Let’s face it — the traditional “60/40” is the avocado toast of portfolio strategies. I started like many others: topic ETFs, later some geographies, maybe some bonds when I got older and a sprinkle of gold.
Most Portfolios Are Static—That’s a Problem
Eventually, you realise something’s off. You notice how little your portfolio responds to the world around it. Inflation spikes? Same allocation. War? Still the same. Interest rates flip? You guessed it…
Traditional investment portfolios are often structured with fixed allocation percentages across asset classes, sectors, and geographies. While this approach aligns with passive investing principles, it assumes a stable macroeconomic environment, which is rarely the case. In reality, financial markets are highly sensitive to economic cycles, central bank policy shifts, and geopolitical developments.
So after reading into systematic allocation and forward looking macro indicators for just over a year, I made a shift. Not into some “factor ETF of the month” — but into something I can control and oversee myself: an adaptive, macro-aware, multi-strategy system.
And since I had to look up most of these terms when I first read about them, let’s unpack that.
Dynamic Allocation Strategy
Step One: Adding a Macro Brain
Instead of guessing where markets are going (which is what most “macro” really means), I wanted to built a system that responds to where markets are. A macro-aware investor systematically adjusts sector weights and asset classes based on leading (!) economic indicators and current market momentum. That means I would want to
- Rotate between global asset classes based on real momentum.
- Tilt between risk-on and risk-off based on macro signals (yep, bond performance does matter).
- Factor in volatility, drawdown probabilities, and… structural imbalances no ETF brochure dares to mention.
And as I know myself very well, I wanted to build a system that prevents me from overtrading and trying to time tops and bottoms in the market by design.
Step Two: Diversifying the Logic
We remind ourselves constantly: “Diversification is good”. At the same time, we rarely question what this means beyond buying the broadest ETF baskets we can find.
After evaluating different portfolio strategies and investment guidelines, I felt it was not enough to diversify what I hold. I wanted to diversify the decision making of how I decide what I hold. And after giving it a try using rather seemingly random rules that I applied manually in a Scalable Capital account, I decided to give a programmatic approach another try. (I have tried many times before, always over-engineering the applications. Likely just because I liked to tinker with the tech.)
In my current “Shuhari Capital” approach, I run three strategy engines:
- Stability Core – A macro-driven core allocation that leans defensive or aggressive depending on real-world shifts. Think global stocks, bonds, commodities.
- Momentum Chaser – Finds the best-performing global assets, and weights them using inverse volatility. Pure trend, minus the fragility.
- Sector Navigator – Rotates into U.S. and global equity sectors showing relative and absolute strength if they pass trend and volatility sanity checks. (The “strongest among the weak” isn’t good enough.)
My allocation engine includes a Global Macro Tracking Tool that monitors conditions across the U.S., Europe, Japan, China, and Emerging Markets. This dataset includes:
✔ Monetary policy trends
✔ Inflation and real GDP growth
✔ Bond yield curves and credit spreads
✔ Sector-specific growth trends
Step Three: Adding Context, Not Complexity
Before I started coding, I had set up a task list to track what I wanted to work on and log the dependencies. Looking at the various data sources and decision logic, I got a little nervous I would overdo it once again and ditch the application a few weeks later.
But as I worked on each of the three portfolio elements separately, I got to see results on the first one rather quickly and realised: as the portfolio got more adaptive, it actually felt like it got simpler to manage. Quite simply because I could finally stop guessing and started observing. The application does not panic, it does not get jittery about news headlines. I have since slowly allocated around 30% of my total wealth to it and am improving the system, not second-guessing it.
Final Thought
This application (and me writing about it) is not about outsmarting hedge funds and Wallstreet. It’s not about hitting double digit returns every month by taking huge risk. It’s about not underestimating reality and having a part of my total wealth allocated to something in my control and made by my own design.
A dynamic portfolio strategy doesn’t mean excessive trading—it means making informed, quantitative adjustments that align risk exposures with economic conditions.
#DynamicInvesting #Macroeconomics #ETFStrategy #SystematicInvesting
