Update app.py

app.py

@@ -1,32 +1,63 @@
 import streamlit as st
-import yfinance as yf
 import pandas as pd
+import numpy as np
+import yfinance as yf
 import matplotlib.pyplot as plt
+from scipy.optimize import minimize
 
 # Fungsi untuk mengunduh data saham
 def get_stock_data(tickers, start, end):
-    data = yf.download(tickers, start=start, end=end)
-    if data.empty:
-        st.error("Data saham tidak ditemukan. Periksa ticker atau tanggal.")
-        return None
-    elif 'Adj Close' in data.columns:
-        return data['Adj Close']
-    elif 'Close' in data.columns:
-        return data['Close']
-    else:
-        st.error("Kolom 'Adj Close' atau 'Close' tidak ditemukan.")
-        return None
+    data = yf.download(tickers, start=start, end=end)['Adj Close']
+    return data
+
+# Fungsi untuk menghitung return harian
+def calculate_daily_returns(data):
+    return data.pct_change().dropna()
+
+# Fungsi untuk menghitung portofolio optimal dengan Model Markowitz
+def optimize_portfolio(returns):
+    num_assets = len(returns.columns)
+    weights = np.random.random(num_assets)
+    weights /= np.sum(weights)
+
+    def portfolio_performance(weights):
+        port_return = np.sum(returns.mean() * weights) * 252
+        port_volatility = np.sqrt(np.dot(weights.T, np.dot(returns.cov() * 252, weights)))
+        return port_volatility
+
+    constraints = ({'type': 'eq', 'fun': lambda x: np.sum(x) - 1})
+    bounds = tuple((0, 1) for _ in range(num_assets))
+    result = minimize(portfolio_performance, weights, method='SLSQP', bounds=bounds, constraints=constraints)
+    
+    return result.x
 
 # Streamlit UI
-st.title("Analisis Portofolio Saham")
-tickers_list = st.text_input("Masukkan ticker saham (contoh: BBCA.JK, TLKM.JK)", "BBCA.JK, TLKM.JK").split(",")
+st.title("Analisis Portofolio Saham Model Markowitz")
+
+# Input pengguna untuk daftar saham
+tickers = st.text_input("Masukkan kode saham (pisahkan dengan koma)", "BBCA.JK,TLKM.JK,UNVR.JK")
 start_date = st.date_input("Pilih tanggal mulai", pd.to_datetime("2020-01-01"))
 end_date = st.date_input("Pilih tanggal akhir", pd.to_datetime("2020-12-31"))
 
-if st.button("Dapatkan Data"):
+if st.button("Analisis"):
+    tickers_list = [t.strip() for t in tickers.split(',')]
     data = get_stock_data(tickers_list, start_date, end_date)
-    if data is not None:
-        st.write("Data Saham:")
-        st.write(data.tail())
-        # Plot harga saham
-        st.line_chart(data)
+    
+    if not data.empty:
+        st.write("Data Harga Saham")
+        st.line_chart(data)
+
+        returns = calculate_daily_returns(data)
+        optimal_weights = optimize_portfolio(returns)
+
+        st.write("Bobot Optimal Portofolio:")
+        for ticker, weight in zip(tickers_list, optimal_weights):
+            st.write(f"{ticker}: {weight:.2%}")
+
+        # Visualisasi Portofolio
+        fig, ax = plt.subplots()
+        ax.pie(optimal_weights, labels=tickers_list, autopct='%1.1f%%', startangle=90)
+        ax.axis("equal")
+        st.pyplot(fig)
+    else:
+        st.error("Gagal mengambil data saham. Pastikan kode saham benar.")