Multi-Pillar Signal Aggregator

Overview

This meta-pillar synthesizes outputs from fundamental, technical, and sentiment analyses into a single, weighted consensus score. It's designed to reduce noise and provide a holistic view, identifying high-conviction opportunities where different analytical methods agree.

What It Does

The Multi-Pillar Signal Aggregator combines the predictive outputs of various other pillars you select. It applies a user-defined or dynamically calculated weight to each input signal, then normalizes and combines them. The result is a unified probability vector and a divergence score that measures the level of agreement between the source analyses.

Why It Matters

Relying on a single type of analysis can create blind spots. This pillar provides a 'wisdom of the models' effect, smoothing out individual biases and confirming signals across different domains. This diversification of analytical sources leads to more robust and reliable predictions.

How It Works

First, you select the active pillars you want to include for a specific market, such as Social Sentiment, Technical Momentum, and Insider Trading. Next, you assign a weight to each pillar based on its historical reliability or your confidence in its relevance. The aggregator then calculates a weighted average of the input signals to produce a final consensus score.

Methodology

The core calculation is a weighted average: Consensus Score = Σ (Pillar_Signal_i * Pillar_Weight_i) / Σ Pillar_Weight_i. Input signals are normalized to a common scale (e.g., 0 to 100) before aggregation. It also calculates a Signal Divergence Score, often using the standard deviation of the weighted input signals, to quantify disagreement among sources.

Edge & Advantage

Its edge comes from identifying consensus across fundamentally different analytical approaches. When social media hype, on-chain data, and financial models all point to the same outcome, the conviction level is significantly higher.

Key Indicators

• Consensus Strength

  high

  The magnitude of the final aggregated score, indicating how strongly the combined signals point to a specific outcome.

• Signal Divergence Score

  high

  Measures the disagreement between the input pillars. A high score suggests conflicting signals and higher uncertainty.

• Weighted Probability Output

  medium

  The final probability assigned to the 'Yes' or 'No' outcome after aggregating all weighted inputs.

Data Sources

• Internal Pillar Data

  This tool does not use external data directly; instead, it processes the output from other activated analysis pillars within the platform.

Example Questions This Pillar Answers

• → Will the S&P 500 close above 5500 by the end of the year?
• → Will the next Federal Reserve meeting result in a rate cut?
• → Will Ethereum's price surpass $5,000 in the next 6 months?

Tags