No More Mystery About My Money

I could answer questions about my risk tolerance. I couldn't explain much about the strategy managing my money.

Across the money managers and advisors I worked with, the conversations felt familiar. There were standard questions, settings, and a discussion that seemed to come back to what percentage of stocks and bonds I wanted.

At one point, I asked my advisor why on earth I’d want bonds in my portfolio so early in my investing life because it made no sense to me. I was trying to give my retirement money a long time to grow in investments with a much higher return potential. He explained that bonds help smooth market dips. Less volatility could make clients less likely to make rash decisions and help them stay calmer through uncomfortable markets.

The explanation was about managing the experience of investing. My question was about the strategy for growing the money.

I wanted my retirement accounts to grow as fast and as responsibly as they could, for as long as they could. When it came time to draw from them, I wanted a large enough account that I wasn't worrying about whether it would last the rest of my life.

But the actual strategy wasn't something we discussed in much detail. My understanding was that an automated system was making the trades underneath it all. The process behind those decisions wasn't something they shared with me.

After about ten years, I moved to a market index fund. In 9 of the 10 years, the managed accounts hadn’t done better than the market. And in the 1 year they did, they still lost money. They just didn’t lose quite as much as the market. I didn't see a reason to keep paying to underperform.

Being an engineer, I also believed there had to be a way to build something better. That belief gave me a reason to start investigating.

The questions behind the holdings

Once I settled on a momentum strategy, I built the system to make the stock pool, rankings, weights, and high-level approach visible.

No more mystery.

That meant designing around four questions.

Which stocks were being considered?

I chose the S&P 500 as the starting pool. I wanted that universe to be clear alongside the selected stocks, so the names in the allocation could be understood in the context of what they were chosen from.

How did the selected stocks rank?

I made the selected stocks' rankings part of the output. A list of holdings shows what was chosen. Including the ranks shows where those stocks stood relative to one another in that month's selection.

How was the money divided?

I included a target weight for each stock: the percentage of the portfolio assigned to it. Owning a company with a small allocation is a different commitment from giving it a large share of the account. I made the proportions visible alongside the selections.

What was the overall strategy?

I built around momentum and a monthly schedule. I wanted the high-level explanation to connect those choices to what appears in the allocation.

Those questions became requirements for what I built and what I chose to show.

More than a monthly list

For Starting Index, I want to make the investment decisions understandable while keeping the exact stock-selection formula proprietary.

The subscriber tools are built to show target weights, time on the list, and rank and weight changes from the prior publication. Monthly reports include the selected stocks' ranks and weights, alongside performance context.

The publication archive provides earlier reports to compare across months. The monthly recap is built to bring profile results and the market comparison together. The broader goal is to make each stock's path through those records easy to understand.

A monthly allocation is one output of that process. The explanation, the dated records, the assumptions, and the limitations belong alongside it. Together, they give someone more to examine than a list of stocks or an attractive chart.

That is the larger vision for Starting Index.

The evidence around the allocation is part of the product, too.

Earlier articles covered backtests, investment rules, and track records. They also explained how leaving failed companies out of a backtest can make the results look better than they were. Each dealt with a different part of the same problem. An investment result is easier to interpret when you can see what produced it and what kind of evidence you're looking at.

Visibility doesn't tell me what a strategy will earn next. It does let me examine what the strategy says it will do, what its records show, and where the questions remain.

For someone evaluating an investment model, the four questions above offer a practical place to begin. What is it choosing from? How are the choices ranked? How is the portfolio divided? What is the overall approach?

Those are the things I wanted to see when I began building my own strategy. They're the starting point for the kind of investment information I want to make available to others.

No more mystery about what the process is trying to do.

The method explains the stock pool, momentum ranking, and monthly publication process behind Starting Index. If you'd like to look more closely, that's a place to start.