A preliminary model for Cephalon share

After the model for Altero Corporation, we present a share pricing model for Cephalon (CEPH). The most recent model uses the monthly closing price as of April 2011 and the CPI estimates published on April 14, 2011. The tenants' and household insurance index (THI) leads by 2 months and the index of prescription drugs (PDRUG) leads by 9 months the CEPH share price.  The latter index might be directly related to Cephalon product. Figure 1 depicts the evolution of the indices which provide the best fit model, i.e. the lowermost RMS residual error, between November 2010 and March 2011.  The model is as follows:

CEPH(t) = -3.94THI(t-2) + 1.61PDRUG(t-9) – 10.04(t-1990) + 120.83

where CEPH(t) is a share price in US dollars, t is calendar time.

Both models are depicted in Figure 2. The residual error is of $5.00 for the period between July 2003 and March 2011.  2009. Notice that the PDRUG index has been growing at a high rate since the beginning and any fluctuation in this index has been directly mapped into the price, which is characterized by high volatility. The THI index has been rising steadily but slowly. 

Figure 1. Evolution of the price indices THI and PDRUG.

Figure 2. Observed and predicted CEPH share prices.

Altera Corporation share in 2012

Our stock pricing concept is very simple and is based on deterministic links between share prices and prices of goods and services included in the consumer price index, CPI. Literally, we decompose a share price (monthly closing price adjusted for splits and dividends) into a weighted sum of two individual CPI components, linear time trend component and constant free term. We allow positive and negative time lags between all variables in the relationship and seek to minimize the RMS model error by varying the involved coefficients. The set of CPI components consists of 92 independent price indices of different level: from major (overall and core CPI) to very small (e.g. photo and related materials). When the modeled share lags behind both defining CPI components we have a deterministic model predicting at a horizon of the smallest time lag. This concept gives excellent results in terms of the model error and very stable pricing models which are valid during several years. In 2008, the model successfully predicted bankruptcy of some major banks, including Lehman Brothers. Fannie May and Freddie Mac. We were able to forecast negative share prices several months ahead [1].  One can also find in [1] a formal model description.  

In this blog, we present and track successful models from the S&P 500 list. They are numerous. For other companies from the S&P 500 list, we also have accurate quantitative models, but they are not deterministic since at least one of defining CPI components lags behind the modeled price. We revisit (recalculate) all models every quarter using new data and report on successful models. In some cases, a model should hold for a year before we publish it.

 In this post, we present a share pricing model for Altera Corporation (ALTR). It belongs to Technology sector and is specialized in semiconductors.  A preliminary model was obtained in September 2010 and covered the period from January 2010. This old model included the same indices as the current one: the price index of food away from home (SEFV) and the index of communication (CO).  The latter index makes some sense as using semiconductors.

The most recent model uses the monthly closing price as of April 2011 and the CPI estimates published on April 14, 2011. The SEFV index leads by 6 months and the CO index leads by 10 months the ALTR share price.  Figure 1 depicts the evolution of the indices which provide the best fit model, i.e. the lowermost RMS residual error, between January 2010 and March 2011.  The model is as follows:

ALTR(t) = -2.84SEFV(t-6) + 2.88CO(t-10) +22.54(t-1990) – 40.23

where ALTR(t) is a share price in US dollars, t is calendar time.

Both models are depicted in Figure 2. The residual error is of $2.02 for the period between July 2003 and March 2011.  The dependence on time has been strong enough ($22.5 per year) to overcome negative influence of both indices since 2009. Notice that the index of food away from home has been growing at a lower rate since 2009 and the index of communication has been falling steadily since the beginning.  From Figure 2, one can expect the share will be stable at the level of $42 during the next half a year.

 

Figure 1. Evolution of the price indices SEFV and CO.

Figure 2. Observed and predicted ALTR share prices.

1. Kitov, I. (2010). Modelling share prices of banks and bankrupts, Theoretical and Practical Research in Economic Fields, ASERS, vol. I(1(1)_Summer) pp. 59-85

Celgene Corporation stocks will not be growing

Here we present a share pricing model for Celgene Corporation (CELG). A preliminary model was obtained in September 2009 and covered the period from October 2008. This old model included the same indices as the current one: the price index of food at home (FH) and the index of housing (H). The most recent model uses the monthly closing price as of April 2011 and the CPI estimates published on April 14, 2011. The FH index leads by 6 months and the H index is synchronized with the CELG share price.  Figure 1 depicts the evolution of the indices which provide the best fit model, i.e. the lowermost RMS residual error, between July 2008 and March 2011.  The model is as follows:

CELG(t) = -1.87FH(t-6) + 2.86H(t-0) +4.21(t-1990) – 247.59

where CELG(t) is a share price in US dollars, t is calendar time.

The observed and predicted prices are depicted in Figure 2. The residual error is $3.91 for the period between July 2003 and March 2011.  Since the dependence on time is weak ($4.2 per year) and the index of food at home had a spurt during the last four months ($7 since December 2010), one can expect a fall by $10 in the next half a year. We assume that the housing index is not going to grow fast.

Figure 1. Evolution of the price indices FH and H.

Figure 2. Observed and predicted CELG share prices.

Loews Corporation share price

Here we present a share pricing model for Loews Corporation (L) (see a brief description of the concept here). A preliminary model was obtained in September 2009 and covered the period from October 2008. This old model included the index of food without beverages (FB) and the index of transportation service (TS).

The most recent model also uses the monthly closing price as of April 2011 and the CPI estimates published on April 14, 2011. Currently, the defining indices are almost the same: the index of food (F) and the TS index. The F index leads by 5 months and the TS index by 4 months.  Figure 1 depicts the evolution of the indices which provide the best fit model, i.e. the lowermost RMS residual error, between December 2009 and March 2011.  The models are as follows:

L(t) = -2.03F(t-5) – 2.12TS(t-5) +28.23(t-1990) +448.98

where L(t) is the share price in US dollars, t is calendar time.

Both models are depicted in Figure 2. The predicted curves lead the observed ones by 4 months. The residual error is of $2.46 for the period between July 2003 and March 2011.  In the second quarter of 2011, the model foresees a fall to the level of $39 per share. 

Figure 1. Evolution of the price indices F and TS.

Figure 2. Observed and predicted L share prices.

Cardinal Health in Q2 2011

Cardinal Health (CAH) is one of the companies with a long story of successful modeling. In September 2009, we first estimated a preliminary two-component model from the full set 73 CPI components. As in all our models, we predict the monthly closing price adjusted for splits and dividends. Here, we revisit the previous model using all data available on April 24^th and an extended set of CPIs.  Also, all time series are 18 months longer what provides a better resolution and reliability.

For CAH, the defining indices are as a year and two years ago: the index of dairy and related products (DAIRY) and the index of pets, pet products and services (PETS). The CPI components are both leading by 2 months. Figure 1 depicts the evolution of both indices which provide the best fit model, i.e. the lowermost RMS residual error, between July 2008 and March 2011:  

CAH(t) = -0.38DAIRY(t-2) – 1.69PETS(t-2) +11.33(t-1990) + 136.12

      

where CAH(t) is the share price in US dollars, t is calendar time.

The predicted curve in Figure 2 is synchronized with the observed one. The residual error is of $2.58 for the period between July 2003 and March 2011.  The next move in the price is likely down according to the growth in both defining indices.

Figure 1. Evolution of the price indices DAIRY and PETS.

Figure 2. Observed and predicted CSC share prices.

Computer Science Corporation will not be growing

A year ago, we first presented a share price (monthly closing price adjusted for splits and dividends) model for Computer Science Corporation (CSC). In this post, we revisit the previous model using all data available on April 24th.  Longer time series provide a better resolution between defining CPIs and higher model reliability.

For CSC, the defining indices are as a year and two years ago: the index of motor vehicle parts (MVP) and the index of sporting goods (SPO). The CPI components are leading by 0 and 5 months, respectively. Figure 1 depicts the evolution of both indices which provide the best fit model, i.e. the lowermost RMS residual error, between July 2008 and March 2011:  

CSC(t) = -3.83MVP(t-0) + 3.16SPO(t-5) +16.31(t-1990) – 137.20

where CSC(t) is the share price in US dollars, t is calendar time.

The predicted curve in Figure 2 is synchronized with the observed one. The residual error is of $3.28 for the period between July 2003 and March 2011.  Since the MVP index has been growing since 2002 and the SPO index has a slight negative trend, the share price will not be growing in the near future.

Figure 1. Evolution of the price indices MVP and SPO.

Figure 2. Observed and predicted CSC share prices.

Comparison of SunTrust Banks (STI) and Franklin Resources (BEN) models

The price model for SunTrust Banks (STI) is a brand new one.  Like Franklin Resources (BEN) reported four days ago, it is a financial company and was analyzed previously as a candidate for a bankruptcy [1]. The newly obtained model is based on is our stock pricing concept and includes the consumer price index of food less beverages (FB) (it was food at home, FH,  for BEN) and the index of tobacco and tobacco products (TOB). The former defining CPI component led the share price by 4 months and the latter one by 6 months (5 and 8 months, respectively for BEN). Therefore, the model has a natural 4-month forecast horizon. It is worth noting that there are two financial companied driven by the same CPIs.

Figure 1 depicts the overall evolution of the involved indices. These two defining CPI components provide the best fit model between March 2011 and July 2010.  Both coefficients are negative, as in many models already reported in this blog, and thus the increasing prices result in decreasing share price. (However, the sensitivity to the TOB index is much lower than to the FB index, as was also valid for BEN). The slope of time trend is positive and would provide a $36 increment per year if both CPIs are fixed. The best-fit 2-C model for STI(t) is as follows:

STI(t) = -5.46FB(t-4)  – 0.19TOB(t-6) + 36.07(t-1990) + 627.06     

where STI(t) is a share price in US dollars, t is calendar time.  The standard deviation of $3.77  between July 2003 and March 2011. There was no growth during  the first quarter of  2011 since no one of the defining indices has demonstarted any big movement. In the second quarter of 2011, the price may drop to the level of $23 (and then to $18) from the current $28, as follows from the predicted and observed curves presented in Figure 2.  Figure 3 displays the model error.

Figure 1. The evolution of the difference between FB and TOB.

Figure 2. Observed and predicted STI share prices. The predicted curve leads by 4 months and was shifted ahead for synchronization with the observed one. Notice excellent prediction of major turns in the price.

Figure 3. The model residual, i.e. the difference between the observed and predicted STI

1. Kitov, I. (2010). Modelling share prices of banks and bankrupts, Theoretical and Practical Research in Economic Fields, ASERS, vol. I(1(1)_Summer) pp. 59-85