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Stocktoflow

BTC $225 000+ By June 2022 - According to Bitcoin Stock-to-FlowAs you can see Bitcoin generated more than 12 000% in both previous cycles after halving. We can observe similarities in the actual pattern and the previous ciyles' pattern. If bitcoin follows the trend and repeats the movement made in the previous cicles, the price should be at least $225 000 by the end of June 2022. In the best case scenario the price could rise even to $350 000 - $400 000. You may think it's just a crazy unbased prediction, but if you do your own research you can see, bitcoin offers one of the best investment opportunity at the moment. This is not a financial advice, it's my opinion based on Bitcoin scarcity and historical macro movements. If bitcoin fails to reach the mentioned area, PlanB's Stock-to-Flow Model will fail too. I won't start arguing, if you believe it, will make your own research. If you agree, apriciate it and leave a comment. If you disagree, share your critical analysis! HODL to the Moon.
BITSTAMP:BTCUSDLong
by CryptoMexMCO
Bitcoin Hash Ribbons Buy SignalWeekly Hash Ribbons buy signal confirmed, price: $43,829 (CB). This would be the 12th buy signal in 9.5 years if not mistaken, after the most aggressive miner capitulation since 2021 with hash rate dropping by more than 50%. . This buy signal is the first in 8 months as well as first of 2021, since the price of $19.375 last year. Recent buy signals : Nov 2020: $19,375 Jul 2020: $9,303 Apr 2020: $7,706 Dec 2019: $7,384 Jan 2019: $3,514 The obvious trade. Reward/risk: 6.5:1. Hash Ribbons indicator: Stock to Flow Rainbow indicator: Logarithmic growth in 2021:
COINBASE:BTCUSDLong
by dragononcrypto
1
BTCUSD Wyckoff accumulation Phase C to D (on the 1hr)Wyckoff accumulation after big mid-May dump. Important inflection point for S2F model IMHO. Would like to see $33k hold and then start to push upwards over next couple of days. $41k breakout to the upside mid July would validate short term Wyckoff thesis, help uphold integrity of S2F model, and restore medium-long term bull run towards end of the year. Pink highlighter is approximate trajectory for successful model. Not financial advice!
BITSTAMP:BTCUSDLong
by SBL2022
BTCUSD Wyckoff accumulation Phase C to D (on the 1hr)Wyckoff accumulation after big mid-May dump. Important inflection point for S2F model IMHO. Would like to see $33k hold and then start to push upwards over next couple of days. $41k breakout to the upside mid July would validate short term Wyckoff thesis, uphold integrity of S2F model, and restore medium-long term bull run towards end of the year. Pink highlighter is approximate trajectory for successful model. Not financial advice!
BITSTAMP:BTCUSDLong
by SBL2022
BTCUSD Wyckoff consolidation Phase C to D (on the 1hr)Wyckoff accumulation after big mid-May dump. Important inflection point for S2F model IMHO. Would like to see $33k hold and then start to push upwards over next couple of days. $41k breakout to the upside mid July would validate short term Wyckoff thesis, uphold integrity of S2F model, and restore medium-long term bull run towards end of the year. Pink highlighter is approximate trajectory for successful model. Not financial advice!
BITSTAMP:BTCUSDLong
by SBL2022
BTC Log Cycles - Based on HalvingsExperimenting with Bitcoin high time frame log charts, I began to notice some patterns. Please note: This is a work in progress and by no means financial advice. Highlighted in yellow are two box areas, the rest is built around them. The similarity appears striking, imo. Does this mean the chart will continue to produce and follow these patterns? Log charts are generally meant for and used with curved lines. However, when one finds a straight forward geometric pattern between the last 2 major cycles and this one, based on halvings... couldn't help but continue to explore, and hope this is interesting for you too. I will continue to monitor and update, if this chart and pattern continues to make sense as it unfolds, and will attempt to simplify so it is easier to read. But wanted to post this before going to sleep, and again, this is only a work in progress. Any feedback, questions or suggestions are welcome. Best.
BITSTAMP:BTCUSDLong
by DestinyJV
6
Do Traders Use Logarithmic Charts? - Bitcoin Stock to FlowI was asked on social media if I use logarithmic charts in my trading. The short answer is "no, not tactically for short term trading" but they do have use in analyzing long term exponentially growing instruments when trying to find patterns. One key use of logarithmic chart analysis is for the Bitcoin Stock to Flow model. This model calculates the price of Bitcoin in relation to its supply and decreasing production. Link to source: medium.com
BITSTAMP:BTCUSD
by norok
3
An Analysis of Macro-Scale Bitcoin CyclesTo date, Bitcoin has followed a repeating cyclic pattern that appears to be directly driven by the mining rate Halvenings. It is useful to take a hard look at what previous cycles were like, in order to capitalize on the bull market happening today. An enormous amount of profit stands to be made by the investor who succeeds in selling a significant share of his or her portfolio as close to the theoretical top of the bull market as possible, followed by a buyback as close to the theoretical bottom of the inevitable bear market as possible. This equity could then be traded at safe prices in the accumulation phase to stack even more profits in preparation for the following bubble. There are several indicators to help gauge how healthy the bull cycle is, such as how much coins are being offloaded from exchanges, the relative unrealized profit/loss, and my favorite, the stock-to-flow model. This chart is an analysis of purely the naked price action on a logarithmic scale, and what characteristics can be seen from it. The important takeaways: None of the previous bull cycles have lasted more than 300 days The percentage increase of each bull market from the previous ATH is decreasing in magnitude each time around. If the bull market follows the same pattern as 2017, then we would expect to top out no more than half the percentage of the 2017 bubble's size. This is due to the ever increasing enormity of Bitcoin's market cap, making it more difficult for prices to rise quickly. One way to mitigate the reduction in percentage gains is to have a portion of your portfolio in top ten altcoins as they will accrete much faster due to the smaller market caps. This obviously has the trade off of increased risk but could be a helpful move for new cryptocurrency investors with low starting capital. Bitcoin bull cycles tend to rise much faster near the end of the cycle. This makes sense if you think about it. The faster the price rises, the more incentive there is for holders to sell more than they are buying. Once a certain threshold is arrived at, the top is put in. A time based selling strategy appears to be a more effective approach than a price based selling strategy. It should absolutely be possible to catch a decent portion of the stratospheric 'finale' of a bitcoin bull cycle by gradually selling away your portfolio as the bull cycle ages. I personally will not start selling until the bubble is at least 240 days old. We are very likely not even half of the way through the current bull cycle. There is absolutely no reason for the pattern to change to shorter bull markets. In fact, the contrarians to this view of Bitcoin's macro picture overwhelmingly support the idea of longer bull markets -- a so called 'super-cycle'. This idea has some merit, making it important to not sell all of your holdings away in the coming months. I have seen no such talk of the opposite happening. Selling heavily now, at 126 days in, will probably cost a fortune in the long run. Thank you for reading, I hope this write-up proves of some use to you.
BITSTAMP:BTCUSD
by mises_satoshi
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
BTC: Pi Cycle, Log Growth, NVT and OBV primedGreetings! Bitcoin looks like it is primed for a final leg of its parabolic move based on a series of indicators which would suggest that alts will be topping in the months afterwards. Log Growth Curves by quantadelic These curves were based on calculations made in October of 2019 and so far have done a really good job of informing users on price action. The script is available but since I am a pine muggle I don't know how to update the data. None-the-less I have identified the fib-channels to either side of the 50% baseline as especially important for suggesting when big moves are going to occur. The purple box shows when the 61.8 level is exceeded and then tested as support BTC price action is right now in the process of confirming the level as support. It looks clearer on the weekly chart on the 3 day chart below. A view of the BLX ticker shows a wider view and shows that rejections at the 61.8 level have happened and been the cause of a major contraction. Pi Cycle Created by Philip Swift and popularized by www.lookintobitcoin.com Per Look Into Bitcoin The pi cycle top indicator goes back to April of 2019 and so it is another backwards looking indicator we are trying to use for the next top. A preliminary look at the main chart shows that once the 61.8 level is confirmed as support then shortly thereafter the pi-cylce flashes its top. The convergence of the two EMAs likewise looks very similar and so once again I think we will be flashing a topping signal in the next 4-6 weeks. On Balance Volume (with EMAs) By Mattzab This is one of my favorite indicators and I have pared it down to just the On Balance Volume and the 100 EMA. At our last market top we saw that OBV started to trend sideways and oscillate around the 100 EMA. The most important thing is the top of the box that was resistance to the OBV but price action was trending upward and setting higher highs. This technical double top sets up bearish divergence and is generally not a good thing. This time around we don't see the OBV oscillating around the 100 EMA and the resistance lasted longer the last go around. We do see two contacts on the top of the current box and I suspect when we get our break out we will again have a blow off top. The higher low on the OBV looks like an ascending triangle, but I am not sure we should be closing our positions just because the OBV reached its target. NVT by aamonkey There are a couple of NVTs out there, but I particularly like this one. It works on both the daily and weekly depending on your choice of timeframe and how much you want to be babying your trade. A look at our last top shows we can go from the middle of the yellow zone to the red zone where the sell signals occur. The weekly chart shows that we are flirting with eloping from the red zone of the ribbon which is why I will definitely not be holding on much longer should the daily NVT flash red. By the time the the weekly NVT falls into the yellow zone the bear trap is near complete. Which is fine if you used the green zone as a buy signal. Stock to Flow By yomofoV Historically price action has had lots of over-performance on the stock to flow but that over-performance has been reduced time over time. I myself have hoped for massive over-performance but I just don't see it happening this time around. This final bit is important. Below in blue is the weekly bollinger band top and baseline. The green is the TOP of the monthly BB. The bottoms are not shown because parabolic moves distort the bottom of the chart as the lower edge goes below zero. The baseline of the weekly is roughly the top of the monthly BB. Trying to buy the dip under these conditions is very risky because you could be looking for a bounce of the 20 week SMA and get a fist full of losses. One way you will be able to tell that the next bear season is upon us is the monthly bollinger bands assert themselves. We don't know the day or the hour but mathematically it has to happen as 95% of the price actin on the monthly chart has to occur within the monthly BB. My personal Battle Plan I am going to grab as much gains as I can in my preferred alts. I think that Dapp coins will top after BTC and then the currency coins, like Bitcoin Cash, Monero, Dash, etc will top after the Dapps but that is intuition right now. There are are going to be some honeybadgers out there like Link was the last bear market which was basically done bottoming out in months and just ravaged market share but we won't know what the honeybadgers are until they start to ravage, and most people will be in disbelief. An appeal If you find this worthwhile show it to some crypto-muggles you may know which may be unprepared for the upcoming move as well as the upcoming bear market. BTC loses 80% of its value all the times and a lot of the tools shown here can stop our friends from losing a lot of money if they are looking for a break of $100k as a buy signal when some of these other indicators are flashing sell signals.
BITSTAMP:BTCUSDLong
by This_Guhy
2
Bitcoin Log and Standard Scale TargetsThe red ray is anchored to the same price on both charts and the only think that has changed is the scale. The top has the stock to flow model and shows historic overperformance to the trend line. It is possible that we get even more over-performance this time around as the people entering the market may lack the sophistication as traders that have been around for a couple of years. There is some activity on the standard scale that I think is worth evaluating at a lower time frame and that is the green magnifying glass The first thing I is a classic Elliot wave pattern and that the red ray was the approximate peak of wave 3. That makes me think that the smart money got out there and started funneling gains into assets that are undervalued relative to bitcoin. Those would be found at the weekly lower limit of the Bollinger band or showing reversal patterns on btc pairs or in reversal structures (such as will be shown in the linked ideas). That means that this peak was formed by day traders and dumb money (sorry). The price action should to a continuation pattern with the lows falling within wave 4. If we see price action going below wave 4 it is time to waste-bin this idea. On higher time frames than the 4h it will look like price action found support on the red trend line as the A and C waves appears a wicks. The fact that wave 3 ended at the red trendline on the standard chart makes me think that we will see wave 3 end on the log chart above and then a blow off top will create wave 5 and then the next bear market. Speaking of dumb money (sorry again, I didn't make the terminology) the red ray has price action going out of the bitcoin log growth curves. There are different formulations of the log growth curves of course but this is one of the most used on trading view. Just as price action fell out of the log growth curve by over 50% we might see price action go above the log growth curve. And remember, if you are just buying bitcoin in regular payments and not trading eventually the whole chart up this point will look as flat as the chart does between 2014 and 2016. Nothing to stress about.
BITSTAMP:BTCUSD
by This_Guhy