Model
Overview
Start here if you want the cleanest route through the model stack, from conceptual framing to weight composition and validation context.
Model section
Understand how the daily signal is assembled
The model section explains how Stacking Sats turns strategy context and market-derived features into a daily scaling signal while keeping the one-year budget window coherent.
App usage: Sign-in, profile plan, and personal API tokens are covered in Quick Start.
Recommended Reading Order
Core mechanics
Weight computation
Start with the model inputs, invariants, and the baseline weight logic that anchors everything else in the system.
Read weight computationSignal assembly
Signal composition
Continue into the weighted-signal construction once the baseline weight and constraints are clear.
Read signal compositionInputs and context
Feature construction
Use the feature-construction page for the data engineering and feature pipeline context behind the model inputs.
Read feature constructionThen Read
- Read Dynamic Multiplier to understand thresholding and scaling behavior.
- Read Model Constants to find fixed defaults, ranges, and hard constraints.
- Jump to Backtest Overview once you want validation results rather than more mechanism detail.