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EDIT 5: After a quick look at the data received for some blue-chip stocks, I can say that math doesn't add up, so the assumptions in that DD were wrong. I still can't grasp how the % of shares held by institutions can be lower than the % of the float held by institutions. Nevertheless, I would like to thank you all for challenging my thesis, and I would like to ask admins to change the flair to DEBUNKED*. Take care guys and stay strong! :)submitted by BartiTheGreat to Superstonk [link] [comments]
Special thanks to u/ikespungler and u/ravada for providing me with Bloomberg data.
EDIT 4: The only way to check whether this calculation method is right or wrong is to apply it to the blue-chip stocks. Some users already contacted me that they are willing to provide me with some data from Bloomberg Terminal, so I will try to analyze it in the following weeks.
EDIT 3: Here, I will try to answer some questions asked by other users.
Did you gather this data yourself from Bloomberg or was this data posted to Superstonk?Yes, I gathered it by myself based on the Bloomberg posts, which were uploaded here and on the other GME subreddits.
You acknowledge here, and other times in this post, that there are unexplained discrepancies in the data. Why did you continue with your analysis when you yourself admit that the data is incorrect?To prove with simple mathematical equations that the data is wrong, and to show that the data given on Bloomberg shouldn't be understood as something without any flaws.
This statement is hyperbole. There are many other logical explanations for why the data could be correct, nor did you actually provide proof of manipulation. It is well known that 13f fillings, where Bloomberg gets their ownership data, is typically inaccurate due to the requirements for when to file, could this not also be an explanation? This question needed to have been answered before analysis can be done.In general, it could be, but in this case, it shouldn't be. Instead of taking data from one reporting period, I gathered data which equivalent to at least 4 quarterly filings. Even if you assume, that the data is "delayed" by the T+45 requirement from the last day of a reporting period it should not influence the overall picture of the results because sooner or later those missings filings have to be submitted within the filing period, thus 1.5 months later the data should be updated.
And actually, I explained why the data is wrong. Even if you throw out all the calculations. Assume, that my math sucks. The % of the institutional ownership and % of the float held by institutions is just simply wrong. The former can't be higher than the latter. It's simple math. Yet, after the January runup, something caused that anomaly.
Most financial institutions calculate IO by using 13f filings from the SEC. Is there a particular reason you decided to compare this number to your own aggregated definition of what institutional ownership is? Could the discrepancy in numbers be caused by an improper calculation of IO from your aggregated definition compared to Bloombergs calculation?I am gonna clarify that a bit. Bloomberg calculates the IO based not only on the 13F filings but also on the research (whatever is that), schedules 13D and G, SEC Forms 3, 4, and 5, the proxy statements, etc. Since I don't have access to all of those documents, it was the only possible solution to anchor the analysis on the IO presented by Bloomberg and compare its % to the Ownership Types (also from Bloomberg).
Going back to the aggregated definition. It is possible, that it might be wrong, but I am gonna repeat once again that was the assumption to proceed with calculations.
IO definition clearly states that:
Institutional ownership is the amount of a company’s available stock owned by mutual or pension funds, insurance companies, investment firms, private foundations, endowments or other large entities that manage funds on behalf of others.Some other Reddit user mentioned, that Investment Advisors should not be included since this is not institutional ownership. It’s individual ownership held beneficially at a brokerage.
If that's true, and I would exclude that that type of ownership then the number of shares in circulation (according to the 2nd method) would vary between 800mln shares and 2 billion shares. The updated tables you can find below.
Where did you get the data from to make your own institutional ownership calculation?The data was taken from Bloomberg Terminal posts, from the Ownership Summary section, and my definition of the IO types is based on the materials from Investopedia. Even if the ownership types were assumed by me wrongly. It would not explain the % of the shares held by institutions and the % of the float held by institutions.
Moved the edits to the top and added a heading.
Guys, I would like to highlight that those numbers of shares in circulation are based only on the data from Bloomberg Terminal, and the number of at least 115 million shares is based on the filings from April 2021. Since then, lots of things have changed eg. including my GME portfolio which quadrupled. We will probably never know what is the real number of shares, but those 115 million, in my opinion, is a bare minimum.
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Last time, when the new Bloomberg Terminal screenshot came out with Gamestop data, it got me thinking if the data there is reliable and can be used to prove the manipulation in the stock. So in order to do that, I analyzed every monthly Bloomberg post dating back to March 2021.
The findings are fascinating and they show that the data might have been manipulated after April 2021, or the method of calculating the Institutional ownership has completely changed. I lean more towards the former. Moreover, based on the data from Bloomberg, I can say with confidence that the number of shares on the market back in April 2021 varied between 115 million to 125 million.
I am gonna shortly present the whole process but first, you may ask why I analyzed the data up to only March 2021. Well…the answer to that is quite simple, I couldn’t find any more posts with Bloomberg data with older dates. Secondly, these last few Bloomberg posts depict that shares held by institutions were above the total number of outstanding shares, more precisely it was 121.74% of the outstanding share and 137.46% of float based on the filing from 25.04.2021. And the most recent one from 17.04.2022, which was available here on Superstonk, shows that institutions hold only 45.81% of total shares, and 40.17% of the float, so something happened between April 2021 and now, and I will try to analyze that.
Hypothesis and the data
My hypothesis is that the data is completely invalid and with the methodology described below I will try to prove it. Since there is no guidance provided by Bloomberg on how the ownership is calculated etc., I need to assume some stuff based on the general knowledge and the findings from the Internet.
I decided to write down the percentage of shares held by institutions and the top ownership type in an Excel spreadsheet, and I started calculating the number of shares based on the numbers provided by Bloomberg.
So here is the data already in the Excel spreadsheet.
Data between 12.12.2021 and 17.04.2022
Data between 30.05.2021 and 28.11.2021
Data between 14.03.2021 and 25.04.2021
As you can see it is quite a lot.
CALCULATION MODEL 1
Let’s start by calculating the number of the top ownership shares. Here in this method, I assume that there is no fuckery and the maximum number of shares existing is the number of shares outstanding, right? I mean it has to be correct. There is no stock manipulation market according to the media.
For all those calculations I took the number of shares outstanding in a specific period and multiplied it by the percentage of the ownership. For demonstration let’s take the filing from the 17th of April 2021. According to it, brokerages own 2.72% and that means that the number of shares held by brokerages is:
2.72% x 75,900,00 (shares outstanding) = 2 064 480.00
The data from the 17th of April 2022
Isn’t it simple?
The same methodology applies to other types of ownership. It is worth noticing that the screenshot of the filing from 17.04.2022 was cut, so I was unable to obtain the data for other types of ownership.
Okay, let’s move on. We have already numbers of shares sorted by top ownership, so let’s try to calculate the total number of shares, based on those ownership numbers and the percentage of the shares held by institutions.
How to specify which types of ownership are included in the institutional holdings. Well, it is quite obvious, we have to google it.
Boom, first google search, straight from Investopedia.
Institutional Ownership from Investopedia
Based on that I decided to include in Institutional Ownership those groups:
Another reason for that was to give some margin error, just in case, there is something wrong in the assumptions or calculations. If we would include shares of these ownership types in the final calculation the total number of shares would be even higher, so yeah, treat it guys as a safety factor.
The results for the data from the 17th of April 2022
In the red cells are the types of ownership included in the calculations and the number in red is the number of shares held by institutions.
You may already notice that something is wrong. Based on Investopedia, the number of shares held by institutions should be more or less equal to the number of shares held by institutional ownership types, but it is not.
Let’s omit that for now and go further with the analysis.
To calculate the total number of existing shares (Z), we need to divide the number of shares held by institutions from the top ownership table (Y) by the percentage of shares held by institutions (X).
Z = Y/X
Z = 44,196,570.00/45.81% = 96,477,996.07
so around 97mln shares. If we would include the Venture Capitals into that the number of total shares on the market would be around 135mln shares, a lot right?
I applied the same method to other dates and here are the results:
Results from 12.12.2021 to 17.04.2022
Results from 30.05.2021 to 28.11.2021
Here, before posting the last picture, I would like to go back to that point in which I discussed that ownership type percentage/number is not similar to the percentage of shares held by institutions. In a perfect world, where there is no stock manipulation, the percentage of the shares held by the institutions should be equal to the sum of percentages of Investment advisors, Pensions Funds, Insurance Companies, etc., but it is not. Well, obviously there is something fishy happening with the data, and the last table, in which the institutional ownership was higher than 100%, will show you that.
Results from 14.03.2021 to 25.04.2021
As you can see, based on the first calculation model the number of shares on the market is lower than the number of shares outstanding, and it makes sense. If you divide the number of the institutional shares by the number bigger than 1. It’s always gonna give you the smaller value.
Here is an example for smooth brains:
Simple representation of how the fraction work
Thus, it proves that something is wrong with the data, and the calculation method I wanted to use from the beginning is not working for all of the time periods. It confirms that way of the data representation in Bloomberg Terminal has changed and it happened between April and May 2021. Please keep that in the back of your head. I will try to explain that a bit later.
CALCULATION MODEL 2
So after proving that the no-fuckery method does not work, it makes now only sense to assume that the percentage of ownership is based on the total number of shares on the market, not on the outstanding ones - that was my previous assumption.
Let’s get to it. Back in April 2021, Bloomberg Terminal showed that the percentage of shares held by institutions was equal to 121.74%, which gives 79,496,220.00 shares held only by institutions. Quite a lot right? and it is after the January sneeze when supposedly shorts had closed their positions…hehehe.
2nd calculation method for the data from March/April 2021
So this time I assumed that the number of total shares is unknown and I can’t use shares outstanding to estimate the number of shares based on the top ownership. That was the flaw of the previous method in which I assume that the number of outstanding shares is the number of total shares on the market.
Following that logic, it gives us 79,496,220.00 held by institutions. Now, the top ownership percentage has to be used to calculate the total number of shares on the market. It is gonna be done similarly to the previous method, so we take only the numbers from the Investment Advisors, Insurance Companies, Trusts, Banks, Others, and Private Equities, and by a sum of those numbers, we will divide the number of shares held by institutions. The result should represent the total number of shares in circulation (real and phantom shares).
Results of the 2nd calculation method for the data from March/April 2021
Here is an explanation based on the 25th of April 2021 data:
X – is the number of shares held by institutions, thus:
X = 79 496 220.00
Y - is the number of total shares on the market and it is our unknown.
Let’s calculate Y:
X = 0,5929Y + 0.0170Y + 0.0273Y + 0.0486Y + 0.0134Y, so
Y = X/(0,5929+0.0170+0.0273+0.0486+0.0134)
Y = 79 496 220.00/0.6372
Y = 124 758 662.90
It means that back in April 2021 number of shares in circulation was around 125mln.
I applied the same method to other filings after April 2021 and once again the total number of shares is smaller than the number of shares outstanding.
Results of the 2nd calculation method for the data from December 2021 to April 2022.
Results of the 2nd calculation method for the data from May to October 2021
The only logical explanation for that is that the percentage of institutional ownership is completely manipulated by Bloomberg, and it all happened after April 2021, when the Institutional Ownership went suddenly from 121.74% to the level of 56%.
Here is the graph, which shows that nicely:
Percentage of outstanding shares and float held by institutions
Look at the crossover of the red line and blue one. The red line should always stay above the blue one. To support that, please look at the % of shares held by institutions and % of float held by institutions and how it changed after April 2021.
The ratio of the shares held by institutions to the float held by institutions
We can clearly see that after April 2021, the percentage of float held by institutions became bigger than the % of shares held by the same body. It should be always lower, which means that the blue line in the graph should be below 1.
Here is a simple explanation of that issue:
The apples represent outstanding shares. Let’s assume that there is a number of 200 outstanding apples, these ones everyone can trade. In that story, there is Ryan, who is an institution and he buys 100 apples out of 200. Thus, the float (remaining apples left on the market) is 100 apples, so these are the apples that can be traded by other people.
So if the Ryan is the institutional investor and he holds 100 of those amazing apples it means that the ratio of the apples he holds to the outstanding apples is 100/200 = 0.5 = 50%, but the ratio of Ryan’s apples to the float is 100/100 = 1 = 100% because he holds 100 apples and the float is 100. Right? So it doesn’t matter how many apples Ryan holds, the percentage of his apples to the outstanding apples should be always lower than the percentage of his apples to the float. ALWAYS.
In the case of Gamestop, it is completely opposite, that’s why I think that the data by Bloomberg is rigged and not reliable…at least the part in which the % of shares held by institutions and % of float held by institutions are displayed.
I do believe, based on those findings, that the Top Ownership always relates to the total shares on the market and we can use those numbers to estimate for example, how many shares are held by individual investors by compiling filings from Gamestop and the data presented in Bloomberg.
If you noticed some errors in my reasonings, calculations or you just simply have questions regarding that DD please let me know. I’ll do my best to answer everyone. Moreover, if there is anyone who has Bloomberg Terminal from before the January sneeze or the data of other companies, I would be really grateful to get those just to check whether my methodology can be applied to other stocks or not.
To summarize, the calculations show that there are at least 115 million shares available on the market and a sudden drop, which happened after April 2021, in the % of shares held by institutional investors was a simple manipulation of the data to hide the real numbers. It proves that we were and we are right about the HFs not closing their short positions, and the only way to end this blatant manipulation happening across the markets is just to buy, register and hold our shares.
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|Operation direction: SELL|
|Opening operation time: 23:18-23:23|
|Closing operation time: 23:41-23:45|
That is how London's LBMA has in the past revealed trading of > 2.5x annual global gold mine production each DAY. The metal contracts on the EXCHANGES themselves are SPOOFS.submitted by j_stars to Wallstreetsilver [link] [comments]
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(Hey everyone, this is the SECOND half of the Finale, you can find the first half here)
The Dollar EndgameTrue monetary collapses are hard to grasp for many in the West who have not experienced extreme inflation. The ever increasing money printing seems strange, alien even. Why must money supply grow exponentially? Why did the Reichsbank continue printing even as hyperinflation took hold in Germany?
What is not understood well are the hidden feedback loops that dwell under the surface of the economy.
The Dragon of Inflation, once awoken, is near impossible to tame.
It all begins with a country walking itself into a situation of severe fiscal mismanagement- this could be the Roman Empire of the early 300s, or the German Empire in 1916, or America in the 1980s- 2020s.
The State, fighting a war, promoting a welfare state, or combating an economic downturn, loads itself with debt burdens too heavy for it to bear.
This might even create temporary illusions of wealth and prosperity. The immediate results are not felt. But the trap is laid.
Over the next few years and even decades, the debt continues to grow. The government programs and spending set up during an emergency are almost impossible to shut down. Politicians are distracted with the issues of the day, and concerns about a borrowing binge take the backseat.
The debt loads begin to reach a critical mass, almost always just as a political upheaval unfolds. Murphy’s Law comes into effect.
Next comes a crisis.
This could be Visigoth tribesmen attacking the border posts in the North, making incursions into Roman lands. Or it could be the Assassination of Archduke Franz Ferdinand in Sarajevo, kicking off a chain of events causing the onset of World War 1.
Or it could be a global pandemic, shutting down 30% of GDP overnight.
Politicians respond as they always had- mass government mobilization, both in the real and financial sense, to address the issue. Promising that their solutions will remedy the problem, a push begins for massive government spending to “solve” economic woes.
They go to fundraise debt to finance the Treasury. But this time is different.
Very few, if any, investors bid. Now they are faced with a difficult question- how to make up for the deficit between the Treasury’s income and its massive projected expenditure. Who’s going to buy the bonds?
With few or no legitimate buyers for their debt, they turn to their only other option- the printing press. Whatever the manner, new money is created and enters the supply.
This time is different. Due to the flood of new liquidity entering the system, widespread inflation occurs. Confounded, the politicians blame everyone and everything BUT the printing as the cause.
Bonds begin to sell off, which causes interest rates to rise. With rates suppressed so low for so long, trillions of dollars of leverage has built up in the system.
No one wants to hold fixed income instruments yielding 1% when inflation is soaring above 8%. It's a guaranteed losing trade. As more and more investors run for the exits in the bond markets, liquidity dries up and volatility spikes.
The MOVE index, a measure of bond market volatility, begins climbing to levels not seen since the 2008 Financial Crisis.
Sovereign bond market liquidity begins to evaporate. Weak links in the system, overleveraged several times on government debt, such as the UK’s pension funds, begin to implode.
The banks and Treasury itself will not survive true deflation- in the US, Yellen is already getting so antsy that she just asked major banks if Treasury should buy back their bonds to “ensure liquidity”!
As yields rise, government borrowing costs spike and their ability to roll their debt becomes extremely impaired. Overleveraged speculators in housing, equity and bond markets begin to liquidate positions and a full blown deleveraging event emerges.
True deflation in a macro environment as indebted as ours would mean rates soaring well above 15-20%, and a collapse in money market funds, equities, bonds, and worst of all, a certain Treasury default as federal tax receipts decline and deficits rise.
A run on the banks would ensue. Without the Fed printing, the major banks, (which have a 0% capital reserve requirement since 3/15/20), would quickly be drained. Insolvency is not the issue here- liquidity is; and without cash reserves a freezing of the interbank credit and repo markets would quickly ensue.
For those who don’t think this is possible, Tim Geitner, NY Fed President during the 2008 Crisis, stated that in the aftermath of Lehman Brothers’ bankruptcy, we were “We were a few days away from the ATMs not working” (start video at 46:07).
As inflation rips higher, the $24T Treasury market, and the $15.5T Corporate bond markets selloff hard. Soon they enter freefall as forced liquidations wipe leverage out of the system. Similar to 2008, credit markets begin to freeze up. Thousands of “zombie corporations”, firms held together only with razor thin margins and huge amounts of near zero yielding debt, begin to default. One study by a Deutsche analyst puts the figure at 25% of companies in the S&P 500.
The Central Banks respond to the crisis as they always have- coming to the rescue with the money printer, like the Bank of England did when they restarted QE, or how the Bank of Japan began “emergency bond buying operations”.
But this time is massive. They have to print more than ever before as the ENTIRE DEBT BASED FINANCIAL SYSTEM UNWINDS.
QE Infinity begins. Trillions of Treasuries, MBS, Corporate bonds, and Bond ETFs are bought up. The only manner in which to prevent the bubble from imploding is by overwhelming the system with freshly printed cash. Everything is no-limit bid.
The tsunami of new money floods into the system and a face ripping rally begins in every major asset class. This is the beginning of the melt-up phase.
The Federal Reserve, within a few months, goes from owning 30% of the Treasury market, to 70% or more. The Bank of Japan is already at 70% ownership of certain JGB issuances, and some bonds haven’t traded for a record number of days in an active market!
The Central Banks EAT the bond market. The “Lender of Last Resort” becomes “The Lender of Only Resort”.
Another step towards hyperinflation. The Dragon crawls out of his lair.
Now the majority or even entirety of the new bond issuances from the Treasury are bought with printed money. Money supply must increase in tandem with federal deficits, fueling further inflation as more new money floods into the system.
The Fed’s liquidity hose is now directly plugged into the veins of the real economy. The heroin of free money now flows in ever increasing amounts towards Main Street.
The same face-ripping rise seen in equities in 2020 and 2021 is now mirrored in the markets for goods and services.
Prices for Food, gas, housing, computers, cars, healthcare, travel, and more explode higher. This sets off several feedback loops- the first of which is the wage-price spiral. As the prices of everything rise, real disposable income falls.
Massive strikes and turnover ensues. Workers refuse to labor for wages that are not keeping up with their expenses. After much consternation, firms are forced to raise wages or see large scale work stoppages.
These higher wages now mean the firm has higher costs, and thus must charge higher prices for goods. This repeats ad infinitum.
The next feedback loop is monetary velocity- the number of times one dollar is spent to buy goods and services per unit of time. If the velocity of money is increasing, then more transactions are occurring between individuals in an economy.
The faster the dollar turns over, the more items it can bid for- and thus the more prices rise. Money velocity increasing is a key feature of a currency beginning to inflate away. In nations experiencing hyperinflation like Venezuela, where money velocity was purported to be over 7,000 annually- or more than 20 times a DAY.
As prices rise steadily, people begin to increase their inflation expectations, which leads to them going out and preemptively buying before the goods become even more expensive. This leads to hoarding and shortages as select items get bought out quickly, and whatever is left is marked up even more. ANOTHER feedback loop.
Inflation now soars to 25%. Treasury deficits increase further as the government is forced to spend more to hire and retain workers, and government subsidies are demanded by every corner of the populace as a way to alleviate the price pressures.
The government budget increases. Any hope of worker’s pensions or banks buying the new debt is dashed as the interest rates remain well below the rate of inflation, and real wages continue to fall. They thus must borrow more as the entire system unwinds.
The Hyperinflationary Feedback loop kicks in, with exponentially increasing borrowing from the Treasury matched by new money supply as the Printer whirrs away.
The Dragon begins his fiery assault.
Hyperinflationary Feedback Loop
As the dollar devalues, other central banks continue printing furiously. This phenomenon of being trapped in a debt spiral is not unique to the United States- virtually every major economy is drowning under excessive credit loads, as the average G7 debt load is 135% of GDP.
As the central banks print at different speeds, massive dislocations begin to occur in currency markets. Nations who print faster and with greater debt monetization fall faster than others, but all fiats fall together in unison in real terms.
Global trade becomes extremely difficult. Trade invoices, which usually can take several weeks or even months to settle as the item is shipped across the world, go haywire as currencies move 20% or more against each other in short timeframes. Hedging becomes extremely difficult, as vol premiums rise and illiquidity is widespread.
Amidst the chaos, a group of nations comes together to decide to use a new monetary media- this could be the Special Drawing Right (SDR), a neutral global reserve currency created by the IMF.
It could be a new commodity based money, similar to the old US Dollar pegged to Gold.
Or it could be a peer-to-peer decentralized cryptocurrency with a hard supply limit and secure payment channels.
Whatever the case- it doesn't really matter. The dollar will begin to lose dominance as the World Reserve Currency as the new one arises.
As the old system begins to die, ironically the dollar soars higher on foreign exchange- as there is a $20T global short position on the USD, in the form of leveraged loans, sovereign debt, corporate bonds, and interbank repo agreements.
All this dollar debt creates dollar DEMAND, and if the US is not printing fast enough or importing enough to push dollars out to satisfy demand, banks and institutions will rush to the Forex market to dump their local currency in exchange for dollars.
This drives DXY up even higher, and then forces more firms to dump local currency to cover dollar debt as the debt becomes more expensive, in a vicious feedback loop. This is called the Dollar Milkshake Theory, posited by Brent Johnson of Santiago Capital.
The global Eurodollar Market IS leverage- and as all leverage works, it must be fed with new dollars or risk bankrupting those who owe the debt. The fundamental issue is that this time, it is not banks, hedge funds, or even insurance giants- this is entire countries like Argentina, Vietnam, and Indonesia.
The Dollar Milkshake
If the Fed does not print to satisfy the demand needed for this Eurodollar market, the Dollar Milkshake will suck almost all global liquidity and capital into the United States, which is a net importer and has largely lost it’s manufacturing base- meanwhile dozens of developing countries and manufacturing firms will go bankrupt and be liquidated, causing a collapse in global supply chains not seen since the Second World War.
This would force inflation to rip above 50% as supply of goods collapses.
Worse yet, what will the Fed do? ALL their choices now make the situation worse.
The Fed's Triple Dilemma
Many pundits will retort- “Even if we have to print the entire unfunded liability of the US, $160T, that’s 8 times current M2 Money Supply. So we’d see 700% inflation over two years and then it would be over!”
This is a grave misunderstanding of the problem; as the Fed expands money supply and finances Treasury spending, inflation rips higher, forcing the AMOUNT THE TREASURY BORROWS, AND THUS THE AMOUNT THE FED PRINTS in the next fiscal quarter to INCREASE. Thus a 100% increase in money supply can cause a 150% increase in inflation, and on again, and again, ad infinitum.
M2 Money Supply increased 41% since March 5th, 2020 and we saw an 18% realized increase in inflation (not CPI, which is manipulated) and a 58% increase in SPY (at the top). This was with the majority of printed money really going into the financial markets, and only stimulus checks and transfer payments flowing into the real economy.
Now Federal Deficits are increasing, and in the next easing cycle, the Fed will be buying the majority of Treasury bonds.
The next $10T they print, therefore, could cause additional inflation requiring another $15T of printing. This could cause another $25T in money printing; this cycle continues forever, like Weimar Germany discovered.
The $200T or so they need to print can easily multiply into the quadrillions by the time we get there.
The Inflation Dragon consumes all in his path.
Federal Net Outlays are currently around 30% of GDP. Of course, the government has tax receipts that it could use to pay for services, but as prices roar higher, the real value of government tax revenue falls. At the end of the Weimar hyperinflation, tax receipts represented less than 1% of all government spending.
This means that without Treasury spending, literally a third of all economic output would cease.
The holders of dollar debt begin dumping them en masse for assets with real world utility and value- even simple things such as food and gas.
People will be forced to ask themselves- what matters more; the amount of Apple shares they hold or their ability to buy food next month? The option will be clear- and as they sell, massive flows of money will move out of the financial economy and into the real.
This begins the final cascade of money into the marketplace which causes the prices of everything to soar higher. The demand for money grows even larger as prices spike, which causes more Treasury spending, which must be financed by new borrowing, which is printed by the Fed. The final doom loop begins, and money supply explodes exponentially.
Monetary velocity rips higher and eventually pushes inflation into the thousands of percent. Goods begin being re-priced by the day, and then by the hour, as the value of the currency becomes meaningless.
A new money, most likely a cryptocurrency such as Bitcoin, gains widespread adoption- becoming the preferred method and eventually the default payment mechanism. The State continues attempting to force the citizens to use their currency- but by now all trust in the money has broken down. The only thing that works is force, but even the police, military and legal system by now have completely lost confidence.
The Simulacrum breaks down as the masses begin to realize that the entire financial system, and the very currency that underpins it is a lie- an illusion, propped up via complex derivatives, unsustainable debt loads, and easy money financed by the Central Banks.
Similar to Weimar Germany, confidence in the currency finally collapses as the public awakens to a long forgotten truth-
There is no supply cap on fiat currency.
When asked in 1982 what was the one word that could be used to define the Dollar, Fed Chairman Paul Volcker responded with one word-
All fiat money systems, unmoored from the tethers of hard money, are now adrift in a sea of illusion, of make-believe. The only fundamental props to support it are the trust and network effects of the participants.
These are powerful forces, no doubt- and have made it so no fiat currency dies without severe pain inflicted on the masses, most of which are uneducated about the true nature of economics and money.
But the Ships of State have wandered into a maelstrom from which there is no return. Currently, total worldwide debt stands at a gargantuan $300 Trillion, equivalent to 356% of global GDP.
This means that even at low interest rates, interest expense will be higher than GDP- we can never grow our way out of this trap, as many economists hope.
Fiat systems demand ever increasing debt, and ever increasing money printing, until the illusion breaks and the flood of liquidity is finally released into the real economy. Financial and Real economies merge in one final crescendo that dooms the currency to die, as all fiats must.
Day by day, hour by hour, the interest accrues.
The Debt grows larger.
And the Dollar Endgame Approaches.
Nothing on this Post constitutes investment advice, performance data or any recommendation that any security, portfolio of securities, investment product, transaction or investment strategy is suitable for any specific person. From reading my Post I cannot assess anything about your personal circumstances, your finances, or your goals and objectives, all of which are unique to you, so any opinions or information contained on this Post are just that – an opinion or information. Please consult a financial professional if you seek advice.
*If you would like to learn more, check out my recommended reading list here. This is a dummy google account, so feel free to share with friends- none of my personal information is attached. You can also check out a Google docs version of my Endgame Series here.
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IF YOU WOULD LIKE to support me, you can do so my checking out the e-book version of the Dollar Endgame on my twitter profile: https://twitter.com/peruvian_bull/status/1597279560839868417
The paperback version is a work in progress. It's coming.
THERE IS NO PRESSURE TO DO SO. THIS IS NOT A MONEY GRAB- the entire series is FREE! The reddit posts start HERE: https://www.reddit.com/Superstonk/comments/o4vzau/hyperinflation_is_coming_the_dollar_endgame_part/
and there is a Google Doc version of the ENTIRE SERIES here: https://docs.google.com/document/d/1552Gu7F2cJV5Bgw93ZGgCONXeenPdjKBbhbUs6shg6s/edit?usp=sharing
Thank you ALL, and POWER TO THE PLAYERS. GME FOREVER
You can follow my Twitter at Peruvian Bull. This is my only account, and I will not ask for financial or personal information. All others are scammers/impersonators.
That is how London's LBMA has in the past revealed trading of > 2.5x annual global gold mine production each DAY. The metal contracts on the EXCHANGES themselves are SPOOFS.submitted by j_stars to SilverSqueeze [link] [comments]
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Forex Markt Manipulation Spoofing. 5 Dinge, die über Spoofing in Finanzmärkten wissen Spoofing ist eine illegale Art von Marktmanipulation, die wie Bluffen funktioniert: Ein Händler legt große Aufträge für Aktien, Anleihen oder Futures, um andere zu denken, dass der Preis nach oben oder unten geht. Dann, im Handumdrehen, der Spoofer hebt diese Befehle und setzt in entgegengesetzte ... Forex trading adalah Leverage sampai dengan 1:1000. Itu berarti Anda dapat mengalikan jumlah investasi Anda lebih bagaimana cara menggunakan Binomo dari 1000 kali. Sebelum Anda memulai trading Anda dapat memilih leverage Anda sendiri dari perdagangan. Market makers generate profits from the difference between the purchase and sale price of an asset. Or, to put it simply, the loss of a trader ... Forex Brokers List For this year’s edition of the best Forex brokers 2020, the team behind TopBrokers.Com spent hours of rigorous data gathering and consolidation to curate the list of leading brokers. In particular, the multi-functional table below provides a detailed comparison of Forex brokers which can be adjusted to a person’s preference. Forex Brokers. Free Broker Comparison List and Top 10 FX Brokers 2020 . Find the best Forex Broker and take your trading to the next level. Forex Expert Advisor Generator 5.1 - Publique sua opinião Registro de software relacionado ao Forex Expert Advisor Generator 5.1 na área de data warehousing. Pesquisa Avançada de Especialistas é uma correlação entre os nomes de especialistas e palavras-chave em uma área determinada de especialistas. Por exemplo, uma procura de análise de documentos pode ser obtida com os nomes de empre Forex-Top-Investments. The EURUSD long idea, buy on dips. Good luck 15. 0. EURUSD Swings lower at its support zone 130 Pips. EURUSD, 240. Short. Saeed966. Welcome Back. Please support this idea with LIKE if you find it useful. *** On a short term, it will rise to the trend line to re-test, then it will head to the downside at the aforementioned support area *** 57. 12. EURUSD Long . EURUSD ... Succeeding when you open up your live forex chart will be no straightforward challenge. You will need an understanding of how and what influences each currency and economy. You will also need to use fundamental analysis, charts, patterns, and the news to spot potential opportunities. Only then can you begin your journey to join the likes of famous forex traders, Ed Seykota and Richard Dennis.
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