def qx12_fd_m(self):
values = ['']
for step in range(self.step_size, self.step_until, self.step_size):
values.append(
look_for_in_df(self.df, 'qx_m', step) +
look_for_in_df(self.df, 'qx2_m', step) -
look_for_in_df(self.df, 'qx_m', step) *
look_for_in_df(self.df, 'qx2_m', step))
self.df['qx12_fd_m'] = values
def index_infl_m(self):
values = [1]
result = 1
for step in range(self.step_size, self.step_until, self.step_size):
result *= (1 + look_for_in_df(self.df, 'forw_infl_m', step))
values.append(result)
self.df['index_infl_m'] = values
def part_percent_m(self):
values = ['']
for step in range(self.step_size, self.step_until, self.step_size):
values.append(
1 -
pow(1 - look_for_in_df(self.df, 'part_percent', step), 1 / 12))
self.df['part_percent_m'] = values
def index_infl_m_ren_exp(self):
values = [1]
result = 1
for step in range(self.step_size, self.step_until, self.step_size):
result *= (1 +
look_for_in_df(self.df, 'forw_infl_m_ren_exp', step))
values.append(result)
self.df = self.df.assign(index_infl_m_ren_exp=values)
def disc_factor_m(self):
values = [1]
last_value = values[0]
for step in range(self.step_size, self.step_until, self.step_size):
values.append(last_value /
(1 + look_for_in_df(self.df, 'spot_rate_m', step)))
last_value = values[step]
self.df['disc_factor_m'] = values
def look_for(self, category, line=None, index=None, label=None):
"""
searching input tables
:param category: column names, text
:param line: number begins with 1 for non-indexed rows
:param index: number begins with 0 for non-indexed rows
:param label: text for indexed rows
:return: the value for a given category and index/line/label
"""
result = "Not found"
if line:
result = look_for_in_df(self.df, category, line - 1)
elif index or index == 0:
result = look_for_in_df(self.df, category, index)
elif label:
result = look_for_in_df(self.df, category, label)
return result
def paidup_percent(self, policy_number, persistency):
values = ['']
for step in range(self.step_size, self.step_until, self.step_size):
values.append(
persistency.look_for(
str(
math.floor(
look_for_in_df(self.df, 'month', step - 1) / 12)),
label=(self.product_assumptions.look_for(
self.lps_ass_key,
label=self.policies.look_for(
'product', line=policy_number)), 'PUP')) / 100)
self.df['paidup_percent'] = values
def surr_value(self, policy_number, surrpenalties, fund):
if self.product_features.look_for(
'surr value (y/n)',
label=self.policies.look_for('product',
line=policy_number)) == 0:
pass
else:
values = []
for step in range(self.step_size - 1, self.step_until,
self.step_size):
values.append(1 - surrpenalties.look_for(
str(math.floor(
look_for_in_df(self.df, 'month', step) / 12)),
label=self.policies.look_for('product',
line=policy_number),
) / 100 * (fund.df['capital_fund_value'][step] +
fund.df['accumulation_account'][step]))
self.df['surr_percent'] = values
def count_live(self, policy_number):
count_live = [1.0]
last_count_live = count_live[0]
count_death = ['']
count_surrender = ['']
count_paidup = ['']
count_critical_illness = ['']
count_maturity = ['']
for step in range(self.step_size, self.step_until, self.step_size):
if self.product_features.look_for('joint life (y/n)',
label=self.policies.look_for(
'product',
line=policy_number)) == 1:
count_death.append(
last_count_live *
(1 - look_for_in_df(self.df, 'surr_percent_m', step) *
self.surrender_timing) *
(1 - look_for_in_df(self.df, 'paidup_percent_m', step) *
self.surrender_timing) *
look_for_in_df(self.df, 'qx12_fd_m', step))
count_surrender.append(
last_count_live *
(1 - look_for_in_df(self.df, 'qx12_fd_m', step) *
self.surrender_timing) *
(1 - look_for_in_df(self.df, 'paidup_percent_m', step) *
self.surrender_timing) *
look_for_in_df(self.df, 'surr_percent_m', step))
elif self.product_features.look_for('joint life (y/n)',
label=self.policies.look_for(
'product',
line=policy_number)) == 2:
count_death.append(
last_count_live *
(1 - look_for_in_df(self.df, 'surr_percent_m', step) *
self.surrender_timing) *
(1 - look_for_in_df(self.df, 'paidup_percent_m', step) *
self.surrender_timing) *
look_for_in_df(self.df, 'qx12_sd_m', step))
count_surrender.append(
last_count_live *
(1 - look_for_in_df(self.df, 'qx12_sd_m', step) *
self.surrender_timing) *
(1 - look_for_in_df(self.df, 'paidup_percent_m', step) *
self.surrender_timing) *
look_for_in_df(self.df, 'surr_percent_m', step))
else:
count_death.append(
last_count_live *
(1 - look_for_in_df(self.df, 'surr_percent_m', step) *
self.surrender_timing) *
(1 - look_for_in_df(self.df, 'paidup_percent_m', step) *
self.surrender_timing) *
look_for_in_df(self.df, 'qx_m', step))
count_surrender.append(
last_count_live *
(1 - look_for_in_df(self.df, 'qx_m', step) *
self.surrender_timing) *
(1 - look_for_in_df(self.df, 'paidup_percent_m', step) *
self.surrender_timing) *
look_for_in_df(self.df, 'surr_percent_m', step))
count_paidup.append(
last_count_live *
(1 - look_for_in_df(self.df, 'surr_percent_m', step) / 2) *
(1 - look_for_in_df(self.df, 'qx_m', step) / 2) *
look_for_in_df(self.df, 'paidup_percent_m', step))
if self.product_features.look_for('critical illness (y/n)',
label=self.policies.look_for(
'product',
line=policy_number)) > 0:
count_critical_illness.append(
last_count_live *
(1 - look_for_in_df(self.df, 'surr_percent_m', step) / 2) *
(1 - look_for_in_df(self.df, 'qx_m', step) / 2) *
(1 - look_for_in_df(self.df, 'paidup_percent_m', step) / 2)
* look_for_in_df(self.df, 'qx_ci_m', step))
elif self.product_features.look_for('critical illness (y/n)',
label=self.policies.look_for(
'product',
line=policy_number)) == 0:
pass
if self.month == self.policies.look_for('pol_term_y',
line=policy_number) * 12:
count_maturity.append(count_live[step])
else:
pass
count_live_value = last_count_live
count_live_value -= count_surrender[step]
count_live_value -= count_death[step]
if self.product_features.look_for('critical illness (y/n)',
label=self.policies.look_for(
'product',
line=policy_number)) > 0:
count_live_value -= count_critical_illness[step]
if self.month == self.policies.look_for('pol_term_y',
line=policy_number) * 12:
count_live_value -= count_maturity[step]
count_live_value -= count_paidup[step]
count_live.append(count_live_value)
last_count_live = count_live[step]
self.df['count_surrender'] = count_surrender
self.df['count_death'] = count_death
if self.product_features.look_for(
'critical illness (y/n)',
label=self.policies.look_for('product',
line=policy_number)) > 0:
self.df['count_critical_illness'] = count_critical_illness
if self.month == self.policies.look_for('pol_term_y',
line=policy_number) * 12:
self.df['count_maturity'] = count_maturity
self.df['count_paidup'] = count_paidup
self.df['count_live'] = count_live
def qx12_sd_m(self):
step_for_calc = 11
values = ['']
previous_calc = look_for_in_df(self.df, 'pm_x', 0) + look_for_in_df(self.df, 'pm2_x', 0) \
- look_for_in_df(self.df, 'pm_x', 0) * look_for_in_df(self.df, 'pm2_x', 0)
blockPrint()
for step in range(self.step_size, self.step_until, self.step_size):
try:
values.append(1 - (
(look_for_in_df(self.df, 'pm_x', step + step_for_calc) +
look_for_in_df(self.df, 'pm2_x', step + step_for_calc) -
look_for_in_df(self.df, 'pm_x', step + step_for_calc) *
look_for_in_df(self.df, 'pm2_x', step + step_for_calc)) /
previous_calc))
previous_calc = look_for_in_df(self.df, 'pm_x', step) + look_for_in_df(self.df, 'pm2_x', step) \
- look_for_in_df(self.df, 'pm_x', step) * look_for_in_df(self.df, 'pm2_x', step)
except KeyError:
values.append(1)
except TypeError:
values.append(1)
enablePrint()
self.df['qx12_sd_m'] = values
