Now Live: FETUSD Perpetual Swap Listing with Up to 10x Leverage 

A new listing featuring – FET – the token of Fetch.AI is available to trade on BitMEX, and with up to 10x leverage. For the lowdown on the latest listing, read on.

If you haven’t signed up for a BitMEX account yet, we’re currently offering up to $5,000 in BMEX Tokens for verified users- you can register here.

FETUSD Quanto Contract Specs

As with all quanto contracts, the FETUSD product has a fixed Bitcoin multiplier, regardless of the FET/USD price. This allows traders to long or short the FET/USD exchange rate without ever touching FET or USD.

Traders can post margin in XBT, and earn or lose in XBT as the FET/USD rate changes. 

This quanto risk premium may be one of the factors that results in the FETUSD swap trading at a premium/discount to the FETUSD spot price. 

Key contract details for our FET token listing:

  • Symbol: FETUSD
  • Margin Currency: XBT
  • Bitcoin Multiplier: 0.0001 XBT (10,000 Satoshis)
  • XBT Contract Value: FETUSD Price * Bitcoin Multiplier (10,000 Sat / 1 USD)
  • Underlying: .BFET
  • Max Leverage: 10x
  • Risk limit: 50 XBT
  • Maker Fee: 0.02%
  • Taker Fee: 0.075%
  • Base Initial Margin: 10.00%
  • Base Maintenance Margin: 5.00%

You can trade the FETUSD perpetual contract here, or refer to the full contract specs here.

About FET – the Fetch.AI Token.

FET is the token of Fetch.AI  – An innovative platform connecting IoT devices and algorithms to enable collective learning. Built on a high throughput sharded ledger, the architecture delivers a unique smart contract capability to deploy ML/AI solutions for the decentralised problem solving. democratises access to AI technology with a permissionless network upon which anyone can connect and access secure datasets by using autonomous AI to execute tasks that leverage its global network of data. The Fetch.AI model is rooted in use cases like optimising DeFi trading services, transportation networks (parking, micromobility), smart energy grids and travel. It is best suited for any complex digital system that relies on large-scale datasets.

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