macro-regime

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Macro regime analysis, bull bear market detection, business cycle analysis, macro environment assessment, interest rate cycle, yield curve analysis, monetary policy, fiscal policy, global macro, central bank posture, credit cycle, recession probability, expansion regime, macro regime shift, stagflation detection

AI & Automation 204 stars 16 forks Updated today Apache-2.0

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## Defaults | Parameter | Default Value | Rationale | |-----------|---------------|-----------| | lookback_quarters | 8 | 2yr captures cycle inflection while remaining responsive | | regime_indicators | yield_curve, credit_spreads, PMI, VIX, fed_posture | Standard macro regime detection set | | probability_weighting | bear/base/bull | Three-scenario framework per institutional standard | ## Preflight Run the canonical pre-flight sequence: MCP health probe, ticker resolution, workspace style override, memory load, and coverage check. See `contracts/preflight.md`. Propagate X-Agentii-Trace header per `contracts/x-agentii-trace-header.md`. ## Data Source Priority (mandatory order) 1. Knowledge entries FIRST — query gold.knowledge_entries for L1 regime frameworks 2. Historical analogues SECOND — query search_by_analogue(market_regime) for matching cases 3. Real-time data LAST — supplemental only ## Methodology ### Retrieval Scope structured_only ### Retrieval Strategy 1. Query knowledge entries for L1 frameworks via search_knowledge_entries 2. Query search_by_analogue for historical regime precedents 3. Supplement with real-time data ### Temporal Scope See frontmatter temporal_scope block. ### Tool Allowlist See frontmatter allowed_tools. ### Protocol 1. Regime Detection — classify current macro environment using yield curve, credit spreads, PMI, VIX, Fed posture 2. Framework Application — apply relevant L1 framework from references/knowledge-frameworks.md 3. Analogue ...

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Author
agentii-ai
Repository
agentii-ai/agentii-investment-intelligence
Created
4 months ago
Last Updated
today
Language
Python
License
Apache-2.0

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