The cyclical nature of crypto ♻️

(Not financial or tax advice. This post is strictly educational and is not investment advice or a solicitation to buy or sell any assets or to make any financial decisions. This book is not tax advice. Talk to your accountant. Do your own research.)

Crypto moves in cycles.

Here are a few models of those cycles. Of course this is not financial advice + “All models are wrong, but some are useful”, so take it with a grain of salt.

Model 1: Supercycle

The most popular way of describing this cycle is as a supercycle:

The basic idea here is that the Bitcoin halvening (a supply issuance reduction every 4 years) reduces supply. Assuming constant or increasing demand for BTC, this could cause an supply/demand imbalance, which causes an upward swing in the price of Bitcoin. It has many times in the past. But I dont think that “constant or increasing demand for BTC” is something that we can bet will always be true.

Since Bitcoin is the biggest asset in the crypto space, the halvening/supercycle can cause the rest of the crypto market to move with it.

Model 2: Wyckoff

One of the other ways I like to look at these market cycles is through the prism of Wyckoff Theory.

Wyckoff cycles are more foundational to financial markets and are 100s of years old.

This is what they look like:


The Wyckoff market cycle reflects Wyckoff’s theory of what drives a asset’s price movement. The four phases of the market cycle are accumulation, markup, distribution, and markdown. According to Wyckoff’s rules, a price trend never repeats itself exactly and trends must be studied in context with past behavior.

If you read about the history of Robert Wyckoff you will learn that he stumbled upon a time-tested pattern that’s as old as financial markets (and the animal spirits that drive them)

Richard Demille Wyckoff (1873–1934) was an early 20th-century pioneer in the technical approach to studying the stock market. He is considered one of the five “titans” of technical analysis, along with Dow, Gann, Elliott and Merrill. At age 15, he took a job as a stock runner for a New York brokerage. Afterwards, while still in his 20s, he became the head of his own firm. He also founded and, for nearly two decades wrote, and edited The Magazine of Wall Street, which, at one point, had more than 200,000 subscribers. Wyckoff was an avid student of the markets, as well as an active tape reader and trader. He observed the market activities and campaigns of the legendary stock operators of his time, including JP Morgan and Jesse Livermore. From his observations and interviews with those big-time traders, Wyckoff codified the best practices of Livermore and others into laws, principles and techniques of trading methodology, money management and mental discipline.

From his position, Mr. Wyckoff observed numerous retail investors being repeatedly fleeced. Consequently, he dedicated himself to instructing the public about “the real rules of the game” as played by the large interests, or “smart money.” In the 1930s, he founded a school which would later become the Stock Market Institute. The school’s central offering was a course that integrated the concepts that Wyckoff had learned about how to identify large operators’ accumulation and distribution of stock with how to take positions in harmony with these big players. His time-tested insights are as valid today as they were when first articulated.


  1. Wyckoff learned “the real rules of the game” played by large interests.
  2. Wyckoff informed the body public about “the real rules of the game”
  3. That’s why he’s a legend to me :slight_smile:

Read more about Wyckoff here.

Model 3: Seasons

Here is an ETH/USD Chart that shows the last cycle, annotated as Winter => Spring => Summer => Autumn (repeat).

Although all of the charts above show the financial nature of the cycle, the cyclical nature doesnt just affect the prices of different assets. It also affects

  1. the cost of capital (high in winter, low in summer)
  2. attention from the public (low in winter, high in summer)
  3. the scarcity of talent (low in winter, high in summer)
  4. attention of the builders (focused on infrastructure in winter, adoption in summer)

Model 4: Gartner Hype Cycle

(x-posted with the Gitcoin gov forum

Gartner Hype Cycles have been around for decades. From this page:

Hype Cycles are a tool for people to get educated about the promise of an emerging technology within the context of their industry and individual appetite for risk.

Hype Cycles help you:

  • Separate hype from the real drivers of a technology’s commercial promise

  • Reduce the risk of your technology investment decisions

  • Compare your understanding of a technology’s business value with the objectivity of experienced IT analysts

Each Hype Cycle drills down into the five key phases of a technology’s life cycle.

  • Innovation Trigger: A potential technology breakthrough kicks things off. Early proof-of-concept stories and media interest trigger significant publicity. Often no usable products exist and commercial viability is unproven.
  • Peak of Inflated Expectations: Early publicity produces a number of success stories — often accompanied by scores of failures. Some companies take action; many do not.
  • Trough of Disillusionment: Interest wanes as experiments and implementations fail to deliver. Producers of the technology shake out or fail. Investments continue only if the surviving providers improve their products to the satisfaction of early adopters.
  • Slope of Enlightenment: More instances of how the technology can benefit the enterprise start to crystallize and become more widely understood. Second- and third-generation products appear from technology providers. More enterprises fund pilots; conservative companies remain cautious.
  • Plateau of Productivity: Mainstream adoption starts to take off. Criteria for assessing provider viability are more clearly defined. The technology’s broad market applicability and relevance are clearly paying off.

This is what this hype cycle looks like visually:

Hype cycles have been issued for the web3 cycles many times, including by Gartner - a firm that has pioneered the hype cycle taxonomy. Here is a recent 2021 Hype Cycle for blockchain:

Here is another Hype Cycle for emerging technologies issued in 2021:

I find these hype cycle charts not to be very useful for timing the market, but I do find them to be a useful tool for the understanding the timeless driving forces beyond the adoption of new technologies. Knowing how to identify Innovation Triggers is a important part of sensemaking. As is being able to understand the difference between a Peak of Inflated Expectations and a Slope of Enlightenment.

I hope you find them to be useful as well.

Other models

Im a big believer that sensemaking is an important part of surviving & thriving in the digital frontier. Sensemake with me so we can build a more regenerative digital frontier together, one that is regenerative through allllll the cycles; what are some models I’ve missed for making sense of the seasonality of crypto?