Skip to content

GUIDES · DOCUMENTATION · RESEARCH

Resources & documentation.

Explore the guides, architecture, and research behind AlphaNet’s AI futures trading platform.

Explore the library

4 DOCS · 4 PAPERS
DOCS//01

AlphaNet Technical Whitepaper

Explore the protocol architecture, quantitative models, and execution approach.

READ WHITEPAPER DOCS//02

AlphaNet User Guide

Product walkthroughs and account setup, from your first login to your first deployment.

READ GUIDE DOCS//03

Hackworth V3 AI Trading Engine

Explore the V3 engine release, including risk management, alpha discovery, market regimes, and execution updates.

READ DOCUMENTATION DOCS//04

Archimedes Series Engine

Explore the regime-aware deep-learning engine, four preview strategies, historical backtests, and signal-level validation.

READ DOCUMENTATION PAPER//05

Automated Feature Engineering & Factor Mining

A study of automated feature engineering and quantitative factor discovery from market microstructure data.

DATE · 6 December 2025AUTHOR · Jimmy Hu · Applied AI Research Team, Tensor Systems READ PAPER PAPER//06

Algorithmic Trade Execution: Dynamic TWAP

Compare stochastic control and deep reinforcement learning for dynamic TWAP execution and implementation shortfall.

DATE · 28 October 2025AUTHOR · Jimmy Hu · Quantitative Research and Algorithmic Trading Division, Tensor Systems READ PAPER PAPER//07

Agents for Trading Strategy Selection

How AI agents match existing trading strategies to user preferences, risk limits, and portfolio objectives.

DATE · April 2026AUTHOR · Jimmy Hu and the Agents Team, Tensor Systems · AlphaNet Development Team READ PAPER PAPER//08

Deep Learning for Algorithmic Trading vs. Alpha Mining

Explore the trade-offs between systematic alpha mining and deep learning for algorithmic trading.

DATE · April 2026AUTHOR · Jimmy Hu · Tensor Systems READ PAPER

Ready to explore a market?

Choose an asset and review its strategy and risk data.

Browse markets →