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Model tool

Macro Model

Review the 12-month macro backdrop through regime probabilities, Net Score, model confidence, and a scenario-weighted Macro Expected Value.

Last updated: 2026-06-02 · TradingSimuLab Research Team
Educational disclaimer: TradingSimuLab is an educational research platform. This tool does not provide financial advice, personalized recommendations, trade signals, or guaranteed predictions.
Macro engine

Run a macro model read

Enter a supported stock, ETF, crypto, or forex symbol. The dashboard estimates the current macro-regime distribution and weights four scenario payoffs into a Macro Expected Value.

Enter a symbol and run the Macro Model to generate the dashboard.

How to read the four macro scenarios

The Macro Model converts the current 12-month macro backdrop into four model-labeled scenarios: P(-2), P(-1), P(+1), and P(+2). These scenarios are connected to macro-condition features such as policy rates, inflation, yield-curve shape, credit spreads, and consumer sentiment. They are not direct textbook labels like "recession" or "stagflation", but those types of environments can be reflected when the underlying feature mix points in that direction.

P(-2) Severe Macro Pressure Stress-heavy / risk-off scenario

This is the most defensive macro scenario. It can appear when the model sees pressure across several inputs at the same time: wider credit spreads, sharply weaker sentiment, yield-curve stress, inflation pressure, tighter policy, or a deteriorating macro score.

Example feature mix: credit stress rises, sentiment falls, policy stays restrictive, and the curve backdrop is unfavorable.
P(-1) Weak Macro Backdrop Cautious / lower-quality scenario

This is not necessarily a crisis scenario. It is a weaker macro backdrop where conditions are less supportive: inflation or policy pressure may still be elevated, sentiment may be soft, spreads may be moderately wider, or liquidity and growth conditions may look less favorable.

Example feature mix: a stagflation-like grind can show up here when inflation and policy pressure are high while sentiment and liquidity are weak.
P(+1) Constructive Macro Backdrop Supportive / soft-landing scenario

This scenario reflects a more constructive feature mix. Inflation pressure may be improving, policy pressure may be easing, credit spreads may be contained, sentiment may be improving, and the macro score may point to a healthier 12-month backdrop.

Example feature mix: inflation improves, spreads stay contained, sentiment recovers, and the curve backdrop becomes less restrictive.
P(+2) Strong Macro / Liquidity Backdrop Strongly supportive scenario

This is the most favorable macro/liquidity scenario. It can appear when the model sees a stronger combination of supportive features: tight credit spreads, strong sentiment, a constructive yield-curve backdrop, easing inflation or policy pressure, and a strongly positive macro score.

Example feature mix: liquidity conditions are supportive, sentiment is strong, spreads are tight, and the broader macro score is positive.

The scenario payoff is asset-specific. It measures how the asset historically behaved over the next 12 months after similar model-labeled macro scenarios. This is why a negative macro scenario can still show a positive payoff for some assets if they historically rebounded after similar pressure windows. Macro Expected Value is the probability-weighted blend of the four scenario payoffs, so unusually large Macro EV readings should be inspected through the scenario table rather than only through the headline.

How to read Macro Expected Value

Macro Expected Value is the probability-weighted blend of the four asset-specific scenario payoffs. It combines the estimated probability of each macro scenario with how the asset historically behaved over the next 12 months after similar model-labeled macro conditions.

The four scenarios are P(-2) Severe Macro Pressure, P(-1) Weak Macro Backdrop, P(+1) Constructive Macro Backdrop, and P(+2) Strong Macro / Liquidity Backdrop. Positive Macro EV means the weighted scenario-payoff profile is constructive; negative Macro EV means the weighted payoff profile is weaker.

Macro EV is not the same as Net Score. Net Score summarizes the macro backdrop, while Macro EV combines scenario probabilities with asset-specific historical payoff behavior. It is a deterministic four-scenario macro payoff read, not a Monte Carlo simulation and not a transformation of Net Score.

What this tool does not do

The Macro Model does not forecast with certainty, issue trade instructions, personalize recommendations, or reveal proprietary feature weights. It is designed to add macro backdrop context to the broader TradingSimuLab workflow.

FAQ

What does the Macro Model measure?

The Macro Model reviews macro regime probabilities, scenario-weighted payoff context, Macro Expected Value, Net Score, confidence, and stress-test behavior.

Is the Macro Model a price prediction?

No. It is an educational scenario framework and should not be treated as investment advice, a trade signal, or a guaranteed forecast.

How should Macro Expected Value be used?

It should be compared with timing, trend quality, persistence, and risk simulation rather than used as a standalone conclusion.

Why do macro scenarios matter?

Different assets can behave differently across weaker, neutral, and stronger macro environments, so scenario context helps avoid one-dimensional analysis.

Which assets are supported?

TradingSimuLab supports symbols where sufficient market and model data is available, including many stocks, ETFs, crypto, and forex pairs.

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