What happens when your biggest financial fear strikes just months into retirement?
Well, that’s exactly what happened to me.

Imagine retiring after years of carefully saving and investing to secure your future, only to see the market plummet -18% in your first year. That was my reality in 2022 - the 5th largest market drop since the Great Depression.

You’d think panic or restless nights would follow. But I had a hidden advantage: WavRyder Signals. Designed to capture gains when markets rise and shield assets when they fall, it transformed the way I invest and redefined my retirement strategy.

WavRyder Signals. Remove emotion. Add discipline.

Shortly before retiring from a lengthy healthcare CFO career, I built an automated investment model to invest my retirement savings. My goal was to build a tool that would remove any emotions from the equation and provide me with clear signals, based on a 60-year back-test of market data. I knew I had built a comfortable nest egg that should last my family and me forever.

Still, I had a lingering concern about what I learned is called the Sequence of Returns Trap – the double hit some experience when both drawing down their portfolio to live on and experiencing a very large drop in the stock market, especially in the first handful of years of retirement.

I began by building a straightforward 3-fund model inspired by John Bogle’s well-known Vanguard approach. After a few days of iterating—swapping different ETFs across the three components (Equities, Bonds, and International Funds) and running back-tests—I realized the results, while solid, weren’t optimal. What stood out was that it was rarely advantageous to hold both equities and bonds at the same time.

I completely understood why the 3 Fund model was in all three funds at the same time - because nobody can know with any degree of certainty when they should be in one fund or another. So, being in all three all of the time would benefit form the law of averages.

But the process of swapping out different funds into the three buckets of the simple 3 Fund portfolio gave me an idea. Could I develop an algorithm using back-test data to try to identify signals of when one fund or another, instead of all three at the same time would be beneficial.

After a few months of testing, I had the foundation of a workable ETF rotation process. From there, I kept refining and stress-testing the approach, letting the data shape the model. Extending the back-test over six decades of daily market history revealed a consistent pattern—15 signals that repeatedly stood out. Together, they formed a single, unified indicator that highlighted which ETF had historically been most effective in similar environments.

The algorithm looks at a wide range of ETFs that I selected to ensure that I have covered the entire market and, on any given day, selects the best fund to invest in. If on any day, the algorithm could not find a suitable investment out of the wide selection of funds, then that meant it was time to shift to cash in the form of a money market fund. 

Throughout the iterative build process, I generally kept the development of the concept to myself. However, I did periodically check in with a financially savvy friend, Tom Drouillard, throughout the build process who helped play devils advocate on my thought processes and approach. I never shared this with him but throughout the iterative design, build and testing phases, my perception of his elevating excitement with the model kept me going and striving to improve the model.

Why so secretive?

I had seen countless times on financial forums I regularly read where folks were berated and belittled for diverging from the 3 Fund Portfolio model and the teachings of John Bogle. I myself was a strong believer in the 3 Fund strategy and it remains today a recommendation for those just starting out in their careers…I tell them to pick an allocation they are comfortable with and to “set-it-and-forget-it” - just like those old Ronco television commercials.

For me, I needed a little more focus on managing the potential for significant downsides while still targeting market level compound annual growth(CAGR). I didn’t have the time to recover from a very bad year in the market - especially without a paycheck coming in anymore.

So even though I knew my 3-Fund Portfolio friends might not appreciate what I was building—since it didn’t fit their mold—I pressed on. For me, the traditional 3-Fund approach fell short of providing what I valued most: protection. I wanted insulation from a major market crash at the very stage of life when I could least afford one—retirement, when I’d be relying on my portfolio to live.

I began investing my own money in this model back in mid-2021, and after just a few months, it was instrumental in signaling me to move to cash in November of 2021, just ahead of the disastrous first full year of my retirement, which saw the S&P 500 crash by -18%, the fifth largest drop since the Great Depression.

Looking back, my greatest fear as retirement drew closer—the day I thought I would finally “hang up my spreadsheets” for good—was the risk of a major market drawdown in those first critical years. That fear drove my obsession with building this model: a way to protect everything I had worked so hard to accumulate and would soon rely on to live in retirement.

Never in my worst nightmares did I imagine my first full year of retirement would coincide with the fifth-largest market crash since the Great Depression. In 2022, the S&P 500 fell by -18%—hardly the welcome I had envisioned for retirement.

Yet, I was largely shielded from the decline. My model had signaled a move to cash in November 2021 and kept me there through most of 2022, providing the protection I had hoped for.

While the rest of the investing world was losing sleep over the market’s rollercoaster, I was perched safely in cash and I Bonds—collecting a modest money market return and a surprisingly solid yield on the I Bonds. It wasn’t glamorous, but it was peaceful.

For the next couple of years, I treated my model like a seasoned guide on a treacherous hike: follow it exactly, or risk stepping into a pitfall. And sure enough, every time I got lazy and ignored its advice, the market reminded me—sometimes harshly—that the guide had known the path all along.

Earlier this year, as I tackled a bucket list item of mine - to publish a book on investing, I ran some routine spreadsheet experiments to create exhibits. One test immediately stood out—it highlighted the power of moving to cash whenever the algorithm couldn’t find a suitable investment in the core rotation. That moment made the model’s logic feel suddenly clear and intuitive - a binary choice either:

That was my “aha” moment. I realized the complex, day-to-day decisions of the algorithm could be boiled down to a simple Red Light/Green Light signal: Red Light when no fund fit the criteria, Green Light when one did.

Suddenly, the model’s inner workings felt far more intuitive—and far easier to follow.

I put the signal to the test across a wide spectrum of portfolios: the classic 3-Fund Model, 60/40 and 70/30 splits, various Target Date Funds, and even strategies modeled on investing legends like Berkshire Hathaway, Carl Icahn, and Dodge & Cox using their SEC 13F filings. I didn’t stop there—smaller, concentrated portfolios with 20 or fewer securities went under the microscope too.

When I applied my model’s Signal across these very different portfolios, the results were striking. Worst-case annual losses dropped dramatically— sometimes 6-8 times lower than before. Risk metrics like Beta, Jensen’s Alpha, Sortino, Sharpe, and Treynor all improved.

CAGR edged slightly lower than the original portfolios, but that wasn’t the point. The model wasn’t about chasing the highest returns—it was about keeping losses in check while still capturing returns close to the market.

I had the luxury of moving between funds and cash several times a month because I was retired, but most investors wouldn’t want that kind of hands-on approach. The good news? If those moves could be simplified into a straightforward Red Light/Green Light—where the only action is shifting from your portfolio to cash on a Red Light and back on a Green Light—almost anyone could follow it.

I shared all these new findings with Tom Drouillard, who recommended I stop writing the book and instead consider starting a company and offered to partner up with me, matching my financial modeling skills with his publishing and marketing skills – a perfect complement.

One of our initial marketing efforts was a detailed Target Date Fund industry analysis. These funds are ideal for novice investors who recognize the need to save for retirement but lack the know-how. Instead, they can select a fund based on their expected retirement date, which automatically adjusts its equity-to-bond ratio as they age.

We were surprised to find that over 60% of all retirement fund investors have defaulted to these amazingly simple investment vehicles - Target Date Funds. After learning that, we felt this was a good jumping-off point to prove the efficacy of our Investment Signal Publication.

We decided to test the Signal on a Target Date Fund with 10 years to retirement. Originally launched with a 90/10 equity-to-bond allocation, it had gradually shifted to roughly 70/30 over the years. Running a 20-year back-test, we wanted to see how the Signal might have influenced the fund’s risk and reward—essentially, how it could have “rode the wave and while dodging the storm.”

The results were hard to ignore. The Target Date Fund’s CAGR barely budged, slipping only from 7.4% to 6.9% with the Signal in place. Meanwhile, the worst annual loss plummeted from a gut-wrenching -34.6% to just -4.4%—an almost eightfold improvement. And for nearly half the time, the investor was safely in cash, sidestepping the market’s wild swings.

At first, Tom and Dan weren’t impressed by a 6.9% CAGR—a little less exciting than the uninspiring 7.4% from the unadjusted Target Fund.

Then the “aha #2” moment hit.

As they reviewed the analysis, they realized that being in cash for 44% of all trading days added a great degree of conservativism to an already conservative model (The Target Date fund maintained a 70/30 mix - a full 30% of the investment was in bonds). So, shifting an already conservative model to the ultimate in conservatism - cash - kept risk incredibly low—Beta just 0.32, and every other metric tightly controlled—but it also limited the potential upside.

They did not want to change the fact that the WavRyder Signal signaled to sit in cash 44% of the time - that was the magic. However, they wondered if it was necessary to be in bonds 30% when the signal already had the entire investment in cash 44% of the time. So, they pulled the bond allocation out of the mix…and in doing so, they scrapped the Target Fund in its entirety and instead created models that simply invested in the one of the three major indices in the form of their corresponding low-cost ETFs or cash when the Signal signaled caution.

They created 3 models:

Even though the model spent a hefty 44% of the time safely in cash, it made the most of the remaining 56% fully invested—and the results were striking. Annual growth jumped from 7.4% in the standard Target Date Fund to a range of 8.4% (Dow) up to 12.3% (Nasdaq), with the S&P 500 landing at 9.2%. Just as impressive, worst-case annual losses shrank from a gut-wrenching -34.6% to a far more manageable -5% to -8%. With betas cut nearly in half, the back-test experienced smoother rides while capturing significantly stronger returns - it “rode the waves while avoiding the storms.”

Here's where it gets exciting: we built a blended model using one-third of each major index. The outcome? A $400K investment made in 2006 would have soared to $2.6M by 2025—that's $1M more than the same investment in the unadjusted Target Date Fund. And the best part? It all came with a much lower risk profile.

We are now trying to devise a way to facilitate the Signal for those 60% of 401K investors, knowing that they cannot simply and freely move into and out of funds like the self-directed IRA investor could in their brokerage account.