2
$\begingroup$

I am seeking help on how to perform Monte Carlo simulations on (potentially) correlated time series. I have a single product (e.g., men's wallets) that are sold out of seven stores in the same city. I have last year's daily sales of wallets for each store. Most days, a store sold zero, some days they sold one, fewer days they sold two... the histogram resembles an exponential distribution.

I want to be able to use last year's sales, to simulate the potential combined sales of the seven stores. (Assume no sales growth year on year). I am wary of just sampling each store's daily sales independently and combining them into a new RV, as there may be some correlation, and some seasonality, of the sales. Ideally I'd be able to simulate a range of the combined sales for January 1, a range of the combined sales for January 2, .... a range of the combined sales for December 31; that takes into account potential correlation and seasonality of the sales. Bonus points if you can point me to some R functions that do this.

It's important to note that I'm not looking to forecast a time series, but rather understand potential range of the 7 stores' sales in sum, based upon variability in the existing 7 stores' time series of sales.

$\endgroup$
1

0

Your Answer

By clicking “Post Your Answer”, you agree to our terms of service and acknowledge you have read our privacy policy.

Browse other questions tagged or ask your own question.