eScholarship
metadata only
CC BY
Macro economists in the machine: a multi-agent LLM framework for commodity-related ETF portfolio construction
We test whether large language models (LLMs) add value in commodity-related ETF portfolio construction when information and implementation rules are held fixed across strategies. Hawkish, Dovish, and Debate Agents and a deterministic z-score Rule Agent receive identical macroeconomic inputs and use
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- Engineering Simplicity: Simple Mechanism Interfaces Steer LLM Agents#1131207
- ERPBench: Evaluating LLM Agents for Enterprise Decision-Making Across Competitive Market Ecologies#927934
- Learning to Steer LLM Agents and Multi-Agent Systems#1357971
- Learning to Steer LLM Agents and Multi-Agent Systems#1348837
- EvoProbe: Evaluation-Driven Benchmark Evolution for LLM Agents#1345256
Record · ID 1424920
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive