Collecting Perpetual Contract Funding Rate Data

In a previous blog post, we explored the principles of perpetual contract funding rate arbitrage. For any trading strategy to be viable long-term, it's essential to analyze its performance across different market conditions—a process that relies heavily on historical data collection.

This article focuses on how to gather historical funding rate data from major exchanges efficiently.

Funding Rate Data Sources

1. Exchange Web Pages

Funding rates are calculated by individual exchanges, making their platforms the primary data source.

Initially, exchanges only displayed the latest funding rate, with no access to expired data. However, as funding rate arbitrage gained popularity, platforms like Binance, Bybit, and OKX began offering downloadable historical datasets.

Binance

• Real-Time Rate: Displayed on the trading page (predictive, not historical).
• Historical Data: Available via Funding Rate History. Users can download full datasets in CSV format.

Bybit

• Provides comprehensive historical data:
  Bybit Funding Rate History.

OKX

• Limitation: Only offers the last three months of data:
  OKX Funding Rate History.

👉 Compare funding rate strategies across exchanges

2. Exchange APIs

For automated or real-time trading, APIs are indispensable. Below are the API endpoints for major exchanges:

Binance

• USDⓈ-M Futures: Funding Rate History API.
• Coin-M Futures: Separate API.

Bybit

• Funding Rate History API.

OKX

• Limited to recent data: OKX Funding Rate API.

3. Automated Data Collection with Python

Using the ccxt library simplifies API interactions. Below is a Python script to fetch Binance’s funding rates for BTC/USDT:

import ccxt
import pandas as pd

def fetch_funding_rates(symbol="BTCUSDT"):
    binance = ccxt.binanceusdm()
    rates = binance.fetch_funding_rate_history(symbol=symbol)
    df = pd.DataFrame(rates)[["datetime", "fundingRate"]]
    df.to_csv("funding_rates.csv", index=False)
    return df

fetch_funding_rates()

Output Example:

[
  {
    "datetime": "2024-05-25T08:00:00.000Z",
    "fundingRate": 0.0001
  },
  {
    "datetime": "2024-05-25T16:00:00.000Z",
    "fundingRate": 0.0001
  }
]

👉 Optimize your API data fetching with these tips

4. Third-Party Platforms

For those who prefer pre-analyzed data, platforms like Coinglass aggregate funding rates from multiple exchanges and provide visualization tools:

• Coinglass Funding Rate Dashboard.

FAQs

Q1: Why is historical funding rate data important?

A: It helps backtest arbitrage strategies and assess their viability under different market conditions.

Q2: Which exchange offers the most comprehensive historical data?

A: Binance and Bybit provide full datasets, while OKX limits access to the last three months.

Q3: Can I automate funding rate data collection?

A: Yes, using APIs and libraries like ccxt in Python allows seamless automation.

Key Takeaways

• Manual Download: Use exchange web pages for one-time downloads.
• API Integration: Essential for real-time data in algorithmic trading.
• Third-Party Tools: Coinglass offers aggregated data and analytics.

By leveraging these methods, traders can build robust datasets for funding rate arbitrage analysis.

Next Step: Analyze funding rate trends to identify arbitrage opportunities.