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Flare unveils the Raindex desktop app to offer seamless trading experiences

1M ago
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AltSignals Presale Investors

Flare has unveiled the Raindex desktop application that offers advanced trading operations on centralized exchanges using the Flare Time Series Oracle (FTSO).

Raindex is an intents-like DEX that makes it possible for those using centralized exchanges to place bid and offer processes, set stop loss, take profit limits, and copy the strategies used by expert traders.

This app will leverage the Rainlang smart contract language, allowing people to design, write, deploy, and manage token trading strategies.

“We’re super excited to introduce Rainlang and Raindex into Flare’s ecosystem, connect with the DeFi community, and see what they create!” said the co-founder of Rain, Josh Hardy.

Users will also use FTSO, the native decentralized price oracle by Flare to create reliable and secure triggers for the asset price.

Flare launches Raindex

Flare has a notable role in the blockchain analytics industry as an Ethereum-virtual machine (EVM) compatible smart contract platform.

Flare is the only smart contract protocol that offers decentralized data acquisition and Web2 API data to boost blockchain utility.

The launch of Raindex, which has been under development for three years, seeks to further Flare’s efforts to achieve its mission.

Those using the app can set their ideal trade outcomes without offering specifics on how trades should be fulfilled.

With Raindex, a trader can perform trades on behalf of another user using a pre-defined strategy.

Raindex users can leverage the Flare Time Series Oracle to create a strategy to sell assets at a given price.

The platform will also facilitate the trade by matching a buyer and a seller, bringing convenience to crypto trades by getting rid of manual order placement and constant market monitoring. 

Raindex brings together the best of the CEX and DEX worlds by offering a CEX-like trading experience with the security and autonomy of DEXs, by giving users more control over their assets.

Raindex also guarantees price accuracy and resistance to censorship using the “Fast Updates” offered by FTSOv2.

By using Rainlang, Flare also guarantees that FTSO data is used within trading strategies to boost market responsiveness and get rid of reliance on third-party and off-chain data oracles.

According to Hardy, traders need secure and reliable data to write their trading strategies, which is made possible through Raindex.

Seamless trading experience

The Rainlang programming language is simple, making it easy for traders to learn how to create smart contracts and implement their customized trading strategies.

Some trading strategies that traders can leverage through this offering include stop losses, dollar-cost averaging (DCA), portfolio rebalancing, liquidity management, Dutch orders, and market making.

With the Raindex desktop app, traders can also develop and write trading strategies and simulate performance before implementing the strategies.

Raindex will also be different from traditional Automated Market Maker (AMM) models by making it possible for traders to set bids and asks, stop loss, and take profit price triggers.

Users can also use Rainlang to deposit tokens into vaults, deploy an order, and have the Raindex app offer real-time performance monitoring.

Flare’s co-founder, Hugo Philion, believes the upgrades to Flare Time Series Oracle will support up to 1,000 asset prices delivered on-chain after every second.

“Combine this with Rain’s intents-like DEX and you enable much of the functionality of a centralized exchange but without the risk of needing to custody your assets with a third party,” Philion said.

Raindex is set to host a trading contest on May 2024, to mark its launch on Flare, with the prize pool of $12,000 going towards those that can use Rainlang to create profitable trading strategies.

For more information: Website | Twitter | Telegram | Discord

The post Flare unveils the Raindex desktop app to offer seamless trading experiences appeared first on Invezz

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