BTCUSD 2023-2025 16k--62k-ish?Here we have BTC-USD-monthly with logistic (growth) function (phi-rameters are somewhat arbitrary) and with simple Triple Exp Moving Average.
Based on this, I am kind of thinking to buy in during the autumn 2023 (somewhere between 12k-16k), and I might be selling during the winter 2025 (somewhere between 44k-62k). Or maybe not.
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This is NOT a trading advise! (It is just my superbiased idea.)
The information shared is not meant to be, and do not constitute, financial, investment, trading, or other types of advice or recommendations!
Logistic
The cryptocurrency market is a market of expectationsLots of good news, but that's just at first glance.
Expectations and reality
1. Last week we had good news about XRP victory, and this news was spread all over the internet and the market reacted with growth. XRP is not a security, but those contracts sold to early stage funds may still be considered securities.
So the case is not closed yet and it will continue as a subject of manipulation
The SEC can appeal this decision at any appropriate time.
2. FTX - there are a lot of rumors and different statements now about the reopening of this exchange, there are a lot of forms on the net ( fraudulent and not) about FTX account recovery and confirmation. Hope is given:) not the fact that the funds will be restored
3. I would not be surprised if they start to restore UST and LUNA case, if they do not start to restore at least give hope. ( reference - the cryptocurrency market is a market of expectations )
4. BTC ETF.
This is the same expectation that has been jutting for a long time and now strong funds such as BlackRock have joined, which have been buying physical bitcoin through other funds for a long time (e.g. at least 10% of Microstrategy belongs to BlackRock).
On the expectation of ETF approval the market is inspired ( I wrote a post about Blackrock ).
In any case after ETF approval we will see a drop here there is a logic:
- ETF contracts can be bought more than physical bitcoins.
- Need a good entry point into the market, 30k+ is not the best entry point
- A drop in price with physical bitcoins + media resources etc. seems to me as very logical and very likely.
All these points should happen at the peak of the hype, when many disillusioned in crypto after FTX and other shocks will start to re-enter the market, it all explains the Logistic Curve - the speed of information dissemination .
The Which curve explains that when FTX crashed in November 2022 was the beginning of a new cycle, which I talked about in previous posts, then everyone was afraid and thought it would go even lower.
And the end zone of the cycle is when the crowd comes into the market, a lot of noise shouting about a bright future, we are on the cusp of these events.
At that time of course we will see a lot of dumb money big green candles on small capitalization altcoins. And that's the time to get out.
Frankly I got out even earlier in stablecoins and now I only do swing trades ( positional orders positions with small stop loss )
If we talk about the time when all this can happen, it is a difficult question, because according to my previous calculations in September-October I was already waiting for the bottom, I am still waiting for it and my portfolio 100% In stablecoins is a proof of it.
Well after the fall we will have the most interesting negative news, here is the list:
- SEC appeal question on XRP
- SEC questions to all crypto companies that made public sale - fines, lawsuit.
- Questions to crypto exchanges ( bankruptcy of crypto exchanges)
- Regulation
- CBDC implementation and trading in some jurisdictions BTC/CBDC ( currency )
You definitely won't want to buy cryptocurrency on news like this, and this will be the moment when the new cycle begins.
So ladies and gentlemen we are here for a long time and welcome to our community. And remember, trading is not a sprint - trading is a marathon.
Best regard EXCAVO
Bitcoin cycles + logistic curve = New bull run 2023-2025 I want to take a closer look at Bitcoin's price weekly logarithmic chart.
Firstly, the chart examines growth and fall cycles, sometimes referred to as economic cycles or trade cycles. As you can see in my analysis, the growth cycle usually lasts approximately 150 weeks and is always longer than the fall cycle that spans out over the course of approximately 51-60 weeks.
150 bars on Bitcoin's weekly price chart, mark the beginning of the next pulse of the growth cycle that we are currently in. Everything in our life is based on cyclical patterns, especially when it comes to financial markets.
If we analyze the rise and fall, we can conclude that the fall occurs faster than the growth of about three times.
About logistic curve
The logistic curve describes the speed of information dissemination among people. This graph describes the distribution of information in an environment.
At first, an instrument is of little interest to anyone, investors are afraid of buying it, and its price fluctuates around r °. At this time, the initiated ("elite"), solely owning important information, begin to buy it, and the price slightly grows. Then the information is shared with a small circle of insiders, individual purchases grow into active buying, and the price of the instrument abruptly takes off. The general public is perplexed and can not understand what is the reason. In the third stage, news comes out and investors fearing not having time to "jump into the last car" buy up this tool that the "elite" and "proxies" are happy to sell to them at the maximum price (with joy, because at that time the "elite" there is already new information that the "elite" has taken into account, a new logistic curve in another instrument begins, or in the same, but with another sign, sales begin). The third stage is completed, when the whole society is aware of what happened, discuss everywhere, in the metro, all who could have already made There is no one to sell.
The only thing that changes is the slope of the logistic curve - the information dissemination rate
As a rule, 90% of bulls in high. And then the market unfolds and vice versa
If you are constantly being told the same thing, then everybody knows it already. It is necessary to look not at the news
If everyone around you screams the same thing, then you are in the upper zone
The task of stepping back from the noise (this time it's useless overpriced NFT pictures)
"WE WILL BE GOLD BEFORE THE PORN, WHILE GOLDEN IDEOLOGISTS WILL EXIST" Rothschild's
"The same situation with cryptocurrencies, but this is only the beginning" Mr.EXCAVO
Best regards EXCAVO
Jumping S-curvesIn this post, I will explain what jumping S-curves means and how you can identify potential S-curves before they jump .
First, let's begin with the chart above (also copied below).
This is a yearly chart of McKesson Corporation (MCK), a medical supplies company.
As you can see in the chart below, this stock has been soaring over the past year despite most other stocks being significantly lower.
Here is the performance of the S&P 500 over the same time period.
Whenever I see something highly unusual in a chart, such as extreme outperformance, I check the higher timeframes to see what's driving price on a technical level. Below is the yearly chart for MCK.
When I examine price action over a long time period, I always log adjust my chart. Below is the log-adjusted chart.
Upon seeing this chart I immediately knew what was going on: the stock price jumped S-curves. I will try to illustrate below how I reached this conclusion.
To begin, I drew Fibonacci levels from the last reaction low to the last reaction high on the yearly timeframe.
The previous reaction low was the bottom of 2008 because that bottom was a Fibonacci retracement of some earlier reaction high, the reaction high is the top in 2015 because price did not surpass that high without first undergoing a Fibonacci retracement (to the golden ratio).
As you can see above, from 2015 to 2018 the price retraced down to the golden ratio (0.618) on the yearly chart. It is often from this retracement level that the base of the second S-curve is created. (For simplicity, I only included the 0.618 Fibonacci level on the chart).
Some may say that this pattern is merely a bull flag or pennant. (See chart below)
Indeed, bull flags and pennants can be another way to visualize S-curve jumps.
Whereas, on a deeper, more mathematical level, S-curve jumps are logarithmic spirals (approximated as Fibonacci spirals or Golden spirals). If you wish to delve deeper into logarithmic spirals, including the Golden spiral, you can check out this Wikipedia page: en.wikipedia.org
These Fibonacci or Golden spirals are present on mostly every chart and they appear on mostly every timeframe (hence they are fractal ).
One of the best charts you can use to visualize these spirals is the chart of Bitcoin. Below are charts of Bitcoin which attempt to show the endless fractal nature of Fibonacci spirals (or "S-curve jumps").
I've only illustrated a few of the spirals, but indeed there are numerous spirals. (I tried to do my best using the tools on Trading View to draw these spirals, but it can be quite hard to manipulate the curves perfectly to price action.)
One may ask what about when price falls? That is obviously not an S-curve jump since the price is falling.
Actually, when price is crashing it is usually just an S-curve jump, or Fibonacci spiral, on the inverted chart.
Although I have not tested it with scientific rigor, I do hypothesize that Bitcoin's price movement is a series of infinitely fractal and competing Fibonacci spirals on various timeframes, including Fibonacci spirals on inverted scales. Price movement can be thought of as an infinite series of S-curve dilemmas where infinitely fractal S-curves, including those of which are inverse S-curves, compete to govern the next price move.
Each dilemma is resolved when an S-curve reaches its inflection point, such that it governs price movement and price moves rapidly in that direction until it approaches capacity and faces its next dilemma.
Those who know Calculus may recognize this chart. Indeed this is the graph of a logistic function. The mathematical terminology for an "S-curve" is sigmoid function .
Here are some more interesting charts of S-curves (none of which is intended to be investment advice)
Meridian Bioscience (VIVO) jumps S-curves on its yearly chart
The U.S. Dollar Index jumps S-curves on its yearly chart
The entire price action of Chinese EV Company (NIO) is an S-curve that just completed a perfect golden ratio retracement
Japan's faces a population S-curve dilemma
Citigroup underwent S-curve growth up until the Great Recession.
Then it crashed or underwent S-curve growth on the inverted chart.
In summary, price movement involves an endless series of S-curves or Fibonacci spirals. Identifying an S-curve on a high time frame before it reaches its inflection point and breaks out can lead to tremendous gains (among the most lucrative gains one can realistically make in the financial markets).
Logistic Uptrend Now ! BUY ON LOWER HIGH SUPPORT Syscorp uptrend nice chart pattern . Nice qr coming soon fly again to break new high , the fourth wave of covid19 pandemic doesn't affect logistic and transportation price.
Logistic curveIf you do not trade, it's time to learn
All about logistic curve
The logistic curve describes the speed of information dissemination among people. This graph describes the distribution of information in an environment.
At first, a instrument is of little interest to anyone, investors are afraid of buying it, and its price fluctuates around r °. At this time, the initiated ("elite"), solely owning important information, begin to buy it, the price slightly grows. Then the information is shared with a small circle of insiders, individual purchases grow into active buying, the price of the instrument abruptly takes off. The general public is perplexed and can not understand what is the reason. At the third stage, news comes out and investors fearing not to have time to "jump into the last car" buy up this tool that the "elite" and "proxies" are happy to sell to them at the maximum price (with joy, because at that time the "elite" there is already new information that the "elite" has taken into account, a new logistic curve in another instrument begins, or in the same, but with another sign, sales begin). The third stage is completed, when the whole society is aware of what happened, discuss everywhere, in the metro, all who could have already made There is no one to sell.
Practice of application: the most important is to determine at what stage the price for the asset is now at which you paid attention and in relation to which you received some information. You can recognize and apply the Elliott waves.
The main thing is not to get into the crowd number at stage 3. If in all financial newspapers, on news sites, on TV there is a discussion of news / ideas - in fact, it is no longer news, this crowd of investors are bred, and this idea should not be used as its defining action (unless with another sign, directly opposite).
Examples in life and the stock market abound. On the classics the same was done with bitcoin last year
People do not change over time. Information and actions of the consonant received information people do the same actions.
The only thing that changes is the slope of the logistic curve - information dissemination rate
As a rule, 90% of bulls in high. And then the market unfolds and vice versa
If you are constantly being told the same thing, then everybody knows it already. It is necessary to look not at the news
If everyone around you screams the same thing, then you are in the upper zone
The task of stepping back from the noise
The main task is to be in the lower green zone. "When there's blood on the streets, buy property"
Logisitc Growth Phase II: Exponential GrowthLogisitic growth describes the acceptance of innovations including new technology. Bitcoin adoption is subject to it (medium.com).
Three Phases
Logistic growth has three consecutive phases:
1) Somewhat chaotic start
2) Exponential growth (early adoption)
3) Logarithmic growth (late adoption)
If we look at the linear chart on the right, we see the characteristic exponential growth curve. It is what is known as a convex function ("it curves down bro"). In comparison, a logarithmic curve is a concave function ('curves up'). Here is a direct comparison, blue is exponential / red is logarithmic www.sosmath.com
Obviously Bitcoin does not look logarithmic at this scale.
Log vs. Linear Charts
It is difficult to see the detail in the linear chart due to the large price difference over the years, so we need to switch to logarithmic to get a clearer picture of microtrends. The logarithm is simply as mathematical function not magic. Log charts are not more or less valid than linear charts, but we need to be aware of the distortions that occur during this transformation.
In trading we use a semilog chart. That means only one axis (price axis) is transformed logarithmically, the other axis (time) remains linear. This has the following effects on exponential and logarithmic curves:
1) Exponentials become linear, i.e. the become straight lines
2) The form of logarithms remains unchanged
Looking at the left chart, we see the underlying exponential form on the right has been transformed into a linear channel. Here is also another example: the same curve shown in log (left) and lin (right) charts
What's the Point?
To me it is clear that the is nothing in BTC history that shows we are undergoing logarithmic growth. The linear charts shows a perfect exponential and the log chart shows a clear linear channel. It represents stable exponential growth. Until the bottom of the channel is broken I do not consider those log charts that show logarithmic curves to be correct - just look at the linear chart!
The formations above the channel are the bubbles that grab the headlines. The stuff at the beginning, under the channel, represents the chaotic start of logistic growth. The bubbles are simply a runaway process that occurs when a certain set of conditions arise upon reaching the top of the exponential channel. If the price is not rejected, the channel top will be broken and a bubble may form. However the underlying exponential trend remains and a return to the mean is a return to this trend. That does not necessarily mean return to the bottom of the channel on the log chart straight away. The mean is actually the median of this channel. But the bottom of the channel is the fundamental support, so should be tested again at some point. This may occur sometime after bottoming.
Next step
Run some python to fit a proper exponential curve and determine the exponent for price long-term forecasts.