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Cycles

XRP start moving to 3.20 $ I see XRP is doing well this week, big banks, big platforms are trusting in XRP, some huge volumes start moving, As we can see, we are above the 0.85 - 0.95 support area, good opportunity for moving up with some accumulation from market makers. In general, we are targeting 3.20 $ by the 1st quarter of 2022 as we see the SEC manipulating the market just to make XRP holders give up and sell their XRP to buy ETH. you can see in the chart blue vertical lines; nearly these dates I expect significant volatility based on Gann square of 9. - - Don't sell your XRP this coin have a good future for the long term. Remember always take some profits to increase your opportunity for buying when the price goes down, I personally believe that XRP is a trusted coin.
BYBIT:XRPUSD.PLong
by youssefallax
Is the SNP500 ready for another correction?I firmly believe that we should soon see a correction deeper than the one we recently had which began at the start of September. The chart suggests that after finally breaking out of the bear wedge; which began at the start of the lows of the correction in March 2020, we are now witnessing what looks like to be a retest of that bear wedge. With the addition of negative weekly RSI divergence this should see some firm movement downwards, below the low recorded in the first week of October. Hard to see the market giving way to such a huge drop, but the market carrier Tesla is due a correction after extreme growth in the recent weeks.
TVC:SPXShort
by SkyTrees
S&P 500 Numerology - Hypothesis of Major Cycle TopThe concept of numerology is most often not taken seriously for obvious reasons. Most principally, it is because it doesn't make logical sense to the human brain. The human brain (of those rooted in western culture, at least) is more attuned to Newtonian logic, structured systems, or the stamp of approval from some poorly run university journal than it is accepting certain "coincidental" truths. The entire subject of "microeconomics" is a testament to this need to reduce human behavior into four or five hard, mathematical equations. I have personally taken a microeconomics class and I can safely say that none of the concepts can be practically applied to real life commerce. Please refrain from commenting if you disagree; you can instead have more fun trying to calculate individual elasticities for trade idea subscriptions. Wow, got pretty sidetracked there. My point is that keeping an open mind to certain market-related concepts can really broaden your understanding of how price action actually works. If that isn't incentive enough, then it can also substantially improve your timing accuracy and a general sense of market direction. If this still isn't incentive enough, then you might be inelastic to certain trade idea subscriptions. I wouldn't know though, since I dropped the class after lecture number 1. In theme with open-mindedness, check out the numerological proof above. The basis for this idea derives from W.D. Gann's concept of squaring price with time, which can be interpreted in any number of ways and applied as such. Basically, his idea stems from his observation that market trends change direction during those instances where some amount of price is equal to some passage of time. Put another way, the market cannot reverse its trend unless the underlying reaches a certain diagonal distance away from its origin, such that the y-axis distance equals the x-axis distance. Put another way, if the diagonal distance from a given origin point is equally distant horizontally and vertically from either respective axis, then that diagonal distance can be drawn at a 45-degree angle, such that a perfect square can be traced around it. If this still seems confusing, that's because it is. The concept of time and price squared is often misinterpreted, and even more often, applied incorrectly. Ever try using a "square of nine" and wondering what the hell you were doing for that many hours? Classic case of not really understanding the concept of price/time squared. The truth is that Gann's work is extremely intensive and valid educational resources are both difficult to come by and usually quite expensive. If you ever come across something Gann-related that isn't either of those things, then it's likely incomplete and will surely leave you more confused than you were beforehand. To alleviate your confusion about the point of my numerological proof up there, all I did was take the square root of a number of calendar days between March 6th, 2009 and September 2nd, 2021 and compared that quotient with the square root of the number of dollars/share in between the low price reached on the former date and the high price reached on the latter date. If the high of 4545 reached last September really is the top of some major trend, then it must necessarily tie out with a corresponding bottom made at some point X in the past. The two square-root quotients of price difference and time difference between two separate dates must relate in some sort of numerological way for these dates to define the starting point and the ending point of an apparent trend. The more obvious and literal the connection, the more sure you can be that you've nailed the defining start and end dates to a major S&P trend. If you don't believe me, then try it out on another set of dates. Eventually, you will see what I mean (hint: try starting your search on a major round number like the first date that hits 1000 price points). Now, if you've read up until this point, I commend you. Your reward in doing so is knowing that the proof succeeded, which means that the September high will not be exceeded in the near future; certainly not in 2021. You should also know that this is stated in the chart above. -CoinciPig SP:SPX TVC:DJI TVC:IXIC
SP:SPX
by UnknownUnicorn5511258
19
Small correction for BTC/USDT | Big Pump AfterwardsGreetings, In the chart you will see the slogan "history repeats itself" depicted on the price of BTC/USDT. Bulls are taking profits since the second pump of the price of the mother of cryptocurrencies. This is taking the price downwards but that doesn't need to scare us. The second wave is incoming as the bulls are accumulating while the bears are selling. This process is taking the price downwards to the green area marked as "Buy zone after correction". Once we reach the green by zone, the price will see a pump of around 50%-60%. After the third pump we will see All time highs for BTC. This is not a financial advise as it's my view for the price of BTC. Never trade without making your own analysis and be smart when it comes to money.
Long
by Engindzhan
BAYN: Long (end of cycle + support)Hello everyone!!! Bayer AG at the channel support. There is hope for the end of the bearish trend that began in 2015. Additionally, according to the cyclical analysis, we can see the completion of a cycle of 1610 days (or 230 weeks, or 4.5 years). The cycle was repeated 7 times: of which 5 times there was an increase in the share price and 2 times - a fall. Therefore, this time too, we can expect the price to rise at least to the slope and horizontal resistance lines - about € 79 or 70% = take profit. My stop loss is set at € 42.610 (about -12% and 3% below the last local low). As for the indicators, the background is bullish. However, there was a huge bullish gap in 1996 and it has not been closed until now .... I plan to increase my position using the pyramiding method. Not a recommendation, not advice. I wish everyone a lot of profit !! PS Bayer AG - is a German multinational pharmaceutical and life sciences company and one of the largest pharmaceutical companies in the world. Headquartered in Leverkusen, Bayer's areas of business include human and veterinary pharmaceuticals; consumer healthcare products; agricultural chemicals, seeds and biotechnology products. The company is a component of the Euro Stoxx 50 stock market index. Werner Baumann has been CEO since 2016. Founded in Barmen in 1863 as a dyestuffs factory, Bayer's first and best-known product was aspirin. en.wikipedia.org
XETR:BAYNLong
by Dr_Chester
1
PALL resurgence medium termLooks like PALL is repeating a previous pattern. Very cyclic and resolves well with Williams Vix Fix. I see a local bottom that was supported with strong resistance from Aug 2021 to current. If growth is continued as anticipated, this commodity will rebound. If safe havens are sought, this commodity will also grow. Solid indicator data fitting PALL for a 20%+ gain in the next 2-3 months. Short term - I think the buy is in the 170-175 range within the next week or two. For ease of interp - lime green indicates local bottom. Just my thoughts.
AMEX:PALLLong
by Elkinthewoods1
⚡️ Crypto Insights ⚡️ #2 - Altcoin CyclesIn this visual we can see an orange graph overlaid onto the BTC price chart for the last peak back in April. This orange graph represents the collective market cap for all crypto excluding BTC. We can see that the price of altcoins lag behind the price of BTC and actually top around around 3 weeks after the peak. If you go back and look at the ATH at the end of 2017 you will see a very similar pattern. Altcoins tend to lag a few weeks behind BTC and, therefore, peak after BTC highs also. If you are an investor, this is a key sign to watch out for and if you have made significant gains will give you a strategic exit.
COINBASE:BTCUSDEducation
by Flow_Capital
AMC End of October: Is $36 the bottom or back to $32?3 weeks have pass since October. I was wrong about the bullish hammer. I expect to go up today but it went down. One pattern I hesitate and over look was the head and shoulder pattern. The price action today confirms the head and shoulder patterns. Interestingly back in September the same thing has occur. And now what to expect October. Will the algorithm repeats? If so, I expect AMC to dip even further to $32 based on the fib retrace of $28.92 and $44.44. If not I expect $36 is the bottom and we are not looking back. The falling wedge will be determine by next week price action.
NYSE:AMC
by gojira91
5
Fourier: Interpreting and Over-interpreting Frequency AnalysisGreetings to all! In this post, I'd like to share some thoughts on frequency analysis based on Fourier transform. This mathematical method breaks down data into cyclical constituents (frequency components). Then the importance of each frequency component in the original data is expressed as the square of its amplitude, that is, power . Some time ago I published a Pine Script implementation of the Fast Fourier Transform (FFT) algorithm. I made it specially designed to be used for filtering data based on its frequency content. The concept of FFT filtering is well known and quite simple (for detail, see the link to my script below). When it comes to frequency analysis , that's a whole different story. Using the power versus FFT frequency plot (i.e., the spectrum ) to study the data is an extremely popular analytical technique in science and technology. But with financial data, it is tougher than it sounds. When dealing with noisy, non-stationary and overall uncertain price data, the FFT never works as well as it does in math textbooks. Here, to illustrate the capabilities, limitations, and some myths of frequency analysis, I generated artificial price data, applied an FFT to each price column, and plotted a power spectrum as a function of time (i.e. a spectrogram ). The spectrogram shows frequency information along the vertical axis. The lowest frequency content is displayed at the bottom, the highest frequency content is displayed at the top. Frequencies are given as the number of cycles per sample size (256 bars in the above chart). Power levels are defined by the color map shown to the right. As for the generated data, it is basically a random walk with a few non-random constituents added at given time intervals (sinusoidal functions and a gap). Now let's discuss a few aspects seen in the chart: 1. True periodicity Starting on a high note, if there is real oscillatory behavior in the data (see the green and red areas in the above chart), the FFT can reveal this quite well. The problem is that the frequency resolution is heavily influenced by the sample size. For example, with a sample size of 64 price bars, it is impossible to resolve cycles longer than, you guessed it, 64 bars. It should also be noted that the ideal deterministic sinusoidal functions shown in the above chart can never be found in real market data. 2. Discontinuities If there is a gap, it's bad. Gaps, that is, discontinuities in the data, are prominent features that have broad and smooth frequency spectra that can overshadow other features. If you google "Fourier transform of a step function", you can see what I mean. Thus, if a gap occurs somewhere within the sample window, the Fourier spectrum is unlikely to be reliable. 3. Random walk This is not surprising, but even purely random data can produce rich frequency content. It is even difficult to tell from the spectrogram where the purely-random area changes into the one containg a sinusoid. (Well, if we accept the random walk theory of markets, the last comment does not make much sense. But here we are talking about syncretic data). The situation, however, becomes much more fun if we analyze the change in data per bar (i.e., data - data ), rather than the actual data. In the case of a random walk, these changes are purely ... well, random. And it is known from textbooks that the Fourier spectrum of random noise contains only noise. However, in areas containing sine, there is an order in the data. In other words, the data is autocorrelated. As a result, the FFT spectra of the data reveal the corresponding frequency components way above the noise level. In this sense, Fourier analysis may seem as a potential tool to to test market efficiency. (There is even a Fourier-based version of the Dickey-Fuller test for stationarity of time series, but that is a different story.) However, I am not aware if it can somehow outperform the more commonly used tests. Conclusion In the context of financial time series, the Fourier transform is often associated with the estimation of marked cycles. I think that's why it has become one of the most polarizing technical tools out there. While it is certainly a powerful math tool, it is helpful to know its limitations. Can one capitalize on the revealed qualitative information about the "cycle" periods? Regardless of how to think about the concept of market cycles, I don't think so. But could the Fourier transform be potentially useful in general for analyzing price data? Definitely yes! See below for how to use FFT to filter data:
AMEX:SPYEducation
by tbiktag
27
BTCUSD "Economic Bubble"?Thought it fitting to sketch Dr. Jean-Paul Rodrigue "Economic Bubble"model over BTCUSD Weekly TF. Imagine how fast this would move once "FEAR" was to properly set in. Thoughts on price action over the next month? "DISCLAIMER: NO ADVICE. The information presented here is general in nature and is for education purposes only. Nothing should be considered to be advice. You should consult with an appropriate professional for specific advice tailored to your situation."
COINBASE:BTCUSDShort
by Trader_Johnni
9
KWEB LONG: DOUBLE DIAMOND + CHANNEL BOTTOM + OSCILLATORS1. Price has drawn 2 diamonds (diamond in diamond) at the bottom of the increasing (purple) channel. Buy signal. 2. A cycle with a length of 756 days (25 months) is found, according to which the price is now at the bottom of the cycle. Buy signal. 3. All major oscillators and indicators are in oversold zones and give long signals. 4. It is necessary to remember about the resistance of the local downtrend (orange). * At the same time, the fundamental background in China is still negative. I entered a long position with a trailing stop loss below the lower edge of the small diamond. After breaking through and/or retesting the upper edge of a large diamond, and then after breaking through the orange resistance, I will buy more. In case the price falls, my trailing sell order will save me. Not advice. Not a financial recommendation.
AMEX:KWEBLong
by Dr_Chester
5