Simulating stock market returns using Monte Carlo › 1. Setting Up The Environment

Michael BrenndoerferJuly 19, 20251 min read
Simulating stock market returns using Monte Carlo › 1. Setting Up The EnvironmentOne section · Sections in this article2 / 8 ↓
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First, let's import the essential libraries we'll need for our simulation and visualization:

In[1]:
Code
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt

# Modern, clean styling
plt.style.use('default')
plt.rcParams.update({
    'figure.facecolor': 'white',
    'axes.facecolor': 'white',
    'axes.edgecolor': '#CCCCCC',
    'axes.linewidth': 0.8,
    'axes.spines.left': True,
    'axes.spines.bottom': True,
    'axes.spines.top': False,
    'axes.spines.right': False,
    'xtick.bottom': True,
    'xtick.top': False,
    'ytick.left': True,
    'ytick.right': False,
    'axes.grid': True,
    'grid.color': '#E5E5E5',
    'grid.linewidth': 0.5,
    'font.size': 11,
    'axes.titlesize': 14,
    'axes.labelsize': 12,
    'figure.dpi': 100
})