Create app.py

app.py

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+import streamlit as st import pandas as pd import numpy as np import yfinance as yf import matplotlib.pyplot as plt
+
+Fungsi untuk mengunduh data saham
+
+def get_stock_data(tickers, start, end): data = yf.download(tickers, start=start, end=end)['Adj Close'] return data
+
+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):
+    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
+
+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)
+
+st.subheader("Bobot Optimal Portofolio")
+st.write(pd.DataFrame(optimal_portfolio.items(), columns=["Saham", "Bobot"]))
+
+fig, ax = plt.subplots()
+ax.pie(optimal_portfolio.values(), labels=optimal_portfolio.keys(), autopct='%1.1f%%', startangle=140)
+ax.axis('equal')
+st.pyplot(fig)
+