the final set, however.
The two-component (2-C) model also includes free term (constant) and linear time term [5-8], which compensates well know linear (time) trends between various CPI components. The best-fit 2-C model for XOM(t) is as follows:
XOM(t)= 3.817RPR(t-4) – 3.983MVR(t-0) + 11.64(t-2000) – 26.88
where RPR in the index of rent of primary residency (CUUS0000SEHA) lagging the stock price by 4 months, MVR is the index of motor vehicle maintenance and repair (CUUR0000SETD) leading by 0 months, (t-2000) is the elapsed time. Therefore, the predicted curve should lag the observed price by 4 months. In other words, the price of a XOM share defines the behaviour of rent of primary residence. Figure 1 depicts the observed and predicted prices, the latter shifted four months ahead for synchronization. The model residual error, i.e. standard deviation, is of $2.76 for the period between July 2003 and February 2010.
The model does not predict the share price. Therefore, it will not be necessary to revisit this prediction before September 2010.
Since March 18, the readings of the headline CPI and its components for February 2010 are available (we retrieve all CPI data from http://www.bls.gov/data). Here we update our model for XOM as one of selected stocks from the S&P 500 list.
Exxon Mobil provides an example of a company, which share price has been leading defining components of the CPI. As always, the model is seeking those two CPI components from a large number of pre-selected ones, which minimize the difference between observed (monthly closing price adjusted for dividends and splits) and predicted prices for the period between July 2003 and February 2010. The original model [2-4] included only nine top CPI subcategories and that obtained in [1] - 34 different CPI indices. Currently, the set of CPI components is extended to 92. This is not the final set, however.
The two-component (2-C) model also includes free term (constant) and linear time term [5-8], which compensates well know linear (time) trends between various CPI components. The best-fit 2-C model for XOM(t) is as follows:
XOM(t)= 3.817RPR(t-4) – 3.983MVR(t-0) + 11.64(t-2000) – 26.88
where RPR in the index of rent of primary residency (CUUS0000SEHA) lagging the stock price by 4 months, MVR is the index of motor vehicle maintenance and repair (CUUR0000SETD) leading by 0 months, (t-2000) is the elapsed time. Therefore, the predicted curve should lag the observed price by 4 months. In other words, the price of a XOM share defines the behaviour of rent of primary residence. Figure 1 depicts the observed and predicted prices, the latter shifted four months ahead for synchronization. The model residual error, i.e. standard deviation, is of $2.76 for the period between July 2003 and February 2010.
The model does not predict the share price. Therefore, it will not be necessary to revisit this prediction before September 2010.
Figure 1. Observed and predicted XOM share prices.References[1] Kitov, I. (2010). Deterministic mechanics of pricing. Saarbrucken, Germany, LAP Academic Publishing.
[2] Kitov, I., Kitov, O., (2009). Modelling selected S&P 500 share prices, MPRA Paper 15862, University Library of Munich, Germany, http://mpra.ub.uni-muenchen.de/15862/01/MPRA_paper_15862.pdf
[3] Kitov, I., Kitov, O., (2009). Predicting share price of energy companies: June-September 2009, MPRA Paper 15863, University Library of Munich, Germany, http://mpra.ub.uni-muenchen.de/15863/01/MPRA_paper_15863.pdf
[4] Kitov, I., (2009). Predicting ConocoPhillips and Exxon Mobil stock price, Journal of Applied Research in Finance, Spiru Haret University, Faculty of Financial Management and Accounting Craiova, vol. I(2(2)_ Wint), pp. 129-134.
[5] Kitov, I., Kitov, O., (2008). Long-Term Linear Trends In Consumer Price Indices, Journal of Applied Economic Sciences, Spiru Haret University, Faculty of Financial Management and Accounting Craiova, vol. 3(2(4)_Summ), pp. 101-112.
[6] Kitov, I., (2009). Apples and oranges: relative growth rate of consumer price indices, MPRA Paper 13587, University Library of Munich, Germany, http://mpra.ub.uni-muenchen.de/13587/01/MPRA_paper_13587.pdf
[7] Kitov, I., Kitov, O., (2009). A fair price for motor fuel in the United States, MPRA Paper 15039, University Library of Munich, Germany, http://mpra.ub.uni-muenchen.de/15039/01/MPRA_paper_15039.pdf
[8] Kitov, I., Kitov, O., (2009). Sustainable trends in producer price indices, MPRA Paper 15194, University Library of Munich, Germany, http://mpra.ub.uni-muenchen.de/15194/01/MPRA_paper_15194.pdf
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