Three Scenarios for Bitcoin’s Late Bear Market & Four Bottom-Fishing Models Explained
In June 2026, Bitcoin briefly broke below the 60,000 round-number level left in February, hitting a low around 59,000 before bouncing and consolidating. The market is fiercely debating whether the bear market bottom is in. While AI and semiconductor stocks are going wild in the equity market, the crypto market feels eerily quiet. At this moment of bullish-bearish divergence and extreme emotional swings, 168X invited Mr. Beggar (@market_beggar), a full-time trader focused on on-chain analysis and technical analysis.
Between late 2024 and early 2025, when almost the entire market was bullish, Mr. Beggar was among the first to call the top and cleared his BTC position. He then gradually built BTC-denominated shorts with low leverage, a call that the subsequent price action has validated. His trading framework can be distilled as: for spot, look at on-chain analysis; for contracts and derivatives, look at technical analysis — each doing its own job. In this conversation, he breaks down on-chain data like Cointime Price and AVIV, as well as the concept of stop hunts and liquidity grabs, and delivers a clear judgment: we are not far from the cycle bottom, but we may still need one last shakeout. Faced with the AI and semiconductor frenzy, he also repeatedly stresses the most important investment mindset for retail traders: always stay inside your own hit zone, and never buy something just because it is going up.
1. Research Framework: A “Dichotomy” Trading System — Spot Looks at On-Chain, Contracts Look at Technical Analysis
Mr. Z: It’s an honor to have Mr. Beggar here today. You are one of the few who can explain Bitcoin on-chain analysis in such a vivid way — what the liquidity looks like at every price level is crystal clear. Could you briefly introduce yourself first, and then sum up in one sentence what stage BTC is in right now?
Mr. Beggar: Thanks for the invitation. I’m currently running the Mr. Beggar Twitter account, where I share content focused on BTC on-chain analysis, while another part is dedicated to technical analysis. My technical analysis is liquidity analysis, a somewhat niche school, similar to what some people have heard of as SMC (Smart Money Concept). But I’ve adapted it to the conditions of the crypto market, for example by incorporating the analysis of takers (market order side) and makers (limit order side). It’s hard to explain in a few words; we can talk more about that later.
As for BTC’s current stage — putting it in one sentence: the final bottom of the bear market may not be in yet, but it is very close. I think in any financial market, whether US stocks, Taiwan stocks, or even crypto and forex, time is the hardest thing to predict. So I prefer to look at space, i.e., price. Judging by BTC’s price of roughly 63,000 today, or the early-June low of 59,000, I think 59,000 is already very close to the final bottom of this bear cycle. But it hasn’t arrived yet, or rather, the bottom I would hope for would be somewhat lower than 59,000. So to answer the question, the current market stage of BTC, in my view, is the late bear market, but there may still be a short stretch left to go — this is my personal bias.
2. Three Scenarios for the End of the Bear Market: Why Breaking Below 59K and Sweeping Lower Liquidity Is Actually Healthier
Mr. Z: Wow, that chills my heart. I just went long at 62,000 yesterday, and I also longed SpaceX at 170. Now I’m struggling to hold these positions — it’s heavy, my shoulders are sore today. So if you were to break down BTC’s next move into three paths, how would you classify them, and which path has the highest probability?
Mr. Beggar: Bitcoin made a low in the first week of this month, on June 5, breaking below the February low at the 60,000 round number. Right after the break it began to bounce, so it looks a bit like a false breakout. Within the liquidity analysis framework, I would call this a liquidity grab, or a stop hunt.
But we can’t conclude that just because it broke the previous low and then recovered above it, it’s definitely a liquidity grab and about to reverse and bottom out. We have to judge based on the consolidation that started after the break. That is, the move from June 5 to today — we would call it “consolidation after a trending move”. Bitcoin has a very clear tendency: after a trend move, whether a surge or a plunge, it will almost certainly enter a period of sideways consolidation to repair the prior move, and at the end of that consolidation it will make its next directional choice. Our job is to extract as much information as possible from this sideways consolidation structure to determine whether the next move will be up or down.
As for this small consolidation since June, I personally think it’s relatively weak, which is why I mentioned earlier that I believe breaking below the early-June low of 59,000 once more would be healthier.
Now, regarding the three scenarios you mentioned: the first is a direct drop; the second is sweeping upside liquidity first, then falling; the third is not making a new low and walking a direct right-side reversal.
The first and second are both relatively short-term paths. In the trading world, the shorter the time frame you look at, the more noise you encounter. So I think these two scenarios have roughly equal probability — I can’t tell from the available information which one is higher. But if I had to lean one way, I’d lean toward the first scenario. Because if this consolidation structure produces a clear signal — for instance, if Bitcoin’s high around 67,300 on June 15 sees a clear stop hunt: the price slowly climbs to 67,300, punches through, and immediately gets slammed down with a big candle, accompanied by relatively large volume, meaning taker market sell orders come in — then we’d say the stop hunt at 67,300 may have formed, and the consolidation structure since early June is approaching its end and possibly about to finish.
This concept is somewhat similar to the period from February to May this year: Bitcoin started consolidating from 60,000, coincidentally met the US-Iran conflict, repeatedly washed out the market, and eventually reached the 80,000 to 82,000 range we had mapped out early on, swept the liquidity above, and then began to decline. Last November to January this year, the consolidation from 80,000 to 97,000 also played out the exact same pattern: first a sharp drop, then a sideways consolidation to repair, and at the last moment, a sweep of the previous highs, completing a stop hunt before coming down. Zooming in, the move from June 5 to today has a somewhat similar structure. But this is only a signal to watch — it could also just go straight down.
As for the third scenario, “no new low, a direct right-side reversal,” why don’t I consider it much? The reason is simple: from June 5 to today’s consolidation structure, too much liquidity has already accumulated below. From my usual liquidity framework, the area from 62,300, 60,700 down to 59,000 actually contains quite a lot of liquidity. If Bitcoin keeps going up without ever coming back, I still wouldn’t think the final bottom is in — and here I’m talking about the cycle-level final bottom. At a smaller level, as long as that liquidity hasn’t been swept, it will eventually have to come back.
This is exactly like the February-to-May period: back then, when it rallied to 79,000, 80,000, 82,000, many people thought the bull market was returning, calling for a breakout above 81K, a trend reversal, right-side signals. But what I wrote in my posts back then — still visible now — was that I believed there was a trendline liquidity between 60,000 and 65,000 that would eventually be hunted. The concept is very similar right now. So my conclusion: a direct drop, or sweeping upside liquidity then dropping — these two are roughly equally likely; I don’t really consider the third right-side reversal. The final bottom still needs to break below 59,000 before it can potentially form.
3. What Is Liquidity: Equal Highs/Lows and Trendline Liquidity — Why Naked Charts Are Enough
Mr. Z: I’m curious — when you talk about liquidity, do you mainly look at how much buying sits at a certain price level, or do you use some indicator?
Mr. Beggar: Many people look at so-called liquidation maps or heat maps; I don’t use those indicators. What I look at is very simple: just the chart. I once wrote a primer post describing the two main, simplest types of liquidity to identify.
The first is equal highs or equal lows — wicks on the chart that form equal highs or equal lows. For equal lows, the shape is a bit like a W, but the low on the right side of the W must not be lower than the low on the left, creating a nearly horizontal level where the lows are almost the same. Equal highs follow the same concept.
The second is more complex, called trendline liquidity, somewhat like the structure from June 5 to today. It’s sloping — you can draw something resembling a trendline. During the consolidation it makes progressively higher lows, but the magnitude of those lows is very close. So once one low is broken, it will charge down a stretch and then form a close with another low; then that low gets broken again and forms a close with the previous low. That’s the source of the liquidity.
So I don’t look at indicators, and I don’t look at the order book. It’s visible purely from the chart pattern. One more point: over at least the past five years, Bitcoin has had only one equal low, one liquidity pocket that wasn’t hunted. All other liquidity was eventually hunted — the probability is basically over 98%. That’s my method for judging liquidity.
4. A School of One’s Own Departing from ICT: Why Technical Analysis Must Be Able to Explain Its Logic
Victor: Mr. Beggar, I’d like to ask specifically about your trading framework. Over the past few years, technical analysis has seen many schools of thought, from traditional false breakouts, false breakdowns, and break-of-bottom reversals to recent methods like ICT that emphasize liquidity sweeps. From what I hear, you’ve integrated various approaches and can directly read bare candlesticks to observe liquidity hunting. How did you build this entire framework, and how did you train yourself to the point where you can tell where liquidity is just by looking at bare candlesticks?
Mr. Beggar: Initially, I was actually inspired by ICT (Inner Circle Trader). He proposed concepts like liquidity sweep, and liquidity sweep is essentially the stop hunt concept — these two should be synonyms.
A long time ago when I was studying technical analysis, the field had too many schools. And if you try to verify them scientifically, they actually can’t be fully supported, so you need your own form of verification. Personally, I don’t really agree with traditional pattern analysis, like head and shoulders tops, rising wedges, falling wedges, flags, or triangles. I’ve studied almost all the schools deeply before, then gradually filtered them out, keeping only the current framework.
The main reason I don’t really buy into traditional pattern analysis is simple: in financial markets, if you want to know whether something works, you must be able to articulate a logic. You can’t just use induction to conclude, “This works.” Induction could very well be survivorship bias caused by an insufficient sample. For example, if a pattern repeated over the last decade but you can’t find its logic, you actually dare not use it directly, because ten years may sound long but you might have fewer than 20 samples. Traditional pattern analysis says “rising wedge is bearish,” but every book and online source fails to explain why that structure leans bearish. I saw a reason in ICT’s liquidity framework — it’s the bearish structure caused by so-called trendline liquidity.
As for how to see it with a naked chart, that’s actually not difficult because it never needed indicators to begin with. ICT didn’t use any indicators in his early teachings — just pure price lines. But reading lines requires some experience. The fastest way to accumulate experience is through replay review, though the process is extremely boring. You might spend 30 minutes every day searching for these liquidities and then verify after the fact whether they got swept. It’s pretty exhausting, but my day job is a full-time trader, so this is naturally part of my work.
5. Discipline in shorting: clearing the position at 100k, building shorts with low leverage, and the confidence of a “God’s-eye view”
Victor: I remember very vividly — around early 2025, when BTC was in the hundred-thousand range, you started building short positions gradually, and with very low leverage, like 1.2x, 1.3x. Later, BTC kept fluctuating at high levels without a clean drop, yet you remained very firm in holding your shorts. Shorting is a counterintuitive decision for most people — how did you manage these positions mentally?
Mr. Beggar: Let me toss a question first: Suppose I tell you I am God and give you next week’s lottery numbers with a 100% win rate. You would buy without any fear because you are absolutely certain. This is called a God’s-eye view.
For me, I started running this Mr. Beggar account in November 2024, and it coincided with a market move very worth sharing. From late November 2024, through December into January, I published articles for about a month saying that Bitcoin had reached a cycle top. In hindsight, I was half right and half wrong. The right part: I cleared my entire position at 103,000 because I saw very, very many classic top signals in on-chain analysis. Hardly anyone in the market mentioned these signals at the time — I was likely the first. Some media outlets even loved writing about my articles; I was a bit shocked myself because during a period when the whole market was bullish, very few were bearish.
Later, a bunch more top signals from my on-chain analysis system were triggered, and the price then continuously crashed to 74,000. Until then, I still thought the bear market hadn’t ended, so I didn’t enter to buy the dip. Then the tariff news suddenly achieved a fantastic outcome, and the price climbed all the way from 74,000 back up to my clearance level of 103,000. So on that part, I indeed got it wrong — I didn’t buy the dip on Bitcoin, only bought the dip on Taiwanese and U.S. stocks. Quite a pity.
All the way to around July last year, those top signals triggered a second time. In the past, whenever those signals triggered, that very point marked the cycle top. But I had already sold all my Bitcoin; I had nothing left to sell. So I went straight to open coin-margined shorts. Actually, when I sold Bitcoin, it wasn’t simply selling spot — I opened a 1x coin-margined short as a hedge and collected funding fees. I collected those for about a year; the Bitcoin I used to open positions was still there. I directly used that to open leveraged shorts.
How to mentally adjust? It comes down to two things. First, I have sufficient confidence in these signals. I have extremely high conviction that it will fall, but I don’t know when it will fall, so I layer my short positions in batches. I opened shorts twice in July, and again at a new high in early October. I added mainly three times, with an average entry around 119,500. Looking at the daily chart, the consolidation from mid-July all the way to early November was where I mainly built the position.
Second is risk control. The leverage I used was very low — only a bit over 1x short. Because anything can happen. Even if the probability of Bitcoin suddenly getting a super bullish catalyst is extremely low, we must ensure that we won’t die; you cannot get wiped out in this market because of one single trade. With these two aspects combined, I could basically guarantee I wouldn’t die, and the subsequent price action validated my thinking.
The only pressure came from running Twitter. For those three months, I kept talking bearish, bearish, bearish every day. With the whole market bullish, loads of people came to call me a dumbass, saying “You’re dead when it hits 180k.” I got used to it. In the moment it stings a bit, but it’s fleeting — it doesn’t affect my own trading.
6. Four major on-chain models for bottom-fishing in deep bear markets: Cointime Price, Realized Price, and AVIV
Victor: You’ve been sharing the four major deep-bear bottom-fishing models recently, looking at data like Cointime Price. Can you share with the audience your entire on-chain data trading framework and how you combine it with technical analysis?
Mr. Beggar: To put it in the simplest terms, it’s a dichotomy: for the spot portion, I look at on-chain analysis; for contracts or other derivatives, I use technical analysis.
For spot, I mainly look at the long term. Long term here isn’t one month, three months, or six months — I look directly at a four-year cycle. Personally, I don’t entirely endorse the four-year cycle theory, but after all, Bitcoin has still exhibited this cycle since its inception. Bitcoin is very special; its bull and bear characteristics are extremely pronounced. Looking at the weekly chart, Bitcoin goes boom-bust, boom-bust, but if you look at the Nasdaq index, it broadly moves up at roughly a 45-degree angle slowly. It’s a completely different emerging asset. It skyrockets a lot on the way up, but many overlook that it also plunges incredibly deep. For example, if you bought one Bitcoin in April 2021 and held until now, you haven’t made money — in fact you’ve lost money. So in the Bitcoin market, if you don’t make some trading plans and just purely hold, the mental grind is very tough.
The biggest advantage of on-chain analysis is its extremely high accuracy in assessing tops and bottoms. It can’t get me to buy at the absolute lowest price, but it can help me capture a relative bottom zone. For example, suppose this cycle’s bottom is at 50,000. On-chain data might give me 50,000, but it ultimately drops to 48,000 or 45,000. In that case, buying at 50,000 is totally fine — this is what’s called “roughly right.” Escaping the top is the same: the first time I exited this cycle at 103,000 and shorted at 119,500, both were relatively okay positions. If I buy the dip later at 50,000 and it drops to 45,000, I completely accept that relative to the future potential upside.
Technical analysis leans more toward the mid- to short-term. Especially for a liquidity-sensitive asset like Bitcoin, a framework centered on liquidity and supplemented by taker/maker data is a relatively advantageous strategy in the current crypto market. But for an ordinary person, whether student or office worker, as long as you’re not a full-time trader, the barrier to entry for short-term trading is a bit too high. That’s why on Twitter I tend to share things with a longer cycle, like the U.S. side capital sentiment curve, Cointime Price, and these deep-bear bottom-fishing models — because they suit ordinary people the best: you don’t need to watch the screen all day, and you don’t even need to predict timing; just keep an eye on these few large-timeframe levels.
Here I’ll add a question a group member once asked: Suppose it drops to a level indicated by the deep-bear bottom-fishing models but no stop hunt occurs — would I still buy the dip? My answer is yes. Because on-chain analysis is specifically designed to handle cycle-level tops and bottoms. Once on-chain signals are triggered, the weight of technical analysis is relatively lowered. At special positions like cycle tops or bottoms, I tend to raise the weight of on-chain analysis. For everyday mid- and short-term trades, I barely reference on-chain analysis, because it doesn’t look at such short timeframes to begin with — that’s also a shortcoming of on-chain analysis; it can’t be used for short-term trading.
Victor: Among your four major deep-bear bottom-fishing models, I see one is AVIV, which is somewhat like an optimized version of MVRV, but most people mainly look at MVRV. Could you explain how you use these four indicators — AVIV, Cointime Price, Realized Price, and Long-Term Holder Realized Price — to determine bottom-fishing levels in bull-bear cycles?
Mr. Beggar: Let’s set the AVIV heatmap aside for a moment and talk about the other three first.
The first is the Realized Price. This is a very classic on-chain metric that measures the average cost basis of the entire BTC market. Assume you bought one bitcoin each at 50k, 60k, and 70k; your average cost is 60k — it calculates this average cost for the whole market. But this metric is a bit rough: it doesn’t consider at all those lost coins, super-ancient coins that haven’t moved for a decade — it includes them all the way back. Although this doesn’t cause a significantly wrong final bottom judgment, it does have that flaw.
The second is the Long-Term Holder Realized Price (LTH Realized Price). It’s stricter — it doesn’t look at the entire market but isolates the long-term holder cohort and calculates their average cost, so the price comes out a bit lower. In the on-chain analysis field, long-term holders are usually regarded as the relatively smart group, because as long as you bought Bitcoin early enough and held it long term, you make money.
Based on the issues with the previous two indicators, Cointime Price was born. It similarly calculates the market’s average cost of holding BTC from an on-chain perspective, but adds an extra step: when each bitcoin is transferred, it looks at how long that coin was held before the transfer and weights by the holding time. If you hold for just one day and sell, the weight may be 1; but if you hold for ten years and sell, the weight would be 3,650 (roughly 3,650 days in ten years). The beauty of this time‑weighted design is: those veteran coins that usually stay dormant are not included in the Cointime Price calculation; only coins that are truly active get included. Another interesting point is that the Cointime calculation also excludes miners, because miners need to keep their operations running and typically sell bitcoins above the Cointime Price to cover costs—they are generally not HODLers. So what it measures is closer to the true market average cost, and that’s my favorite indicator.
The fourth one, the AVIV heatmap, follows the same concept. Both AVIV and Cointime Price are indicators that came from a paper co-authored by ARK and Glassnode, called Cointime Economics—that's where these two concepts were introduced. AVIV is basically an improvement on MVRV, because MVRV also takes into account coins that haven't moved, are lost, or almost certainly haven't budged in 800 years. AVIV strips those out, giving a more precise reading.
As for the AVIV heatmap, it's a model I built myself. I factored in Bitcoin's declining volatility and wrote it using a normal distribution. So on the chart, red means the cycle is at its tail end—the late stage of a bull market—and blue means the market has bottomed. It oscillates back and forth between these colors, like a rainbow repeating itself. Usually, blue marks a cyclical bottom, and right now we're very, very close to the blue zone. That's basically the logic behind these four models.
7. Accumulation Trend Score and PSIP: Which Are Cyclical Indicators and Which Are Just Swing Indicators
Victor: Mr. Beggar, what platform or tools do you use to look at all this data? There's a lot of on-chain data available, but you seem to evaluate how useful an indicator is before deciding whether to add it to your framework, and you even read papers like the one by ARK and Glassnode. How did you learn on-chain analysis?
Mr. Beggar: At the very, very beginning, it was just about making money, you know. Entering this crypto market, I'd try to learn whatever seemed like it could make money, and if I found out it was junk, I'd toss it. One day I suddenly realized Bitcoin had something called on-chain analysis, so I started researching. Naturally, the first thing I saw was the super-famous MVRV. But as I dug deeper, I asked myself: Why is this useful? What are its flaws? Under what conditions does it fail? I studied the logic behind it and found that MVRV does have shortcomings.
I'm not someone who provides data websites, I can't code, and I don't understand blockchain, so what could I do? I had to look for existing resources and dig deeper and deeper. Eventually, I found that I wasn't the only one who thought MVRV had problems—some teams with resources and expertise had designed new indicators. I looked at the reasoning they gave in their papers and found that while not perfect, they were at least better than MVRV, so I replaced the old indicator with those.
For Asian users, the barrier to learning on-chain analysis is relatively high, for a simple reason: Chinese-language resources are almost nonexistent—so scarce it's barely more than zero. That means you have to seek out foreign resources, at least from relatively well-known indicator creators or established data sites. The data site I usually look at is Glassnode. They do a pretty good job, but I normally don't recommend it to everyone because you have to pay to see those indicators, and some indicators you can't even see by paying because I wrote them myself. If my followers want to check the current status of the indicators I usually share, they can just tell me in the comments, and I'll pull up the data for them. I try my best to let everyone see it at low or even zero cost. I really wouldn't advise someone who isn't a full-time trader to spend money on this. Just follow my sharing, and if you want to see a particular piece of data, let me know.
Victor: You recently posted the BTC Accumulation Trend Score, and it's now trending upward. How would you interpret this indicator? And how can we use on-chain data to see the movements of major players' chips?
Mr. Beggar: The Accumulation Trend Score is something I shared on June 16. It's a relatively composite indicator. To put it simply, it tells you whether on-chain activity is predominantly buying or selling at the moment—or, to use more formal terms, accumulation or distribution.
When Bitcoin dropped to 59K in early June, this indicator started to turn toward accumulation, but at that moment we couldn't be sure whether a reversal was really underway. As time passed, this choppy structure gradually gave us more information: it accumulated more liquidity on the downside, and after breaking below the 60K prior low it reclaimed that level. We had to check whether this was actually a structural reversal driven by liquidity. Taken together, the choppy structure over the past two-plus weeks wasn't really conducive to building a base. So when I combine that with the Accumulation Trend Score, I don't see it as a signal that a true cyclical bottom has formed.
This comes back to a very important point in on-chain analysis: many indicators can be categorized into different tiers. For example, Cointime Price—if price drops to that level, it's a highly reliable cyclical bottom indicator. But indicators like the US-side capital sentiment curve and the Accumulation Trend Score are not cyclical indicators. They lean more toward medium-term swings. They can absolutely change color during a consolidation in a bull market rally or inside a continuation pattern during a bear market drop. So just because I saw some accumulation behavior after the drop to 59K doesn't make me think a cyclical bottom is coming. It only tells me that the current bounce is happening because people have started buying, but that buying alone isn't enough to signal a cyclical bottom is here.
One additional point: a cyclical bottom signal has already appeared. On June 8, I shared a PSIP bear market bottom signal. It was the first cyclical bottom signal to light up since 2023. But only this one has lit up so far, so it's still not quite enough. And looking at the past performance of this indicator, the first time it fires is usually not the actual bottom. The signal tends to stay lit for a while until the bottom truly arrives. So putting it all together, I think we just need one final move that breaks below 59K, and then the bottom may come. That also echoes what I said at the very start of the show: I can't predict the timing, but the distance really isn't far anymore.
Victor: I saw that PSIP post on June 8. Can you explain to the audience what it is?
Mr. Beggar: PSIP stands for Percent Supply in Profit. In simple Chinese, it's the percentage of all circulating Bitcoin that is held at a profit. For example, if there are 100 bitcoins in circulation and 60 are in profit while 40 are at a loss, the indicator's value would be 60%.
This is a very classic model, and the signal trigger condition is simple: when PSIP drops below 50%, it lights up, meaning more than half of all circulating Bitcoin is underwater. From an on-chain perspective, we can calculate the cost basis of every coin and compare it with the current price to know which coins are in profit and which are at a loss.
Why is below 50% very likely a cyclical bottom signal? The reason has to do with supply and demand. Market prices are determined by supply and demand. For the price to rise, there are essentially two possibilities: the first is a large increase in demand, with a flood of people coming in to buy—like vegetable prices before a typhoon, when everyone rushes to stock up and pushes the price up. But there's a second scenario that fewer people pay attention to: a significant decline in supply, meaning fewer people are selling. If buy-side demand is already low but sell-side supply suddenly drops dramatically, buying pressure becomes relatively stronger and will also push the price up.
PSIP below 50% is about this second scenario. It involves behavioral finance: when you're sitting on unrealized profit, like 5,000 USDT floating gain, you feel a strong urge to close the position and take profits because you're afraid it'll vanish an hour later. But when you're at a loss, the mindset flips—you think, "I'll just hold a little longer, and it might come back." At that moment, your risk appetite actually increases. It's irrational, but that's how humans behave. So when most coins are underwater, people are reluctant to sell. This directly leads to a sharp decrease in selling pressure in the Bitcoin market, which is why PSIP below 50% can serve as a cyclical bottom signal.
Right now, this signal only flashed very briefly. When the price dropped to 59,000 in early June, the PSIP reading hit a low of about 47.8%. But since it just barely lit up and other deep-bear bottom-picking models haven't triggered yet, I can't say with absolute certainty that the bottom is in. If you're someone who absolutely doesn't want to overthink, the current price might be a decent level—this is not investment advice. But if you want to refine your approach, spending a little more patience and waiting a while longer might be a better choice. At least that's what I'm willing to do myself.
8. US vs. Asia Capital Sentiment Curves: A Risk Signal of Smart Money Front-Running
Victor: Earlier we touched on some medium- to short-term swing indicators. I'd like to specifically ask about US-side and Asia-side capital. Since this cycle started in 2023, a large share of BTC's pricing power has shifted to Wall Street. ETF trading volume has already surpassed exchange volume, and CME futures also hold significant pricing power. You've mentioned before that Asian money acts more like dumb money and US money like smart money. After observing over the past year or two, what different moves between US and Asian capital can you spot from on-chain data, and how can we use that to profit from swings?
Mr. Beggar: The connection between pricing power and the US-side capital sentiment curve isn't extremely strong, but there is some.
First, let's talk about using the sentiment curves. As everyone can see, it's currently the Asian trading session, and Bitcoin basically doesn't move much. But once the US stock market opens, during the US working hours, both volatility and trading volume increase significantly. That shows the main trading capital is mostly active during US working hours. So if we see prices rising and the US capital sentiment curve also rising at the same time, we can reasonably deduce after the fact: this is obviously Americans pumping the price.
But if we see an anomaly—Bitcoin's price going up while the US capital sentiment curve is falling—that's very strange. Working backward from the calculation logic, it suggests that after an earlier rally, it was actually Asians buying during the Asian session while Americans were selling during the US session. So the price either trades sideways or slowly grinds higher, but the US capital sentiment curve is declining. In my trading system, that's a very noteworthy risk signal. It means they're front-running, pulling back, and Asian money is left holding the bag.
I've shared this concept twice. The first time was around November 2025—a textbook case: the Asia sentiment curve shot straight up, the US curve plummeted, and price just chopped sideways. The day I posted about it, the market tanked that afternoon, falling from around 110K all the way down to the 80K range. The second time was this May, when Bitcoin surged to the 81,000–82,000 area, rallying all the way up. Then suddenly one day, US capital sentiment dove while the price hadn't moved yet, so I posted to warn everyone to watch out for risk. And after that, it really did just keep dropping.
Therefore, we can use the attitude of U.S. funds to assist in risk assessment. Suppose you were originally long and don't understand this analysis, but you see this risk – you can be on alert, add some insurance to your long position, do some hedging or reduce your position, or hedge through derivatives. In any case, this thing can at least help us flag risks, which is its greatest use.
IX. Event-Driven Trading: Long-Short Arbitrage from BTC, ETH to SOL in Practice
Mr. Z: Your entire trading framework is based on on-chain data and technical analysis. Do you ever lean towards news-based or capital-flow-based judgments? For example, when news of an ETF launch comes out, would you become more bullish? Or do you think the Bitcoin market is already mature and efficient enough that one shouldn't use news as a basis for judgment?
Mr. Beggar: Let me share a case. Since I started doing Mr. Beggar, my attention has been fragmented, and I haven't been trading as diligently as before. But I used to really enjoy a type of trading called event-driven (事件驱动型交易).
Given the current state of the crypto market, although it can't compare to the US stock market, its efficiency has reached a fairly mature stage. So trying to capture market inefficiencies through information to extract alpha is somewhat difficult for the average retail investor, unless you're doing high-frequency trading—but retail investors don't have the equipment, team, or resources for that. However, event-driven trading is still doable.
For example, let's go back to the day the Bitcoin spot ETF was approved. Before the approval, Bitcoin had already rallied a bit because the market had priced in the news in advance. On the actual approval day, it didn't surge immediately, but there was a very notable signal: Ethereum skyrocketed. With Bitcoin barely moving, the ETH/BTC exchange rate shot straight up; if I recall correctly, it rose about 10% to 20%, a huge candle. Why? Because if Bitcoin got an ETF, it meant the crypto market as an asset class could have an ETF, so what's the next one? There was only one possibility: Ethereum, absolutely no second option. So a lot of smart money rushed in immediately at that point—that's market efficiency. To use this kind of information for event-driven trading, the first approach is: you're super smart and anticipated two things before the Bitcoin approval—one, the Bitcoin ETF would be approved, two, Ethereum would surge—so you bought Ethereum in advance.
The second was a trade I did in 2024: the Ethereum ETF. The period leading up to its approval was very turbulent, with the market generally thinking it wouldn't pass and pricing it at only about a 20% to 25% probability. Then one day in May 2024, around May 23rd, Bloomberg's senior ETF analyst Eric posted a tweet in the wee hours, saying they now thought the approval probability was extremely high, and Ethereum immediately surged, gaining 20% in a single day, wiping out short sellers instantly. I remember it vividly: I came back from the bathroom and suddenly saw the price as if there was a display error, how could it spike so much—and it turned out to be real, Ethereum jumped to 4,000. As a side note, in hindsight that was actually the peak for Ethereum in that phase; it later dropped to 2,000.
Mr. Z: At that time, when Bloomberg's Eric suddenly said the approval probability had risen, was there any specific reason?
Mr. Beggar: We don't know the reason, only that this person is very authoritative in the ETF space. It's like if I said the market was going to cut interest rates today, nobody would pay attention; but if Powell said rates would be cut, everyone would listen. Eric is that kind of authority in the ETF world. He must have known some information—we don't know where he got it—but at least he released that information to the market, and the market immediately priced it in.
But there still wasn't room for event-driven trading at that moment. What I thought that day was: if Ethereum gets approved, who's the next to surge? Just replicate the Bitcoin playbook. I did some homework and identified two best candidates: the first was SOL, the second was XRP, and I ended up picking SOL. How to do this trade? The simplest way is to short Ethereum and long Solana—that's the so-called long-short strategy, holding the spread between these two tokens. The premise was that I needed to confirm the probability of Ethereum's approval was high.
Here's a less intuitive logic: When most retail investors see a company release positive news, their first reaction is "it'll go up, I'll buy it." But that's the most intuitive and least profitable approach, because everyone will buy. You can also think in another direction: will its competitors suffer and fall? So rather than buying it, I prefer to short its competitors. By the same logic, with the probability of the Ethereum ETF approval rising sharply, I'd think about what's next, replicate the Bitcoin playbook, and pick SOL. Indeed, later the SOL/ETH exchange rate saw a rather significant rally.
However, there was a bit of luck involved because it coincided with the most glorious era of on-chain meme coins (金狗, 土狗), and everyone was buying SOL to punt on those on-chain coins, so SOL got another wave of associated upside. In this trade, I captured the expected profit, and the later part was essentially a gift from the market. That's a classic case of event-driven trading. You can think along these lines about things others might not have thought of, which gives you a chance to extract some alpha in a highly efficient market.
X. Will MicroStrategy Blow Up: Blowing Up Is Not the Cause of a Bear Market Bottom
Mr. Z: Now with MicroStrategy, these ETFs, DATs (digital asset treasury companies), the largest Bitcoin buyer is essentially MicroStrategy. Recently we've seen some FUD around its fixed-income product STRC. Although looking at its reserves it should be fine, the market tends to panic. From your perspective, before the next bull run in this cycle, is MicroStrategy in a bit of a predicament? It seems like everyone wants to short it and make it blow up, and only then might the market see another wave of upside?
Mr. Beggar: This is indeed a question many people care about; I've been asked many times. Let me give my personal view.
A couple of years ago, before they issued STRC, I specifically looked at their debt structure. From the debt structure perspective, the probability of them blowing up is very low. Why do I think they're very smart? Their debt maturities are almost all after 2028, so as long as Bitcoin doesn't experience a super extreme scenario and continues to drift lower all the way to 2028 without recovery, they definitely won't get into trouble. I haven't studied this latest STRC in detail; I only saw that it de-pegged and seems to have fallen below 83 dollars, but from a cash reserve perspective I haven't researched it deeply, so I won't say too much. However, based on a trader's intuition, I think the probability of them blowing up is really not high.
They might sell Bitcoin; the earlier sales could have been testing market sentiment or managing expectations. Selling could indeed cause market panic. But to think that this company, this Bitcoin empire, has to completely collapse in order for a bull market to arrive, I find that a bit unrealistic, because I can't imagine a direct causal link between the two. Why must they die for Bitcoin to have a big rally? They've been buying Bitcoin for five or six years; they didn't die in the last bull market, even though the amounts they bought back then can't compare to now. If they don't die, why would that block a bull market? That's something worth questioning.
More fundamentally: they were never the hands that steer the cycle. At least in the current Bitcoin market, cycles are determined by the market; no single entity can control Bitcoin's price. Short-term movements can be manipulated, that's inevitable, but can you say that over a long-term cycle scale, one entity could drive Bitcoin from 10,000 to 100,000? I think that's unlikely; that's definitely the result of market-wide consensus of capital. Since they aren't the hands manipulating the entire Bitcoin market and have no absolute control over Bitcoin, whether they die or not should have no bearing on when a bottom appears.
Some might say that in past bear market bottoms, there have always been institutions blowing up. But I think those blow-ups weren't the cause of the bottom; rather, the market was already in terrible shape, capital had already left, everyone who was going to leave had left, and even those who didn't want to leave were forced out because the market was so unattractive. For example, some ecosystems' TVL (total value locked) declined, certain protocols couldn't sustain operations, or people just wanted to exit—these institutional or protocol failures were the result of a bad market, not the cause of the market worsening and then bottoming. This logic must be clarified: whether they blow up or not is not directly linked to whether the market bottoms out. And from a trader's intuition, they've played their financial tricks so shrewdly that the probability of putting themselves into such an exaggeratedly dangerous situation is still on the low side.
XI. Different Ways to Play Altcoins: The Smaller the Market Cap, the Greater the Potential for Manipulation
Victor: You've mainly been trading BTC, sometimes ETH, SOL, these major coins, and you also invest in the overall US stock market. Do you think coins other than BTC, like ETH and SOL, have different trading styles compared to BTC? Can the framework you use on BTC—on-chain analysis, technical analysis, stop hunt—be applied to other major coins as well?
Mr. Beggar: We can split this into two parts. First, the inertia of each asset and each coin is definitely somewhat different. Bitcoin is the boss of this market, so on-chain analysis is absolutely aimed at it directly—that's a given.
If you are "investing" rather than "trading"—that is, holding long-term and believing in its value—then the simplest way is: look at when BTC bottoms, and then decide to deploy some spot positions in altcoins, whether it's Ethereum, SOL, BNB, whatever.
But if you are "trading," with the liquidity framework on altcoins you need to consider one thing: because altcoins have smaller market caps—even major altcoins are still quite large, but relative to Bitcoin they're small—the smaller market cap means the possibility of large whales, smart money, or institutions manipulating the price is greater. This is not conspiracy theory, it's a hard fact. If you've seen small coins in crypto, take the most extreme examples, like a long time ago TRB was pulled from 9 to over 600, obviously someone was manipulating it. Or like LPT, the old coin PEOPLE in 2024, ZRX—these are clearly manipulated coins, there are manipulators inside.
You say, does Ethereum have a whale? I believe not, after all, its market cap is big enough. But its market cap is still relatively small compared to Bitcoin, so when we take that liquidity framework originally used for analyzing Bitcoin and apply it to altcoins for short-to-medium-term trading, we have to lower the weighting a bit, because we must also factor in the higher likelihood of this coin being manipulated. The whale you imagine may not behave like the real whale. For instance, if this whale simply doesn’t like playing liquidity hunting, then there’s nothing you can do, because the price is always up to him. When using stop hunts and liquidity to analyze the market, the weighting has to be forced down. You can’t apply the exact same weighting to Bitcoin and to these altcoins; otherwise it becomes a bit of a forced fit and not quite appropriate.
12. Asset Allocation and the Strike Zone: Don’t Buy Just Because “It’s Going Up”
Victor: Mr. Beggar, how would you allocate different assets right now? We can see from on-chain data that BTC is gradually entering a zone where you can buy the dip, but on the other hand, the stock market has been on a tear all year, especially AI and semiconductors. Just investing in QQQ (Nasdaq 100 ETF) has already delivered great returns this year. How would you allocate among BTC, the broad US stock market, and individual stocks? If I start dollar-cost averaging into BTC now, will I miss out on opportunity cost because the stock market is performing so well and end up earning less of the market’s Beta? How should we position ourselves at this point in time?
Mr. Beggar: I’ll break this question into three pieces.
The first piece is my own asset allocation. My style is very simple: after living expenses, half goes into crypto and half into Taiwan stocks and US stocks, primarily US stocks. This is just my personal preference; there is no absolute right or wrong. Long-time followers might remember that I publicly bought the dip in Taiwan and US stocks in April 2025. In the stock market I mainly do index investing, plus a tiny bit of individual stocks. I bought a little TSMC, but I’m not watching it now — I just leave it alone. Only when the next major crisis appears would I possibly hedge or clear my position, and that sort of move happens very infrequently, maybe once every five or even ten years. So you can set that part aside; it’s a long-term investment. The other half is in crypto, which is the cyclical trading and short- to medium-term swing plays I usually share.
The second piece: with semiconductors and AI so red-hot right now, every day you open the charts and see them going up, and any pullback is just a shallow dip before they keep surging. How should retail investors deal with this “only goes up, never drops” situation? Should they just rush in head-first, or wait for a crash to buy? There’s no absolute answer, but the key point is: you should not buy simply because it is going up. The fact that it went up and you saw it go up, and therefore want to buy — that is not a valid reason to buy. The only reason to buy is that you expect it to go up in the future. You need to look at the future, not the present or the past. How do you know whether it will go up in the future? Exactly — that is the hardest part of trading. You need enough familiarity with it, a very strong understanding, and you have to do a lot of research. You cannot just buy because you see it keep going up. Have you ever thought: if you buy and it goes up 10%, you’re happy, but then it crashes 20%, what do you do? Do you add to your position or cut your losses and get out? You can’t start thinking about these things only after you’ve bought in; you need to anticipate them before you buy.
The third piece is the so-called baseball theory, meaning the concept of the strike zone. When you are unfamiliar with something but still want to operate in a field you don’t know, you are effectively just liquidity for the market. Because you have no idea when to take profits when it keeps rising, nor whether you should add to your position or run away if it drops after you buy. If you want to trade the short to medium term, it’s essentially entering a zero-sum game. Whose money do you plan to make? Do you think there are people in this market whose money can be taken by someone like you, who hasn’t done any research on the market at all? That logic clearly doesn’t hold.
So I often emphasize the strike zone: you have to work within the areas you are familiar with. I don’t have a very deep understanding of semiconductors and AI, so my strategy in the stock market has always been the same: index investing, with an extra 10% to 20% allocated to individual stocks that I believe have Alpha, but the majority is still index investing. Because I know that as long as I hold and let time compound for me, I can earn the Beta I deserve, and at the very least I won’t miss out on the market’s Beta. Crypto, on the other hand, is my strike zone. The bottoms and tops I identify are the trades I’m more skilled at and very confident in. So if you ask me whether I would move that 50% crypto allocation into US stocks — it’s basically impossible, because the proportions were set from the very beginning.
One thing I’m very certain about: on the day when Bitcoin truly hits its bottom in the future, the market will be overwhelmingly bearish. Everyone will agree that crypto is finished and Bitcoin is finished, and at that moment I will actually be more at ease stepping in. Anyone who scrolls through Twitter will notice that when Bitcoin drops 3% in a day, all the shorts come out and everyone starts shouting that it’s over. Even a 3% or 5% move can cause such a huge uproar. Look at the recent drop from 82-83K down to 59K: people’s sentiment went from “the bull is back, the bull-bear boundary has been broken, a new bull market is about to begin” to suddenly “Bitcoin is going to crash to 30K.” That emotional swing is terrifying. So I’m very sure that at the real moment to buy the bottom, nobody will even care. People will be more inclined to chase themes like SpaceX, OpenAI, Anthropic, or semiconductor AI. That will be the best time for me to quietly accumulate Bitcoin. In practice, of course, I will still combine that with the data from the deep bear bottom model; that data gives me the greatest confidence to buy the dip.
So to summarize for everyone: if you really want to charge into AI and semiconductors to make that money, you need to think through a few things first. First, if it goes up after you buy, do you want to sell, and at what gain? If you sell and it keeps going up another 20% or 30%, is that going to make you uncomfortable? Second, if it immediately drops after you buy, are you going to cut your losses? Or how much does it have to fall before you add to your position, or add again, or cut and get out right away? There are no right answers to any of these. It depends on your risk tolerance, your source of funds (using a loan puts you under extreme pressure; using idle cash is relatively less stressful), and your research on these companies. What makes you think buying now can yield a profit? What events or macro conditions do you expect will trigger that rise? If the market doesn’t follow your expectations, how will you respond?
This advice may not directly help you make money, but I’m certain it can help you avoid losing money you shouldn’t lose. Even if you earn a little less, that money wasn’t yours to earn in the first place. You absolutely must earn wealth that is within your own circle of competence. Don’t invest out of a moment of spite or just because you see everyone else piling in. That is some advice I can share with you all.
