Following a model investment portfolio sounds straightforward.
See what the model owns. Look at the target allocations. Make similar trades in your own account.
In practice, it can get complicated pretty quickly.
We subscribe to High Yield Investor (HYI), a private investing group on Seeking Alpha that maintains model portfolios and issues trade alerts as those models change. Trades might happen a few times a month, and the underlying allocations are updated along the way.
For a while, keeping our own portfolio aligned meant a spreadsheet, some rough calculations, and a fair amount of time.
The spreadsheet eventually became unwieldy. Market values kept changing. New investments appeared. Others disappeared. And every trade meant figuring out how the change should translate into our own portfolio.
Mistakes were easy to make. Sometimes we invested too much. Sometimes too little.
More importantly, we weren’t actually trying to duplicate the HYI portfolio.
We wanted to make it ours.
The model is an input, not the answer.
That’s the idea behind Investment Portfolio Modeler.
The application takes a model portfolio, our actual holdings, and our own investing preferences and helps answer a much more useful question:
What does this model mean for my portfolio?
HYI currently provides the primary source models. The application can sync those models on demand from their source data, while our actual holdings can be maintained manually or imported from Fidelity.
From there, the modeling becomes personal.
We can blend HYI’s Core and Retirement portfolios—for example, modeling an IRA as 50% Core and 50% Retirement, or 80/20.
We can keep investments that aren’t in the model.
We can exclude model investments we don’t want to own.
We can substitute one ticker for another, or even split an allocation among alternatives.
And we can set drift tolerances so the application doesn’t treat every mathematical difference as something that requires a trade. A $1,000 difference on a $50,000 position may simply not matter to that investor.
The goal isn’t to perfectly mirror somebody else’s portfolio.
It’s to use the model as an input for maintaining your own.
The useful part is the recommendation.
When HYI issues a trade alert, there’s a natural temptation to react quickly.
The application has changed that experience for us.
We can sync the latest model when we’re ready, update our actual holdings, and regenerate the Recommendations panel. It shows which investments are aligned, which are over or under their modeled allocation, the amount of drift, and the resulting buy or sell guidance.
Then we can decide what actually needs attention.
Maybe the announced trade matters to us.
Maybe our portfolio is already close enough.
Maybe one of our preferences changes the result.
Maybe we decide to wait.
The application keeps track of the data and does the modeling when we’re ready. That takes some of the noise and pressure out of following an actively managed investment service—while helping us get more practical value from the research we’re paying for.
It also remembers.
If an investment leaves a source model and later returns, the application remembers the preferences we’ve already established for it rather than starting over. New investments can enter with sensible defaults and then be adjusted as needed.
It doesn’t have to be HYI.
HYI was where the project started, and it’s still the application’s most developed use case.
But the modeling engine has already grown beyond it.
A user can create a model portfolio directly in the application by giving it a name, description, tickers and target weights. Once created, that portfolio can use the same matching, blending, tolerance, drift and recommendation capabilities as the HYI models.
That opens up a much broader idea.
The model could come from HYI. It could eventually come from another curated investing service. Or it could simply be one you create yourself.
The basic problem remains the same:
Here is a model. Here is my portfolio. Here are my preferences. What do the differences mean for me?
A note about investing
Investment Portfolio Modeler is a modeling and decision-support tool. It does not place trades, and the investor remains responsible for all investment decisions. Material on this website describing the project is provided for informational purposes and is not investment advice or a recommendation to buy, sell, or hold any security.
Still on the bench.
Investment Portfolio Modeler has become one of the applications we rely on regularly, but there’s still plenty to do.
The user experience can be polished and streamlined. Updating actual holdings still involves an import or manual changes. The application is desktop-first today, and there are useful things we’d eventually like to make available from a phone without trying to squeeze the entire modeling experience onto a small screen.
There’s also a larger question about distribution.
Right now, it’s a personal application. Longer term, it could become a SaaS application, a packaged desktop application, or some combination that makes it practical for other investors to use with their own portfolios and models.
Whatever form that takes, one boundary is important.
The application is a modeling tool, not an automated trading system.
It can show the investor how their portfolio differs from a chosen model and provide dollar-based guidance for bringing the two closer together. It can expose the calculations behind those recommendations so they can be reviewed.
It does not place trades.
The investor stays in charge.
That’s intentional.