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Glassnode Insights, a crypto market analytics company, has developed a framework to assess seller exhaustion over multiple timeframes. The framework, based on Glassnode’s Breakdown Metrics allows for the isolation of specific points of unrealized losses and investor capitulation.
Long-term investors tend to be highly profitable during a bull market. The short-term holders are the main source of losses realized. They can also provide valuable information about inflection points when there is a sell-off.
The new framework is able to identify seller exhaustion in day traders and weekly-monthly investors. It uses both unrealized losses and realized losses to gauge the response of targeted investor classes to market downturns.
The framework was designed to identify the inflection point during corrections or consolidations that occur within a bullish trend. Seller Exhaustion can be defined as an oversold condition where the majority of sellers are likely to sell. This can be used to establish a local bottom.
The framework utilizes three metrics to determine the level of pressure that investors are under: MVRV ratio, which measures the unrealized profits or losses held by investors in the cohort, SOPR, which measures the average magnitudes of profit or losses locked in by cohort, and Realized Loss which is the USD denominated magnitude of loss locked in the cohort.
Daily traders are the most active and sensitive group, responding almost instantly to all price changes. Weekly-Monthly traders are less sensitive to price than Day Traders, but also more likely experience volatility, as the spot price fluctuates near their cost basis.
The new metrics provide a comprehensive overview of the different cohorts. This allows for valuable insights into the market dynamics, and helps to identify periods of exhaustion of sellers.
On-chain data offers analysts and investors a high degree of transparency regarding the actions, incentives and positioning of different market participants. Glassnode's new breakdown metrics allow investors to isolate subsets, allowing them to pinpoint micro-capitulation points that are often associated with local market lows. This allows investors to better predict and understand market movements.
Disclaimer: This article is not intended to provide investment advice. The data provided is for educational and informational purposes only. You are responsible for making your own decisions about investing and should not base any investment decisions on this information.
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