Stock Price Volatility by Sector

import matplotlib.pyplot as plt
import numpy as np
from scipy import stats

np.random.seed(111)

sectors = ['Tech', 'Finance', 'Healthcare', 'Energy', 'Consumer', 'Industrial']
colors = ['#27D3F5', '#6CF527', '#F5276C', '#F5B027', '#4927F5', '#F54927']

data = {
    'Tech': np.random.normal(0, 2.5, 600),
    'Finance': np.random.normal(0, 1.8, 600),
    'Healthcare': np.random.normal(0, 1.5, 600),
    'Energy': np.random.normal(0, 3.0, 600),
    'Consumer': np.random.normal(0, 1.2, 600),
    'Industrial': np.random.normal(0, 1.6, 600)
}

fig, ax = plt.subplots(figsize=(12, 8), facecolor='#0a0a0f')
ax.set_facecolor('#0a0a0f')

overlap = 1.7
x_range = np.linspace(-10, 10, 300)

for i, (sector, returns) in enumerate(data.items()):
    kde = stats.gaussian_kde(returns, bw_method=0.25)
    y = kde(x_range) * 4
    baseline = i * overlap
    
    # Intense glow
    for w, a in [(14, 0.08), (10, 0.12), (6, 0.2), (3, 0.4)]:
        ax.plot(x_range, y + baseline, color=colors[i], linewidth=w, alpha=a)
    
    ax.fill_between(x_range, baseline, y + baseline, alpha=0.5, color=colors[i])
    ax.plot(x_range, y + baseline, color='white', linewidth=1.2, alpha=0.9)
    
    ax.text(-11.5, baseline + 0.15, sector, fontsize=11, color=colors[i],
            ha='right', va='bottom', fontweight='600')

ax.axvline(x=0, color='#333333', linewidth=1, linestyle='--', alpha=0.5)
ax.set_xlim(-14, 10)
ax.set_ylim(-0.3, len(sectors) * overlap + 2)
ax.set_xlabel('Daily Return (%)', fontsize=12, color='#666666', fontweight='500')
ax.set_title('Stock Price Volatility by Sector', fontsize=16, color='white', fontweight='bold', pad=20)

ax.tick_params(axis='x', colors='#555555', labelsize=10)
ax.tick_params(axis='y', left=False, labelleft=False)
for spine in ax.spines.values():
    spine.set_visible(False)

plt.tight_layout()
plt.show()