Tradelytics Macro Market Regime Vector

Objective

The Macro Market Regime Vector converts the structural macroeconomic environment observed during the preceding 90 days into a standardized 8-dimensional numerical representation.

Its purpose is to identify historical periods in which the underlying macroeconomic conditions most closely resemble those prevailing today.

The model focuses on six major macroeconomic forces: interest rates, inflation expectations, energy prices, credit conditions, gold and the U.S. dollar.

These forces are represented through eight quantitative components. Historical 90-day periods with the smallest weighted distance from the current macro environment are identified as the strongest historical regime analogues.

Why These Macro Symbols?

Symbols	Macro Regime Information
IEF, TLT	Intermediate-term and long-duration U.S. Treasury securities help capture changes in interest-rate conditions, duration behavior and monetary-policy expectations.
TIP	Inflation-protected Treasury securities are compared with nominal Treasuries to capture changes in inflation-sensitive and real-rate conditions.
HYG, LQD	High-yield and investment-grade corporate debt help identify changes in credit conditions, financing stress and the relative willingness of investors to assume credit risk.
USO	Oil captures changes in energy prices associated with global demand, supply constraints, geopolitical developments and inflationary pressure.
GLD	Gold helps capture changes in real-rate expectations, inflation concerns, geopolitical uncertainty and demand for defensive stores of value.
UUP	U.S. dollar strength reflects relative monetary conditions, global liquidity, capital flows and demand for dollar-denominated assets.

Metrics and Weighting

Each raw macro component is converted to a historical Z-score and capped between -3 and +3 standard deviations.

This allows components with different natural scales to be compared consistently while limiting the ability of extreme observations to dominate the regime classification.

The eight component weights total 100%. Greater weight is assigned to the factors considered most important in defining the prevailing macroeconomic environment.

Macro Factor	Components	Total Weight	Reasoning
Interest Rates	TLT - IEF Return IEF Return	35.71%	Provides the largest influence because interest-rate conditions affect financing costs, discount rates, investment activity, asset valuation and monetary-policy transmission across the economy.
Inflation Expectations	TIP - IEF Return	18.57%	Helps distinguish inflationary, disinflationary and real-rate regimes by comparing inflation-protected and nominal Treasury behavior.
Energy Prices	USO Return	15.71%	Captures energy-driven inflation, global demand conditions, supply shocks and geopolitical pressure.
Credit Conditions	HYG - IEF Return HYG - LQD Return	17.14%	Measures changes in financing stress, corporate credit quality and the relative pricing of risky debt versus government and investment-grade debt.
Gold	GLD Return	7.14%	Adds information about real-rate expectations, inflation concerns, monetary confidence and defensive demand.
U.S. Dollar	UUP Return	5.71%	Captures relative monetary conditions, global liquidity and cross-border capital-flow pressure.
Total		100.00%

8 Macro Vector Components

#	Component	Weight
1	TLT - IEF Return	25.71%
2	IEF Return	10.00%
3	TIP - IEF Return	18.57%
4	USO Return	15.71%
5	HYG - IEF Return	11.43%
6	HYG - LQD Return	5.71%
7	GLD Return	7.14%
8	UUP Return	5.71%
	Total	100.00%

How the Macro Vector Is Standardized

The eight macro components operate on different numerical scales. Tradelytics therefore converts every component to a historical Z-score:

Normalized values are capped between -3 and +3 standard deviations. This reduces the ability of exceptional observations to dominate the overall macro-regime comparison.

Constructing the Weighted Macro Vector

Each normalized macro component is multiplied by the square root of its assigned weight:

The resulting eight weighted components form the Macro Market Regime Vector.

Using the square root of the weight is intentional. When Euclidean distance is calculated, the squared difference becomes:

Each macro component therefore influences historical regime similarity according to its intended economic importance.

How Historical Macro Regime Similarity Is Determined

The most recent complete 8-component Macro Regime Vector becomes the target regime.

Every complete historical vector whose 90-day period ended before the current target 90-day period began is eligible for comparison. This deliberately prevents overlap between the current regime and historical candidate periods.

A weighted distance near zero represents a highly similar macro regime. Historical observations are ranked by ascending distance, or equivalently by descending similarity score.

An identical macro vector produces a similarity score of 100. Increasingly different macro environments produce progressively lower scores.

How This Improves Backtest Selection

The matched historical date identifies a 90-day period whose underlying macroeconomic conditions immediately preceding that date resemble the 90 days preceding the current date.

That date can then be used as an anchor into the historical backtest data. Instead of evaluating every historical segment equally, Tradelytics can examine portfolio and strategy behavior following historically similar macroeconomic starting conditions.

For example, if the current combination of interest rates, inflation expectations, energy prices, credit conditions, gold and U.S. dollar behavior closely resembles a historical 90-day window, the subsequent 90-day, 180-day, 270-day and longer backtest performance following that historical regime becomes particularly relevant.

This allows portfolio construction and strategy selection to be informed by conditional historical evidence—what happened after macro environments resembling the current one—rather than relying only on unconditional historical averages.

Interpretation

A high Macro Regime Similarity Score indicates that the weighted combination of interest-rate conditions, inflation expectations, energy prices, credit conditions, gold and U.S. dollar behavior was collectively similar during the historical period.

It does not mean that every individual component was identical. A historical regime can remain a strong overall match even when one component differs, provided the weighted macroeconomic environment remains sufficiently close.

The similarity score is not a probability, forecast or guarantee that subsequent market performance will repeat. It measures similarity of the starting macroeconomic environment.

Model: 8 Structural Macro Components | 90-Day Regime Window | Component Weights = 100% | Z-Score Standardization | Weighted Euclidean Distance