檢視當前 alpha 信號品質，顯示 top picks 和投資建議。當使用者想看最佳信號、 信號排名、投資建議時使用。觸發詞: alpha信號, signal review, 信號檢視, top picks, 最佳信號, alpha review, 投資信號, 信號排名, 買什麼, 推薦
從 data/data.db 查詢原始與增強 alpha 信號，生成投資信號檢視報告。
cd "D:/VScode_project/NLP data for trading" && python -c "
import sqlite3
conn = sqlite3.connect('data/data.db')
conn.row_factory = sqlite3.Row
c = conn.cursor()
print('=' * 80)
print(' PAM Alpha 信號檢視報告')
print('=' * 80)
# --- 原始 Alpha Signals Top 10 ---
print('\n## 原始 Alpha Signals Top 10 (by signal_strength)\n')
c.execute('''
SELECT ticker, asset_name, politician_name, chamber, direction,
transaction_type, signal_strength, confidence, expected_alpha_5d,
expected_alpha_20d, sqs_score, sqs_grade, has_convergence,
convergence_bonus, politician_grade, filing_lag_days, created_at
FROM alpha_signals
ORDER BY signal_strength DESC
LIMIT 10
''')
rows = c.fetchall()
if rows:
for i, r in enumerate(rows, 1):
conv = ' [CONVERGENCE]' if r['has_convergence'] else ''
a5 = f'{r[\"expected_alpha_5d\"]:.4f}' if r['expected_alpha_5d'] else 'N/A'
a20 = f'{r[\"expected_alpha_20d\"]:.4f}' if r['expected_alpha_20d'] else 'N/A'
cb = f'+{r[\"convergence_bonus\"]:.2f}' if r['convergence_bonus'] else '+0.00'
grade = r['politician_grade'] or 'N/A'
sqs_g = r['sqs_grade'] or 'N/A'
lag = r['filing_lag_days'] if r['filing_lag_days'] is not None else '?'
print(f' #{i} {r[\"ticker\"]:6s} ({r[\"asset_name\"] or \"N/A\"})')
print(f' Direction: {r[\"direction\"]} | Type: {r[\"transaction_type\"]} | Chamber: {r[\"chamber\"]}')
print(f' Politician: {r[\"politician_name\"]} (Grade: {grade})')
print(f' Strength: {r[\"signal_strength\"]:.4f} | Confidence: {r[\"confidence\"]:.4f}')
print(f' Alpha 5d: {a5} | Alpha 20d: {a20}')
print(f' SQS: {r[\"sqs_score\"]:.1f} ({sqs_g}) | Conv Bonus: {cb}{conv}')
print(f' Filing Lag: {lag}d | Date: {r[\"created_at\"]}')
print()