A Smarter Way To Manage Risk Right Now

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Recently, a piece of global debt data stood out to me. Not because it signals an immediate market event, but because it helps explain the kind of market environment investors are navigating.

According to the International Monetary Fund, six of the seven largest developed economies now carry government debt equal to or greater than their annual economic output. In the United States, total debt is near $38 trillion, roughly 125% of the gross domestic product (GDP). Net interest payments are approaching $1 trillion per year, making interest one of the largest components of federal spending.

Japan’s situation is even more pronounced. Government debt exceeds 200 percent of the GDP, and after decades of near zero interest rates, the Bank of Japan has begun tightening policy. When Japanese bond yields rose recently, U.S. Treasury yields moved higher as well. Large capital markets are connected, and changes in one do not remain isolated.

High debt levels do not automatically cause recessions or market crashes. Their primary effect is constraint. Rising interest costs reduce policy flexibility and gradually work their way into higher borrowing costs for businesses, consumers, and homeowners. Growth slows at the margin, and markets become more sensitive to uncertainty.

This is not a short-term trading signal. It is a structural backdrop.

That backdrop is precisely why I developed an indicator.

Markets move through cycles of expansion, contraction, fear, and complacency. Structural pressures like elevated debt levels tend to increase volatility and reduce predictability over time.

Rather than relying on long-term forecasts or assuming stable conditions will persist, our work focuses on identifying when risk and volatility are being mispriced in the present.

The indicator I developed was designed to function across market environments. It has been applied successfully in periods of rising rates, falling rates, high volatility, low volatility, strong growth, and economic stress. It is used to support both put selling strategies and short-term stock trading, where risk is defined and capital is not committed indefinitely.

Instead of depending on long duration positions that require years of favorable outcomes, the approach emphasizes flexibility. Trades are structured around current conditions, not long-term assumptions. When conditions change, exposure adjusts.

The global debt picture matters because it increases the likelihood of uncertainty over time. Our response is not to predict how that is resolved, but to manage risk in a way that does not depend on long term outcomes being right.

That is the foundation of the indicator and the strategy built around it. It is not a reaction to headlines. It is a disciplined framework designed to operate in a market with less margin for error than in past cycles.


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Samuel Rowland 1 hour ago Member's comment
This is a thoughtful framework, especially the distinction between debt acting as a constraint rather than a direct trigger. That resonates, particularly the idea that higher debt levels create an environment with less margin for error rather than an immediate catalyst for market stress.

I’m curious about the indicator itself and how you distinguish moments when risk is being mispriced versus periods where volatility is simply low. In practice, what are the observable inputs that tell you risk is under- or over-compensated in the present?

A few points I’d love more clarity on: is the indicator primarily driven by volatility measures like implied versus realized volatility, term structure, or skew, or does it also incorporate cross-market signals such as rates, credit, or FX relationships? How does it behave during regime transitions, when volatility shifts abruptly rather than gradually? And since you mention it functioning across both rising and falling rate environments, what specifically tells you that conditions have changed enough to warrant adjusting exposure?

I really appreciate the emphasis on flexibility over long-duration conviction. Understanding how that flexibility is actually operationalized would be incredibly helpful.