Ready for first real test

state/sandbox/tmp6or4tzss/script.py

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+import yfinance as yf
+import pandas as pd
+import numpy as np
+import matplotlib.pyplot as plt
+
+# Tickers
+main = 'MRVL'
+peers = ['AVGO','AMD','NVDA']
+lookback = '180d'
+
+# Download data
+df_main = yf.download(main, period=lookback, progress=False)
+df_peers = {t: yf.download(t, period=lookback, progress=False) for t in peers}
+
+# Technical indicators for main
+for ma in [20,50,200]:
+    df_main[f'SMA{ma}'] = df_main['Close'].rolling(ma).mean()
+
+# Return and volatility
+df_main['Ret'] = df_main['Close'].pct_change()
+df_main['Vol20'] = df_main['Ret'].rolling(20).std() * np.sqrt(252)
+
+# Correlation with peers
+corr_df = pd.DataFrame(index=df_main.index)
+for t in peers:
+    corr_df[f'{t}_corr'] = df_main['Ret'].rolling(60).corr(df_peers[t]['Close'].pct_change())
+
+# Plot price + MA
+plt.figure(figsize=(12,6))
+plt.plot(df_main['Close'], label='Close')
+plt.plot(df_main['SMA20'], label='SMA20')
+plt.plot(df_main['SMA50'], label='SMA50')
+plt.plot(df_main['SMA200'], label='SMA200')
+plt.title(f'{main} price with moving averages')
+plt.legend()
+plt.tight_layout()
+plt.savefig('mrvl_ma.png')
+
+# Plot volatility
+plt.figure(figsize=(12,4))
+plt.plot(df_main['Vol20'], label='20‑Day Vol (annualized)')
+plt.title(f'{main} 20‑Day volatility')
+plt.legend()
+plt.tight_layout()
+plt.savefig('mrvl_vol.png')
+
+# Plot correlation heatmap
+plt.figure(figsize=(8,6))
+corr_vals = corr_df.mean().values
+plt.bar(peers, corr_vals)
+plt.title('Average 60‑day correlation of MRVL with peers')
+plt.ylabel('Correlation')
+plt.tight_layout()
+plt.savefig('mrvl_corr.png')
+
+print('Charts generated: mrvl_ma.png, mrvl_vol.png, mrvl_corr.png')