AFLAC share price in Q2 2011

It’s time to revisit our stock price model for Aflac Incorporated (AFL). This is a financial company in the S&P 500 list. We predicted the price using the CPI estimates published by the BLS on April 14, 2011. It was a preliminary model.  The share price was defined by the consumer price index of household furnishing and operations (HFO) and that transportation services (TS). The defining time lags are as follows: the HFO index leads the share price by 2 months and the TS by 4 months. The best-fit 2-C model for AFL(t) was as follows:

AFL(t) =  -5.02HFO(t-2) – 2.87TS(t-6)  + 20.42(t-1990) + 997.71

where AFL(t) is the AFL share price in U.S. dollars,  t is calendar time.

 In April 2011, we predicted that “During the second quarter of 2001, the share price has to decrease to the level of $50.”   In May 2011, the monthly closing price was $47.49 and fell to $46.68 in June. Our prediction was correct considering the ambiguity of the monthly closing price as the best measure of stock prices. Figure 1 depicts the high and low monthly prices for an AFL share together with the predicted and measured monthly closing prices (adjusted for dividends and splits). As a rule, the predicted prices is well within the bounds of the share price uncertainty and leads by two months.  

We will model the evolution of the AFL price in Q3 2011 when the CPI components of the model are published by BLS.

Figure 1. Observed and predicted AFL share prices.

SunTrust Banks share in Q2 2011

In April 2011, we made the following prediction for SunTrust Banks (STI) share price: “… In the second quarter of 2011, the price may drop to the level of $23 (and then to $18) from the current $28“.

This prediction was obtained from a model based on the consumer price index of food less beverages (FB) 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. Therefore, the model has a natural 4-month forecast horizon.. 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. Figure 1 displays the model and actual prices. The STI actual price has fallen from $28.83 in March to $25.8 in June 2011. We have overestimated the fall but it is still within the uncertainty bounds defined by high/low monthly prices. We expect the price to fall in July 2011.

Figure 1. Observed and predicted STI share prices with monthly high/low (adjusted) prices

On the successful prediction of the HPQ share price in Q2 2011

Three months ago, we presented a model for HPQ stock price based on the decomposition into a weighted sum of two CPI components. We predicted the evolution of the monthly closing price (adjusted for dividends and splits) four months ahead using the CPI estimates published by the BLS on April 14.

The long term model is defined by the index of food without beverages (FB) and that of rent of primary residency (RPR). The former CPI component leads the share price by 4 months and the latter one leads by 5 months. Figure 1 depicts the overall evolution of both involved indices through March 2011. The best-fit 2-C model for HPQ(t) was as follows:

HPQ(t) = -3.34F(t-4) + 3.41RPR(t-5) + 0.51(t-1990) – 85.44

The predicted curve is shown in Figure 2 and covers the period between July 2003 and March 2011. In the second quarter of 2011, the model predicted the share price to fall to the level of $37 in June 2011 and then to $33 by the end of July 2011. Figure 3 demonstrates that this prediction was almost correct and the closing price of June 2011 is $36.4.

The U.S. Bureau of Labor Statistics will publish the estimates for the involved CPI components for June 2011 only in the middle of July. We are going to revise the current HPQ model and publish our prediction for the third quarter of 2011. Meanwhile, we expect a HPQ share to fall in July 2011 to the level of $33.

Figure 1. Evolution of the price of FB and RPR.

Figure 2. Observed and predicted HPQ share prices in March 2011. The contemporaneous prediction is shown by red line. Black diamonds present the original line shifted 4 months ahead, i.e. the model. We expect the price to fall down to $33 in July 2011.

Figure 3. The evolution of a HPQ share price as predicted in March 2011 and the actually observed monthly closing price (adjusted for dividends and splits) between April and June 2011.

 Update.
The monthly closing price is one of many measures of stock prices. One can average daily or hourly prices over one month and model them instead of the monthly closing price. Therefore, the predicted prices should be considered in the framework of the uncertainty in actual prices. Figure 4 depicts the predicted and observed monthly closing prices for HPQ together with (adjusted) monthly low and high prices. The predicted price is well inside the uncertainty of the observed one but four months ahead of it.

Figure 4. Monthly observed and predicted closing prices together with monthly low and high prices.

The IEA projection for oil

The International Energy Agency has issued a new oil price projection through 2016:
For oil, the projections are based on prevailing futures prices, which form an assumption as opposed to a price forecast. The crude price assumption used in the outlook averages $103 per barrel, or around $20 more than in last year’s MTOGM.

We also presented a projection for oil price through 2016 which is based on the presence of a sustainable linear trend in the difference between the core and headline CPI in the USA. This price will be progressively decerasing to the level of $35 to $50 per barrel in 2016. It would be interesting to compare these prejections in, say, 3 years.

Oil price will be decreasing through the rest of 2011. CPI vs core CPI

The U.S. Bureau of Labor Statistics has reported the estimates of various consumer price indices for May 2011. According to our schedule, we have to revisit the difference between the headline and core CPI only in July 2011. However, the new estimates likely manifest a short-term turn in the difference which is worth mentioning.

Figures 1 and 2 briefly introduce our concept of sustainable (quasi-linear) long-term trends in the difference between the headline and core CPI in the U.S. There were two clear periods of linear behaviour: between 1981 and 1999 and between 2002 and 2009. A natural assumption of the future evolution of the difference was that a new trend has to emerge around 2010 after a short period of very high volatility. 

Figure 1. Linear regression of the difference between the core CPI and CPI for the period from 1981 to 1999 (R²= 0.96 the slope is 0.67) and linear regression of the difference between the core CPI and CPI between 2002 and 2009 (R²=0.91, and the slope is -1.59). 

Accordingly, Figure 2 illustrate this hypothesis with the reversion (like mirror reflection) of the trend between 2002 and 2009. We expected this new trend with a positive slope to be developed between 2008 and 2011, as shown by the solid red line. Against our expectations, after a year of “right” evolution in 2010 the difference fell to the zero line again.

Figure 2. The evolution of the difference between the core and headline CPI since 2002.

The May 2011 estimates suggest the end of the fall in the difference and a pivot to the long-term trend (solid red line in Figure 2). Figure 3 depicts the most recent period with a clear turn in May 2011. Thus, we expect the difference will return to the long-term trend by the end of 2011. This return should be accompanied by a remarkable drop in the index price of energy which was the driver of the headline CPI in 2011.  Hence, ol price will be falling during the rest of 2011.

Figure 3. The evolution of the difference between the core and headline CPI since 2010.

Recession? In 2012-2013!

Is a new recession coming? This is currently one of hot questions in economic blogosphere. We expect it in 2012 and 2013. Our prediction is based on a quantitative growth model.

The first post in this blog was devoted to real GDP growth and its relation to the change in a specific age population. We have presented a number of growth models for various developed counties and validated them by new data. The original model  for the U.S. links the change rate of real GDP per capita, dlnG/dt, to the change in the number of 9-year-olds, dlnN9/dt, and the reciprocal value of the attained level of GDP per capita, A/G:

dlnG/dt= A/G + 0.5dlnN9/dt (1)

where A is an empirically derived constant. One can rewrite (1) relative to N9 and obtain the following equation in a discrete form:

N9(t) = N9(t-1)[2.0( dlnG - A/G) + 1] (2)

where dt=1 year.

Figure 1 presents the result of the N9 modeling between 1960 and 2005. The agreement between the measured and predicted N9 is excellent and we have shown that these time series are cointegrated. Our model has passed all rigorous econometric tests and can be used for GDP forecasts when the quality of population estimates is good enough.

Figure 1. Measured number of 9-year-olds in the U.S. and that predicted from real GDP per capita.

After 2003, the U.S. Census Bureau has been publishing extremely smoothed and thus biased population estimates, which are not appropriate for the purposes of real GDP prediction. This unfortunate situation might be resolved only after the 2010 census. We do not have quantitative estimates of the 9-year-old population yet but can use the age pyramid presented in Figure 2, which we borrowed from the U.S. Census Bureau.

At first glance, the 2008-2009 recession was induces by a negative value of dlnN9/dt, as one can judge from the number of 12- and 11-year olds. These people were 9-year-olds three and two years ago. One should not forget that younger cohorts accumulate more and more people with time due to intensive immigration and thus the numbers of people above 12 years of age are all biased up relative to the younger generations.

 

The number of 10- and 9-year-olds is slightly higher than in two older cohorts, and thus, we observe a period of positive real economic growth in 2010 and in 2011(the growth rate of real GDP per capita is about 1% per year lower than that of the overall GDP). However, the fall in N8 and N7 (male) almost guarantees a new recession in 2012-2013. Hence, a new recession is around the corner. We will present a more accurate quantitative estimate when the 2010 census data are available.

Oil price in May

In 1 minute, the BLS will report a number of producer price indices, icluding  the price index of crude petroleum.  Oil price in May was fluctuating around $100 per barrel. In April, the average price was closer to $110. Hence, we expect a dramatic fall in the oil price index from its current level.

Update. June 14, 14:33
As expected, the oil index has fell from 309.8 to 275.8, i.e. by ~11%. In June, this trend is extended. As we forecasted, oil price and thus the price index of motor fuel will be decreasing into 2011. It may be the cause of employment-population ratio growth and fall in the rate of unemployment.