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trader-portfolio
Optimize portfolio allocation using npx neural-trader mean-variance engine with risk constraints and rebalancing plan
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Optimize portfolio allocation using npx neural-trader mean-variance engine with risk constraints and rebalancing plan
Spawn nested sub-agents (agents that spawn sub-agents, up to depth=5) via Claude Code's native Task tool — for context-managed deep delegation
Author a workflow — either an MCP workflow template (persisted, lifecycle) or a native .claude/workflows/*.js orchestration script (agent/parallel/pipeline fan-out)
Run a workflow — drive an MCP workflow lifecycle (execute/pause/resume/cancel) or invoke + resume a native .claude/workflows/*.js orchestration via the Workflow tool
Side-by-side comparison of ruflo vs HAL vs other GAIA harnesses — capability gaps, design decisions, and improvement roadmap
Diagnose why a GAIA question failed — extract trace, classify failure mode, and propose a fix
Walk through a complete GAIA benchmark→submit flow — from key resolution through HAL-compatible package generation
| name | trader-portfolio |
| description | Optimize portfolio allocation using npx neural-trader mean-variance engine with risk constraints and rebalancing plan |
| allowed-tools | Bash Read mcp__claude-flow__memory_store mcp__claude-flow__memory_retrieve mcp__claude-flow__memory_search mcp__claude-flow__neural_predict mcp__claude-flow__agentdb_pattern-search |
| argument-hint | [--risk-target NUMBER] |
Optimize portfolio allocation using neural-trader's portfolio engine.
Steps:
npm ls neural-trader 2>/dev/null || npm install --ignore-scripts neural-tradermcp__claude-flow__memory_search({ query: "current portfolio holdings", namespace: "trading-portfolio" })npx neural-trader --portfolio optimize
With risk target:
npx neural-trader --portfolio optimize --risk-target <number>
npx neural-trader --risk assess --portfolio current
npx neural-trader --var --portfolio current
npx neural-trader --correlation --portfolio current --flag-threshold 0.8
mcp__claude-flow__neural_predict({ input: "expected returns for [HOLDINGS] given current regime" })npx neural-trader --portfolio rebalance
Output: trades needed, current vs target weights, estimated costsmcp__claude-flow__agentdb_pattern-search({ query: "optimized portfolio Sharpe > 1", namespace: "trading-portfolio" })mcp__claude-flow__memory_store({ key: "portfolio-optimal-TIMESTAMP", value: "ALLOCATION_JSON", namespace: "trading-portfolio" })