Benjamin Felix

So if equity returns have been high recently because valuations have increased a lot, or if valuations have increased a lot and that's contributed to recent stock returns, we do adjust for that in that long-term measure.

And I mean, likewise, if stock valuations plummeted all of a sudden and the historical return dropped, we would adjust for that valuation change.

And then we combine that with 25% market-based expected return, which as I mentioned is the inverse of the Shiller CAPE.

It's not

statistically robust, but we ran a bunch of regressions on how predictive has the Shiller Cape been historically for future returns.

Statistician would probably mock us for our methodology on this specific part, but we figured that a 25% contribution from the market-based expected return was

roughly in line-ish approximately sort of with the historical predictive power of that metric.

And then for fixed income, we do the inverse where it's 25% historical return and 75% the current yield to maturity on bonds.

And again, that's because historically bond yields have been much more predictive of future realized returns than the CAPE has over future realized stock returns.

But again, they're not perfect statistically derived numbers.

They're rough estimates that work well for doing our expected return estimates.

And then for factor tilted portfolios, we do add factor premiums to market cap expected returns.

We use historical factor premiums that we then shrink down for post-publication shrinkage of each factor.

We also have to do estimates for the composition of expected returns.

If you're doing a projection, particularly for a taxable investor, you need to split out how much of the return is coming from Canadian dividends, how much is foreign dividends, how much is interest, how much is realized versus unrealized capital gains.

So we have methodologies for all of those things and include them in our data.

And then you have to estimate a correlation matrix.

We use historical correlations for that.

And we're currently doing our projections, our distribution of returns using a Gaussian distribution.

We simulate returns using a multivariate normal distribution.