When Will Bitcoin Mining Reach Its Limit

Real drivers and realistic setups

Current Challenges in Bitcoin Mining

Bitcoin mining is a complex and resource-intensive process, relying on the computational power of specialized hardware to secure the network and validate transactions. As of now, the total supply of Bitcoin is capped at 21 million coins. This means that every four years, the amount of new Bitcoin mined halves, a phenomenon known as halving. The most recent halving occurred in May 2020, and it has significant implications for miners and investors alike.

The increasing difficulty of mining new Bitcoin and the decreasing reward per block make it more challenging for miners to maintain profitability. This trend raises questions about the future sustainability of Bitcoin mining and the overall supply dynamics.

What Matters

• The current pace of halvings and their impact on mining profitability
• Technological advancements in mining hardware and software
• Environmental concerns and energy consumption of Bitcoin mining
• Economic factors such as market demand for Bitcoin
• Potential changes in regulatory landscapes affecting mining operations

Example

A miner named Alex had been mining Bitcoin since 2017. Initially, Alex found it profitable due to high rewards per block. However, as more miners joined the network, competition intensified, leading to increased difficulty levels. By 2020, Alex’s profitability dropped significantly due to the first halving event. To adapt, Alex invested in more efficient hardware and explored alternative energy sources like hydroelectric power. This strategy helped Alex continue to generate returns even as conditions became more challenging.

Question

How can miners stay profitable through multiple halvings?

By continuously upgrading hardware to keep up with increasing difficulty levels, exploring cheaper or renewable energy sources, diversifying investments, and staying informed about regulatory changes, miners can maintain profitability over time.

Risk management you can actually use

• Risk per trade = account equity × risk% (e.g., 1%).
• Position size = risk per trade ÷ (entry − stop).
• Expectancy (E) = win_rate × avg_win − (1−win_rate) × avg_loss.
• Cap total portfolio risk; journal every trade.

A quick example

Account $10,000, risk 1% → $100 risk per trade. Entry $50, stop $48 → $2 risk/share → 50 shares. Target $54 (2R). If stopped, −$100; if target hits, +$200 (before costs).

How much capital do I need to start?

Use an amount you can afford to lose while learning a repeatable process.

How do I size positions?

Decide a fixed risk % per trade, then divide by the price distance to your stop.

How often should I review?

Match your timeframe: DAIly/weekly for swing; weekly/monthly for long-term.

What goes into my journal?

Thesis, entry/exit, risk (R), emotions, result, next improvement.

Sources & Signals (add before publish)

• Earnings or guidance: …
• MaCRO data or policy: …
• Sector flows: …
• Unusual volume/price action: …