The evolution of Anadarko Petroleum’s (NYSE: APC) share price is of interest since it is different from that demonstrated by Apache (APA) which is presented in our previous article. Both companies are likely driven by the same forces but their current prices are on opposite sides from their fundamental levels estimated with our pricing model. According to the previously developed procedure, we also compare the APC pricing model to that for ConocoPhillips (COP), which is a recognized benchmark for energy related companies.

Imagine that you have to predict (describe) the evolution a share price for a company from Energy sector. It would not be a big mistake to assume that this share price is likely to be driven by the change in the overall energy price or some of its components (we use price indices for modeling). Even if the company does not change its production the overall increase in the price of its product should be manifested in the overall profit and thus the share price. On the other hand, when the overall price level (as expressed by the headline CPI) rises faster than the energy price index (say, 10% vs. 1% per year, respectively) one should not expect the energy company to gain extra pricing power. The company would rather suffer a share price decline. Thus, considering the secular increase in the overall price level, it is not the absolute change in energy prices what affects the stock price but its current deviation from some energy independent price. We have proposed to use the simplest model as based on the difference between the headline CPI,

*C*, and the core CPI,*CC*, without any time lag between these indices and the share price. The headline CPI includes all kinds of energy and thus provides the broadest proxy to the energy price index. The core CPI excludes energy (and food) and thus may represent the energy independent and dynamic reference.First, we present here the model for COP. We use it as a benchmark showing the quality of the concept and its predictive power. Figure 1 depicts the observed and modeled COP prices. Taking into account that both defining CPIs might be not the best proxies to some true defining indices, the accuracy of prediction is very good. We consider the predicted price as a fundamental one, i.e. the price which is defined by two economy-wide or fundamental indices. Quantitatively, we have estimated the following relationships to minimize the model error between 1998 and 2012:

COP(t) = 72.3 – 5.35(CC(t) - C(t)) (1)

where COP(t) is the share price in U.S. dollars at time t.

Figure 1. Historic (monthly closing) prices for COP (black line) and the scaled difference between the core CPI and the headline CPI (red line).

Now we may suggest that the COP model determines the benchmark behavior for an energy related company, i.e. its share price has to gravitate to the fundamental price defined by the difference between the core and headline CPI. In our previous article, we estimated an empirical model for APA:

APA(t) = 110 – 8.1(CC(t) - C(t))

For APC, the best fit relationship is as follows:

APC(t) = 67 – 4.7(CC(t) - C(t)) (2)

Figure 2 depicts both models, i.e. the observed and predicted prices for APA and APC. For APC, the overall agreement is relatively good but the deviation from the predicted price has been much higher since 2009. From Figure 2, the actual price is currently overvalued

**by $15. The underlying model is too crude, however, and we have developed several advanced APC models. The best from these advanced models shows that the current APC price is only slightly overvalued.**Figure 2. Historic (monthly closing) prices for APA (upper panel) and APC and the scaled difference between the core CPI and the headline CPI - relationship (2).

We have extended the original model and described the evolution of the APC share price as a weighted sum of two individual consumer price indices (or PPIs) selected from a large set of CPIs borrowed from the Bureau of Labor Statistics. We allow both defining CPIs (PPIs) lead the modeled share price. Additionally, we introduced a linear time trend on top of the intercept. As for many already presented companies, we have tested two principal pairs of CPIs: C and CC; CC and the index of energy, E, as well as the pair the PPI and the producer price index of crude oil, OIL. The best fit (as defined by standard error) model is obtained with the pair PPI and OIL:

*APC(t)= 3.28C(t) – 5.56CC(t-1) + 12.25(t-2000) + 323.56; sterr=$6.12 (3)*

*APC(t)= -2.79CC(t-2) + 0.32E(t) + 13.73(t-2000) + 326.49; sterr*

*=$5.80 (4)*

*APC(t)= -0.21PPI(t-10) + 0.14OIL(t-9) + 4.31(t-2000) – 19.95; sterr=$*

*5.48*

*(5)*

where APC(t) is the (monthly closing) share price in U.S. dollars. We allowed both time leads in (3) through (5) to vary between 0 and 12 months. Figures 3 through 5 depict the observed and predicted monthly prices from (3) through (5). For an oil company, it is not excluded that oil controls its price.

Figure 5 shows that the advanced model based on the producer price index of crude petroleum (domestic production) accurately predicts the current APC price. There were two major excursions in the first half of 2010 and in the fourth quarter of 2011. Both ended on the fundamental price curve. This behavior is very instructive – all deviations should return to the predicted curve.

Figure 3. The observed and predicted monthly closing prices for APC between July 2003 and March 2012. The model is based on C and CC.

Figure 4. The observed and predicted monthly closing prices for APC between July 2003 and |March 2012. The model is based on CC and E.

Figure 5. The observed and predicted monthly closing prices for APC between July 2003 and March 2012. The model is based on PPI and OIL.

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