diff --git a/example/13-quality-portfolio.py b/example/13-quality-portfolio.py
new file mode 100644
index 0000000..4f4b168
--- /dev/null
+++ b/example/13-quality-portfolio.py
@@ -0,0 +1,60 @@
+import pandas as pd
+import numpy as np
+import matplotlib.pyplot as plt
+import seaborn as sns
+import quantcommon
+
+# 퀄리티(우량주) 포트폴리오. 영업수익성이 높은 주식
+engine = quantcommon.QuantCommon().create_engine()
+
+ticker_list = pd.read_sql("""
+select * from kor_ticker
+where 기준일 = (select max(기준일) from kor_ticker) 
+and 종목구분 = '보통주';
+""", con=engine)
+
+fs_list = pd.read_sql("""
+select * from kor_fs
+where 계정 in ('당기순이익', '매출총이익', '영업활동으로인한현금흐름', '자산', '자본')
+and 공시구분 = 'q';
+""", con=engine)
+
+engine.dispose()
+
+fs_list = fs_list.sort_values(['종목코드', '계정', '기준일'])
+fs_list['ttm'] = fs_list.groupby(['종목코드', '계정'], as_index=False)['값'].rolling(
+    window=4, min_periods=4).sum()['값']
+fs_list_clean = fs_list.copy()
+fs_list_clean['ttm'] = np.where(fs_list_clean['계정'].isin(['자산', '자본']),
+                                fs_list_clean['ttm'] / 4, fs_list_clean['ttm'])
+fs_list_clean = fs_list_clean.groupby(['종목코드', '계정']).tail(1)
+
+fs_list_pivot = fs_list_clean.pivot(index='종목코드', columns='계정', values='ttm')
+fs_list_pivot['ROE'] = fs_list_pivot['당기순이익'] / fs_list_pivot['자본']
+fs_list_pivot['GPA'] = fs_list_pivot['매출총이익'] / fs_list_pivot['자산']
+fs_list_pivot['CFO'] = fs_list_pivot['영업활동으로인한현금흐름'] / fs_list_pivot['자산']
+
+quality_list = ticker_list[['종목코드', '종목명']].merge(fs_list_pivot,
+                                                  how='left',
+                                                  on='종목코드')
+# print(quality_list.round(4).head())
+
+quality_list_copy = quality_list[['ROE', 'GPA', 'CFO']].copy()
+quality_rank = quality_list_copy.rank(ascending=False, axis=0)
+
+mask = np.triu(quality_rank.corr())
+fig, ax = plt.subplots(figsize=(10, 6))
+sns.heatmap(quality_rank.corr(),
+            annot=True,
+            mask=mask,
+            annot_kws={"size": 16},
+            vmin=0,
+            vmax=1,
+            center=0.5,
+            cmap='coolwarm',
+            square=True)
+ax.invert_yaxis()
+
+quality_sum = quality_rank.sum(axis=1, skipna=False).rank()
+print(quality_list.loc[quality_sum <= 20,
+                 ['종목코드', '종목명', 'ROE', 'GPA', 'CFO']].round(4))
\ No newline at end of file