QCM NexusOne Insight # 11

NOVEMBER 2025

Aref Karim - Ershadul Haq - Raami Karim

BUILDING COHERENCE WITH SIGNALS

HOW DISPARATE SIGNALS FORM A STRATEGY

The Paradox of Complexity

In modern markets, data is everywhere: prices, flows, sentiment, volatility, macro indicators, policy expectations, and even the weather. Each data stream carries some fragment of truth, yet on its own, it rarely tells the whole story. The challenge for systematic managers is not finding information but turning it into insight –– filtering noise, reconciling contradictions, and distilling coherence from complexity.

Markets are multi-dimensional systems. A single signal may capture a trend, another might highlight a mean-reversion opportunity, a third could flag changes in risk appetite or liquidity. On their own, each signal offers a partial view, a single note in a larger composition. The art of systematic investing lies in orchestrating those notes so that the group produces harmony rather than dissonance.

From Fragments to Framework

A robust strategy does not rely on any one signal, but on the interplay between many. Each model, dataset, or idea is a lens revealing one aspect of market behaviour while missing others. By combining multiple perspectives, a portfolio can achieve balance across timeframes, conditions, and sources of risk. However, simply adding more signals does not automatically produce diversification. Coherence requires structure. Signals must complement, not necessarily compete. They should capture different edges: one directional, another mean-reverting, a third regime-sensitive. These must be scaled so that no single behaviour dominates.

This is why signal design is both an analytical and philosophical process. It requires understanding what each signal is truly measuring such as momentum, mispricing, volatility compression, carry, positioning, and how it interacts with others. The goal is not to find perfect forecasts, but to blend imperfect ones so that their combined output is more stable, adaptive, and self-correcting.

The Architecture of Integration

In a systematic framework, coherence is achieved through a series of layers, each responsible for translating raw information into actionable portfolio decisions.

At the foundation are signal layers: quantitative rules that convert data into direction or conviction. These may include price-based indicators, macro-fundamental measures, or sentiment-driven variables. Each is tested for persistence, reliability, and interaction with others.

Above this sits the integration layer where signals are combined through weighting schemes, filters, and correlation structures. The objective is not simply to maximise returns, but to stabilise the portfolio. Signals that overlap too much in behaviour are normalised or reduced; those that add diversity are amplified.

Finally, the portfolio construction layer enforces coherence at the portfolio level — ensuring that aggregated exposures across asset classes, geographies, and strategies reflect intended risk budgets, not statistical noise.

Coherence, in other words, is engineered and not assumed.

The Power of Disagreement

Ironically, coherence often arises not from agreement, but from disagreement. Signals that occasionally diverge are what make a system robust. When one model underperforms in a regime it was not built for, another often compensates. The result is smoother returns and more consistent behaviour through cycles. This concept mirrors the principle of biological ecosystems: diversity breeds resilience. In markets, where change is constant, strategies that rely on uniformity or a single dominant driver are inherently fragile. A coherent system is not one where everything moves in lockstep — it is one where differences coexist productively within an overarching structure.

Coherence Without Correlation

There is a subtle but important distinction between coherence and correlation. Correlation is statistical; coherence is structural. Correlation can tell you that two signals tend to move together. Coherence tells you why and whether that relationship strengthens or weakens the system.

Systematic coherence is achieved when the behaviour of individual components, even when independent, contributes predictably to the portfolio’s broader goals. It is less about convergence of views and more about consistency of purpose: every signal, every exposure, every layer working toward the same goal –– stable, risk-efficient returns across regimes.

NexusOne Insight: Converting Complexity into Clarity

At QCM’s NexusOne, coherence is the foundation of design. Our approach integrates diverse signals — macro, momentum and mean-reversion, volatility and convexity, cross-asset correlations and regime transitions — into a single, adaptive framework. Each signal brings its own perspective; none is treated as absolute. Instead, the system learns from the interactions — how different forces amplify or offset one another across time and market states. Liquidity, volatility, and diversification constraints ensure that the result remains both balanced and executable in real markets.

This is what transforms a collection of models into a strategy –– and a strategy into a philosophy. Coherence is not about simplicity; it is about clarity. It is the process of turning a complex world into a structure that can withstand.

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For informational purposes only. Not investment advice or an offer to invest.