TU AI Model — AI-Generated Analysis and Scenario Framework

Some analytical sections on Traders Union may include AI-generated technical commentary and structured scenario outputs (“TU AI Model”). These materials are automatically generated for informational and educational purposes only and do not constitute investment advice, trading recommendations, or an offer to buy or sell any financial instrument.

The TU AI Model is designed to help users interpret market structure, technical indicator readings, and liquidity dynamics in a standardized format. It does not execute trades, manage portfolios, or provide personalized financial guidance.

• Data Inputs Used by TU AI Model

  The TU AI Model generates its outputs based on structured market data and technical signals available at the time of calculation. Inputs may include:

  Technical Indicator Layer

  • Moving averages (EMA/SMA across multiple periods)
  • RSI, MACD, momentum indicators
  • VWAP anchors (monthly/quarterly)
  • ATR-based volatility measures
  • Volume profile and trend structure analysis

  Liquidity and Derivatives Overlay (when available)

  To improve structural context, the model may incorporate liquidity and positioning metrics from trusted third-party providers such as Coinglass and similar platforms, including:

  • Liquidation heatmap clusters (long/short concentration zones)
  • Estimated liquidation trigger levels
  • Open interest dynamics and funding rates
  • Order book depth and bid/ask imbalance indicators
  • Long/short ratio metrics
  • Exchange inflow/outflow.
  • Options open interest concentration and expiry-related levels
  • Max pain thresholds and qualitative gamma regime classification

  These inputs are used to identify potential volatility zones, liquidity compression areas, and key support/resistance clusters. Traders Union does not guarantee the completeness or precision of third-party liquidity datasets.

• Scenario Probabilities and Market Bias

  The TU AI Model may present probability-weighted scenario distributions (Bullish / Bearish / Neutral). These probabilities are generated through an internal scoring framework that aggregates:

  • Trend and momentum structure
  • Volatility regime conditions
  • Proximity to liquidity and liquidation zones
  • Derivatives positioning context
  • Institutional and ETF flow direction (when available)

  Scenario probabilities represent model-based likelihood estimates, not predictive certainty, and should be interpreted as analytical context only.

• Forecast Update Policy

  AI-generated forecasts are updated under a structured versioning framework. Each update creates a new forecast version.

  Forecasts are refreshed on a rolling basis at least once every 7 days. An earlier update may occur if key scenario levels (such as target or invalidation levels) are confirmed.

  To ensure consistency and reduce noise during volatile market conditions, predefined validation rules are applied before any regeneration is triggered.

  Each new version incorporates the context of the previous forecast. Scenario changes are made only when supported by meaningful market developments.

  Scenario levels are validated using consistent price confirmation rules designed to reduce intraday noise and false breakouts.

• Trade Plan Blocks and Risk Parameters

  Some pages may display structured scenario-based trade frameworks, including:

  • Entry zone estimates
  • Stop-loss reference levels
  • Target projections
  • Risk/Reward ratios
  • Invalidation conditions
  Important Notice:

  Trade setups are illustrative analytical examples, not actionable signals. Any trade plan, entry level, stop-loss, target, or risk/reward metric shown by the TU AI Model is a scenario-based analytical structure and must not be interpreted as a recommendation, instruction, or solicitation to trade.

  Users remain solely responsible for all trading decisions and risk management.

• Alternative AI Model Commentary

  In some cases, Traders Union may display additional AI-generated interpretations (“Alternative AI Model Predictions”) that summarize the same structured dataset from different model perspectives. Variations between models may occur due to differences in:

  • Indicator weighting
  • Volatility sensitivity
  • Scenario threshold calibration
  • Risk interpretation logic

  Such alternative outputs remain informational and probabilistic in nature.

  Alternative AI Model Predictions are displayed for comparison purposes only and do not affect the TU AI Model’s Overall Bias, signal, or Trade Plan.

• Limitations and Model Risk Disclosure

  Artificial intelligence and quantitative models are subject to inherent limitations. TU AI Model outputs may be affected by:

  • Incomplete or delayed third-party flow and derivatives data
  • Rapid volatility spikes and liquidation cascades
  • Missing implied volatility or options surface metrics
  • Parameter instability during extreme market events
  • Unpredictable geopolitical or macroeconomic shocks

  AI-generated outputs may be incomplete, inaccurate, or out-of-date, especially in fast-moving markets. No AI model can reliably anticipate all “black swan” events.

• Data Providers (TU AI Model)

  The TU AI Model may use structured market data and analytical inputs from the following third-party providers:

  Multi-Asset Market Data Providers

  Used for real-time and historical price quotes, as well as fundamental indicators:

  Twelve Data	Real-time and historical data for stocks, forex, ETFs, indices, commodities, and cryptocurrencies
  Financial Modeling Prep	Financial statements, valuation ratios, and key company metrics
  Massive.com (ex Polygon.io)	Institutional-grade market data for stocks, options, forex, and crypto

  Cryptocurrency Exchange Reference Feeds

  Used as reference sources for aggregated cryptocurrency market pricing and trading activity indicators.

  Binance MEXC Bybit OKX Gate.io

• Liquidity, Liquidation, and Derivatives Metrics (TU AI Model)

  Used to enhance liquidity structure and positioning analysis:

  • Coinglass — liquidation heatmaps, estimated long/short liquidation clusters, open interest dynamics, funding rates, long/short positioning ratios, exchange flow indicators, and selected order book imbalance metrics
  • Deribit — cryptocurrency options open interest concentration, expiry positioning levels, and max pain reference thresholds

  Public financial reporting sources (including Bloomberg and similar platforms) may also be used to contextualize significant derivatives events, ETF flow developments, or institutional positioning shifts.

  Traders Union does not guarantee the completeness, accuracy, or uninterrupted availability of third-party information.

  Important Notice

  All price forecasts and predictions are provided for informational purposes only and should not be considered as investment advice. Market prices can be influenced by unpredictable events. Forecasts may change based on current market conditions. Traders Union recommends applying proper risk management strategies when making investment decisions.

  © [2026] Traders Union. All rights reserved. No part of this document may be reproduced or transmitted in any form or by any means without the prior written consent of Traders Union. The use, reproduction, or distribution of this methodology or its parts without the express permission of Traders Union is strictly prohibited.