Research

Treasury Companies and ETFs: How Institutional Money is Reshaping Crypto in 2025

The convergence of treasury companies, ETF expansion, and consumer application growth is creating a new phase of cryptocurrency adoption. Unlike previous cycles driven by retail speculation, this institutional wave appears sustainable and growing.
Token Metrics Team
6 min
MIN

The cryptocurrency market is experiencing a seismic shift as institutional adoption accelerates through treasury companies and exchange-traded funds. This institutional wave is fundamentally altering market dynamics and creating new investment opportunities for both retail and professional investors.

The Treasury Company Explosion

Treasury companies have emerged as the dominant force driving crypto adoption in 2025. These entities, which hold cryptocurrency as primary treasury assets, are experiencing unprecedented growth and creating massive buying pressure across major digital assets.

MicroStrategy Leads the Charge

MicroStrategy continues to dominate Bitcoin treasury holdings with an impressive $70 billion worth of Bitcoin, including $23 billion in unrealized gains. The company's strategy has proven so successful that it's spawning imitators across multiple cryptocurrency ecosystems.

Recent data shows treasury companies are expanding beyond Bitcoin into Ethereum and other major cryptocurrencies, creating diversified institutional exposure to digital assets.

Ethereum Treasury Revolution

BitMine recently made headlines with a $2.2 billion Ethereum purchase, signaling institutional confidence in ETH's long-term prospects. The company has set an ambitious target of capturing 5% of Ethereum's total supply, demonstrating the scale of institutional appetite.

This move coincides with Ethereum hitting new all-time highs of $4,946, up 250% from April lows. The combination of treasury company purchases and growing DeFi activity has created a powerful upward momentum for ETH.

Beyond Bitcoin: Diversification Across Ecosystems

Solana Treasury Strategies

The Solana ecosystem is witnessing significant institutional interest:

  • Sharp Technologies raised $400 million with Paradigm and Pantera for SOL treasury operations
  • Galaxy Jump and Multicoin are raising $1 billion for a Solana-focused treasury company
  • These developments suggest Solana may soon follow Bitcoin and Ethereum's institutional adoption path

BNB Strategic Holdings

B Strategy, backed by Binance founder CZ and former Bitman CFO, launched a $1 billion US-listed vehicle specifically to purchase BNB tokens. This institutional backing provides significant credibility to Binance's native token and demonstrates the expanding scope of treasury strategies.

The Stablecoin Revolution

Parallel to treasury company growth, stablecoins are experiencing explosive expansion. Total stablecoin supply now exceeds $250 billion, with projections suggesting growth to $1 trillion by next year.

MetaMask Enters the Stablecoin Race

MetaMask's launch of MUSD, their native stablecoin developed with Bridge (acquired by Stripe), represents a significant development. Key features include:

  • Multi-chain deployment: Initially on Ethereum and Linea
  • 30 million user base: Immediate access to a massive user network
  • MasterCard integration: Direct retail spending capabilities
  • Seamless experience: On-ramp, swap, transfers, and bridging within MetaMask

Current supply stands at 41 million MUSD with 5,000 holders, but this is expected to grow rapidly to billions given MetaMask's user base.

Traditional Institution Adoption

Several major developments indicate mainstream financial adoption:

Singapore's DBS Bank launched tokenized structured notes on Ethereum mainnet, though initially limited to accredited investors.

SBI Holdings from Japan, managing $74 billion, entered a joint venture with Startale to tokenize US and Japanese stocks, enabling 24/7 trading and fractional ownership.

Multiple South Korean banks are in discussions with Tether and Circle to distribute USD stablecoins, following increasing regulatory clarity.

ETF Expansion and Regulatory Progress

The ETF landscape continues expanding beyond Bitcoin, creating new institutional access points:

Solana ETF Applications

  • VanEck and Jito filed for Solana ETF applications
  • Solana Foundation and Multicoin are leveraging SEC guidelines for liquid staking ETFs
  • The deadline for approval is October, with industry experts optimistic about approval

Ethereum Momentum

Ethereum ETFs are seeing increased inflows as institutional interest grows. The combination of ETF buying and treasury company purchases is creating sustained upward pressure on ETH prices.

AI and Privacy Tokens Gaining Institutional Interest

Venice AI: Privacy-Focused Innovation

Vanna AI represents a new category of projects attracting institutional attention. Founded by Eric Voorhees (Shapeshift founder), the project offers:

  • Privacy-first AI: Local inference without data upload to centralized servers
  • Multiple AI models: Text, image, and specialized model integration
  • Fair token distribution: 50% airdropped to community
  • Stake for Access: API credits model with $1 per day per staked token
  • Growing adoption: 6 million monthly visitors indicate mainstream appeal

The project demonstrates how utility-focused tokens can attract both institutional and retail interest through genuine product-market fit.

Hidden Opportunities in Emerging Ecosystems

Hyperliquid Ecosystem Growth

The Hyperliquid ecosystem is experiencing explosive growth, with several projects showing institutional-grade metrics:

Kinetic Protocol serves as the liquid staking solution for Hyperliquid's native HYPE token, similar to Lido for Ethereum. TVL has grown from under $400 million to over $1.7 billion, demonstrating organic adoption.

Unit Protocol acts as the native bridge for Bitcoin, Ethereum, and USDC to Hyperliquid, with nearly $1 billion TVL despite no active point system.

DeFi Infrastructure Expansion

Traditional DeFi protocols are expanding to capture multi-chain market share:

  • AAVE launched on Aptos, becoming the first major DeFi protocol on a Move-language blockchain
  • Multi-chain strategies are becoming standard for major protocols
  • Increased TVL across networks shows growing institutional DeFi adoption

Consumer Applications and Mass Adoption

Base Ecosystem Leadership

Base, Coinbase's Layer 2 solution, is emerging as a leader in consumer-focused crypto applications. The rebrand from Coinbase Wallet to Base App signals a broader strategy to become the "super app" for crypto.

Recent consumer applications include:

  • Fantasy Football platforms generating millions in revenue within days of launch
  • Gaming integrations bringing Web2 users into crypto seamlessly
  • Social and entertainment apps abstracting blockchain complexity

Investment Strategies for the New Landscape

Blue Chip Focus

Given the institutional wave, experts recommend focusing on established assets:

  • Bitcoin: Continued treasury adoption and regulatory clarity
  • Ethereum: DeFi growth and institutional ETF flows
  • Solana: Emerging treasury strategies and ETF potential
  • Hyperliquid: Revenue-generating protocol with strong tokenomics

Emerging Opportunities

Secondary opportunities include:

  • Liquid staking tokens on growing ecosystems
  • Bridge and infrastructure protocols with real revenue
  • Privacy-focused AI projects with utility beyond speculation
  • Consumer applications with demonstrated product-market fit

Risk Management in Institutional Markets

Valuation Metrics

Treasury companies often trade at premiums to their underlying holdings, similar to traditional investment vehicles. Key metrics to monitor:

  • Net Asset Value (NAV): Compare stock price to underlying crypto holdings
  • Premium levels: Historical peaks around 2.5x suggest caution
  • Revenue generation: Focus on companies with operating businesses beyond holding crypto

Market Timing

The altcoin season indicator currently sits at 58%, approaching the 60%+ zone that historically marks cycle tops. This suggests:

  • Profit-taking opportunities may emerge soon
  • Risk management becomes crucial as markets mature
  • Diversification across asset classes and strategies

The Future of Institutional Crypto

The institutional adoption wave shows no signs of slowing. Predictions suggest:

  • $10 trillion stablecoin market within 2-3 years
  • Multiple treasury companies for each major cryptocurrency
  • Regulatory clarity enabling broader institutional participation
  • Consumer applications bringing billions of users to crypto

Conclusion

The convergence of treasury companies, ETF expansion, and consumer application growth is creating a new phase of cryptocurrency adoption. Unlike previous cycles driven by retail speculation, this institutional wave appears sustainable and growing.

Investors who understand these trends and position accordingly—whether through direct cryptocurrency exposure, treasury company stocks, or emerging ecosystem tokens—are likely to benefit from this fundamental shift in crypto market structure.

The key is recognizing that we're no longer in an early-stage speculative market, but rather witnessing the birth of a mature digital asset class with institutional backing, regulatory clarity, and real-world utility. This transformation creates both opportunities and risks that require sophisticated analysis and strategic positioning.

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Token Metrics Team
Token Metrics Team

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Choosing the Right Crypto API for Your Bot: REST vs WebSockets Explained

Token Metrics Team
6
MIN

As crypto trading automation accelerates into 2025, choosing the right API interface for your bot could be the critical difference between lagging behind or capitalizing on real-time opportunities. But when it comes to REST vs WebSocket crypto APIs, which technology should you select for power, reliability, and performance? This post details the core differences, essential trade-offs, and latest best practices for crypto API comparison, empowering you to make a technical, mission-aligned decision for your next-generation trading bot.

REST and WebSocket: Core Concepts for Crypto APIs

To understand which API protocol is optimal for your crypto bot in 2025, let’s clarify what REST and WebSocket actually do—especially in a high-frequency, automation-driven ecosystem.


     

     


The fundamental contrast: REST works in a "pull" model (request/response), while WebSockets operate in a "push" paradigm (real-time streams). This distinction plays a major role in how bots interact with exchanges and handle crypto market shifts.

Performance, Latency, and Reliability for Crypto Bots

Performance and data freshness are critical for crypto APIs in 2025. High-frequency or latency-sensitive trading bots depend on receiving accurate, instant data on price movements and order book changes.

       

Yet reliability considerations persist. WebSocket connections may experience drops, require reconnection logic, and occasionally miss events during high network volatility. REST, while slower, may provide more consistency under unstable conditions.

Scalability, Security, and Use Cases in Crypto API Comparison

Your crypto bot’s requirements—frequency of updates, types of orders, and compliance frameworks—may drive the API choice. Here’s how REST and WebSocket compare across scenarios relevant in 2025:


     

     


Security-wise, REST can offer granular access controls per endpoint. WebSockets, though encrypted, have unique session management and timeout considerations—especially important for bots managing real funds.

In the ever-evolving crypto automation landscape, developers and researchers are seeing:


     

     

     


Ultimately, the “better” API depends on your bot’s profile: Speed-critical, event-driven bots gravitate to WebSockets, while research bots or those trading on daily signals may remain with REST. Many leading bot frameworks in 2025 offer seamless switching or even run hybrid workflows for best-in-class resilience.

Practical Tips for Comparing REST vs WebSocket Crypto APIs

When evaluating crypto APIs for your bot or automation project, consider these practical criteria:

    Above all, test API performance in real-market scenarios—using sandboxes or historical replays—to ensure your bot’s architecture is future-proofed for 2025 volatility and growth.

    Build Smarter Crypto Apps & AI Agents with Token Metrics

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    FAQ: REST vs WebSocket Crypto APIs for Bots in 2025

    What are the main differences between REST and WebSocket APIs?

    REST APIs use isolated request/response cycles and are suited for infrequent or simple queries. WebSocket APIs sustain continuous, two-way connections for real-time market data updates. The choice depends on whether your bot needs static or streaming data.

    Which API type is better for real-time crypto trading bots?

    WebSocket APIs are preferred for real-time trading bots due to their lower latency and ability to push instant data updates. However, implementation complexity and stability must be considered.

    Can I use both REST and WebSocket in the same bot?

    Yes. Many bots use REST for account management or trade execution and WebSocket for live data streams. This hybrid approach leverages the strengths of each protocol.

    Are there security differences between REST and WebSocket crypto APIs?

    Both protocols utilize SSL encryption and API key-based authentication, but WebSocket sessions require more careful management and regular re-authentication to prevent stale or hijacked connections.

    How do I choose the right API for my crypto bot?

    Assess your bot’s use case—speed versus reliability, frequency of queries, data intensity, and integration requirements. Testing both protocols with your trading logic is recommended for optimization.

    Disclaimer

    This content is for educational and informational purposes only. It does not constitute investment, trading, or financial advice. Past performance and API platform capabilities are not guarantees of future results. Always perform independent research and technical due diligence before building or deploying trading bots or utilizing API-based automation tools.

    Research

    Avoid These Common Pitfalls When Creating Your First Crypto Trading Bot

    Token Metrics Team
    6
    MIN

    Coding your first crypto trading bot can be an exciting journey into algorithmic trading, automation, and the world of digital assets. But for many beginners, the path is full of unexpected hurdles. Rushing into bot development without understanding key risks can lead to costly errors, technical failures, and frustration. In this article, we break down the top mistakes to avoid when building your first crypto trading bot, and offer actionable insights so you can start your automation journey on solid ground.

    Jumping in Without Market or Technical Knowledge

    Many new developers are eager to start building a crypto trading bot after seeing success stories or reading about impressive returns from algorithmic strategies. However, skipping foundational learning can result in critical errors:

    • Limited understanding of market structure: Crypto markets operate differently from traditional assets, with unique liquidity, volatility, and trading hours.
    • Lack of programming proficiency: Writing robust, bug-free code is vital. Even minor logic errors can trigger unexpected trades or losses.
    • Neglecting data analysis: Bots rely on processed signals and historical data to inform actions. Without knowing how to interpret or validate data sources, a bot may act on false assumptions.

    Before you start coding, invest time to learn how exchanges work, typical trading strategies, and the programming language you intend to use (often Python or JavaScript for most bot frameworks). Familiarize yourself with basic quantitative analysis and backtesting tools to ground your bot in solid logic.

    Overlooking Risk Management Essentials

    One of the most widespread beginner crypto bot mistakes is failing to build robust risk controls into the automated system. While automation can remove human error and emotion, it cannot protect you from strategy-flaws or market anomalies by default. Major risks include:

    • No stop-loss or position sizing: Without defined parameters, a bot could open positions too large for your portfolio or fail to exit losing trades, compounding losses.
    • Ignoring exchange downtime or slippage: Bots need to account for order execution issues, network delays, or sudden liquidity drops on exchanges.
    • Insufficient monitoring: Set-and-forget mentality is dangerous. Even well-designed bots require monitoring to handle edge-cases or technical glitches.

    Consider embedding risk-limiting features. For example, restrict order sizes to a fraction of your total balance and always code for the possibility of missed, delayed, or partially filled orders.

    Choosing Unstable or Unsafe Exchange APIs

    APIs are the backbone of any crypto trading bot, allowing programmatic access to price data, balances, and order actions. For beginners, choosing subpar or poorly documented APIs is a frequent pitfall. Key issues include:

    • Insecure key storage: API keys grant powerful permissions. Storing them in plain text or repositories increases the risk of theft and account compromise.
    • Throttling and limits: Many exchanges impose usage limits on their APIs. Failing to handle request throttling can break your bot's functionality at critical moments.
    • Lack of redundancy: If your bot depends on a single API and it goes offline, your strategy can fail entirely. Good practice includes fallback data sources and error handling routines.

    Take time to evaluate API documentation, community support, and reliability. Explore well-maintained libraries and modules, and always use environment variables or secure vaults for your credentials.

    Failing to Backtest and Simulate Bot Performance

    It's tempting to deploy your trading bot live the moment it compiles without error. However, skipping backtesting—testing your bot on historical data—or forward-testing on a demo account is a recipe for unexpected behavior. Top mistakes here include:

    • Curve-fitting: Over-optimizing your bot to past data makes it unlikely to work under changing real-world conditions.
    • Test environment differences: Bots may behave differently in a testnet/sandbox compared to mainnet, especially regarding latency and real order matching.
    • Poor scenario coverage: Not simulating rare but critical events (such as flash crashes or API downtime) can leave your bot vulnerable when these inevitabilities occur.

    Carefully test your strategies with a range of market conditions and environments before risking live funds. Look for open-source backtesting libraries and consider using paper trading features offered by many exchanges.

    Neglecting Security and Compliance Considerations

    Crypto trading bots operate with sensitive account access and sometimes large balances at risk. New developers often underestimate the importance of security and regulatory compliance. Watch out for:

    • API abuse or leaks: Credentials, if exposed, can lead to unauthorized actions on your exchange accounts.
    • Open-source hazards: Downloading random code from forums or GitHub can introduce backdoors or exploits.
    • Compliance oversight: Depending on your location, automated trading or data collection may have legal implications. Always review exchange policies and seek out reliable, neutral sources on legal requirements before deploying trading bots.

    Implement best practices for code security and stay attentive to legal developments in your jurisdiction. Avoid shortcuts that could put your assets or reputation in danger.

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    What programming languages are best for building a crypto trading bot?

    Most crypto trading bots are built in Python or JavaScript due to strong libraries and exchange support. Some advanced users deploy bots in Java, C#, or Go for higher performance, but Python is considered beginner-friendly.

    How can I test my crypto bot safely before going live?

    Start with backtesting using historical data, then use exchange-provided sandboxes or paper trading environments. This lets you observe your bot’s actual behavior without risking real money or assets.

    What are best practices for managing API keys securely?

    Store API keys in environment variables or encrypted vaults, restrict key permissions, and never share or publish them. Rotate keys periodically and monitor logs for unauthorized activity.

    Can a crypto bot lose money even with a tested strategy?

    Yes; even well-tested bots can lose money due to market changes, exchange outages, slippage, or unforeseen bugs. Continuous monitoring and updates are essential for risk control.

    What tools or platforms can help beginners build better crypto trading bots?

    Platforms offering real-time market data, robust APIs, and community support can help. AI-powered research tools like Token Metrics can assist with backtesting and market analysis, while open-source frameworks provide learning resources.

    Disclaimer

    This article is for educational purposes only and should not be construed as investment, financial, or trading advice. Crypto trading bots carry risks, and readers should conduct thorough research and consult with professionals as appropriate. Always follow relevant laws and exchange terms of service.

    Research

    Mastering Binance & Coinbase APIs for Automated Crypto Trading

    Token Metrics Team
    6
    MIN

    Automating crypto trading with APIs is revolutionizing how traders and developers interact with digital asset markets. If you've ever wondered how to connect directly to exchanges like Binance and Coinbase, automate your strategies, or build your own trading bots, understanding their APIs is the crucial first step. This guide unpacks the essentials of using the Binance and Coinbase APIs for automated crypto trading—explaining the technology, potential use cases, and important considerations for getting started.

    What Are Crypto Trading APIs?

    APIs, or Application Programming Interfaces, enable software to interact directly with external services. Within cryptocurrency trading, APIs provide a standardized way for users and programs to connect with exchange platforms, fetch market data, execute trades, manage portfolios, and access account information programmatically.

    • Market Data: Real-time and historical prices, order books, trade volume, and related metrics.
    • Order Placement: Automated buying/selling, stop-loss, take-profit, and other order types.
    • Account Management: Retrieve balances, view transaction history, or monitor active positions and orders.

    This seamless integration supports the development of sophisticated trading strategies, algorithmic trading bots, portfolio trackers, and research analytics. The most widely adopted crypto trading APIs are those offered by Binance and Coinbase, two of the largest global exchanges.

    Getting Started with Binance API Trading

    Binance’s API is well-documented, robust, and supports diverse endpoints for both spot and futures markets.

    1. Create Your Binance Account: Ensure that your account is verified. Navigate to the Binance user center and access the API Management section.
    2. Generate API Keys: Label your key, complete security authentication, and note both your API key and secret. Keep these credentials secure and never share them publicly.
    3. API Permissions: Explicitly select only the API permissions needed (e.g., read-only for analytics, trading enabled for bots). Avoid enabling withdrawal unless absolutely necessary.
    4. Endpoints: The Binance REST API covers endpoints for market data (public), and trading/account management (private). It also offers a WebSocket API for real-time streams.

    Popular use cases for Binance API trading include automated execution of trading signals, quantitative strategy deployment, and real-time portfolio rebalancing. The official documentation is the go-to resource for development references. Consider open-source SDKs for Python, Node.js, and other languages to streamline integration.

    Unlocking the Power of the Coinbase API

    Coinbase provides comprehensive APIs for both its retail platform and Coinbase Advanced Trade (previously Coinbase Pro). These APIs are favored for their security and straightforward integration, especially in regulated environments.

    1. API Creation: Log in to your Coinbase account, go to API settings, and generate an API key. Set granular permissions for activities like account viewing or trading.
    2. Authentication: The Coinbase API uses a combination of API key, secret, and passphrase. All API requests must be authenticated for private endpoints.
    3. Endpoints & Features: The API allows retrieval of wallet balances, transaction histories, live price data, and supports programmatic trading. The Coinbase API documentation offers detailed guides and SDKs.

    Use the Coinbase API for automated dollar-cost averaging strategies, portfolio analytics, or to connect external research and trading tools to your account. Always apply IP whitelisting and two-factor authentication for heightened security.

    Key Challenges and Considerations in Automated Crypto Trading

    While APIs empower sophisticated trading automation, several technical and strategic considerations should be addressed:

    • API Rate Limits: Both Binance and Coinbase restrict the number of API calls per minute/hour. Exceeding limits can lead to throttling or IP bans, so efficient coding and request management are essential.
    • Security First: Secure storage of API keys, use of environment variables, and permission minimization are vital to prevent unauthorized access or loss of funds.
    • Handling Market Volatility: Automated trading bots must account for slippage, API latency, and unexpected market events.
    • Testing Environments: Utilize the exchanges’ testnet or sandbox APIs to validate strategies and avoid live-market risks during development.

    For more complex strategies, combining data from multiple APIs—including on-chain analytics and AI-powered research—can provide deeper insights and help navigate uncertain market conditions.

    Leveraging AI and Advanced Analytics for Crypto API Trading

    The real advantage of programmatic trading emerges when combining API connectivity with AI-driven analytics. Developers can harness APIs to fetch live data and feed it into machine learning models for signal generation, anomaly detection, or portfolio optimization. Tools like Python’s scikit-learn or TensorFlow—paired with real-time data from Binance, Coinbase, and third-party sources—enable dynamic strategy adjustments based on shifting market trends.

    AI agents and intelligent trading bots are increasingly built to interface directly with crypto APIs, processing complex data streams to execute trades or manage risk autonomously. Such systems benefit from robust backtesting, frequent monitoring, and a modular design to ensure security and compliance with exchange requirements.

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    Token Metrics provides real-time prices, trading signals, and on-chain insights all from one powerful API. Grab a Free API Key

    FAQ: How Do Binance and Coinbase APIs Compare?

    Both Binance and Coinbase offer REST APIs, but Binance has broader asset coverage and advanced trading features, including futures and options support. Coinbase’s APIs prioritize security, are well-suited for U.S. users, and offer streamlined integration for both spot and advanced trade scenarios.

    FAQ: What Programming Languages Can Be Used for Crypto Trading APIs?

    Python, JavaScript/Node.js, and Java are the most popular choices for building automated trading bots due to the availability of SDKs and community support. Most modern APIs are RESTful and compatible with any language that can perform HTTP requests.

    FAQ: How Do I Keep My API Keys Secure?

    Best practices include storing API keys in environment variables, never exposing them in source code repositories, limiting permissions, and regularly rotating keys. Also, use IP whitelisting and two-factor authentication if supported by the exchange.

    FAQ: Can I Use Multiple Exchange APIs Together?

    Yes. Many advanced traders aggregate data and trade across several exchange APIs to increase liquidity access, compare prices, or diversify strategies. This often requires unifying different API schemas and handling each exchange’s unique rate limits and authentication protocols.

    FAQ: What Are the Risks of Automated Trading with Crypto APIs?

    Automated trading can lead to unintended losses if there are bugs in the code, API changes, or sudden market movements. Proper error handling, backtesting, and initial development in sandbox/testnet environments are key risk mitigation steps.

    Disclaimer

    This article is for informational and educational purposes only. It does not constitute investment advice or an offer to buy or sell any cryptocurrency. Always implement robust security practices and perform due diligence before integrating or deploying automated trading solutions.

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