CryptoQuant User Guide
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  • CryptoQuant数据使用指南
  • 为何市场主体很重要?
  • 15大预置图表⭐
  • Quick Start
    • 巨鲸抛售
    • 矿工售币
    • 巨鲸囤币
    • 大额场外交易
    • 买卖压力
    • 市场趋势
    • 市场情绪
  • Market Indicators
    • MVRV比率
    • 预估杠杆率
    • 稳定币供给比率
  • Network Indicators
    • NVT比率
    • NVT黄金交叉
    • 普尔倍数
    • 存量产量比
    • 存量产量比的回归
    • NVM比率
  • Flow Indicators
    • 交易所巨鲸比率
    • 资金流动比率
    • 稳定币比率
    • 矿工持仓指数
  • Market Data
    • 未平仓量
    • 资金费率
    • 接受者买卖成交量/比率
    • 市值模型
  • Fund data
    • 灰度比特币信托(GBTC)
      • GBTC数字资产持仓
      • GBTC溢价或折扣
  • 灰度以太坊信托(ETHE)
    • ETHE数字资产持仓
    • ETHE溢价或折扣
  • Exchange Flows
    • 交易所储备
    • 交易所流入/流出与净流入
    • 交易所地址数量
    • 交易所交易笔数
  • Stablecoin Exchange Flows
    • 稳定币交易所储备
    • 稳定币交易所流入/流出与净流入
    • 稳定币交易所地址数量
    • 交易所稳定币交易笔数
  • Miner Flows
    • 矿工流出量
  • Inter Entity Flow
    • 交易所间转账总额
    • 矿工向交易所转账总额
  • stablecoin network data
    • Stablecoin Network Data
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On this page
  • Definition
  • Interpretation
  • Use Case
  • Statistical analysis on SF ratio
  • Link to Our Data

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  1. Network Indicators

存量产量比

存量产量(SF)比率是指当前流通中的加密货币与新供应的加密货币的比值。

Previous普尔倍数Next存量产量比的回归

Last updated 4 years ago

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Definition

Stock to Flow (SF) Ratio is defined as a ratio of currently circulating coins divided by newly supplied coins.

SF Ratio=Currently circulating coinsNewly supplied coins\text{SF Ratio} = \frac{\text{Currently circulating coins}}{\text{Newly supplied coins}}SF Ratio=Newly supplied coinsCurrently circulating coins​

Interpretation

SF ratio assumes that the scarcity of the coin drives the price of the coin. The analysis on SF ratio is first presented by a pseudonymous who operates under the Twitter account “”. By looking at SF ratio as a chart, we can spot where the market regime is.

Use Case

Statistical analysis on SF ratio

The original authors claim that the log of SF ratio is in a linear relationship with the log of the price. We reproduce the results of what they claim and as a result, shown in the figure below, SF ratio and price are in a linear relationship (not perfectly but in some sense) with significant statistics (p-value under 0.01, R-square over 90%).

Following the above linear statistics (trend and intercept), we can plot how closely they are related in a time-series manner. With this graph, we can recognize that the current price is in what regime recently.

Link to Our Data

Stock to Flow in CryptoQuant Live Chart
Stock to Flow in CryptoQuant Data API Docs
Dutch institutional investor
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