Points of Focus

• Peer-reviewed study models Bitcoin price using fixed supply and rising demand dynamics.
• $1M target by 2027 depends on sustained withdrawals from liquid supply.
• Outcomes vary sharply based on institutional behavior and supply constraints.

A peer-reviewed study published in the Journal of Risk and Financial Management presents a supply-and-demand framework indicating Bitcoin could reach $1 million by early 2027 under specific market conditions. The model doesn’t rely on historical price trends. 

Instead, it focuses on a structural imbalance between Bitcoin’s fixed supply and accelerating demand, particularly from institutions and long-term holders.

"Bitcoin could reach $1 million by 2027 and $5 million by 2031."

According to a peer-reviewed pricing model published in the Journal of Risk and Financial Management. pic.twitter.com/qBxxjJfGuY

— Bitcoin Archive (@BitcoinArchive) April 4, 2026

Bitcoin’s fixed supply limits how price can respond to demand

The study centers on a simple but critical constraint. Bitcoin’s total supply is capped at 21 million coins and can’t expand in response to demand.

Unlike commodities where higher prices increase production, Bitcoin’s issuance is predetermined. As of the April 2024 halving, over 93% of total supply had already been mined, leaving a shrinking pool of new coins entering circulation.

At the same time, a large portion of existing Bitcoin is effectively inactive. The paper estimates that more than 45% of supply hasn’t moved for at least three years, limiting what is actually available for trading.

This means price is set by a relatively small pool of liquid supply, making it more sensitive to new demand.

Model links $1M scenario to daily supply withdrawals

The headline projection depends on one key variable: how quickly Bitcoin is removed from liquid circulation.

According to the model:

• 1,000 BTC withdrawn daily → $1M by early 2027
• Higher withdrawal rates → up to $2M in 2027 and $5M by 2031
• Long-term simulations show a 75% probability of $4.8M+ by 2036

Can Bitcoin Hit $1 Million by 2027?

A peer-reviewed study in the Journal of Risk and Financial Management says YES, under the right conditions.

The Model is Built on Pure Economics: Bitcoin's fixed supply vs. Surging institutional demand.

Key findings:
→ $1M by early 2027 (if… pic.twitter.com/bqfPIzoxT1

— Crypto Patel (@CryptoPatel) April 4, 2026

The model’s conclusions depend heavily on assumptions that may not hold in real market conditions. Sustained withdrawals of 1,000 BTC per day require consistent large-scale accumulation by institutions or governments, which can vary with price cycles and broader macro conditions.

There is also uncertainty around Bitcoin’s true liquid supply. Estimates of lost coins and long-term holdings are not precise, and some dormant supply could re-enter the market at higher price levels, easing the supply pressure assumed in the model.

Institutional demand is the primary demand driver

The study places strong emphasis on institutional allocation. It highlights how even small portfolio allocations from large funds can absorb a significant portion of remaining liquid supply.

Recent market activity supports this trend. Spot Bitcoin ETFs in the United States have recorded steady inflows since their approval in early 2024, contributing to sustained demand pressure.

https://twitter.com/DaInvestopedia/status/2029452096458903672

The model also accounts for credit-driven demand. Firms such as Strategy have used debt issuance to acquire Bitcoin, expanding demand without requiring capital rotation from other assets.

Outcomes depend on assumptions

The projections are highly sensitive to model assumptions. If daily withdrawals slow or demand growth weakens, the model shows significantly lower price trajectories.

There are also structural uncertainties:

• Estimates of lost or inactive coins remain imprecise
• Long-term holders may sell into higher prices, increasing supply
• Demand elasticity may change as Bitcoin matures as an asset

Alternative frameworks, including power law and statistical models, have historically struggled with timing accuracy, raising further questions about forecast reliability.