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Economic Cycles

Elliott Wave View: SPY Looking to Resume HigherShort Term Elliott Wave View in SPDR S&P 500 ETF (SPY) suggests pullback to 575.04 ended wave ((4)). The ETF has resumed higher in wave ((5)) with internal subdivision as 5 waves impulse. Up from wave ((4)), wave ((i)) ended at 585.99 and dips in wave ((ii)) ended at 578.35. From there, wave (i) ended at 583.81 and wave (ii) ended at 578.90. Wave (iii) higher ended at 595.56 and pullback in wave (iv) ended at 590.35. Final wave (v) ended at 607.7 which completed wave ((iii)). Pullback in wave ((iv)) ended at 604.67 and wave ((v)) higher ended at 610.78. This completed wave 1 in higher degree. The ETF then pullback in wave 2 with internal subdivision as a zigzag Elliott Wave structure. Down from wave 1, wave ((b)) ended at 609.96 as a double three Elliott Wave structure. Up from wave ((a)), wave (w) ended at 605.96 and wave (x) ended at 599.22. Wave (y) higher ended at 609.96 which completed wave ((b)) in higher degree. The ETF turned lower in wave ((c)) towards 589.5 which completed wave 2 in higher degree. It has turned higher in wave 3. Near term, as far as pivot at 575.04 low stays intact, expect pullback to find support in 3, 7, 11 swing for more upside.
AMEX:SPY
by Elliottwave-Forecast
1
Bitcoin Cycle Evolution: Angular Analysis of Peak FormationsAs the cryptocurrency market matures, we observe a fascinating phenomenon in Bitcoin's price dynamics: the gradual reduction in cycle volatility. This analysis presents a geometric approach to understanding and potentially forecasting this pattern through the lens of angular momentum in logarithmic price movements. P.S. TradingView has broken the candlestick ratio, you can still adjust the angle lines correctly using the chart scaling change. Methodology By examining the angular coefficients of price trajectories during Bitcoin's historical 4-year cycles, we can identify a distinct pattern of decreasing slope intensity. These angles, measured from cycle lows to peaks, demonstrate a logarithmic decay pattern that aligns with market maturation theory. Our analysis focuses on end-of-year movements, particularly November-December periods, which have historically served as critical pivot points in Bitcoin's price action. Current Findings The angular progression suggests two key trajectory angles for upcoming cycles: Current cycle (2021-2025): ~34° upward momentum Next cycle (2026-2029): ~29° upward momentum This decreasing angular pattern reflects growing market efficiency and institutional participation, leading to more moderate price appreciations in subsequent cycles. Price Projections Based on this geometric framework, we anticipate three key price levels: 2024 Cycle Peak: $150,000-200,000 Primary resistance: $150,000 Maximum extension potential: $170,000 (scam-wick) Characterized by reduced volatility compared to previous cycles 2024 Cycle Bottom: $44,000-50,000 Represents a higher structural low Optimal accumulation zone for long-term positions Enhanced market stability at support levels 2028 Cycle Peak: ~$300,000 Terminal point: November 2029 Reflects continued market maturation Demonstrates significantly dampened volatility Market Implications This geometric approach aligns with efficient market hypothesis principles, suggesting that as Bitcoin's market structure becomes more sophisticated, price movements naturally become more measured. The decreasing angular coefficients quantify this maturation process, providing a mathematical framework for what many market participants intuitively understand. Risk Assessment While this analysis provides a structured approach to understanding Bitcoin's cycle evolution, it should not be considered financial advice. The model is based on geometric patterns and historical behavior, which may not fully capture future market dynamics. Like the work? Hit the like button to support more analytical content. Note: This analysis employs logarithmic scaling to better visualize percentage-based price movements and cyclical patterns.
BITSTAMP:BTCUSDLong
by Paramonov95
Elliott Wave View: Gold Miners ETF (GDX) Impulse Rally ProgressShort Term Elliott Wave View in Gold Miners ETF (GDX) suggests rally from 12.30.2024 low is in progress as an impulse. Up from 12.30.2024 low, wave 1 ended at 38.2 and dips in wave 2 ended at 36.84. Internal subdivision of wave 2 unfolded as a zigzag Elliott Wave structure. Down from wave 1, wave ((a)) ended at 37.31 and wave ((b)) ended at 37.95. Wave ((c)) lower ended at 36.83 which completed wave 2 in higher degree. The ETF has extended higher in wave 3 with subdivision as a 5 waves with extension (a nesting impulse). Up from wave 2, wave ((i)) ended at 38.16 and pullback in wave ((ii)) ended at 36.84. The ETF extended higher in wave (i) towards 39.73 and pullback in wave (ii) ended at 38.14. Up from there, wave i ended at 39.92 and wave ii ended at 39.24. Wave iii higher ended at 41.53 and pullback in wave iv ended at 40.80. Expect the ETF to end wave v of (iii), then it should pullback in wave (iv) before higher again. Near term, pullback should find support in 3, 7, or 11 swing against 36.83 low for further upside.
AMEX:GDX
by Elliottwave-Forecast
2
Ethereum/Bitcoin (ETH/BTC) Cycle Analysis – Potential Bottom AheAnalyzing the historical cycles of ETH/BTC, we observe a repeating pattern in Fibonacci retracements and price drawdowns: 🔹 Cycle 1: Fibonacci retracement: 83% Price drop: 80% 🔹 Cycle 2: Fibonacci retracement: 94% Price drop: 89% 📉 Projected Cycle 3: If ETH/BTC reacts to the Fibonacci retracement, it could find support in the 0.020 - 0.023 range. However, if the bearish trend continues, based on historical patterns, it may drop further to the 0.010 - 0.015 range. ETH/BTC is currently at a critical level. The key question is whether Fibonacci support will hold this time or if the historical downtrend will continue. ⚠ Disclaimer: This is not financial advice. Always conduct your own research and assess risks before making trading decisions. 📊 What’s your take? Will this pattern repeat, or will we see a different outcome this time? 🚀
by TradeEngineering
Ascending traingles on AMD higher time frame chartLooks like AMD will be bottoming soon (~90's) AMD is following the ascending triangle pattern and the descent it is experiencing right now is very similar to the ABC it had before. Similar projection from the top of ABC and if the similarity continues, it will fall on the green/support trendline and bounce. The stock might hit the trendline when the price is around 90's or it might just wick down to the trendline and bounce too. Anything in the 90's should be a BUY in my opinion. Feel free to share your thoughts.
NASDAQ:AMD
by avprashanth07
BTC updateThe Illusion of Certainty in Markets & The science of Bias In trading, the desire for certainty is one of the most dangerous psychological pitfalls a trader can fall into. While BTC may be displaying bullish behavior, the fact remains that we cannot "know" what will happen next. This fundamental truth often clashes with human nature, as our brains are wired to seek patterns and predictability. However, markets are probabilistic, not deterministic. As price unfolds, the picture becomes clearer , not because the market is revealing some preordained script, but because each new piece of data refines our understanding of probabilities. The most successful traders accept this reality and remain fluid, adjusting their perspectives as new information becomes available. The science of Encoding Poor Information One of the greatest cognitive traps traders fall into is becoming married to their desires or biases. This happens because of the way our brain encodes information: 1. Dopaminergic Reinforcement - When we form an expectation (e.g., "BTC is bullish, so it must go higher"), and the market moves in our favour, our brain releases dopamine , reinforcing the belief that we were "right." - This creates a confirmation loop, we start filtering information to support our bias and dismiss evidence that contradicts it. 2. Cognitive Rigidity & Belief Encoding - The prefrontal cortex , responsible for rational thinking, is often overridden by the limbic system , which governs emotions and survival instincts. - If we've emotionally attached ourselves to an outcome, our brain literally rewires itself to treat contradicting information as a threat rather than a useful input. 3. Sunk Cost Fallacy & Commitment Bias - The more time and energy we invest into a particular belief, the harder it becomes to let go, even when new information suggests we should. - This is why traders hold onto losing trades , refusing to accept new probabilities because it would require admitting they were wrong. How to Stay Probabilistic & Avoid Mental Traps 1. Detach from Outcomes Focus on executing a well-defined process , not on proving your prediction was "right." 2. Constant Re-Evaluation Every new price movement should be treated as new information that either strengthens or weakens existing probabilities. 3. Active Neutrality Never assign a fixed narrative (e.g., "BTC is going to explode higher"). Instead, frame it probabilistically: - "BTC has an X% probability of continuing higher, but a Y% probability of reversal if conditions change." 4. Train Yourself to Embrace Opposing Views If you are bullish, seek out bearish arguments and assess their validity. 5. Use Mental Stop-Losses for Biases Just as we place stop-losses on trades, we must be willing to "cut" faulty narratives when price action disproves them. Final Thought The market is not a certainty machine—it is a probability engine . The sooner a trader embraces uncertainty, the sooner they free themselves from emotional bias. Traders don’t predict, they adapt. It’s not about being right. It’s about staying on the right side of probability.
BITSTAMP:BTCUSD
by SERVER_SEVEN
Probabilistic RealmI remember taking the CMT exam, where one question referenced the Efficient Market Hypothesis (EMH), which asserts that price action is purely random. To avoid losing points, I had to select “random” as the correct answer, despite knowing that market behavior is far more structured than EMH suggests. Despite of passing I still won't ever agree that market is random. Prices are neither random nor deterministic. Market fluctuations follow a chaotic structure, but chaos is not the same as randomness. Chaos operates within underlying patterns and scaling, whereas randomness lacks any order or predictability. Although chaos makes predictions difficult, keep in mind that the universe is not random— effects still follow causes in continuity . No matter how chaotic a system may seem, it always follows a trajectory toward a certain point. For example, in Lorenz’s model of chaos, the trajectory formed a pattern resembling the wings of a butterfly. Understanding these patterns of chaos has practical applications. In the market, even a slight fluctuation can trigger irreversible changes, reinforcing the idea that we cannot rely on absolute forecasts— only probabilities . The market is not necessarily a reflection of the economy; rather, it reflects participants’ feelings about the “economy.” The human emotional component drives the uncertainty and chaos, making it essential to visualize price dynamics exclusively through "systematic" lens. Market Structure Is Self-Referential Markets move in proportion to their own size, not in fixed amounts. Price is arbitrary, but percentage is universal – A $10 move on Bitcoin at $100 is not the same as a $10 move at $100,000. Percentage metrics reflects this natural scaling and allows comparability across assets and timeframes – A 50% swing in 2011 holds similar structural significance to a 50% swing in 2024, despite price differences. Using log scale is a must in unified fractal analysis. Percentage swings quantify the intensity of collective emotions—fear, panic, euphoria—within market cycles. Since markets are driven by crowd psychology, percentage changes act as a unit of measurement for emotional extremes rather than just price fluctuations. After all it's the % that make people worry.. The magnitude of percentage swings encodes emotional energy, shaping the complexity of future market behavior. This means that larger past emotional extremes leave deeper imprints on market structure, influencing the trajectories future trends. The inverse relationship between liquidity and psychology of masses partially explains the market’s fractured movements leading to reversals. In bullish trends, abundant liquidity fosters structured price behavior, allowing trends to develop smoothly. In contrast, during bearish conditions, fear-driven liquidity contraction disrupts market stability, resulting in erratic price swings. This dynamic highlights how shifting sentiment can amplify price distortions, causing reactions that are often disproportionate to fundamental changes. PROBABILISTIC REALM Rather than viewing fluctuations as a sequence of independent events, price action unfolds as a probabilistic wave shaped by market emotions. Each oscillation (outcome) is relative to historical complexity, revealing the deep interconnectedness of the entire chart that embodies the “2-Polar Gravity of Prices.” Fibonacci numbers found in the Mandelbrot set emphasizes a concept of order in chaos. The golden ratio (Phi) acts as a universal constant, imposing order on what appears to be a chaotic. This maintains fractal coherence across all scales, proving that price movements do not follow arbitrary patterns but instead move relative to historic rhythm. The reason why I occasionally have been referring to concepts from Quantum Mechanics because it best illustrates the wave of probability and probabilistic realm of chaos in general. Particularly the Schrodinger's wave equation that shows probability distributions. Key intersections in Fibonacci-based structures function as "quantum" nodes, areas of market confluence where probability densities increase. These intersections act as attractors or (and) repellers, influencing price movement based on liquidity and market sentiment. Similar to Probability Distribution in QM. Intersections of Fibonacci channels reveal the superposition of real psychological levels, where collective market perception aligns with structural price dynamics. These points act as probabilistic zones where traders’ decisions converge, influencing reversals, breakouts, or trend continuations. Don’t expect an immediate reversal at a Fibonacci level—expect probability of reversal to increase with each crossing. To prove that Efficient Market Hypothesis is wrong about prices being random, I'd go back to a very distant past from current times. For example, price fell 93% from 2011 ATH, reversed and established 2013 ATH. Using a tool "Fibonacci Channels" to interconnect those 3 coordinates reveals that markets move within its fractal-based timing derived from direction. If prices were random, this would have never happened. The bottomline is that viewing current price relative to history is crucial because markets operate within a structured, evolving framework where proportions of past movements shape future probabilities. Price action is not isolated—it emerges from a continuous interaction between historical trends as phases of cycles, and liquidity shifts. By analyzing price within its full historical context , we can differentiate between temporary fluctuations and meaningful structural shifts justified by the fractal hierarchy. This approach helps identify whether price is expanding, contracting, or aligning with larger fractal cycles. Without referencing historical complexity, there is a risk misinterpreting patterns from regular TA, overreacting to short-term noise, and overlooking the deeper probabilistic structure that governs price behavior.
BITSTAMP:BTCUSDEducation
by fract
20