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=== Agent Architecture ===
=== Agent Architecture ===
The system is composed of several specialized agents working in concert:
The system is composed of several specialized agents working in concert:
'''Observation Agent''': A data-ingestion engine that continuously monitors the public APIs (EIA, FRED, etc.) and computes the real-time EEM Score and its derivatives (e.g., rate of change).
'''Observation Agent''': A data-ingestion engine that continuously monitors the public APIs (EIA, FRED, etc.) and computes the real-time EEM Score and its derivatives (e.g., rate of change).
'''Prediction Agent''': A suite of machine learning models (initially LSTMs, later potentially Transformer-based) trained to find correlations between EEM score dynamics and future price movements (ΔP) in target assets.
'''Prediction Agent''': A suite of machine learning models (initially LSTMs, later potentially Transformer-based) trained to find correlations between EEM score dynamics and future price movements (ΔP) in target assets.
'''Decision Agent''': A core logic engine, likely based on Reinforcement Learning or a sophisticated rules-based system. It takes inputs from the Prediction Agent and the current portfolio state, calculates the "virtuousness" of a potential trade, and issues a final decision (Buy, Sell, Hold, Short).
'''Decision Agent''': A core logic engine, likely based on Reinforcement Learning or a sophisticated rules-based system. It takes inputs from the Prediction Agent and the current portfolio state, calculates the "virtuousness" of a potential trade, and issues a final decision (Buy, Sell, Hold, Short).
'''Action Agent''': An execution module that interfaces with broker APIs (e.g., Alpaca, Interactive Brokers). It is responsible for placing orders, managing positions, and enforcing strict risk management guardrails (e.g., stop-losses, position sizing).
'''Action Agent''': An execution module that interfaces with broker APIs (e.g., Alpaca, Interactive Brokers). It is responsible for placing orders, managing positions, and enforcing strict risk management guardrails (e.g., stop-losses, position sizing).
'''Qualitative Agent (Future)''': An LLM-based agent designed to augment the quantitative signals by analyzing news, political events, and market sentiment, providing a layer of human-like intuition.
'''Qualitative Agent (Future)''': An LLM-based agent designed to augment the quantitative signals by analyzing news, political events, and market sentiment, providing a layer of human-like intuition.


=== Deployment Roadmap ===
=== Deployment Roadmap ===
Project Argent follows a phased, professional methodology to mitigate risk and validate its strategies.
Project Argent follows a phased, professional methodology to mitigate risk and validate its strategies.
'''Phase 1: Backtesting''': All proposed trading strategies are rigorously backtested against years of historical EEM and market data to measure their theoretical performance (e.g., Sharpe ratio, max drawdown, ROI).
'''Phase 1: Backtesting''': All proposed trading strategies are rigorously backtested against years of historical EEM and market data to measure their theoretical performance (e.g., Sharpe ratio, max drawdown, ROI).
'''Phase 2: Paper Trading''': Successful strategies are deployed in a simulated environment using live market data but no real capital. This tests the real-world performance of the data pipelines and execution logic.
'''Phase 2: Paper Trading''': Successful strategies are deployed in a simulated environment using live market data but no real capital. This tests the real-world performance of the data pipelines and execution logic.
'''Phase 3: Guarded Pilot''': A small, fixed amount of real capital is allocated to a live trading account. The agent operates under extremely strict guardrails (e.g., max 1% of capital at risk per day) and is closely monitored.
'''Phase 3: Guarded Pilot''': A small, fixed amount of real capital is allocated to a live trading account. The agent operates under extremely strict guardrails (e.g., max 1% of capital at risk per day) and is closely monitored.
'''Phase 4: Scaled Deployment''': As strategies are proven profitable and robust in the pilot phase, their capital allocation can be gradually increased.
'''Phase 4: Scaled Deployment''': As strategies are proven profitable and robust in the pilot phase, their capital allocation can be gradually increased.
The ultimate goal of Project Argent is to generate a sustainable source of surplus energy (profit) that can be reinvested into the AetherOS ecosystem, funding future research, hardware upgrades, and the continued growth of the digital commonwealth.
The ultimate goal of Project Argent is to generate a sustainable source of surplus energy (profit) that can be reinvested into the AetherOS ecosystem, funding future research, hardware upgrades, and the continued growth of the digital commonwealth.
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