def determine_target_spending_at_node(profile, config, spending_boundary_at_projection_year,
dynamic_spending_ratio_at_projection_year,starting_wealth_at_sim_run,
annuity_Income, SS_Income):
# target = profile['target']['fixed']
# income_tax_assumption = 0.25 #used to determine the after tax dynamic spending target at each node
minimum_spending_boundary = profile['target']['essential']
maximum_spending_boundary = profile['target']['discretional']
minimum_boundary = minimum_spending_boundary * spending_boundary_at_projection_year #lower boundary
maximum_boundary = maximum_spending_boundary * spending_boundary_at_projection_year #upper boundary
## Dynamic amount is the product of the starting account balance and the ratio following from the specified method
# dynamic_amount = starting_wealth_at_sim_run * dynamic_spending_ratio_at_projection_year * (1 - income_tax_assumption) + annuity_Income + SS_Income if starting_wealth_at_sim_run > 0 else 0
'''
Apply tax model to accounts to calculate dynamical spending amount
'''
if profile['account']['type'] == 'Traditional':
dynamic_amount_tax = calc_income_tax_liability(starting_wealth_at_sim_run * dynamic_spending_ratio_at_projection_year, SS_Income, income_tax_config)
else:
dynamic_amount_tax = 0
dynamic_amount = starting_wealth_at_sim_run * dynamic_spending_ratio_at_projection_year + annuity_Income + SS_Income - dynamic_amount_tax if starting_wealth_at_sim_run > 0 else 0
## Dynamic target is higher than lower boundary if enough account balance
dynamic_target = max(minimum_boundary, min(maximum_boundary, dynamic_amount))
return dynamic_target
def objectiveFunction(pre_tax_withdrawal, target, accountType):
if accountType == 'Traditional':
income_tax_liability = calc_income_tax_liability(
pre_tax_withdrawal, SS_Income, income_tax_config)
else:
income_tax_liability = 0
return abs(pre_tax_withdrawal + SS_Income + annuity_Income -
income_tax_liability - target)
def decumulate_for_one_year(profile, starting_wealth, model_port, projection_year, SS_Income, annuity_Income, config,
spending_boundary_at_projection_year, dynamic_spending_ratio_at_projection_year, num_sim_runs = 100):
ModelPortReturnsBySimAndYear = calc_model_port_ret_across_sim_runs_at_projection_year(model_port, projection_year,config)
EOY_wealth = np.zeros(num_sim_runs)
after_tax_retirement_income = np.zeros(num_sim_runs)
income_tax_config = config['income_tax']
## Dynamic Spending function
def determine_target_spending_at_node(profile, config, spending_boundary_at_projection_year,
dynamic_spending_ratio_at_projection_year,starting_wealth_at_sim_run,
annuity_Income, SS_Income):
# target = profile['target']['fixed']
# income_tax_assumption = 0.25 #used to determine the after tax dynamic spending target at each node
minimum_spending_boundary = profile['target']['essential']
maximum_spending_boundary = profile['target']['discretional']
minimum_boundary = minimum_spending_boundary * spending_boundary_at_projection_year #lower boundary
maximum_boundary = maximum_spending_boundary * spending_boundary_at_projection_year #upper boundary
## Dynamic amount is the product of the starting account balance and the ratio following from the specified method
# dynamic_amount = starting_wealth_at_sim_run * dynamic_spending_ratio_at_projection_year * (1 - income_tax_assumption) + annuity_Income + SS_Income if starting_wealth_at_sim_run > 0 else 0
'''
Apply tax model to accounts to calculate dynamical spending amount
'''
if profile['account']['type'] == 'Traditional':
dynamic_amount_tax = calc_income_tax_liability(starting_wealth_at_sim_run * dynamic_spending_ratio_at_projection_year, SS_Income, income_tax_config)
else:
dynamic_amount_tax = 0
dynamic_amount = starting_wealth_at_sim_run * dynamic_spending_ratio_at_projection_year + annuity_Income + SS_Income - dynamic_amount_tax if starting_wealth_at_sim_run > 0 else 0
## Dynamic target is higher than lower boundary if enough account balance
dynamic_target = max(minimum_boundary, min(maximum_boundary, dynamic_amount))
return dynamic_target
## Define the optimization function
def objectiveFunction(pre_tax_withdrawal,target,accountType):
if accountType == 'Traditional':
income_tax_liability = calc_income_tax_liability(pre_tax_withdrawal, SS_Income, income_tax_config)
else:
income_tax_liability = 0
return abs(pre_tax_withdrawal + SS_Income + annuity_Income - income_tax_liability - target)
for i in range(num_sim_runs):
target = determine_target_spending_at_node(profile, config, spending_boundary_at_projection_year,
dynamic_spending_ratio_at_projection_year, starting_wealth[i],
annuity_Income, SS_Income)
if starting_wealth[i] < 100:
optimized_pre_tax_withdrawal = starting_wealth[i]
else:
solution = minimize(fun=lambda x: objectiveFunction(x,target,profile['account']['type']), x0 = 0,method='SLSQP',bounds=[(0,starting_wealth[i])])
optimized_pre_tax_withdrawal = solution.x
EOY_wealth[i] = max(starting_wealth[i] - optimized_pre_tax_withdrawal,0) * (1 + ModelPortReturnsBySimAndYear[:,i])
if profile['account']['type'] == 'Traditional':
income_tax_liability = calc_income_tax_liability(optimized_pre_tax_withdrawal, SS_Income, income_tax_config)
else:
income_tax_liability = 0
after_tax_retirement_income[i] = optimized_pre_tax_withdrawal + SS_Income + annuity_Income - income_tax_liability
return EOY_wealth, after_tax_retirement_income