Investment Portfolio Analysis

import matplotlib.pyplot as plt
import numpy as np
from matplotlib.colors import LinearSegmentedColormap

np.random.seed(42)
n_assets = 8000

# Risk (volatility %) and return %
risk = np.random.lognormal(2, 0.6, n_assets)
risk = np.clip(risk, 2, 50)

# Return correlates with risk (with noise)
expected_return = 2 + 0.3 * risk + np.random.normal(0, 3, n_assets)
expected_return = np.clip(expected_return, -10, 40)

fig, ax = plt.subplots(figsize=(10, 8), facecolor='#ffffff')
ax.set_facecolor('#f5f3ff')

colors = ['#f5f3ff', '#ede9fe', '#ddd6fe', '#c4b5fd', '#a78bfa', 
          '#8b5cf6', '#7c3aed', '#6d28d9', '#5b21b6', '#4c1d95']
cmap = LinearSegmentedColormap.from_list('violet', colors, N=256)

hb = ax.hexbin(risk, expected_return, gridsize=35, cmap=cmap, mincnt=1,
               edgecolors='white', linewidths=0.3)

# Efficient frontier approximation
risk_line = np.linspace(5, 40, 100)
frontier = 2 + 0.5 * risk_line - 0.002 * risk_line ** 2 + 5
ax.plot(risk_line, frontier, '-', color='#6d28d9', linewidth=3, alpha=0.9, label='Efficient Frontier')

# Risk-free rate
ax.axhline(y=4, color='#22c55e', linestyle='--', alpha=0.7, linewidth=2, label='Risk-Free Rate')

# Capital Market Line
cml_x = np.linspace(0, 40, 100)
cml_y = 4 + 0.5 * cml_x
ax.plot(cml_x, cml_y, ':', color='#0ea5e9', linewidth=2, alpha=0.8, label='Capital Market Line')

cbar = plt.colorbar(hb, ax=ax, pad=0.02, shrink=0.85)
cbar.set_label('Asset Count', fontsize=11, color='#4c1d95', labelpad=10)
cbar.ax.yaxis.set_tick_params(color='#5b21b6')
cbar.outline.set_edgecolor('#ddd6fe')
plt.setp(plt.getp(cbar.ax.axes, 'yticklabels'), color='#5b21b6', fontsize=9)

ax.set_xlabel('Risk (Volatility %)', fontsize=12, color='#4c1d95', fontweight='600', labelpad=12)
ax.set_ylabel('Expected Return (%)', fontsize=12, color='#4c1d95', fontweight='600', labelpad=12)
ax.set_title('Portfolio Risk-Return Analysis', fontsize=16, color='#2e1065', fontweight='700', pad=20)

ax.tick_params(colors='#5b21b6', labelsize=10, length=0)
ax.spines['top'].set_visible(False)
ax.spines['right'].set_visible(False)
ax.spines['left'].set_color('#ddd6fe')
ax.spines['bottom'].set_color('#ddd6fe')

ax.legend(loc='lower right', fontsize=9, frameon=True, facecolor='white', 
          edgecolor='#ddd6fe', labelcolor='#4c1d95')
ax.grid(True, alpha=0.3, color='#ddd6fe', linestyle='-', linewidth=0.5)
ax.set_axisbelow(True)
ax.set_xlim(0, 50)
ax.set_ylim(-10, 40)

plt.tight_layout()
plt.show()