Co-founder of Zurcoin.
On January 12, 2021, President Trump, in what would be his last, and perhaps most symbolic action as Commander-in-chief of the United States armed forces, made a journey to Texas to visit the border wall he had four years earlier promised Americans he would erect to keep out illegal immigrants from Latin America. “They said it couldn’t be done and we got it done. One of the largest infrastructure projects in the history of our country,” Trump told reporters in a brief statement that day. Trump could have just as easily have been talking about the cryptocurrency markets as he was the Alamo wall he was there to see up close.
During the four-year term of his administration’s office, cryptocurrencies had, after encountering a temporary bull market from mid-2017 to early-2018, been in something of a prolonged downturn after US attorneys and securities regulators had become anxious to prevent what they saw as unregistered securities listings in digital form from evolving on the Ethereum blockchain, where digital assets could be created at a whim.
Despite this fact, since January 12, 2017 until the day President Trump visited the wall, the digital asset market however had grown in value by over half a trillion dollars. In the weeks to come immediately following the Texas visit by Air Force One, the cryptocurrency markets would grow a further 3 times still by mid-way through the first quarter, enlarged by over 10,000% since President Trump had come to office. To what extent was such growth a US-led effort, however, or even anything to do with the Trump administration? Consider for a second the following: During the 2017-2021 period, USDT, a US dollar proxy, issued an additional 34.99 billion units of currency, representing an increase in the currency’s total capitalisation of 233,940%.
In addition, Goldman Sachs-sponsored blockchain company Circle and Binance both undertook during the same period to create separate US dollar proxy assets worth an additional combined $10 billion. When taken together, this makes the US dollar the third largest digital asset in the world today. In actual fact, there are roughly three times as many US dollar assets in digital form on the Blockchain today as there were digital assets in existence at the start of President Trump’s tenure in 2017. The explosion of digital asset values by over 100 times combined value happened in one of the most lackluster markets in the history of finance.
The very fact that such an enormous number of US dollar proxy assets were released into the digital currency markets over the past four years seems to be the only reason for that market’s explosive incremental growth over the same period in time. After all, releasing dollars into the cryptocurrency market expands it in size, but only very incrementally, especially if those dollars are being used as purchase units for other digital assets that are otherwise being sold continually against one another day-in, day-out. The 2017-2021 period was one in digital asset markets of some of the least innovation around. Unlike in the previous bear cycle from 2014-2016, there was no great technological innovation in the works such as Ethereum during this time.
Unlike periods of more subdued activity such as in 2012, there was no protocol innovation either such as had been the case back then with Proof-of-Stake blockchains. There was nothing. It was not Bitcoin, nor Ethereum, nor any kind of dynamic Blockchain innovation trend that led to the creation of trillions of dollars of assets, then. Rather, it was the issuance of so many US dollars in digital form into that market that led to this unprecedented explosion of the digital asset market.
A number of other observations reinforce the notion that digital asset markets during this period were part of a greater US policy agenda. Tether was a cryptocurrency ostensibly created by the controversial Blockchain entrepreneur and former Bitcoin Foundation President Brock Pierce. Pierce, a child star-turned-digital currency mogul, was under pressure in 2018 by US authorities to justify how he was backing every USDT in circulation with real greenbacks. After running for President in the 2020 US elections, Pierce’s problems had by early 2021 seemingly faded away, however. In February 2021, the company was fined $18 million, a paltry fraction of the billions in value that had been created in the intervening years. Not to reconcile these things with any sort of US political directive belies disbelief. The most significant evidence for Blockchain assets being some centrally-directed policy action from in part the Trump Administration’s Treasury Department however shows up in the expansion of the US money supply during 2020-2021.
Over the Covid-19 period, the US M1 money supply grew to what would by the end of the year represent an ongoing 80% rate of expansion. The M2 money supply, factoring in account deposits and other dollar-equivalent assets, and often used as a benchmark proxy for inflation, was growing by 25% a year and headed for annual expansion approaching 38% a year by the end of 2021 versus an annual average growth in recent years of just 6% a year.
The effect of this enormous expansion of the US money supply should have been creating rampant inflation in the US, pushing up all sorts of consumer goods prices. And yet, while higher, at 0.7% annual inflation by Q1 2021, inflationary pressure can hardly be squared with such a huge expansion of the gross US money supply.
In this article, I argue for the first time ever that the cryptocurrency markets are none other than a sort of value wall that has been interposed between the US dollar and the various global currencies that use it as a reserve store of value around the world.
In this paper, specific trends, characteristics, and functions of digital assets as blank slate inflation hoovers are identified and discussed in some considerable detail. Many of these have never been identified or discussed before the publication of this article.
The concept of a new value wall that now exists in a rapidly-growing trillion-plus dollar digital architecture rapidly in the process of being scaled, shaped into something of a macroeconomic Colosseum presents a number of problems and opportunities for a generation of traders and entrepreneurs throughout the world. It is to these problems that the focus of this White Paper is turned towards, and to the specifics of this unique, once-in-a-millennia or so event that is currently being played out, that the associated opportunities are identified.
The Mirror reflects waves off its surface, reversing an image in an equal yet opposite angle from the person staring at it. It also has a tendency to fool us into a false perspective of how others really perceive us.
Fig. 1: Hyperinflation of the dollar is reversed in the cryptocurrency mirror image
The mirror shows an exact picture of the scene except now reversed. Now consider how the US Treasury expands the number of dollars monthly. It does so by printing more of them, pushing the value of the dollar downwards. Now, however, it imposes a mirror against the printing of the dollar. This mirror is a slate of blank values, incrementally smaller in size than the number of dollars, in much the same way as a mirror’s waves are incrementally smaller in size than the light it receives. Instead of absorbing and refracting the light of the mirror image of the man hitting the ball however, the mirror, in this case, consumes the excess dollar notes by buying them up.
What is the effect of this monetary mirror? For one, it reverses the value equation of inflation, instead turning inflation into asset price growth. Depending on what the blank slate that is buying up the additional banknotes is – be it a security, representing assets and income values at some multiple, or be it a property, representing a place to house families, workers or goods and products – it will tend to reflect whatever value it is that is being consumed by the additional notes as increased value. How do we make the perfect economic mirror? The answer is, we make an asset with absolutely nothing representing its true value.
One of the problems with securities and properties is that they have very specifically-defined values. A house is worth roughly per square meter what the one next door is worth, and value increases are slow and steady, while a security has a multiple ascribed to it, representing the number of present year’s income that an investor is paying for a share of a company for example. Clearly, there are not many investors willing to pay 1 million years’ of the current year’s earnings of a company for a share, since doing so feels like stupidity.
These limitations on value are only natural when it comes to rational value selection: after all, we measure our relative status by our location, and our lifetime in years. If a house were to rise above the price of our own in a worse-off neighbourhood then it would make no specific practical sense to sell our own and move. If we were to pay one million times the value of a company’s present annual income, we might contemplate that given that most of us have only 70-90 years alive, that the one million year wait to get the entirety of our value back seemed a little far-fetched.
What if, however, we were to insert in the place of the mirror a blank, clean slate asset, one which had no particular location whatsoever, nor cultural nor any intrinsic bias in its composition? Further, what if this asset represented nothing other than the price that was last paid for it? This asset would be able to appreciate infinitely in value, to the extent that it wouldn’t really matter if it was $1, $1000, $100,000 or even $1 million, as long as someone was willing to pay this price for the asset today. But who would be willing to do that? The Federal Reserve Bank prints around $420 billion new US dollar banknotes a month, as of the start of 2021, which is around 2-3% the total value of all dollars currently in circulation.
Fig. 2: US M2 Supply Increase 2020-2021.
With so many new dollars being printed, consumer price inflation in the US should be skyrocketing. Electronics that cost $1000 should be selling for at least $1300 or more; raw materials such as wood, grain, coal etc. should be twice the price every 6 months. And yet they remain remarkably stable.
Why? Just as for the mirror, which absorbs the rays of light reflected into its surface and produces smaller ripples of light back, so the economic mirror of cryptocurrency assets reflects the dollar inflation as a reverse form of inflation once they are used to purchase the new dollars in circulation. In other words, purchasers of US dollars with cryptos acquire a huge amount of new, worthless dollars that they then keep on their balance sheet and which they give in return cryptocurrencies for in order to buy up. We can see superficially this is the case right now. Keep in mind the shape of the curve in the graph depicted in Fig. 2 as you look now at the graph for the rise in values of cryptocurrencies in the same period:
Fig. 3: CoinMarketCap Index Value 2020-2021
The reality of what is going on could not be more clear: an unprecedented number of dollars are being printed, inflating the US economy with new money supply. Then, within a period of 6-9 months, just within the time frame necessary for this inflation to bear out its worst effects on consumer prices in the US, during this period many of the new dollars are used to purchase cryptocurrency assets.
Finally, having risen some 500% in value (a similar percentage by which US M2 inflation rises in the same period), these inflated cryptocurrencies are then used to repurchase the new US dollars. It’s a “magic money machine” Paul Murphy from the Financial Times calls it – no net inflation! There are two practical issues with continually sustaining this strategy. They are:
To the first point, I refer to an interview I once held with Roger Ver, one of Bitcoin’s original investors. Ver was highly critical of the rise of altcoins, and maintained that someone must be purposefully trying to diminish the value of Bitcoin by creating so any other cryptocurrency assets. “I can’t think of a better way to destroy Bitcoin’s value that to break it up into thousands of other coins,” he told me. In some ways, that was correct, and in others not so.
Cryptocurrencies rise at phenomenal rates against the dollar. With thousands of cryptocurrencies constantly being subject to increased amounts of dollar purchasing power per month, this creates an even greater number of rising asset prices (in dollar terms) with which to purchase other cryptos, thus creating a sort of boomerang effect of value reflection. In other words, the cryptocurrency market has become something of a chamber of mirrors, with each mirror shining into the face of the other asset in an endless sequence of exaggerated infinite reflections. It is this effect that is fundamental to the utilisation of the cryptocurrency market as a vehicle with which to buy up over-inflated dollar notes, since the downward volatility becomes incrementally smaller, being as it is shared over a wider range of assets, while the repurchasing of cryptocurrency assets actually requires only a few initial channels into which dollars must be directed to get going.
It is clear from the US money supply expansion over the past year that inflation has risen substantially, to historical highs. This continued expansion of the US money supply creates the perfect environment for fresh new dollars to repurchase the beaten-down cryptos that are being used to repurchase the new dollars only a week or so before they begin to fall. There’s another problem too – by purchasing excess dollars with rising cryptocurrencies, you aren’t really stemming off inflationary pressure at all. More millionaires doesn’t mean less inflation, it just means less distributed inflation. This creates a whole other subset of problems.
Chief among these problems is the yawning gap between the two ends of the wealth spectrum that will surely become more exaggerated now that there are those participating in the growth of such assets and those who aren’t. Specifically, while the former will become immensely well off, being as they are to some extent reflectors of the inflationary pressure being assuaged by cryptocurrency markets, so will the lifestyles of the relatively much poorer majority of people not participating in such markets become increasingly less identifiable with those who are playing in these markets. In many ways, the effect will be one akin to a global Wall Street Investment Banking culture that mushroomed out of the post-war era of the 20th century.
Being prepared for this division in wealth spectrums and making sure one is on the right side of it is surely the number one aim of every intelligent young adult today.
It is not just for the sake of poetry that I describe the cryptocurrency market as a dollar inflation wall, and point to its attributes of value reflection as those of multiple mirror images. The cryptocurrency market is a highly-specifically-constructed macroeconomic architecture and its properties, like many properties of financial innovations, are directly analogous to equations and formulae that are discovered in everyday physics. In construction, there are two values that are commonly used to measure and describe insulation mechanics.
These are U values and R values. U values measure the insulating performance of insulated glass units such as windows in a building – that is, the extent of heat transfer (heat gained or lost through the glass panels). The lower the U value, the lower the temperature loss inside the room due to the glass, and hence the more efficient the type of glass is as an insulating surface. R values measure the insulating performance of all the other materials in a building, such as the walls, the roof, the flooring and so forth, and are a proxy for heat resistance. The higher the R value, the better insulation the materials in the building provide.
U values are directly disproportionate to R values, so 1/U = R and 1/R = U. For example, a U value of 0.1 (very little temperature transfer) would equal an R value of 10 (very good insulation), since 1/0.1 = 10. If we replace the concept of heat in temperature with dollar inflation, we can see that cryptocurrencies work in an identical sequence of trading pairs with respect to one another in a functional digital asset market.
Most cryptocurrency market crashes in fact are caused by an improper ratio between these U and R value proxies. This is why the ascent of the US dollar inside cryptocurrency markets has been the most long-term stabilising force of digital asset prices, and consequently, it is also why digital assets themselves are so effective at hoovering up the excess implied inflation that such a huge recent expansion of the US money supply has incurred. Quite simply, a currency trading pair needs to both reflect (transfer) inflation from an increase in supply to capturing and insulating such inflation inside a digital asset with no specific inherent value attribute.
This is why cryptocurrencies tend to ascend and descend in pairs, and are most effective when paired with dollar substitutes (since these hold fast and steady at a base value even as supply is increased, thus pressuring the inflatable asset – that being the target cryptocurrency – upwards in value, which is popular with investors and hence good for liquidity of the overall market).
The most obvious recent example of the effect of these values at work can be observed in the rise during February 2021 of Binance coin (BNB). In a matter of weeks, BNB soared from a low of around $7 to a high approaching over $300. In the days following this rise, BNB held steady around the $250-mark. How did this happen? Simply put, dollar inflation was injected into BNB in the enormous purchase of BNB with dollar assets and other rising cryptocurrencies. Once it had risen, BNB held steady as the result of the use of dollar-equivalent digital assets continuing to repurchase all BNB that fell into the low-$200 range.
These dollar-equivalent assets were in the form of Cardano (ADA). Following the rise of BNB, ADA began trading at just over a dollar and change. What was notable immediately at that point was the striking similarity in the supply of ADA and USDT. As the two currencies paired side-by-side among the top 5 cryptocurrency assets, it became clear that with a 10% smaller supply than USDT, that at around $1.10, ADA was effectively equivalent in substance and form to USDT, which itself is a dollar proxy. In other words, BNB was partly a mechanism for the US Treasury to add an additional $30 billion of US dollars to the Blockchain market.
How does this relate to the U and R values used in construction? If we consider digital currencies to be the glass through which high temperatures (dollar inflation) are transferred, then they are much like the insulated glass units we find in buildings. The lower such currencies U values, the less inflation escapes them back into the wider economy. Similarly, the more insulated these currencies are with the component value purchases of all other digital currencies, the more effective they are at retaining the inflation that has been passed onto them in the form of an increase in dollar supply buying them.
In the case of BNB, the asset has both attributes in place. We can think of high R values as being represented in things like multiple asset trading pairs, high-volume market-making usage and so forth. Clearly, functioning as it does as the base pair for the largest cryptocurrency exchange in the world (Binance), BNB has a very high R value in an inflation-equivalent context. Asset price inflation is retained in the coin which is used to buy other digital coins which then go up in value etc. In this way however, it also transmits inflation across the market as it is used to purchase the other cryptocurrencies.
To prevent BNB’s sudden asset price inflation from being lost in the form of pass-through as BNB was sold to buy other assets which were rising sharply as a result of this, a cryptocurrency with a vast amount more units and a very low price that could be stabilised around $1 each was used to repurchase BNB every time BNB was being used to purchase other cryptocurrency assets. ADA has the equivalent of an extremely low U value as a result of its vast supply of 34 billion coins and as a result of it superficially functioning very similarly to USDT, with traders arbitraging 2%-10% gains either side of the dollar price point.
Once traders recognised that ADA was in effect being used as a USDT proxy with wider value attributions (i.e. wherein they could make quicker short term profits) volumes in ADA trading soared as the currency wavered between $0.90 and $1.10 per ADA. In this way, ADA functioned as the perfect inflation insulation tool with which to maintain BNB’s high R value – inflation transference – character component throughout the rest of the market. We can see this relationship expressed in the mathematics of the supply and volumes traded.
On Thursday, February 25, for the previous one day period, BNB traded between a band of $236-$280, with most of the volumes focused around $245-$255, while ADA traded between $0.09731 and $1,07. BNB has the wider range here (around 19%) and ADA has the narrower range here (10%). If we take the amount of volumes traded of each coin, that being around 27 million BNB and around 7 billion ADA, and we put the averages of each trading percentile differential over the coin’s traded supply, we get:
BNB: 17% / 27,310,339 = 6.3E-9 ADA: 10% / 7827800480 = 1.21E-11
Now, to establish an inverse correlation, we put the answer to the formula for ADA over the answer to the formula for BNB:
1.21E-11 / 6.3E-9 = 0.0019
We now take the differences between E-9 and E-11 into account (E+2) in order to correctly express the percentage adjustment effect that ADA has on BNB in this 24-hour period as a currency pair:
0.19 = 19%
We can see here that the percentile if correctly adjusted upwards is identical to the percentile price variation in BNB during the period (19%). In this way, BNB can be considered to hold the inflation (insulating US dollar inflation) while ADA can be considered to be resisting the escape of such dollar inflation that has been injected into BNB.
Digital currency pairs work for dollar inflation exactly as do buildings for temperature. ADA is notable for the fact that it is never used for making payments. The ADA supply is most certainly very tightly held by a handful of individuals. After some brief marketing in 2017 the Cardano Blockchain has really made no progress whatsoever on any innovation front at all. This is because it was designed quite simply never to have such an impact. It was clearly launched with the intention of acting as a dollar proxy. We can see this from the fact that ADA maximum supply – 45 billion units – is identical to the maximum authorised number of units that USDT has – also 45 billion units.
Note that if we were to reverse this purchasing effect so that it was BNB that was purchasing ADA during the same period we would have likely ended up with a $1.99 BNB price and a $498 ADA price:
(6.3E-9 / 1.21E-11) = 51,793% / (7112484646 ADA / 27310339 BNB) = 260.43 = $1.99 BNB / $518.79 ADA
Naturally, this assumes only one-way buying, which is never the case. In reality, assets are bought and sold together. If we apply a 50:50 ratio to those prices we get:
$1 BNB / $259.35 ADA
Here is evidence of a precise inverse correlation with the actual price averages for both currencies that we witnessed materialising in the same 24-hour period in late February. This startling fact provides yet more evidence of dollar inflation correlation utility within Blockchain assets, since for this to be reversed, a very deliberate trading strategy has clearly been applied wherein values such as the U and R value equivalents used in construction for thermal insulation effectiveness are similarly applied to maximising the impact of dollar inflationary pressures inside the digital asset market’s price performance gains.
Clearly, dollar inflation was injected into BNB, and then both BNB and ADA in almost exactly equal portion were used thereafter to maintain the BNB holding price so that inflation was not lost to the wider digital asset market. This helps explain why substantial selling pressure is often artificially applied to Bitcoin and Ethereum, the world’s top two digital currencies by market cap, during such trading periods.
I have shown as has no one before now in a variety of ways – some anecdotal, some data-based, some theoretical and some using equations lifted directly from the physics of construction – how cryptocurrency assets are in essence, dollar inflation houses and essentially, nothing more than this. The cryptocurrency market was built to sustain a continued printing of the US dollar without transmitting inflation pressures onto the wider US economy. In order to achieve this, assets with no particular value whatsoever, and no discernible traditional value attributes were created over a period of years, and such assets were bought up gradually with the introduction of the US dollar via unofficial digital currency channels.
No doubt, the US dollar will be officially listed on the digital currency markets in the future, further adding to the inflationary effect of cryptocurrency market capitalisations. As far as new financial innovations and architecture goes, the birth of cryptocurrencies is some of the most audacious and significant of all economic events in history. Part of this architecture has to do with the concept of the Internet of Things (IoT).
IoT is a term broadly used to describe a world in which digital devices communicate with one another in order to better anticipate the requirements of their users, to improve efficiency or performance.
The issue with developing a sustainable IoT world to the present date has been that enabling the sort of value efficiency that such communications between devices entails in the consequential economic knock-on effects has been almost impossible with the present-day financial infrastructure we have in place. For example, the more efficient you make energy, the less of it is consumed. Since energy is sold in the form of oil and gas and other fossil fuels (for the most part at the rawest component level) and such fuels are sold in US dollars, the more efficient energy consumption translates into less dollar utility.
This lacking in dollar utility has been shored up by banks that are incentivised to lend these dollars to consumers who then spend them, but such a cycle only increases the cost of goods – including, ultimately, energy too. The resultant effect is one with higher living costs for North Americans and less base utility for the US dollar. This is just one simple example of why a dollar inflation wall has become so essential for the sustenance of the global economy but it clearly shows the risk that is embedded at the macro level today as a result of global innovation trends.
This exact scenario is indeed the sort of one which hyperinflation crises are made of. Thus, the Blockchain is not so much a new technological architecture, and the core components of decentralised finance are not necessarily, as has been sold, those of technological and privacy concerns foremost. Primarily, the Blockchain is a financial architecture aimed at converting consumer price inflation into capital asset gains on blank slate assets and in so doing, distributing inflation away from the North American shores around the world.
If we begin to view the Blockchain and associated digital assets in this way, it becomes much clearer what we ought to be primarily concerned with.
First, we need to be invested in such assets, since they are likely to rise significantly higher henceforth now the underlying dollar infrastructure is completely built-in to the Blockchain market making framework. Second, we need to be well-diversified, poised to capture any of the single rising assets among the multitudinous, and likely increasingly multiplying, quantities and types of digital assets around. Third, because of the emphasis of the market as one of possessing what can be best described as an inherently cooperative advantage, that being in that cooperation as opposed to competition builds increased size and influence, and capital gains returns within such a market, whatever strategy or structure we undertake to build on should be inherently decentralised at the core of its essence and purpose. Finally, we need to be well positioned to benefit from the impact of such value inflation increases as they continue to swell at the uppermost end of the market.
In times when utility, which is another way of saying economic benefit, was something that most people saw as being unconnected to value – such as achieving a win in a contest or raising a child, for example things were ordered much more differently throughout society than they are in today’s greed-biased economy.
Risk tolerance was generally higher over more prolonged periods, while innovation was more frequent and diverse rather than crowding around one or two themes in particular (such as apps or Blockchain). Skepticism actually ran to a much higher extent than it does today, where it is swallowed up in the corporate PR marketing engine. Where utility is comprised of experience-based as opposed to transaction-based activities, there is a higher degree of emphasis on the participant.
Value is inherently minority while utility is inherently collective. What has happened in recent years however is that value has become increasingly collective as vast amounts of money have been printed by sovereign governments, while new forms of utility have become scarcer. This process inverting the roles of value and utility has produced a largely apathetic, consumption-oriented, expectant population which is inherently dependent.
Value is the modern-day population’s primary utility. As long as people have more value, their utility demands are satisfied. As a result, the overall intellectual, emotional and ultimately, critical reasoning capabilities of people today are more intensively challenged far more frequently and for much more extended periods than they ever have been before. This trend is borne out in a number of interesting and worrying ways.
Throughout the 20th century, something known as the Flynn Effect1 came into play as production, innovation and wealth creation soared at an almighty rate. The Flynn Effect accounts for the increase in IQ as the years of the 20th century advanced. Up until 1975, there was almost a linear correlation in the year you were born and your likely IQ score being higher than that of your parents. And then abruptly, it began to reverse (Fig 1). In 2017, a study carried out by three Norwegian academics showed a sharp decline in IQ of children born in the years from 1975 to 19902.
The average IQ of an adult born within these years declined by about 3% from the start to the end of the period, the researchers found. Moreover, the further you get towards the end of the 1980s, the faster people’s IQs fall on average. As to why IQs are falling so fast, the researchers were stumped for an explanation, since cross-examinations of the results of each individual showed no particular cause.
“There is at most a minor role for explanations involving genes and … parental education socialisation effects of low-ability parents, and family size. While such factors may be present, their influence is negligible,” they concluded, adding that “changes in IQ over time are too large to plausibly reflect selection-driven genetic change in the population. While our results support the claim that the main drivers of … these effects are environmental and vary within families, we are unable to identify the causal structure of the environmental effects.”
Proponents of the environmental theory point to the rise in technological applications, in particular in computers, as the primary cause for the shocking decline in IQ every year that people are being born today.
This theory is easy to test. Moore’s Law stipulates that roughly every two years the number of transistors in a microchip doubles, and is used as a proxy for all sorts of technology growth comparisons. When we correlate the IQ decline rate from 1975-1990 alongside Moore’s annual 0.5 average rate, however, there is only a 4.7% correlation between the rate of technological growth and IQ decline over the years of the individual’s life. In fact, the evidence is that those with access to technologies are increasingly smarter than those without them.
When we map the money supply growth year-on-year alongside the decline of IQ of individuals studied by the researchers in Norway, there is an alarming 93%-97% correlation in the year in which someone was born and the decline in IQ they are likely to have versus the rate of increase in the money supply in the years in which they were born and which they lived. Incredibly, the greater that the money supply is increased throughout the years of early adulthood of the individual, the sharper the drop in IQ that the Norwegian researchers recorded in their study. In other words, an increase in the global currency supply is dumbing us down at a rate of what may be approaching around 0.5% a year for every year we are born. Transactional utility is weapon of mass-destruction to human intellect.
There is also on the flip side plenty of evidence to show how experience-based utility improves IQ over relatively very short spaces of time. A study carried out in Venezuela showed that after playing chess regularly over a period of just 4 months, IQ rates among children at school improved substantially.
Experience – which is to say, the general process of proactively engaging in activities that require vastly different types of of intellectual and emotional response, or in socially-constructive activities (and especially competitive ones) – makes us smart. Processing payments, visiting the Mall, flicking through catalogues or going to casinos has the opposite effect completely. With the rise of online stores such as Amazon, the corrosive effects of collective value appreciation on our general intellectual abilities is only speeding up. Karl Marx wrote in his second most studied economic treatise Das Kapital that “nothing can have value without being an object of utility.” The Communist economist did not mean this in a good sense. To Marx, elite men enslaved workers to their maximum expendable limits, putting them to work in factories and on farms until they could work no longer.
At the start of the Industrial Revolution, when Marx lived, this was a fair challenge to government of the day. It is becoming an equally fair challenge to the government of this day and age however that it engages in encouraging something of the opposite. Since the beginning of the decade, governments throughout the world have encouraged, cajoled and then forced individuals to stay at home, not to work at all, and in a few cases, even fined or arrested their citizens for breaking these rules. Forget for a moment about the reasons for these policy decisions, and just consider for a moment how much life has changed since the early 1800s when Marx was living. The Diary of Elizabeth de Hart Bleeker is the diary of a New York socialite that recorded her life from the age of 18 in 1799 until her early 20s in 1806. In several of the 1803 segments of the diary. de Hart Bleeker details in vivid prose the effects of an outbreak of Yellow Fever that year in Manhattan.
“Mama, Mary and Anthony went to Morris Town — Mama has not been very well for some time past, and she has gone to try if change of air will be of service to her,” writes de Hart Bleeker. “There is some talk of the Fever — a Vessel has been suffer’d to come in to the Dock, from the West Indies — one or two persons who had been on board have died. In the afternoon James mov’d his family out of Water Street to Mama’s — several persons have died near him with the fever … I believe it has been traced that almost every one that has died, has had some connection with the Vessel from the West Indies … in the afternoon, I went to William’s — his wife was very sick with the cholera …Papa and Mama return’d from Morris Town”
Now, alongside the above, consider the following observations from French publication Laissez-Affairs regarding the impacts on society of a purported outbreak of a novel strain of Coronavirus, the effects of which are negligible to those of the flu for by far the vast majority of people under 60 years old (and for those of de Hart Bleeker’s age, mostly unnoticeable):
While de Hart Bleeker spends her days visiting multiple sick and dying neighbours, speculating as to where the source of a recent outbreak of Yellow Fever in an almost excited fashion, 21st century 20-somethings are stuck in front of Netflix shows.
It is hardly surprising to find out that, during only the years in her late teens and early 20s that de Hart Bleeker write her diaries, transpired the following world-changing human achievements:
When sitting down to write the first draft of this article, an economics PhD who runs an asset management firm took contention with the hypothesis herein and asked to see the data being used. I scaled the IQ decline alongside the M2 money supply growth for the years from 1975-1990. My economist friend then independently created logarithmic variables on an inter-year basis, essentially adjusting the data for any blind spot variances between the years and neutralising it in accordance with gross variations over time. The result was that we ended up with a statistical variance of just 0.2. That's a bullseye covariance (see Fig 7).
There is however another explanation for the rapidly-declining IQs among the population other than that people are getting less smart. That is: our sampling data is getting much wider. As the money supply is increased so dramatically, numerous public-sector jobs are created in the process, as well as other benefit schemes put into place which materially make people much more well-off on the whole. This would have the effect of increasing the sampling data of individuals who might usually fall under the radar of the research analysts carrying out the testing. A calculation that I identified indicates strong probable likelihood that this is the case.
Annualised Lifetime Salary (ALS) is a simple method of calculating someone’s relative performance to another persons’ performance. In this method, we take the average salary of someone over the past 5 years and divide it by the number of years that person has lived.
So if you earned $20,000 5 years ago, $60,000 4 years ago, $80,000 3 years ago, $100,000 2 years ago and $150,000 last year, and you are 35 years of age, your ALS score would be $2342.86 ($20,000+$60,000+$80,000+$100,000+$150,000/5 Years Work = $82,000/35 Years Lived). ALS scores are revealing in a number of ways.
One way in which this data is revealing is that it shows that for all but the top 1% of people in the workplace, 40 years old is where most individuals reach their maximum income potential. In the top 1% of earners, there is an unusual trend that can be observed unique to this particular category, for while they do tend to peak around 40 years old, just as for the others, losing about 10% of their earnings power shortly after, they subsequently rediscover it and better it again during the next 19 years.
This double peak is unique entirely to the top 1% of earners and not observable in any other category of top earner. Furthermore, the ALS score loss is much more extreme in the 40-45 year old period in percentage terms than for the other earnings categories (about 10%).
Fig 4 – Income shares among earning brackets in the United States
Why is this? One possible explanation is that these individuals take far more risk than those in the other categories. Taking risk means that the individual is more likely to succeed big and lose big, of course. Most often, financial success – as for all things – is made up of a combination of experiences.
Another plausible explanation is that competition among such individuals intensifies much more in the 4-50 age group, as many of these top earners seek to take their careers or businesses to the next level, thus creating a significantly more crowded marketplace at the top at this juncture; by 59, of course, such individuals are invaluable to anyone starting a new business, in government or in any advisory or even senior management capacity, and thus their incomes return to their former status by this point. The other way in which this data is so potentially valuable is that it shows us how much we are currently skewering the real income curve.
There is still a lot of criticism concerning the wealth gap, which is the type of gap that de Hart Bleeker’s generation would have experienced in far more extremity than we do today. For all the talk of widening inequality, the wealth gap has not grown substantially further apart in the past 200 years, but has in fact come much closer together, especially in terms of gross household wealth5. When we use the ALS data to pool the gross wealth pools per income segment, we find that while there is considerably more income per capita among the wealthiest 1% of earners (naturally), the pool (share) of capital that they share in per unit of economic contribution (output) is in fact comparatively much lower since the 1970s, when the IQ data began dropping in tandem. The top 1% of all earners comprise about 3.3 million people in North America who generate about $30 billion of income a year. That is approximately a 7% share of all the wealth in the country annually that is generated by just 1% of the workforce in personal income alone.
For the other brackets of income earners, wealth is quite distributed as a percentage share, at around a fifth to a quarter of income generated by each progressively lower bracket of income earners. What this amounts to is a dramatic under-rewarding of the top income earners and a over-subsidisation of the bottom earners. On a net basis, this makes us all about six times worse off in terms of wealth circulation that it would if we hadn’t messed with it in the first place.
Specifically, we are underpaying the top 1% of earners by about 8.5 times while we are over-paying the bottom 25% of earners by roughly 10 times. There is no question that this is a result of the expansion of the money supply in recent years.
With so many public-private sector jobs created as a result of increasing subsidies, lobbying activities and in general, inflation of the money supply overall, many who used to get paid very minimal amounts for mundane, economically insignificant contributions have begun to see their incomes rise.
As a result of increasing regulation, higher taxes and the expanse of state-wide interference in private industry, top income earners have found it either impractical or unappealing to claim their fair share of returns for economic output. What effect would this have on IQ levels, though?
Well, for one, it decreases the incentive for smart people to think smarter than beyond a certain benchmark, for fear of being penalised for being too smart. Most of all however, this meddling in the wealth gap ratio introduces a whole other branch of people into classrooms and everyday white collar working society that would not otherwise have been there in the first place.
The effect is exactly the same effect as if one was to calculate a sliding IQ score, as quite simply, every year there are more people who are less intelligent being sampled by researchers testing for IQ scores. What’s the end-result of all this meddling in the money supply now, then, this time in the form of cryptocurrencies? To answer this, we must consider the effects of cryptocurrency price inflation on society overall from a monetary standpoint.
As I pointed out earlier on, with so much trapped inflation being distributed throughout the world there is not ultimately less inflation, but rather more distributed inflation. Whereas the ALS today between the bottom and the top of earners is relatively compact, we might expect to see a more natural free-market ALS distribution occur within throughout the world in the coming 5-10 years. This will undoubtedly have huge ramifications on societies everywhere, and makes combining oneself with others who have access to knowledge and pooling ones skills with other skilled individuals even more essential in the decentralised economy.
Decentralisation may promise everyone the opportunity to become rich, but it will ultimately end up falling much more on the onus of the individual concerned whether that outcome manifests or not. In this sense, decentralised, informal networks of vast ranges, being broad in spectrum of the cumulative knowledge equation of the network overall and varied in demographic mixtures of people of different class, race, gender and age, will hold enormous advantages over corporations with centralised and rigid hiring policies. In this way, to become a part of a leading network today is to end up becoming a part of something unimaginably prosperous and presenting in unthinkable levels of opportunities tomorrow.
Social Income Expansion
First, consider the following publicly available data:
Federal and State government employees in North America spending per capita outweighs individual personal expenditure on average about 17 times. This means that if the average person were to spend in the same manner that the state does, they would be around $750,000 in debt a year to banks and credit card companies. On average, most people have worked 13 years in the US. Therefore, the average employee in America, were he to behave as do his State and Federal government officials, would be about $9.5 million in debt barely a decade into his career.
Recall that the average employee peaks in terms of earnings power around 40 years old, and this means that by his point he obtains his maximum earnings potential, which is most likely around $100,000 a year, he is already $2 million in debt before interest, were he to spend in the manner that every government employee spends daily on average.
Curiously though, when we run the data alongside the earnings power of the Top 1% of earners, two things stand out. The first is that the Top 1% of income earners could just about afford to maintain such a running debt and retire without any debt at all. The second thing that stands out is just how easily the Top 1% of earners could handle such debt accrual were they to be working in a free-market vs. a state-regulated market. In fact, after 40 years old, the top 1% of earners would have more than twice the amount of annual income flowing in as was their very worst year of accumulated unpaid debt throughout their career counting all the years added up together. In this light, it becomes very easy to see what the government is doing: it is, via a process of regulating, interfering in and co-opting various private industry sectors, lowering the top 1% of income earners’ earnings potential by 90%, in order to direct this money towards the government spending treasure chest. In this way, real taxation of the top 1% of income earners is not so much an issue of direct taxation (although that does come into play too).
What government does is effectively oppress the earnings of 1% of all the highest earners among working people nationwide by around 90% in order to re-distribute such funds for spending among 5% of workers who are employed by the State. When viewed in this way, this might be considered a cause for some degree of alarm.
Now consider the following:
Yet again, we are presented with a compelling picture of how incomes are being streamlined, with the lowest level wages being constantly pushed higher, while the upper end of earners being pushed lower in capacity. A critic of such an argument might point to the 36% savings advantage that a higher-income earner benefits from over the average individual vs. the 64% disadvantage a public sector worker is at to the same person in this respect. But is this really the case?
When we factor in work hours, we find that actual income ratio differences drop substantially to those presented in the savings columns. Instead of being around 100% apart from one another, adjusted private and public sector incomes fall to just over a tenth of that much, at around 12.3% apart. What is interesting here is how the data stacks up with our earlier findings in the previous section in this paper. In section 4, I revealed how, in effect, as I stated above just now, there was a reduction of over 10 times in the incomes of the top earners in a state-run system vs. what would occur in a free-market system. Once again, we find the same slicing and dicing of the income ratio, with work hours playing a significant role in slicing up the differences between the highest and lowest earners to the average earner by a similar factor. There is simply no other way to state it more clearly – the government is purposefully obfuscating enterprise development. The traditional line is that government does this in order to stimulate maximum median income distribution in society, which produces more social equality/ There is scant evidence that this is either effective or in any way true, in reality.
It seems that social equality (which leads to a plethora of problems of its own in society, many, if not most of which are violent or undesirable) is the side-effect of something far more deliberate and less altruistic in intention: increasing government spending capacity.
The gap exists because of regulations and state interference in free markets, remember: regulations and market interference by government actors is always carried out for the same purpose as for most people going about their professions – to increase their income and their power in the area in which they are working. Thus, by meddling in the fortunes of upper-income earners, State actors are merely creating an increasing reliance on themselves as guardians of the monetary system. This presents a split with the ways of the past, where traditionally a local industry captain or two would dish out jobs, charity and orders to the town or village in which he lived and prospered. Instead now, the government has become more increasingly the one to which people have been encouraged to look for these same benefits.
What happens when this same population who have been encouraged to listen to, look up to, and vote for their elected officials as the protectors of their livelihoods discover that instead of maintaining their comparatively disadvantaged cash savings with ample value cover, those savings are being eaten away by excessive inflation those state actors themselves are responsible for bringing about in the first place? The answer to this question best explains why government needs so desperately in developed countries now to find a solution of any kind to the unprecedented increase in the money supply over the 2020-2021 period.
Quite simply, if there is no value that government can install against or underneath the rapidly-expanding vast quantity of units of medium of exchange, then their efforts to squeeze the income ratios ever closer together will literally all have been for naught. To make naught jump to a positive whole number takes a kind of multiplication that somehow, in front of everyone’s eyes, turns the number 0 into a positive fraction, then a positive whole number, and then a positive large whole number. And so it was that in 2011 Bitcoin could be purchased for around $0.50, and then by 2013 for a few hundred dollars; after that, in 2017, for a five-figure sum, and in 2021, what looks to be a pending six-figure dollar amount.
Crime & Society
One of the core arguments of those who argue for the necessity of the expansion of the State is that more policing equals less crime. Often, this argument is accompanied by a diagram showing how over the years, since around 1988-1990, crime rates have declined dramatically.
Upon closer inspection however, this argument does not stand up to scrutiny.
Fig 5 – Crime rates
When you map the crime rate in North America by percentage from the years 1960 up until the present day, what you notice foremost is a sharp rise from around the time that IQ started declining. At the point where we stopped mapping IQ declines however, which is to say around 1990, there is suddenly a sharp drop until the present day in the crime rate. Is it possible that IQ, or what is more, money supply, could stimulate fluctuations in the crime rate? The answer is yes and no.
First of all, it is not the case that simply because crime rates show a general tendency towards arching to a peak in about 1990 and then declining that this is true of all crime. Crime changes over time, as a result of technology, lifestyles and social factors. In 1960, cybercrime was all but unheard of. Perhaps most descriptive of these changes is the adverse increase in the growth in number of rapes. For all its spending on policing, government seems to be powerless to prevent the growth in male aggressors of their (mostly) female colleagues.
Fig 6 – Rape
At the same time, the number of assault cases appears to be declining in line with the broader trend of crime rates overall.
Why is there a sharp rise in recent years of rape crimes vs. assault and battery crimes? What is actually going on here? In essence, we can consider the transference of assault to rape as one of the same thing, except in the case of the latter a female is most often a victim, whereas in the case of the former, the victim is more likely to be male. This is an extremely worrying observation.
Men have ceased attacking other men and instead turned their aggression towards women. There is no question that this antagonism has something to do with the underlying equality that is being pushed on society’s income streams as a result of unprecedented state expansion. In other words, it’s possible to see the massive expansion of the money supply and the state overall as actually hurting rather than helping the problem of crime. When we adjust crimes for population growth and remove property crimes such as home break-ins (undoubtedly ameliorated by the expansion of the public sector) the crime curve is a lot flatter at the tail-end.
Given the extraordinary shifts in the decline in population growth then, it is impossible not to attribute the decline of crime in part to what is simply a less voraciously-growing population. In fact, population growth trends show a remarkable correlation with the curvature we see in the increase and then the decline of crime rates in the population over the past half century or so. In particular, it is notable that population growth shot up in the years when IQ decline set in sharpest over the 1970s-1980s. This undoubtedly all has to do in some way with the expansion of the public sector, which created a huge growth in jobs where there were none before, and thus resulted in an unprecedented number of births. The difference is that the previous generation was reactive to the money supply increase; what seems to have changed in society in recent years is how passive it has become. The 1980s was an era still imbued with intensive innovation growth; software, medical sciences, aviation and even the internet were all to come out of this period in time. None of these sorts of game-changing innovation are to be found among the multi-billion dollar capital injections that Venture Capital funds are pouring into technology startups nowadays, however.
Perhaps most curious of all is the growth in self-directed crime, particularly among males. During the periods of the population drop-offs and consequent crime rate declines, the number of suicides per 100,000 population has surged by 25%.
It is difficult not to see the rise in male suicides and the parallel increase in the number of rapes as part of the same problem, especially when these violent crimes are tabulated alongside the increasing equalisation of the income gap to near-like-for-like public-private salary levels. It appears that government, in its bid to increase the money supply so as to govern everything, has created a truer form of equality in society than has any ruling power at any point in history. Within this equality, however, exists vast unfairness, with the least capable individuals rewarded ten times better on average than they ought to be, and the most capable ones getting paid the same exponent less than they otherwise would in a free market environment. Added to this are a whole series of knock-on socio-political movements, as people in general take the government’s lead towards driving equality to extremes.
The effects of all this extra cash are, it appears, drastically lower birth rates, more workers with less intellectual capability and hence much less real economic progress, an over-reliance on the State, a pent up anger between the genders whereas there is a more passive relationship between members of the same sex, who no longer compete for money or sexual partners, since the government ensures their income ratios are kept within a safe band while that broad equalisation fails to product the sort of co-dependency that the most innovative generations before us relied on for their day-to-day measure of sanity.
In the end, just as more money failed to make us smarter on the whole or lead to more innovation (in fact it has had the reverse effect), so has a drive towards equality and political correctness managed in much the same sort of way to bring down the crime rate slightly without really affecting the level of violence that exists between members of society at all. Instead of men beating up men outside bars for the sake of a promotion or a hotly-contested significant career opportunity or the blonde or a brunette who’s inside, instead they are now placidly taking her home to rape her and then slit their wrists afterwards.
When the reality is scrutinised more closely for what it is becoming today, it ultimately becomes simply impossible to describe the expansion of the government policing budget as in any way having a fundamentally beneficial impact on day-to-day life, when the government’s expansion of state programs in so many other areas does so much to undermine any possible impact a larger police force could ever reasonably be expected to have in terms of contributing to our general well-being.
We have now covered in some detail a vast range of social and economic outcomes that are the direct result of the dramatic increase in the money supply that has been the single continuous, unwavering policy of governments across the world. We have come to understand that this reckless strategy of expansion of the State at any cost – including at any human cost – is being, out of necessity, subverted, by the State’s implementation of blank-slate assets with zero real utility or value and without any particular value ascription other than the values that purchase such assets and their reflected monetary quanta.
This summary is fitting in order to explain the general background and sociological context of what is going on today with respect to cryptocurrency market ascension. But what is the core economic driving force that is unleashing the present necessity and viability of such a strategy as that of raising a virtual currency wall that interposes the world’s number one reserve asset – that being US dollars – and the rest of the world’s currencies? If such a feat is being undertaken, there is most surely an economic formula that drives such activity, after all, as for all matters of economics. Z-Efficiency is a term I use here to explain the more quantitative economic reality that is bringing the current cryptocurrency market into bloom as we are witnessing now at the start of 2021. Through understanding the inherent dynamics of Z-Efficiency, I contend that the current path of ascending values of digital assets – and especially those of a decentralised, mineable and vintage pedigree most of all – is inevitable for at least the next 40 years and possibly more, in the same exact way that the lowering of interest rates in the US economy down to what is effectively the current real rate of interest, which is zero percent, was such an inevitability over two centuries ago.
Before understanding Z-Efficiency however, it helps to have a basis of knowledge in how monetary returns work and have evolved since the early 20th century.
Fig 7: Interest rates as displayed on CNBC
Economists often like to point out how the long-term direction of interest rates is cyclical, with periods of interest rate increases and decreases peppering the chart. While certainly true, this characterisation of interest rate trends misleads on a number of fronts.
First of all, every market trend confirms to its own internal asset cycles and as such it not very helpful therefore to point this observation out as being in any way characteristic or defining of the government bond market. Second, economists fail to take into account that interest offered by the US government on money invested in the 1700s is far from the same thing as interest offered on money invested today. Once again, we refer to the expansion of the global money supply.
Let’s be charitable, and overlook the inconvenient reality for a moment that back in 1798, when the chart in Fig 17 displayed on CNBC begins, money was exchangeable for precious metals, and simply start somewhere in the early 1900s as the fixed exchange of dollar bills and underlying precious metals for which they could be exchanged was starting to fall apart.
Around 1920, there were only 4 billion US dollar bills in circulation. Five percent of four billion is 200 million dollar bills. This was the effective rate at which the US government was required to expand the money supply then to make its interest payments. Nowadays, the number of dollar bills in circulation is around 5000 times larger in size. Therefore, an interest rate of 5 percent means the production of an additional 1 trillion dollar bills. This is, in and of itself, 250 times the entire amount of US dollar currency that was in circulation a century ago – and that is just the rate of expansion required to meet an interest payment.
When we speak of interest rates in the context of making comparisons between the Federal Funds Rate and the potential rise in cryptocurrency valuations, we must treat the former with the appropriate dilution curve that is embedded in the rate of US dollar expansion over time. US interest rates, what are called in economics the Risk Free Rate of Return (Rm), are currently set at 0.25%. This is approximately 20 times smaller than the rate of interest 100 years ago. At the same time, The money supply is 5000 times greater, and as such, we have in effect a real historically-equivalent rate of 0.00005% today. In real terms then, the interest rate impairment suffered by the dilution of currency has grown by around 2 million percent in size. When we translate this effect into cryptocurrency asset price gains that lie ahead, we can see that from CoinMarketCap’s index, which begins around $1.5 billion in gross value, that to date the index has inflated in value by approximately 1000 times.
During the period from 1936, when gold was part-unpegged from the dollar, until the 1970s when Nixon abolished the peg outright, the US dollar inflated in value approximately 10x, or about 2x per decade, or 20% per year. This appears to conform to some sort of underlying economic growth with the addition of some kind of government spending surplus requirement, so we can use this data as the broad benchmark against which we are to weigh the extent of cryptocurrency returns.
Cryptocurrencies have grown in value at around 100x per year on average over the past decade. Therefore, our benchmark unit of account is:
(CrG * USDi) * (CMCI*n)
wherein CrG is Cryptocurrency annualised asset growth, USDi is the annualised US dollar inflation, CMCI is the present value of CoinMarketCap Index and n is the number of years we are looking to forecast growth for.
For 2025 , the equation for solving how great the cryptocurrency market is looks like this:
(100 * 0.2) * (1,500,000,000,000 * 5 Years) = $150,000,000,000,000
Therefore, in just 5 years, we can expect a cryptocurrency market to sustain an exponential return up until $150 trillion. Naturally, in 5 years’ time, the equation will expand more so (as for the dilution of real interest offered on a US dollar investment in Treasury bonds over time), so the 10 year forecast for CMCI looks like this:
(100 * 0.2) * (150,000,000,000,000 * 5 Years) = $15,000,000,000,000,000
There will naturally be some sort of erosion curve on this forecast basis. If we wish to account for the erosion curve, the period between 1960 and 1970 offers us a potential example of how such a curve might play out; between these dates, the US money supply increased comparatively less than in previous decades, by around 65%, or 6.5% per year. Thus, accounting for the erosion curvature of asset price gains in the cryptocurrency markets in a similar way over the subsequent 5-year period:
(100 * 0.065) * (150,000,000,000,000 * 5 Years) = $4,875,000,000,000,000
The cryptocurrency market will most likely, by the turn of the decade then, equal roughly 5 quadrillion dollars in size. This represents annualised growth of around 320% per year. However you try, there are few investments you will find that hold this much potential around.
This effect is compounded by the reality that if the Federal government is indeed meddling in such a way in the cryptocurrency markets, then this makes such assets a long-term safe harbour, much as for Treasury bonds. After all, what is the core defining feature of risk-free? Is it not that the US government is intervening in the market and thus supporting it in some way, far beyond the extent of its organic limitations?
If we define risk-free accordingly (and there is really no other way to properly define it), then the cryptocurrency markets, represented by the Top 25 cryptocurrencies, are also subject to a risk-free rate. In which case, then the current risk free rate, commonly represented by the letters Rf, is effectively not 0.25% but rather, at least in terms of investments made in cryptocurrencies, around 320%.
Given that the historic re-adjusted (for inflationary dilution) risk-free rate from 100 years ago to the present-day is only 62.5%, then this is roughly 5 times over the historic risk-free rate broadcast until the present. CAPM is an equation that harnesses Rf to evaluate the likely expected return of an investment over a given period of time and is used as a conventional mechanism for evaluating all sorts of investments. It is expressed thus:
ERi = Bi(ERm-Rf)
where ERi is the expected return of investment, Rf is the risk-free rate, Bi is the Beta (volatility) of the investment and ERm is the expected return of the market.
With what is in effect such a high risk-free rate of return percolating the market the effective is one that should be ultimately massively destructive to the value of all sorts of investments with traditionally appealing income-tied return values on them, such as securities or real estate until the extent of cryptocurrency valuations is so large that the digital asset markets readjust and begin to move at less than around 5% a year over a 5-year average period.
To visualise this last point clearly, imagine you are assessing the value of a stock with a variance of 20% a year, and the stock market is returning around 30% a year on average. First, we use the Federal Funds Rate as the risk-free rate in the equation (0.25%):
1.2(30%-0.25%) = 35.7%
In this scenario, the investment gives us an expected risk-adjusted return of just over a third, which is a handsome profit for what is relatively soft speculative risk. Now, however, we use the 300% cryptocurrency forecast return of the market as our risk-free rate:
1.2(30%-300%) = -324%
The investment now is expected to generate us a risk-adjusted loss of over 3 times our money! Here is the fundamental opportunity-cost of building this value wall manifest in real financial terms: for the period of several years while the cryptocurrency markets are under construction in earnest, there will be no other appealing assets to purchase from a comparative basis to cryptocurrencies.
Naturally, all yield ultimately reverts to income, and so properties and securities will ultimately regain favour among investors, and maybe even in a number of cycles will blank-slate value and income value compete with each other over many decades, but unless you are using the cryptocurrency markets as a proxy for some sort of Rf expression within your chosen investment strategy, you are negative of alpha (market outperformance). This will come as a shock to not a few hedge fund managers and real estate fund managers in the subsequent years. A mixture between highly volatile blank slate asset returns and income asset returns is probably likely, given that investors will use different versions of the risk-free rate in their calculations as the wall of value shielding and consuming, and then ejecting worldwide US dollar inflationary pressure rises. This could have far-reaching effects for volatility and asset price gains in areas, as well as complete collapses of asset prices in other areas.
Applying CAPM to investment valuations also helps us see why it is Consider for a second how despite the extraordinary 25,000% difference between the century-ago dilution-adjusted real interest rate today of 0.00005% and the present nominal Federal Funds rate of 0.25%, there is a barely noticeable outcome in expected investment return pay-offs using the two:
With 0.25% as the Rf then 1.2(30%-0.25%) = 35.7% and with 0.00005% as the Rf then: 1.2(30%-0.00005%) = 35.999994% the percentage difference between the two being: (35.999994%-35.7%)/35.7% = 0.84%
In other words, after over 50,000% dilution of the US dollar in a century, there is less than 1% of value-utility flexibility left in dollar expansion. Another way of saying this is, even if the dollar was to increase by another 2%, the excess number of dollars in circulation could not afford to be invested in securities, real estate or any other form of income assets, since doing so would simply create a global asset price collapse.
Once you see the situation in this light, it becomes clear why the government is so protective and sensitive over entrance into the cryptocurrency markets. Simply, cryptocurrency assets are the last remaining hope the world has of avoiding financial implosion right now. Is there a long-term relationship between interest rates and cryptocurrencies? This is highly likely.
The more interest rates on government bonds are increased, then the better cryptocurrencies can be expected to perform, in reverse to the securities markets. This is because as interest rates are raised, so more international (foreign government) buyers will consume the new dollars being produced. In the process, less cryptocurrencies will be required to repurchase the excess dollars being printed. This however is a relationship where it still remains to be seen whether it materialises. More likely, the increase in cryptocurrency values will slowly start to give the US government more latitude in respect of its interest rate policy, as it increasingly becomes more self-sustaining to print new dollars. As a result, rising cryptocurrency prices may also mean rising bond yields, which again, would have a negative impact on securities and property markets.
If by this point you are starting to get a little lost, don’t worry. Most of those who I showed early drafts of this article to, many of whom are financial professionals with considerably more experience and success than I, had the same reaction.
There are only a few core concepts out of the above section that need to be fundamentally understood to get your head around the idea of Z-Efficiency and I will list them here in bullet point form to make it easy: * Cryptocurrencies are being used to buy up increased numbers of dollars * More and more dollars are being printed today out of necessity to keep the US government open and public services systems functional (i.e. to pay salaries, costs etc.)
Z-Efficiency refers to an economic definition that in this paper I am ascribing to asset values that are the result of conservative levels of monetary stimulus. When governments print new money, there are a number of options open to them:
Whenever governments print money and pursue one of these four directives, the net effect (especially in the case of 2) is to push the value of asset prices higher, if, that is, the government wants to avoid the outcome presented in 4. For the most part, the four options listed above are the available ones to governments that are printing increasing quantities of money in order to sustain the cost of running their social welfare systems and various government agencies.
It was this strategy of propelling asset price inflation versus consumer price inflation that is what most likely – either in major part or certainly in substantial part – produced the collapse of the property market in 2007-2008. By stimulating the property market to such an extent, by reducing purchasing thresholds for property buyers and making credit readily available, the US government found itself in part in competition with financial institutions that required the end-users – in other words, the property buyers – to meet interest payments on their enlarged property debts. For a long period of time, much of these defaults were offset by decreasing market regulation thresholds for lenders and by allowing new entrants into the market. Ultimately, this had the effect of stimulating the number of new lenders operating in the marketplace faster than it did the rate of income growth that property buyers had coming in, and as a result, property buyers simply refinanced between the excessive number of lenders around, taking advantage of interest-free periods of borrowing and moving on.
When the number of players willing to enter the increasingly tumultuous lending market began to slow down, the buyers had nowhere to refinance their property loans, and ended up having to forfeit their real estate assets to the lending firms. As a direct result, sellers – or foreclosed property buyers, more like – outnumbered new buyers, and property prices crashed. Clearly, asset price stimulus are more desirable than consumer price stimulus in a market that doesn’t consist of majority wholesalers.
The US economy consists of more buyers than sellers. At least in the case of an asset price stimulus, there is some outcome wherein the owner borrow against the asset on more favourable conditions or sell at a better price, and use the cash in order to start a business, buy a house, or educate his children, after all. This is what made the property market so effective as a target for inflation. When people buy and sell houses, they usually use all or most of the money that they receive selling one property to finance the purchase of another.
Naturally, there are additional consumer retail sales involved in the purchase of furniture and installations, but for the most part these purchases do not impact the cost of basic goods that someone purchases on a daily or weekly basis.
Money made from the capital gain increase of one property tends for the most part to flow into the refinancing of the property in order to acquire a second property or as additional capital that affords a bigger down-payment on a new property.
After subprime, property prices were not a viable option for inflation targeting for a while, and so naturally, the excess dollar cash targeted the next most desirable asset class: securities. Since the previous bottom of the Dow Jones was reached on March 9, 2009, the index has risen an average of 25% a year, while the bull market run in stocks has extended approximately 50% over its average cycle period. By comparison, in the previous bull run, from around 2002 until 2007, the Dow Jones increased just 8.3% a year.
Still, the present bull run in stocks is far from matching the 40% a year bull run experienced during 1988-1998, in what was an unprecedented (for the time) period of monetary expansion. The discerning reader will notice that earlier I indicated that cryptocurrencies and securities naturally move in opposition to one another, and that specifically, I indicated that the rise in cryptocurrencies should, on an market value basis, have a downward effect on the prices of stocks. Is the present stock market bull run due for a sharp ending, then?
This is an interesting question, and the effects of cryptocurrency price inflation on the stock market in general remain to be seen in full. Certainly, securities listings are increasingly inclined to cash vehicles (presumably to convert such cash holdings into cryptocurrencies or to allow for more dollar inflation investments as time goes on) and towards a trend of companies taking reserve holdings in major cryptocurrencies (Tesla, Sun Micro and even possibly Apple, soon, if it takes the advice of the venture capital investor Tim Draper.)
Most likely, many stocks will fall quite a lot before they rise again, whereupon they will experience exorbitant rises in value. This is because of the effect of Z-Efficiency. Z-Efficiency is the amount of value in an income-producing asset that is market-efficient, external of any value created by government monetary policy action.
In latter years, many stocks have risen, as we have discussed, simply for the reason that the money supply has been so substantially increased. This amounts to a net Z-inefficiency in the pricing of listed securities. When assets are Z-inefficient, they tend to go in the opposite direction to the one that they are going in currently. When they are as Z-inefficient as they are today, with historically-extended bull market runs, the declines can be very rapid very quickly.
What is unclear for now is to what extent the stock market is likely to continue being Z-inefficient now that the US government has begun buying up and using cryptocurrencies in earnest as a vehicle to harness US inflationary pressures. It is highly possible that as cryptocurrencies rise a lot initially that many institutional investors will simply refinance their cryptocurrency investments and use the excess cashflow to invest in back-door listings of larger, more cash-flow heavy foreign companies from emerging markets that come in force to the US as the dollar strengthens on the back of the wall of these cryptocurrencies. In this case, stocks could have some way to go before they reverse course, and the probability is that this is indeed the case for the time being at the start of 2021.
Cryptocurrencies, of course, are pure Z-inefficiency encapsulated in an asset class. There is nothing that is remotely Z-Efficient about cryptocurrencies whatsoever – they are simply the byproduct of US dollar inflation fed into a blank slate asset with no utility or value that in turn consumes the additional dollars that inflated their values in the first place. The whole entire point of cryptocurrencies is that they mop up Z-inefficiencies form the wider economy.
Z-Inefficiencies are manifest in skewered equations, wherein real historic interest rates are decimated to zero and where negative capital asset returns are the outcome of valuations that factor in the risk-free market rate of return. In markets with high Z-Efficiency, such anomalies are not present since capital functions as a medium of exchange only, and as nothing more than that. Z-Efficient economies are not always the best ones to live in, however.
Markets with rampant hyper-inflation in consumer goods prices can – and usually are – still highly Z-Efficient, since in such cases (in particular those in Latin American countries over the past 20-30 years) inflation affects the purchase of raw goods but not necessarily the value of assets and investments that have an income yield, which otherwise tend to hold up very well as a result of their cash producing characteristics. \ For example, in 2019 Argentina’s economy relapsed for a second time in two decades into hyper-inflation. Consumer goods prices surged more than double the cost at the start of the year. Property prices, however, before they were readjusted for downward inflationary pressure on the foreign exchange purchase values, only nudged lower by 2.5%
In a market where consumer goods prices had risen by so much in the preceding year, the lack of price impact on Argentinian real estate valuations stands out. This is Z – the intrinsic value of the asset, without any monetary policy influence accorded to its pricing – at its most efficient. When Z is present, hyper-inflation economies are able to recover, and in most cases, the presence of Z is the reason in major part that they do recover. In such cases asset pricing in property and even securities markets, despite being surrounded by an economy afflicted by some of the most devastating pricing effects of all, which is to say, the day-to-day trials and tribulations of fluctuating living costs, remain relatively stable and unaffected, since normally in such cases governments haven’t interfered in such markets, their focus typically being more public-services directed.
We calculate the amount of Z in an asset by performing a standard correlation analysis between two or more data sets, in the same way that I did when analysing the IQ of individuals born between 1970 and 1990 and the direction of the money supply. In the case of the Dow Jones Industrial Index, I took the monthly data going back to September 2019 up until the start of 2021, and adjusted the data to reflect the number of billions of dollars that the market rose or fell in a given month. I then performed the same analysis with Bitcoin, which represents 60% of the cryptocurrency market. For every single point in the DJIA there is around $264 billion of value that moves up or down with it on any given day. One can see from a cursory glance that the two values are highly-correlated, even down to the billions of dollars that both ebb and flow within:
Figure 8: Stock Market vs. Monetary Inflation (Growth)
The correlation analysis shows just to what extent the two are related: Once again, we have dead ringers for correlation. There are a few things to notice here however. The first thing to notice is that the DJIA is just under 85% correlated to the increase or decrease of the levels of capital produced by the Federal government influencing the money supply, and that Bitcoin is 80% correlated to the same event. This is, in statistical terms called a valid correlation analysis (as you will recall from the comments made earlier on my analysis of IQs by my economist friend, “anything 0.2 or lower is significant”). Second, however, is to the question of whether the two values are positively or negatively correlated. In April, we can see that there was an enormous stimulus undertaken by the government.
Given that the extent of the stimulus was so historically unprecedented, I calculated two numbers, with one including the stimulus month and the months before that, and one that only showed the correlation since May 2020. As you can see, the stock market performed inversely to Bitcoin in both events. When we tabulate the results for the entire period, the stock market shows a positive correlation with the money supply increase for the entire period (0.1470986), whereas when we map the results for the period since May 2020 only, the correlation becomes negative (-0.145600131). Conversely, when we map the Bitcoin price fluctuations monthly for the entire period, we have a negative correlation (-0.2365), and further, a slightly less than precise correlation than is statistically valid. However, once we take the post-May numbers into consideration, we have a precise positive correlation (0.2019).
There is perhaps no other evidence greater than that presented in the above paragraph that cryptocurrencies are Z-inefficient assets designed to absorb US inflationary pressure more that presented in the above paragraph. In simple terms, what the data spells out is that since the massive 2020 stimulus at the start of the second quarter, whenever the money supply was expanded by more than the previous month, the stock market began to go down by a comparative amount more than the money supply was increased by, whereas Bitcoin began to go up by the same amount that the money supply was increased.
This shows clearly the inverse relationship that securities have to cryptocurrency prices as I outlined earlier in this section perfectly clearly. The reason for the inverse correlations is, as I explained, cryptocurrencies function like government bonds do, consuming excess dollars as their prices rise (or, in the case of government bonds, as their bond yields narrow due to interest rates going up). Cryptocurrencies are more like Treasury bonds than any other asset we have ever seen, which is why they function so well as cash.
All this no doubt has some interesting accounting implications for companies buying and holding Bitcoin, as has been the case in the very recent past. On a company’s financial balance sheet, there is a line entry marked “Cash & Equivalents” that you will notice towards the top of the financial statement. The “Equivalents” portion is typically reserved for assets such as Treasury bonds and Bank Certificates of Deposit – in other words, assets with risk-free characteristics (CDs are often considered risk-free due to their Federal Depositary Insurance Certificate status – the cash behind them, being as it is, guaranteed by the US government in event of loss). It is in this line entry that is where ultimately Bitcoin and any Top 25 cryptocurrency holding belonging to a company ought to end up, since the asset held, in this case Bitcoin, most strongly resembles the assets typically put in place on that line item entry point. If this is the case, then it will become possible for a company to refer to its inflated balance sheet as “cash”, thus invigorating over time the market for Mergers & Acquisitions, and perhaps even stimulating many hostile takeovers of poorly-performing or debt-saddled companies in the same way that the credit boom in the 1980’s provided corporate acquirers with an easy means to snap up a rival firm.
To summarise then, Z-Efficiency is the amount of Value Independence that a given asset has versus the Value created by the government in which an asset is situated or priced stimulating or reducing its money supply. We can calculate Z-Efficiency as a correlation; where there is a strong correlation (<0.2) then the asset is Z-Inefficient, meaning that its Value is highly tethered to the government increase or reduction of the monetary supply, whereas when there is a medium correlation or a strong correlation (>0.2), then this is a sign that the asset’s Value is derived more commonly of substance that is derived from other factors. Further, since Z is expressed as a correlation, unlike X or Y, it has two possible interpretations. The first is that Z is positive; where this is the case, then this assumes that the monetary stimulus policy of the government in which the asset resides or under whose currency issuance the asset is priced is being directly stimulated in order to sustain the value of the asset concerned. Where Z is negative, then this tells us that there is some other variable (asset) that lies in between the asset being analysed and the money supply.
Fig. 9: How Z works
Clearly, we would expect assets with positive correlation to government monetary stimulus actions to increase rapidly and wildly in value whenever the monetary supply is increased above a certain level, and ones with negative correlation to act in the reverse way, going down. However, this is on a purely theoretical level. The problem with economics as a science is that it is a science of a philosophical variety, seeking to exact human behaviour in the most calculated terms. Human behaviour is, if anything, unscientific in practice. Over time therefore the relationship between positively and negatively Z-correlated assets is not necessarily as straightforward as outlined in the Figure, despite that being the rational model for behavioural activity presented by the Z Efficiency theory.
Most likely, especially if it is unduly large, any capital gain an investor receives in the positive correlation asset class is likely to be reinvested in the negative correlation asset class should the latter fall in value while the former goes up a lot, since pricing in the negatively correlated asset class is likely to present an extremely attractive investment opportunity. Hence, there may be a great many incidences in which monetary stimulus is expanded aggressively, but, because of the previous month’s (or quarter’s) equally aggressive expansion of monetary supply, stock prices are buoyed by extra-aggressive gains that investors receive investing in cryptocurrencies.
If cryptocurrencies become used as financing vehicles in and of themselves, without being bought and then sold as capital assets but rather, used to borrow against to produce increasing (over time) amounts of capital that is then invested in securities, this could have a massively-incremental positive value effect on the prices seen in securities markets.
Such a financing strategy is appropriately applied would most likely highly-efficiently allocate Z by offsetting excess Z in the unencumbered part of the positively-correlated asset class represented in the loan collateral. This may be one long-term policy aim of the Federal government in stimulating the cryptocurrency markets as they are today.
Readers who are not economists may be wondering why I have ascribed the label Z-Efficiency to Value that is unaffected by government stimulus. Simply, Z is the next letter in line after X and Y, both of which are standard economic efficiencies and inefficiencies used to express corporate operating performance in relation to government policy. In 1966, Ukrainian-born economist Harvey Leibenstein postulated that economic theory was inexact in its measuring of productivity in corporations.
Economics dictates that a company will always allocate all available capital towards being as productive as it could be. Dr. Lebenstein maintained that this was incorrect when it came to monopolies. Monopolies owned by the government, he argued, were different to private corporations in that they did not need to compete with anyone for business. In such environments, Lebenstein argued, production (“X”) as an allocative efficiency, actually declined over time, the longer that the company was owned by the public sector.
Subsequently, in 1981, D.W. Pearce added to Dr. Leibenstein’s X-Efficiency paradigm by postulating that, even if a monopoly was as efficient at production as any private corporation, it could still potentially violate another economic principle – that companies will always seek to maximize profit. Where there is no incentive to compete, there is no requirement by a company’s management to produce anything other than what it already produces, stated Dr. Pearce.
X and Y inefficiencies are allocative inefficiencies then that are derived from the inappropriate allocation of resources to a problem as a result of government interference in a market. Ultimately, X and Y inefficiencies, when allowed to go on for a long enough period, lead to economic decay and a lack of overall innovation and economic capture by the economy housing such companies. It is on the basis of this theoretical foundation that I derive the term and academic justification for the concept of Z-efficiency.
I contend that wherein a company is privately-held by stockholders, and where it is both X- and Y-efficient, that the government’s stimulus of the economy continually via net increasing the money supply amounts to the same thing as XY inefficiencies reflected in the form of absurdly increased valuations on the stock prices of companies. While it is possible for a company to retain production and profitability efficiencies in line with privatized corporate practice, it is the tendency of any private actor to try and embolden the valuation of his company to the greatest extent possible over time.
Where there is monetary stimulus available in the market in excess to what is being recycled via appropriate X- and Y-efficient capital allocation gains, there is a deterioration of Z, to which we can ascribe the correlating value of a company’s share price to its actual financial performance within a reasonable price-to-earnings or price-to-book ratio spectrum. When we look at the P/E ratios of S&P 500 companies over the past century, there is a clear inflation of median valuations present.
This inflation of value is the result of the inflation of the monetary supply.
Value can be defined here alternately as growth, since when we refer to a company going from “a $2 million garage enterprise to a $2 billion giant” in the media, what we actually mean most of the time is the net valuation of the company that investors are willing to stomach in the market, since far more often than not, this is the largest number that we can ascribe to a corporate value.
As can be seen in Fig 20, whereas X-inefficiencies are mismanagements of cost allocations within a enterprise, Y-inefficiencies are mismanagement of market share quanta. Z-inefficiencies by necessity assume that companies have managed to close these loops, and are running as productively and profitably as they can be.
As a result of the stimulus effect created by a government’s expansion of the money supply, companies in effect choke themselves on their own profitability and market opportunism to the extent that they become nothing other than vehicles for capital market pricing of monetary value allocation.
This, in turn, achieves two Z-inefficiencies – a positively-correlated one wherein a focus on mass-production (or sales) leads to excessive focus on volumes of goods sold at the expense of profit, or a negatively-correlated one wherein a focus on underlying cash value leads to the premia valuation effects of a company’s cash a as a portion of balance sheet assets.
This dichotomous splitting effect in the stock market is exactly what we have witnessed since 2020, where the majority of investment action in listed companies has revolved around cash vehicles. Cash vehicles are a tell-tale sign of high levels of negatively-correlated Z-inefficiency in a market, since at such a point a company seeks to emulate the expansion of monetary supply as much in line as possible with the government stimulus actions, since not doing so punishes a company’s valuation. This is why so many companies are starting to buy up the most positively-correlated Z-inefficient asset there is going around – cryptocurrencies.
Fig. 10: P/E Ratios of S&P 500 Companies
To what extent will the establishment of a negatively-correlated relationship between private industry and the government have on companies in the forthcoming years? Most likely, production (or sales) will start to come in second place to public enterprises acting as mere holding vehicles for value accrual in order to maintain their bloated P/E values. This will create a number of opportunities for start-up companies looking to take parts of market share of such companies that was previously thought to be a challenge that is akin to being almost insurmountable in effort.
As major listed companies gravitate more so to becoming investment holding vehicles and less and less operationally-efficient in allocation of their time, money and resources, so will opportunity open up to the entrepreneur to provide the underlying services that such companies used to maintain in X- and Y-efficient ways. For the investor, such new variations in Z-efficiency make the act of making money initially easier and then much trickier. For the first period of the currency Z-inefficiency cycle, making money is as easy more or less as buying and holding an asset (and maybe even leveraging the asset a little so that another asset can be purchased). However, as entrepreneurs begin to take aim at Z-inefficient companies (which is to say, companies with such high levels of XY-efficiency allocation that they become ultimately little more than holding vehicles for the production of value within the gross domestic monetary expansion), so will value begin to fragment accordingly.
It is when this happens, in the second cycle of the breakdown in z-inefficiency, that z-efficiency can be gleaned as breaking through. At present, there is no telling how long the present cycle of Z-inefficiency will continue to go on. It will likely last at least 5-10 years in earnest, until value accumulation is so extensive in some pockets and so relinquished in other pockets of the market that channels for capital flow begin to open up transparently. Conclusion: Mind The Gap If you’ve ever travelled on the London Underground subway, you’ll recognise the expression “Mind The Gap”, where the announcer – usually a telephonically programmed voice today, warns passengers alighting and disembarking the carriage to beware of a gap between the train and the platform.
Much could be said for markets of high levels of one sort of efficiency or another. Efficiencies in corporate operations tend to be manifest in the sealing of gaps manifest in operating inefficiencies, and the affect is one that is usually money-related. In the same way, efficiencies in monetary economies tend towards value being identified and made fairer and more distributed in how it is represented in the pricing of capital assets. Inefficiencies in both operating and investing contexts tend towards identification of the gaps that are manifest in these respects and in closing them up. The problem for investors in allocating capital in markets with high organic levels of Z-inefficiency is similar to the one for operators working in markets with high levels of allocative inefficiencies. While there are indeed valuation effects that in ordinary market environments be targets of potential sealing, conventional asset pricing doesn’t always work the way its meant to, for some of the reasons that I outlined in this paper.
This means that what George Soros termed as “reflexivity” – the extent of mis-pricing in relation to market equilibrium valuations that goes on for extended periods of time – is present to an extended degree. For investors who are investing according to General Equilibrium methods of capital allocation, there is a break-down in the rules. This is because, much like the passenger boarding the London underground subway train, value inefficiencies in markets of a degree of rotation of Z-inefficiency re-allocation are powerless to seal the gap that lies before them due to the extent of power created by fiscal stimulus. Where such traditionally conservative and applied economic and investment theory is practical, it is likely to be so in ways that are non-conforming to the traditional asset valuation stereotype.
You tend to hear a lot of Blockchain innovators these days talk about “alpha” and “fundamentals”. What possible market alpha could an asset with zero intrinsic value rightly have, though, let alone intrinsic value to form the basis of what we usually group together under the term fundamentals? The answer is – none. And yet such investors are achieving many times the returns of investors who apply conventional capital allocation strategies with what is usually an extended period of outperformance, time and again.
This is the effect of massive Z-inefficiency at work, wherein markets with capital assets of any king are best-served by the pure production of capital itself, in an attempt to mirror the increase of the money supply. Will these effects fundamentally alter the future of valuation, or are they are trend like any sort of market fad, that comes today and is gone tomorrow? This is a hard question to answer. It is like answering whether operational inefficiencies among monopolies operating in communist countries are more likely to become more efficient in light of such monopolies trying to compete on an international level with privately-owned market incumbents, or whether because of the relative comfort such monopolies enjoy with respect to being government-subsidised, they will simply continue being less-efficient than the competition. In some ways, such companies have over the past 2 decades become much more efficient, hiring in outside personnel to close efficiency gaps so that operations become more streamlined.
Governments, most of all, have benefitted from such incorporation of private industry practices within their gargantuan monopolies naturally, as they are the majority owners. Governments have also found a viable cash resource in selling off portions – or sometimes, entire holdings – of publicly-owned state assets. In such cases, companies have broadly become more XY-efficient, though not necessarily more innovative. It is most likely a similar situation with respect to the proliferation of Z-efficiency effects in the capital asset market. Companies will, rather than become entirely dislocated from conventional valuation mechanisms, be heavily reliant on at least a portion of Z-inefficient asset value representation in order to be successful.
What this means that over the long term, more companies can be expected to hold cryptocurrency assets on their balance sheets as Cash & Equivalents line items in order to remain intrinsic value-competitive with others that do, at the same as maintaining their XY-efficiencies in tandem, since by doing so, they will in fact become more Z-efficient. The backwards logic of this statement is not immediately apparent to most investors, but it is the case.
By maintaining a highly selective approach to how cash is represented according to a fundamental economic inefficiency that is acknowledged to be pervasive within a market, a company is more independent of the effects of a government’s monetary policy than if it simply holds cash, which is directly being inflated by the government under whose laws it is domiciled. In this sense, cryptocurrencies, while ultimately being created as hyper-z-inefficient assets, are one step removed from the z-inefficiency of the most significantly-employed asset class in the world: cash.
A company that holds vast quantities of cash on its balance sheet, after all, is more directly impacted by the government’s monetary stimulus effects than is one which holds the cash in the form of a uniquely-applied allocation of cryptocurrencies, since at least the latter is an indirect representation rather than a direct manifestation of quantitative easing and tightening approaches. After all, as we inadvertently saw was the case earlier in this paper, cash and Treasury Bonds’ interest rate mechanisms, if scientifically applied, are equivalent to the amount of inflation that the government has subjected cash to over a period of time, whereas cryptocurrency, while still broadly z-inefficient in the same way, maintains an approximation of this inflation. That approximation is manifest as a reflection of the monetary inflation quanta as opposed to the exact replication of it in substance. The title of this paper implies that the effect of cryptocurrency price ascension and the prevalence of digital asset value creation in the marketplace over the forthcoming years will be one of substantial transformative effect. Whatever one’s position in commercial or government service, this observation is the most important take-away from this paper.
The old world of sovereign cash values trading against one another in line with imports and exports will seem vastly more simplistic than the one where there are numerous different relative trading values with which to offset the inconvenience of cost, production, capital reliance and profitability. Instead, in the place of such burdens, will emerge numerous opportunities to the entrepreneur, who will be able to, with very little substantial reserves or perhaps facing a very certain end, transform his own ideas into profitable, scalable reality in what now seem implausibly short periods of time as he bridges – rather than welds together as in times past – the gaps of this new form of government-initiated capital market inefficiency. For everyone else, there will always be the US dollar to continue to spend irreverently into bankruptcy administration.
(Disclaimer: the author is a co-Founder at Zurcoin)
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