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feat: Enhance Monte Carlo simulation plot with improved visualization and styling

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Bobby (aider) 2025-02-17 15:13:13 -08:00
parent 9b3b1f27ac
commit 3eb6b7b62b
1 changed files with 66 additions and 14 deletions
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80
src/pages/analysis/monte_carlo_page.py
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@ -77,39 +77,91 @@ def create_simulation_plot(paths: np.ndarray, dates: pd.DatetimeIndex,
row_heights=[0.7, 0.3]
)
# Plot all simulation paths with low opacity
for i in range(paths.shape[1]):
fig.add_trace(
go.Scatter(
x=dates,
y=paths[:, i],
name=f'Simulation {i+1}',
line=dict(color='orange', width=0.1, opacity=0.1),
showlegend=False
),
row=1, col=1
)
# Plot confidence intervals
percentiles = np.percentile(paths, [5, 25, 50, 75, 95], axis=1)
# Add price paths
# Add upper bound (blue)
fig.add_trace(
go.Scatter(x=dates, y=percentiles[2], name='Median Path',
line=dict(color='blue', width=2)), row=1, col=1)
go.Scatter(
x=dates,
y=percentiles[4],
name='Upper 95% Confidence',
line=dict(color='blue', width=2)
),
row=1, col=1
)
# Add confidence intervals
# Add lower bound (red)
fig.add_trace(
go.Scatter(x=dates, y=percentiles[4], name='95% Confidence',
line=dict(color='rgba(0,100,80,0.2)', width=0)), row=1, col=1)
go.Scatter(
x=dates,
y=percentiles[0],
name='Lower 95% Confidence',
line=dict(color='red', width=2)
),
row=1, col=1
)
# Add median path
fig.add_trace(
go.Scatter(x=dates, y=percentiles[0], name='95% Confidence',
fill='tonexty', line=dict(color='rgba(0,100,80,0.2)', width=0)),
row=1, col=1)
go.Scatter(
x=dates,
y=percentiles[2],
name='Median Path',
line=dict(color='white', width=2)
),
row=1, col=1
)
# Add starting price line
fig.add_trace(
go.Scatter(x=dates, y=[last_price] * len(dates), name='Current Price',
line=dict(color='red', dash='dash')), row=1, col=1)
go.Scatter(
x=dates,
y=[last_price] * len(dates),
name='Current Price',
line=dict(color='green', dash='dash', width=2)
),
row=1, col=1
)
# Add histogram of final prices
fig.add_trace(
go.Histogram(x=paths[-1], name='Final Price Distribution',
nbinsx=50), row=2, col=1)
go.Histogram(
x=paths[-1],
name='Final Price Distribution',
nbinsx=50,
marker_color='orange'
),
row=2, col=1
)
# Update layout
fig.update_layout(
title=f'Monte Carlo Simulation - {ticker}',
showlegend=True,
height=800
height=800,
template='plotly_dark', # Dark theme for better visibility
plot_bgcolor='rgba(0,0,0,0)', # Transparent background
paper_bgcolor='rgba(0,0,0,0)'
)
# Update axes
fig.update_xaxes(showgrid=True, gridwidth=1, gridcolor='rgba(128,128,128,0.2)')
fig.update_yaxes(showgrid=True, gridwidth=1, gridcolor='rgba(128,128,128,0.2)')
return fig
def monte_carlo_page():