Stockaskill

Multi-market intelligent stock selection for A-share/HK/US stocks and ETFs. Use when user asks about stock analysis, market scanning, portfolio construction, factor screening, quantitative strategy signals, fund screening, backtesting, or investment diagnosis. Triggers on stock codes (600519, AAPL, 0700.HK), Chinese stock names (贵州茅台), fund codes (510300), and queries with keywords like "分析", "选股", "scan", "portfolio", "backtest", "因子", "评分", "BUY/SELL/HOLD", or "诊断".

Smart Stock Selector

Multi-market stock selection with AKShare + SQLite caching. Covers A-shares, HK, US, and funds (ETF/LOF).

Core promise

Given a stock code, market, or investment theme, return actionable signals with scores. All analysis is script-driven and cache-backed. First fetch the pool if cache is cold.

Triggers

Activate on any of these user intents:

Keyword / pattern	Likely intent
Code like 600519, AAPL, 0700.HK, 510300	Single stock analysis or diagnosis
Chinese name like 贵州茅台	Resolve from pool, then analyze
分析, 评分, signal, BUY/SELL/HOLD	Run analysis or diagnosis
选股, scan, top, ranking	Market scan (A/HK/US/FUND)
组合, portfolio, 分配	Portfolio construction
回测, backtest, 验证	Strategy backtest
因子, 动量, alpha, momentum	Alpha momentum scan
基金, fund, ETF	Fund/ETF screening
情绪, sentiment, 行情	Sentiment / breadth check
刷新, fetch, 缓存, cache	Data operations

Before you start

Refresh all data pools on first run:

bash

python scripts/run.py fetch pool

Workflows

1. Single stock analysis

Normalize code by convention: 6xxxxx/0xxxxx/3xxxxx -> A, xxxx.HK -> HK, plain ticker -> US.

bash

python scripts/run.py analyze 600519 --market A           # terminal output
python scripts/run.py analyze 600519 --market A --format json  # JSON only
python scripts/run.py analyze 600519 --market A --format md     # save MD report

Output: PE/PB/ROE/Dividend, composite factor scores, strategy signal.

2. Deep diagnosis

Comprehensive BUY/SELL/HOLD with risk assessment:

bash

python scripts/run.py diagnose 600519 --market A
python scripts/run.py diagnose 600519 --market A --output-dir ./reports

JSON structure: final_decision.signal, adjusted_score, factors, strategy, technical, sentiment, fundamentals, risks.

Present results:

• BUY -> include stop-loss and take-profit references
• SELL -> explain risk factors
• HOLD -> explain what would need to change

3. Market scan

bash

python scripts/run.py scan A --top 20                    # top 20 A-shares
python scripts/run.py scan HK --top 10 --format json
python scripts/run.py scan FUND --top 20 --output-dir ./reports

If scan returns all zeros, fall back to alpha mode:

bash

python scripts/run.py alpha A --top 10 --candidates 200

For sector-filtered scanning:

bash

python -c "from advisor.scanner import MarketScanner; MarketScanner().scan_by_sector('A', top_n=5)"

4. Alpha momentum scan

Full multi-factor ranking with thread-parallel scoring:

bash

python scripts/run.py alpha A --top 10 --candidates 200

Results include ranked list with scores, signals, F-Score, and BUY summary. Explain which factors drove top rankings (momentum + low-vol + quality ~73% combined).

5. Portfolio construction

bash

python scripts/run.py portfolio --codes 600519,000858,002475 --capital 1000000
python scripts/run.py portfolio-enhanced --capital 1000000

For custom methods (equal weight, risk parity, min variance), see references/python-api.md.

6. Backtest

bash

python scripts/run.py backtest                  # standard Alpha Momentum
python scripts/run.py backtest-enhanced         # enhanced core-satellite

Requires >= 1500 trading days cached. Report CAGR, Sharpe, MaxDD.

7. Fund/ETF screening

bash

python scripts/run.py scan FUND --top 20

For deeper programmatic access:

python

from data_engine import get_fund_pool, get_fund_nav

8. Data operations

bash

python scripts/run.py fetch pool                # full pool refresh
python scripts/run.py fetch kline 600519        # single stock K-line
python scripts/run.py fetch fundamentals 600519 # single stock fundamentals

Output guidelines

Terminal output (auto-detected):

Use emoji indicators for scannability:

text

 600519 贵州茅台
   评分 82.3/100 | 信号: BUY (F=8)
   核心驱动: 质量(88.7) + 动量(76.5)
   风险: 低
   参考止损/止盈: 1480.50 / 1980.00

Full diagnosis report format:

1. Decision signal and score
2. Top-3 driving factors
3. Strategy that triggered the signal
4. Sentiment adjustment if >5% impact
5. Risk level and key risks
6. Stop-loss and take-profit reference prices

JSON output (--format json):

All scripts accept --format {json,md,both,none}. JSON for programmatic use, MD for readable reports.

Language:

Use Chinese for A-share content unless the user writes in English. Use English for US/HK.

Gotchas

Symptom	Cause	Fix
ModuleNotFoundError: No module named 'config'	Wrong working directory	Run from project root (where scripts/ is)
Scan returns 0 results	Cache empty	python scripts/run.py fetch pool first
"Daily API limit reached"	AKShare rate limit (500/day)	Wait; use cached data
No BUY signals	Market weakness or cold cache	Run diagnose on individual stocks
import akshare fails	Not installed	pip install akshare efinance baostock
Code not found	Pool not fetched	python scripts/run.py fetch pool
Backtest fails	Insufficient data	Ensure >= 1500 trading days cached

Key principles

1. Cache first, fetch on miss — SQLite cache before AKShare API. Refresh on TTL expiry.
2. Multi-factor, multi-strategy — Weighted vote across 6 strategies from 7 factor dimensions.
3. Script-driven — Run python scripts/run.py, never reimplement logic.
4. Parallel scoring — Thread pool (8 workers) for alpha scans.
5. Graceful degradation — Cache-only mode on API limit. Partial results over failures.

Reference files

Load only when needed:

• Factor weights & scoring: references/factors.md
• Strategy weights & signals: references/strategies.md
• Sentiment adjustment: references/sentiment.md
• Python API & code: references/python-api.md
• Enhanced Momentum: references/enhanced-momentum.md
• Market sources: references/market-source-playbook.md
• AKShare docs: references/akshare_official_docs.md
• Output style: references/output-style-and-language.md
• Research: references/research-sources.md
• Risk & compliance: references/risk-and-compliance.md
• Dialogue protocol: references/serenity-dialogue-protocol.md

Output file specs

1. Path: ./reports/
2. Naming: {YYYY-MM-DD-HHMM}_{Short Title}.{json,md}
3. Format: Standard Markdown with hierarchy

Risk disclaimer

For investment reference only, not investment advice. Data sources are third-party public platforms with 10-15 minute delay. Past performance does not guarantee future returns.