Stock Returns Distribution by Quarter

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

np.random.seed(42)
quarters = ['Q1 2022', 'Q2 2022', 'Q3 2022', 'Q4 2022', 'Q1 2023', 'Q2 2023', 'Q3 2023', 'Q4 2023']
volatilities = [0.02, 0.035, 0.04, 0.03, 0.025, 0.02, 0.03, 0.025]
means = [0.01, -0.02, -0.01, 0.02, 0.015, 0.02, 0.01, 0.025]

fig, ax = plt.subplots(figsize=(12, 10), facecolor='#0a0a0f')
ax.set_facecolor('#0a0a0f')

colors = ['#F5276C', '#F54927', '#F5B027', '#6CF527', '#27F5B0', '#27D3F5', '#276CF5', '#4927F5']

x = np.linspace(-0.15, 0.15, 200)
overlap = 1.8

for i, (quarter, vol, mean, color) in enumerate(zip(quarters, volatilities, means, colors)):
    data = np.random.normal(mean, vol, 1000)
    kde = stats.gaussian_kde(data)
    y = kde(x) * 0.08
    y_offset = i * overlap
    
    ax.fill_between(x, y_offset, y + y_offset, alpha=0.85, color=color, edgecolor='white', linewidth=0.8)
    ax.axvline(0, color='#333333', linewidth=0.5, linestyle='--', alpha=0.5)
    ax.text(-0.17, y_offset + 0.3, quarter, fontsize=9, color='white', va='center', ha='right', fontweight='500')

ax.set_xlim(-0.20, 0.15)
ax.set_ylim(-0.5, len(quarters) * overlap + 2)
ax.set_xlabel('Daily Returns', color='white', fontsize=11, fontweight='500')
ax.set_title('Stock Returns Distribution by Quarter', color='white', fontsize=14, fontweight='bold', pad=20)
ax.tick_params(colors='#888888', labelsize=9)
ax.set_yticks([])
for spine in ax.spines.values():
    spine.set_visible(False)
ax.spines['bottom'].set_visible(True)
ax.spines['bottom'].set_color('#333333')

plt.tight_layout()
plt.show()