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Stacking Sats is an open source initiative for building, backtesting, and deploying optimal Bitcoin accumulation strategies for both retail and institutional investors.

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Stacking Sats Docs
Stacking Sats Docs
IntroductionQuick Start
OverviewSignal InterpretationAccumulation StrategiesAssumptions and Limitations
OverviewWeight ComputationFeature ConstructionSignal CompositionDynamic MultiplierModel Constants
OverviewPerformance ResultsSPD CalculationModel ScoreValidation Checks
OverviewAgent APIAgent builder guideGlossaryBitcoin
OverviewContributing
Model

Model

Signal Composition

Explains how weighted signals and modifiers combine into final allocation behavior.

Last reviewed
March 10, 2026

The model combines three primary signals with modifier terms to produce a daily dynamic multiplier.

Primary Signals

SignalWeightDescription
MVRV Value Signal70%Lower valuation tends to increase allocation
MA Signal20%Price below trend tends to increase allocation
4-Year Percentile10%Cycle context adjustment

Signal Modifiers

ModifierEffect
AccelerationBoost/reduce based on momentum shifts
ConfidenceIncreases effect when indicators align
Volatility DampeningReduces exposure in unstable regimes

Final Weight Calculation

For each day, a dynamic factor is applied to a uniform base allocation, then normalized across the window to ensure sums remain 1.0.

Worked Example

Assume a baseline allocation of $100 and the following signal realization:

  • Weighted base signal score: 1.20
  • Confidence modifier: +0.10
  • Volatility dampening: -0.05

Net dynamic multiplier: 1.20 + 0.10 - 0.05 = 1.25

Resulting daily allocation: $100 * 1.25 = $125

For term definitions, see Glossary and Signal Interpretation.

Prerequisites

  • Weight Computation
  • Feature Construction

Next Step

Dynamic Multiplier

Related Pages

  • Model Constants
  • Backtest Model Score
  • Backtest Validation Checks
  • Glossary

Feature Construction

Shows how model features are derived from raw price and MVRV data.

Dynamic Multiplier

Details the dynamic multiplier logic, extreme-zone boosts, and trend adaptation.

On this page

Primary SignalsSignal ModifiersFinal Weight CalculationWorked Example
Stacking Sats Logo

Stacking Sats is an open source initiative for building, backtesting, and deploying optimal Bitcoin accumulation strategies for both retail and institutional investors.

Quick Links

AboutDocumentation

Connect

DiscordDiscordXX (Twitter)LinkedInLinkedInGitHubGitHub
© 2024 Stacking Sats. All rights reserved.
PrivacyPrivacy Policy•TermsTerms of Service