Beyond the Quadrant: A Risk-On/Risk-Off Framework for a Fragmented World
Macro Insights
QuantCube’s latest insights into systematic asset allocation and risk management
Summary
Systematic macro strategies often begin with a simple intuition: asset returns are driven by the interaction between growth and inflation. Our Macro Regime Quadrant was built on that foundation. By classifying the environment according to growth and inflation momentum, we developed multi-asset rotation strategies capable of adapting to cyclical dynamics – risk-on in reflation, defensive in growth slowdowns, constructive on duration in disinflation.
This framework has proved effective. By relying on our real-time nowcasts rather than lagging official data, the Quadrant has consistently anticipated regime shifts. As discussed in August 2025 (Mispricing Stagflation: What Markets Got Wrong About Trump 2.0), it correctly signalled a risk-on stance following Liberation Day in April 2025, identifying economic resilience rather than a transition to stagflation.
However, the Quadrant does not directly adjust to geopolitical shocks. In an environment where international tensions can reprice markets overnight, it is worth complementing the macro signal with an additional risk overlay. This is where our Risk-On/Risk-Off framework extends the model. Rather than relying solely on quadrant classification, it integrates macro momentum with a dedicated geopolitical risk layer. The objective is straightforward: to provide a broader, real-time assessment of global risk conditions.
The Macro Core: Growth and Inflation Momentum
The macro backbone of the strategy remains disciplined, and data-driven.
On growth, we now rely exclusively on our China GDP Leading Indicator. Empirical testing shows that China provides the most forward-looking signal for the global industrial and trade cycle, reflecting its role as a marginal driver of global manufacturing, commodities, and supply chains.
On inflation, we retain our US inflation nowcast. Despite recurring debates about dollar dominance, the Federal Reserve remains central to the global monetary cycle. US inflation momentum therefore continues to anchor global financial conditions.
For both variables, momentum – not levels – is what matters.
We compute a 20-day rolling slope to capture trend rather than noise. Daily year-on-year changes are evaluated across progressively longer horizons within the window, placing greater weight on recent dynamics. Each observation is clipped into a binary signal (positive or negative) and averaged, producing a smoothed momentum score between 0 and 1.
Importantly, rising inflation is treated as supportive for risk when it reflects demand strength rather than supply disruption - unless offset by other factors.
The Geopolitical Layer: Capturing Shock Risk
The key innovation lies in the integration of a geopolitical factor.
We aggregate geopolitical risk indicators across the 16 largest global economies, standardised over a one-year rolling window. Given the immediacy of geopolitical shocks, we apply a shorter five-day momentum measure. Changes are calculated, inverted (so rising risk is negative), clipped, and averaged (Exhibit 1).
The resulting score captures short-term geopolitical momentum aligned with typical market reaction functions.
From Signals to Allocation
Each day, the model computes the average of three components – China growth momentum, US inflation momentum, and geopolitical momentum.
The composite score ranges between 0 and 1. A threshold of 0.1 determines the regime:
Above 0.1: Risk-on
Below 0.1: Risk-off
The relatively low threshold reflects the structurally positive bias of US equity markets over long horizons. The strategy is implemented via S&P 500 futures, with the objective of outperforming the benchmark on a risk-adjusted basis.
Risk Management: Signal and Volatility Discipline
Risk control operates at two levels.
First, exposure adjusts directly to the signal. A shift to risk-off reduces equity allocation; capital is not rotated into alternative assets.
Second, a volatility target is applied. Realised annualised volatility is calculated over a 10-day window. If observed volatility exceeds the target, exposure is proportionally scaled down. No leverage is applied when volatility is below the target.
Lower volatility targets materially reduce drawdowns without significantly impairing Sharpe ratios. For example, reducing the target from 20% to 10% lowers maximum drawdown by approximately 10 percentage points while preserving risk-adjusted performance.
Empirical Performance and Regime Detection
Between 2021 and 2026, the strategy generated higher Sharpe ratios than the S&P 500 benchmark, with volatility control limiting drawdowns during geopolitical stress periods (Table 1).
As Exhibit 2 illustrates, the model successfully identified major risk-off inflection points, including the 2022 Russian invasion of Ukraine, and the April 2025 Liberation Day escalation. In both episodes, geopolitical momentum offset otherwise constructive macro signals, preventing premature risk-on positioning.
Strengths – and a Key Limitation
The advantages are clear:
Daily macro-driven signals
Explicit geopolitical integration
Institutional volatility targeting
Capital-efficient futures implementation
Meaningful drawdown mitigation
The main limitation lies in interpreting inflation momentum. Rising inflation may reflect healthy demand – or emerging stagflation. In 2022–23, this ambiguity was resolved because inflation acceleration coincided with rising geopolitical risk, preventing false risk-on signals. Without the geopolitical layer, the model would have been more exposed to misclassification.
Conclusion
In an increasingly fragmented world, risk cannot be understood through growth and inflation alone. By combining macro momentum with geopolitical dynamics, this new framework moves beyond the Quadrant toward a more adaptive definition of risk – one designed for markets shaped as much by political shocks as by economic cycles.
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