OPEN-SOURCE SCRIPT

(mab) Dynamic Bitcoin NVT Signal

Bitcoin`s NVT is calculated by dividing the Network Value (market cap) by the USD volume transmitted through the blockchain daily. Note this equivalent of the bitcoin token supply divided by the daily BTC value transmitted through the blockchain, NVT is technically inverse monetary velocity.

Credits go to Willy Woo for creating the Network Value Transaction Ratio (NVT). Credits go also to Dimitry Kalichkin improving NVT and creating the NVT Signal (NVTS).

According to its creator, the NVT Ratio is somewhat similar to the PE Ratio used in equity markets. When Bitcoin`s NVT is high, it indicates that its network valuation is outstripping the value being transmitted on its payment network, this can happen when the network is in high growth and investors are valuing it as a high return investment, or alternatively when the price is in an unsustainable bubble.

I created this indicator because the NVT indicator I was using suddenly stopped working. I tried a number of other NVT indicators, but all of them seem to have the same problem and stopped updating after a certain date. The cause is that the data feed from 'Quandl' that is used by most NVT indicators is no longer updated through the previous API.
Instead TradingView created a special API to access 'Quandl" data. This indicator not only uses the new API for 'Quandl', it can also access data from other providers like 'Glassnode', 'CoinMetrics' and 'IntoTheBlock'. However, the 'Quandl' data feed seems to produce the best results with this indicator.

The indicator provides dynamically adjusting overbought and oversold thresholds based on a two year moving average and standard devition with adjustable multipliers. It also implements alerts for NVT going into overbought, oversold or crossing the moving average.


Version 1.0

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Version history

0.1 Beta
- Initial version
1.0
- First release
BTCNVTnvtsnvtsignalTrend AnalysisVolume

开源脚本

本着真正的TradingView精神,此脚本的作者已将其开源,以便交易者可以理解和验证它。向作者致敬!您可以免费使用它,但在出版物中重复使用此代码受网站规则约束。 您可以收藏它以在图表上使用。

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