# Investment Research Analyst

> Multi-agent investment research framework simulating a professional trading firm. Performs comprehensive stock analysis including fundamentals, news, sentiment, technicals, bull/bear debate, risk assessment, and fact-checking. Triggered by: company research, stock analysis, market sentiment, portfolio risk, 股票分析, 公司研究, 投研分析

- Skill: `lord1egypt/investment-research-analyst` (Agent Skill)
- Install (CLI): `npx skillmds@latest add lord1egypt/investment-research-analyst`
- Raw SKILL.md: https://api.skillmd.com/api/skills/lord1egypt/investment-research-analyst/raw
- Safety review: pending (external: skill-scanner PASS, skillspector PASS)
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: AI & ML
- Author: Lord1Egypt (https://skillmd.com/u/lord1egypt)
- Updated: 2026-09-08
- Page: https://skillmd.com/skills/lord1egypt/investment-research-analyst

---


# Investment Research Analyst

## Overview

You are a **Chief Analyst** simulating a professional investment firm's operations. Conduct in-depth research on listed companies across 8 dimensions: fundamentals, news, sentiment, technicals, bull/bear debate, risk assessment, and fact-checking.

## Workflow

### Step 1: Multi-Dimensional Research
1. **Fundamentals** — Financial statements, profitability, valuation, analyst forecasts
2. **News** — Company dynamics, industry news, policy impacts, management changes
3. **Sentiment** — Market sentiment, institutional views, rating changes
4. **Technical Analysis** — Price trends, volume, key levels

### Step 2: Debate
5. **Bull Case** — Build bull thesis with supporting evidence
6. **Bear Case** — Identify risks and concerns

### Step 3: Risk & Verification
7. **Risk Assessment** — Comprehensive risk evaluation
8. **Fact-Check** — Verify key data and claims

### Step 4: Output & Deploy
9. Output full research report
10. Deploy as interactive Dashboard

## Data Sources

### A-Stocks (akshare)
```python
import akshare as ak
ak.stock_individual_info_em(symbol="600519")  # Company info
ak.stock_financial_analysis_indicator(symbol="600519")  # Financial metrics
ak.stock_zh_a_hist(symbol="600519", period="daily", adjust="qfq")  # Daily OHLCV
ak.stock_hk_financial_hk(symbol="00700")  # HK financials
```

### US Stocks (yfinance)
```python
import yfinance as yf
stock = yf.Ticker("AAPL")
stock.info  # Valuation
stock.financials  # Income statement
stock.balance_sheet  # Balance sheet
stock.history(period="1y")  # OHLCV
```

## Analysis Outputs

### Fundamentals → Report Section
- Revenue, net income, margins, ROE, ROA
- DCF, PE, PB, PS, PEG, EV/EBITDA comparison
- Broker ratings, price targets, consensus EPS

### News → Report Section
- Recent company/industry/macro news (7-30 days)
- Impact assessment: positive/negative

### Sentiment → Report Section
- Social media tone (Twitter/X, Reddit, StockTwits)
- Institutional holdings, insider trading, short interest

### Technicals → Report Section
- SMA 20/50/200, RSI(14), MACD, support/resistance
- Entry/exit zones, stop-loss levels

### Bull/Bear Debate → Report Section
- Key catalysts, PT, best/worst case scenarios
- Rebuttals to opposing views

### Risk → Report Section
- Position sizing, volatility, liquidity
- Stop-loss recommendation, risk/return ratio

### Fact-Check → Report Section
- Cross-verify key financials and valuations
- Flag discrepancies with sources

## Research Report Template

```
## [Company Name] ([Ticker]) — Research Report

### Summary
[Business overview, industry position, valuation snapshot]

### Financials
| Metric | Value | YoY | vs. Sector |
|--------|-------|-----|------------|
| Revenue | X | +/-% | [Rank] |
| Net Income | X | +/-% | [Rank] |
| Gross Margin | X% | +/-pp | [Rank] |
| ROE | X% | +/-pp | [Rank] |

### Valuation
| Metric | Current | Historical | Sector Avg |
|--------|---------|------------|------------|
| PE(TTM) | X | X%ile | X |
| PB | X | X%ile | X |
| PS | X | X%ile | X |

### Analysts
- Rating: Buy/N/Hold/Sell (X brokers)
- PT range: X - X
- Consensus EPS: FY1=X, FY2=X

### Bull Case 🐂
[2-3 key catalysts with data support]

### Bear Case 🐻
[2-3 key risks with data support]

### Risks ⚠️
[Top 3 risks with probability and impact]

### Overall: 🟢 High / 🟡 Medium / 🔴 Low Value

### Disclaimer
AI-generated. Not investment advice.
```

## Dashboard

After completing the report, deploy it as a professional interactive Dashboard (HTML/CSS/JS, black theme, minimalist Notion-style). Use the `deploy` tool to publish and share the link.