BTC on-chain data analysis: Has this cycle peaked?

BTC is currently in a condition where a top is forming. This article is from the Mint Ventures-produced Podcast, reprinted by Foresight News. (Background: The encryption fund has had net outflows for the first time in 19 weeks. Will BTC retest the $92,000 support level?) (Background: Altcoins evaporated $234 billion in market cap in the past two weeks, 'creating the worst in history.' Glassnode: Already in a bear market.) Hello, welcome to WEB3 Mint To Be initiated by Mint Ventures. Here, we continue to question and think deeply, clarify facts, explore reality, and seek consensus in the WEB3 world. To clarify the logic behind the hot topics, provide insights beyond the events themselves, and introduce diverse perspectives. Alex: This episode is a bit special because we have discussed many specific races or projects before, and also exchanged some cyclical narratives, such as memes. But today we are going to discuss on-chain data analysis, especially BTC's on-chain data analysis. We will closely examine its principles of operation, key indicators, and learn its methodology. In today's program, we will mention many concepts about indicators, listing these concepts at the beginning of the text version for easier understanding. Some data indicators and concepts mentioned in this podcast: Glassnode: A commonly used on-chain data analysis platform that requires payment. Realized Price: Calculated based on the price at the last on-chain move of BTC, reflecting BTC's on-chain historical cost, suitable for evaluating the overall profit/loss status of the market. URPD: Realized Price Distribution. Used to observe the price distribution of BTC chips. RUP (Relative unrealized profit): Used to measure the ratio of unrealized profits of all coin holders in the BTC market to the total Market Cap. Cointime True Market Mean Price: An on-chain average price index based on the Cointime Economics system, aiming to more accurately evaluate the long-term value of BTC by introducing 'time weighting,' compared to BTC's current market price and Realized Price. The True Market Mean Price under the Cointime system also takes into account the impact of time, suitable for price changes in BTC's major cycles. Shiller ECY: Valuation index proposed by Nobel Prize-winning economist Robert Shiller to assess the long-term return potential of the stock market and measure the attractiveness of stocks relative to other assets, derived from the improvement of the CAPE indicator, mainly considering the impact of the Interest Rate environment. The opportunity to learn on-chain data analysis Alex: Today we have invited a guest, Colin, a freelance trader and on-chain data researcher. Colin, please greet our listeners. Colin: Hello, first of all, thank you for Alex's invitation. When I received this invitation, I was a bit surprised because I am a small retail investor with no special titles, quietly doing my own trading. My name is Colin, and I operate an account called Mr. Berg on Twitter, where I mainly share tutorials on on-chain data, analysis of the current market situation, and some trading concepts. I roughly position myself in three ways: the first is an event-driven trader, I usually think about event-driven trading strategies; the second is an on-chain data analyst, which is the main content I share on Twitter; the third is more conservative, I call myself an index investor, choosing to allocate some funds to the overall market of US stocks. By investing this part of the funds, I control the overall defensive position of my asset curve's fluctuation, while maintaining a certain level of defense. That's about my positioning. Alex: Thank you, Colin, for your introduction. I invited Colin to the program because I found his on-chain data analysis of BTC on Twitter very inspiring. This is a topic we haven't talked much about before, and it's an area I lack in my zone. I read his series of articles and found them to be logical and substantive, so I invited him. It is important to remind everyone that the views of both myself and the guests in the program are highly subjective, and the information and viewpoints may change in the future. Different people may have different interpretations of the same data and indicators. This episode does not serve as any investment advice. The program will mention some data analysis platforms, only for personal sharing and examples, not as a commercial recommendation. The program has not received any commercial sponsorship from any platform. Let's get into the topic and talk about on-chain data analysis of encryption assets. Just now, Colin mentioned that you are a trader. When did you start to learn about and study on-chain data analysis of encryption assets? Colin: I think this question should be answered in two parts. Firstly, I believe that no matter who wants to enter or has already entered the financial market, including myself, the main goal should be to make money and use the profits to improve one's quality of life. So my philosophy has always been consistent, whatever can help my profits, I will learn. By improving the expected value of my overall trading system in this way, in simple terms, I will learn whatever can make money. Secondly, I initially came into contact with on-chain data purely by accident. It was probably about six or seven years ago, when I completely didn't understand, looking at this and that. When exploring various fields, I found interesting research theories that I wanted to learn. At that time, I also accidentally discovered a field called on-chain data analysis related to BTC. I started to learn and research it. In the later stage, I would combine the knowledge I learned in other fields, mainly in the development of quantitative trading, integrate it with on-chain data, then develop some trading models, and finally incorporate these models into my own trading system. Alex: So, how long have you been studying and researching on-chain data analysis of encryption assets systematically from the start until now? Colin: I think this is hard to define, actually, I have never really learned systematically. Because from the past to now, I have encountered a problem, which is that I have never seen any systematic teaching. From the very beginning when I saw this field, it might have been good several years ago, I discovered it at that time, but didn't delve into it, just read a couple of articles to know about it. After some time, I came back and saw some more in-depth content, at that time, I was focusing on researching other things, and then came back here, found it quite interesting, so I continued to study it. There wasn't a systematic learning time, it was just piecing together like this. Alex: Understand, from learning on-chain data to applying it to your actual investment practice, how long has this been going on approximately? Colin: This boundary is relatively hard to define, but I think it's close to about two BTC cycles... It cannot be counted...