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The Golden Triangle: Understanding the Long-Term Profitability and Competitive Dynamics of Mining

Phillip Ng, VP Corporate Development

Cryptocurrency mining is the compute mechanism that allows for digital currency networks to exist without a trusted third party. This process is adversarial and rewards network nodes (“miners”) for solving a computational puzzle that verifies and records transactions. The economic incentives of this process are the key innovation that makes cryptocurrency distinct from other methods of transacting digitally.

Cryptocurrency mining has become big business.  In Bitcoin alone, miners will have earned over 5 billion dollars in newly minted cryptocurrency. Bitmain, the largest producer of crypto-mining hardware generated 1.1 billion dollars of net income in 1Q18 alone. Across the globe, miners have sought to invest significant capital.

The Golden Triangle drives returns to equilibrium as the result of economic forces. 

Miners have raised significant capital to purchase computing hardware and deploy the infrastructure. Over the last year, the fortunes of miners have swung wildly due to overall volatility in cryptocurrency prices. In this environment, miners are undertaking big risks in exchange for the opportunity for considerable profits. Or are they?

This blog will explore the frameworks for mining and demonstrate that investors in cryptocurrency mining, like investors in any industry, will be driven by the economic forces of supply and demand. With this, they can and should anticipate the industry to have a long-term return profile based on the risk profile of the industry. While we have used Bitcoin in our analysis, these principals should generally apply to most proof-of-work mining markets.

The Golden Triangle

The following inputs determine miner's returns and margins:

  • Cryptocurrency price levels – The market value of the cryptocurrency rewarded to a miner.
  • Difficulty – The probability that a network node will solve the “blockchain puzzle” or “hash puzzle” during the process of adding a new block to the blockchain. Difficulty is algorithmically determined and increases as overall network computing power increases, to steady block rewards and adherence to a planned total minting period.
  • Miner cost inputs – The costs a miner must pay to generate compute. Electricity is the main operational cost, varying from miner to miner. Initial CapEx cost is hardware procurement, which can be quite significant.

By understanding the interplay between these inputs, one can develop a framework for analyzing miners and comparing them against one another and understand the dynamics of the cryptocurrency mining industry.

Now picture a triangle and each of these variables is a point on the triangle. At Soluna, we refer to this as the "Golden Triangle." The Golden Triangle drives returns to equilibrium as the result of economic forces.


Economic Analysis: How the Golden Triangle is Maintained

Understanding the triangle inputs allows us to have a clear picture of the economics of mining. Consider the following:  

1:  Miners Have Limited Short-Term Recourse to Shifts in Asset Prices

  • Miners are price-takers of the crypto assets they generate. One bitcoin is no different than any other bitcoin. Therefore, miners have two options with regards to the mining process: produce or don’t. Mining hardware prices are a significant upfront capital cost to mining and represent a sunk cost once purchased.
  • Miners will continue to mine so long as the marginal profit from mining exceeds the marginal costs of operation. However, miner’s will only reinvest capital in equipment if the expected return on mining exceeds its risk-adjusted return. Therefore, miners will eventually exit the market in adverse price environments.
  • Conversely, miners will expand their compute footprint in periods where expected returns well exceed cost of capital.


2:  Network Difficulty Dynamically Responds to Compute Levels

  • The Bitcoin network’s difficulty level resets every 2,015 blocks generated so that the rate of block generation is maintained on average at 10 minutes per block. This mechanism was created to allow the network to compensate for changes in computing power and network participation and ensure a steady minting of coins over 130-years.
  • As such, increased total network computing power results in higher difficulty and lowers expected return per unit of compute input. Conversely, lower network computing power raises expected return per unit of compute.
  • Here we see the beginning of cryptocurrency’s two-way causality: higher price levels mean more participants, which raises difficulty, which lowers average profits back to an equilibrium level. In the long run, lower levels of profits will cause miners to exit, which results in lowered difficulty, raising average miner profit levels.  
  • The result: The total compute network increases and decreases as a result of miner’s expected return. Therefore, the level of mining difficulty tends to revert to maintain a relatively constant level of profitability level for miners.


3: Hardware Producers Have Low Marginal Production Cost

  • The cost structure of any producer of silicon chips is well documented. Chip production is an intensely competitive business with large upfront research and development requirements and low marginal production costs once a chip design is complete. With high fixed costs and low variable operating costs, production volumes are the key to profitability for a chip manufacturer.
  • This cost structure has important implications for how manufacturers price their chips. Miner’s capex-invest decision tree is based on the expected return on capital as outlined above. Therefore, we can expect chip vendors to price their chips at a level which will achieve the minimum return profile required by miners to make their investment decision, while also maximizing chip production volumes. As marginal cost on a chip is almost immaterial in relation to the initial research and development expenditure, there is virtually no lower bound to the chip production price.
  • Therefore, in periods adverse to miners, we can expect chip producers to lower the price of chips to almost any level to induce miners to reinvest. Conversely, periods of high demands will see high chip prices.

Empirical Evidence: Profitability Levels on Mining Have Maintained a Constant Level

To investigate the effectiveness of Bitcoin’s built-in network difficulty adjustment, we studied miner profitability for the time from July 11, 2016 to October 1, 2018. We believe this two-year period is a good sample set as the mining block reward was constant in this period and the chip technology was relatively constant throughout the period and had a high level of market penetration.

Market profitability available to a miner at a point in time can be expressed as a ratio of the average value of the output generated, divided by the average difficulty level of a network.

We studied difficulty using a one-year and six-month averages.  Using the formula above, our results can be summarized as follows:

As shown from the diagram above, miner’s profit ratio has maintained a narrow range over the last two years with a standard deviation of 38% and 32% of the average level for the one-year and six-month average BTC price, respectively. This band is relatively tight considering the extraordinary volatility of BTC prices, with BTC levels ranging from $438-$19,290 and a standard deviation of $4,036.

Thus, we find support for dynamic change network: as crypto prices surged over the past few years, new miners joined, and difficulty rose to meet the new level of interest.


Empirical Evidence: Expected Returns on Mining Hardware has Maintained a Constant Level

We studied the payback period on chips at different price and difficulty levels across the last two years to see if there is support for the hypothesis that hardware producers are largely price takers. For a quarter’s BTC price, difficulty, and chip level, we researched how long it would take for a chip’s revenues to recover the initial cost of the miner.

Our results are as follows:

Expected payback on chips has maintained an average payback period of 5.3 months, with a standard deviation of approximately 15 days. The best predictor of chip prices is the profitably level of miners. Here again we find support for a level of consistency in chip prices. In periods of high profitability, chip prices rise as producers capture their share of excess profits, offsetting the payback period. In periods of low profitability, prices fall to compensate the shift in aggregate demand.



Parsing of the supply and demand dynamics for each input of the Golden Triangle shows that the changes in these variables are largely endogenous and that there is two-way causality between them. This blog has sought to provide both a theoretical framework and empirical evidence that there are various market-driven valves to maintain profitability levels at some equilibrium, even despite the tremendous volatility in BTC price.


Implications for Investors

If the Golden Triangle hypothesis holds, it provides a framework to compare miners against one another. Investors should consider the following:    

  1. Value operational excellence above all else – miners are unable to affect price and difficulty levels in a meaningful way. Also, once chips have been purchased, that capital cost is also largely sunk. Therefore, the main lever mining firms can pull is through operational excellence, via efficiencies from scale, operational management, and low-cost electricity.  Electricity cost is and will remain the most important avenue to operational improvement for miners.
  2. Survive the winter – As noted, the capital-intensive nature of the business represents a sunk cost and a barrier to exit for many miners. It is possible for the mining industry to move into periods of adverse price or difficulty where many miners can cover their marginal cost, but not their return-on-capital targets. We can expect these miners to exit at the end of their equipment’s useful life and relieve the pressure on the rest of the industry. In the long-term, a miner can expect a recovery in their fortunes. However, the short-term can be challenging.The implication is that downside-proof business models should be valued over more vulnerable ones. Arrangements, such as take-or-pay electricity contracts can be a heavy burden for miners when their marginal cost to produce becomes negative. Resilient business models, such as companies with alternate paths to revenues should be more highly valued.
  3. Buy the downturn – As a result of the capital-intensive nature of mining, the ability to procure chips at a competitive price can be the difference between poor and significant returns for investors. In periods of exuberance for cryptocurrency prices, enthusiastic new entrants will give chip producers great bargaining power. Conversely, low interest in the space can be a boon, as it will give buyers purchasing leverage.

You can learn more about how Soluna is working to power the blockchain economy for years to come by listening to our podcast series on YouTube and iTunes.



[1] See Understanding the Blockchain for further discussion.
[4] Approximately every two weeks
[5] having an internal cause or origin
[6] J.P. Morgan estimates energy cost makes up 44% of the total cost of Bitcoin mining.

ABOUT THE AUTHOR Phillip Ng, VP Corporate Development

Phillip is an Associate at Brookstone Partners and manages business development opportunities related to Blockchain at Soluna. Before joining Brookstone, Phillip worked as a Senior Consultant at Ernst & Young’s Transaction Advisory group as well as in the Financial Advisory Group of Deloitte Chile. He holds a BBA in Economics and Finance from the University of Georgia. He holds a Chartered Financial Analyst (CFA) designation.

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