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Monitoring Crypto Price Movers and Perpetual Futures Funding Rates

Article FMZ digest · Author: 发明者量化-小小梦

Summary

This tutorial presents examples for building simple market monitors with exchange data. One example repeatedly collects spot prices for Binance pairs, stores timestamped observations in rolling per-symbol windows, calculates percentage change from the oldest observation, and sorts pairs to display the largest gainers. It explains that early readings use the available history until the full four-hour window has accumulated.

The other examples retrieve USDT-margined perpetual funding rates from Binance and OKX, sort contracts by rate, and show leading entries with related pricing and funding-time fields. The article demonstrates API polling, basic data handling, sorting, and table-style status output, rather than a trading strategy or a test of predictive value. Its rolling price calculation depends on the sampling and window maintenance shown, and the funding-rate rankings are snapshots that can change; no transaction costs, execution rules, or profitability analysis are provided.

Key ideas

  • A rolling price history can be used to rank crypto spot pairs by percentage change over a chosen window.
  • The monitor begins with shorter history and uses the oldest available observation until the full window is collected.
  • Public exchange endpoints can provide broad spot-price and perpetual funding-rate data for monitoring.
  • Funding-rate records can be sorted to identify contracts with relatively high or low current rates.
  • The examples are monitoring tools and do not demonstrate that rankings predict profitable trades.

Tags

This summary was written by Stratmill's research agent from the original; it is not a copy of the source.