A lot of effort in the investment space has gone into giving people advice about their proper asset allocation. There’s a good reason for that – academic studies have shown that over 90% of variation in returns is determined by asset allocation. As a result, there’s a lot of advice out there. Academics talk about efficient frontiers and Monte Carlo simulations. Companies such as Financial Engines and Betterment have come along to help people.
Me? I’m more in the William Bernstein camp. The problem is that the inputs to the models are unknown. Things like the risk premium accorded to equities and correlations between asset classes are not very stable over time. Plugging historical data seems unlikely to work – times change, there are different periods, and the future almost certainly won’t look like an average of the past. Having written a Monte Carlo simulator for these types of things, I can tell you that it’s mostly junk. The answers you get heavily depend on whether you think the risk premium for equities will be 4%, 4.5%, or 5%, or other such wonky inputs. I wouldn’t believe anyone who says they know which it will be.
So what do you do, then? I’d start with simply being diversified and rebalancing your portfolio yearly. Also, no matter what you decide, stick to it. You don’t want to introduce unnecessary churn, and you don’t want to chase performance.
Beyond that, here is a reasonable portfolio. It probably won’t be the optimal portfolio over any time horizon, but, hey – it’s worth what you paid for it, and it’s probably just as good as anything else you’ll see.
30% US Large Cap (iShares IWB)
15% US Small Cap (Vanguard’s VB)
20% International (Vanguard’s VXUS)
10% Emerging Markets (Vanguard’s VWO)
5% REITs (Vanguard’s VNQ)
10% Treasuries (iShares IEF)
10% TIPS (SPDR IPE)
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