Hewlett Packard should not fall below $20 per share

Hewlett Packard (HPQ) provides a good example of a successful share price prediction at a several month horizon.  We have already published our predictions at a four month horizon four times (July 2010, January 2011, March 2011, and July 2011). All predictions were based on our concept of share pricing as decomposition into a weighted sum of two CPI components.  We calculated the evolution of the monthly closing price (adjusted for dividends and splits). Here we test and update the model using data through September 2011.  

Originally, the long term model for HPQ share price was defined by the index of food without beverages (FB) and that of rent of primary residency (RPR). The former CPI component led the share price by 4 months and the latter one led by 5 months. Figure 1 depicts the overall evolution of both involved indices through August 2011. Below we present three best-fit 2-C models for HPQ(t) obtained at different times:  

HPQ(t) = -3.20FB(t-4) + 2.91RPR(t-5) + 3.64(t-1990) - 50.82, July 2010

HPQ(t) = -3.34FB(t-4) + 3.41RPR(t-5) + 0.51(t-1990) - 85.44, June 2011

HPQ(t) = -3.46FB(t-4) + 3.68RPR(t-5) – 0.72(t-1990) - 99.88, September 2011

where HPQ(t) is the price in US dollars, t is calendar time. All coefficients have been slightly drifting. This process expresses the trade-off between the linear trend in the difference between  the defining CPIs and the time trend term in the above equtions.  

The predicted curves are shown in Figure 2 (March and September 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.   

From Figure 2, we predict the price to stabilize around $20 because the current price level is below the predicted one. Therefore, one can expect the price not to drop below $20 per share.    

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

Figure 2. Observed and predicted HPQ share prices in March (upper panel) and September (lower panel) 2011. The contemporaneous prediction is shown by red line. In March, we expect the price to fall down to $33 in July 2011. In September, we predict the price to stabilize around $20.

Is Boston Scientific on the brink?

We posted on Boston Scientific (BSX) in January and April 2011 and presented a share price model for Boston Scientific as based on our stock pricing concept.  Both models were similar and included the consumer price index of housing (H) and the index of durable goods (DUR). (Figure 1 depicts the overall evolution of the involved indices.) The former defining CPI component led the share price by 5 month and the latter one by 3 months.  Here we update the original model using data through September 2011. The updated model has the same defining components and time lags with slightly different coefficients. Therefore, the original model provided a reliable prediction through the past year and further in the past. Currently, the best fit model predicts the share to fall below zero in the near future what is equivalent to bankruptcy. A similar prediction (negative share price) was obtained for Lehman Brothers and other financial institutions before they failed.  As an alternative, our model may fail with the change in the overall CPI trends.

                                                                                                                                                

The best-fit 2-C models (March and September) for BSX(t) are as follows:

BSX(t) = -1.41H(t-5) – 2.85DUR(t-3) – 0.09(t-1990) + 630.92, March 2011

BSX(t) = -1.46H(t-5) – 2.71DUR(t-3)  + 0.36(t-1990) + 615.69, September 2011   

where BSX(t) is the (monthly closing adjusted for splits and dividends) share price in US dollars,  t is calendar time.  Both coefficients are negative, and thus the increasing consumer prices result in decreasing share price. The slope of time trend is negligible.

Both models predicted the price at a three month horizon with standard deviation of $1.94 between July 2003 and September 2011 ($1.83 in March). The currently observed growth in the defining consumer price indices should drive the share price down. In the fourth quarter of 2011, the price may drop below zero.    

   

Figure 1. The evolution of H and DUR.  

Figure 2. Observed and predicted BSX share prices. Upper panel: March model with red curve representing the contemporaneous prediction. Lower panel: the updated prediction. The price is negative by the end of 2011.

Figure 3. The model residual, i.e. the difference between the observed and predicted BSX share prices. 

Avery Dennison share price will likely be falling further

In April 2011, we presented a model for Avery Dennison Corporation (AVY) based on our concept linking share pieces and consumer price indices. The share price model for Avery Dennison Corporation was defined by the index of food (F) and that of new and used motor vehicle (NUMV). In the original model, the former CPI component led the share price by 4 months and the latter one led by 2 months.

Here we revisit the model using the monthly closing prices (adjusted for splits and dividends) and CPIs for the period through September 2011. (The CPIs are available only for August 2011.) The principal result is that the underlying model is practically the same as six months ago with the same time lags but slightly different coefficients. In March 2011, we predicted a fall in the price which actually happened. Currently, the share price is overestimated if to consider that the predicted price expresses the right behavior. We expect that AVY stocks will be falling by the end of 2011 down to $16 per share from the September closing level $25.08.  

Figure 1 depicts the overall evolution of both involved indices between July 2005 and August 2011. These two defining components provide the best fit model between January 2010 and September 2011.  Both models, the original and the updated one, are shown below. The best-fit 2-C models for AVY(t) are as follows 

AVY(t) =  -4.24F(t-4) – 3.23NUMV(t-2)  + 23.29(t-1990) + 799.24 , March2011

AVY(t) =  -3.92F(t-4) – 2.70NUMV(t-2)  + 21.60(t-1990) + 710.60 , September 2011 

where AVY(t) is a share price in US dolalrs, t is calendar time. Relevant coefficients are both negative. The slope of time trend is positive.  There is some fluctuation in the coefficients caused by the uncertainty in measurements of both the stock prices and CPIs.  Nevertheless, both models provide an accurate prediction at a two-month horizon.  

The predicted curve in Figure 2 (both versions are depicted) leads the observed price by 2 months with the residual error of $2.57 ($2.68 in April) for the period between July 2003 and September 2011. The model residual for the same period is shown in Figure 3. The original model predicted the share price in the past and foresaw a fall in 2011 Q2.  

Figure 1. Evolution of the price of F and NUMV. 

Figure 2. Observed and predicted AVY share prices. Upper panel – March 2011; lower panel – September 2011. 

Figure 3. The residual error of the model. The mean residual error is 0.0 with the standard deviation of $2.57. Currently, the price is slightly overestimated.  

Another chance to sell oil futures

Two weeks ago, when oil was at $84,  I recommended  to sell oil futures before oil price falls to $79 and even lower. After this recommendation, oil actually fell down to $76 and could bring a 10% return. Today, oil is approaching $83, as we predicted five days ago. Therefore, a good time to sell oil futures is coming again. Below I reproduce some details of the model predicting oil price.

In May 2011, we predicted oil (WTI) price to fall to the level of $70 per barrel by the end of 2011. This is a monthly revision for September 2011. We consider the average oil price of $84 per barrel what is equivalent to the producer price index of 244 in September. (Actual estimate will be published by the Bureau of Labor Statistics in the middle of October.)
        Figure 1 compares our prediction with actual oil price in 2011. In August 2011, the predicted price is a bit higher than the measured one. In any case, we expect the price to fall by approximately $5 per month to the level of ~$70 in December 2011. We also expect the price to slowly fall through 2016 and put the uncertainty bounds for the long-term trend in oil price. The level of oil price in 2016 is between $30 and $60 per barrel. These bounds are also shown in Figure 1.

       

This part is the prediction of the current growth in oil price given days ago.

 A week ago, when oil price was at ~$79 per barrel, we recommended buying oil futures. The intuition behind this idea was that $79 is approximately $5 below the expected price for September. This is a disequilibrium which should be recovered in the short run. Today, oil price is at the level of ~84. This is the equilibrium level for September. A small hike in oil price is possible during the next few days. However, at a two-week horizon, oil price should fall again. Therefore, I recommend selling now and buying in approximately two weeks or when the price will be around $75. It will grow to the level of ~$82 to $85 in October or November.

Figure 1. Oil price prediction in 2011. The price is expected to fall by $5 per month between June and December 2011. The price level is ~$70 in December 2011. We also show the range of expected price evolution by 2016.

Disappointing Bernanke

Federal Reserve Chairman Ben Shalom Bernanke made several important statements in testimony to Congress's Joint Economic Committee that the Fed. In essence, they show the  impotence of economic theory and thus economic authorities basing their policies on wrong understanding. Several examples:
1. “.. Recent revisions of government economic data show the recession as having been even deeper, and the recovery weaker, than previously estimated; indeed, by the second quarter of this year--the latest quarter for which official estimates are available--aggregate output in the United States still had not returned to the level that it had attained before the crisis.”

Any economics, financial or monetary policy should include some expected level of uncertainty in real time measurements such as real GDP and inflation (the GDP deflator). If it is always a surprise, how can one build a reasonable response and policy? One should never characterize an economy with one number without uncertainty. It contradicts scientific methodology.

2. “Slow economic growth has in turn led to slow rates of increase in jobs and household incomes.”

This statement presumes that there can be a situation when slow growth may lead to higher rates of increase in jobs and incomes. Actually, all these processes are equivalent and no one leads to another. They coexist.

3. “ Consumer behavior has both reflected and contributed to the slow pace of recovery.”

This statement is beyond any understanding. Consumers are treated as a black box without any rules how “garbage in” is converted into “garbage out”. This is a typical economic statement which explains every deviation in real economic growth as consumer behavior expressed in demand/supply shocks. Nobody knows what drives these shocks and why the economy runs away from the balance. In a way, this explanation creates a malice loop without start and end.

4. “Other sectors of the economy are also contributing to the slower-than-expected rate of expansion. The housing sector has been a significant driver of recovery from most recessions in the United States since World War II. This time, however, a number of factors--including the overhang of distressed and foreclosed properties, tight credit conditions for builders and potential homebuyers, and the large number of "underwater" mortgages (on which homeowners owe more than their homes are worth)--have left the rate of new home construction at only about one-third of its average level in recent decades. “

This deserves a special attention. Here Ben unfolds reasons one layer down. The housing sector slumps due to a number of factors. These factors are obvious results of the overall economic slump. What raises again the question on the reasons of the economic slump itself, and this is not housing as one can judge.

5. “ Nonetheless, financial stresses persist.”

Thus, the current financial crisis is a process which does not depend on real economic growth and when it is over, the economy will rocket up. Does that mean that the financial crisis could be healed without economic growth, but as it is? I would expect that the financial crisis will end when real economic growth recovers. In my opinion, it will happen in 5 to 10 years.

6. “In view of the deterioration in the economic outlook over the summer and the subdued inflation picture over the medium run ...”

This is a mere declaration of the status quo. However, the inflation projection is right as we showed many years ago

Political Calculations on GDP in Q3

There is an interesting post by Ironman @ Political Calculations. The author predicts the possibility of recession in the third quarter of 2011. It is in line with our projections of real GDP per capita in the US for the next five years. This post also uses the term "inertia" which we consider  the key phenomenon in real economic growth.

Goldman Sachs on recession in Germany

Via Market Watch - Goldman Sachs foresees a period of recession in eurozone with Germany falling into negative growth in the forth quarter of 2011. In May 2011, we posted on recession in germany and showed that this period will be a lenghty one ( http://mechonomic.blogspot.com/2011/05/how-long-will-last-real-economic-growth.html) . Figure 1 reproduces  some details of our prediction  of real GDP per capita in Germany.

Figure 1. Observed and predicted rate of real GDP growth in Germany after the reunification.
Lower panel - The original curves are smoothed with MA(3).