Original Article Title: "On-chain Data School (Part 7): A Brand New, Ark Participated Research Magical Pricing Methodology for $BTC (II)"

Original Article Author: Mr. Berg, On-chain Data Analyst

If you are not familiar with Cointime Price, it is recommended to read the first article: "On-chain Data School (Part 6): A Brand New, Ark Participated Research Magical Pricing Methodology for BTC (I)"

TLDR

- The Cointime Price series consists of three articles, and this is the second article

- This article will introduce the application of Cointime Price in identifying market tops

- This article will introduce a personally designed deviation model

1. Brief Review of Cointime Price

The concept of Cointime Price originates from Cointime Economics and uses a "time-weighted" approach to evaluate BTC's fair price.

Compared to simple distinctions between Long-Term Holders (LTH) and Short-Term Holders (STH), Cointime Price is more elastic, sensitive, and can effectively exclude the impact of ancient lost BTC.

The first article provided a detailed introduction to Cointime Price and its bottom-fishing application. If you already understand the concept, let's move on to today's topic: the top identification application.

2. Top Identification Application Methodology: Cointime Price Deviation Model Design

Cointime Price Deviation is one of the models I designed during my on-chain data research and has been applied in the weekly market top analysis report.

Related Tweet: [Top Model Introduction](https://x.com/market_beggar/status/1870763628645032213)

The following sections will explain the design principle of the model and how to use it to identify the top of BTC. All content in this article is original research, the research process is not easy, so please show your support.

1. Quantifying Current Price Deviation from Cointime Price

Why Measure Deviation?

- The Cointime Price significantly represents the true holding cost of BTC chips, especially for Long-Term Holders (LTH).

- Since Long-Term Holders have a greater impact on the Cointime Price, when the BTC current price is significantly higher than the Cointime Price, the profit-taking motivation of Long-Term Holders increases, potentially triggering distribution behavior.

· Calculation Formula: Deviation Rate = (Current Price - Cointime Price) / Current Price

· Observing Deviation Rate (Distribution Rate)

As shown in the chart, we can see the Distribution Rate curve (purple line). We can observe that whenever the Distribution Rate is at a high level, it often corresponds to the BTC top.

So, how do we define a "high level"? Next, we will use a statistical method to address this issue.

2. Cointime Price Deviation Extreme Value Definition

If we observe historical data, we will find that the high points of Deviation are not fixed; in each bull market cycle, the peak value of Deviation slightly decreases. Therefore, using a fixed value to define a "high level" is not rigorous.

To address this, I adopt the concept of statistical "standard deviation":

· Calculate the mean and standard deviation of historical Deviation data.

· Define "mean + n standard deviations" as the "high level (top signal)," referred to as the Threshold.

· Smooth the Deviation data with a moving average to reduce noise.

· When the moving average value of Deviation> Threshold, trigger a top signal.

· Why Use Standard Deviation?

· The historical trend of Deviation exhibits mean reversion characteristics (as shown in the chart).

· Standard deviation measures volatility; as BTC price volatility decreases, the Threshold will also dynamically adjust, making it more elastic.

As shown in the above image, after the above processing, we can obtain the following chart.

· Supplementary Explanation

- In Point 2, the "Mean + n Standard Deviations," where n is a tunable parameter: the larger the n, the lower the probability of vertex signal occurrence, making the model more stringent.

- Point 3's Moving Average Smoothing: mainly filters out short-term market fluctuations to enhance signal reliability.

3. Top Escape Signal Example

As shown in the figure, when the purple line (Distribution Ratio) exceeds the orange line (Threshold), the corresponding BTC price is often at a local top.

III. Conclusion

This article is the second in the Cointime Price series, continuing the concepts of the previous article, sharing how individuals can design a top escape model using Cointime Price.

· Summarize the core points:  

- Cointime Price Deviation quantifies the deviation of the current BTC price from the Cointime Price, speculating on long-term holders' distribution motivation, used to determine the BTC top.

- By adopting the "standard deviation" method to dynamically define the top signal, ensure the model is more adaptive.

- The model has been practically applied in a weekly report and can effectively capture BTC's high-level signals.

Future plans:  

- The third article in this series will continue to explore the application of Cointime Price in top escapes. Stay tuned.

Original Article Link

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