Ready for first real test

state/sandbox/tmpcaqxszjc/script.py

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+import yfinance as yf
+import pandas as pd
+import numpy as np
+import matplotlib.pyplot as plt
+
+stock='NVDA'
+sector='SMH'
+lookback='365d'
+
+s= yf.download(stock, period=lookback, progress=False)
+se= yf.download(sector, period=lookback, progress=False)
+
+s['SMA20']=s['Close'].rolling(20).mean()
+s['SMA50']=s['Close'].rolling(50).mean()
+s['SMA200']=s['Close'].rolling(200).mean()
+s['Ret']=s['Close'].pct_change()
+s['Vol20']=s['Ret'].rolling(20).std()*np.sqrt(252)
+
+merged=pd.merge(s[['Close','Ret']], se[['Close']], left_index=True, right_index=True, suffixes=('','_etf'))
+merged['Ret_etf']=merged['Close_etf'].pct_change()
+merged['Corr']=merged['Ret'].rolling(60).corr(merged['Ret_etf'])
+
+# plots
+plt.figure(figsize=(12,6))
+plt.plot(s['Close'],label='Close')
+plt.plot(s['SMA20'],label='SMA20')
+plt.plot(s['SMA50'],label='SMA50')
+plt.plot(s['SMA200'],label='SMA200')
+plt.legend()
+plt.title('NVDA price & moving averages')
+plt.savefig('nvda_ma.png')
+
+plt.figure(figsize=(12,4))
+plt.plot(s['Vol20'],label='20‑Day Vol (annualized)')
+plt.legend()
+plt.title('NVDA volatility')
+plt.savefig('nvda_vol.png')
+
+plt.figure(figsize=(12,4))
+plt.plot(merged['Corr'],label='60‑Day Correlation with SMH')
+plt.legend()
+plt.title('NVDA vs SMH correlation')
+plt.savefig('nvda_corr.png')
+
+print('Done')