A Stock-to-Flow model for Bitcoin and Litecoin that calculates price projections based on asset supply, providing long-term trend insights using daily timeframe analysis.
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The Stock-to-Flow (S2F) model calculates the ratio between total existing cryptocurrency supply and annual new supply generation. It uses daily data from sources like Glassnode to track circulating supply and new coin creation for Bitcoin and Litecoin.
By applying a customizable multiplier, the model projects potential price trajectories based on the scarcity principle. The 500-day moving average smooths these projections, offering a more stable long-term perspective on potential asset valuation trends.
Why it may be useful
The S2F model provides traders with a unique framework for understanding cryptocurrency valuation based on fundamental supply dynamics. It offers insights into potential long-term price movements by quantifying asset scarcity and projected supply constraints.
By integrating supply-side economic principles, the model helps investors assess potential future value beyond traditional technical analysis. It serves as an educational tool for understanding how limited supply might influence cryptocurrency price discovery and market behavior.
When to explore it
The S2F model is most effective for long-term strategic investment analysis, particularly for swing traders interested in macro trend perspectives. It works best when applied to daily timeframes and used in conjunction with other fundamental and technical analysis methods.
Traders should utilize this model as a supplementary tool for understanding potential long-term price trajectories, recognizing it as an exploratory framework rather than a definitive predictive mechanism. It is most valuable for investors seeking broader market insights beyond short-term price fluctuations.
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What we’ve verified
Access, alerts and repainting behaviour have not been independently verified for this indicator. Check the creator’s current publication and settings.
General descriptions and classifications are recovered research. Verified details above identify the specific checks we have completed. Check the creator’s current publication for later changes.
