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Sell in May, if you're g....ame to miss out. Bitcoin needs to reach a 60 day cycle high above $90k AND close the next 60 day cycle above ~84k to stand a chance at keeping hopes for a right-translated cycle alive. Failure to do this will make the previous top of $109k look much stronger as the left-translated cycle top and crush many dreams. Even if momentum for a right-translated top stays alive through these targets in the 60 day cycle, most people are delusional calling for highs of $169k - $250k, these expectations are baked in and will likely not be reached--too much complacency on these price targets. If we do see a right-translated cycle top towards November of this year, it's likely the top will be just barely higher than previous ATH and crush many expectations. Many will fail to take profits and will get stuck bag-holding for 4 years.
COINBASE:BTCUSD
by herblock
Why the Bitcoin Pi Cycle Indicator will not trigger this cycleIn this post, we’ll take a closer look at the Pi Cycle Indicator and explain why we believe it is unlikely to trigger in this cycle. Instead, we present an alternative signal that may better indicate the true Bitcoin top. Understanding the Pi Cycle Indicator The Pi Cycle Indicator has historically been highly accurate in predicting Bitcoin cycle tops. It consists of two simple moving averages: The 111-day simple moving average (SMA) (blue) The 350-day simple moving average (SMA) multiplied by two (green) A signal is generated when the 111-day SMA crosses above the multiplied 350-day SMA, which is marked by a red vertical line. Why This Signal Alone Isn’t Enough While this signal has been useful in the past, we believe it doesn't provide the full picture—specifically, it doesn’t indicate how strong the crossover is. By transforming this indicator into an oscillator that measures the ratio between these two moving averages, we gain a more nuanced perspective: In the chart, the green line represents the ratio between the two moving averages. When it crosses above the red horizontal line (ratio > 1), a Pi Cycle signal occurs (marked by a red vertical line). Notably, the 2017 signal was significantly stronger than the 2021 signal, suggesting a pattern of diminishing returns. We highly recommend checking out our post on diminishing returns and the overall timeline for the current cycle here . Additionally, we've developed our own Bitcoin model that factors in the effects of diminishing returns. Check it out here . The TRUE cycle top signal The key question is whether this diminishing return is strong enough to prevent a signal from forming in this cycle. Based on our analysis, we believe it is. By extrapolating this trend into the future using a white diagonal trend line, it becomes clear that the ratio will likely remain below 1, meaning no crossover is expected this cycle. Instead, we anticipate that the next Bitcoin top will occur at a ratio of approximately 0.9 , as indicated by the orange area on the chart. In summary, while the Pi Cycle Indicator has been a reliable tool in previous cycles, its diminishing strength suggests that it may not trigger this time. Rather than relying solely on this metric, we suggest considering looking deeper into the true value of this indicator instead.
COINBASE:BTCUSD
by Cryptonerds
Are we building a possible Super-Cycle & leave the 4-year cycleChart shows comparison to the last two cycles which have been scaled to match this cycle. With all the differences this cycle has offered, the early run before the halving, the long drawn out mini bear market retracements, but yet all the bullish news for Bitcoin and Crypto from here on out in the U.S.A, might we not experience a traditional bear market and instead play out a Super Cycle instead? It seems to me like this is, or could be playing out like the beginning of a Super Cycle. A move that takes Bitcoin into the millions. Just the same large parabolic run, similar when you zoom out and view the traditional Dow/S&P Stock Market as a whole since the 1980s. I suppose the absence of a deep and long bear market could be another clue that indicates this theory, until then it's just a theory and time will tell all....
by SammyCasket
Chart looks identical to May 2021...may be in for some hurtJust a simple low IQ comparison. Looking at the weekly circa May 2021 looks identical to what we're seeing today. Drew the same pattern in red and a bull case in case we still see a new high with the 4 year cycle, but it's looking bleak. We're getting close to completing another weekly cycle and should expect the new low within the next 2 candles. Question is, are we about to retrace 55% like May 2021, or continue the bull run into a new high later this year?
COINBASE:BTCUSD
by herblock
Long Idea on CC1! (Cocoa)1)Climate change is having a significant impact on cocoa production in West and Central Africa, according to a study by Wageningen University & Research (WUR). The region accounts for more than 70% of global cocoa production. Changes in temperature and rainfall are making some areas less suitable for cocoa cultivation. 2) Seasonality gives us a bullish pattern which is 98% correlated with the actual price 3)quantitative data shows 80% win rate with a good profit factor 4) The price rejected the 50 EMA forming a Pin Bar Candlestick pattern 5) The price also bounced on a demand zone 6) Price is undervalued against several benchmarks
ICEUS:CC1!Long
by kingosamafxx
Business CycleAll the credits to Ostium labs insights. Found here Intuition behind different indicators NFCI - NATIONAL FINANCIAL CONDITIONS INDEX Note y axis is inverted. Rising NFCI here suggests loosening of financial conditions. Btc outperform in loose conditions. DRTSCILM - NET % OF BANKS TIGHTENING LENDING STANDARDS Note y axis is inverted. This tracks changes in the willingness of banks to lend, where tightening lending standards is indicative of caution, whereas looser lending standards suggest economic confidence. Here the graph is inverted - a rise shows improving willingness to lend and a fall shows tighter lending standards. HYG Real time proxy for demand of junk bonds which is a good proxy for risk appetite in the market. Demand for junk bonds is correlated with the rest of the risk curve, with Bitcoin tending to outperform during periods of strength for HYG, and vice-versa. BAMLH0A0HYM2 - HY ICE CREDIT SPREADS Note y axis is inverted. This measures the premium demanded by investors over government bonds. As one would imagine, wider credit spreads mean that more yield is being demanded to invest in junk bonds vs safe bonds, which itself is suggestive of risk in the economy. Narrow spreads, meanwhile, are indicative of confidence. The graph is inverted such that the peaks are the tightest spread. If credit spreads are narrow, risk appetite is high, which means assets further out the risk curve benefit. This is also suggestive of expansion vs contraction in the business cycle, where widening spreads would be suggestive of downturn and narrowing spreads of continued growth. USMNO/USNMNO - US MANUFACTURING ORDERS / NON-MANUFACTURING ORDERS Manufacturing New Orders growing faster than Non-Manufacturing New Orders is generally indicative of early recovery in a business cycle, whereas late cycle dynamics are more heavily weighted towards services, largely driven by consumer spending and therefore this ratio would begin to contract, as Non-Manufacturing New Orders dominate. USBC0I - US PMI A composite of the Manufacturing and Services sectors in the US economy. Above 50 = expansion and below 50 = contraction. T10YIE - 10-YEAR INFLATION BREAKEVENS A market-based measure of average expected inflation over the next 10 years. Bitcoin likes it very much when the average expected inflation rate has bottomed and is trending higher and it generally underperforms when 10-year inflation breakevens are declining. Bitcoin also tends to front-run peaks in 10-year inflation breakevens by about 6-9 months, which in turn tend to peak after Global M2 YoY growth has peaked and is turning lower. This measure also is useful for understanding what is likely to happen to financial conditions - tighter after peaks and looser after bottoms. The clearest correlation here is not to the downside but the upside: when breakevens have bottomed out and cycle higher, Bitcoin tends to do very well indeed. DFII10 - 10-YEAR REAL YIELD Note y axis is inverted What is interesting here is that whilst there is not a strong correlation as real yields rise, there is a clearer correlation as real yields fall. Falling real yields tend to be supportive of Bitcoin, whilst rising real yields have occurred whilst BTC has outperformed and underperformed historically. This one is not as key for mapping out the market cycle, but still worth keeping an eye on.
BITSTAMP:BTCUSDEducation
by Oxfirefist
Beans looking to drop hard, after all... Beans have been looking weak lately, and all this current and near future trade war fundamentals and uncertainty aren't going to help at all. Volatility is likely to go up this week across a lot of markets, and the ag commodities will certainly be part of that, with emotional fears from the last market crashing during the last Trump term. Beans especially didn't fair well during that time, and the corn-to-bean ratio was out of wack to where us farmers didn't want to plant beans period. We all thought (and were told) they might go to $7 or less! All while corn was poor, but much more palatable with the breakevens. Farmers, as a rule, certainly prefer to plant corn over beans anyway, if they live where they can choose as such. But back to the bean chart, I've been thinking there was a decent enough chance we could chop around in here and bounce off of any short term weakness and key support, to make new highs for the move. A lot of guys were looking to target the high 10s and even around $11, before expecting a notable correction. Well, unfortunately, I think we've already recently peaked and are more likely to now keep correcting down, potentially quite violently. On Friday, the 20 day EMA gave us bounce off support, but if we get a confirmation close Monday below that (likely), my opinion is we confirm we're in a larger scale wave 3 down already, and should eventually target the 9.47 and likely even lower ultimately, before we bottom in February or March, before spring seasonality and US planting weather premium allows for us to rise again. Longterm, for this summer and beyond into 2026, I am quite bullish grains and ultimately, expect to see new all time highs, but it's not gonna be this year. Mostly due to the likelihood of a major cycle drought of our lifetime, which could happen this year but not truly affect the supply issue drastically until new crop turns into "old crop".
CBOT:ZS1!Short
by farmerisland
1
Fractal Phenomenon Proves Simulation Hypothesis?The humanity is accelerating towards the times when virtual worlds will get so realistic that their inhabitants gain consciousness without realizing they exist in a simulation. The idea that we might be living in a simulation was widely introduced in 2003 by philosopher Nick Bostrom. He argued that if the civilization can create realistic simulations, the probability that we are living in one is extremely high. Modern games only render areas that the player is observing, much like how reality might function in a simulation. Similarly, texture of game environments update as soon as they are viewed, reinforcing the idea that observation determines what is rendered. QUANTUM MECHANICS: The Ultimate Clue Quantum Mechanics challenges our fundamental understanding of reality, revealing a universe that behaves more like a computational process than a physical construct. The wave function (Ψ) describes a probability distribution, defining where a particle might be found. However, upon measurement, the particle’s position collapses into a definite state, raising a paradox: why does the smooth evolution of the wave function lead to discrete outcomes? This behavior mirrors how digital simulations optimize resources by rendering only what is observed, suggesting that reality itself may function as an information-processing system. The Born Rule reinforces this perspective by asserting that the probability of finding a particle at a given location is determined by the square of the wave function’s amplitude (|Ψ|²). This principle introduced probability into the very foundations of physics, replacing classical determinism with a probabilistic framework. Einstein famously resisted this notion, declaring, “God does not play dice,” yet Quantum Mechanics has since revealed that randomness and structure are not opposing forces but intertwined aspects of reality. If probability governs the fabric of our universe, it aligns with how simulations generate dynamic outcomes based on algorithmic rules rather than fixed physical laws. One of the most striking paradoxes supporting the Simulation Hypothesis is Schrödinger’s Cat, which illustrates the conflict between quantum superposition and observation. In a sealed box, a cat is both alive and dead until an observer opens the box, collapsing the wave function into a single state. This suggests that reality does not exist in a definite form until it is observed—just as digital environments in a simulation are rendered only when needed. Similarly, superposition demonstrates that a particle exists in multiple states until measured, while entanglement reveals that two particles can be instantaneously correlated across vast distances, defying classical locality. These phenomena hint at an underlying informational structure, much like a networked computational system where data is processed and linked instantaneously. Hugh Everett’s Many-Worlds Interpretation (MWI) takes this concept further by suggesting that reality does not collapse into a single outcome but instead branches into parallel universes, where each possible event occurs. Rather than a singular, objective reality, MWI posits that we exist within a constantly expanding system of computational possibilities—much like a simulation running countless parallel computations. Sean Carroll supports this view, arguing that the wave function itself is the fundamental reality, and measurements merely reveal different branches of an underlying universal structure. If our reality behaves like a quantum computational system—where probability governs outcomes, observation dictates existence, and parallel computations generate multiple possibilities—then the Simulation Hypothesis becomes a compelling explanation. The universe’s adherence to mathematical laws, discrete quantum states, and non-local interactions mirrors the behavior of an advanced simulation, where data is processed and rendered in real-time based on observational inputs. In this view, consciousness itself may act as the observer that dictates what is “rendered,” reinforcing the idea that we exist not in an independent, physical universe, but within a sophisticated computational framework indistinguishable from reality. Fractals - Another Blueprint of the MATRIX? Price movements wired by multi-cycles shaping market complexity. Long-term cycles define the broader trend, while short-term fluctuations create oscillations within that structure. Bitcoin’s movement influencing Altcoins exemplifies market entanglement—assets affecting each other, much like quantum particles. A single event in a correlated market can ripple across the entire system like in Butterfly effect. Just as a quantum particle exists in multiple states until observed, price action is a probability field—potential breakouts and breakdowns coexist until liquidity shifts. Before a definite major move, the market, like Schrödinger’s cat, remains both bullish and bearish until revealed by Fractal Hierarchy. (Model using Weierstrass Function ) A full fractal cycle consists of multiple oscillations that repeat in a structured yet complex manner. These cycles reflect the inherent scale-invariance of market movements—where the same structural patterns appear.. By visualizing the full fractal cycle: • We observe the relationship between micro-movements and macro-structures. • We track the transformation of price behavior as the fractal unfolds across time. • We avoid misleading interpretations that come from looking at an incomplete cycle, which may appear random or noisy From Wave of Probability to Reality 1. Fractal Probability Waves – The market does not move in a straight line but rather follows a probabilistic fractal wave, where past structures influence future movements. 2. Emerging Reality – As the price action unfolds, these probability waves materialize, turning potential fractal paths into actual price trends. 3. Scaling Effect – The same cyclical behavior repeats at different scales (6H vs. 1W in this case), reinforcing the concept that price movements are self-similar and probabilistically driven. If psychology of masses that shapes price dynamics is governed by mathematical sequences found in nature, it strongly supports the Simulation Hypothesis Do you think we live in a simulation? Let’s discuss in comments!
INDEX:BTCUSDEducation
by fract
21
AAVE - DeFi leader As I have stated in my previous analysis AAVE is one of the leaders in DeFi sector, and stays quite underpriced still. Just as I predicted, it reached my target and now I think it will go for .618 Fib. After that in theory there also will be a correction. But if you look at Solana chart, it has gained a lot of attraction in this cycle and has made a new ATH. I think AAVE will be one of the few Altcoins which have the required potential to make new ATH also. Let's hope and monitor
Long
by AlexLukyanin
BTC - Time cycles unlock some key insights BTC is very clearly able to be carved out into time cycles, or 'Hurst' cycles, which are regular appearing patterns of units of time which can help us in informing price action. Looking at BTC, it's clearly cutting into cycles of about 40 days with the price action within each cycle very clearly going in either direction - apart from one! Looking at the most recent cycle we just entered into, the price action is likely to rise and continue to rise until either the middle of the cycle (target) or the end of the cycle (vertical line). So please add Hurst cycles to your cocktail of methods for understanding 'when' an event is likely to take place, or at least give you a marginally higher percentage probability. Good luck. Follow and share for more.
Long
by cryptechcapital
1