Apply pecking order theory (Myers and Majluf, 1984) to analyze how information asymmetry drives financing hierarchy decisions. Use this skill when the user needs to explain why firms prefer internal over external financing, interpret equity issuance as a negative signal, evaluate capital raising decisions, or when they ask 'why did the stock drop on the equity offering', 'should we use debt or equity', or 'why do firms hoard cash'.
npx skills add https://github.com/asgard-ai-platform/skills --skill grad-pecking-order
Pecking order theory (Myers & Majluf, 1984) argues that firms follow a strict financing hierarchy — internal funds first, then debt, then equity — driven by information asymmetry between managers and outside investors. Unlike tradeoff theory, there is no target leverage ratio.
IRON LAW: Firms prefer internal financing first because external
financing signals negative private information. Equity issuance is
the most informationally sensitive — and therefore most costly — source.
Key assumptions:
| Source | Adverse Selection Cost | Pecking Order Rank |
|--------|----------------------|-------------------|
| Retained earnings | None | 1st (preferred) |
| Bank debt (secured) | Low | 2nd |
| Public debt (bonds) | Medium | 3rd |
| Convertible debt | Medium-High | 4th |
| Equity issuance | Highest | Last resort |
## Pecking Order Analysis: [Firm / Decision]
### Information Environment
- Asymmetry level: [High / Medium / Low]
- Key drivers: [R&D intensity, asset complexity, etc.]
### Financing Decision
| Option | Available | Adverse Selection Cost | Chosen? |
|--------|-----------|----------------------|---------|
| Internal funds | [Y/N] | None | [Y/N] |
| Debt | [Y/N] | [Low/Medium] | [Y/N] |
| Equity | [Y/N] | [High] | [Y/N] |
### Signaling Implications
- [Expected market reaction and rationale]
### Assessment
- [Consistent with pecking order? If not, why?]
This skill provides an advanced financial modeling suite with DCF analysis, sensitivity testing, Monte Carlo simulations, and scenario planning for investment decisions
This skill retrieves upcoming earnings announcements for US stocks using the Financial Modeling Prep (FMP) API. Use this when the user requests earnings calendar data, wants to know which companies are reporting earnings in the upcoming week, or needs a weekly earnings review. The skill focuses on mid-cap and above companies (over $2B market cap) that have significant market impact, organizing the data by date and timing in a clean markdown table format. Supports multiple environments (CLI, Desktop, Web) with flexible API key management.
This skill should be used when analyzing recent market-moving news events and their impact on equity markets and commodities. Use this skill when the user requests analysis of major financial news from the past 10 days, wants to understand market reactions to monetary policy decisions (FOMC, ECB, BOJ), needs assessment of geopolitical events' impact on commodities, or requires comprehensive review of earnings announcements from mega-cap stocks. The skill automatically collects news using WebSearch/WebFetch tools and produces impact-ranked analysis reports. All analysis thinking and output are conducted in English.
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Inventory management for TikTok Shop — demand forecasting, viral stock planning, FBT optimization
Take asgard-ai-platform/grad-pecking-order from the repository into ~/.claude/skills for personal
use, or into .claude/skills inside a project.
The agent identifies a skill by the name field in its header. Two skills with the
same name cannot sit side by side — one of them will be ignored.