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AlphaNet AI DEX launch on Phoenix Global introduces AI powered execution and quantitative trading strategies for retail perpetuals traders.
Author: Akshay
Published On: Thu, 01 Jan 2026 08:08:43 GMT
January 1, 2026. The AlphaNet AI DEX launch marks Phoenix Global’s entry into AI driven decentralized perpetuals trading, introducing a platform built around proprietary machine learning models. The exchange is now live for whitelisted users through Phoenix Global’s trading interface.
AlphaNet introduces an AI powered execution engine designed to reduce slippage and improve fill quality, including cases of negative slippage. Machine learning models assist with trend detection and entry and exit optimization.
The platform also offers click to deploy quantitative strategies, including market neutral, mean reversion, and volatility based approaches. Users can monitor and adjust strategies in real time, with more models and tutorials planned.
January 1, 2026. The launch of AlphaNet AI DEX on Phoenix Global has driven positive short term sentiment, with $PHB trading around $0.72 to $1.77 USD across sources and posting intraday gains of 3 to 8 percent, while 24 hour volume surged to as much as $40 million, reflecting strong interest from the whitelisted rollout and upcoming feature expansions.
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December 31, 2025. Phoenix Global advanced its ecosystem in 2025 with a strong focus on AI infrastructure and enterprise oriented Web3 products. Development centered on the PhoenixONE research platform and groundwork for the AlphaNet AI DEX rollout.
Key progress included the launch and upgrade of PhoenixONE, expanded enterprise pilots, and growing community engagement through research tools and competitions. $PHB traded in consolidation through late 2025, reflecting a shift toward utility driven growth and positioning Phoenix Global for broader AI DeFi adoption in 2026.
Phoenix Global’s AlphaNet AI DEX launch highlights the role of artificial intelligence in DeFi perpetuals trading. Students can explore how machine learning reduces slippage, optimizes timing, and deploys quantitative strategies such as market neutral and mean reversion for retail users. Discuss ethical AI use, including transparency and bias risks, alongside the democratization of institutional trading tools. Compare traditional quantitative trading barriers with blockchain based open access. Highlight real time monitoring as an example of adaptive algorithms. This case illustrates AI and DeFi convergence, bridging finance, computer science, and blockchain for future trading education.
Real voices. Real reactions.
@Phoenix_Chain 🤖 AI-driven execution and quantitative strategies add edge for institutional-grade trading. Maturing tools for leveraged environments. @Phoenix_Chain #AITrading
@Phoenix_Chain @ranyi1115 Looks like Orderly strikes again
@Phoenix_Chain Insane. The agentic future of trading is finally happening — not just charts and buttons, but AI that executes, predicts and trades for you. AlphaNet feels like what Hyperliquid or GMX should have been in 2025. Retail finally gets institutional-grade alpha. Let’s go. 🚀🔥
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