May I please ask the community's support with the following problem?

I have 2 time series, with approximately 1000 observations each (same number of observations for both). They represent the daily closing prices for 2 stocks: asset A and asset B. Assuming we are currently at time t, I'm interested in computing (forecasting) the probability that, (at anytime) over the next 5 days (i.e. t+1, t+2, t+3, t+4, t+5), either stock A's or B's price will fall by at least r_loss%:

Pr( P^A_t+i < P^A_t (1-r_loss) or P^B_t+i < P^B_t (1-r_loss) ) = ?

where:

i = {1,2,3,4,5}, periods for which I want to forecast ahead (not yet observed)

t = current time

P^A, P^B = price of stock A, price of stock B

r_loss = loss threshold, e.g. r_loss = 0.03 => P^A_t+i < P^A_t (1-0.03)