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%matplotlib inline

Exposure Triangle

Although triangles have both origin and development attributes, it is often convenient to create premium or exposure vectors that can work with loss triangles. The Triangle class treats the development parameter as optional. This example instantiates a 'premium' triangle as a single vector.



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import chainladder as cl
import pandas as pd
import seaborn as sns
sns.set_style('whitegrid')

import chainladder as cl

# Raw premium data in pandas
premium_df = pd.DataFrame(
    {'AccYear':[item for item in range(1977, 1988)],
     'premium': [3000000]*11})

# Create a premium 'triangle' with no development
premium = cl.Triangle(premium_df, origin='AccYear', columns='premium')

# Create some loss triangle
loss = cl.load_dataset('abc')
ultimate = cl.Chainladder().fit(loss).ultimate_

# Plot
(ultimate / premium).plot(
    kind='area', title='Loss Ratio by Accident Year',
    alpha=0.7, color='darkgreen', legend=False);