Why Can't Bitcoin Be Explained by a Single Economic Cycle?

Bitcoin prices are often explained by a single “main cause”: sometimes it’s due to the four-year halving cycle, other times it’s macro liquidity, and occasionally it’s driven by speculative demand. However, this one-dimensional view overlooks the reality that BTC operates within a complex economic environment where multiple forces act simultaneously and interact with each other.
Bitcoin does not exist in a vacuum. It is both a digital asset with a fixed supply mechanism and a risk asset influenced by global liquidity cycles. Therefore, trying to encapsulate price volatility into a simple story often leads to a misunderstanding of the market’s true dynamics.
When the Halving Cycle and Macroeconomic Cycle Intersect
Analyst Giovanni emphasized that the halving cycle—primarily driven by FOMO effects and social feedback loops—still plays a significant role in the structure of the Bitcoin market. The scheduled reduction of block rewards is a mechanical change that directly impacts miners’ economics.
When rewards decrease, mining costs change, selling pressure from miners can adjust, and this ripple effect influences the entire BTC ecosystem. Halving is not an illusion; it is a real variable within Bitcoin’s supply model.
However, this does not mean halving explains everything.
Alongside Bitcoin’s intrinsic cycle is the macroeconomic cycle, reflected in indicators like the PMI (Purchasing Managers’ Index). Interestingly, PMI has also shown a roughly four-year cyclical pattern. This raises an important question: are we witnessing an interaction between two different cycles—a endogenous cycle (halving) and an exogenous cycle (macro)?
Shifting from the argument “the four-year cycle is just an illusion” to “the four-year cycle explains everything” is merely replacing one oversimplification with another. A more accurate approach is to quantify the interaction between these cycles.
In mathematics and econometrics, tools such as cycle coupling, phase alignment, and interaction effects have been developed. Applying these methods, it’s likely we won’t find a simple story but rather a more complex structure where endogenous and exogenous cycles continuously intertwine.
15-Minute Probability Model: Is the Market Being Manipulated by Bots?
From another perspective, analyst known as The Smart Ape developed a probabilistic model to estimate the likelihood of Bitcoin price increases or decreases in 15-minute markets on Polymarket.
This model is extremely simple: it uses only three variables:
Target price
Current BTC price
Remaining time before the market round ends
Remarkably, the model’s results nearly match the actual probabilities priced by the market, with a deviation of only about 1–5%.
In prediction markets like Polymarket, probabilities are directly derived from participant transactions. When the market’s implied probabilities closely align with such a simple mathematical model, it suggests that trading behavior is heavily influenced by algorithms and bots.
If the market were primarily driven by human emotions, maintaining such a high level of synchronization with a simple theoretical model would be unlikely. This reflects a reality: at short timeframes—especially 15 minutes—the market structure is increasingly mechanized.
Bitcoin Is a Multi-Layered System, Not a Single Narrative
From both perspectives—the long-term cycle and the short-term model—a common point emerges: Bitcoin is a multi-layered system.
At the macro-structural level: halving impacts supply and miner economics.
At the macroeconomic level: liquidity, interest rates, and global economic cycles influence risk flows.
At the micro level: algorithms and bots shape short-term volatility.
Bitcoin’s price results from the overlay of these layers, not a single variable.
Trying to find a “dominant story” makes the market easier to communicate but impoverishes the ability to analyze its true nature. Meanwhile, a quantitative approach—though more complex—can help us see the interaction structure among these forces.
Bitcoin is not simple. And perhaps that’s why it remains one of the most elusive assets in the digital finance era.