Franklin Resources' rally may come to end

In this article, we revise our tentative pricing model for Franklin Resources (NYSE: BEN) presented on March 18, 2012.  According to Yahoo.com “The firm provides its services to individuals, institutions, pension plans, trusts, and partnerships. It manages, through its subsidiary, separate client-focused equity, fixed income, and balanced portfolios.” BEN is a financial company and we analyzed it three years ago as a candidate for bankruptcy. (Unlike Lehman Brothers, Freddie Mac, Fannie Mae and many other financial companies, Franklin Resources has never been near the zero line of share price.) In March 2012, our quantitative model, which foresaw the evolution at a five month horizon, signaled a negative correction to BEN’s share price. We expected that the price would likely fall in the second quarter of 2012 and then would stay at $105 in 2012Q2. In February 2012, the monthly closing (adjusted for splits and dividends) price was at the level of $117.07, in March - $123.44, and in April - $124.91 (all reading are borrowed from finance.yahoo.com). After a large negative correction in May the price fell to $106.28 and was $110 in June. Therefore, the prediction was strikingly accurate in time and size. The revised model based on the monthly closing prices through October 2012 and consumer price indices available for the same period, shows a possibility of a further increase in the price at a four months horizon. The price is expected to rise to $134 in January 2012 with the current (Nov. 23) level of $133.18. This means that BEN’s price has reached its January’s level and may stall at the current level. After a six month period of fast growth (from $106 to $133) and the above market return (~20%) the probability of the growth extension into 2013 cannot be high. One should not exclude that now is the best time to fix profit.  

We presume that any share price can be represented as a weighted sum of two consumer price indices (not seasonally adjusted in our model) which may be leading the share price by several months. Our model also includes a linear time trend and an intercept in order to remove mean and trend components from all involved time series.  The intuition behind our pricing model is obvious – we link a given share to those goods and services which are produced/provided by the company. In order to provide a dynamic reference we also introduce in the model some relative and independent level of prices (also expressed by CPIs). Hence, one needs two different CPIs to define the model. These CPIs we select from a big set of 92 CPIs by minimizing the residual model error.

In March 2012, the tentative model was driven by the consumer price index of food at home, FH, leading the price by five months and the index of other goods and services, O, which led by nine months. In the revised model, the former index is replaced by the index of food without beverages, FB, which leads the share price by four months. Both food related indices are very close, as Figure 1 shows. The tentative and revised pricing models are as follows: 

BEN(t) = -5.47FH(t-5) – 1.81O(t-9) – 59.55(t-2000) + 1327.36, February 2012  

BEN(t) = -7.33FB(t-4) – 1.52O(t-9) – 69.58(t-2000) + 1536.22, October 2012   

where t is calendar time.  The standard error between July 2003 and October 2012 is $7.36 ($7.55 in March). 

Figure 2 depicts the observed and predicted monthly closing prices since 2003 and also provides the high/low monthly prices, which may serve as the estimates of uncertainty in the monthly price. (One can model the monthly high or low price instead of the closing one.) At a four month horizon, the price is expected to grow to the final level of $134. Figure 3 shows that BEN’s price is currently very close to the predicted one.  

Figure 1. The evolution of defining CPIs.

Figure 2. Observed and predicted BEN share prices together with the high/low monthly prices.

Figure 3 . The standard model error.

Goldman Sachs may rise to $133 in January 2013

We have been trying to build a preliminary pricing model for Goldman Sachs (NYSE: GS) since 2008. This company was included in our study of bankruptcy cases in the USA. All in all, the model was not stable over time and the prediction for 2009 was not fully correct.  Originally, the stock price was defined by the index of housing operations (HO) and that of food away from home (SEFV).  In January 2011, we presented an updated model as based on the CPIs available till November 2010 and the December monthly closing (adjusted for splits and dividends) price of GS. In the updated model, the defining CPIs are the index of other food at home (OFH) and the housing index (H). Thus, the difference between the preliminary and the updated model was not too large because the pairs of defining indices are very close. Here we present a revised model, which includes new data obtained since December 2010. The revised model shows that GS share may grow to $133 from its current level of $118. This might be a good long idea together with that for Prudential Financial.

The concept of share pricing based on the link between consumer and stock prices has been under development since 2008. In the very beginning, we found a statistically reliable relationship between ConocoPhillips’ stock price and the difference between the core and headline consumer price index (CPI) in the United States. Then we extended the pool of defining CPIs to 92 and estimated quantitative models for all companies from the S&P 500. The extended model described the evolution of a share price as a weighted sum of two individual consumer price indices selected from this large set of CPIs. We allow only two defining CPIs, which may lead the modeled share price or lag behind it. The intuition behind the lags is that some companies are price setters and some are price takers. The former should influence the relevant CPIs, which include goods and services these companies produce. The latter lag behind the prices of goods and services they are associated with. In order to calibrate the model relative to the starting levels of the involved indices and to compensate sustainable time trends (some indices are subject to secular rise or fall) we introduced a linear time trend and constant term. In its general form, the pricing model is as follows:

sp(t_j) = Σb_i∙CPI_i(t_j-t_i) + c∙(t_j-2000 ) + d + e_j                 (1)    

where sp(t_j) is the share price at discrete (calendar) times t_j, j=1,…,J; CPI_i(t_j-t_i) is the i-th component of the CPI with the time lag t_i, i=1,..,I (I=2 in all our models); b_i, c and d  are empirical coefficients of the linear and constant term; e_j is the residual error,  whose statistical properties have to be scrutinized.

By definition, the bets-fit model minimizes the RMS residual error. It is a fundamental feature of the model that the lags may be both negative and positive. In this study, we limit the largest lag to eleven months. System (1) contains J equations for I+2 coefficients. We start our model in July 2003 and the share price time series has more than 100 points. To resolve the system, standard methods of matrix inversion are used.  A model is considered as a reliable one when the defining CPIs are the same during the previous eight months. This number and the diversity of CPI subcategories are both crucial parameter.  For example, Table 1 lists defining parameters for GS between March and October 2012. For each month, the best model is based on the same defining CPIs – the consumer price index of food and beverages, F, and the index of owners’ rent of primary residence, ORPR.  In all cases, the lags are the same: three and two months, respectively. Other coefficients and the standard error suffer just slight oscillations or drifts (e.g. c and d).  It is important to stress again that all models for months except October also include those with future CPIs relative to the given month. Table 1 confirms that no future CPIs drive the share price in March 2012. The best fir model is always based on the past values of F and ORPR, at least since March 2012.

Figure 1 depicts the overall evolution of both involved consumer price indices: F and ORPR. It also presents the evolution of two defining indices from the previous model: the index of other food at home, OHF, which is a part of F, and the index of housing, H, with ORPR representing a part of H.  The OHF and H indices provided the best fit model between March 2010 and December 2010.  The best-fit models for GS(t) are as follows:  

GS(t) = -11.06OFH(t) +11.06H(t-12) - 1.82(t-2000) – 99.4, December 2010

GS(t) = -13.79F(t-3) +11.03ORPR(t-2) + 29.93(t-2000) + 33.75, October 2012      

The predicted curve in Figure 2 leads the observed price by two months. The residual error is of $14.52 for the period between July 2003 and October 2012. The price of a GS share is relatively well defined by the behaviour of the two defining CPI components. Figure 2 also depicts the high and low monthly prices for the same period, which illustrate the intermonth variation of the share price. These prices might be considered as natural limits of the monthly price uncertainty associated with the quantitative model. Since 2009, the predicted price is well within the high/low band. Figure 3 displays the residual error. 

Table 1. The evolution of GS model since March 2012

Month	CPI1	t1	b1	CPI2	t2	b2	c	d	sterr,$
October	F	3	-13.795	ORPR	2	11.026	29.934	33.75	14.52
September	F	3	-13.791	ORPR	2	11.013	29.992	35.82	14.58
August	F	3	-13.786	ORPR	2	11.002	30.023	37.10	14.64
July	F	3	-13.759	ORPR	2	10.978	30.018	37.64	14.70
June	F	3	-13.730	ORPR	2	10.933	30.124	41.98	14.75
May	F	3	-13.703	ORPR	2	10.876	30.342	48.75	14.76
April	F	3	-13.661	ORPR	2	10.818	30.449	53.17	14.80
March	F	3	-13.786	ORPR	2	10.942	30.439	48.63	14.76

 

 

Figure 1. Evolution of F and ORPR. Also shown are defining CPI of the 2010’s model:  OFH and H.

Figure 2. Observed and predicted GS share prices. The prediction horizon is two months.

Figure 3. Standard error of the model $14.52.