Calculator for Backtesting a Portfolio or Asset Allocation (Also Monte Carlo Simulations) — Oblivious Investor


A reader writes in, asking:

“Is there a website or calculator that you recommend for showing the historical results of a portfolio? Something where I can enter an asset allocation and the calculator will tell me what the return would have been and how risky.”

Yes, absolutely. is an excellent tool for this sort of thing. From the homepage, select the link for “backtest asset allocation” if you want to choose from inputs such as “US large cap,” or click the link for “backtest portfolio” if you would prefer to provide the ticker symbols of specific mutual funds.

The calculator lets you adjust your modeling for various rebalancing options. For example, you can assume the portfolio is rebalanced monthly, rebalanced annually, never rebalanced, or rebalanced using “rebalancing bands” (e.g., rebalanced whenever the allocation is off-target by 10%).

And it lets you make assumptions about ongoing contributions to, or spending from, the portfolio. You can make adjustments such as whether the spending is a fixed percentage or a fixed dollar amount. (And if it’s a fixed dollar amount, should it be inflation-adjusted over time?)

After you provide all of your inputs, the calculator tells you the historical return, standard deviation, best/worst years, maximum drawdown, and other various results.

PortfolioVisualizer also has the option to run Monte Carlo simulations. (Select the link for such from the homepage.) On the Monte Carlo simulation page, you can have it use historical data, or you can select other options for the return assumptions (e.g., “parameterized returns,” which lets you input expected return and standard deviation for yourself).

The PortfolioVisualizer website also has a ton of other calculators that I’ve never even used. In short, it’s an incredible resource. And it’s free. (Though there’s also a paid version that gives you some additional capabilities, such as saving results, exporting to spreadsheets, etc.)

Of course, when backtesting, be sure to remember the limitations of relying on historical data. Just because a portfolio provided a particular return in the past doesn’t mean it will do so in the future. And the same goes for all of the other outputs (e.g., how risky an allocation would be, or whether it would have satisfied a particular spending rate in the past).

And ditto for the Monte Carlo simulations. They can be useful, but remember that we don’t actually know what the future distribution of returns will look like for any asset class. If a set of Monte Carlo simulations shows, for example, that a particular portfolio has a 92% chance of satisfying a given spending rate over a given length of time, we don’t actually know that the portfolio has a 92% chance of satisfying that spending rate over that length of time. Rather, what we know is that, given the assumptions that you used, the portfolio had a 92% chance of success.

“A wonderful book that tells its readers, with simple logical explanations, our Boglehead Philosophy for successful investing.”
– Taylor Larimore, author of

Source link

Related Articles