John Yang

For example, what does a typical year look like for Canadian equities?

How often do we see a strong year?

Second question we're asking is how do the asset classes behave together, how they move together?

For example, when U.S.

equity is down, are Canadian international equities also down?

Or when equity is down, does bond help offset the loss?

When we're modeling it, we also do it separately.

First, we handle the dependent structure, actually.

And we do that through a t-copula.

Without being too technical in getting to what copula is, an easy way to explain it is it's just a part of the model that links the portfolios, linked asset classes together.

It helps you generate the correlated data by encoding it with essentially a matrix.

And the reason we were using a T copula rather than the Gaussian copula that PWL was using before is the T copula captures the coat movement at the tail better.

That was one of the challenges that we were talking about earlier.

And I think what is more interesting is how we are modeling the distribution of each individual asset classes.

Originally, the method was just looking at asset classes as a classic bell curve.

You're assuming perfect symmetry, smooth distribution of returns, but that is not realistic.

So instead of forcing our portfolio into the same bell curve, we let the historical data describe the shape more directly.

For the distribution that we're modeling, we also divide this problem into two parts.

For most of the distribution, we use the actual historical pattern of the returns.

We first standardize the returns.