How the Relative Rotation Graph Maps Sector Momentum

Most charting tools answer one question: is this sector going up or down? The Relative Rotation Graph answers a more useful one. Across the entire sector universe, which names are gaining ground relative to the benchmark, and is that momentum accelerating or fading? As of May 2026, sector leadership in US equity markets is both concentrated and shifting, with Technology commanding roughly 35% of the S&P 500 and Energy quietly regaining relevance despite a benchmark weight of only around 3.5%. For investors trying to move beyond qualitative sector views, the challenge is translating momentum observations into specific, defensible allocation weights. This article explains how the Relative Rotation Graph works from the ground up, how its four quadrants map to allocation logic, and how a quantitative model built on RRG signals can translate sector positioning into specific portfolio weights, including a real-world example drawn from May 2026 positioning.

The charting problem the Relative Rotation Graph was built to solve

Open a standard charting platform, pull up the 11 GICS sector ETFs, and the problem becomes apparent within seconds. Each chart shows absolute price movement. None of them, on their own, can simultaneously show how a sector performs relative to a benchmark and whether that relative performance is accelerating or fading. Comparing two sectors requires toggling between ratio charts. Comparing all eleven requires a spreadsheet or an exceptionally good memory.

The MSCI GICS sector framework, jointly developed with S&P Global, defines the 11 official sectors that form the standard universe plotted on the Relative Rotation Graph when analysing US equity market rotation.

Julius de Kempenaer, a Dutch technical analyst, built the Relative Rotation Graph to replace that fragmented view with a single two-dimensional plot of the entire sector universe at once. The tool is now most widely accessed via StockCharts.com, the primary US platform where practitioners, registered investment advisors, and technically oriented portfolio managers use it as a decision-support layer.

The standard US application plots the following SPDR sector ETFs against SPY as the benchmark:

• XLK (Technology)
• XLE (Energy)
• XLF (Financials)
• XLI (Industrials)
• XLY (Consumer Discretionary)
• XLP (Consumer Staples)
• XLV (Health Care)
• XLU (Utilities)
• XLB (Materials)
• XLRE (Real Estate)
• XLC (Communication Services)

The framework extends beyond sectors to factor ETFs, multi-asset rotation, and individual stock selection. But the core use case, and the one that built its following, is this: all eleven sectors on one screen, their relative positioning visible at a glance.

How to read the two axes and what they actually measure

On screen, the RRG looks deceptively simple: a scatter plot with dots and trailing tails. Each dot represents a sector. Each tail traces its recent trajectory. The two axes driving the plot, however, encode distinct information, and the combination of the two tells investors something neither axis can say alone.

RS-Ratio: measuring relative strength vs. the benchmark

The x-axis, called the JdK RS-Ratio, measures whether a sector is currently outperforming or underperforming the benchmark. Both axes are normalised around a value of 100, which becomes the quadrant boundary. An RS-Ratio above 100 indicates outperformance relative to SPY; below 100 indicates underperformance.

The StockCharts ChartSchool RRG documentation provides the canonical technical reference for both axes, detailing exactly how the JdK RS-Ratio and JdK RS-Momentum calculations are constructed and normalised around the 100 centreline that separates quadrants.

This axis tells the investor where a sector stands today. It is a snapshot of the current relative strength relationship, nothing more.

RS-Momentum: measuring whether that lead is growing or shrinking

The y-axis, called the JdK RS-Momentum, measures the rate of change of that relative strength. An RS-Momentum reading above 100 indicates the relative strength trend is strengthening; below 100 indicates it is weakening.

This is where the earlier signal lives. RS-Momentum often shifts direction before RS-Ratio does, which means a sector can still be outperforming (RS-Ratio above 100) while its momentum is already deteriorating (RS-Momentum below 100). Treating that sector as a straightforward overweight, without recognising the fading momentum, is the most common misreading of the tool.

The trailing tail on each sector’s data point shows the recent trajectory, revealing both the direction and velocity of rotation.

A sector can be rising in price while still underperforming the benchmark. The Relative Rotation Graph makes that gap visible by plotting relative, not absolute, performance on both axes.

The four quadrants and the clockwise rotation pattern

The two axes, normalised around 100, divide the chart into four quadrants. Each maps to a distinct phase of the sector leadership cycle.

The characteristic pattern is clockwise rotation: Leading to Weakening to Lagging to Improving and back to Leading. The tail on each sector visualises where on this arc it currently sits.

A transition from Improving to Leading may indicate emerging sector leadership. A move from Leading into Weakening can signal that an outperforming sector is beginning to fade. Sectors in the Lagging quadrant require exceptional circumstances before being considered for overweighting.

Here is where interpretive skill matters: sectors can skip quadrants, reverse direction, or oscillate on quadrant borders. The tail’s direction carries as much information as the quadrant itself. A sector sitting in the Weakening quadrant with a tail curving back toward Leading tells a very different story from one with a tail pointing sharply toward Lagging.

From quadrant signals to portfolio weights: how a quantitative allocation model works

Reading the chart is one step. Turning it into a portfolio is another.

A rules-based RRG allocation model, such as the framework described by Cedric Thompson, CMT, CFA, writing for FXEmpire (developed since 2018), takes the visual information and converts it into specific portfolio weights. The process follows a defined sequence:

1. Observe quadrant positions across multiple RRG timeframes (weekly for medium-term sector allocation decisions, daily for fine-tuning entries and exits).
2. Score each sector based on its quadrant position and tail direction across those timeframes.
3. Compare each sector’s score to its S&P 500 benchmark weight.
4. Set overweight or underweight targets, with Leading and Improving sectors receiving overweight signals and Weakening and Lagging sectors receiving underweight or zero-weight signals.
5. Apply an absolute trend filter as a gate: if a sector’s price sits below its 200-day moving average, the model does not act on a favourable relative signal, regardless of quadrant position.

That final step addresses a well-documented failure mode. A sector can show improving relative rotation while both the sector and the benchmark are declining in absolute terms. The absolute trend filter prevents the model from overweighting a sector that is losing money in real terms just because it is losing less than the index.

Practitioners frequently describe the Relative Rotation Graph as a “visual risk budget,” a way to see and manage how far sector tilts deviate from the benchmark, rather than a forecasting system.

The model was designed to produce clear directional tilts versus the benchmark, not index-hugging allocations. The chart is the input. The portfolio weight is the output.

What the model looks like in practice: Technology and Energy in May 2026

The numbers make the active bet concrete.

In May 2026, the RRG-driven allocation model positions Technology at approximately 49.4%, against a benchmark weight of roughly 35%, an overweight of approximately 14 percentage points. Energy sits at approximately 13.2%, against a benchmark weight of roughly 3.5%, an overweight of approximately 9.7 percentage points.

Each position maps directly to its quadrant logic. Technology occupies the Leading quadrant: high RS-Ratio, strong momentum, consistent with AI-related earnings growth and secular revenue expansion that has driven the sector’s benchmark weight upward from approximately 30-32% in early-to-mid 2025 toward 35% by early 2026. Energy occupies the Improving quadrant: rising momentum, early-cycle characteristics, supported by higher oil prices and strong cash return programmes including buybacks and dividends.

Energy’s move into the Improving quadrant reflects energy sector capital reallocation dynamics that extend beyond domestic supply and demand, with the 2026 Iran embargo reducing available supply, lifting oil prices, and simultaneously directing institutional capital toward energy infrastructure at a pace that reinforces the sector’s rising RS-Momentum reading.

The combination creates what practitioners describe as a “tech and energy barbell,” overweighting the secular growth leader and the cash-rich cyclical improver simultaneously. The portfolio expresses two distinct RRG-validated theses rather than concentration in a single narrative.

A 49.4% Technology allocation is not a passive or benchmark-hugging decision. It is a substantial conviction call. Seeing the RRG logic behind it, and the quadrant signals that produced it, helps investors evaluate whether a similar framework fits their own risk tolerance and process.

A 49.4% Technology allocation amplifies the S&P 500 concentration risk already embedded in cap-weighted index funds, where Goldman Sachs estimates the sector has driven roughly 85% of the benchmark’s year-to-date gain as of mid-May 2026, meaning passive holders are already running a substantial unintentional bet on the continuation of the AI growth narrative before any active tilt is applied.

Where the tool earns scepticism: limitations every RRG user should understand

The Relative Rotation Graph is a relative strength momentum visualisation. It does not generate alpha mechanically. It visualises a momentum signal, and that signal is vulnerable to trend breaks and regime shifts, just like any momentum approach. Three limitations deserve explicit attention:

• False precision near quadrant borders. Small movements in RS-Momentum can be over-interpreted, particularly when a sector oscillates near the 100 line that separates quadrants. Treating minor position changes as meaningful reallocation signals can generate costly overtrading that erodes any relative strength advantage.
• The absolute trend blind spot. This is the most commonly cited practitioner warning. A sector can show “Improving” relative rotation while both the sector and the benchmark are declining in absolute terms. Acting on a favourable relative signal without checking absolute price direction (such as price versus the 200-day moving average) is a documented misuse.

The absolute trend filter addresses a specific failure mode that narrow market breadth data makes visible: when fewer than 60% of S&P 500 constituents trade above their 200-day moving average despite index-level highs, the benchmark’s headline strength is concentrated in a small cohort of mega-cap names, and a favourable relative rotation reading in that environment does not confirm broad-based sector health.

• Similar performance to simpler alternatives. Pure relative strength ranking approaches, which are simpler to implement, tend to produce similar quantitative outcomes to RRG-based models. The broader relative strength rotation literature, including work from the CFA Institute Research Foundation and Research Affiliates, confirms that momentum-based sector rotation has historically shown the ability to improve risk-adjusted returns in certain sample periods but carries higher turnover, trading costs, and meaningful underperformance risk in sideways or mean-reverting markets. RRG’s primary differentiated value lies in visualisation, communication, and behavioural adherence to a rules-based process, not in generating a uniquely superior signal.

Investors who embed the tool within a broader process, one that includes absolute trend filters, explicit position sizing limits, and realistic cost assumptions, are using it as its creator and most experienced practitioners intend. Those who treat it as a standalone timing system are likely to encounter each of these failure modes in practice.

RRG as a structured language for sector conviction, not a crystal ball

The Relative Rotation Graph does not predict which sectors will lead. It makes the current state of relative momentum legible in a consistent, actionable format that supports more disciplined allocation decisions. That distinction matters.

The tool’s value compounds when embedded in a process that includes multiple RRG timeframes, benchmark weight comparisons, absolute trend confirmation, and explicit position sizing logic. The May 2026 Technology and Energy positioning illustrates how such a process translates RRG signals into specific, defensible weights rather than vague directional views.

Sector leadership shifts continuously. The clockwise rotation pattern gives investors an early-warning system for when today’s leaders may be beginning to fade, which is arguably more valuable than confirming what has already happened. Investors exploring the framework for the first time can access the tool on StockCharts.com, where Julius de Kempenaer publishes ongoing sector rotation analysis using the US SPDR sector ETFs plotted against SPY.

For investors wanting to understand when the Technology overweight would be challenged, the conditions for sustained sector broadening identified by Wolfe Research are more demanding than a single macro catalyst: material bond yield compression below 4.25% held over multiple quarters, confirmed Iranian supply increases, and earnings beats from sectors outside the top 25 mega-caps would need to coincide before rotation away from AI-linked growth stocks becomes durable.

This article is for informational purposes only and should not be considered financial advice. Investors should conduct their own research and consult with financial professionals before making investment decisions. Past performance does not guarantee future results. Financial projections are subject to market conditions and various risk factors.