Bitcoin (BTC) has dropped nearly 7% from its local peak of $82,800, as several groups of wallet holders switched from accumulation to distribution. Data suggests that this distribution, combined with increasing realized losses, points to a potential shift in momentum.

Key takeaways:

• Whale absorption of newly mined BTC supply drops to all-time lows below -150%.
• Bitcoin holders shift from accumulation to distribution after BTC price drop
• Bitcoin realized losses surged above $600 million in a single day as BTC price fell to $76,000.

Bitcoin whales absorbing at all-time lows

The yearly absorption rate measures the amount of new BTC issued that has been absorbed by the market over the past year. Currently, the absorption rate by exchanges is improving while whales are losing coins at a historic pace.

Notably, Bitcoin’s yearly absorption rate by exchanges has improved to -75 % from below -100% in April as inflows continue.

Bitcoin yearly absorption rates. Source: Glassnode

The chart above shows that a similar jump in the exchange absorption rate in January preceded a 38% BTC price decline to $60,000 from $98,000. 

While large holders (100–1,000+ BTC) are scooping up more than 150% the new issuance, the rate has dropped sharply since mid-April and is significantly below the record levels seen in November 2025.

Meanwhile, the rate of accumulation among whales (entities holding more than 1,000 BTC) has dropped to -151%, its lowest in Bitcoin’s history.

Bitcoin yearly absorption rates by whales and sharks. Source: Glassnode

This marks a shift in institutional sentiment, particularly with heavy outflows from spot Bitcoin’s exchange-traded funds, reflecting a reduction in long-term conviction among large holders.

All Bitcoin holder cohorts are “taking profits”

Bitcoin investors went risk-off, distributing their BTC as the price dropped to $76,000.

Glassnode’s Accumulation Trend Score (ATS) is near zero (light yellow), indicating that whales are selling BTC or not accumulating. 

Related: Bitcoin retakes $71K as US sends Iran 15-point ceasefire plan

The drop in the trend score indicates a transition from accumulation to distribution across almost all cohorts. This shift mirrors a similar pattern observed in mid-January 2025, which aligned with Bitcoin’s drop to $60,000 in February. 

Bitcoin accumulation trend score. Source: Glassnode

Additional data from Glassnode reveals a shift toward distribution or inactivity across all investor cohorts, as seen in the chart below.

Bitcoin accumulation trend score by cohort. Source: X/Glassnode

This is in contrast to Q4 2024, where broad cohort accumulation preceded a sustained rally that saw BTC/USD trade above $100,000 for the first time in history, fueled by the 2024 US Presidential elections.

CryptoQuant analyst Woominkyu highlighted “continued selling pressure” from whales who sent more than 8,000 BTC to exchanges on Monday. 

“As Bitcoin rallied to a peak of $82,196, whales began sending coins back to exchanges,” the analyst said in a QuickTake note on Thursday, adding:

“This is a classic sign of smart money selling into strength — taking profits while retail FOMO was building.”

Bitcoin whale activity. Source: CryptoQuant

Bitcoin’s realized losses jump to $600 million

Bitcoin’s latest correction triggered a sharp spike in realized losses. The losses by long-term holders (LTHs) reached $513.6 million on Tuesday, while losses by short-term holders (STHs) reached $101.8 million.

The aggregate realized losses across all holders reached $616 million after Bitcoin dropped to $76,000 on Monday. 

This marked the highest single-day loss realization since March and an over 1,500% jump in less than two days, compared with $41.5 million on Sunday.

Bitcoin realized losses by LTHs and STHs. Source: Glassnode

LTHs account for the bulk of the losses, while STH losses stay comparatively contained, indicating that the stress is largely on older buyers.

As Cointelegraph reported, Bitcoin investors who have held their coins for over six months could sell near their entry price after extended drawdowns, creating strong overhead pressure that may stall Bitcoin’s recovery.

A key indicator of institutional crypto market participation, the Coinbase premium has fallen deeper into negative territory, indicating increased selling pressure from institutions.

The Coinbase premium has been mostly negative since late April, but it has fallen much faster over the past seven days and recorded its lowest level this month at -0.0983% on May 21.

“Institutional selling pressure has intensified recently,” CryptoQuant analyst Darkfost said on Thursday. 

“This suggests that the population of institutional and professional investors trading on Coinbase Advanced is selling more aggressively than investors trading on Binance.”

Institutional investors are also shying away from store-of-value assets such as gold, which is down 5.8% over the past month, favoring stocks with the S&P500 and Dow Jones indexes trending up since the beginning of April. 

Analyst Axel Adler said the results suggest “zero confirmation from US spot demand.”

The Coinbase premium is a measure of the difference between Bitcoin prices on Coinbase, which is used more by US institutions, and Binance, favored more by retail investors. 

Coinbase premium falls to its lowest level this month. Source: Coinglass

Institutions are repositioning  

“The uncertainty surrounding the current macro environment appears to be pushing institutions toward hedging strategies while waiting for greater clarity,” Darkfost said. 

LVRG research director Nick Ruck told Cointelegraph the decline of the Coinbase premium could also reflect the “emergence of net selling pressure from larger holders,” and suggest institutions are taking profits or repositioning, which  “could weigh on near-term price momentum across major crypto assets.”

Bitcoin ETF outflows accelerate, derivatives decline

Another signal of institutional selling pressure is US spot Bitcoin exchange-traded funds, which have seen four trading days of outflows totaling $1.3 billion since May 14, according to CoinGlass.

Related: Bitcoin longs soar despite weak US macroeconomic data: Is $82K BTC next?

Derivatives demand also appears to be weakening, with open interest, or the value of open Bitcoin futures or perpetual contracts, dropping by around $1.5 billion this week, “clearing much of the leverage built up during Bitcoin’s move toward $82,000,” said Bitfinex.

“With short-side fuel exhausted and long positioning reset lower, the next major move likely depends on spot demand,” it added.

Bitcoin has declined 4.5% over the past week, hitting a monthly low just above $76,000 on Tuesday. It was flat on the day at $77,621 at the time of writing, down 38% from its October peak.

Magazine: Crypto scammers face death, Aussie CGT makes Asian hubs attractive: Asia Express

Bitcoin BTC$77,415.47 traded near $77,733 by midday Hong Kong time, according to CoinDesk data, little changed over the past 24 hours, after sliding as low as $76,685 and failing to hold above $78,000 during U.S. trading hours.

Derivatives positioning suggested the recent selloff may have been more of a leverage flush than the start of a broader market breakdown. Open interest, a measure of outstanding leveraged futures positions, held relatively steady while funding rates stayed low or negative, a sign that traders were not aggressively piling into bullish bets before the drop.

“There was no massive accumulation of leveraged longs prior to this, meaning most of those liquidated in this drop were leveraged funds attempting short-term bottom-fishing. Second, this signals that we are not in the middle of a structural trend reversal downward. The temporary bottom of $75,000–$77,000 remains well-defined,” Tim Sun, senior researcher at HashKey Group, told CoinDesk

The bigger problem, he said, is macro: investors are de-risking as long-term yields rise, oil and inflation risks remain in focus, and there is “currently no compelling reason for new capital to enter the market.”

CoinGlass data showed $200 million in crypto liquidations over the past 24 hours, split almost evenly between long and short positions, suggesting the move was less a one-sided capitulation than a volatile market whipping both directions.

Sun pointed to the U.S. 30-year Treasury yield, which recently pushed above 5%, as the more important pressure point. Higher long-term yields tend to weigh on speculative assets by raising the opportunity cost of holding non-yielding assets like bitcoin while tightening broader financial conditions.

The next catalyst may come from geopolitics.

Sun said a meaningful de-escalation in U.S.-Iran tensions could cool oil prices and inflation expectations, easing pressure on yields and giving bitcoin room to rebound.

But if yields remain elevated and geopolitical risks persist, bitcoin may stay stuck in what he described as a defensive, range-bound market, with the $75,000 to $77,000 zone serving as the key near-term support level.

The reported attempt to kidnap the wife of The Sandbox co-founder Sébastien Borget has shifted attention to the physical side of crypto security.

The attack took place on May 20 at Borget’s home in Seine-et-Marne, France, according to Le Journal du Dimanche. The report said one suspect arrived dressed as a delivery worker before five masked accomplices entered the courtyard and tried to force Borget’s wife into a car.

Neighbors heard her cries and intervened. Four suspects fled in a vehicle, while two others escaped on foot and later ordered an Uber. Police from the Meaux Anti-Crime Brigade stopped the ride-hail car soon after. Officers allegedly found a fake handgun, cable ties, and balaclavas.

AI day trading bots are reshaping stock trading in 2026 with faster signals, automation, and real-time analysis.

Stock day trading in 2026 is becoming more data-driven, faster, and more difficult to manage manually. Intraday price movements can be influenced by earnings updates, inflation reports, Federal Reserve expectations, AI-sector momentum, ETF flows, analyst ratings, and sudden changes in market liquidity. For traders watching multiple tickers, the challenge is not only finding opportunities, but also reacting with discipline when markets move quickly.

This is one reason AI-assisted trading tools are attracting more attention. Some platforms help traders scan stocks in real time. Others focus on technical alerts, strategy testing, broker execution, or custom algorithm development. These tools are often described as AI day trading bots, but their functions can vary widely.

A useful day trading bot does not simply promise speed. It should help traders build a clearer workflow: monitoring stocks, filtering signals, testing rules, managing alerts, and supporting execution decisions. At the same time, traders should remember that AI tools do not remove market risk. Intraday trading can lead to losses, especially when strategies are poorly tested or used during volatile conditions.

This guide looks at eight AI day trading bot platforms for stocks in 2026, including BulkQuant, Trade Ideas, TrendSpider, StockHero, Tickeron, SignalStack, Alpaca, and QuantConnect. The goal is not to declare one platform as suitable for everyone, but to compare how each tool may fit different trading styles.

Quick comparison: AI day trading bot platforms for stocks in 2026

1. BulkQuant — AI-assisted trading workflow and strategy execution support

BulkQuant is included in this list for traders who want to explore AI-assisted market monitoring and simplified trading workflow support. Instead of focusing only on stock alerts or chart signals, BulkQuant presents itself as a platform that helps users access AI-driven strategy tools across different markets, including stocks, crypto, and forex.

For stock day traders, the appeal of a platform like BulkQuant is its attempt to reduce some of the repetitive work involved in monitoring market conditions. Intraday trading often requires traders to follow price movement, react to changing volatility, control position exposure, and avoid emotional decision-making. A system that organizes these steps into a more structured workflow may be useful for users who do not want to build everything manually.

BulkQuant may be especially relevant for users who are new to AI-assisted trading tools and want a simpler entry point. Rather than requiring users to code strategies or configure complex technical indicators from the beginning, the platform focuses on accessibility, market monitoring, and strategy execution support.

That said, traders should still review the platform carefully before using real capital. Important details include risk controls, account terms, supported markets, cost structure, withdrawal rules, and how the platform handles strategy execution. Trial access or promotional credits can help users explore the interface, but they should not be interpreted as proof of future performance.

Where BulkQuant may fit

BulkQuant may suit traders who want:

• A more guided AI-assisted trading workflow
• Exposure to stock trading automation tools
• Market monitoring support
• Strategy execution features
• A beginner-friendly interface
• Access to multiple asset classes from one platform

BulkQuant is not necessarily the right choice for traders who want full control over every line of strategy logic. Developers or highly technical traders may prefer platforms such as Alpaca or QuantConnect. But for users who want a more accessible way to explore trading automation, BulkQuant is one of the platforms worth reviewing.

New users can register and receive rewards

2. Trade Ideas — real-time AI stock scanning for active traders

Trade Ideas is widely known among active stock traders for real-time market scanning and AI-assisted trade discovery. It is not designed as a simple one-click trading tool. Instead, it helps traders identify stocks that may be moving, forming setups, or matching certain intraday conditions.

For day traders, scanning speed is important. During the first hour of the trading session, hundreds of stocks may show unusual volume, price gaps, momentum changes, or breakout attempts. Manually watching every ticker is unrealistic. Trade Ideas helps users filter the market more efficiently and focus on stocks that meet specific conditions.

Its AI assistant, Holly, is often discussed as one of the platform’s better-known features. The tool can generate trade ideas and signal-based suggestions, but users still need to evaluate whether those ideas match their own strategy, risk tolerance, and trading plan.

Where Trade Ideas may fit

Trade Ideas may be useful for traders who want:

• Real-time stock scanning
• Intraday trade alerts
• AI-generated stock ideas
• Entry and exit signal references
• A research-heavy workflow for active trading

Compared with BulkQuant, Trade Ideas generally requires more active decision-making from the trader. It may be better suited to users who already understand day trading setups and want a faster way to discover opportunities.

The platform may feel overwhelming for beginners because it is built around active market participation. Traders need to know how to interpret alerts, manage risk, and decide whether a signal is worth acting on.

3. TrendSpider — Technical analysis automation and strategy alerts

TrendSpider focuses on technical analysis automation. It is useful for traders who rely on chart patterns, trendlines, indicators, price levels, and multi-timeframe conditions.

Instead of manually drawing levels or constantly checking whether a stock has reached a technical setup, traders can use TrendSpider to automate parts of the chart-monitoring process. This can be especially helpful in day trading, where timing matters, and conditions can change quickly.

TrendSpider also supports alert-based workflows. Traders can create alerts based on technical criteria, and those alerts may be connected to other execution tools through webhooks. This makes the platform useful for traders who already have a defined strategy and want to reduce manual chart watching.

Where TrendSpider may fit

TrendSpider may suit traders who want:

• Automated technical analysis
• Chart-based alerts
• Multi-factor trade conditions
• Strategy testing features
• Webhook-supported workflows
• A structured approach to technical setups

TrendSpider is not necessarily a beginner-first platform. It is most useful when the trader already understands technical analysis and knows which conditions they want to monitor. Automating a weak or unclear strategy will not improve the strategy itself.

For traders who are comfortable with charts and want more automation around technical signals, TrendSpider can be a practical part of an intraday trading workflow.

4. StockHero — No-code bot building for stock traders

StockHero is designed for traders who want to create stock trading bots without writing code. This makes it different from developer-first platforms such as Alpaca or QuantConnect.

For users who have a basic trading idea but do not want to build a system from scratch, StockHero provides a more visual way to create and test bot logic. Traders can set up strategies, connect supported brokers, and test ideas through paper trading before considering live use.

Paper trading is particularly important for day trading. A strategy that looks promising in theory may behave differently in live conditions because of spreads, slippage, delayed reactions, or sudden price reversals. Testing a bot in a simulated environment can help users understand how the rules behave before exposing real capital.

Where StockHero may fit

StockHero may be useful for traders who want:

• No-code bot creation
• Paper trading and strategy testing
• Broker-connected trading workflows
• A more visual way to build automated stock strategies
• A middle ground between manual trading and coding

StockHero still requires user judgment. Traders need to define strategy rules, review bot behavior, and understand when a setup may not be suitable for live trading. The platform can reduce technical barriers, but it does not remove the need for risk management.

5. Tickeron — AI stock signals and pattern recognition

Tickeron focuses on AI-generated stock signals, pattern recognition, trading robots, forecasts, and market idea discovery. It may appeal to traders who want AI-assisted research rather than a complete trading workflow.

For day traders, signal discovery can be useful because it helps narrow down the market. Instead of manually searching through many stocks, traders can review AI-generated signals and pattern-based ideas. This may help users find potential setups faster, especially during active trading sessions.

However, signal-based platforms should be used carefully. A signal is not the same as a trading plan. Traders still need to consider entry timing, position size, stop-loss levels, broader market conditions, and whether the trade fits their strategy.

Where Tickeron may fit

Tickeron may suit traders who want:

• AI-generated stock signals
• Pattern recognition tools
• Forecast-style market ideas
• Trading robot categories
• Decision support for stock research

Tickeron may be less suitable for users who want simplified execution support or a more guided trading workflow. It is better understood as an AI-assisted research and signal platform.

For traders who like to compare multiple signals and use them as part of a broader decision process, Tickeron may be worth reviewing.

6. SignalStack — Alert-to-order automation for existing trading systems

SignalStack is different from most other platforms in this list. It is not mainly an AI stock picker or charting platform. Instead, it helps traders connect alerts from other platforms to live broker orders.

This can be useful for traders who already have a signal source. For example, a trader may use TradingView, TrendSpider, or another alert system to identify a setup. SignalStack can help convert that alert into an order workflow, reducing the delay between signal and execution.

For day trading, this matters because timing can affect results. If a trader receives an alert but takes several minutes to place an order manually, the setup may change. An alert-to-order tool can help create a more consistent execution process.

Where SignalStack may fit

SignalStack may suit traders who want:

• Alert-to-order automation
• Broker-connected execution workflows
• No-code order routing from alerts
• Faster response to existing trading signals
• A bridge between chart alerts and trade execution

SignalStack should not be confused with a complete AI trading bot. It does not replace strategy development or signal generation. Traders still need a reliable source of trade logic, clear risk parameters, and a plan for monitoring execution.

It may be most useful for traders who already have a working alert system and want to reduce manual steps in the execution process.

7. Alpaca — API infrastructure for custom stock trading bots

Alpaca is a developer-focused trading API platform. It is not a ready-made AI day trading bot for beginners, but it can be used as infrastructure for building custom trading systems.

Developers and algorithmic traders may use Alpaca to connect strategy logic, market data, and order execution. This gives users more flexibility than many no-code tools, but it also requires more technical skill.

For AI-assisted stock trading, Alpaca can serve as the execution layer. A trader or developer may build a machine learning model, signal engine, or rule-based intraday strategy, then connect it to Alpaca for order placement.

Where Alpaca may fit

Alpaca may suit users who want:

• Trading API access
• Custom bot development
• Market data integration
• Paper trading environments
• Developer control over strategy logic
• Broker execution infrastructure

Alpaca is not ideal for traders who want a simple interface and guided setup. Users need to handle coding, testing, error management, order logic, risk controls, and monitoring.

For developers, however, Alpaca can be a flexible foundation for building AI-assisted or rule-based stock trading systems.

8. QuantConnect — Algorithmic research and strategy testing

QuantConnect is designed for algorithmic trading research, backtesting, and live strategy deployment. It is one of the more advanced platforms in this list and is generally better suited to users with coding or quantitative trading experience.

For day traders, QuantConnect can be useful because it allows users to test intraday strategies before using them in live markets. Traders can research momentum systems, mean reversion strategies, opening range breakouts, volatility filters, or other systematic approaches.

The platform gives users significant control, but that control comes with complexity. A trader needs to understand data quality, strategy assumptions, backtesting limitations, execution behavior, and live trading risks.

Where QuantConnect may fit

QuantConnect may suit users who want:

• Algorithmic strategy research
• Historical backtesting
• Custom trading models
• Live strategy deployment
• Multi-asset strategy development
• A more technical quant environment

QuantConnect is not the easiest choice for beginners. It may be more appropriate for traders who already understand coding, data analysis, and systematic strategy design.

For advanced users, however, it can be a powerful environment for testing and refining stock day trading systems.

How to choose an AI day trading bot for stocks

Choosing an AI day trading bot should depend on a trading style, technical ability, and risk tolerance.

A beginner may prefer a platform with simpler onboarding, clearer workflow support, and fewer technical barriers. In that case, BulkQuant or StockHero may be easier to review than developer-heavy platforms.

An active trader who already understands intraday setups may prefer Trade Ideas for scanning or TrendSpider for technical alerts.

A trader who already has alerts but wants faster execution may consider SignalStack.

A developer or quant trader may be more interested in Alpaca or QuantConnect because these platforms offer more control over strategy logic and execution design.

The key is to avoid choosing a platform only because it uses the word “AI.” Traders should ask practical questions:

• Does the platform provide signals, execution, or both?
• Can strategies be tested before live use?
• Are risk controls clearly explained?
• Does the platform support the trader’s broker or preferred workflow?
• Is the user expected to build the strategy manually?
• Are fees, limitations, and order behavior transparent?
• Does the platform match the trader’s experience level?

A good tool should support a trading process, not replace basic judgment.

What makes a useful AI day trading bot in 2026?

A useful AI day trading bot should help traders manage speed, structure, and risk. In fast markets, the value of automation is not just about placing trades quickly. It is about creating a repeatable workflow.

Important features include:

Real-time market monitoring

Day traders often need to track many stocks at once. AI-assisted scanning tools can help filter the market and highlight stocks that match certain conditions.

Clear signal logic

A trading tool should help users understand why a signal appears. Black-box signals may be difficult to evaluate, especially for beginners.

Testing tools

Paper trading, backtesting, or trial access can help users observe how a strategy behaves before using real funds.

Execution support

Some traders need alerts, while others need order-routing tools. The right choice depends on whether the user wants research support or execution workflow support.

Risk controls

Stop-loss rules, exposure limits, position sizing, and drawdown awareness are important for intraday trading. A platform that ignores risk management may encourage poor trading habits.

Usability

A platform may be powerful but still unsuitable for a beginner. Traders should choose tools that match their knowledge level.

Transparency

Users should understand costs, limitations, supported markets, account rules, and how the platform handles trades or alerts.

Risks of using AI day trading bots

AI day trading tools can support faster analysis and more structured workflows, but they also introduce risks.

False signals

Intraday markets are noisy. A stock may appear to break out and then reverse quickly. AI tools and technical scanners can still misread short-term price action.

Overtrading

Automation can make it easier to take too many trades. Without strict rules, this may increase transaction costs and losses.

Slippage

The price shown when a signal appears may differ from the actual execution price, especially during volatile periods.

Overfitting

A strategy may perform well in historical tests but fail in live trading because market conditions change.

Technical issues

API errors, broker delays, platform outages, or incorrect settings can affect execution.

User misunderstanding

Some traders may rely too heavily on automation without understanding order types, drawdowns, position sizing, or market conditions.

For these reasons, traders should test carefully, start small, review performance regularly, and avoid treating any AI trading bot as a guaranteed solution.

Platform-by-platform summary

FAQs

What are AI day trading bots for stocks?

AI day trading bots for stocks are software tools that may help traders scan markets, generate signals, automate alerts, test strategies, or support order execution. Some tools are beginner-friendly, while others are designed for developers or advanced traders.

Can AI day trading bots remove trading risk?

No. AI tools do not remove market risk. Stock prices can move unpredictably, and automated systems can still produce losses. Traders should use risk controls, test strategies, and avoid relying entirely on any tool.

Is BulkQuant suitable for beginners?

BulkQuant may be worth reviewing for beginners who want a more accessible AI-assisted trading workflow. It focuses on market monitoring, strategy execution support, and simplified access, but users should still review all terms, risks, and platform settings before trading.

Which platform is better for active day traders?

Active day traders may prefer Trade Ideas for real-time stock scanning or TrendSpider for technical analysis automation. The better choice depends on whether the trader relies more on market scanning or chart-based setups.

Which platform is better for developers?

Developers may prefer Alpaca or QuantConnect. Alpaca provides API infrastructure for building custom trading systems, while QuantConnect offers a more advanced environment for backtesting and algorithmic strategy research.

Are no-code trading bots useful?

No-code trading bots can be useful for traders who want to test rule-based strategies without programming. However, users still need to understand trading logic, risk controls, and market behavior.

Final thoughts

AI day trading bots are becoming part of the modern stock trading workflow, but they are not all built for the same type of user. Some platforms help traders find intraday ideas. Some automate chart alerts. Some support order execution. Others provide infrastructure for custom algorithmic systems.

BulkQuant may be considered by users who want a more accessible AI-assisted trading workflow with market monitoring and strategy execution support. Trade Ideas and TrendSpider may appeal to more active traders who prefer scanning and technical analysis. StockHero may fit users who want no-code bot creation, while Tickeron focuses more on AI-generated signals. SignalStack, Alpaca, and QuantConnect are more specialized tools for execution workflows, API-based systems, and advanced algorithmic research.

The right platform depends on the trader’s experience level, preferred workflow, technical ability, and risk tolerance. In 2026, the more practical approach is not to look for a tool that claims to do everything, but to choose one that supports a clear, disciplined, and testable trading process.

U.S. lawmakers have introduced ARMA, a new bill that seeks to create a Treasury-run Strategic Bitcoin Reserve with a 20-year holding rule.

Rep. Nick Begich introduced the American Reserve Modernization Act of 2026 alongside co-lead Rep. Jared Golden. Begich’s office said the bill would create a Strategic Bitcoin Reserve within the U.S. Treasury and a separate Digital Asset Stockpile for non-Bitcoin assets held by the federal government.

The bill builds on the Strategic Bitcoin Reserve framework created by executive order in March 2025. That order directed Treasury officials to manage government Bitcoin obtained through forfeiture and other lawful proceedings, while also creating a stockpile for other seized digital assets.

Bitcoin holdings face 20-year lock

ARMA would require Bitcoin held in the reserve to remain there for at least 20 years. Begich’s office said the bill also protects the right of Americans to own, transfer, and self-custody digital assets.

The proposal also calls for quarterly proof-of-reserve reports, third-party audits, congressional oversight, and a full accounting of federal digital asset holdings. It directs a study into budget-neutral acquisition methods that would avoid higher taxes, deficit spending, or new national debt.

Lawmakers cite need for federal policy

Golden said the U.S. already holds Bitcoin but lacks a clear policy for managing it. He said “digital currencies are not the fringe phenomenon they once were,” adding that Congress had not set federal rules for what the government should do with those assets.

Begich said ARMA would protect taxpayer interests, support financial sovereignty, and extend private property rights into the digital space. Other supporters framed the bill as a way to stop the government from selling strategic digital assets without a long-term plan.

Bill follows White House reserve push

The bill arrives after renewed White House attention on the reserve. Recent crypto.news coverage noted that Patrick Witt, from the President’s Council of Advisors for Digital Assets, said officials were working through the legal structure needed to manage government-held Bitcoin.

Fox Business reported that Begich wants the U.S. to hold about 1 million Bitcoin, equal to roughly 5% of Bitcoin’s fixed supply. The proposal builds on earlier BITCOIN Act language for up to 200,000 BTC a year over five years.

For now, ARMA remains a bill, not law. Its next steps depend on committee action, House support, and Senate alignment with broader crypto legislation. The proposal places Bitcoin reserve policy back in Washington’s crypto debate as lawmakers weigh custody, debt, and property-rights rules.