Update app.py

app.py

@@ -3,49 +3,61 @@ 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
+# Fungsi untuk mengunduh data saham
+def get_stock_data(tickers, start, end):
+    data = yf.download(tickers, start=start, end=end)['Adj Close']
+    return data
 
-def get_stock_data(tickers, start, end): 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
-
-def optimize_portfolio(data): returns = data.pct_change().dropna() mean_returns = returns.mean() cov_matrix = returns.cov() num_assets = len(data.columns) num_portfolios = 10000
-
-results = np.zeros((3, num_portfolios))
-weights_record = []
-
-for i in range(num_portfolios):
+# 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)
-    weights_record.append(weights)
-    
-    portfolio_return = np.sum(weights * mean_returns)
-    portfolio_stddev = np.sqrt(np.dot(weights.T, np.dot(cov_matrix, weights)))
-    sharpe_ratio = portfolio_return / portfolio_stddev
-    
-    results[0, i] = portfolio_return
-    results[1, i] = portfolio_stddev
-    results[2, i] = sharpe_ratio
 
-max_sharpe_idx = np.argmax(results[2])
-optimal_weights = weights_record[max_sharpe_idx]
-optimal_portfolio = {data.columns[i]: optimal_weights[i] for i in range(num_assets)}
-return optimal_portfolio
+    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
 
-Streamlit UI
-
-st.title("Optimasi Portofolio dengan Model Markowitz")
-
-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("Optimasi Portofolio"): tickers_list = [ticker.strip() for ticker in tickers.split(",")] data = get_stock_data(tickers_list, start_date, end_date) optimal_portfolio = optimize_portfolio(data)
+    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
 
-st.subheader("Bobot Optimal Portofolio")
-st.write(pd.DataFrame(optimal_portfolio.items(), columns=["Saham", "Bobot"]))
+# Streamlit UI
+st.title("Analisis Portofolio Saham Model Markowitz")
 
-fig, ax = plt.subplots()
-ax.pie(optimal_portfolio.values(), labels=optimal_portfolio.keys(), autopct='%1.1f%%', startangle=140)
-ax.axis('equal')
-st.pyplot(fig)
+# 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("Analisis"):
+    tickers_list = [t.strip() for t in tickers.split(',')]
+    data = get_stock_data(tickers_list, start_date, end_date)
+    
+    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.")