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Bitcoinindex

Log channels of bitcoins entire history suggest serious upsideIm seeing confluence of last bull market cycles potential pennant target(yellow dotted line) and the current bitcoin cycle flag’s measured move line (purple target). Now I’m not suggesting that we will definitely reach this target level on the current bull market, as we have already seen this was a target from the pennant we broke up from during the last bull market and have already had a bear market since then before getting anywhere near the target, so there’s a solid chance we could see another bear market before finally reaching this target in the bull market after the current one. However considering the bitcoin etfs have led to such an exponential increase in institutional buying, there’s also still a decent probability that we could somehow hit this target during the current bull market. A safer bet is probably somewhere around 120-140k imo,then again if we have a massive correction here thats larger than the average 30-40% corrections we usually have during bull markets maybe that could help reset the health of the market to prolong it and allow it to reach higher heights.Hard to say. Either way I wanted to post a copy of this idea while I have it charted so I can look back it later to see how price action responds to these channel trendlines once it reaches them. If somehow e do reach the full target of the current bullflag we are breaking up from we could see anywhere from 300-320k the dotted blue line I included is for if the previous bull pennants pole is actually the fully extended price impulse, if so i am almost certain it will take at least 1-3 more bull markets before we would reach the full dotted blue line. I also have a monthly char that shows key channels that connect the previous few bull and bear cycles tops and bottoms but not the entire history like this one does and those channels would only allow for about 140-150k top in 2025 if we were to stay inside of them….if we broke out of them that’s when the targets shown here then start to become more of a reality in the current bull run. Until then I won’t expect anything above 140-160k and more realistically probably 120k range. Still worth posting this to eep a better eye on it. *not financial advice*
INDEX:BTCUSD
by DrDovetail
2
using sss and trama as a guidexbt is trending in bull reversal, and we have an hourly pullback from the current day high that is showing price will revisit one of these levels. the most bullish case is we stay long sss and qqe 15 minute and bounce off signal or moving average and that is marked out in dark green. the slightly less bullish case is if we go for a touch of rising trama. if we bounce from there the range is marked out in light green. the slightly more bearish case is if we break trama and head for that sss supply zone. this is an area we could still bounce from and its marked out in light red. if we go red sse and qqe and break beneath sss supply zone we could follow the path marked in dark red. over all were still in a trending market that is bullish.
BITMEX:XBTLong
by cerealpatterns
Dollar vs Bitcoin: who wins?Hey guys. In this study I compare the dominance of the dollar in the crypto market, against the price of Bitcoin. The dominance of the dollar in stable coins represents the percentage of capital in this asset in relation to the cryptocurrency market as a whole. When this percentage rises, it means that people are more positioned in dollars. On the contrary, when the percentage drops, it means that there is a higher positioning in the other cryptoassets. If we look at the dominance of stable coins, such as 'USDT.D' (Theter), 'USDC.D' (Circle), etc., and compare with Bitcoin, we can say that there is a negative correlation. In the graph at the top that I present to you, I added the dominance of all the important stable coins -- USDT, USDC, DAI, UST, BUSD, HUSD, USDK. And not to leave out the weight of the traditional market, I also added the DXY (U.S. Dollar Currency Index). In this one I divided the value by 100, aiming to have a more adequate measure proportion. On the bottom chart of the screen we have the price of Bitcoin, in an ascending triangle, which is a bullish pattern. Fact. Regardless of war, pandemic, FED, news or whatever. We have two important regions within the parallel channel, within the dollar chart: every time the value reaches the top of the channel, we have strong Bitcoin appreciation; and every time the value reaches the bottom of the channel, we have a strong devaluation of Bitcoin. In the current scenario, we are in an important region, indicating a possible depletion of dollar strength, through a 'shoulder-head-shoulder' graphic formation, which would be a bullish scenario for Bitcoin. However, not everything is flowers. Imagine that you are a whale (if you are, congratulations), and knowing the value of BTC and everything it represents (of you being your own bank, having the freedom to do whatever you want with YOUR money, regardless of parasite politicians), you want to acquire more BTCs. Well then, what would you do? I would try to buy it as cheaply as possible. And that includes manipulating the market, creating fear, panic, FOMO (...) (not that I would) We are seeing a flurry of news, both for the positive and for the negative... saying that institutional X acquired millions of Bitcoins... that company Y adopted Bitcoin as a form of payment. 'Everyone is buying, now I'll be a millionaire'... Meanwhile, proponents of the apocalypse always claim that the end of the world is coming: 'war on Ukraine', 'new pandemic wave', 'Fed monetary tightening'... All this for the sardine to get confused, buying top and selling bottom, and rotating equity. Who wins are the brokers with the brokerage fees. And even if it makes sense to execute a sell trade in bottom (imagining the world is going to end), there is always a buyer on the counterparty. Just to reflect. So watch out for the news.
GLASSNODE:HUSD_MARKETCAPLong
by andre_007
Will Bitcoin Go Up?Hello traders. Lately I've been doing my technical analysis alone, due to lack of time to clearly write ideas. But this time I managed to share. I hope it helps. Any suggestion or idea, just say the word. Some things I say very briefly to save space. Here I will analyze some aspects that I think relevant. 1. Stochastic On the weekly chart, looking at the Stochastic Momentum Index Ergodic (SMI), we see important momentum. I particularly use two overlapping periods. With blue and red lines, I use a shorter period, with a loopback of 21 periods and a smoothing of 5. With green and purple lines, I use a long period, with a loopback of 100 periods and a smoothing of 5. When both cross upwards, and there is considerable upside up to the 100 limit, we can see in the past that it was an explosive upswing moment. When that happened, I underlined the circles in red. 2. Moving Averages (Rainbow) Monthly chart: I use this rainbow of exponential moving averages ranging from the 5-period average to 85-period. It's a custom version that I developed myself... I'll publish it soon. What we can see here is that the last time the price hit the bottom of the rainbow was during the pandemic. If that happens now, the price would be between $20,000 and $18,000. Weekly chart: On the weekly chart I circled the times when the price broke the rainbow, just like it did now recently. If the behavior repeats the past, we would have the following scenarios: Scene 1: Scenario 2: Scenario 3: Scenario 4: Scenario 5: Scenario 6: Scenario 7: It is worth mentioning that there are 7 circles. Out of the 7 times this happened, 4 times we had a bullish scenario, 2 times we had a bearish scenario, and 1 time we had a tie scenario. That is, in 57% of the time the price went up, in 0.15% it was undefined and in 28% of the time the price went down. Now we are in the eighth time... what will happen? 3. Pitchfork Long-term Looking at the long-term Pitchfork, we see that the price is within the red range. The last time the price broke below was in the pandemic in March/2020. The central white line can be a strong resistance. 4. Pitchfork Short-term Looking at the short-term inverse fork, we see a possible breakout of the diagonal in green. 5. Shoulder-head-shoulder The chart appears to be forming a head-to-shoulder, which is nothing more than a weakening of the uptrend. However, this bearish pattern hasn't even happened yet, and it may never happen. It will only confirm if there is a pullback to the downside and the price fails to break the $52k resistance. 6. Fib Speed ​​Resistance Fan In this chart pattern we see that the price is in the green range. Theoretically, the maximum drop would be in the blue range, around $32k 7. Trend-Based Fib Time Interestingly, tracing the bottom of August/2015 to the top of December/2017, we see that the 1,382 Fibonacci time coincides with the beginning of the war. Would another important period be in September 2022? I do not know... 8. Projection to next targets In the first Fibonacci projection we would theoretically have a target of $268,000 at 100% Fibo. In the second longest projection, it could 100% drop by $480,000. 9. Bullish channel and bar patterns The price remains within the bullish channel. I put some scenarios in the figures above. Scenario 1: Scenario 2: Scenario 3: 10. Elliott Waves I'm not an ace in Elliot waves, but I think that we possibly ended the corrective wave C within Elliott wave 2. 11. 4h chart with bearish divergence We have a bearish divergence on the 4-hour chart. 12. Gap in the futures of CME In the Bitcoin CME Futures, we have a gap. Will it be filled? 13. Price zones in the futures of CME There is strong resistance at $52k. If it drops to $45,500, it would be a great entry price. It can fall into the vacuum between US$42,000. 14. NVT - Network Value to Transactions The indicator shows a strong rise. 15. Volumes in on-chain data In red we have the average movement in stable coins (USDT, USDC, etc.) In green we have the average movement in BTC (both BTC on the Bitcoin network and WBTC enveloped on the Ethereum network). In yellow we have the average movement in the main DeFi platforms (Curve, AAVE, etc.). We can see a progressive drop in volume, with the last peak on 01/28/22 indicating strong support at $40k ~ $38k.
INDEX:BTCUSDLong
by andre_007
Market in troubled time, including BitcoinHi. Hope you all are well. Price analysis Considering the Arnaud Legoux averages, I can see the strength of the trend within the price chart itself. What we have? The average of 32 (green) has crossed below the average of 64 (blue), and there is now an expansion in width between these two averages. And the average of 128 (white) started to slant down. This indicates a fall in the short and medium term. The averages of 256 (yellow) and 512 (orange) still point up, but tend to sideways, indicating possible support and resistance. Hard time to predict. In a possible bigger drop, theoretically the next support would be in the average of 1024 (cyan), and if a meteor falls on the Earth it would be in the average of 2048 (purple). In short, we see a driving force pushing the price down, at least in the short term. It remains to be seen how long this will happen. On-chain analysis Now let's look at Glassnode's indicator 'Price Drawdown from ATH', which is the percent drawdown of the asset's price from the previous all-time high. Currently, the loss of those who bought at the top is 27% (0.27 x 100). What is the crux of this indicator? The best buying region is when the drawdown reaches high values, and then there is an upward reversal. We can cite the peak of July 20, 2021, when the drawdown reached 50%. Soon after that, the market understood that it was a good region to buy, and the price continued to rise. If this happens again and the market crashes, the next good entry price would be $28,755, when the drawdown reaches 50%.
INDEX:BTCUSDShort
by andre_007
1
Bitcoin at a turning point [EN-US]Daily Graph NVT (Network Value to Transaction) indicator This indicator describes the relationship between volume of transfers and market capitalization. It is also described as the price/earnings ratio of cryptocurrencies. The calculation is done by dividing the network value by the daily volume. At the moment, we can verify an indefinite moment. A good bullish indicator would be to break resistance (blue dotted line), and stay above 75. Accumulated Volume Percent This volume indicator works similarly to OBV, except that it puts weight on volumes according to intraday volatility. You can see a resistance on the dotted line at 5. Breaking up would be a bullish signal. Breaking below zero would be a bearish signal. Simple Moving Average of 365 periods Moving averages are great tools for plotting possible supports and resistances. As we can see, the 365-day average is holding the price. If it is broken, it is a warning sign for a bearish move. Schiff's Fork Schiff's fork demonstrates the projection of Bitcoin price in the last periods, since May/2021. If the price breaks the upper limit, it could be a bullish signal. Watch out for false breakouts. Corona Day Support The red dotted line is a support traced from March/2020. If this line is broken, watch out for a Bear Market. Bearish channel The bearish channel, highlighted in orange, is another important indication. Watch out if the price breaks the resistance or support of this channel. * Follow your own risk management * Past profitability is no guarantee of future profitability
INDEX:BTCUSD
by andre_007
Bitcoin Index ($XBT) Analysis by imRedaSouhail#Bitcoin Index $XBT Analysis🧩// Head and Shoulders. ----- Bitcoin is still Bearish📉 A head and shoulders pattern is a chart formation that appears as a baseline with three peaks, the outside two are close in height and the middle is highest. as technical analysts, a head and shoulders pattern describes a specific chart formation that predicts a bullish-to-bearish trend reversal. ----- Bitcoin index may get a bullish correction to retest its previous Broken Neckline and we might see it act as a resistance level for The $XBT index. ----- ISMASHPROFIT 💎
BITMEX:XBT
by TopGBanks
1
BTC DOMINANCE Index: Is it Altseason right now?Greeting from IRAN to whole trading community 💙✔ BTC D. made a new ATL in 2018 which was about 38% After that index started an uptrend which brought back the index above 50% In 2019 and 2020 we haven't seen BTC D. dropped under 50% In early 2021 BTC D. was above 70% and after that it started a downtrend which last until now BTC D. is in the lowest level since 2018!!!!! Is it ALTSEASON right now? Whats your opinion? Do you prefer to hodl bitcoin or switch to the altcoins? KEEP IT SIMPLE :)
CRYPTOCAP:BTC.D
by nima-mohammadkhani
15
Curvy Mayhem, Stock-to-Flow, and a Critique of Pure SimplicityDisclaimer: This is not financial advice. I am not a statistician. I am not a trading/investing expert. I am a wildlife biologist. This is just a regurgitation of my research, thoughts, and opinions, along with my attempt at having fun with numbers to create an incredibly speculative model for Bitcoin’s future price action. Hang in there folks, this is a long one. Since I entered the crypto realm in 2017 (I know, such a newbie), I have been obsessed with Bitcoin’s historical logarithmic price chart. Something about the way it smoothly sweeps across the orders of magnitude separating its former obscurity from its financial relevance has drawn me into a fantasy of elegant mathematics, an illusion of design, and a tempting allure for fate. The hindsight is heavy, and it all seems so simple, but it rarely ever is. I often see BTC log charts with curves that march atop the market cycle peaks or support the lengthy slumber of the prices below. I’ve fallen into this habit myself, but these curves are all equally vapid. You can fit infinite curves to any three points after all. (Which of the twelve curves above is the correct one? I personally like light green.) When we create models, we mustn’t be arbitrary for the sake of beauty. What feels right is usually not what ends up being right. Any experienced day-trader will tell you this. We need objectivity. Financial models are hard to create. For centuries, humans have struggled to keep up with the emergent complexity of the markets they formed. The intricacies of our systems tend to outpace us, and some things forever elude our understanding. However, we desire simple answers to complex questions. We see patterns in everything; it’s just an evolutionary heuristic that our prehistoric ancestors utilized for hunting, gathering, and not dying. But in our hyper-complex modern world, this feature of pattern recognition is usually used to a fault. In the following paragraphs, I outline some issues with models created by others and myself. On the surface, these models appear elegant and well-fit, but when we delve into the assumptions behind such models we often find that simple answers are woefully insufficient to predict the future of a complex and turbulent world. BITCOIN STOCK TO FLOW MODEL While the controversial Stock-to-Flow (S2F) model introduced in 2019 by Plan B has proven to be a good fit for Bitcoin’s early price growth thus far, there are several fundamental problems with the model, like failure to account for demand as an influence of price and the lack of a relationship between price and S2F in other scarce stores of value including cryptocurrencies. But perhaps worst of all, this model fails to address the growth-resistant factors that Bitcoin will soon face. Linear regression models on a log-log plot predict infinite growth when extrapolated. Whether limitations arise from resource depletion, social and political behaviour through competition and regulation, or even the laws of physics, nothing can grow indefinitely. So what will ultimately limit Bitcoin? Let’s start with the energy consumption problem. Bitcoin already consumes about 0.5% of the world’s energy supply, more than most individual countries on the planet, and this percentage is increasing rapidly. The issue lies with Bitcoin’s proof-of-work architecture, an algorithm used in the Bitcoin blockchain that incentivizes miners to expend computational energy to cryptographically secure others’ transactions. As speculation drives the price of Bitcoin higher and the available minable supply decreases, miners face greater competition and expend more energy. Eventually, and probably sooner than later, Bitcoin’s price will rise to such a level that the hash rate, and subsequent mining cost, will no longer be able to keep up. Even putting human behaviour aside, Bitcoin’s energy consumption would exceed the entire energy supply on Earth by the 2030’s given the unfettered growth predicted by the S2F model. This may be the gravest threat to Bitcoin’s development into an economic juggernaut, though some solutions like proof-of-stake have been proposed to address this crisis. Two more restrictive factors on Bitcoin’s price are governmental regulation and financial pressure. For the most part, Bitcoin has been allowed to grow naturally without too much interference. However, as it becomes a more significant market force, powerful governmental and financial forces will inevitably attempt to influence, control, or even destroy it. Perhaps the latter is unlikely to happen, if not impossible to do, but market adoption can absolutely be decelerated, leading to a suppression of demand and price. Finally, assuming relatively tame fiat inflation rates, there’s not even enough money on Earth to support the level of growth predicted by the S2F model for even a couple more decades. Eventually, the market will become saturated, demand will diminish, and the price will stabilize. The only way this model works and gives us bitcoins worth $1 trillion in 2050 is if USD inflation goes nuclear and sends the global economy into abject chaos. Even Plan B has admitted as much. By then, your crypto gains would probably be the last thing on your mind. I think it’s clear that any models attempting to predict the future price of Bitcoin need to include a factor that limits growth over time or extrapolates from existing decelerating price patterns. So I decided to create two alternative models based solely on Bitcoin’s price history. For simplicity’s sake, I chose the more speculative route of creating a model based on the peaks of each of Bitcoin’s bubbles. (Note: Data used in statistical analysis was monthly high bitcoin prices collected from barchart.com and yahoo finance.) FOUR-PARAMETER LOGISTIC REGRESSION MODEL Even a brief glance at the logarithmic chart shows a pattern of price bursts steadily decreasing in intensity, revealing a long-term trend of logistic growth. This is not surprising, considering it gets prohibitively harder to 10x a market cap the second, third, or eighth time around. The best-fitting model for four points following a logistic pattern is, of course, the four-parameter logistic model. This provides a moving target for an end to this bull run. (Note: I made this chart before INDEX:BTCUSD was released, so pre-August 2011 prices were drawn in) Despite giving a tamer near-term outlook, this model still overestimates long-term prices and runs into many of the same problems as S2F, leveling out at a price of 10^230 USD long after our planet is gone and stars stop forming… but at least it levels out. I would also argue that this model is heavily overfitted, using four parameters given only four data points. Furthermore, it places too much emphasis on the starting price of Bitcoin, which may have had little or no influence on its future price. MARKET CYCLE RATE-OF-INCREASE POWER REGRESSION MODEL Instead, I looked to a different measure to predict Bitcoin’s bubble behaviour: price increase over time within each market cycle, extrapolated with a power regression model. I defined market cycles as the time between peaks and calculated the percentage price increase over time (in months) from peak to peak. During the first cycle, when Bitcoin jumped from its first-traded value of $0.09 to about $30, the rate of increase over time was astronomical. The percentage rise of each subsequent bubble has decreased since then while market cycles have lengthened. This gives us three complete market cycles ending in June 2011, November 2013, and December 2017, and three data points describing, as an average monthly percentage, the constant rates of increase in price from one peak to the next. Extrapolated with a power regression (y = 2758x^-4.119; R^2 = 0.994), we are left with a shallower rate of increase between the 2017 peak and the approaching peak. This again provides a linear moving target for an end to the run. On a logarithmic chart, the straight lines between peaks look a little different. This model proves much more flexible than many others. Instead of a specific date or price level, Bitcoin is free to trade however it wishes until the moving target is hit, whereupon the bubble will deflate and we enter a new cycle with a new sloped upper bound. The slope of this bound is determined by the previous market-cycle peak price and the next rate-of-increase value provided by the power regression. These slopes constantly increase, but by less and less each cycle until the price of Bitcoin plateaus. The price level of this ceiling would be determined by the frequency/length of market cycles. Time itself acts as (or at least tracks) the decelerating force. So, it’s a fun model, and quite pretty on a logarithmic chart, but how good is it actually? Well… Problems with this model: It fails to properly define peaks. One can gain an intuitive sense of when each bubble ended, but without an objective definition of this point, the very parameters on which this model relies can be interpreted differently by others. How are we to know if this current run has ended? Was the spike in April 2013 a peak? (Probably not, but you get the point). This one is easy enough to remedy, but I can’t be bothered. We have only three data points, hardly enough to make a reliable trend, let alone one we can extrapolate (Counterpoint: The power regression extrapolation of only the first two points predicts the third with a surprisingly reasonable margin of error for these scales – about 0.2 orders of magnitude, suggesting this model may already have some predictive power. In other words, if you had followed this dubious two-point model in 2017, you’d have sold at about $12,000.). Additionally, extrapolation leaves us with a much greater margin of error than interpolation, especially when we’re working with such a small sample size. At this point, we risk falling into the trap of moving the goalposts by adjusting our model to match new data as it comes in, not unlike what has been done with the S2F model. This ad hoc method constantly maintains the fit of a model but proves that the initial version had somewhat poor long-term predictive power to begin with. This model also places too much emphasis on Bitcoin’s starting price in July 2010. I find it unlikely that this asset’s long-term growth dynamics were heavily influenced by this initial value. It relies on the assumption that the declining rate-of-increase of market-cycle price peaks can be extrapolated into the future. It might be possible to justify this, but I can’t be bothered. This write-up is already nearing 2,000 words. The use of a power regression forces the assumption that long-term growth will never be negative; instead, Bitcoin will approach a plateau at some point. While there are any number of black swan events that could deflate Bitcoin’s price, no simple price extrapolation model can predict and incorporate these possibilities with any reliability. If this model somehow plays out perfectly, I’d be elated. But I wouldn’t have been right. I’d have been lucky. The possibilities for Bitcoin’s behaviour during this cycle and the next are innumerable. All you need is 3 data points and you can make anything happen. Perhaps you remember that colorful, curvy chart a bit further up. However, that doesn’t mean it’s not fun to try. Probing the long-term price action of a novel market with statistical fervor has proven to be a rather entertaining and educational experience. It also shows the difficulty, and perhaps the futility, of finding simple solutions to incredibly complex systems. CONCLUSION I recently watched a youtube video posted by an astrophysicist. He discussed whether we should rely on beauty and simplicity when creating models to accurately describe the intricate and incredibly complex details of our physical universe. Take the theory of gravity and planetary motion, for example. As physicists, theoreticians, and thinkers studied the skies for millennia and searched for simple answers, the theories progressed from that of circular orbits, to more complex ellipses, to a law for gravitational attraction, to requiring special and general relativity – a dramatic increase in complexity and certainly a less beautiful solution, even if more accurate. I have noticed the same trend in my own field. The theories describing ecosystem equilibrium and the interactions between species have grown more complex as ecologists learn more about the biosphere at various resolutions. I believe these same principles can be applied to most aspects of reality. Simplicity has its place, but we often take it for granted. As tempting as simplicity and beauty are, we mustn’t fail to respect and embrace the complexity of our world, however we interact with it.
INDEX:BTCUSD
by Kelly_John
2
Bitcoin Index Bitcoin versus major world currencies. Bearish market for now, no doubt. I would not go long at any case. Breakdown below yearly S1 will send BTC to the lowest yearly low of S3 or even S4. I have bearish look because: 1. Price below yearly pivot and year CPR (opened below those, tested and rejected from both) 2. Price below monthly pivot and monthly CPR (opened below those and rejected from both) 3. Lower value relationships (lower lows) between both yearly and monthly pivots, CPRs. Though this year we did have CAMR3-CAMS3 (value area) squeeze within last yearly value area. And if price would start trendling above current yearly CAMR3 then I would take a bullish stance but it did not and more narrow 2020 CPR suggests more volatility to the downside. Price might reach 2020 CAMS4.
GEMINI:BTCUSDShort
by ICFX
BTD.D | Inverse Head & Shoulder Pattern Forming?Seems like there is potential for there to be an inverse head and shoulder parttern to form on the BTC.D chart with the neckline at the 67.94% mark. What could this mean if so? Seeing an increase in Bitcoin dominance could mean two potential things: 1. Bitcoin breaks out beating the rest of the altcoin market I see this as unlikely as given the current macro environment of the economy but possible albeit briefly 2. A large sell off in the crypto markets with altcoins losing the greatest value This is more probable. We're more likely to see a further sell off in traditional markets as although there is a bounce in equities there's no fundamental reason why other than central banks printing money and providing as much liquidity to markets as possible, however what is really causing a sell off is the various governments guidance. Limited amount of business operating, mass unemployment, most people staying home, and extremely limited limited economic activity.
CRYPTOCAP:BTC.D
by BullAndBearCrypto