So, it randomly samples from the empirical distribution? That’s not a good idea, returns (especially of bonds) have time-series structure which should not be ignored. And what about asset class correlations?
I don’t know how Vanguard does their simulator, but as a technical point it’s easy to encode time-series structure and asset class correlations into Monte Carlo simulations. Correctly estimating that time series structure and the correlations may be another story, especially for financial data.
What’s hard is producing a reasonable model. Once you have one, sampling from it is easy.
I expect the Vanguard simulator to be an exercise in marketing and so be trivially simple (pick a random historical return for S&P500, pick another random historical return from, say, some aggregate bond index, combine according to portfolio weights, repeat).
What’s hard is producing a reasonable model. Once you have one, sampling from it is easy.
Agreed.
I expect the Vanguard simulator to be an exercise in marketing and so be trivially simple (pick a random historical return for S&P500, pick another random historical return from, say, some aggregate bond index, combine according to portfolio weights, repeat).
Clicking through the link, this is close to what they’re doing (they appear to select the same year to preserve the asset class correlations):
For each year of each simulation, we randomly select one year of stock, bond, and stable-value returns from the database. Using those values, we calculate what would happen to your portfolio—subtracting your spending, adjusting for inflation, and adding your investment return. We repeat this process, one year at a time, until the end of your retirement or until your portfolio runs out of money. The next simulation starts the whole process from the beginning. After 5,000 independent simulations, we’ve tested a broad range of possible scenarios, and clear patterns begin to emerge.
This seems to be a rather inefficient method of calculating an average return :-/ I’m not being quite fair here because doing it this way accounts for things like higher moments and so is better, but still...
The underlying assumption is that both the stock market (represented by different proxies at different points in time!) and the bond market (ditto) are stable unchanging processes since 1926. That, um, does not look likely to me.
I don’t know how Vanguard does their simulator, but as a technical point it’s easy to encode time-series structure and asset class correlations into Monte Carlo simulations. Correctly estimating that time series structure and the correlations may be another story, especially for financial data.
What’s hard is producing a reasonable model. Once you have one, sampling from it is easy.
I expect the Vanguard simulator to be an exercise in marketing and so be trivially simple (pick a random historical return for S&P500, pick another random historical return from, say, some aggregate bond index, combine according to portfolio weights, repeat).
Agreed.
Clicking through the link, this is close to what they’re doing (they appear to select the same year to preserve the asset class correlations):
This seems to be a rather inefficient method of calculating an average return :-/ I’m not being quite fair here because doing it this way accounts for things like higher moments and so is better, but still...
The underlying assumption is that both the stock market (represented by different proxies at different points in time!) and the bond market (ditto) are stable unchanging processes since 1926. That, um, does not look likely to me.