metaAndAssetCtxs | Hyperliquid info

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Parameters

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Request body

• type (string, required) — The request type. Must be "metaAndAssetCtxs" to retrieve asset contexts.

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Response

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Response structure

1. Universe metadata — Static asset definitions and trading parameters
2. Asset contexts — Real-time market data for each asset

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Universe metadata structure

• name — Asset symbol (e.g., “BTC”, “ETH”, “AVAX”)
• Corresponds to the perpetual contract identifier

• szDecimals — Number of decimal places for size precision
• maxLeverage — Maximum leverage allowed for this asset
• onlyIsolated — Boolean indicating if asset requires isolated margin mode

• Size decimals determine minimum order size increments
• Max leverage sets risk management limits
• Isolated margin requirement affects trading strategies

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Asset contexts structure

• markPx — Current mark price used for margin calculations
• midPx — Mid price between best bid and ask
• oraclePx — Oracle price from external price feeds
• prevDayPx — Price from 24 hours ago for daily change calculation

• impactPxs — Array of two impact prices [buy impact, sell impact]
• Shows expected price impact for market orders
• Useful for assessing market liquidity and slippage

• funding — Current funding rate for the perpetual contract
• premium — Premium of mark price over oracle price
• Indicates market sentiment and arbitrage opportunities

• dayNtlVlm — Daily notional volume traded
• openInterest — Total open interest across all positions
• Measures market activity and participation

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Data interpretation

• Mark price vs oracle price indicates market premium/discount
• Mid price vs mark price shows funding impact
• Impact prices indicate market depth and liquidity

• High volume with stable prices indicates healthy liquidity
• Large premium suggests strong directional bias
• High open interest indicates active participation

• Funding rates affect carry costs for positions
• Impact prices help estimate execution costs
• Volume patterns indicate market activity cycles

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Market analysis insights

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Liquidity assessment

• Impact prices reveal available liquidity at different levels
• Tight spreads between impact prices indicate deep markets
• Wide spreads suggest lower liquidity or higher volatility

• Daily notional volume shows market activity levels
• Compare volume across assets to identify active markets
• Volume trends indicate changing market interest

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Funding rate analysis

• Funding rates determine the cost of holding positions
• Positive funding means longs pay shorts
• Negative funding means shorts pay longs

• Persistent positive funding indicates bullish sentiment
• Persistent negative funding indicates bearish sentiment
• Funding rate changes signal sentiment shifts

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Price discovery insights

• Premium indicates market’s view vs external prices
• Persistent premiums suggest strong directional bias
• Premium convergence indicates arbitrage efficiency

• Impact prices help estimate execution costs
• Compare impact across assets for relative liquidity
• Use for optimal order sizing and execution strategies

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Risk management applications

• Max leverage varies by asset based on volatility and liquidity
• Isolated margin requirements for certain assets
• Use constraints for position sizing and risk management

• Price changes from previous day show daily volatility
• Premium volatility indicates market uncertainty
• Impact price spreads reflect intraday volatility

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Example request

curl -X POST \
  -H "Content-Type: application/json" \
  -d '{"type": "metaAndAssetCtxs"}' \
  https://api.hyperliquid.xyz/info

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Example response

[
  {
    "universe": [
      {
        "name": "BTC",
        "szDecimals": 5,
        "maxLeverage": 50
      },
      {
        "name": "ETH",
        "szDecimals": 4,
        "maxLeverage": 50
      },
      {
        "name": "HPOS",
        "szDecimals": 0,
        "maxLeverage": 3,
        "onlyIsolated": true
      }
    ]
  },
  [
    {
      "dayNtlVlm": "1169046.29406",
      "funding": "0.0000125",
      "impactPxs": [
        "14.3047",
        "14.3444"
      ],
      "markPx": "14.3161",
      "midPx": "14.314",
      "openInterest": "688.11",
      "oraclePx": "14.32",
      "premium": "0.00031774",
      "prevDayPx": "15.322"
    },
    {
      "dayNtlVlm": "1426126.295175",
      "funding": "0.0000125",
      "impactPxs": [
        "6.0386",
        "6.0562"
      ],
      "markPx": "6.0436",
      "midPx": "6.0431",
      "openInterest": "1882.55",
      "oraclePx": "6.0457",
      "premium": "0.00028119",
      "prevDayPx": "6.3611"
    }
  ]
]

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Use cases

• Trading platform development: Build trading interfaces with real-time market data
• Market making: Develop market making strategies using price and liquidity data
• Risk management: Implement risk controls based on leverage limits and market conditions
• Portfolio management: Manage multi-asset portfolios with comprehensive market context
• Price discovery: Analyze price relationships and arbitrage opportunities
• Liquidity analysis: Assess market liquidity and execution costs across assets
• Funding rate strategies: Develop strategies based on funding rate patterns
• Market surveillance: Monitor market conditions and detect anomalies
• Academic research: Study perpetual futures markets and price discovery mechanisms
• Algorithmic trading: Build automated trading systems with market context
• Order management: Optimize order execution based on impact prices and liquidity
• Market data feeds: Provide real-time market data to trading applications
• Analytics platforms: Build comprehensive market analysis and reporting tools
• Educational tools: Create educational content about perpetual futures markets
• Compliance monitoring: Monitor market conditions for regulatory compliance
• Arbitrage detection: Identify arbitrage opportunities between mark and oracle prices
• Volatility analysis: Analyze market volatility patterns across different assets
• Liquidity provision: Optimize liquidity provision strategies based on market depth
• Cross-asset analysis: Compare market conditions across different perpetual contracts
• Market timing: Time market entries and exits based on funding and premium data
• Position sizing: Optimize position sizes based on leverage limits and market impact
• Execution algorithms: Develop sophisticated execution algorithms using market context
• Market microstructure research: Study the microstructure of perpetual futures markets
• Trading strategy backtesting: Use historical contexts for strategy development and testing
• Client advisory: Provide market insights and trading recommendations to clients