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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

Feature Construction

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

Last reviewed
March 10, 2026

The model builds a compact feature set from price and on-chain inputs.

200-Day Simple Moving Average

price_ma200 = price.rolling(200, min_periods=100).mean()
price_vs_ma = (price / price_ma200) - 1

MVRV Z-Score

mvrv_zscore = (mvrv - rolling_mean(365)) / rolling_std(365)

Additional Features

  • 4-year rolling percentile (cycle context)
  • Short-window MVRV gradient (trend direction)
  • Volatility terms used for dampening

Prerequisites

  • Accumulation Strategies
  • Basic familiarity with rolling-window statistics.

Next Step

Signal Composition

Related Pages

  • Weight Computation
  • Model Constants
  • Backtest Overview

Weight Computation

Documents default weight computation inputs, model properties, and behavior.

Signal Composition

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

On this page

200-Day Simple Moving AverageMVRV Z-ScoreAdditional Features
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