title: How to compute the combined probability of loss for 2 time series (consisting of historical stock prices)?
body: <p>May I please ask the community's support with the following problem?</p>
  <p>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<sub>loss</sub>%:</p>
  <p><strong>Pr(</strong> P<sup>A</sup><sub>t+i</sub> &lt; P<sup>A</sup><sub>t</sub> (1-r<sub>loss</sub>) <strong>or</strong> P<sup>B</sup><sub>t+i</sub> &lt; P<sup>B</sup><sub>t</sub> (1-r<sub>loss</sub>) <strong>)</strong> = <strong>?</strong></p>
  <p><strong>where:</strong></p>
  <p>i = {1,2,3,4,5}, periods for which I want to forecast ahead (not yet observed)</p>
  <p>t = current time</p>
  <p>P<sup>A</sup>, P<sup>B</sup> = price of stock A, price of stock  B</p>
  <p>r<sub>loss</sub> = loss threshold, e.g. r<sub>loss</sub> = 0.03 <strong>=&gt;</strong> P<sup>A</sup><sub>t+i</sub> &lt; P<sup>A</sup><sub>t</sub> (1-0.03)</p>