As AlphaNet is adding more strategies - users are presented with more diverse choices of alpha. By end of Q2 we expect to have 100+ institutional-grade strategies. How to create an agentic system for user-driven strategy selection and deployment based on personalized goals?
This represents the next evolution of AlphaNet's platform => institutional-grade alpha + agentic autonomous personalized systems, currently already in intermediate stages of development.
Read our brand new research paper below:
"Novel Agentic System for User Preference-Driven Strategy Selection"
https://t.co/hIL3Nsswzn
Another big new month comes for AlphaNet - but before we see what June has to offer, let's recap on the month of May in our latest user newsletter, where we go over key metric snapshots, strategy trading behavior, market volatility, and close look into what happens under the hood for Hackworth Series strategy engine.
New live performance metrics, leaderboards, and analytics coming soon to AlphaNet.
Read the newsletter below:
https://t.co/6Ub8UnrYyH
Public launch (hypergrowth), new features, new user-driven guild system, extended credits (leverage), and more.
Floodgates of adoption has opened.
#AITrading#vibetrading
The much anticipated AlphaNet public launch is now here. No whitelist applications - simply connect, explore, select, and deploy across an arsenal of institutional-grade quantitative AI strategies.
New features include strategy capacity gauge and signals & trading view to help users understand a strategy's popularity and give a preview of how it trades.
A much awaited, brand-new user and merit-driven Guild Leader System and Extended Credits program for VIP users will be unveiled shortly.
Happy alpha-generating!
AlphaNet will be open to all users starting May 25, 2026 - no whitelisting or approvals required. After months of meticulous testing, upgrades, and getting early user feedback, we are ready to ignite the growth engine.
Premium user tiers and brand-new user-driven guild and referral system coming soon.
Traditional quant strategies utilize "alpha mining", utilizing often explainable signals (price/volume, microstructure, macro, event-driven etc) to generate trades and positions - and this is what majority of Wall Street firms use. In China over 80% of the top quant firms heavily utilize deep learning systems (including Deepseek's parent High Flyer), a black-box approach that is often non-explainable and uses deep neural network based trained on years of historical data to output predictions from hundreds or thousands of data points.
It is a controversial topic, which practitioners in category often critiquing the other. This 47-page paper compares in detail both approaches and provides an argument on why deep learning has bigger long-term moat.
It also covers frontier approaches for portfolio management in deep learning strategies. (Hint: multi-asset portfolio strategies coming to AlphaNet)
The paper is first being published first in the Chinese quant and academic industry - source is below:
https://t.co/0uLstFrsxa
If the current edge and alpha we provide users is not enough - here's some more: prediction markets data from Polymarket now integrated into Hackworth Series V2 strategies (Prime, OptimaShort, Trend), bringing the number of data points (features) utilized in Hackworth proprietary engine up to over 500.
After meticulous testing and experimentation that proved to improve performance, Polymarket crypto data (5 min prediction to daily) is now integrated into all Hackworth Series V2 strategies (for applicable pairs and strategies) - further advancing our users' edge.
Now Hackworth Series V2 (currently used by XMR and ADA) strategies inclusive of Polymarket data utilize over 500+ features (data points) for its core deep learning-based engine.
Additional updates including multi-language support and shareable strategies:
https://t.co/gEL8xOTdbb
AlphaNet wraps up April strong with plenty of alpha for our users ๐ช Proprietary quantitative engine + ample AI compute speak for itself. We have over 60+ more strategies being vetted in the pipeline.
As AlphaNet is growing and now on average approving 30+ whitelist requests per day, we are listening and catering to varying needs of different users.
From 5/15 onwards, we will be enabling Extended Credits for select users that fit certain criteria (deployment sizes, overall PnL performance, age on platform). This would enable users to extend leverage to their strategy deployments of up to 1.5x account size initially. For example, an initial account size of 10,000 USDT would be able to deploy 15,000 across strategies of the users' choice.
#AIquant #vibetrading
The left is a chart showing sideways action of $XMR for April. Right shows AlphaNet smoothly delivering a half-month return of 9% for the same month.
Can you beat AlphaNet trading the chop? We're soon to find out as we roll out user vs AlphaNet trading competitions.
#AITrading #vibetrading $PHB
Not even halfway into April and AlphaNet continues to deliver for users - notably newcomer Hackworth Trend XMR coming in strong within less than 10 days of being online.
The odds of generating alpha and beating the market will continue to be in our users' favor.
#AITrading #vibetrading #aiquant
https://t.co/S9pznDiUBE
New official site and portal for AlphaNet has launched, featuring a new look and better accessibility. This launch precedes next steps in platform growth and hyperscaling.
Trading will be relocated to https://t.co/PEmpQROFWA this week, which may require some users to reconnect their wallet depending on browser settings.
#tradingevolved #AITrading #vibetrading
New strategies for $ADA and $XMR utilizing the new and improved Hackworth Prime V2 engine to be online on March 31.
AlphaNet's alpha capacity and choices continue expanding with no signs of slowing down.
#vibetrading#AITrading
Why doesn't any trading platform offer SOTA algo trade execution for minimizing slippage? Simply because its no trivial matter, and requires low-latency systems, machine learning knowhow and specialized R&D resources. As AlphaNet onboards new early users and institutional partners, maximizing alpha capacity across strategies means continue pushing the envelope for proprietary algorithmic execution engines to minimize trading costs.
Below is the newest benchmark of a ~15BTC, 30 second algo execution via AlphaNet's V4 TWAP Engine (compared to prior versions), which utilizes tick-level data and predictive deep learning to balance liquidity and price directional drift for optimizing overall cost. The results yielded an astounding average slippage of $4.68 across over 1000 trials.
For those interested in the basic theory and system behind AlphaNet's execution engine, refer to the technical whitepaper section below:
https://t.co/AZoazkgM3d
With the proliferation of DEXs, prediction markets, and leveraged โgambling housesโ of various forms โ retail traders canโt seem to find what theyโre looking for: consistent trading edge and alpha. According to sources, 74-89% of leveraged retail traders on CEXs lose money, and up to 95% on perp DEXs are unprofitable.
Upon 2 and a half months of launch, AlphaNet has delivered what no other platform in this market has โ consistent systematic alpha with superior risk-adjusted returns. And it has delivered it in a seamless fashion with minimal effort from users, with a click of a button.
With such a definitive and differentiated value proposition for the market and technical prowess to back it โ we are hellbent on building, growing out, and scaling the platform. No obstacles can stop us.
We are initiating hypergrowth with various new feature & strategy rollouts, community incentive initiatives, and strategic maneuvers - including community guild leaders and other ownership-based programs.
Stay tuned. #AITrading #vibetrading #tradingevolved
AlphaNet is receiving acclaim from early users and partners in the trading ecosystem for being differentiated in its value-delivery approach to trading โ it has also garnered substantial institutional attention, namely in terms of potential equity investors, in which we aim to close an equity funding round within the next month.
We are aware of the monitoring tag situation and have reached out to Binance to communicate since the day of. Since then, we have pinpointed and assessed the scope of the issue to 1) no significant tech and product-level developments being communicated in past 2 months and 2) subpar community communication on planning, developmental, and governance related issues. (1/5)
As we learned, a regular overall project review was triggered via Proposal 1 token economics changes, and the issues were assessed in the process. No problem was with Proposal 1 itself, as Phoenix has communicated and outlined with detail the specifics, including voting results with Binance team in advance. We are working to rectify these points ASAP. (4/5)