PHD Ratio, Rock Bottom Mining & Peak Tether

Bitcoin’s Hashrate (Daily PetaHashes) to Daily Mining Earnings (PetaHashDollar) is a robust metric to asses the day to day mining profitability. In addition, when plotted over the past five years, its overall trend represents a good way to quantify and visualise the relative progress in efficiency of ASICs (more specifically the inverse of that metric: 1/relative mining efficiency).

However, this is a relative and unadjusted metric. Its mathematically correct units (peta)hashes per USD are somewhat inappropriate when assessing the long-term trend. For an adjusted version, it is necessary to consider not only the increase in efficiency of processing power (c. 60 fold), but other factors which are significantly more difficult to quantify. These factors are related to the configuration and cooling of the equipment, the economy of scale, the geographical relocation of these operation and other innovative ways to access cheap electricity / cooling (aspects which are inevitably driven by scale and smaller profit margins).
This more apt measure of mining efficiency would have to be calculated inversely than the PHD ratio, and in terms of appropriate units e.g. USD/MegaJoul. For the purpose of this article, the PHD ratio should suffice in giving an overall picture of the hard physics and financial limitation at play in the Bitcoin market.
Tethered Between a Rock Bottom and a Hashingrate Pace
A Market Manipulation Rationale
The main and inescapable selling pressure of Bitcoin is caused by mining operations in order to finance their running costs, as well as investing to upgrade and maintain a competitive edge — an extremely delicate balancing act. Thus, it is imperative for them to have a long-term strategy and judge the market cycles to the best of their abilities. The euphoria of the 2017 bull market might have led to overoptimistic miscalculations regarding the amount of cash which needed to be raised at the top, as well as the ratio of the gains to be allocated towards growth (increasing their hashrate), to that of the savings for covering future running costs.
Considering the current area of profit curve, it would be reasonable to speculate that miners with the aid of exchanges have been propping up the price, in order to meet their need to sell without further adding to the selling pressure and driving the prices even lower. A concerted effort as such benefits all parties involved: the competing mining operation, exchanges, and much welcomed by bullish traders of all sizes.
It is obvious that a market manipulation of this nature cannot be achieved by dumping BTC on the market willy-nilly. It has to be conducted in a calculated manner and the selling pressure of the miner’s BTC has to be absorbed by another asset, preferably something, obscure in its workings, unregulated and easily controlled. This, in turn, can then be used as a counterweight and “simulate” buying pressure: meet Tether.
First Bitcoin Rally/ ”dead cat bounce” February - March ’18 ->
No significant change Tether MC/ supply”:

Second Bitcoin Rally/ “dead cat bounce” April — May ‘18
Change in Tether MC: from 2.3 to 2.2–2.1 Million
~100–200 Million Tether “rescinded”:

The Third & Fourth (ongoing) Rally
& Peak Tether: $2.86 Billion
(All Time Peak, “Market Cap”/ “Circulating Supply”)
Third rally/ “dead cat bounce” June — July ‘18
Change in Tether MC: from 2.7 to 2.5–2.4 million
~200–300 Million Tether “rescinded” (correct correlation)Fourth (ongoing) rally August — September ‘18
[“dead cat bounce” and not longer ongoing by the time the article was published]
Change in Tether MC: from 2.4 to 2.85
~ 450 Million Tether “printed” !!!

What can the “PHD ratio” tell us about the current state of affairs within the Bitcoin Market?

In the two previous market cycles Bitcoin has bounced back considerably earlier than the PHD ratio: halfway into the profitability cycle in 2013, and at one third in 2014–15. At present, however, we find ourselves much closer to the asymptotic tapering of the profitability/ efficiency curve than in the last cycles. This could radically change the dynamics of this relationship and that of price action. However, the most likely scenario that can be intuitively drawn from this data, is the least exciting one: the market has already bottomed (or shortly make a slightly lower low) and then continue to trade sideways until March 2019.
I would be grateful if anyone with a mathematical or financial background would give me some feedback regarding the above analysis and make instructive comments, pointing to anything that I might have left out and ought to be taken into account for the purpose of this metric/ analysis.
Disclaimer: the content is only to be taken as my personal OBSERVATION and QUESTIONS for the purpose to be further considered, answered or discarded, hence this article is far from exhaustive and IS NOT and CANNOT serve as basis for any financial / investment / trading advice.

