Background & Summary
Bitcoin is a peer-to-peer electronic payment system that has gained immense popularity in recent years. As a distributed ledger technology (DLT), Bitcoin records transactions in a decentralized manner, eliminating intermediaries like banks and reducing transaction costs.
Bitcoin relies on unspent transaction outputs (UTXOs) to verify new transactions efficiently. UTXOs can be generated as block rewards or transaction outputs. Block rewards are newly minted bitcoins (BTC) distributed to miners for maintaining the network. All UTXOs trace back to block rewards, with timestamps recorded at creation and spending.
Key Concepts:
- UTXO: Unspent transaction output (like a "live" bitcoin).
- STXO: Spent transaction output (a "used" bitcoin).
- Age of UTXO: Time elapsed since creation.
- Lifespan of STXO: Time between creation and spending.
Cohort Analysis Approach
We apply cohort analysis—originally used for population data—to Bitcoin blockchain data:
- Birth Cohort: UTXOs created on the same day.
- Death Cohort: UTXOs spent on the same day.
- Age/Lifespan Cohorts: Groupings based on UTXO age or STXO lifespan.
This framework reveals insights into Bitcoin’s economic functions:
- Store of Value: Long-held UTXOs (e.g., 11.5M BTC inactive >1 year).
- Medium of Exchange: Frequently transacted UTXOs (e.g., 2.2M BTC aged <1 month).
Methods
Data Processing Workflow
- Data Retrieval: Query Bitcoin transaction data (~45 GB processed from 1.3 TB raw data) using Google BigQuery.
- Partitioned Tables: Split data by creation/spending dates for efficient cohort analysis.
Cohort Metrics:
- Weighted Average Lifespan (WAL) of STXOs.
- Age distribution of UTXOs.
- Visualization: Generate time-series charts (e.g., token velocity, supply trends).
Key Formulas:
- WAL:
$$WAL[date=i] = \frac{\sum_{date=i} (\#_{UTXO} \times Lifespan)}{\sum_{date=i} \#_{UTXO}}$$ - Circulating Supply:
$$Supply[date=i] = \sum_{date \le i} \#_{created} - \sum_{date \le i} \#_{spent}$$
Data Records
- Datasets: UTXO and STXO records (2009–2021, daily frequency).
- Format: CSV (<1 MB per file).
- Availability: Published on Harvard Dataverse.
Technical Validation
- Verified block rewards halving pattern (50 BTC → 6.25 BTC per block).
- Circulating supply calculations match external sources (e.g., CoinMetrics).
Usage Notes
Applications:
- Finance: Predict market bubbles, design trading strategies.
- Computer Science: Evaluate blockchain scalability/security.
- Macroeconomics: Study policy impacts on crypto transactions.
Limitations:
- Granularity: Daily data; higher frequencies possible (e.g., per-block).
- Dust UTXOs: Small, uneconomical-to-spend outputs skew age metrics.
- UTXO vs. Account Models: Cohort methods here apply only to UTXO-based chains (e.g., Litecoin).
Code Availability
- GitHub: UTXO Cohort Analysis Toolkit.
- License: GPL-3.0.
FAQs
1. What is a UTXO?
A UTXO (Unspent Transaction Output) is a discrete Bitcoin amount that hasn’t been spent yet, serving as the basic unit of transaction verification.
2. How does cohort analysis help study Bitcoin?
It groups UTXOs by creation/spending dates (cohorts) to analyze behavioral patterns—like how long users hold BTC (store of value) or transact frequently (medium of exchange).
3. Where can I access the datasets?
👉 Download UTXO/STXO datasets here from Harvard Dataverse.
4. Can this method analyze Ethereum?
No—Ethereum uses an account-based model. Future research may adapt cohort analysis for such chains.
5. What’s the significance of BTC’s "dust" outputs?
Dust refers to tiny UTXOs (<0.0001 BTC) often left unspent due to high fees. They inflate age metrics but don’t necessarily indicate storage behavior.
👉 Explore Bitcoin transaction trends with our interactive tools.
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