I plan to next explore how a multi-period term structure of capital market assumptions affects base case retirement forecasts differently from single period forecasts and how we might hedge the downside risks differently given the term structure.
I'm wondering whether a 3-period forecast approach something like this might make sense:
Real Returns (CAGR%) by period (Speculative approach)
- 2026-2030: ~5.5-5.9% based on iERP
- 2031-2035: ~4.8% based on Expected Returns method + valuation compression to return Forward P/E ratio to 16.75x
- 2036+: ~5% based on Expected Returns meth
Here’s the rub: the amount of uncertainty around all three of your estimates is huge. (And it couldn’t be otherwise, or there wouldn't exist such a large ERP as we have!)
So getting as nuanced as you're doing doesn't make sense to me personally. If there was a larger trend, it might make a difference. But would you really trust decisions like roth conversions on that?
In my own pralana I've simply been averaging the two big models and just using that for all time periods. Research Affiliates site has a neat feature that lets you "mix and match" any proportion of their Valuation and Growth&Yield estimates, depending on your confidence about either model. (I use 50/50.)
Yah, for sure! It's definitely fair to argue that because the standard deviation is +/- ~17%, therefore all my hand-wringing about whether next year's Real expected mean return is 3% or 6% is a waste because there is a >50% chance that next year the stock market will be either down more than -5% or up more than +15%, and then next year I'll start the process all over again either materially poorer or materially richer. Therefore it seems fair to argue that this huge uncertainly about next year's returns grossly overwhelms any benefit there may be to trying to making my estimates of the Mean hyper accurate.
But, probably not surprisingly given my other posts, that's not my point of view.
I enjoy learning this sort of thing and I think that doing the analysis RIGHT is a lot like computing the probabilities in poker to bet "right". After the first, partial set of cards are dealt you need to decide whether it is worth the risk to bet an additional X dollars to see the next card and have a chance to win Y dollars, given the cards you've received, the number of other players in the hand, and how the players have already bet. It takes a lot of effort to get that decision "right", it takes a lot of effort long before the game studying, practicing, analyzing, and learning and then during the game you need to perform that mental computation quickly and under stress.
And after all that effort, all my hard work and hand-wringing gets overwhelmed when the very next card gets dealt and all the odds change massively again.
But in my mind when we face a betting opportunity paying 2 to 1, doing the computation correctly to determine whether it has a probability of success of 52% or just 48%... that's what the whole game is!
For me, I prefer to know the real odds ahead of time and risk losing to bad fortune rather than to not know the real odds and play anyways. I do however respect that others might say that to them that is not a game worth playing, or at least not worth playing that way...
Good discussion. I'll throw in my two cents, which, as always, only applies to me, my way of thinking, and my retirement planning. For me, any financial prediction, put forth by anybody, is meaningless information to me. There is a good discussion on predictions on the PRC Forum thread under Information Sharing > Sharing of Inflation Rates, Rates of Inflation > Asset Allocation page 10 May 30, 2023 2:19 PM. I also think cranking through all these financial calculations (CAPE, SD, CAGR%, iERP, Cleveland Fed Model, whatever) again provides me with zero information in terms of what to put into PRC or developing my Retirement Plan. Fun to play around with, you bet!! But I fear in provides a false sense of security about what the future will bring. It's mostly a psychology thing, no disrespect intended. Humans really don't like not knowing what the future will bring, and even more upset about not being able to doing anything about it. So we come up with predictions and elaborate gyrations to take control. A very good book I recommend is The Psychology of Money by Morgan Housel 2020.
Here’s the rub: the amount of uncertainty around all three of your estimates is huge. (And it couldn’t be otherwise, or there wouldn't exist such a large ERP as we have!)
So getting as nuanced as you're doing doesn't make sense to me personally. If there was a larger trend, it might make a difference. But would you really trust decisions like roth conversions on that?
I think that doing the analysis RIGHT is a lot like computing the probabilities in poker to bet "right". After the first, partial set of cards are dealt you need to decide whether it is worth the risk to bet an additional X dollars to see the next card and have a chance to win Y dollars, given the cards you've received, the number of other players in the hand, and how the players have already bet. It takes a lot of effort to get that decision "right", it takes a lot of effort long before the game studying, practicing, analyzing, and learning and then during the game you need to perform that mental computation quickly and under stress.
And after all that effort, all my hard work and hand-wringing gets overwhelmed when the very next card gets dealt and all the odds change massively again.But in my mind when we face a betting opportunity paying 2 to 1, doing the computation correctly to determine whether it has a probability of success of 52% or just 48%... that's what the whole game is!
For me, I prefer to know the real odds ahead of time and risk losing to bad fortune rather than to not know the real odds and play anyways. I do however respect that others might say that to them that is not a game worth playing, or at least not worth playing that way...
I don't think our confidence in return estimates is like poker. The game of poker is very full of chance but well understood, and every aspect is quantifiable other than human psychology. It is a very controlled chance. With these return models we're not even sure, epistemically, the models themselves are correct, let alone the details of their predictions. One thing I like about the actuarial model we both use is that is "self correcting", and you don't have to be 100% accurate about your predicted returns. Getting it too high or low will merely adjust the slope of your withdrawal, so any error is spread out across the whole plan.
The first thing that popped into my head reading your investment planning thinking process the Kelly Criterion, coming from gambling theory, which attempts to justify the rational amount of risk to take. Merton generalized it in what's known as the "Merton share". (It is also closely related to the sharp ratio.) Have you heard of it? It essentially attempts to quantify the amount of risky asset justified by a given SD: It's two asset version (Risky asset and riskless asset) is:
Equity Premium / (SD squared * risk aversion). Victor Haghani and James White talk about it at length in their Missing Billionaires book. (By survey they claim most people are in the 2-3 risk aversion range, fwiw.) I remain skeptical of the whole thing, but it seems right up your alley.
