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solvency2: cashflows#
Net liability cashflows by SCR shock scenarios for selected policies
See also
The
solvency2
library
import modelx as mx
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
sns.set_theme(style="darkgrid")
model = mx.read_model("model")
def draw(polid, t0):
fig, ax = plt.subplots()
fig.suptitle('Net Cashflows')
title = 'Policy ID: ' + str(polid) + ', Shock at ' + str(t0)
data = {}
for risk, shock in (('base', None),
('mort', None),
('longev', None),
('lapse', 'up'),
('lapse', 'down'),
('lapse', 'mass'),
('exps', None)):
proj = model.SCR_life[t0, polid].Projection(risk, shock)
last_t = proj.last_t()
label = risk + ('(' + shock + ')' if shock else '')
data[label] = [proj.NetInsurCF[t] for t in range(t0, last_t)]
return pd.DataFrame(
data, index=range(t0, last_t)).plot(
ax=ax, kind='line', title=title)
for polid, t0 in [(41, 5), (171, 5)]:
draw(polid, t0)
Total running time of the script: ( 0 minutes 1.011 seconds)