Lately, we have developed and tested a concept of stock pricing as based on the dependence on consumer price index [1]. The model was originally introduced by Kitov and Kitov [1,2] and then applied to Exxon Mobile (XOM) and ConocoPhillips (COP) [4]. It is instructive to 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 [1] for ConocoPhillips (COP), as one of selected stocks from the S&P 500 list.
ConocoPhillips provides a good example of a company, which share price has been lagging behind defining components of the CPI. The model is seeking those two CPI components from 92 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 [1] 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 COP(t) is as follows:
COP(t)= 2.792MCS(t-3) – 4.477PETS(t-2) - 10.964(t-2000) – 267.54
where MCS in the index of medical care services (CUUR0000SAM2) leading the stock price by 3 months, PETS is the index of pets and pet products (CUUR0000SERB) leading by 2 months, (t-2000) is the elapsed time. Therefore, the predicted curve leads the observed price by 2 (!) months, i.e. contemporary readings of relevant CPI subcategories allow the prediction at a 2-month horizon. Figure 1 depicts the observed and predicted prices, the latter shifted two months back for synchronization. Figure 2 presents the residual error, with standard deviation of $3.78 for the period between July 2003 and February 2010.
The model predicts the price to grow in March and April 2010 to the level of $55 and $60.7, respectively. We will revisit this prediction in May 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 [1] for ConocoPhillips (COP), as one of selected stocks from the S&P 500 list.
ConocoPhillips provides a good example of a company, which share price has been lagging behind defining components of the CPI. The model is seeking those two CPI components from 92 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 [1] 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 COP(t) is as follows:
COP(t)= 2.792MCS(t-3) – 4.477PETS(t-2) - 10.964(t-2000) – 267.54
where MCS in the index of medical care services (CUUR0000SAM2) leading the stock price by 3 months, PETS is the index of pets and pet products (CUUR0000SERB) leading by 2 months, (t-2000) is the elapsed time. Therefore, the predicted curve leads the observed price by 2 (!) months, i.e. contemporary readings of relevant CPI subcategories allow the prediction at a 2-month horizon. Figure 1 depicts the observed and predicted prices, the latter shifted two months back for synchronization. Figure 2 presents the residual error, with standard deviation of $3.78 for the period between July 2003 and February 2010.
The model predicts the price to grow in March and April 2010 to the level of $55 and $60.7, respectively. We will revisit this prediction in May 2010.
Figure 1. Observed and predicted share prices.
Figure 2. Residual error of the model, σ=$3.78 for the period between July 2003 and February 2010.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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