import sys
import os
from collections import defaultdict, Counter
# プロジェクトルートをPythonパスに追加
project_root = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
sys.path.insert(0, project_root)
def analyze_volume_surge_stocks():
"""出来高急増銘柄の詳細分析"""
try:
from src.finviz_client.screener import FinvizScreener
screener = FinvizScreener()
print("=== 出来高急増銘柄の詳細分析 ===")
# スクリーニング実行
results = screener.volume_surge_screener()
print(f"総銘柄数: {len(results)}")
# セクター別分析
sector_analysis = defaultdict(list)
industry_analysis = defaultdict(list)
# 価格変動率別分析
price_change_ranges = {
"10%以上": [],
"5-10%": [],
"2-5%": []
}
# 時価総額別分析
market_cap_ranges = {
"大型 (50B+)": [],
"中型 (2B-50B)": [],
"小型 (300M-2B)": []
}
# 上位銘柄詳細
top_performers = []
for i, stock in enumerate(results[:20]): # 上位20銘柄を詳細分析
# セクター情報
sector = getattr(stock, 'sector', 'Unknown')
industry = getattr(stock, 'industry', 'Unknown')
# 基本情報
ticker = stock.ticker
price = getattr(stock, 'price', 0)
price_change = getattr(stock, 'price_change', 0)
volume = getattr(stock, 'volume', 0)
market_cap = getattr(stock, 'market_cap', 0)
# データ蓄積
sector_analysis[sector].append({
'ticker': ticker,
'price_change': price_change,
'volume': volume
})
industry_analysis[industry].append(ticker)
# 価格変動率分類
if price_change >= 10:
price_change_ranges["10%以上"].append(ticker)
elif price_change >= 5:
price_change_ranges["5-10%"].append(ticker)
else:
price_change_ranges["2-5%"].append(ticker)
# 時価総額分類（概算）
if market_cap and market_cap > 50000: # 50B+
market_cap_ranges["大型 (50B+)"].append(ticker)
elif market_cap and market_cap > 2000: # 2B-50B
market_cap_ranges["中型 (2B-50B)"].append(ticker)
else:
market_cap_ranges["小型 (300M-2B)"].append(ticker)
# 上位パフォーマー
if i < 10:
top_performers.append({
'rank': i + 1,
'ticker': ticker,
'price': price,
'price_change': price_change,
'volume': volume,
'sector': sector
})
# 結果出力
print("\n=== TOP 10 パフォーマー ===")
for performer in top_performers:
print(f"{performer['rank']:2d}. {performer['ticker']:6s} | "
f"{performer['price_change']:+6.2f}% | "
f"${performer['price']:7.2f} | "
f"{performer['volume']/1000000:6.1f}M vol | "
f"{performer['sector']}")
print("\n=== セクター別分布 ===")
sector_summary = {}
for sector, stocks in sector_analysis.items():
count = len(stocks)
avg_change = sum(s['price_change'] for s in stocks) / count if count > 0 else 0
sector_summary[sector] = {'count': count, 'avg_change': avg_change}
print(f"{sector:25s}: {count:3d}銘柄 (平均変動: {avg_change:+5.2f}%)")
print("\n=== 価格変動率分布 ===")
for range_name, tickers in price_change_ranges.items():
print(f"{range_name:10s}: {len(tickers):3d}銘柄 ({len(tickers)/len(results)*100:4.1f}%)")
if tickers:
print(f" 代表銘柄: {', '.join(tickers[:5])}")
print("\n=== 時価総額別分布 ===")
for cap_range, tickers in market_cap_ranges.items():
print(f"{cap_range:15s}: {len(tickers):3d}銘柄")
# 分析結果を辞書で返す
return {
'total_stocks': len(results),
'top_performers': top_performers,
'sector_summary': sector_summary,
'price_change_distribution': {k: len(v) for k, v in price_change_ranges.items()},
'market_cap_distribution': {k: len(v) for k, v in market_cap_ranges.items()},
'top_sectors': sorted(sector_summary.items(), key=lambda x: x[1]['count'], reverse=True)[:5]
}
except Exception as e:
print(f"エラーが発生しました: {e}")
import traceback
traceback.print_exc()
return None
if __name__ == "__main__":
analyze_volume_surge_stocks()
