Solving the Other PacBio Puzzle (non-bioinformatics)

Solving the Other PacBio Puzzle (non-bioinformatics)

Warning to readers:

(i) The following discussion is not related to bioinformatics.

(ii) It contains an example of real forecasting, not one of this type. We have found that people do not like our kind of forecasting.

In our earlier discussion on recent publications combining Illumina and PacBio reads, we left with an unsolved problem that was beyond the scope of the papers. However, it is not beyond the scope of our blog.

Needless to say, neither paper answers, or can possibly answer, an important question regarding PacBio in many peoples mind. Can any algorithm turn the slope of this curve upward?

Pacific Biosciences is an innovative Silicon Valley company with very smart people, yet its stock price peaked on the first day of IPO and is way below now. We lived in Silicon Valley for many years and found that the employees were trained to blame themselves for above kind of stock performance. Is that appropriate?

When we broaden our search, we find that stock prices of many other recently IPO-ed Silicon Valley type companies have similar features - GEVO, ZNGA, CDXS, AMRS , GRPN, FB - have similar structures. We know of several employees in the above companies, and many are highly intelligent. How did they all fail?

Here we present few observations that may provide an alternate explanation for the above phenomenon.


Observation 1. An working person usually earns the highest amount of money during his ages of 45-60. It is also the same period, when he starts building up his retirement nest egg.

For the first 21 years of life, a person runs on negative cash flow from societal stand point. Then he gets a junior level job, moves from job to job, starts family, etc. Only after another 20-25 years, he has enough stability and security to be able to save enough for retirement.

Observation 2.

Observation 1 is not that interesting from a societal point of view, because in a society there are always some babies, some college kids, some adults and some old people. However, let us consider a thought experiment, where we introduce a million babies in a country with population of another two million, and track the country from outside. What happens? In year 1, the country will start to import tons of baby food and diapers. In year 5, it will get pencils and erasers. In year 45-60 after beginning of the experiment, the country will have many net savers worrying about retirement. In year 70, it will need many doctors.

Interestingly, that experiment has already been tried on countries we know about.

Observation 3.Let us say you start an investment/retirement company in the above country. You will see that from year 45 onward, money will keep pouring into your account from all kinds of places. The country has surplus of people trying to retire, and they will need secure place to save.

If you start a Ponzi scheme, demographic tailwinds will help you run it for another 15 years without being detected. Cool, isn’t it? Intelligent readers may compare Madoff’s time line with the demographics graph posted in Observation 2.

Observation 4.Within USA, California started to become an attractive place for living after world war 2. Many WWII soldiers fighting in Pacific Front stayed in the bases of California, and liked the weather and lifestyle. You can plot the population growth of Los Angeles from data here.

When people move into a state or country from outside, it sees similar savings and investment pattern as in 1-3, but without the cost of raising babies. So, investments in California has both Ponzi components due to birth-related demographics and migration-related demographics. It is Ponzi-squared.

Observation 5.California has disproportionally large state government, and the government employees all save their retirement money in state pension funds. Older employees in many of the large private entities (Universities, Hospitals, etc.) have similar private pension funds. All those pension funds see similar inflow-outflow of money as described in 1-3.


How are the above observations related to PacBio and other crashing stocks?

Once you read and study enough about the demographic and social trends in California, you will find better explanation of various bubbles (housing, tech stock, VC, private equity, hedge fund) it experienced. Pension funds have surplus of money it wants to invest somewhere, and so it hands a part to VCs. The VCs invest the money into development of technologies, and then takes the companies to IPO, which is the process of dumping back the companies to pension funds.

Unfortunately, the year 60 for the peak of the demographics chart is arriving soon. The peak baby boom was in 1953-54, which means the year 60 is in 2013-14. Insiders know that the party is near end. That is where the urgency to dump all stock after IPO is coming from.


What happens next?

The various pension funds that were seeing an inflow of money over the last 15 years will see net outflow starting any time.

The pension funds will go broke starting with Calpers, which had been lying about its returns like Madoff. Compare this and this report, and you will understand the difference. You may also check this report to compute expected rate of return on your own [Hint. it will be lot less than 7.5%.

As we explained, as long as Ponzi demographics continues to sustain the trend, everything is ok. When it does not, look out below.

Written by M. //