Climate Change Conspiracy Against us All


800,000-year Ice-Core Records of Atmospheric Carbon Dioxide (CO2)

QUESTION: Are you saying that CO2 is not a pollutant and we should not be concerned about rising levels?

OD

ANSWER: Correct. CO2 levels have been much higher than currently over the millennia. The Global Warming crowd has an agenda and the core of that is to reduce the population. They remain influenced by the Malthus theory and have been hell-bent on stopping population growth.

Over the past 100 million years, we have been in a decline in CO2 level dropping from 500 ppm to 200 ppm with an average of about 300 ppm. They refuse to address any of the historical evidence no less the cycle of life itself.

Humans exhale typically consists of 40,000 ppm to even 50,000 ppm of CO2. Should we be fined or extinguished because we are a major contributor to COs levels? Those who are demonizing CO2 as a “pollutant” fail to explain that in a room filled with people CO2 levels can commonly reach 2000 ppm with no apparent ill effects. Even the US Navy sets its limit for CO2 in submarines at 5000 ppm to avoid any measurable effect on sailors. NASA also sets similar limits for humans in spacecraft at the same basic level.

If you measure CO2 level where crops are growing or in a rain forest, they drop drastically because the plants suck it up for that is what they thrive on to live. If you want to lower CO2, then plant more crops and trees.

Thomas Malthus (1766-1834) had predicted that we would run out of food which started this entire theory about curtailing population growth which is really behind the whole Global Warming movement. In his 1798 book An Essay on the Principle of Population, Malthus observed that an increase in a nation’s food production improved the well-being of the populace. However, the improvement was temporary because it led to population growth, which in turn restored the original per capita production level.

In other words, mankind had a propensity to utilize food abundance for population growth rather than for maintaining a high standard of living, Malthus saw this as the doom of humanity.

The flaw in Malthus’ work is the same in the Global Warming crowd. They are completely ignorant of a cycle and take whatever trend they see and project that it will linearly continue to the end.

Food Supply & Population

There have been countless investigations into the food supply and the population growth of animals. What has been revealed is that as food supply declines, so does the birth rate. Malthus’ observation that an increase in food supply led to an increase in population was correct, but only one side of the cycle. The Global Warming crowd ignores the fact that CO2 levels used to be measured in thousands of ppm instead of hundreds. In fact, the temperature does not even correlate very well with CO2 levels. During ice ages in the Ordovician period, some 450 million years ago, when the CO2 levels were several thousand of ppm this did not result in temperatures 10 times greater than today.


  •  P.C. Quinton and K.G. MacLeod, “Oxygen isotopes from conodont apatite of the midcontinent US: Implications for Late Ordovician climate evolution,” Palaeogeography, Palaeoclimatology, Palaeoecology, 2014, 404: 57–66.

The Evolution of Growing Food


QUESTION: Mr. Armstrong; You previously mentioned that we can grow crops inside warehouses without the sun or soil. How did mankind survive the last mini Ice Age wit dropping temperatures as we have seen in recent winters here in Europe?

LW

ANSWER: With each cycle, we tend to improve upon technology. Being able to grow food inside will be an important advance for us during this cycle. You can set one up in your basement.

Previously, there was the invention of the fruit wall which appeared around the beginning of the Little Ice Age that ran the course of about 200 years from about 1550 to 1850.

The invention of the fruit wall saved society. They built walls which reflected sunlight during the day essentially using solar energy to improve growing conditions. These walls also absorbed solar heat, which in turn was slowly released during the night, preventing frost damage. They created a warmer microclimate 24 hours per day.

Fruit walls also protected crops from cold blasts of winds from the north as we are experiencing today. They eventually began to construct wooden canopies to shield the fruit trees from rain and hail. They would also use mats suspending then from the walls in case of bad weather. I remember my grandfather loved figs and he had fig trees he would wrap during the winter to protect them in New Jersey. In Europe, these fruit walls were used as far north as England and the Netherlands.

Conrad Gessner (1516 – 1565) was a true Renaissance man. He was a Swiss physician, naturalist, bibliographer, philologist, zoologist, and a botanist. He wrote of the effect of the Fruit Walls which then popularized them in Europe.

The French began to improve the technology by pruning the branches of the fruit trees in such ways that they could be attached to a wooden frame on the wall.

The French botanist Charles Lucien Bonaparte (1803 – 1857) is credited with building the first practical modern greenhouse in Leiden, Holland, during the 1800s to grow medicinal tropical plants. The French called their first greenhouses orangeries since they were used to protect orange trees from freezing. Today, Holland grows more food in greenhouses than any other country.

metropolis-farms-24

Today, the next step forward is growing food in warehouses without the sun or earth.

Analysis of Global Temperature Trends, January, 2018, what’s really going on with the Climate?


The analysis and plots shown here are based on the following two data series. First NASA-GISS estimates of a global temperature shown as an anomaly (converted to degrees Celsius) as shown in their table Land Ocean Temperature Index (LOTI) and shown in Chart 1 as the red plot labeled NASA the scale for the temperatures is on the left. The NASA LOTI temperatures are shown as a 12 month moving average because of the large monthly variation. Second NOAA-ESRL Carbon Dioxide (CO2) values in Parts Per Million (PPM) which are shown in Chart 1 as a black plot labeled NOAA the scale for CO2 is shown on the right.

NASA published data as stated in the first paragraph is shown as an anomaly, but what is a temperature anomaly?  An anomaly is a deviation from some base value normally an average that is fixed. There were two problems with the system that NASA picked which were number one there is no “actual” global temperature and two since climate is a variable there cannot be a real base to measure from. NASA known for its science and engineering expertise back in the day thought it could get around these issues and created a system to do so. First they developed a computer model which took readings from all over the planet and made required adjustments to them which they called homogenization and came up with the estimated global temperature. Second they picked the period 1950 to 1980 (30 years) and averaged the values found in that period and came up with 14.00 degrees Celsius and make that their base.  Then they took the calculated monthly temperature and subtracted the base from it which gave them the anomaly. The problem is that both are arbitrary.

Now that we have a base to work with we are going to add to Chart 1 three things. The first is a trend line of the growth in CO2 since that is according to the government through NASA and NOAA the entire basis for climate change. That plot is superimposed over the black plot of the actual NOAA CO2 values as the cyan line labeled as the CO2 Model and one can see there is a very good fit to the actual NOAA values so there should be no dispute about its validity, and it’s historically accurate.  This plot allows us to make projections to future global temperatures according to the projected level of CO2 .  The second added item is James E. Hansen’s 1988 Scenario B data, which is the very core of the IPCC Global Climate models (GCM’s) and which was based on a CO2 sensitivity value of 3.0O Celsius per doubling of CO2. This plot is shown here in lavender and is part of a presentation that Hansen showed to congress in 1988 when the UN was about to set up the International Panel on Climate Change (IPCC) and this plot is labeled as Hansen Scenario B which Hansen stated was the most likely to happen based on his 1979 climate theories’.  The third item is the current plot of the most likely temperature of the planet based on the growth of CO2 published by the IPCC. This plot is shown in Red and is labeled as IPCC AR5 A2 as that is the table where the data was found. This plot is a GCM computer projection of the planets temperature based on the complex relationships developed on the levels of CO2 by the IPCC primarily though NASS and NOAA.

It can be seen in Chart 2 that the lavender plot and the Hansen plot are very close from 1965 to around 2000 after that, from 2000 to 2014, there is a very large and deviation reaching close to .5 degrees Celsius in 2015, which is not an insubstantial number.  Also of note is that there doesn’t seem to be a good correlation between the growth in CO2 and the increase in the planets temperature. The CO2 is going up in a log function and the Temperature was going down until 2015 and then there was a mysterious spike up. That unexplained change in temperature direction appeared to have occurred between 2013 and 2014 and is the subject of this monthly paper.

Next we have Chart 3 which is developed from the raw data from NASS and NOAA as shown in Chart 1.  This plot was made first by adding ten years blocks of temperature and CO2 as indicated in the Chart 1 and diving by 120 to give an average for each.  Then the average Temperature was divided by the average CO2 to give degrees of temperature increase per PPM of CO2. After that was plotted it appeared that there were two different curves. The first was from block 1965-1974 through block 2004-2014 shown as Black Dots and the second was from block 1995-2004 through block 2005-2017 shown as Black Dashes. When trend lines were added they were both almost perfect fits to the raw data and so you cannot see the data points very well on Chart 2.  These blocks were picked to represent the entire period of time where we had both NASA temperature data and NOAA CO2 levels.

On Chart 3 there are two sets of color coded information. The first is Cyan plot and the Cyan box with the equation in it along with the R2 value of 1.0 are for the first series from block 1965-1974 through block 2004-2014. The other is the Red plot and the Red box with the equation in it along with the R2 value of 1.0 which are for the first series from block 1965-1974 through block 2004-2017. We can speculate on how this change happened but it can’t be said that the plot change is not real; however additional data will be required to actually prove that something has changed.

In summary the Cyan data set indicates a diminishing effect of CO2 on global temperature for about 54 years and the Red data set represents an increasing effect of CO2 on global temperature for the past 3 years. Since both data sets have an R2 value of 1.00 the trend lines cannot be in question.

Continuing the analysis of what happened to the NASA data in table LOTI from Chart 3, the following Chart 4 was constructed from the same NASA data. It’s very sad to say but it seems to prove without much doubt that the global temperatures have been manipulated by NASA probably at the request of the federal government such that a case could be made for supporting the COP21 Paris climate conference in December 2015 by showing that the earth was much hotter than it actually was. The dates on the x axis are the date of the NASA LOTI download file. The plots for specific date groupings are set such that one can see what that date range did in each separate NASA download. The proof is shown in Chart 4 below and a discussion will follow below Chart 4 on how Chart 4 was constructed.

At the bottom of Chart 4 is a blue trend line of NASA LOTI temperatures prior to 1950 and starting in2012 the values started going down, getting colder. At the same time the NASA LOTI temperatures from 2012 to the present went up as shown in the red line.  There was no change in the base period, black line. This cannot happen with random variables they will cancel each other out; this could only be caused by specific program changes in the process that NASA and NOAA use, in other words it is intentional. So there can be no other reason but an attempt to support the adoption of the Climate accord agreement by the administration, and they were successful as it was agreed to in Paris at COP21.

How this table was constructed is important so a discussion is needed. As stated in the opening paragraph of this paper NASA publishes a table of the estimated global temperature each month as anomalies from a base of 14 degrees Celsius. This table starts with January 1880 and runs to the current date. The new table typical comes out mid-month with the values for the previous month and for December 2017 there were 1,656 values. The process that is used to create this Table is very complex and is called homogenization. What that means is that the entire table is recreated each month and what that also means is that the temperature value for any given month is a variable.

When I realized the extent of that in 2012 I started to save the printouts of the NASA LOTI tables and I went back and found a few of them from when I started this project in 2007. When I started this project what I did is type in all the values from the NASA table into a spreadsheet each month which was a daunting task and I was very happy when NASA started to publish a csv file along with the text of the LOTI data. Then all I had to do is create a routine in excel that would turn the table format into a column format.  There are now 65 months in the spreadsheet, when I started this method in 2012 there were maybe only a dozen. The values are residing in the spreadsheet as columns going from left to right so that the individual months are lined up side by side. This makes comparison of months very easy. One note is required here, when I started this model in 07 and for several years thereafter all I was doing is adding the current NASA LOTI current months number to the existing file, a single column, and it never occurred to me that the prior numbers were changing. The past was fixed, so I thought. This was also the way I was entering the NOAA CO2 data which doesn’t change over time.

The original goal was to see if the changes were just random or rounding errors. If that was so then they would wash out over time especially if I grouped the monthly data into blocks. I’ve used both 10 year (120 values) and 20 year (240 values) blocks which would be enough to maintain a fixed number if it was random or rounding. What I found was something quite different after I had a dozen or so columns in the spreadsheet, it appeared that NASA was making the past colder and the present warmer. And the purpose of the previous two Charts 3 and 4 is to show the result. Chart 4 is a bit complex but I have not found a better way to show what happened.

From 1880 to 1960 I used four 20 year blocks.  Then I needed the base so there is a 30 year block from 1950 to 1980 and lastly four 10 year blocks from 1980 to the present. The last block is not yet complete as it will run to December 2019. Because the 30 year base block is fixed at 14.0 degrees Celsius there wasn’t much point in charting those individual yearly values even though there was some minor movement in those numbers. That raises an interesting issue for how can the base numbers not change and all the other numbers from 1880 to 2017 can change each month? A note, for each data set of years the plot on Chart 4 should be a straight line from left to right; very minor fluctuation would be OK. For example the plot for 1930 to 1949 (hidden behind the black plot) is what would be normally expected. This is the only plot that doesn’t show major manipulation.

In the four data sets in the 1880 to 1940 blocks in Chart 4 all have moved down probably about a .25 degree Celsius which is not insignificant. So the bottom line is that NASA made all the values from 1880 to 1940 colder by an average of a quarter of a degree Celsius. So that alone accounts for a high percentage of the supposed global warming that NASA shows. From 1980 to 2009 the data change appears to add another .1 degrees Celsius making the apparent differential between data from early 00’s to the present about .35 degrees greater than it was before 2009. That is not random that is a major change and clearly shows manipulation. I would probably never had caught this is if I hadn’t put the values in column format. Looking at all the data from 2008 to 2014 we find that around 2008 NASA showed that the planet had warmed about .75 degrees, Blue double arrow, from the 19th century. Then in 2014, four years later NASA showed that the planet had warmed about .95 degrees Red double arrow from the 19th century. However it gets a worse after that.

The change started in 2012, Green Oval, and Global temperature jumped almost a quarter of a degree by December 2015 just as the COP21 conference was in session. The temperatures kept going up with an eventual increase in global temperature of about 1.2 degrees Celsius in late 2016. At that point with the pressure off NASA appears to be erasing what they did as the global temperatures have now started back down.  I’m not sure how many know of this blatant manipulation but it is serious. This is not science.

Now we need to consider other factors than CO2 on Climate change.  The fault that occurred in the work that was done in the 1980’s was in assuming that there was an optimum or constant global temperature and therefore any change that was being observed was from the increasing amount of CO2 in the atmosphere.  There may have been correlation but it was never proved that there was causation (high R2 value) between CO2 and global temperatures; Chart 3 clearly shows there is not. With that assumption, which limited options, we moved from true science into the realm of political science.  True science has an open mind and finds relationships that work in matching observations with predictions.  Political science changes history and/or facts to match the desires of the politicians. Since the politicians control the money political science is what we get; which means that what we get may not be technically correct.

A decade ago when I started looking at “climate” change the first thing I did was look at geological temperature changes since it is well known that the climate is not a constant; I learned that 53 years ago in my undergrad geology and climatology courses in 1964. The next paragraph explains currently observed patterns in climate related to this subject and is historical accurate.

Ignoring the last Ice Age which ended some 11,000 years ago when a good portion of the Northern hemisphere was under miles of ice the following observations give a starting point to any serious study on the subject of climate. First, there is a clear up and down movement in global temperatures with a 1,000 some year cycle going back at least 3,000 to 4,000 years; probably because of the apsidal precession of the earth’s orbit of about 20,000 years for a complete cycle. However about every 10,000 years the seasons are reversed making the winter colder and the summer warmer in the northern hemisphere. 10,000 years from now the seasons will be reversed again. Secondly, there are also 60 to 70 year cycles in the Pacific and the Atlantic oceans that are well documented. These are known as the Atlantic Multi Decadal Oscillations (AMO) in the Atlantic and as La Nina and El Nino in the Pacific. Thirdly, we also know that there are greenhouse gases such as carbon dioxide that can affect global temperatures. Lastly the National Academy of Sciences (NAS) estimated that carbon dioxide had a doubling rate of 3.0O Celsius plus or minus 1.5O Celsius in 1979 when there were only two studies available and one for sure and maybe both were not peer reviewed.

The result of looking objectively at the three possible sources of global temperature changes was a series of equations based on these observations that when added together produced a sinusoidal curve that seemed to follow NASA published temperatures very closely when first developed in 2007, and modified a few years later when it was found the short and long cycles were related to multiples of Pi.  Since this curve was based on observed temperature patterns it was called a Pattern Climate Model (PCM) which has been described in previous papers and posts on my blog and since it is generated by “equations” many assume it is some form of least squares curve fitting, which it is not. It does seem to be related to ocean currents where the bulk of the planet’s surface heat is stored.

Chart 5 shows the PCM a composite of two cycles and CO2. There is a long trend, 1036.7 years with an up and down of 1.65O Celsius (.00396O C per year) we in the up portion of that trend. Then  there is a 69.1 year cycle that moves the trend line up and then down a total of 0.29O Celsius and we are now in the downward portion of that trend (-.01491O C per year), which will continue until around ~2035. Lastly, there is CO2 currently adding about .0079O Celsius per year so together they all basically wash out at -.0039O C per year, which matches the current holding pattern we were experiencing until 2014. After about 2035 the short cycle will have bottomed and turn up and all three will be on the upswing again duplicating what was observed in the 1980’s.  Note: the values shown here are only representative from what is in the model.

When using a 12 month running average for global temperatures up until 2014 the PCM model was within +/- .01 degrees of what NASA was publishing in their LOTI table since the early 1960’s as shown in Chart 5. Further the back projection of the PCM plot matched historical records and global temperatures going back past the time of Christ. It should also be considered that geologically CO2 levels have reached levels many times that of the current 400 ppm without destroying the planet so the current hysteria over the current very small numbers can only be explained by political science not real science.

The nest step in this analysis is to put all of the known data and projections into Chart 6 which contains: NASA’s temperatures plot, NOAA’s CO2 plot, the CO2 model plot, the PCM model plot, Hansen’s Scenario B plot, and lastly the IPCC AR5 A2 global temperature plot. With that done we can look at the results and try to make some sense of what is going on with the various arms of the federal government that are promoting that we tax carbon based fuels to eliminate them since they are responsible for the global temperature level  going up.  As previously stated when the government pours money into the sciences the sciences respond with technical papers the support the governments views, this is what I call political science verses real science as was done prior to the 1980’s; money talks and BS walks as everyone on the street knows.

Chart 6 shows a good overview and contains no data manipulation and the only change that was made was to convert the NASA anomalies back to degrees Celsius to make it more readable to lay people.  This is only a change in units and has no bearing on the look.  We also need to understand the NASA homogenization process and its relationship to the 30 year base period. The portion in the black circle contains the NASA base period of 14.00 degrees Celsius and the reason it’s brought up here is that the Homogenization process causes the global temperatures to move around since the entire data base all the way back to 1880 is recalculated each month.  But since the base has to stay at 14.00 degrees Celsius the program must be set to not allow changes in that period of time. I’m sure the programmers have fun with that. Prior work here has shown how this creates a teeter totter effect with the data plots, some of which have recently been significant.

Next Chart 7 looks at the period from 2010 to 2020 so we can see where a change in CO2 of only a few ppm has caused a major change in the global temperature way beyond anything previously shown in any published NASA data. There are two black ovals on Chart 7 one at the top of Chart 7 which is a black oval around the CO2 levels from 2012 to 2016 and part of 2017 and it’s very obvious that there has been very little change, maybe 7 ppm or about 1.9%. Then at the bottom of Chart 7 is another black oval around the NASA global temperature levels for the same period and its very obvious that there has been a large change, almost .50 degrees Celsius or about 3.1%. There has never been such a large increase in temperature from such a small increase in CO2. By contrast the previous comparable period of the last part of 2010 through 2013 shows about the same increase for CO2 at 1.1% but no increase for global temperature but actually small decrease.

Clarification is needed here as the plot seems to show the jump in temperature in 2016 not 2015; this is a result of the large jump in temperature shown by NASA. Since we are using a 12 month moving average and the increase occurred in only a few months it actually shifted the curve into 2016. The raw data for December 2015 showed the temperature at 15.12 degrees Celsius compared to December 2014 where it was 14.78 degrees Celsius. The actual peak was in February 2016 at 15.35 degrees Celsius.   With the global temperature over 15.0 Celsius at COP21 the climate accord was approved and the manipulation was a success. After COP21 the need for Fake Warming was no longer needed and so we are now seeing a downward trend developing.

In summary, the IPCC models were designed before a true picture of the world’s climate was understood. During the 1980’s and 1990’s CO2 levels were going up and the world temperature was also going up so there appeared to be correlation and causation. The mistake that was made was looking at only a ~20 year period when the real variations in climate all move in much longer cycles of decades and centuries.  Those other cycles can be observed in the NASA data but they were ignored for some reason.  By ignoring those actual geological trends and focusing only on CO2 the Global Climate Models will be unable to correctly plot global temperatures until they are fixed. Also the temperature data from 1850 to 1880 was dropped for some reason as it showed a lower temperature that supported the PCM cycle shown in this paper.

In summary we have Chart 8 which shows why CO2 is not increasing the temperature of the planet by any meaningful amount. The problem, intentional or not, goes back to physics and how we show information. It’s critical that when we talk to nonscientists that information is properly displayed. And nowhere is this more important than when we are discussing temperature.  When we talk about weather and local temperatures its going be in Celsius (C) in the EU or degrees Fahrenheit (F) in America e.g. for the base temperature that NASA uses it’s 14.00 C or 57.20 F; but these are both relative measures and do not tell us how much heat (thermal energy) is there. To know that we must use Kelvin (K) and that would be 287.150 K and all three of those numbers 14.00 C, 57.20 F, and 287.150 K are exactly the same temperature, just using a different base. But if the current temperature is 15.00 C that is a 7.1% increase in C, a 3.1% increase in F and a .35% increase in K; so which one is real? The answer is .35% because Kelvin is the only one that measures the total energy!

To show this graphically Chart 8 was constructed by plotting CO2 as a percentage increase from when it was first measured in 1958 the Black plot, the scale is on the left and it shows CO2 going up about 28.5% by January of 2018. That is a large change as anyone would agree.  Now how about temperature, well when we look at the percentage change in temperature using the proper units Kelvin we find that the changes in global temperature are almost unmeasurable. The red plot, also starting in 1958, shows that the thermal energy in the earth’s atmosphere has varied by less than +/- .17%; while CO2 has increased by 28.3% which is over 80 times that of increase in temperature. So is there really a problem here?

Lastly, Chart 9 shows what a plot of the PCM model, in yellow, would look like from the year 1400 to the year 2900. This plot matches reasonably well with recorded history and fits the current NASA-GISS table LOTI data, in red, very closely, despite homogenization.  I do understand that this PCM model is not based on physics but it is also not some statistical curve fitting. It’s based on observed reoccurring patterns in the climate. These patterns can be modeled and when they are, you get a plot that works better than any of the IPCC’s GCM’s. If the real conditions that create these patterns do not change and CO2 continues to increase to 800 ppm or even 1000 ppm then this model will work well into the foreseeable future.  150 years from now global temperatures will peak at around 15.750 to 16.000 C and then will be on the downside of the long cycle for the next ~500 years.

The overall effect of CO2 reaching levels of 1000 ppm or even higher will be about 1.50 C which is about the same as that of the long cycle.  The Green plot on Chart 9 shows the observed pattern with no change in CO2 from the pre-industrial era of ~280 ppm. CO2 cannot affect global temperatures more than 1.500 C +/- no matter what the ppm level of CO2 is. The reason being that the CO2 sensitivity value is not 3.00 per doubling of CO2 but less than 1.00 C per doubling of CO2 as shown in more current scientific work and it’s a logistics curve not a log curve.

The purpose of this post is to make people aware of the errors inherent in the IPCC models so that they can be corrected. 

The Obama administration’s “need” for a binding UN climate treaty with mandated CO2 reductions in Europe and America was achieved as predicted at the COP12 conference in Paris in December 2015. To support this endeavor NASA was forced to show ever increasing global temperatures that will make less and less sense based on observations and satellite data which will all be dismissed or ignored.  Within a few years the manipulation will be obvious even to those without knowledge in the subject, but by then it will be to late the damage to the reputation of science will have been done.

In closing keep this in mind. The current panic generated by the government using political science is that the current global temperature of around 15.0O Celsius is an increase of 7.14% from the 1960’s when the global temperature was 14.0O Celsius; and that does seem like a lot. However those views would be in error as the actual increase in thermal energy, as measured by temperature, would be only .35% because we must use Kelvin not Celsius when working with heat energy. When we use kelvin the temperature goes from 287.15O K to 288.15O K which is only .35% not 7.14% about 1/20 of what is implied by the IPCC. What the IPCC shows is not technically wrong as much as it is extremely misleading to anyone without a very strong science background.

Sir Karl Raimund Popper (28 July 1902 – 17 September 1994) was an Austrian and British philosopher and a professor at the London School of Economics. He is considered one of the most influential philosophers for science of the 20th century, and he also wrote extensively on social and political philosophy. The following quotes of his apply to this subject.

If we are uncritical we shall always find what we want: we shall look for, and find, confirmations, and we shall look away from, and not see, whatever might be dangerous to our pet theories.

Whenever a theory appears to you as the only possible one, take this as a sign that you have neither understood the theory nor the problem which it was intended to solve.

… (S)cience is one of the very few human activities — perhaps the only one — in which errors are systematically criticized and fairly often, in time, corrected.

Cryptocurrency Maybe Become a Tax Nightmare


Credit Karma is reporting that of the first 250,000 tax filings, less than 100 people reported owning any cryptocurrency. Credit Karma is reporting that only 0.04% of cryptocurrency-traders are paying taxes to Uncle Sam.

The dangerous aspect here is the IRS got over 20,000 names from the exchanges and they will match their accounts to tax returns. Anyone who thinks this is an alternative currency that circumvents taxes and the central banks will have a new reality after April 15th. They will know everyone who has bought or sold any cryptocurrency.

Volatility – What is It?


 

QUESTION: Dear Martin,

In the private blog you mentioned a few times that the volatility will rise again in the week of the 12th. When you mention volatility, do you mean volatility as measured by the VIX index?

 

So far the VIX has lost around 1/3 this week so I suppose you mean something else?

Thanks!

JWD

 

ANSWER: The VIX is not a true indicator of volatility. We have three main volatility measurements and each is different.

(1) you have the traditional measurement of close to close. That is interesting, but it does not truly capture the concept of volatility.

(2) Then there is intraday volatility which we measure and simply the percentage movement between the high and low of that session. You can have a 1,000 point swing in the Dow intraday yet close nearly unchanged. The first volatility measurement would never even show a blip.

(3) The third measurement is overnight volatility. This is measured from the previous close to the open of the current day session. For example, Monday, February 5th the Dow opened at 25337.87 compared to Friday’s closing of 25520.96 gapping down.

Our indicators are intended for trading, unlike the VIX. In our Arrays, you will see Overnight Volatility, Intraday Volatility, and Panic Cycles, which are extreme moves in one direction or an outside reversal which exceeds the previous session high and penetrates the previous secession low.

 

The VIX is a convoluted formula that does not reflect trading but more of a trend lending itself to manipulations. Hence, the VIX is not very reliable. The VIX is a measure of expected volatility calculated as 100 times the square root of the expected 30-day variance (var) of the S&P 500 rate of return. The variance is annualized and VIX expresses volatility in percentage points.

Volatility Index VIX Futures

where var = (365/30) x Expected 30-day variance.

The 30-day variance is the sum of squared standard deviations st (“volatilities”) of the S&P 500 rate of return at every point in time t during the 30 days:

Volatility Index VIX Futures

Japan Sells US Debt Trying to Ease A Trade War


The Japanese government once again reduced its holdings of US government bonds during December 2017. In total, Japan sold bonds worth $ 22.5 billion. This is not a huge amount. Nevertheless, this puts the total stock of US debt at about $ 1.06 trillion, which is the lowest level since 2012. Japan used to be the largest holder of debt externally. However, it has fallen to number two just behind China.

By contrast, the Chinese government increased its holdings by about $8.5 billion in December to $ 1.18 trillion. The acquisitions in the entire year 2017 were as extensive as last 7 years ago. Naturally, the hard-money biased reporting paints this as an imminent crash in the dollar. What they fail to understand is that helping to lower the dollar is a tactic to ease trade friction

Obama’s Portrait – What Does it Say?


 

The official portrait of Obama was painted by Kehinde Wiley. This is a very unusual painting putting a president in a garden setting which traditionally was limited to women’s portraits. It reminds me of the painting in the Villa of Livia, the wife of the first Roman Emperor Augustus (27BC-14AD).

Obama’s portrait’s background is filled with blue lilies from Africa, jasmine flowers from Hawaii, and American chrysanthemums rising up from a field of ivy that begins to overtake the armchair on which Obama sits. This obviously refers to his origins.

However, the picture also refers to Abraham Lincoln’s official portrait where he sits in a chair. This is an obvious connection to Lincoln who ironically was the founder of the Republican Party in contrast to Andrew Jackson who was a slave owner and the founder of the Democratic Party.

Yet the abundance of flowers and the garden scene infers something more than just his origins. This is also a symbol of his support for the Global Warming movement. Ironically, the greater the vegetation the lower the CO2 since plants thrive on CO2.

Real Estate v Quantitative Easing


QUESTION: Hi Martin,
I just finished your new NYSE Boom/Busty report. This is excellent work and as always extremely fascinating. Thank you for continuing to share these profound views with us.
My question relates to your view that we are looking at a complete collapse of Quantitative Easing and that will likely see a massive capital flight to the dollar and the major safe haven will be EQUITIES. In the context of this possibility, are you able to comment on how this may relate to Real Estate. Your ECM seems to be calling for Real Estate to top out and structurally fall in 2032. Is it not possible that with the collapse of QE and potentially economies that we will see more negative rates in the short end and with the government powers to seize assets in bank accounts, would it not be prudent to have zero cash in hand and hence we see a massive capital flight to Real Estate too? Or will the collapse of QE lead to significantly higher rates across the curve and hence blow all leveraged exposure sky high?

Many thanks as always,

David

ANSWER: The problem with real estate has been that its value depends upon lending. This was what the government did as part of the New Deal by creating 30-year mortgages. This was a scheme to get prices up by extending the period people could pay off the loan. Typically, the duration was 5 years previously.

The collapse in Quantitative Easing will have the effect of causing rates to rise on the long-term. However, there will be a shift toward private assets and this will help to a large extent. However, keep in mind that many institutions will be trapped and unable to shift to private assets. Many boards will not understand the shift and still believe, wrongly, that unsecured government debt is best.

Prices of real estate will decline in proportion to the decline in mortgage availability. We are already witnessing banks beginning to withdraw from lending on real estate.

I have provided the guide-posts for what is to come. This will be an interesting future.

Short v Long-Term Rates


QUESTION: Hi Mr Armstrong, I have read somewhere that you think that interest rates will go up higher than expected and at faster pace. I don’t understand its relations with bonds. Also your opinion seems to be in clear contrast to everyone else who thinks it will go up slowly over the next few years. If this happened this year, this would be one of your many landmark predictions.
thanks

HH

ANSWER: To some extent, you are mixing short v long-term. The short-term is set by the rates the central banks set. Even this will rise beyond what the central bank desires because of demand.

The long-term is set by the market. That is why the central banks tried Quantitative Easing buying in long-term bonds hoping that would lower the long-term rates which are set by the auction process.

I am not forecasting that the central banks will rapidly raise rate all on their own. They will be forced to follow long-term rates and as Quantitative Easing is reduced, rates will rise when government deficits expand because the fiscal side of the balance sheet has been on life-support by the monetary policy

Understanding the Reversals


QUESTION: Martin,

Last week, we had elected the weekly reversals at 24741.6 and 24395. Yesterday, we briefly recaptured, then re-lost those levels again.

Do weekly reversals expire at the end of the week, expire once they are elected, or do they remain active from week to week?

As always, thanks for all you do with your blog and with Socrates.

DB

P. S. – Do you prefer “Martin” or “Marty”? Many address you as “Marty”, but I don’t know if you reserve that name for your close friends. I certainly do not want to offend you.

ANSWER: No worry. I answer to both. As far as the Reversal System is concerned, when you pass beyond Reversals electing them on the close by more than 1% away from the number, you will typically rally back to test them before proceeding. In this case, you went to the third one and bounced. You always generate counter-trend reversals when you are making a low. In most cases, they are above the market activity.

In this case, two Weekly Bullish Reversals were elected and that is why we bounced. It was also why I have warned that it appeared this was not a 1987 meltdown, but a consolidation and choppy period. There were no Double Weekly Bearish Reversals that would indicate a meltdown if elected as was the case from the 1987 and 1989 highs.

The two reversals 24741.6 and 24395 were elected and they will provide overhead resistance. In the case of 1987, you took out all four Weekly Bearish Reversals and there was a gap from 286 on the S&P500 to 181.

The great thing about the Reversal System is we eliminate human opinion. The numbers are very black and white. How they are laid-out in a given market identifies the potential for a meltdown or just a correction. Then our Timing Array showed turning points every two weeks indicating also a choppy pattern. In this way, we are able to eliminate the human subjectivity that is always hit or miss.