Hyperliquid API Trading Bot Guide — Build Your Own Automated Strategy

Why Build a Bot for Hyperliquid?

Hyperliquid's low-latency infrastructure and zero maker fees make it ideal for algorithmic trading. With sub-millisecond order execution and a clean API, it is one of the best DEXs for running automated strategies. Whether you want to run market-making bots, arbitrage strategies, or simple DCA (dollar-cost averaging), the Hyperliquid API gives you full control.

Because Hyperliquid runs on its own L1 blockchain, the API is more responsive than traditional DEXs built on Ethereum or Solana. There is no gas war, no mempool frontrunning, and no block delay — just fast order matching.

Getting Started: API Access

To use the Hyperliquid API, you need a wallet connected to the platform. The API authenticates using Ed25519 signature signing, similar to how you would sign transactions on Solana or Near. Here is the process:

• Create a wallet (MetaMask or any EVM wallet works with Hyperliquid's bridge)
• Deposit funds into your Hyperliquid account
• Generate an API key through the Hyperliquid dashboard under Settings > API
• Your API key consists of a public address and a secret key (keep this safe)

Never share your secret key or commit it to public code repositories. Use environment variables to store credentials.

Connecting to the Hyperliquid API

The Hyperliquid API base URL is https://api.hyperliquid.xyz. There are two main interfaces:

• REST API: For fetching market data (order books, candles, account info) and placing orders
• WebSocket API: For real-time streaming of order book updates, trades, and user data

Most automated strategies use both: REST for placing orders and checking account state, WebSocket for real-time price feeds and execution confirmations.

Example: Python Trading Bot Skeleton

Here is a basic structure for a Hyperliquid trading bot in Python:

import hashlib
import hmac
import json
import requests
import time

BASE_URL = "https://api.hyperliquid.xyz"

def get_market_data():
    """Fetch current order book for a symbol."""
    payload = dict(type="allMids")
    resp = requests.post(
        BASE_URL + "/info",
        json=payload
    )
    return resp.json()

def sign_payload(payload, secret_key):
    """Sign payload with Ed25519 secret key."""
    # Hyperliquid uses Ed25519 for signing
    # Implement based on your SDK/language
    pass

def place_order(wallet, asset, side, size, price, is_limit=True):
    """Place a limit or market order."""
    order = dict(
        action=dict(
            type="order",
            orders=[dict(
                a=asset,
                b=is_limit,
                p=price,
                s=side,
                r=False,
                sz=size,
                t=dict(limit=dict(tif="Gtc"))
            )],
            grouping="na"
        )
    )
    # Sign and send
    return requests.post(BASE_URL + "/exchange", json=order)

Note: You will need the official Hyperliquid Python SDK or implement Ed25519 signing manually. The SDK handles authentication, signature generation, and WebSocket connections out of the box.

WebSocket Streaming

For real-time data, connect to wss://api.hyperliquid.xyz/ws. You can subscribe to:

• l2Book — Level 2 order book data
• trades — Recent trade feed
• candle — OHLCV candlestick data
• user — Account-level events (fills, order updates)

Subscribing to the WebSocket stream is straightforward. Send a JSON payload with type "subscribe", channel "l2Book", and coin "BTC" and you will receive streaming updates.

Strategy Ideas for Your Hyperliquid Bot

Grid Trading Bot

Place multiple limit orders at different price levels. When an order fills, place the opposite order at a profit target. With Hyperliquid's zero maker fees, grid trading is highly profitable — every fill earns you maker rebates instead of costing fees.

Funding Rate Arbitrage

Monitor funding rates across Hyperliquid and other exchanges. When funding is significantly positive on Hyperliquid, short the perpetual and go long on spot (or another DEX) to capture the funding spread. This requires both API access and careful position management.

TWAP / VWAP Execution

Split large orders into smaller chunks executed over time to minimize market impact. A TWAP bot places small limit orders at regular intervals, using the API to check fill status and adjust prices.

Risk Management for Bot Trading

Automated bots can lose money fast if not properly configured. Follow these rules:

• Set a daily loss limit: If the bot loses more than X% in a day, shut it down automatically
• Use stop-loss orders: Every position should have a stop loss. Hard-code this in your bot logic
• Monitor position size: Do not let the bot compound losses. Cap position size as a percentage of your account
• Test on testnet: Hyperliquid has a testnet environment for development and backtesting

Start with a small capital allocation, run the bot for a week, analyze performance, and only then scale up. Automated trading is a marathon, not a sprint.