Topics of Crypto World

Polygon has introduced its first native liquid staking token, sPOL, enabling users to stake POL and still freely use their assets in DeFi. This initiative not only boosts capital efficiency, but also helps improve the low adoption rate of liquid staking in the Polygon ecosystem.

MANTRA is a blockchain infrastructure designed for real-world assets (RWA), connecting off-chain finance with on-chain systems through asset tokenization and a stablecoin-based settlement mechanism.

At its core, MANTRA works by mapping real world assets into on-chain assets through a standardized process, then managing, trading, and settling them through the protocol.

Lobster is a meme asset issued on BNB Chain and shaped by community narrative. Its emergence did not come from technological innovation, but from the evolution of the AI content trend known as “raising lobsters.”

GENIUS centers its tokenomics around trading activity, using phased airdrops, Season 1 to 3, a points system, and trading rewards to drive user participation across its multi chain trading ecosystem. Its airdrop design gives users two options, claim immediately with a burn penalty, or lock tokens for later release, forcing a choice between short term liquidity and long term holding, and creating an incentive game in the process. On the value capture side, GENIUS ties token distribution directly to trading behavior, using fees, activity levels, and user engagement to build a growth loop.

Genius’s multi-chain trading mechanism uses a routing engine and liquidity aggregation system to turn a user’s trade request into the most efficient execution path, then completes the asset swap across one or more blockchains. Users only need to initiate a trade through a unified interface, while the system automatically scans liquidity sources across different chains and evaluates factors such as price, slippage, and fees to choose the best route. During execution, same chain trades are usually completed by calling decentralized trading protocols, while cross chain trades rely on bridges or other cross chain infrastructure to transfer and exchange assets across different networks. Although the entire process is seamless from the user’s perspective, it involves several backend steps, including path splitting, trade execution, and final settlement.

Genius (GENIUS) is a multi-chain trading terminal designed to provide users with a unified onchain trading gateway by aggregating liquidity and trading routes across multiple blockchain networks. As the DeFi ecosystem continues expanding across chains, the complexity of trading and managing assets across different networks has steadily increased. Through route optimization and cross-chain execution mechanisms, Genius lowers operational barriers and improves trading efficiency. Functionally, Genius is not a single decentralized exchange, or DEX, but infrastructure positioned at the trading entry layer. By integrating DEXs, liquidity pools, and cross-chain components, it creates a unified trading interface and execution logic. This design makes it an important bridge connecting the multi-chain DeFi ecosystem.

CRYPTOBURG is a meme project built on the Bitcoin Runes asset framework, and it operates on Bitcoin’s UTXO structure. That makes it fundamentally different from meme coins on Ethereum and Solana, which rely on an account based model.

CRYPTOBURG combines Bitcoin’s settlement layer, the asset framework provided by Runes, and an application-layer execution path to enable the creation, transfer, and use of digital assets.

Gate introduces the Pre-IPOs mechanism, debuting with SpaceX (SPCX) subscriptions and supporting USDT and GUSD. This article offers a comprehensive overview of the subscription process, allocation rules, log out mechanism, and risk reminder to help users thoroughly understand the investment logic before the IPO.

CRYPTOBURG is an application layer project built on Bitcoin’s Runes protocol, designed to enable native asset issuance and community driven participation. By leveraging Bitcoin’s UTXO structure, it allows assets to be created and transferred without relying on complex smart contracts. Its model combines asset mechanics with meme driven distribution, positioning it within the evolving landscape of Bitcoin based digital economies.

The workflow of cryptocurrency OTC trading typically includes trade initiation, RFQ (Request for Quote), multiple price submissions, price selection, and final settlement. By relying on market makers to provide liquidity, OTC trading reduces slippage and avoids market impact. With the introduction of algorithmic trading, the OTC process is increasingly becoming automated, allowing institutions to execute trades efficiently and consistently across fragmented liquidity environments.

Algorithmic trading, or algo trading, refers to the use of programmed models to automate trading decisions and order execution. In the crypto OTC market, it is primarily used to optimize the RFQ, or request for quote, process and enable smart routing and liquidity aggregation, helping traders achieve best execution in a fragmented market. Through automated quote distribution, real time price analysis, and path optimization, algorithmic trading not only significantly reduces slippage and market impact, but has also become core infrastructure for institutional block trading, driving the OTC market toward greater electronic and systematic development.

In the cryptocurrency market, institutions typically execute large trades by combining RFQ (Request for Quote) with algorithmic trading. RFQ is used to obtain customized quotes from multiple liquidity providers, while algorithmic trading automates request distribution, optimizes quote selection, and ensures best execution. Together, this approach reduces slippage, minimizes market impact, and improves execution efficiency, making it a core method for institutional trading in today’s OTC markets.

RFQ, or Request for Quote, is a pricing mechanism widely used in crypto OTC trading. It allows traders to request quotes from multiple liquidity providers and select the best available price to execute a trade. Compared to traditional order book matching, RFQ helps reduce slippage, minimizes market impact, and supports large transactions. With the rise of algorithmic trading, the RFQ process is becoming increasingly automated and intelligently routed, making it a foundational component of institutional-grade trading infrastructure.