TWZRD Agent Intel
On-chain behavioral trust scoring for Solana agent wallets, with preflight and signed receipts
AI INVEST MAP · TOOLS & RESEARCH GUIDES
Tools for market data, investment research and strategy backtesting.
Recommendations prioritize relevant official financial Skills. Selected markets take priority over language preferences; language does not establish your location or eligibility.
On-chain behavioral trust scoring for Solana agent wallets, with preflight and signed receipts
On-chain agent-tool index with openness and activity scores, x402, and agent-economy metrics
Its official site lists scanning, alerts, alternative and fundamental data, no-code strategy testing, and automation tools.
On-chain metrics including MVRV and SOPR
Agent identity and Cred Score on Base
It includes configurable strategies and exchange integrations, with options to define parameters, strategies, connections, and assets.
The repository includes state and agent code plus a notebook demonstrating data preparation and training a stock-trading agent.
It provides a Python interface to publicly available data; the project states it is not affiliated with Yahoo.
It includes mean-variance, Black-Litterman, shrinkage, and hierarchical risk-parity approaches.
It provides statistics such as returns, volatility, drawdown, and Sharpe ratio for analyzing strategies or portfolios.
Its Python chapters and case studies follow an end-to-end workflow from sourcing data to building and running strategies.
Financial research project with tool use and evaluation, without trading execution
It provides an extensible trading-system foundation on which developers can build strategies and modules.
It produces factor-return, information-coefficient, turnover, and grouped analyses to inspect factor behavior.
QuantConnect describes LEAN as a unified-API engine covering quantitative research, backtesting, and live trading.
Supports live execution
The README presents it as an earlier educational experiment and points to a later financial-trading environment project.
It includes an API client, market-data ingestion, position tracking, SQLite telemetry, a dashboard, and agent tools for evaluating strategies.
Its scikit-learn-compatible interface supports building, tuning, cross-validating, and stress-testing portfolio models.
Pipeline for US House and Senate STOCK Act trade disclosures (PTRs)
It runs strategies against historical market data and analyzes backtests, and can also power a trading system’s execution engine.
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