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Target Tracker [TT] & AI Price Target Guide

Understand the critical difference between the Target Tracker [TT] metric and the AI Target [Ai] projection. Learn how to use these metrics to identify asymmetric risk-reward trading setups.

🎯 4.1 What is Target Tracker (TT)?

Target Tracker (TT) is a dynamic distance metric displayed on every stock card (e.g. [TT +8.4%]). It represents the exact percentage remaining between the current live market price and the algorithmic take-profit target.

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Positive Distance (e.g. +8.4%)

The stock is currently trading below its algorithmic target. The positive percentage indicates remaining upside potential before reaching resistance.

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Negative Distance (e.g. -2.1%)

The stock has exceeded its initial target price or is experiencing a sharp pullback below support levels.

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N/A (Target Reached / Neutral)

The asset has consolidated at target equilibrium, indicating no active open trade target at this moment.

🎛️ 4.2 Interactive Target Tracker Calculator

Test the Target Tracker formula directly in your browser. Enter any hypothetical market price and target price:

🎯 Live Target Distance Calculator
Interactive Tool
Calculated Target Tracker Output
TT +9.6%
Trade Management Analysis: Price has +9.6% ($12.50) remaining upside before hitting resistance. Favorable asymmetric setup.

🤖 4.3 What is AI Target [Ai]?

While Target Tracker (TT) reflects the strategy take-profit point, AI Target [Ai] is the direct probabilistic output of the Google TimesFM 2.5 neural foundation model at the selected forecasting horizon (e.g. [Ai +12.6%] for 7 Days).

🧠 How AI Target Is Calculated

The AI Target represents the expected median price return projected by the Google TimesFM 2.5 neural network. It compares the model's central probabilistic price projection against the current live market price, giving you a clear statistical growth forecast based on machine learning rather than subjective guesswork.

⚖️ 4.4 Target Tracker vs AI Target Differences

Feature Target Tracker (TT) AI Target [Ai] (Q50)
Origin Algorithmic strategy Take-Profit calculation. Google TimesFM 2.5 Neural Foundation Model.
Purpose Actionable trade management & execution level. Objective probabilistic trajectory projection.
Short Position Behavior Reflects profit potential on downside exits. Always reflects raw price direction (negative for drop).
When It Decays Decreases as price approaches target. Updates dynamically with live price movements.

💡 4.5 Spotting High-Probability Setups

When screening the Dashboard or Leaderboard, look for the following powerful confluence pattern:

Step 1: High Confidence Signal

Look for stocks displaying a strong BUY 80%+ badge under the 7D or 14D horizon.

Step 2: Aligned Target Tracker & AI Return

Verify that both TT (e.g. +6% to +10%) and Ai (e.g. +8% to +15%) are strongly positive.

Step 3: Favorable Risk-Reward Ratio (P10 vs P90)

Open the Detail Screen and check the Forecast Chart. Ensure the upside ceiling (P90) is at least 2.5x to 3x greater than the downside floor (P10).

Step 4: Execute Simulated Position

Tap TRADE and enter your simulated position with a clearly defined risk limit based on the P10 floor!

🔍 ESC