Discount factors for premiums.

Returns a 2D numpy array. The array contains discount factors for discounting premiums of each model point. The timings of premium cashflows are adjusted by payment_lag(). Since payment_lag() differs by model point, disc_factors_prem() returns a 2D array by model point and by time index i. In each projection step, premium payments before and after policy anniversary are modeled separately, so different discount factors are returned depending of the value of j. When j='LAST', the returned discount factors are for discounting premiums paid before policy anniversary, while when j='NEXT', the factors are for premiums after the anniversary. For each i and j, disc_factors_prem() is defined as:

(1 + disc_rate(i))**(-t)

where t is defined as for j='LAST':

(months_(i) + payment_lag(i, j)) / 12

and for j='NEXT' as:

(months_(i) + last_part(i, j) + payment_lag(i, j)) / 12

j – ‘LAST’ or ‘NEXT’