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Trend Analysis

Key Insights into Bitcoin’s Halving Cycles1. Halving Cycle Structure This chart leverages Bitcoin's logarithmic scale to illustrate its price behavior across halving cycles, providing a clearer perspective on exponential growth and diminishing returns. Key Takeaways from Bitcoin's Halving Cycles 1. Halving Cycle Structure Cycle Length: Each cycle spans 1432 days (approximately 4 years), divided into: Bull Market Phase (1064 days): Gradual accumulation followed by accelerated growth. Bear Market Phase (365 days): Sharp corrections and consolidation before recovery. Historically, bull markets account for the majority of price growth, with bear markets serving as cooling-off periods. 2. Historical Price Performance Cycle 1 (2012 Halving): Entire Cycle move: 11644% Pre-Halving having: +390% Post halving +2947% 96.65% of the entire move was after the Halving. Cycle 2 (2016 Halving): Entire Cycle move: 2503% Pre Halving: +213% Post halving +703% 91.5% of the entire move was after the Halving Cycle 3 (2020 Halving): Still going... Hypothesis: 86% of the entire move was after the Halving. Entire Cycle move: 1671.43%% based on my maths Pre Halving: +234% so far Post halving +92% so far If the hypothesis is true then 905k is the projected price. 3. Upcoming 2024 Halving Predictions Bull Market (2024–2027): Projected move: 905K USD peak if historical patterns persist and the Hypothesis holds. Bear Market (2027–2028): Based on prior cycles, corrections could range from -70% to -80%, leading to a consolidation Resistance Zones: $250K, $500K, and $905K projected peaks based on logarithmic trends. Trade safe Tarder Leo
INDEX:BTCUSDEducation
by BTM-LEO
2
YOUR GUIDE TO CANDLESTICK ANALYSIS! What's up guys it's been a while! I know it's the holiday seasons, and that's the best time of year for me. Here is a wonderful present for you all, as a token of my appreciation. Thankful for the supportive and hateful people, not equally of course! 🤣 Anyways.... the things you must keep in mind when utilizing candlestick analysis in your trading are the following, Gs: 1) Understanding the anatomy of a candlestick - images.ctfassets.net 2) Candlestick color - The color of the candles individually matter in structure but also together they tell a story.... three inside down candle stick pattern at a lower high point in market structure for example. 3) Size of the candle - size of candle does matter as it indicates how volatile and wide reaching the market can be that day based on this data. 4) Volume - This one is obvious, Gs. 5) Timeframe of candlesticks being observed - understand candlesticks on higher timeframe hold more weight so they're more valid. (1h+) in consolidated structure on higher timeframe, lower timeframe candlestick structure is what you need to identify breakouts that'll be big on HTF. 6) Candlestick patterns - content.stockstotrade.com 7) Length of wicks on the candles - This is huge because wicks are a direct indication of exhaustion, which BASICALLY is buyer or seller weakness which directly aids me in basically every trade when finding that sniper entry i'm known for! Do not sleep on this step (or any, for that matter, I don't make these for FUN.) 8) Support/Resistance levels - I recommend going to lower time frames in these areas and using steps 2, 3, 6 mixed with timeframe correlation to make a sniper entry. GOODLUCK Gs!
Education
by PipSniperJ
6
Again... $NQ hits 4x Asian Session Standard Deviation *smc*I made a tutorial not long ago that this setup happens mroe often than not. So I'm posting a second setup to prove my case. What's the difference? The entrance will depend on previous buy/sell models and if price hits the right order block without needing to go after sell side liquidity the higher the entry (or sell side, the lower the entry)... in this case is the higher. Because below is a lot of price action and the bottom hits just below the asian session at a breaker. Exit will head toward liquidity. On the 4 hr chart the liquidity point is 21,190. 4HR HART I hope these tutorials will help you continue to keep finding these setups. Happy Trading CME_MINI:NQ1! BLACKBULL:NAS100 CAPITALCOM:US100
CME_MINI:NQ1!Education
by BodiesXWix
Rolling Correlations and Applications for Traders and Investors1. Introduction Markets are dynamic, and the relationships between assets are constantly shifting. Static correlation values, calculated over fixed periods, may fail to capture these changes, leading traders to miss critical insights. Rolling correlations, on the other hand, provide a continuous view of how correlations evolve over time, making them a powerful tool for dynamic market analysis. This article explores the concept of rolling correlations, illustrates key trends with examples like ZN (10-Year Treasuries), GC (Gold Futures), and 6J (Japanese Yen Futures), and discusses their practical applications for portfolio diversification, risk management, and timing market entries and exits. 2. Understanding Rolling Correlations o What Are Rolling Correlations? Rolling correlations measure the relationship between two assets over a moving window of time. By recalculating correlations at each step, traders can observe how asset relationships strengthen, weaken, or even reverse. For example, the rolling correlation between ZN and GC reveals periods of alignment (strong correlation) during economic uncertainty and divergence when driven by differing macro forces. o Why Rolling Correlations Matter: Capture dynamic changes in market relationships. Detect regime shifts, such as transitions from risk-on to risk-off sentiment. Provide context for recent price movements and their alignment with historical trends. o Impact of Window Length: The length of the rolling window (e.g., 63 days for daily, 26 weeks for weekly) impacts the sensitivity of correlations: Shorter Windows: Capture rapid changes but may introduce noise. Longer Windows: Smooth out fluctuations, focusing on sustained trends. 3. Case Study: ZN (Treasuries) vs GC (Gold Futures) Examining the rolling correlation between ZN and GC reveals valuable insights into their behavior as safe-haven assets: o Daily Rolling Correlation: High variability reflects the influence of short-term market drivers like inflation data or central bank announcements. Peaks in correlation align with periods of heightened risk aversion, such as in early 2020 during the onset of the COVID-19 pandemic. o Weekly Rolling Correlation: Provides a clearer view of their shared response to macroeconomic conditions. For example, the correlation strengthens during sustained inflationary periods when both assets are sought as hedges. o Monthly Rolling Correlation: Reflects structural trends, such as prolonged periods of monetary easing or tightening. Divergences, such as during mid-2023, may indicate unique demand drivers for each asset. These observations highlight how rolling correlations help traders understand the evolving relationship between key assets and their implications for broader market trends. 4. Applications of Rolling Correlations Rolling correlations are more than just an analytical tool; they offer practical applications for traders and investors: 1. Portfolio Diversification: By monitoring rolling correlations, traders can identify periods when traditionally uncorrelated assets start aligning, reducing diversification benefits. 2. Risk Management: Rolling correlations help traders detect concentration risks. For example, if ZN and 6J correlations remain persistently high, it could indicate overexposure to safe-haven assets. Conversely, weakening correlations may signal increasing portfolio diversification. 3. Timing Market Entry/Exit: Strengthening correlations can confirm macroeconomic trends, helping traders align their strategies with market sentiment. 5. Practical Insights for Traders Incorporating rolling correlation analysis into trading workflows can enhance decision-making: Shorter rolling windows (e.g., daily) are suitable for short-term traders, while longer windows (e.g., monthly) cater to long-term investors. Adjust portfolio weights dynamically based on correlation trends. Hedge risks by identifying assets with diverging rolling correlations (e.g., if ZN-GC correlations weaken, consider adding other uncorrelated assets). 6. Practical Example: Applying Rolling Correlations to Trading Decisions To illustrate the real-world application of rolling correlations, let’s analyze a hypothetical scenario involving ZN (Treasuries) and GC (Gold), and 6J (Yen Futures): 1. Portfolio Diversification: A trader holding ZN notices a decline in its rolling correlation with GC, indicating that the two assets are diverging in response to unique drivers. Adding GC to the portfolio during this period enhances diversification by reducing risk concentration. 2. Risk Management: During periods of heightened geopolitical uncertainty (e.g., late 2022), rolling correlations between ZN and 6J rise sharply, indicating a shared safe-haven demand. Recognizing this, the trader reduces exposure to both assets to mitigate over-reliance on risk-off sentiment. 3. Market Entry/Exit Timing: Periods where the rolling correlation between ZN (Treasuries) and GC (Gold Futures) transitions from negative to positive signal that the two assets are potentially regaining their historical correlation after a phase of divergence. During these moments, traders can utilize a simple moving average (SMA) crossover on each asset to confirm synchronized directional movement. For instance, as shown in the main chart, the crossover highlights key points where both ZN and GC aligned directionally, allowing traders to confidently initiate positions based on this corroborative setup. This approach leverages both correlation dynamics and technical validation to align trades with prevailing market trends. These examples highlight how rolling correlations provide actionable insights that improve portfolio strategy, risk management, and trade timing. 7. Conclusion Rolling correlations offer a dynamic lens through which traders and investors can observe evolving market relationships. Unlike static correlations, rolling correlations adapt to shifting macroeconomic forces, revealing trends that might otherwise go unnoticed. By incorporating rolling correlations into their analysis, market participants can: Identify diversification opportunities and mitigate concentration risks. Detect early signs of market regime shifts. Align their portfolios with dominant trends to enhance performance. In a world of constant market changes, rolling correlations can be a powerful tool for navigating complexity and making smarter trading decisions. When charting futures, the data provided could be delayed. Traders working with the ticker symbols discussed in this idea may prefer to use CME Group real-time data plan on TradingView: www.tradingview.com - This consideration is particularly important for shorter-term traders, whereas it may be less critical for those focused on longer-term trading strategies. General Disclaimer: The trade ideas presented herein are solely for illustrative purposes forming a part of a case study intended to demonstrate key principles in risk management within the context of the specific market scenarios discussed. These ideas are not to be interpreted as investment recommendations or financial advice. They do not endorse or promote any specific trading strategies, financial products, or services. The information provided is based on data believed to be reliable; however, its accuracy or completeness cannot be guaranteed. Trading in financial markets involves risks, including the potential loss of principal. Each individual should conduct their own research and consult with professional financial advisors before making any investment decisions. The author or publisher of this content bears no responsibility for any actions taken based on the information provided or for any resultant financial or other losses.
COMEX:GC1!Education
by traddictiv
When is a stock too high to buy? (Example: IHG)How do you know when you’ve missed the boat? A stock has already gone up a tonne, so bascally you are too late! Sometimes, you just have to let go, right? Sometimes yes, but not always - let’s look at an example. International Hotels Group (IHG) Back in 2020, LSE:IHG IHG shares were trading down at ~2000 GBX, now they are a hairs breadth from 10,000 - that’s 5X in about 4 years. Not bad. Can you really even think about buying shares at 10,000 that were 2,000 only 4 years ago. 🤔 We’re saying YES.. if you follow some guidelines. Clearly this is not a value investment - this is a momentum trade. To be buying IHG shares up here, one is basically arguing that the price at new highs indicates and buyers are in charge and the price is going to keep going up for the time being. This helps define the trade risk very well. If the trade is that IHG has broken out over the previous peak at ~8,800. We don’t want to be owning shares below this level - if they’re back below 8,800 the momentum has stalled and we need to be out. To put it another way, we are not buying just under 10,000 and willing to hold the shares all the way back down to 2,000 again - no. We want to ride the momentum up - not down ! From here there’s a pretty good chance that momentum takes the price up to the 10,000 level. As a big round number, there is also a good chance that profit taking takes place here too. That creates our buy zone between 8,800 and the current market price (9,750). So what might a trading strategy look like to capture this situation? The following is a way to have: An intial risk of £1000 to test the waters A total risk £3000 if/when the trade starts working A 2X profit potential (with the opportunity to capture more) Spread Betting Strategy: Target £6000+ Profit with £1000 Initial Risk Entry Points and Stops 9000 GBX Entry: Stop Loss: 8600 GBX. Bet Size: £2.50 per point. Risk: £1000. 9200 GBX Entry: Stop Loss: 8800 GBX. Bet Size: £2.50 per point. Risk: £1000. 9400 GBX Entry: Stop Loss: Trailing 400 points. Bet Size: £2.50 per point. Initial Risk: £1000. Profit Targets First Position (9000): Gain: 1000 points. Profit: £2500. Second Position (9200): Gain: 800 points. Profit: £2000. Third Position (9400): Trailing Stop Profit Example: 10,400 GBX: Profit = £2500. 11,000 GBX: Profit = £4000 or more. Summary Total Risk: £3000. Fixed Profit (First Two Positions): £4500. Potential Profit (Third Position): Variable, based on trailing stop. Reward-to-Risk Ratio: 2:1 or higher, depending on trend continuation.
LSE:IHGEducation
by jasperlawler
5
How Traders Use Support and Resistance Indicators in TradingHow Traders Use Support and Resistance Indicators in Trading Strategies In the dynamic realm of trading, traders employ a variety of tools to navigate the continually evolving market landscape. Among these, support and resistance stand out as pivotal instruments, aiding traders in understanding important price levels on the charts. This article seeks to explore the indicators for support and resistance, offering insights into how they can be used to analyse market changes. Why Traders Use Support and Resistance Levels By effectively utilising support and resistance trading strategies, traders may enhance their decision-making processes. Here is why traders use these trading tools: - Entry Points: Support and resistance are crucial in identifying optimal entry points for trades. When the price approaches support, traders anticipate a potential upward reversal, providing a buying opportunity. Conversely, when the price nears a resistance, traders may look for signs of a downward reversal, indicating a potential selling point. - Trend Identification: The levels may aid in identifying market trends. When the price consistently finds support at higher levels, it indicates an uptrend. Conversely, if the price continually hits resistance at lower levels, it suggests a downtrend. When the price rebounds from horizontal levels, it indicates a consolidation range. - Stop Loss and Take Profit: Support and resistance help traders determine where to place their stop-loss and take-profit orders. By setting a stop-loss just below/above support/resistance, traders can potentially limit their losses if the price breaks below support/resistance. Similarly, placing a take-profit order just below/above a resistance/support may help secure potential returns before a market reversal. Trading Support and Resistance Levels Support and resistance act as psychological barriers where price action tends to stall, reverse, or accelerate. Here is how traders may trade with them: - Reversals: Trading reversals involve implementing the entry points concept mentioned above. For instance, if the price bounces off support, traders might enter a long position, expecting the market to rise. Conversely, if the price reverses at resistance, traders might enter a short position, anticipating a drop. - Breakouts: Breakout trading occurs when the price moves decisively through support or resistance. Traders enter trades in the direction of the breakout, expecting the market to continue moving the same way. A breakout above resistance may signal the start of an upward trend, while a breakdown below support could indicate the beginning of a downward trend. Support and Resistance Indicators Various technical indicators are used to identify the major support and resistance points. The TickTrader trading platform by FXOpen has all the major indicators needed to find these levels on a chart. Let us go through the most popular ones in detail and explain how traders can use them. Pivot Points Pivot points are a popular technical indicator used in trading to analyse market trends and strong reversal points across various financial instruments, such as stocks, currencies, and commodities. Although there are many types of pivot points, the main idea is that they are calculated using the high, low, and close prices of the previous trading period to determine key levels: the central pivot point, support, and resistance. How to Use Pivot Points Traders may use the pivot points for the following: 1. Breakout Trading: A bullish breakout involves entering a buy trade when the price breaks above the pivot point (P) or the first resistance (R1) and closes above it, targeting the next resistance (R2). Conversely, a bearish breakout involves entering a sell trade when the price breaks below the pivot point (P) or the first support (S1) and closes below it, targeting the next support (S2). 2. Reversal Trading: A bullish reversal strategy involves entering a buy trade when the price stalls above S1 or S2 without breaking below it, with the pivot point as the first target. Similarly, a bearish reversal strategy involves entering a sell trade when the price stalls below R1 or R2 without breaking above it, targeting the P level. Fibonacci Retracements Fibonacci retracements are based on the Fibonacci sequence and the Golden Ratio, used by traders to identify potential support and resistance points. The Fibonacci sequence starts at 0 and 1, with each subsequent number being the sum of the previous two. Key ratios derived from this sequence, such as 38.2%, 50%, and 61.8%, are used to determine key market points. How to Use Fibonacci Retracements These are the most common ways to use the Fibonacci retracements: - Trend Continuation: In trending markets, Fibonacci retracements are essential for identifying potential support and resistance points. In an uptrend, the market often pulls back to the 38.2%, 50%, or 61.8% level before continuing its upward movement, with these points acting as support. Conversely, in a downtrend, the market typically retraces to these same levels before resuming its downward trajectory, where they serve as resistance. - Reversals: Traders combine Fibonacci retracements with other technical analysis tools like candlestick patterns (e.g., hammer and shooting star) and chart patterns (e.g., triangles and wedges) for additional confirmation. You may monitor how the price reacts at the Fibonacci retracements. If it closes through the Fibs cleanly, it's less likely to reverse. If it shows signs of rejection (e.g., long wicks), the level is more likely to hold. Moving Average Moving averages (MAs) are some of the commonly used indicators. They have many use cases, including identifying support and resistance points. MAs calculate an asset's average price over a specified period, continuously updating and recalculating as new data points become available. This allows them to smooth market fluctuations. Also, the MA is a lagging indicator, which allows it to provide insights into trend strength. How to Use Moving Averages Moving averages are versatile tools and can be used in various ways to potentially enhance trading strategies. - Support and Resistance: The MA acts as a dynamic support/resistance based on the price position relative to it. Traders consider it support if the price is below it and resistance if the price is above it. - Crossovers: Crossovers between two MAs with different periods can help traders strengthen the signals of the support/resistance levels as they reflect changes in market sentiment and potential trend reversals. Donchian Channel The Donchian Channel indicator is a straightforward yet powerful tool for traders. It consists of three lines on a chart: an upper boundary (highest high over N periods), a lower boundary (lowest low over N periods), and a midpoint line ((Upper Boundary + Lower Boundary) / 2). Typically set to 20 periods by default, N can be adjusted to increase responsiveness or reduce noise based on market conditions. How to Use the Donchian Channel Traders may use the indicator as follows: 1. Trading Breakouts: Upper and lower boundaries serve as support and resistance. Traders look for the price breaking above the middle line to open buy trades and close them near the upper boundary and vice versa. 2. Identifying Reversals: Traders may close long positions near upper boundaries and short trades near lower boundaries before the market reverses. Multiple touches increase the strength of support and resistance. Bollinger Bands Bollinger Bands consist of three lines: a middle band (typically a 20-period simple moving average), an upper band (20-period simple moving average + (20-period standard deviation of price * 2)), and a lower band (20-period simple moving average - (20-period standard deviation of price * 2)). These bands adjust based on market volatility, expanding during periods of high volatility periods and contracting during periods of low volatility. How to Use Bollinger Bands Traders may use the Bollinger Bands to determine entry and exit points as upper and lower bands serve as support and resistance: - Trend Trading: Traders can buy near the lower band in an uptrend and sell near the upper band in a downtrend. - Range Trading: Traders look for buy signals near the lower band and sell signals near the upper band when the market consolidates within a narrow range. Final Thoughts Incorporating support and resistance analysis alongside fundamental analysis is crucial for a well-rounded market perspective. Remember, trading carries inherent risks, so it's vital to employ effective risk management strategies. As you refine your analytical approach and gain confidence in your trading abilities, consider leveraging your strategy across 600+ instruments by opening an FXOpen account. FAQ What Is the Support and Resistance Concept in Forex? Support and resistance in forex refer to levels where a currency pair often encounters barriers to moving lower (support) or higher (resistance). These are crucial for traders in making decisions about entering or exiting the market. How Can I Find Support and Resistance? To find support and resistance, traders analyse historical data. They look for areas where the price repeatedly reversed or stalled, often using tools like trendlines, pivot points, and moving averages. How Can I Identify Strong Support and Resistance? Strong support and resistance are identified by multiple price bounces or reversals occurring at the same level over time. The more times the market has reacted at a particular level, the stronger that level is considered. However, it may also mark that point as prone to breaking in the future. How Can I Trade Support and Resistance? Trading support involves buying when the price approaches this level with the expectation that it will bounce higher. Trading resistance involves selling when the price approaches this level with the expectation that it will reverse lower. Is Supply and Demand the Same As Support and Resistance? While related, supply and demand zones and support and resistance levels are not the same. Support and resistance focus on specific levels where buying (support) or selling (resistance) pressure is concentrated, whereas supply and demand zones encompass broader areas influenced by market orders. This article represents the opinion of the Companies operating under the FXOpen brand only. It is not to be construed as an offer, solicitation, or recommendation with respect to products and services provided by the Companies operating under the FXOpen brand, nor is it to be considered financial advice.
Education
by FXOpen
1
Traps Of Technical Analysis: Navigating The Pitfalls For SuccessTechnical and fundamental analyses are cornerstones for understanding how financial markets operate. While technical analysis focuses heavily on graphical representations and past price data, it can lead to significant pitfalls—especially when employed thoughtlessly. This post explores common traps that novice traders often fall into. 1. Indicator Overload One of the most prevalent mistakes among beginning traders is the overwhelming reliance on too many indicators. The assumption that a greater number of indicators equates to improved accuracy is misguided. In fact, indicators can produce conflicting signals, creating confusion rather than clarity. Many indicators are designed to promote services or websites rather than provide genuine analytical insights. While a handful of fundamental tools can effectively cover most statistical needs, attempting to integrate 20 different indicators into a single chart is unnecessary and counterproductive. Instead, combining a varied set—such as moving averages, oscillators, support and resistance levels, and chart patterns—can yield more meaningful results. 2. Overlooking Fundamental Analysis Ignoring fundamental analysis can skew a trader's understanding of market dynamics. Historical signals based on technical indicators may have been influenced by news events, leading to potentially misleading conclusions. To establish a clear picture, traders should focus on less turbulent timeframes, like the H1, and select periods of low market activity to minimize external influences. Understanding the impact of macroeconomic factors and market makers can significantly enhance the reliability of technical analysis. 3. Misinterpreting Historical Data Traders often rely on backtesting strategies against historical data, but this approach can be risky. Past performance does not guarantee future results, especially in real trading environments. While testing strategies is essential, time-consuming optimization can be a poor use of resources. Due to varying quote suppliers among brokers, discrepancies of just a few points can drastically alter outcomes. Many experts suggest improving trader’s instincts by practicing on demo accounts as a more productive alternative to exhaustive backtesting. 4. False Breakouts False breakouts frequently occur in strategies that depend on channel trading or trend line breakouts. These incidences often arise when market participants react counter to the prevailing trend. For instance, a price surge that surpasses a resistance level may provoke profit-taking from certain traders, potentially reversing the trend. A nuanced understanding of the market's fundamental basis—such as in crypto markets, where large fund involvement can bolster price movements—can help traders evade premature entries. It’s advisable to remain cautious and wait for confirmation through additional price action before acting on a breakout signal. 5. Ignoring Instrument-Specific Characteristics Each trading instrument has unique characteristics that influence its behavior, such as volatility and trading volume. Conducting analyses without accounting for these differences can lead to misguided strategies. For example, cryptocurrencies often exhibit daily fluctuations of 10%, while indices may show changes closer to 2%. Hence, applying identical settings across diverse assets is inappropriate. Understanding the contextual drivers—for example, industry legislation or technological advancements—can illuminate the vulnerabilities of trading strategies. 6. Psychological Traps The mental aspect of trading is often underestimated, with traders falling prey to cognitive biases such as wishful thinking. A signal may appear strong due to emotional fatigue or the desire to recoup losses, yet that doesn’t validate its authenticity. Traders must strive to remain objective and grounded, conducting thorough analyses and verifying signals against fundamental factors rather than succumbing to emotional impulses. 7. Neglecting Timeframe Analysis Focusing solely on a single timeframe, such as H1, can result in missed opportunities and significant oversights. Many traders disregard other timeframes, such as daily and weekly charts, which can provide crucial context to ongoing trends. An upward trend on the daily chart should ideally reflect in multiple candlesticks on the smaller H4 timeframe. A comprehensive analysis of various timeframes can offer a more rounded view and aid in making informed trading decisions. 📍 Conclusion Despite meticulous efforts to master technical analysis, errors and pitfalls are inevitable. Acknowledging these traps and actively mitigating their impact is critical in successful trading. Furthermore, incorporating robust risk management techniques and fostering emotional resilience will enhance a trader's journey. Each mistake serves as a valuable learning opportunity, paving the way for continuous growth and adaptation in trading financial markets. Traders, If you liked this educational post🎓, give it a boost 🚀 and drop a comment 📣
Education
by Lingrid
3
How I identify the best forex pairs to trade: (2)Here is how I identify the best forex pairs to trade: (Publication #2 / Update) In the top left panel, the indicator 'Compare Forex' displays the PERFORMANCE of each major currency. The USD (red line) has been the strongest currency for the past 2 months on H6 charts. By identifying the strongest currency, all that remains is to trade the USD against all the other currencies since they are weaker. = Smooth stress-free charts. I look at my trades 2-3 times a day to see if they are still blue or red. Takes a few minutes. __ DEC 1st UPDATE: Last week, the JPY became the strongest performing currency. The JPY (yellow line) crossed above the USD (red line). When the performance of the USD became weaker than the JPY = The USDJPY PAIR turned down.
Education
by ascension
Understanding ICT Bullish Mitigation BlockA Bullish ICT Mitigation Block is a concept from Inner Circle Trader (ICT) methodology. It forms at the end of a bearish trend when the price reaches a strong bullish institutional reference point, such as a bullish order block or breaker block. Formation: It occurs when the price fails to create a lower low in a bearish trend and instead reverses to shift the market structure to the bullish side. Identification: Look for a price level where the market attempted to break lower but was halted by significant buying pressure. Trading Implications: This area can serve as a strong demand level, from which the price can rally further stronger because of short traders exit and long traders enter at the same area. Multi Time Frame Analysis: Higher Time Frame - H4 Lower Time Frame - M15 Institutional Framework: Price Expansion (MMXM Buy Model) Institutional Reference Points: Bullish Mitigation Sell Side Liquidity (SSL)
NSE:HUDCOEducation
by chartology369
Reality & FibonacciParallels between Schrödinger’s wave function and Fibonacci ratios in financial markets Just as the electron finds its position within the interference pattern, price respects Fibonacci levels due to their harmonic relationship with the market's fractal geometry. Interference Pattern ⚖️ Fibonacci Ratios In the double-slit experiment, particles including photons behave like a wave of probability, passing through slits and landing at specific points within the interference pattern . These points represent zones of higher probability where the electron is most likely to end up. Interference Pattern (Schrodinger's Wave Function) Similarly, Fractal-based Fibonacci ratios act as "nodes" or key zones where price is more likely to react. Here’s the remarkable connection: the peaks and troughs of the interference pattern align with Fibonacci ratios, such as 0.236, 0.382, 0.618, 0.786. These ratios emerge naturally from the mathematics of the wave function, dividing the interference pattern into predictable zones. The ratios act as nodes of resonance, marking areas where probabilities are highest or lowest—mirroring how Fibonacci levels act in financial markets. Application In markets, price action often behaves like a wave of probabilities, oscillating between levels of support and resistance. Just as an electron in the interference pattern is more likely to land at specific points, price reacts at Fibonacci levels due to their harmonic relationship with the broader market structure. This connection is why tools like Fibonacci retracements work so effectively: Fibonacci ratios predict price levels just as they predict the high-probability zones in the wave function. Timing: Market cycles follow wave-like behavior, with Fibonacci ratios dividing these cycles into phase zones. Indicators used in illustrations: Exponential Grid Fibonacci Time Periods Have you noticed Fibonacci ratios acting as critical levels in your trading? Share your insights in the comments below!
BITMEX:BTCUSD.PEducation
by fract
19
Crypto Money Flow CycleHello, The Crypto Money Flow Cycle is a flow model that discusses the route of investments from fiat to Bitcoin, from Bitcoin to altcoins, and backward into fiat, booking profit at every step. The model theorizes that most Bitcoins in circulation aren't mined but are bought for fiat. Before every bull run, investors don't necessarily buy mining equipment but purchase Bitcoins from their fiat money. As more and more money flows from fiat into Bitcoin, Bitcoin price rallies. At this phase, Bitcoin usually pumps more than most altcoins. At the end of the phase, investors buy altcoins from their Bitcoins. They prioritize large caps like Ethereum. So, the price of large caps rallies compared to fiat and Bitcoin. Usually, these rallies outperform Bitcoin because the investors can afford to invest not only the initial fiat value but all the profits so far. That is Bitcoin's performance on fiat compounded by the large caps' performance compared to Bitcoin. Over time, investors move the value from large caps to medium caps and from medium caps to small caps, pumping the markets in this order. Since the investment in medium caps is larger with the profit than the large caps, medium caps usually pump more, and similarly, small caps pump even more when money from medium caps flows into them. To realize all the profit so far, investors can exchange small-cap altcoins back into Bitcoin, which means Bitcoin will pump once again. Then all the money so far, which is the initial fiat value compounded by the profit from each phase can return into fiat. Usually, this is when Bitcoin suffers correction and drags altcoins with itself. That's how the Crypto Money Flow Cycle usually works. It's a model, which might or might not be true. However, I can say AI could trade the estimated phases with a success rate of over 71.23%, which means there might be more to this model than luck. Regards, Ely
COINBASE:ETHUSDEducation
by Elysian_Mind
9
Drummond Geometry - Introduction to Time Frames in TradingDrummond Geometry emphasizes the importance of understanding and utilizing multiple time frames for trading. It outlines that higher time periods (HTP) provide critical directional context, while lower time periods (LTP) offer granular confirmation and entry/exit signals. This interplay allows traders to align their trades with the broader market structure while timing their actions effectively. For example, strong resistance in the HTP might signal a downtrend in the LTP, guiding shorter-term trading strategies within a defined market context. Trading Idea Based on Time Frames: Strategy: Higher Time Frame Support/Resistance Alignment 1. Objective : Trade in the direction indicated by the higher time period while fine-tuning entries and exits using the lower time period. 2. Setup : - Identify strong support or resistance in the higher time period (e.g., daily or weekly charts). - Confirm the trend's alignment in the lower time period (e.g., hourly or 15-minute charts) by observing price movement or the behavior of key levels like PL Dots. 3. Execution : - Enter trades on the LTP when it confirms the HTP direction (e.g., breakout of a lower time resistance in an uptrend supported by the HTP). - Exit trades when the LTP shows reversal signals or approaches a critical HTP level. This method ensures alignment with the market's broader context while allowing for precision in execution.
COINBASE:DOGEUSDEducation
by JordanMT
2
Measured Moves: A Guide to Finding TargetsMeasured Moves: A Guide to Finding Targets Visualizing the boundaries of price movement helps anticipate potential swing points. The concept of measured moves offers a structured framework to estimate future price behavior, based on the observation that each swing move often mirrors the size of the previous one, assuming average price volatility remains consistent. While not exact, this approach provides a practical method to approximate the extension of a swing move. Background Determining profit targets across various methods and timeframes can be challenging. To address this, I reviewed the tactics of experienced traders and market research, noting key similarities and differences. Some traders relied more on discretion, while others used technical targets or predetermined risk-to-reward ratios. Levels of support and resistance (S/R) and the Fibonacci tool frequently appeared, though their application varied by trader. Based on current evidence, levels appear most relevant when tied to the highest and lowest swing points within the current price structure, for example in a range-bound market. In contrast, sporadic or subtle levels from historical movements seem no more significant than random points. The Fibonacci tool can provide value since measurements are based on actual price range; however, the related values have limited evidence to support them. To explore these ideas, I conducted measurements on over a thousand continuation setups to identify inherent or consistent patterns in swing moves. It’s important to emphasize that tools and indicators should never be used blindly. Trading requires self-leadership and critical thinking. The application of ideas without understanding their context or validity undermines the decision-making process and leads to inconsistent results. This concept formed the foundation for my analysis, ensuring that methods were tested rather than taken at face value. Definitions Trending price movement advances in steps, either upward or downward. This includes a stronger move followed by a weaker corrective move, also known as a retracement. When the corrective move is done and prices seem to resume the prevailing trend, we can use the prior move to estimate targets; this is known as a projection. For example, if a stock moves up by 10%, pauses, and subsequently makes another move, we can utilize that value to estimate the potential outcome. Well thats the idea.. Data Through manual measurements across various timeframes, price structures, and stock categories, I have gathered data on retracements and projections. However, this information should not be considered precise due to market randomness and inherent volatility. In fact, deviations—such as a notable failure to reach a target or overextensions—can indicate a potential structural change. As this study was conducted with a manual approach, there is a high risk of selection bias, which raises concerns about the methodology's reliability. However, it allows for a more discretionary perspective, enabling observations and discretion that might be overlooked in a purely automated analysis. To simplify the findings, the presented values below represent a combination of all the data. Retracement Tool In the context of price movements within a trend, specifically continuation setups, retracements typically fall between 20% and 50% of the prior move. While retracements beyond 50% are less common, this does not necessarily invalidate the setup. From my observations, two distinct patterns emerge. First, a shallow retracement where the stock consolidates within a narrow range, typically pulling back no more than 10% to 20% before continuing its trend. Second, a deeper retracement, often around 50%, followed by a nested move higher before a continuation. For those referencing commonly mentioned values (though not validated), levels such as 23.6%, 38.2%, 44.7%, and 50% align with this range. Additionally, 18% frequently appears as a notable breakout point. However, I strongly advise against relying on precise numbers with conviction due to the natural volatility and randomness inherent in the market. Instead, a more reliable approach is to maintain a broad perspective—for example, recognizing that retracements in the 20% to 50% range are common before a continuation. This approach allows flexibility and helps account for the variability in price action. Projection Tool When there is a swing move either upward or downward, we can utilize the preceding one of the same type for estimation. This approach can be used exclusively since it is applicable for retracements, projections, and range-bound markets as long as there has been a similar price event in recent time. In terms of projection, the most common range is between 60% and 120% of the prior move, with 70% to 100% being more prevalent. It is uncommon for a stock to exceed 130% of the preceding move. Frequently mentioned values in this context include 61.8% and 78.6% as one area, although these values are frequently surpassed. The next two commonly mentioned values are 88.6% and 100%, which are the most frequent and can be used effectively on their own. These values represent a complete measured move, as they closely mimic the magnitude of the prior move with some buffer. The last value, 127%, is also notable, but exceeding this level is less common. Application The simplest application of this information is to input the range of 80% to 100% into the projection tool. Then, measure a similar prior move to estimate the subsequent one. This is known as the measured move. There are no strict rules to follow—it’s more of an art. The key is to measure the most similar move in recent times. If the levels appear unclear or overly complicated, they likely are. The process should remain simple and combined with a discretionary perspective. Interestingly, using parallel channels follows the same principle, as they measure the range per swing and project average volatility. This can provide an alternative yet similar way to estimate price movement based on historical swings. The advantage of this method is its universal and adaptable nature for setting estimates. However, it requires a prior swing move and is most effective in continuation setups. Challenges arise when applying it to the start of a new move, exhaustion points, or structural changes, as these can distort short-term price action. For instance, referencing a prior uptrend to project a downtrend is unlikely to be effective due to the opposing asymmetry in swing moves. In some cases, measured moves from earlier periods can be referenced if the current range is similar. Additionally, higher timeframes take precedence over lower ones when determining projections. This is nothing more than a tool and should be used with a discretionary perspective, as with all indicators and drawing tools. The true edge lies elsewhere. Example Use 1. Structure: Identify an established trend or range and measure a clear swing move. 2. Measured Move: Apply the measurement to the subsequent move by duplicating the line to the next point or using a trend-based Fibonacci extension tool set to 100% of the prior swing. The first two points define the swing move. The third point is placed at the deepest part of the subsequent pullback or at the start of the new move. 3. Interpretation: While this is a simple tool, its effective use and contextual application require experience and practice. Remember, this process relies on approximation and discretionary judgment.
NASDAQ:QQQEducation
by StockLeave
12
The Psychology of Wealth 🔸The psychology of wealth centers on cultivating a mindset that aligns your thoughts, beliefs, and actions with abundance, financial success, and prosperity. 🔸The affirmations you’ve mentioned—such as "money comes easily," "I deserve success," and "I’m in control of my future"—are key components of a wealth-oriented mindset. This approach isn’t just about positive thinking; it’s about rewiring your brain, creating empowering habits, and developing the emotional resilience needed to achieve financial and personal success. 🔸Here’s a breakdown of how these affirmations and principles relate to the psychology of wealth: 1. "Money Comes Easily" ▪️Belief in Ease and Flow: This statement fosters a belief that financial opportunities are abundant and accessible. When you believe money can come easily, you’re more likely to notice opportunities, attract resources, and act on them confidently. ▪️Shift from Scarcity to Abundance: Many people operate with a scarcity mindset, feeling money is hard to earn. By affirming that money comes easily, you break free from this limiting belief and open yourself to creative solutions and ideas. 🔸Actionable Steps: ▪️Identify opportunities in your field or new markets. ▪️Develop skills that make earning money simpler and more sustainable. 2. "I Deserve Success" ▪️Self-Worth and Wealth: Believing you deserve success ties your financial achievements to your sense of self-worth. If you subconsciously feel undeserving, you may sabotage your efforts or settle for less. ▪️Breaking Limiting Beliefs: Many people are conditioned by childhood experiences or societal expectations to believe success is reserved for others. Reaffirming that you deserve success challenges these limiting beliefs. 🔸Actionable Steps: ▪️Reflect on past achievements and recognize your value. ▪️Engage in self-care and personal growth activities to reinforce your worthiness. 3. "There Is an Abundance of Money" ▪️Abundance Mentality: This statement helps shift from a scarcity mindset to an abundance mindset. Believing there’s enough wealth for everyone fosters collaboration, innovation, and generosity. ▪️Law of Attraction: When you focus on abundance, you’re more likely to act in ways that attract wealth and prosperity into your life. 🔸Actionable Steps: ▪️Practice gratitude daily to focus on what you already have. ▪️Seek out stories or examples of abundance to reinforce this belief. 4. "Nothing Can Stop Me from Success" ▪️Resilience and Determination: This affirmation builds a mindset of resilience and perseverance. It reminds you that challenges are temporary and that you have the power to overcome obstacles. ▪️Reframing Failure: By adopting this belief, you view setbacks as opportunities to learn and grow, rather than insurmountable barriers. 🔸Actionable Steps: ▪️Break big goals into manageable steps to maintain momentum. ▪️Develop a "growth mindset," where challenges are viewed as essential for improvement. 5. "I’m in Control of My Future" ▪️Empowerment and Responsibility: This belief emphasizes personal accountability and the ability to influence your financial destiny. It counters feelings of helplessness and external blame. ▪️Focus on What You Can Control: While you can’t control every external event, you can control your reactions, decisions, and efforts. 🔸Actionable Steps: ▪️Set clear financial and personal goals. ▪️Continuously educate yourself about wealth-building strategies, such as investing, saving, and entrepreneurship. Final Thoughts The psychology of wealth is about more than financial gain—it’s about cultivating a mindset of abundance, gratitude, and empowerment. By believing that money comes easily, you deserve success, and you are in control of your future, you set the stage for proactive behaviors and sustained growth. Pair these beliefs with practical strategies, and you’ll find yourself on a path toward financial freedom and personal fulfillment.
Education
by ProjectSyndicate
16
Stop Thinking Backwards: The True Power of Cryptocurrency We’ve got to change how we see crypto. Too many people treat it as just a way to "cash out" into fiat money—like taking a step forward just to go backward! 💸 Cryptocurrency isn’t here to build the old system. It’s here to create a new one. Think about it: every time someone invests in crypto and then exchanges it back for dollars, they’re missing the point. Crypto’s value isn’t just its price in fiat—it’s in its utility and ecosystem. 🛠️ Adoption and Utility are what make crypto thrive: When businesses start accepting tokens like XRP directly, we’ll no longer need to convert back to dollars. Imagine paying rent, buying groceries, or even getting paid in crypto! The more we hold and use tokens within the ecosystem, the stronger it becomes. It’s about building a future where crypto isn’t just an investment—it’s a lifestyle. 💡 Crypto’s potential depends on us: ✅ Governments supporting and understanding its role. ✅ Businesses adopting tokens for real-world use. ✅ Education to shift the mindset from "get rich quick" to "build something lasting." So, next time you think about cashing out, ask yourself: are you helping build the future, or are you holding onto the past? 🌟
CRYPTOCAP:TOTAL2Education
by MoNi_MoN
Understanding ICT Classic Weekly Profile on BANKNIFTYICT weekly profiles are conceptual frameworks that describe typical patterns of price behavior during a trading week. Each ICT weekly profile has unique characteristics that can hint the traders in anticipating potential market movements. However, it is important to note that these profiles are not fixed predictions but rather frameworks to understand market tendencies and works with Higher Time Frame PD arrays confluences. ICT weekly profile is explained below with BANKNIFTY Chart analysis Classing Thursday High of Week (Bearish Setup) Key element to focus : Higher Time Frame Premium array (Weekly Buy Side Liquidity) for bearish setup Time Frames alignment : HTF --> W1 (PD Arrays) LTF ---> H4 (Market Structure) ETF --> M15 (Entry) Process : 1. Market offers Liquidity from Monday to Wednesday 2. Market seeks Liquidity on Thursday 3. Market rebalances on Friday
NSE:BANKNIFTYEducation
by chartology369
The Wildest Forex Stories You Won’t Believe Actually HappenedIf you think the forex market is all about boring spreadsheets, economic data, and mind-numbing chart patterns, think again. Beneath the surface of the world’s largest financial market lies a treasure trove of jaw-dropping, laugh-out-loud, and occasionally heart-wrenching tales. Some of these stories will make you double-check your stop-losses, while others might tempt you to try your hand at trading—if only for the adrenaline rush. Here’s a whirlwind tour of the forex market’s wildest moments. Spoiler alert: truth really is stranger than fiction. The “Flash Crash” That Shook the Yen Imagine logging into your trading platform, coffee in hand, only to see the yen skyrocket in a matter of minutes. That’s precisely what happened on January 3, 2019, when the USD/JPY pair nosedived by 4% in less than 10 minutes. The culprit? A rare combo of thin holiday liquidity, panicked algorithms, and a trigger-happy market reacting to Apple’s earnings warning . Traders watching the carnage were left rubbing their eyes in disbelief as billions of dollars evaporated faster than you can say “where’s my stop loss.” Some savvy players profited handsomely, while others were left staring at margin calls and wondering if they’d just witnessed a glitch in the Matrix. Lesson learned : Low liquidity markets can be as risky as walking on thin ice. George Soros: The Man Who Made $1 Billion in a Day No list of wild forex stories is complete without the ultimate trading flex: George Soros’s legendary short against the British pound in 1992. Dubbed “Black Wednesday,” this was the day Soros and his Quantum Fund went toe-to-toe with the Bank of England—and won. Convinced by his partner Stanley Druckenmiller that the pound was overvalued and would be forced out of the European Exchange Rate Mechanism (ERM), Soros bet billions on its decline. The result? A cool $1 billion profit in a single day, a humiliated Bank of England, and Soros’s elevation to trading legend. Lesson learned : Never underestimate the power of conviction—or billions in leverage. The Swiss Franc Tsunami On January 15, 2015, the Swiss National Bank (SNB) shocked the world by unpegging the Swiss franc from the euro . In the blink of an eye, the EUR/CHF pair plummeted as much as 19%, and chaos erupted across the forex market. Brokers went under, traders were wiped out, and even the most seasoned professionals were left scrambling for answers. Lesson learned : Central banks play by their own rules, and when they change the game, expect pandemonium. The Trader Who Bet Against the Euro—and Won Big Meet John Taylor, the founder of currency hedge fund FX Concepts and one of the original forex market wizards. In the early 2000s, Taylor made a name for himself by betting against the euro when everyone else was bullish. Armed with a combination of macroeconomic analysis and a deep understanding of market psychology, he rode the euro’s decline to rack up massive profits. His contrarian approach earned him a reputation as a forex maverick, proving that going against the herd can pay off big—if you’ve done your homework. But not for long. Long story short: FX Concepts got up to $14 billion in assets in 2008 and declared bankruptcy in 2013. Lesson learned : In forex, sometimes the best trades are the ones no one else sees coming. But also—it’s tough to know when to call it quits. The Currency Crash That Inspired a Coup In 1997, the Asian Financial Crisis sent shockwaves through global markets, but few places felt it as acutely as Indonesia. The rupiah lost more than 80% of its value , sparking widespread economic turmoil and political unrest that ultimately led to the resignation of President Suharto after 31 years in power. While most forex traders were focused on the numbers, the crisis served as a stark reminder that currencies aren’t just lines on a chart—they’re the backbone of entire economies. Lesson learned : Forex trading can shape history in ways few other markets can. The Pound’s Post-Brexit Rollercoaster In June 2016, the Brexit referendum sent the British pound on a ride so wild it could rival any theme park attraction. As the "Leave" vote defied polls and pundits, the pound plummeted 10%, hitting levels not seen since the 1980s . Traders who had been banking on a "Remain" victory were left scrambling, while those betting against the pound made a killing. The chaos didn’t stop there. In the months and years that followed, every Brexit-related headline became a market-moving event. Negotiation updates? Pound down. Political drama? Pound down. A tiny glimmer of clarity? Pound up—until the next twist. This wasn’t just a currency reacting to uncertainty; it was a masterclass in how politics can take control of forex markets. Lesson learned : Currencies are deeply tied to national identity and global sentiment. And when politics enters the mix, expect fireworks. What’s Your Wildest Forex Story? The forex market is a place of extremes—extreme risk, extreme reward, and extreme stories that prove truth is stranger than fiction. Have your own wild forex story to share? Maybe you caught the Swiss franc wave or survived a flash crash with your account intact. Drop your tale in the comments and let’s get talking!
Education
by TradingView
23
Understanding Trends and Waves in TradingIntroduction In trading education, recognising price movements is crucial. Prices move in trends, and these trends move in waves. Understanding these waves is essential for successful trading. The Two Types of Waves Impulsive/Primary Trend Comprises a minimum of five waves. Dictates the overall direction of price movement. Corrective/Secondary Trend Comprises a maximum of three waves. Provides insights into the ongoing trend. This phase is the most critical for traders to master. Conclusion To trade successfully in a trending market, it’s vital to learn how to accurately count waves. Mastering this skill can significantly enhance your trading decisions. Best wishes for your trading success!
Education
by Charts247TradingAcademy
5
Real Success Rates of the "Rising Wedge" in TradingReal Success Rates of the "Rising Wedge" in Trading Introduction The rising wedge, also known as the "rising wedge" in English, is a chart pattern that has a remarkable success rate in trading. This analysis details its performance, reliability and complementary indicators to optimize its use. Success Rate and Performance -Key Statistics Overall success rate: 81% in bull markets Average potential profit: 38% in an existing uptrend -Breakout Direction Bearish: 60% of cases Bullish: 40% of cases Contextual Reliability Bull market: 81% success, average gain of 38% After a downtrend: 51% success, average decline of 9% Important Considerations The rising wedge is generally a bearish pattern, indicating a potential reversal. Reliability increases with the duration of the pattern formation. Confirmation of the breakout by other indicators, especially volume, is crucial. Complementary Indicators -Volume Gradual decrease during formation Significant increase during breakout -Oscillators RSI (Relative Strength Index): Identifies overbought/oversold conditions Stochastics: Detects price/indicator divergences -Moving Averages Crossovers: Signal trend changes -Dynamic Support/Resistance: Confirm the validity of the wedge -Momentum Indicators MACD: Identifies price/indicator divergences Momentum: Assesses the exhaustion of the trend -Other Elements Fibonacci Levels: Identify potential support/resistance Japanese Candlestick Analysis: Provides indications of reversals Conclusion The rising wedge is a powerful tool for traders, offering a high success rate and significant profit potential. The combined use of complementary indicators increases the reliability of the signal and improves the accuracy of trading decisions. It is essential to look for a convergence of signals from multiple sources to minimize false signals and optimize trading performance. _______________________________________________ Here are the best times to enter a trade after a rising wedge, in a professional manner: -The confirmed breakout Wait for the candle to close below the support line of the wedge. Look for a significant increase in volume during the breakout to confirm its validity. -The retest Look for a pullback on the broken support line, which has become resistance. Enter when the price rebounds downward on this new resistance, confirming the downtrend. -The post-breakout consolidation Identify the formation of a flag or pennant after the initial breakout. Enter when this mini-formation breaks in the direction of the main downtrend. -The confirmed divergences Spot bearish divergences on oscillators such as the RSI or the MACD. Enter when price confirms divergence by breaking a nearby support. -Timing with Japanese Candlesticks Identify bearish formations such as the Evening Star, Bearish Harami, or Dark Cloud. Enter as soon as the next candle confirms the bearish pattern. -Important Considerations Always place a stop-loss to manage risk effectively. Be patient and wait for the setup to be confirmed before entering the trade Check the trend on higher timeframes to ensure the consistency of the trade. Integrate the analysis of the rising wedge with other technical indicators to improve the quality of decisions. By following these recommendations, traders can optimize their entries on rising wedges while minimizing the risk of false signals.
BINANCE:BTCUSDEducation
by Le-Loup-de-Zurich
Natural Patterns & Fractal GeometryIn my previous research publication, I explored the parallels between the randomness and uncertainty of financial markets and Quantum Mechanics, highlighting how markets operate within a probabilistic framework where outcomes emerge from the interplay of countless variables. At this point, It should be evident that Fractal Geometry complements Chaos Theory. While CT explains the underlying unpredictability, FG reveals the hidden order within this chaos. This transition bridges the probabilistic nature of reality with their geometric foundations. ❖ WHAT ARE FRACTALS? Fractals are self-replicating patterns that emerge in complex systems, offering structure and predictability amidst apparent randomness. They repeat across different scales, meaning smaller parts resemble the overall structure. By recognizing these regularities across different scales, whether in nature, technology, or markets, self-similarity provides insights into how systems function and evolve. Self-Similarity is a fundamental characteristic of fractals, exemplified by structures like the Mandelbrot set, where infinite zooming continuously reveals smaller versions of the same intricate pattern. It's crucial because it reveals the hidden order within complexity, allowing us to understand and anticipate its behavior. ❖ Famous Fractals List of some of the most iconic fractals, showcasing their unique properties and applications across various areas. Mandelbrot Set Generated by iterating a simple mathematical formula in the complex plane. This fractal is one of the most famous, known for its infinitely detailed, self-similar patterns. The edges of the Mandelbrot set contain infinite complexity. Zooming into the set reveals smaller versions of the same structure, showing exact self-similarity at different scales. Models chaos and complexity in natural systems. Used to describe turbulence, market behavior, and signal processing. Julia Set Closely related to the Mandelbrot set, the Julia set is another fractal generated using complex numbers and iterations. Its shape depends on the starting parameters. It exhibits a diverse range of intricate, symmetrical patterns depending on the formula used. Shares the same iterative principles as the Mandelbrot set but with more artistic variability. Explored in graphics, simulations, and as an artistic representation of mathematical complexity. Koch Snowflake Constructed by repeatedly dividing the sides of an equilateral triangle into thirds and replacing the middle segment with another equilateral triangle pointing outward. A classic example of exact self-similarity and infinite perimeter within a finite area. Visualizes how fractals can create complex boundaries from simple recursive rules. Models natural phenomena like snowflake growth and frost patterns. Sierpinski Triangle Created by recursively subdividing an equilateral triangle into smaller triangles and removing the central one at each iteration. Shows perfect self-similarity; each iteration contains smaller versions of the overall triangle. Highlights the balance between simplicity and complexity in fractal geometry. Found in antenna design, artistic patterns, and simulations of resource distribution. Sierpinski Carpet A two-dimensional fractal formed by repeatedly subdividing a square into smaller squares and removing the central one in each iteration. A visual example of how infinite complexity can arise from a simple recursive rule. Used in image compression, spatial modeling, and graphics. Barnsley Fern A fractal resembling a fern leaf, created using an iterated function system (IFS) based on affine transformations. Its patterns closely resemble real fern leaves, making it a prime example of fractals in nature. Shows how simple rules can replicate complex biological structures. Studied in biology and used in graphics for realistic plant modeling. Dragon Curve A fractal curve created by recursively replacing line segments with a specific geometric pattern. Exhibits self-similarity and has a branching, winding appearance. Visually similar to the natural branching of rivers or lightning paths. Used in graphics, artistic designs, and modeling branching systems. Fractal Tree Represents tree-like branching structures generated through recursive algorithms or L-systems. Mimics the structure of natural trees, with each branch splitting into smaller branches that resemble the whole. Demonstrates the efficiency of fractal geometry in resource distribution, like water or nutrients in trees. Found in nature, architecture, and computer graphics. ❖ FRACTALS IN NATURE Before delving into their most relevant use cases, it's crucial to understand how fractals function in nature. Fractals are are the blueprint for how nature organizes itself efficiently and adaptively. By repeating similar patterns at different scales, fractals enable natural systems to optimize resource distribution, maintain balance, and adapt to external forces. Tree Branching: Trees grow in a hierarchical branching structure, where the trunk splits into large branches, then into smaller ones, and so on. Each smaller branch resembles the larger structure. The angles and lengths follow fractal scaling laws, optimizing the tree's ability to capture sunlight and distribute nutrients efficiently. Rivers and Tributaries: River systems follow a branching fractal pattern, where smaller streams (tributaries) feed into larger rivers. This structure optimizes water flow and drainage, adhering to fractal principles where the system's smaller parts mirror the larger layout. Lightning Strikes: The branching paths of a lightning bolt are determined by the path of least resistance in the surrounding air. These paths are fractal because each smaller branch mirrors the larger discharge pattern, creating self-similar jagged structures which ensures efficient distribution of resources (electrical energy) across space. Snowflakes: Snowflakes grow by adding water molecules to their crystal structure in a symmetrical, self-similar pattern. The fractal nature arises because the growth process repeats itself at different scales, producing intricate designs that look similar at all levels of magnification. Blood Vessels and Lungs: The vascular system and lungs are highly fractal, with large arteries branching into smaller capillaries and bronchi splitting into alveoli. This maximizes surface area for nutrient delivery and oxygen exchange while maintaining efficient flow. ❖ FRACTALS IN MARKETS Fractal Geometry provides a unique way to understand the seemingly chaotic behavior of financial markets. While price movements may appear random, beneath this surface lies a structured order defined by self-similar patterns that repeat across different timeframes. Fractals reveal how smaller trends often replicate the behavior of larger ones, reflecting the nonlinear dynamics of market behavior. These recurring structures allow to uncover the hidden proportions that influence market movements. Mandelbrot’s work underscores the non-linear nature of financial markets, where patterns repeat across scales, and price respects proportionality over time. Fractals in Market Behavior: Mandelbrot argued that markets are not random but exhibit fractal structures—self-similar patterns that repeat across scales. Power Laws and Scaling: He demonstrated that market movements follow power laws, meaning extreme events (large price movements) occur more frequently than predicted by standard Gaussian models. Turbulence in Price Action: Mandelbrot highlighted how market fluctuations are inherently turbulent and governed by fractal geometry, which explains the clustering of volatility. 🔹 @fract's Version of Fractal Analysis I've always used non-generic Fibonacci ratios on a logarithmic scale to align with actual fractal-based time scaling. By measuring the critical points of a significant cycle from history, Fibonacci ratios uncover the probabilistic fabric of price levels and project potential targets. The integration of distance-based percentage metrics ensures that these levels remain proportional across exponential growth cycles. Unlike standard ratios, the modified Fibonacci Channel extends into repeating patterns, ensuring it captures the full scope of market dynamics across time and price. For example, the ratios i prefer follow a repetitive progression: 0, 0.236, 0.382, 0.618, 0.786, 1, (starts repeating) 1.236 , 1.382, 1.618, 1.786, 2, 2.236, and so on. This progression aligns with fractal time-based scaling, allowing the Fibonacci Channel to measure market cycles with exceptional precision. The repetitive nature of these ratios reflects the self-similar and proportional characteristics of fractal structures, which are inherently present in financial markets. Key reasons for the tool’s surprising accuracy include: Time-Based Scaling: By incorporating repeating ratios, the Fibonacci Channel adapts to the temporal dynamics of market trends, mapping critical price levels that align with the natural flow of time and price. Fractal Precision: The repetitive sequence mirrors the proportionality found in fractal systems, enabling to decode the recurring structure of market movements. Enhanced Predictability: These ratios identify probabilistic price levels and turning points with a level of detail that generic retracement tools cannot achieve. By aligning Fibonacci ratios with both trend angles and fractal time-based scaling, the Fibonacci Channel becomes a powerful predictive tool. It uncovers not just price levels but also the temporal rhythm of market movements, offering a method to navigate the interplay between chaos and hidden order. This unique blend of fractal geometry and repetitive scaling underscores the tool’s utility in accurately predicting market behavior.
BITSTAMP:BTCUSDEducation
by fract
17
The Anatomy of a Downtrend: A case study of silver XAGUSDTopic 1: Downtrend analysis Introduction: This post serves two purposes: to educate readers and to act as a personal reference tool for future analysis. We’ll be reviewing recent price action in Silver (XAGUSD) , offering valuable insights that apply not just to commodities but also to equities. This sequence of events, while varying in scale, repeats itself across all time frames—daily, monthly, yearly. As a rule, the higher the time frame, the greater the potential returns. Rant We don’t need a million strategies. We don’t need overpriced guru courses claiming to deliver “10,000% gainers” (cue eye roll). What we need is a solid understanding of market behavior and the tools to make informed decisions. Preface Due to charting limitations, I’ve compressed the information here. Additional research may be necessary for a full understanding. This analysis incorporates: • Classical Chart Patterns (Part 1) • Elliott Wave Theory (Part 2) • Support & Resistance Levels (Blended) Getting Started: Understanding Trend Reversal Silver Price Peak Notice the rejection at $34.86 red circle on October 24. Silver spiralled lower, first to $33.08, briefly rebounded to $34.58, but lost momentum and rolled over again big purple circle. Reversal Peak Draw a trendline from $34.5 down to $30.615, connecting as many wicks as possible. Pay attention to the price swings during this dramatic decline. Downtrend Sequence Silver followed this classic pattern of lower highs and lower lows: 1. Swing Low 2. Lower High 3. Lower Low 4. Lower High 5. Lower Low Tip: Identifying Swing Extremes Use your drawing tool to circle ⭕️ or draw a square ⬛️the major swing points—areas where price reacted most sharply or moved the furthest before reversing. These are key reference points for understanding market structure. Potential Reversal Price broke out of its down trend and subsequently broke over its (lowest high) last purple swing point. At this point price formed a new high green circle 🟢 however a (higher lower) has not yet been confirmed on the higher time frame. In the next post, I’ll dive into the lower time frames, focusing on Elliott Wave Theory and key observations since the trendline break. If you found this analysis helpful, please leave a like and share your thoughts in the comments—thank you!
FX:XAGUSDEducation
by coilemard
4