From 4459164fd6a088fe81a730515e8d3543c85c9839 Mon Sep 17 00:00:00 2001
From: Ayuriel <zephyrdark@gmail.com>
Date: Mon, 10 Mar 2025 17:53:06 +0900
Subject: [PATCH] =?UTF-8?q?feat:=2013-2-1=20=EB=B2=A0=ED=83=80=20=EA=B3=84?=
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---
 example/13-2-1-calculate-beta.py | 28 ++++++++++++++++++++++++++++
 1 file changed, 28 insertions(+)
 create mode 100644 example/13-2-1-calculate-beta.py

diff --git a/example/13-2-1-calculate-beta.py b/example/13-2-1-calculate-beta.py
new file mode 100644
index 0000000..2892fbc
--- /dev/null
+++ b/example/13-2-1-calculate-beta.py
@@ -0,0 +1,28 @@
+import yfinance as yf
+import pandas as pd
+import statsmodels.api as sm
+
+KOSPI_CODE = '^KS11'
+KIIUM = '039490.KS'
+# KOSPI 코드(^KS11), 전통적인 고베타주인 증권주 중 키움증권(039490.KS)
+tickers = [KOSPI_CODE, KIIUM]
+
+all_data = {}
+for ticker in tickers:
+    all_data[ticker] = yf.download(ticker, start="2020-01-01", end="2024-12-31")
+
+# print(all_data)
+# for tic, data in all_data.items():
+#     print(f"{tic}: {type(data)} -> {type(data['Close'])}")
+#     print(data['Close'])
+
+# 종가(Close)에 해당하는 열만 선택해서 데이터프레임으로 가공
+prices = pd.DataFrame({tic: data['Close'].squeeze() for tic, data in all_data.items()})
+# 수익률 계산(pct_change), NA 데이터 삭제(dropna)
+ret = prices.pct_change().dropna()
+
+ret['intercept'] = 1
+reg = sm.OLS(ret[[KIIUM]], ret[[KOSPI_CODE, 'intercept']]).fit()
+
+print(reg.summary())
+print(reg.params)
\ No newline at end of file