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NeoAlpha

Run quantamental stock research, thesis tracking, preset screeners, valuation workflows, portfolio ledgers, and multi-market monitoring across equities.

personAuthor: suidgehubclawhub
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NeoAlpha

Quantamental investing system for OpenClaw across US, HK, and CN equities. NeoAlpha combines thesis-driven fundamental research with quantitative data flows: Longbridge market data, asynchronous thesis tracking, SMAM momentum scans, DCF valuation, natural-language portfolio ledger, and automated premarket/live/close workflows.

When to Use

Use for stock research, investment thesis creation or updates, momentum screening, valuation/modeling, portfolio review, and cron-driven market monitoring.

Core Rules

  1. Verify every number — use Longbridge first; use web search only as a supplement; include source dates.
  2. Route before composing — use the most specific reference or script for the requested workflow.
  3. Use scenarios for valuation — DCF, LBO, and earnings preview outputs need Bear / Base / Bull cases.
  4. Keep the research discipline — facts before inference, verification before judgment, risk before return, quantified payoff.
  5. Use preset screeners for batch evaluation — for short-term or long-term stock selection, call scripts/screen_stocks.py with an explicit preset and universe.
  6. Prioritize market state intraday — market_watch is the live workflow's primary object; single-stock triggers are evidence.
  7. Identify the market session first — for tape reading or short-term analysis, state whether the target market is premarket, regular session, postmarket, closed, lunch break, or cross-day.
  8. Do not misuse extended-hours fields — only cite premarket/postmarket fields when the current time is actually inside that session; otherwise treat them as stale historical context.
  9. Refresh live data for live judgments — intraday/tape-reading answers must pull fresh data in the current session and avoid stale cache unless explicitly disclosed.

Quick Reference

See references/quick-reference.md for request routing.

Common entry points:

External Endpoints

| Service | Purpose | Auth | |---------|---------|------| | longbridge CLI | Quotes, k-line, fundamentals, consensus, events, valuation, and news | User-managed Longbridge auth | | OpenClaw web tools | Supplemental public research when market data is incomplete | Built in |

Data Storage

  • Thesis files: ${INVESTMENT_THESIS_DIR:-~/Documents/neoalpha/thesis-tracker}
    • US: <SYMBOL>.US.md, for example TLN.US.md
    • HK/SH/SZ: <CODE>.<MARKET>-<CompanyName>.md, for example 0700.HK-Tencent.md
  • Daily strategies: memory/strategies/{us,hk}-daily.md
  • Portfolio ledger: memory/strategies/portfolio/transactions.csv as the source of truth
  • Generated portfolio snapshots: memory/strategies/portfolio/positions-current.json and memory/strategies/positions-tracker.md
  • Owner prompts: memory/strategies/{us,hk}-premarket-prompt.md
  • Skill presets and strategy YAML: presets/*.json and strategies/*.yaml

Security and Privacy

  • Do not publish personal thesis files, portfolio ledgers, strategy outputs, prompts, or generated position snapshots.
  • Keep credentials in each tool's own auth store; this skill does not require checked-in tokens or API keys.
  • Treat all scripts as research and monitoring helpers only. They do not place trades.

Position Ledger Protocol

When the user describes a position change in natural language, do not hand-edit position snapshots. Record the transaction first, then continue the analysis.

python3 skills/neoalpha/scripts/portfolio_ledger.py record "<trade description>"

If one message contains multiple trades, split it into atomic records. If price, quantity, side, or symbol is ambiguous, ask before recording.

Related Sibling Skills

  • longbridge and Longbridge sibling skills for market data, news, positions, and valuation.
  • github for GitHub operations.