Nonato-B1069

Abstract
This paper examines the efficacy of on-chain analysis as a methodology for assessing crypto-assets, specifically Bitcoin (BTC). Unlike traditional financial markets, blockchain networks offer a public and auditable ledger, enabling the extraction of transactional data in real time. This study categorizes and correlates fundamental metrics of market value, miner behavior, and supply-and-demand dynamics. The objective is to demonstrate how the confluence of these indicators can identify structural patterns of accumulation and distribution, providing an analytical framework for understanding market psychology and network efficiency.
---
## 1. Introduction
The emergence of crypto-assets has introduced an unprecedented paradigm in financial analysis: the total transparency of transaction and custody data. While traditional capital markets rely on quarterly reports and opaque order book data, networks like Bitcoin allow for the granular monitoring of every monetary unit since its issuance.
On-chain analysis arises as a discipline that utilizes this raw data to derive signals of network health and participant sentiment. This work proposes a systematization of the primary metrics, dividing them into: (1) Valuation and Profitability, (2) Supply Dynamics, and (3) Network Security and Activity.
## 2. Valuation Metrics and Market Psychology
The evaluation of a digital asset’s price requires a distinction between current speculative value and intrinsic value based on the network's acquisition cost.
### 2.1. MVRV (Market Value to Realized Value)
The MVRV ratio is the relationship between Market Capitalization and Realized Capitalization. Realized Cap replaces the current price with the price at the time of the last movement of each UTXO (Unspent Transaction Output), serving as a proxy for the aggregate cost basis of all network participants.
*Economic Interpretation:** High MVRV values indicate that the market holds significant unrealized profits, increasing the incentive for liquidation. Low values suggest the asset is trading below the average acquisition cost, signaling undervaluation and capitulation.
### 2.2. NUPL (Net Unrealized Profit/Loss)
NUPL measures the difference between Relative Unrealized Profit and Relative Unrealized Loss.
*Behavioral Analysis:** This indicator maps the investor's emotional cycle, ranging from "Capitulation" (maximum losses) to "Euphoria" (maximum profits). Extreme positive deviations tend to correlate with cycle tops due to profit saturation.
### 2.3. SOPR (Spent Output Profit Ratio)
SOPR calculates the profit or loss realized only for coins moved within a specific period. A SOPR consistently above 1 indicates the market is absorbing profits, while values below 1 during uptrends indicate seller exhaustion.
## 3. Supply Dynamics and Mining Economics
Bitcoin's security infrastructure creates a class of compulsory sellers: miners, who must cover operating expenses (OPEX) and capital expenditures (CAPEX).
### 3.1. Puell Multiple
This indicator explores miner revenue. It is calculated by dividing the daily coin issuance (in USD) by its 365-day moving average. Historically low levels indicate revenue compression, often forcing the capitulation of inefficient operators, which historically coincides with market bottoms.
### 3.2. Exchange Net Flows
Monitoring wallets identified as centralized custodians reveals the market's immediate intent:
*Inflow:** An increase in deposits suggests intent to liquidate or use as collateral.
*Outflow:** Withdrawals to self-custody indicate a long-term holding strategy and a reduction in liquid supply.
## 4. Ownership Structure and Network Maturation
Analyzing wealth distribution and the time coins remain in wallets offers insights into investor conviction.
### 4.1. HODL Waves and Illiquid Supply
HODL Waves categorize supply based on the age of the last movement. The growth of long-term bands during price corrections denotes accumulation by high-conviction investors (Smart Money).
### 4.2. Monitoring Large Entities
Analyzing addresses with large balances, adjusted to exclude intermediaries and exchanges, allows for the identification of net accumulation or divestment phases by institutional holders.
## 5. Research Methodology
This investigation adopts a quantitative and exploratory approach, based on the analysis of time-series data from the Bitcoin network.
1. Data Collection: Extraction of primary data via network nodes and specialized APIs (Glassnode/CoinMetrics) for the period from 2012 to 2025.
2. Statistical Treatment: Application of the Z-Score to identify standard deviations from the historical mean of the metrics.
3. Confluence Analysis: Validation of historical accuracy through backtesting, correlating independent variables to validate trend reversals.
## 6. Limitations and Conclusion
While on-chain analysis provides a significant informational advantage, it has limitations. Transactions on layer-two networks (such as the Lightning Network) and internal transfers between exchange wallets can introduce noise into the data.
However, the synthesis of metrics such as MVRV, Puell Multiple, and supply flows allows the transformation of the blockchain from a mere registry system into a market intelligence database. It is concluded that on-chain analysis is an indispensable component for risk mitigation and the identification of asymmetries in digital asset cycles.
---
## 7. Bibliographic References
ANTONOPOULOS, Andreas M. Mastering Bitcoin: Programming the Open Blockchain. 2. ed. Sebastopol: O'Reilly Media, 2017.
BURNSIDE, A.; PARKER, J. On-Chain Analysis: A New Framework for Asset Valuation. Journal of Digital Banking, v. 4, n. 2, 2020.
GLASSNODE INSIGHTS. The Week On-chain: Metrics and Market Analysis. Available at: [https://insights.glassnode.com/](https://insights.glassnode.com/).
NAKAMOTO, Satoshi. Bitcoin: A Peer-to-Peer Electronic Cash System. 2008.
PUELL, David; MAHMUDOV, Murad. The Market-Value-to-Realized-Value (MVRV) Ratio. Adaptive Capital, 2018.
TASCA, Paolo; TESSONE, Claudio J. A Taxonomy of Blockchain Technologies: Principles of Identification and Classification. Ledger, v. 4, 2019.
WOO, Willy. The Bitcoin Price Models. Woobull Charts, 2021.

#BTCMiningDifficultyDrop #BTC走势分析 $BTC
$ETH

🧭 1. Fundamentalne metryki rynku On-Chain

📌 MVRV (Wartość Rynkowa do Wartości Zrealizowanej)

Co to jest: porównuje wartość rynkową (aktualna cena × podaż w obiegu) z wartością zrealizowaną (średnia cena, po której każda moneta została zakupiona).

Interpretacja:

MVRV niski → inwestorzy są, średnio, na stracie → możliwa strefa akumulacji.
MVRV wysoki → zrealizowany zysk wysoki → potencjalny szczyt cyklu.

📌 Puell Multiple

Co to jest: stosunek między dziennym przychodem z wydobycia (w USD) a jego średnią ruchomą z 365 dni.