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Hurst Diamond Notation PivotsThis is a fairly simple indicator for diamond notation of past hi/lo pivot points, a common method in Hurst analysis. The diamonds mark the troughs/peaks of each cycle. They are offset by their lookback and thus will not 'paint' until after they happen so anticipate accordingly. Practically, traders can use the average length of past pivot periods to forecast future pivot periods in time🔮. For example, if the average/dominant number of bars in an 80-bar pivot point period/cycle is 76, then a trader might forecast that the next pivot could occur 76-ish bars after the last confirmed pivot. The numbers/labels on the y-axis display the cycle length used for pivot detection. This indicator doesn't repaint, but it has a lot of lag; Please use it for forecasting instead of entry signals. This indicator scans for new pivots in the form of a rainbow line and circle; once the hi/lo has happened and the lookback has passed then the pivot will be plotted. The rainbow color per wavelength theme seems to be authentic to Hurst (or modern Hurst software) and has been included as a default.
Pine Script® indicator
by BarefootJoey
84
ZigCycleBarCount [MsF]Japanese below / 日本語説明は英文の後にあります。 Based on "ZigZag++" indicator by DevLucem. Thanks for the great indicator. ------------------------- This indicator that displays the candle count (bar count) at the peaks of Zigzag . It also displays the price of the peaks. You can easily count candles (bars) from peak to peak. Helpful for candles (bars) in cycle theory. This logic of the indicator is based from the mt4 zigzag indicator . Parameter: Depth = depth (price range) Backstep = Period Deviation ＝ Percentage of how much the price has wrapped around the previous line. Example: Depth = 12 Backstep = 3 Deviation = 5 In this case, the price range is updated by 12 pips or more (Depth), and after 3 or more candlesticks line up (Backstep), if the price deviates from the previous line by 5% or more (Deviation), a peak is added. ------------------------- Zigzagの頂点にローソクカウント（バーカウント）を表示するインジケータです。 頂点の価格も表示します。 頂点から頂点までのローソク（バー）を容易にカウントすることができます。 サイクル理論のローソク（バー）に役立ちます。 Zigzagロジック自体はMT4のzigzagインジケータを流用しています。 ＜パラメータ＞ Depth＝深さ（値幅） Backstep＝期間 Deviation＝価格がどれだけ直前のラインの折り返したかの割合 例： Depth＝12 Backstep＝3 Deviation＝5 この場合、値幅を12pips以上更新し（Depth）、ローソク足が3本以上並んだ後（Backstep）、価格が直前のラインの5％以上折り返せば（Deviation）、頂点を付けます。 ＜表示オプション＞ Label_Style = "TEXT"…テキスト表示、"BALLOON"…吹き出し表示
Pine Script® indicator
by Trader_Morry
32
Gold–Bitcoin Correlation (Offset Model) by KManus88This indicator analyzes the correlation between Gold (XAU/USD) and Bitcoin (BTC/USD) using a time-offset model adjustable by the user. The goal is to detect cyclical leads or lags between both assets, highlighting how capital flows into Gold may precede or follow movements in the crypto market. Key Features: Dynamic correlation calculation between Gold and Bitcoin. Adjustable offset in days (default: 107) to fine-tune the temporal shift. Automatic labels and on-chart visualization. Compatible with multiple timeframes and logarithmic scales. Interpretation: Positive correlation suggests synchronized trends between both assets. Negative correlation signals divergence or rotation of liquidity. The time-offset parameter helps estimate when a shift in Gold could later reflect in Bitcoin. Recommended use: For macro-financial and global liquidity cycle analysis. As a complementary tool in cross-asset momentum strategies. © 2025 – Developed by KManus88 | Inspired by monetary correlation studies and global liquidity cycles. This script is for educational purposes only and does not constitute financial advice.
Pine Script® indicator
by kmanus88
Altcoins Exit Planner [SwissAlgo]Altcoins Exit Planner Navigating Altcoin Exits: A Strategic Approach: Planning your exits before emotions take over ------------------------------------------------------------------ ✅ THE PSYCHOLOGY OF ALTCOIN TRADING Many traders face recurring challenges when managing altcoin positions: The Greed Trap : Holding through euphoric rallies, hoping for unrealistic targets, only to watch gains evaporate during market reversals. The Paralysis Problem : Sitting on large unrealized profits but unsure which assets to exit, when, or how much — leading to inaction. The FOMO Cycle : Rotating into trending coins too early or too late, often abandoning solid positions prematurely. Analysis Overload : Consuming endless opinions and indicators without ever forming a clear, actionable exit strategy. These patterns often stem from a lack of structure and planning . Emotional decision-making in volatile markets can be costly — especially with altcoins. Developing a systematic framework can help define exit levels in advance , aiming to reduce emotional bias and improve decision clarity. The goal is to build disciplined exit strategies based on predefined logic rather than reactive impulses. ------------------------------------------------------------------ ✅ FEATURES & FUNCTIONALITY This indicator is designed to provide traders with a structured framework for exit planning. It aims to reduce decision-making under pressure by offering a visual roadmap on the chart. The tool provides an analysis of key data points, including: Structured Analysis : The indicator evaluates asset strength, identifies potential market phases, and derives potential exit levels from historical price behavior. This analysis may help traders assess whether an asset shows characteristics of strength (e.g., potential for extended targets) or weakness (e.g., early exit signals). Actionable Information : It generates specific price levels and quantities for consideration as part of a predefined exit strategy. Proactive Alerts : The system includes configurable alerts that can notify users as prices approach these key levels, allowing time for preparation. This feature is intended to support a shift from reactive trading toward systematic, criteria-based exit planning. ------------------------------------------------------------------ ✅ HOW IT WORKS - AUTOMATED ANALYSIS & PLANNING This indicator is designed to automate key aspects of exit planning that would otherwise require manual effort: Fibonacci Level Calculation & Plotting : Automatically identifies key historical cycle points (e.g., bear market lows, bull market highs, recent pullbacks) and calculates relevant Fibonacci levels (both "Fib Retracments" from previous cycle ATH to bear market bottom, and "Fib. extensions" - considering major price impulses/waves in current bull market). This may help reduce manual drawing errors and streamline target identification. Automated Calculation and Plotting of "Fib. Retracement "Levels (from ATH of previous cycle to bottom in bear market) Fibonacci retracement levels are a popular tool used in technical analysis to identify potential support and resistance levels in a market. After a significant price move, traders look for the price to "retrace" or pull back to one of several key Fibonacci ratios of the original move before continuing in its original direction. The most common retracement levels are 23.6%, 38.2%, 50%, 61.8%, and 78.6%. These levels are static horizontal lines on a chart, and their predictive power is based on the idea that they are "areas of interest" where a trend might pause or reverse. Automated Calculation and Plotting of "Fib. Extension" Levels (Price Impulses/Waves within current Bull Market) Fibonacci extension levels are used to identify potential price targets or profit zones once a market has moved past its previous high or low. Unlike retracements, which measure a pullback, extensions project how far a trend might continue in the direction of its impulse move. They are typically used to anticipate where a wave or a rally might end and are based on ratios like 127.2%, 161.8%, 261.8%, and sometimes even higher. Extensions are a key tool for traders looking to set price targets for taking profits. Coin Strength Assessment: Evaluates recovery performance relative to previous cycle peaks and classifies assets into four categories (Weak, Average, Strong, Outlier). Strength ratings may adjust dynamically based on momentum conditions — all derived from price data. Market Phase Detection : Continuously monitors trend indicators, volume behavior, and altseason dynamics to estimate the current market phase. This may assist in contextualizing exit decisions without requiring manual phase analysis. Exit Level Generation : Based on the asset’s strength classification and selected strategy (Conservative, Balanced, Aggressive), the system generates sequential exit levels with suggested percentages and quantities. Designed to support structured planning across three stages. Signal Detection : Tracks multiple conditions — including price extensions, volume surges, momentum shifts, and cycle patterns — to generate alerts when predefined criteria are met. Emergency Exit Detection : Scans for rare but high-risk scenarios (e.g., cycle top formations with multiple confluences) that may warrant immediate attention. Alerts are designed to highlight potential overextension during volatile phases. Transfer Alerts : Calculates proximity to key exit zones and may issue early warnings to prepare for execution (e.g., moving assets from cold storage to exchanges), aiming to reduce last-minute decision pressure. The script operates in two distinct modes: Coin Analysis Mode Displays automatically-calculated Fibonacci levels, asset strength classification, market phase estimation, and contextual risk factors — designed to support structured analysis. Exit Plan Mode Generates a customizable exit strategy with calculated price levels, suggested quantities, and potential outcome scenarios — aiming to assist with disciplined planning and reduce emotional bias. ------------------------------------------------------------------ ✅ SETUP & INSTALLATION Step 1: Chart Setup Add the indicator to your altcoin USD chart (e.g., spot market pairs). Recommended timeframe: 3 days for signal clarity. Dark theme suggested for visual contrast. Step 2: Configure Your Exit Strategy Open Settings → “Setup Your Exit Plan” Choose your strategy: Conservative: Prioritizes earlier exits for stricter risk control; Balanced: Combines early and late exits for a mixed approach; Aggressive: Targets later exits, accepting potentially higher volatility. Input your asset quantity. (Optional) Set a minimum sell price to block exit signals below your defined threshold. (Optional) Set a sell-now price to trigger a sell alert when your exit target is reached, bypassing intermediate levels. Step 3: Choose Display Mode Coin Analysis Mode: View market conditions, strength classification, Fibonacci levels, and contextual risk insights. Designed to support monitoring and signal validation. Exit Plan Mode: Displays your structured exit roadmap with suggested price levels, quantities, and visual chart overlays. Focuses on execution and planning. Step 4: Set Up Alerts (Recommended) Click the “Alert” button on the chart. Select “Altcoins Exit Planner” as the condition. Choose alert type: Planned Exit, Emergency Exit, Transfer Alert, Local Top, Trend Change Set expiration to “Open-ended” Configure your preferred notification method. Alert Types Include: Planned Exit Alerts: Triggered when suggested exit levels are reached (Exit #1, #2, #3). Emergency Exit Alerts: Highlight potential cycle tops or full-exit conditions. Transfer Alerts: Advance notice to prepare for execution (e.g., moving assets to exchanges). Local Top Alerts: Short-term pullback signals for tactical decisions. Trend Change Alerts: Indicate potential market phase transitions. Once configured, the indicator begins analyzing and may notify you when exit conditions align with your selected strategy. ------------------------------------------------------------------ ✅ USER INTERFACE The interface is organized into two primary modes: 1) Coin Analysis Mode Analysis Table Includes: Fibonacci levels with price targets and percentage differentials Market trend status (e.g., Strong Bull, Weakening Bull, Bear Market) Volume behavior (Normal / Abnormal) Price extension status (Overextended / Within range) Altseason detection Coin strength classification Reversal risk assessment (Low / Average / High) Suggested action based on current conditions Visual Elements: Bull/Bear trend EMA line Volume-based candle coloring (overrides default chart candles) Pivot points for key structural levels Selectable Fibonacci extension/retracement lines Background highlighting during altseason periods (potential cycle peak phase) 2) Exit Plan Mode Exit Plan Table Displays: Suggested quantity to sell at each exit level Estimated portfolio value in USD Structured exit plan with Fibonacci levels, percentages, quantities, and projected amounts Average exit price calculation Potential outcome scenarios if all exit levels are reached Price Lines: Individual exit level markers with contextual details Average exit price reference line Minimum sell price line (if enabled) Sell-now price line (if enabled) Signal Indicators: Blue diamonds: Planned exit levels reached Red triangles: Cycle top warnings Orange triangles: Local top signals These elements are designed to assist with visual interpretation and structured decision-making. All outputs are derived from price data and user-defined settings. ------------------------------------------------------------------ ✅ LIMITATIONS Market Cycle Dependency: This indicator is designed for cryptocurrency market cycles and will not perform similarly in other asset classes or market conditions. Its logic is based on historical crypto behavior, which may not repeat. Assumption-Based Framework: The methodology relies on assumptions about market cycles, Fibonacci relationships, and altcoin behavior patterns. These assumptions may not hold under future conditions. User Responsibility All signals require user interpretation and decision-making. The indicator provides information, not investment advice. Signals should be validated with additional analysis. Position sizing and risk management remain the user's responsibility. Technical Requirements Intended for use on the 3-day timeframe. Designed for altcoin/USD trading pairs. Requires sufficient historical data for Fibonacci calculations. May not function properly on newly listed assets with limited price history. Risk Management Guidelines. Recommended practices include: Use with limited portions of your portfolio. Combine with other technical and fundamental tools. Consider broader market context beyond indicator signals. Maintain independent stop-loss levels. Review and adjust settings as market conditions evolve. Signal Interpretation Emergency signals highlight conditions that may warrant immediate review. Planned exits support gradual, structured position reduction. Transfer alerts provide preparation time before potential execution. Local top signals may assist short-term tactical decisions. ------------------------------------------------------------------ ✅ DISCLAIMER This indicator is for educational and informational purposes only . It does not constitute financial, investment, or trading advice. The indicator: Makes no guarantees about future market performance. Cannot predict market movements with certainty. May generate false signals or miss key developments. Relies on historical patterns that may not repeat. Should not be used as the sole basis for trading decisions. Users are responsible for: Conducting independent research and analysis. Understanding the risks of cryptocurrency trading. Making their own investment/divestment decisions. Managing position sizes and risk exposure appropriately. Cryptocurrency trading involves substantial risk and may not be suitable for all investors. Past performance does not guarantee future results. Users should only invest what they can afford to lose and consult qualified professionals before making financial decisions. The indicator’s assumptions may be invalidated by changing market conditions. By using this tool, users acknowledge these limitations and accept full responsibility for their trading decisions.
Pine Script® indicator
by SwissAlgo
Power Metcalfe's + Fibonacci Channel## Metcalfe's Law + Fibonacci Channel - Optimized Bitcoin Valuation Model This indicator presents an enhanced variation of the classic Bitcoin Metcalfe's Law model, combining logarithmic regression analysis with Fibonacci retracement levels to create a comprehensive valuation framework. **Key Features:** - **Optimized Metcalfe's Law calculation** using historical cycle data (2013-2022) for improved accuracy - **Fibonacci channel overlay** with key levels: 0.382, 0.618, 1.272, 1.618, 2.000, 2.618, 3.000 - **Dynamic trading zones** with visual buy/sell signals based on price position relative to the channel - **Real-time targets** displaying current Fibonacci projections and fair value estimates **What makes it different:** Unlike standard Metcalfe's Law implementations, this version integrates logarithmic growth principles and uses a refined dataset that accounts for Bitcoin's maturation cycles. The Fibonacci overlay provides clearer entry/exit points while maintaining the long-term growth trajectory based on network adoption. **Best suited for:** Long-term Bitcoin holders and macro traders looking for mathematical support/resistance levels based on network adoption dynamics and scarcity. The model automatically updates calculations and provides a comprehensive information table showing current formula parameters and key price targets.
Pine Script® indicator
by didaz
Shift 3M - 30Y Yield Spread🟧 Shift 3M - 30Y Yield Spread - This indicator visually displays the **inverse of the US Treasury short-long yield spread** (3-month minus 30-year spread reversal signal) in a "price chart-like" form. - By default, the spread line is shifted by 1 year to help anticipate forward market moves (you can adjust this offset freely). - Especially customized to be analyzed together with the movements of US indices like the S&P 500, and to help understand broader market cycles. ✅ Description - Normalizes the spread based on a rolling window length you set (default: 500 bars). - Both the normalization window and offset (shift) are fully customizable. - Then, it scales the spread to match your chart’s price range, allowing you to intuitively compare spread movements alongside price action. - Instantly see the **inverse (reversal) signals of the short-long yield spread**, curve steepening, and how they align with actual price trends. ⚡ By reading macro yield signals, you can **anticipate exactly when a market crash might come or when an explosive rally is about to start**. ⚡ A perfect tool for macro traders and yield curve analysts who want to quickly catch major market turning points! copyright @invest_hedgeway ============================================================ 🟧3개월 - 30년 물 장단기 금리차 역수 - 이 인디케이터는 미국 국채 **장단기 금리차 역수**(3개월물 - 30년물 스프레드의 반전 시그널)를 시각적으로 "가격 차트"처럼 표시해 줍니다. - 기본적으로 스프레드 선은 **1년(365봉) 시프트**되어 있어, 시장을 선행적으로 파악할 수 있도록 설계되었습니다 (값은 자유롭게 조정 가능). - 특히 S&P500 등 미국 지수 흐름과 함께 분석할 수 있도록 맞춤화되었으며, 시장 사이클을 이해하는 데에도 큰 도움이 됩니다. ✅ 설명 - 지정한 롤링 윈도우 길이(기본: 500봉)를 기준으로 스프레드를 정규화합니다. - 정규화 길이와 오프셋(시프트) 모두 자유롭게 설정 가능 - 이후 현재 차트의 가격 레인지에 맞게 스케일링해, 가격과 함께 흐름을 직관적으로 비교할 수 있습니다. - **장단기 금리차의 역전(역수) 시그널**, 커브 스티프닝 등과 실제 가격 움직임의 관계를 한눈에 확인 ⚡ 거시 금리 신호를 통해 **언제 폭락이 올지, 언제 폭등이 터질지** 미리 감지할 수 있습니다. ⚡ 시장의 전환점을 빠르게 캐치하고 싶은 매크로 트레이더와 금리 분석가에게 완벽한 도구! copyright @invest_hedgeway
Pine Script® indicator
by invest_hedgeway
1
DECODE Global Liquidity IndexDECODE Global Liquidity Index 🌊 The DECODE Global Liquidity Index is a powerful tool designed to track and aggregate global liquidity by combining data from the world's 13 largest economies. It offers a comprehensive view of financial liquidity, providing crucial insights into the underlying currents that can influence asset prices and market trends. The economies covered are: United States, China, European Union, Japan, India, United Kingdom, Brazil, Canada, Russia, South Korea, Australia, Mexico, and Indonesia. The European Union accounts for major individual economies within the EU like Germany, France, Italy, Spain, Netherlands, Poland, etc. Key Features: 1. Customizable Liquidity Sources Include Global M2: You can opt to include the M2 money supply from the 13 listed economies. M2 is a broad measure of money supply that includes cash, checking deposits, savings deposits, money market securities, mutual funds, and other time deposits. (Note: Australia uses M3 as its primary measure, which is included when M2 is selected for Australia). Include Central Bank Balance Sheets (CBBS): Alternatively, or in addition, you can include the total assets held by the central banks of these economies. Central bank balance sheets expand or contract based on monetary policy operations like quantitative easing (QE) or tightening (QT). Combined View: If you select both M2 and CBBS, and data is available for both, the indicator will display an average of the two aggregated values. If only one source type is selected, or if data for one type is unavailable despite both being selected, the indicator will display the single available and selected component. This provides flexibility in how you define and analyze global liquidity. 2. Lead/Lag Analysis (Forward Projection): Lead Offset (Days): This feature allows you to project the liquidity index forward by a specified number of days. Why it's useful: Global liquidity changes can often be a leading indicator for various asset classes, particularly those sensitive to risk appetite, like Bitcoin or growth stocks. These assets might lag shifts in liquidity. By applying a lead (e.g., 90 days), you can shift the liquidity data forward on your chart to more easily visualize potential correlations and identify if current asset price movements might be responding to past changes in liquidity. 3. Rate of Change (RoC) Oscillator: Year-over-Year % View: Instead of viewing aggregate liquidity, you can switch to a Year-over-Year (YoY%) Rate of Change (ROC) oscillator. Why it's useful: Momentum Identification: The ROC highlights the speed and direction of liquidity changes. Positive values indicate liquidity is increasing compared to a year ago, while negative values show it's decreasing. Turning Points: Oscillators make it easier to spot potential accelerations, decelerations, or reversals in liquidity trends. A cross above the zero line can signal strengthening liquidity momentum, while a cross below can signal weakening momentum. Cycle Analysis: It helps in assessing the cyclical nature of liquidity provision and its potential impact on market cycles. This indicator aims to provide a clear, customizable, and insightful measure of global liquidity to aid traders and investors in their market analysis.
Pine Script® indicator
by decodejar
6
MTF Fractal Bias Confluence DetectorMTF Fractal Bias Confluence Detector This indicator, the MTF Fractal Bias Confluence Detector, is based on the idea that the market exhibits fractal behaviour. The origin of the idea traces back to 1963, when Benoit Mandelbrot analyzed the fluctuations in cotton prices over a time series starting in 1900, discovering that price changes exhibited scale-invariant patterns. This means that the curve representing daily price changes mirrored the shape of monthly price changes, highlighting the fractal nature of market behaviour. When applied to swing points across multiple timeframes (MTF), this concept suggests that swing points demonstrate similar patterns regardless of the timeframe being analyzed. These self-similar fractal structures provide traders with insights into market reversals and trends, making them a powerful tool for multi-timeframe analysis. A Swing Point is made up of three main parts: a move away from the last Break level; forming a peak (pivot point) with a Fakeout of the peak (explained through an example later); and a subsequent move away from it. These swing points recur across all timeframes as part of cyclical momentum patterns, meaning each swing point gives rise to a new cycle of market movement. Due to the fractal nature of the market, larger cycles encompass multiple smaller ones. The theory behind the Fractal Bias Confluence Detector utilizes the idea that the market movements are fractal in nature and illustrates how such swing points can be identified across MTFs. To do so, we examine the Peak Fakeouts within these cycles, as they form. It is not possible to know in advance how long each of these moves will last, but a Swing Point will often occur with a Peak Fakeout. Therefore, the most critical element is to identify the Peak Fakeout. The snapshot below captures a Peak Fakeout, as discussed earlier. Similarly, the following snapshot shows various possible breakdowns of Higher Time Frame (HTF) cycles into smaller Lower Time Frame (LTF) movements. The chart contains a white table(not part of the indicator and shown for illustration purposes only). To further illustrate. Consider the combination of Time Frames (TF) from the 2nd row (from the above snapshot). Cycle TF (1M), Setup TF (1W), Momentum TF (1D) etc. Price movements in the 1M TF highlight the direction in which HTF traders are pushing the market. Often, when markets have broken out of a level, they tend to form a peak and can then pull back towards the prior breakout level. Once the pullback is beyond the last breakout level, in the opposite direction, we may say the peak formation is created, and directional bias has changed. This is also called Peak Fakeout. Due to the fractal nature of the market, Swing Points on the HTF will often constitute multiple Swing Points on the LTF, though they are not always in sync. However, after such peak formation, there is a high probability that the price might move away from the peak for at least 1 candle (in the cycle TF). This theory illustrates that once a new cycle is in play, we can then look at 1W (Setup TF) to look for possible in-sync movements, at least within that 1 candle of the HTF. Repeating the same for further lower TFs, we may arrive at a confluence of Fractal Bias and see how the movements in LTF are driven by the HTF momentum. Another example within the chart: Note: The above examples are just for illustration purposes, and other permutations and combinations of movements across multiple TFs are also possible. This indicator aims to help users identify such fractal-bias-confluences, so that they can leverage the fractal nature of the market to get a holistic view. To do so, the indicator displays how the market has moved across multiple time frames, with respect to different historical levels. Features: 1. The bias summary table The following snapshot depicts the bias summary table at the bottom right of the chart. 1.1. Workings: The table will display, for various TFs, in the first four (starting from "current" to Prev ) rows, one of the following. "F/H" , " Acronym for the failed break of the previous high", "F/L" , " Acronym for the failed break of the previous low", "B/H" , " Acronym for the break of the previous high", "B/L" , " Acronym for the break of the previous low", "IN" , " Acronym for an inside candle (never broke high or low of perv candle)", "OT" , " Acronym for an outside candle (broke both high and low of previous candle and closing price is in between previous high and low)". Note: these acronyms are customizable according to the user's choice of terminology in any language, as shown in the snapshot below. 1.1.1 In the above snapshot, the 1st row, called "Current", shows how the current candle is evolving with respect to the previous one. The "previous" row shows how the previous candle closed with respect to the pre-previous one. The next two rows represent the bias of the pre-previous and pre-pre-previous in a similar manner. By default, the bias is updated in real-time, even for the already closed historical candles. For example, if the previous 4H candle closed as a B/H and the current price then comes below the pre-previous 4H candle high, then the bias of the previous candle will get updated to F/H. This informs the user that the break above the pre-previous high has failed. However, the user has the option to turn this off. The information in these four rows shows the user how the market is moving currently and how it evolved before reaching the current price levels. Note: The calculation done by the indicator is to keep track of how the price is moving with respect to the last candle levels in real-time. This means if the price first goes above the previous high and then goes below the previous low, the indicator is equipped to display what happened in the most recent time. The snapshot below shows the option to turn on/off such updates in the bias summary table. Note: While the bias summary table is turned on, the user also has the option to turn off Prev and Prev rows, as shown in the snapshot below. 1.1.2 The 2nd to last row, called CL/CS(Consecutive Long/Short), shows whether consecutive (2+) breaks of high/low happened or not in one direction without taking out the previous candle's range in the opposite direction. When conditions are met, it will show the number of times the price has been pushed in one direction (in the above manner), followed by "L" for long and "S" for short, for each TF, for example, "4L". It gets updated in real-time for each push in the same direction. Furthermore, a good analogy of "4L" on an HTF is 4 consecutive Break of Structure (BOS) (in the same direction) on LTF, without a Change of Character (CHoCH). Another example would be Stacey Burke's 3 consecutive rises that can be mapped in the indicator, if the conditions are met for "3L" for a given TF. 1.1.3 The last row, FRC/FGC, stands for the first red/green candle. It shows whether the last candle of a TF has closed as green (i.e., close>open) after posting two red candles (i.e., close
Pine Script® indicator
by Harshb25
EMD Oscillator (Zeiierman)█ Overview The Empirical Mode Decomposition (EMD) Oscillator is an advanced indicator designed to analyze market trends and cycles with high precision. It breaks down complex price data into simpler parts called Intrinsic Mode Functions (IMFs), allowing traders to see underlying patterns and trends that aren’t visible with traditional indicators. The result is a dynamic oscillator that provides insights into overbought and oversold conditions, as well as trend direction and strength. This indicator is suitable for all types of traders, from beginners to advanced, looking to gain deeper insights into market behavior. █ How It Works The core of this indicator is the Empirical Mode Decomposition (EMD) process, a method typically used in signal processing and advanced scientific fields. It works by breaking down price data into various “layers,” each representing different frequencies in the market’s movement. Imagine peeling layers off an onion: each layer (or IMF) reveals a different aspect of the price action. ⚪ Data Decomposition (Sifting): The indicator “sifts” through historical price data to detect natural oscillations within it. Each oscillation (or IMF) highlights a unique rhythm in price behavior, from rapid fluctuations to broader, slower trends. ⚪ Adaptive Signal Reconstruction: The EMD Oscillator allows traders to select specific IMFs for a custom signal reconstruction. This reconstructed signal provides a composite view of market behavior, showing both short-term cycles and long-term trends based on which IMFs are included. ⚪ Normalization: To make the oscillator easy to interpret, the reconstructed signal is scaled between -1 and 1. This normalization lets traders quickly spot overbought and oversold conditions, as well as trend direction, without worrying about the raw magnitude of price changes. The indicator adapts to changing market conditions, making it effective for identifying real-time market cycles and potential turning points. █ Key Calculations: The Math Behind the EMD Oscillator The EMD Oscillator’s advanced nature lies in its high-level mathematical operations: ⚪ Intrinsic Mode Functions (IMFs) IMFs are extracted from the data and act as the building blocks of this indicator. Each IMF is a unique oscillation within the price data, similar to how a band might be divided into treble, mid, and bass frequencies. In the EMD Oscillator: Higher-Frequency IMFs: Represent short-term market “noise” and quick fluctuations. Lower-Frequency IMFs: Capture broader market trends, showing more stable and long-term patterns. ⚪ Sifting Process: The Heart of EMD The sifting process isolates each IMF by repeatedly separating and refining the data. Think of this as filtering water through finer and finer mesh sieves until only the clearest parts remain. Mathematically, it involves: Extrema Detection: Finding all peaks and troughs (local maxima and minima) in the data. Envelope Calculation: Smoothing these peaks and troughs into upper and lower envelopes using cubic spline interpolation (a method for creating smooth curves between data points). Mean Removal: Calculating the average between these envelopes and subtracting it from the data to isolate one IMF. This process repeats until the IMF criteria are met, resulting in a clean oscillation without trend influences. ⚪ Spline Interpolation The cubic spline interpolation is an advanced mathematical technique that allows smooth curves between points, which is essential for creating the upper and lower envelopes around each IMF. This interpolation solves a tridiagonal matrix (a specialized mathematical problem) to ensure that the envelopes align smoothly with the data’s natural oscillations. To give a relatable example: imagine drawing a smooth line that passes through each peak and trough of a mountain range on a map. Spline interpolation ensures that line is as smooth and close to reality as possible. Achieving this in Pine Script is technically demanding and demonstrates a high level of mathematical coding. ⚪ Amplitude Normalization To make the oscillator more readable, the final signal is scaled by its maximum amplitude. This amplitude normalization brings the oscillator into a range of -1 to 1, creating consistent signals regardless of price level or volatility. █ Comparison with Other Signal Processing Methods Unlike standard technical indicators that often rely on fixed parameters or pre-defined mathematical functions, the EMD adapts to the data itself, capturing natural cycles and irregularities in real-time. For example, if the market becomes more volatile, EMD adjusts automatically to reflect this without requiring parameter changes from the trader. In this way, it behaves more like a “smart” indicator, intuitively adapting to the market, unlike most traditional methods. EMD’s adaptive approach is akin to AI’s ability to learn from data, making it both resilient and robust in non-linear markets. This makes it a great alternative to methods that struggle in volatile environments, such as fixed-parameter oscillators or moving averages. █ How to Use Identify Market Cycles and Trends: Use the EMD Oscillator to spot market cycles that represent phases of buying or selling pressure. The smoothed version of the oscillator can help highlight broader trends, while the main oscillator reveals immediate cycles. Spot Overbought and Oversold Levels: When the oscillator approaches +1 or -1, it may indicate that the market is overbought or oversold, signaling potential entry or exit points. Confirm Divergences: If the price movement diverges from the oscillator's direction, it may indicate a potential reversal. For example, if prices make higher highs while the oscillator makes lower highs, it could be a sign of weakening trend strength. █ Settings Window Length (N): Defines the number of historical bars used for EMD analysis. A larger window captures more data but may slow down performance. Number of IMFs (M): Sets how many IMFs to extract. Higher values allow for a more detailed decomposition, isolating smaller cycles within the data. Amplitude Window (L): Controls the length of the window used for amplitude calculation, affecting the smoothness of the normalized oscillator. Extraction Range (IMF Start and End): Allows you to select which IMFs to include in the reconstructed signal. Starting with lower IMFs captures faster cycles, while ending with higher IMFs includes slower, trend-based components. Sifting Stopping Criterion (S-number): Sets how precisely each IMF should be refined. Higher values yield more accurate IMFs but take longer to compute. Max Sifting Iterations (num_siftings): Limits the number of sifting iterations for each IMF extraction, balancing between performance and accuracy. Source: The price data used for the analysis, such as close or open prices. This determines which price movements are decomposed by the indicator. ----------------- Disclaimer The information contained in my Scripts/Indicators/Ideas/Algos/Systems does not constitute financial advice or a solicitation to buy or sell any securities of any type. I will not accept liability for any loss or damage, including without limitation any loss of profit, which may arise directly or indirectly from the use of or reliance on such information. All investments involve risk, and the past performance of a security, industry, sector, market, financial product, trading strategy, backtest, or individual's trading does not guarantee future results or returns. Investors are fully responsible for any investment decisions they make. Such decisions should be based solely on an evaluation of their financial circumstances, investment objectives, risk tolerance, and liquidity needs. My Scripts/Indicators/Ideas/Algos/Systems are only for educational purposes!
Pine Script® indicator
by Zeiierman
8
Neural Network Synthesis: Trend and Valuation [QuantraSystems]Neural Network Synthesis - Trend and Valuation Introduction The Neural Network Synthesis (𝓝𝓝𝒮𝔂𝓷𝓽𝓱) indicator is an innovative technical analysis tool which leverages neural network concepts to synthesize market trend and valuation insights. This indicator uses a bespoke neural network model to process various technical indicator inputs, providing an improved view of market momentum and perceived value. Legend The main visual component of the 𝓝𝓝𝒮𝔂𝓷𝓽𝓱 indicator is the Neural Synthesis Line , which dynamically oscillates within the valuation chart, categorizing market conditions as both under or overvalued and trending up or down. The synthesis line coloring can be set to trend analysis or valuation modes , which can be reflected in the bar coloring. The sine wave valuation chart oscillates around a central, volatility normalized ‘fair value’ line, visually conveying the natural rhythm and cyclical nature of asset markets. The positioning of the sine wave in relation to the central line can help traders to visualize transitions from one market phase to another - such as from an undervalued phase to fair value or an overvalued phase. Case Study 1 The asset in question experiences a sharp, inefficient move upwards. Such movements suggest an overextension of price, and mean reversion is typically expected. Here, a short position was initiated, but only after the Neural Synthesis line confirmed a negative trend - to mitigate the risk of shorting into a continuing uptrend. Two take-profit levels were set: The midline or ‘fair value’ line. The lower boundary of the 𝓝𝓝𝒮𝔂𝓷𝓽𝓱 indicators valuation chart. Although mean-reversion trades are typically closed when price returns to the mean, under circumstances of extreme overextension price often overcorrects from an overbought condition to an oversold condition. Case Study 2 In the above study, the 𝓝𝓝𝒮𝔂𝓷𝓽𝓱 indicator is applied to the 1 Week Bitcoin chart in order to inform long term investment decisions. Accumulation Zones - Investors can choose to dollar cost average (DCA) into long term positions when the 𝓝𝓝𝒮𝔂𝓷𝓽𝓱 indicates undervaluation Distribution Zones - Conversely, when overvalued conditions are indicated, investors are able to incrementally sell holdings expecting the market peak to form around the distribution phase. Note - It is prudent to pay close attention to any change in trend conditions when the market is in an accumulation/distribution phase, as this can increase the likelihood of a full-cycle market peak forming. In summary, the 𝓝𝓝𝒮𝔂𝓷𝓽𝓱 indicator is also an effective tool for long term investing, especially for assets like Bitcoin which exhibit prolonged bull and bear cycles. Special Note It is prudent to note that because markets often undergo phases of extreme speculation, an asset's price can remain over or undervalued for long periods of time, defying mean-reversion expectations. In these scenarios it is important to use other forms of analysis in confluence, such as the trending component of the 𝓝𝓝𝒮𝔂𝓷𝓽𝓱 indicator to help inform trading decisions. A special feature of Quantra’s indicators is that they are probabilistically built - therefore they work well as confluence and can easily be stacked to increase signal accuracy. Example Settings As used above. Swing Trading Smooth Length = 150 Timeframe = 12h Long Term Investing Smooth Length = 30 Timeframe = 1W Methodology The 𝓝𝓝𝒮𝔂𝓷𝓽𝓱 indicator draws upon the foundational principles of Neural Networks, particularly the concept of using a network of ‘neurons’ (in this case, various technical indicators). It uses their outputs as features, preprocesses this input data, runs an activation function and in the following creates a dynamic output. The following features/inputs are used as ‘neurons’: Relative Strength Index (RSI) Moving Average Convergence-Divergence (MACD) Bollinger Bands Stochastic Momentum Average True Range (ATR) These base indicators were chosen for their diverse methodologies for capturing market momentum, volatility and trend strength - mirroring how neurons in a Neural Network capture and process varied aspects of the input data. Preprocessing: Each technical indicator’s output is normalized to remove bias. Normalization is a standard practice to preprocess data for Neural Networks, to scale input data and allow the model to train more effectively. Activation Function: The hyperbolic tangent function serves as the activation function for the neurons. In general, for complete neural networks, activation functions introduce non-linear properties to the models and enable them to learn complex patterns. The tanh() function specifically maps the inputs to a range between -1 and 1. Dynamic Smoothing: The composite signal is dynamically smoothed using the Arnaud Legoux Moving Average, which adjusts faster to recent price changes - enhancing the indicator's responsiveness. It mimics the learning rate in neural networks - in this case for the output in a single layer approach - which controls how much new information influences the model, or in this case, our output. Signal Processing: The signal line also undergoes processing to adapt to the selected assets volatility. This step ensures the indicator’s flexibility across assets which exhibit different behaviors - similar to how a Neural Network adjusts to various data distributions. Notes: While the indicator synthesizes complex market information using methods inspired by neural networks, it is important to note that it does not engage in predictive modeling through the use of backpropagation. Instead, it applies methodologies of neural networks for real-time market analysis that is both dynamic and adaptable to changing market conditions.
Pine Script® indicator
by QuantraSystems
4
Moon Phases + Daily, Weekly, Monthly, Quarterly & Yearly Breaks█ Moon Phases From LuxAlgo description. Trading moon phases has become quite popular among traders, believing that there exists a relationship between moon phases and market movements. This strategy is based on an estimate of moon phases with the possibility to use different methods to determine long/short positions based on moon phases. Note that we assume moon phases are perfectly periodic with a cycle of 29.530588853 days (which is not realistically the case), as such there exists a difference between the detected moon phases by the strategy and the ones you would see. This difference becomes less important when using higher timeframes. █ Daily, Weekly, Monthly, Quarterly & Yearly Breaks This indicator marks the start of the selected periods with a vertical line that help with identifying cycles. It allows to enable or disable independently the daily, weekly, monthly, quarterly and yearly session breaks. This script is based on LuxAlgo and kaushi / icostan scripts. Moon Phases Strategy Year/Quarter/Month/Week/Day breaks Month/week breaks
Pine Script® indicator
by Yatagarasu_
ETH Growth | AlchimistOfCrypto⚠️ DISCLAIMER: This indicator's source code is kept private as it represents a first-of-its-kind innovation in algorithmic cycle detection and visualization for Ethereum. The mathematical models and proprietary algorithms powering this indicator are the result of extensive research and development. 🌈 ETH Growth Rainbow – Unveiling Ethereum's Logarithmic Growth Fields 🌈 "The ETH Growth Rainbow, engineered through advanced logarithmic mathematics, visualizes the probabilistic distribution of Ethereum's price evolution within a multi-cycle growth paradigm. This indicator employs principles from logarithmic regression where coefficients p001, p002, and p003 create mathematical boundaries that define Ethereum's long-term value progression. Our implementation features algorithmically enhanced rainbow visualization derived from Fast Fourier Transform (FFT) spectral analysis, creating a dynamic representation of Ethereum's logarithmic growth with adaptive color gradients that highlight critical cycle-based phase transitions in the asset's monetary evolution." 📊 Professional Trading Application The ETH Growth Rainbow transcends traditional price prediction models with a sophisticated multi-band illumination system that reveals the underlying structure of Ethereum's monetary evolution. Scientifically calibrated across multiple 85-week cycles (detected through spectral analysis) and featuring seamless rainbow visualization, it enables investors to perceive Ethereum's position within its macro growth trajectory with unprecedented clarity. - Cycle Detection Methodology 🔬 The 85-week Ethereum cycle was discovered through sophisticated Fast Fourier Transform (FFT) analysis: - Logarithmic price returns extracted from historical Ethereum data - FFT decomposition identifies dominant frequency components in price movements - Signal amplitude analysis reveals the 85-week cycle as the most statistically significant periodicity - Adaptive frequency filtering validates cycle consistency across multiple market phases - Cycle duration rounded to nearest week for practical application - Visual Theming 🎨 Scientifically designed rainbow gradient optimized for cycle pattern recognition: - Violet-Blue: Lower value accumulation zones with highest mathematical growth potential - Green: Fair value equilibrium zone representing the regression mean - Yellow-Orange: Moderate overvaluation regions indicating potential resistance - Red: Statistical extreme zones indicating mathematical cycle peaks - Deep Red: New euphoria band (+6) capturing exceptional market extremes - Cycle Visualization 🔍 - Precise cycle boundaries demarcating Ethereum's fundamental cycle events - Adaptive band spacing based on mathematical cycle progression (p003 = 0.858) - Multiple sub-cycle markers revealing the probabilistic nature of Ethereum's trajectory - Initial cycle starting from 0.1639 (August 3, 2015) to preserve historical accuracy 🚀 How to Use 1. Identify Macro Position ⏰: Locate Ethereum's current price relative to regression bands 2. Understand Cycle Context 🎚️: Note position within the current 85-week cycle for time-based analysis 3. Assess Mathematical Value 🌈: Determine potential over/undervaluation based on band location 4. Adjust Investment Strategy 🔎: Modulate position sizing based on mathematical value assessment 5. Identify Cycle Phases ✅: Monitor band transitions to detect accumulation and distribution zones 6. Invest with Precision 🛡️: Utilize lower bands for strategic accumulation, upper bands for strategic reduction 7. Manage Risk Dynamically 🔐: Scale investment allocations based on mathematical cycle positioning #ethereum #ETH #cryptocurrency #tradingview #technicalanalysis #logarithmicregression #rainbowchart #cryptotrading #tradingstrategy #priceaction #cryptoinvesting #ethanalysis #tradingbands #cryptoresearch #FFTanalysis #cyclicalanalysis #ethinvestment #ethusd #buyandsell #accumulation #macroindicator #valueanalysis #priceprediction #ethgrowth #cryptosignals #cyclicpatterns #mathematicaltrading #AI #smartmoney #cryptowhales
Pine Script® indicator
by AlchimistOfCrypto
Bitcoin Logarithmic Regression BandsOverview This indicator displays logarithmic regression bands for Bitcoin. Logarithmic regression is a statistical method used to model data where growth slows down over time. I initially created these bands in 2019 using a spreadsheet, and later coded them in TradingView in 2021. Over time, the bands proved effective at capturing Bitcoin's bull market peaks and bear market lows. In 2024, I decided to share this indicator because I believe these logarithmic regression bands offer the best fit for the Bitcoin chart. How It Works The logarithmic regression lines are fitted to the Bitcoin (BTCUSD) chart using two key factors: the 'a' factor (slope) and the 'b' factor (intercept). The two lines in the upper and lower bands share the same 'a' factor, but I adjust the 'b' factor by 0.2 to more accurately capture the bull market peaks and bear market lows. The formula for logaritmic regression is 10^((a * ln) - b). How to Use the Logarithmic Regression Bands 1. Lower Band (Support Band): The two lines in the lower band create a potential support area for Bitcoin’s price. Historically, Bitcoin’s price has always found its lows within this band during past market cycles. When the price is within the lower band, it suggests that Bitcoin is undervalued and could be set for a rebound. 2. Upper Band (Resistance Band): The two lines in the upper band create a potential resistance area for Bitcoin’s price. Bitcoin has consistently reached its highs in this band during previous market cycles. If the price is within the upper band, it indicates that Bitcoin is overvalued, and a potential price correction may be imminent. Use Cases - Price Bottoming: Bitcoin tends to bottom out at the lower band before entering a prolonged bull market or a period of sideways movement. - Price Topping: In reverse, Bitcoin tends to top out at the upper band before entering a bear market phase. - Profitable Strategy: Buying at the lower band and selling at the upper band can be a profitable trading strategy, as these bands often indicate key price levels for Bitcoin’s market cycles.
Pine Script® indicator
by CryptoRiskAlert
1
TFPV — FULL Radial Kernel MA (Short/Long, Time Folding, Colored)TFPV is a pair of adaptive moving averages built with a radial kernel (Gaussian/Laplacian/Cauchy) on a joint metric of time, price, and volume. It can “fold” time along the market’s dominant cycle so that bars separated by entire cycles still contribute as if they were near each other—helpful for cyclical or range-bound markets. The short/long lines auto-color by regime and include cross alerts. What it does Radial-kernel averaging: Weights past bars by their distance from the current bar in a 3-axis space: Time (αₜ): linear distance or cycle-aware phase distance Price (αₚ): normalized by robust price scale Volume (αᵥ): normalized by (log) volume scale Time folding: Choose Linear (standard) or Circular using: Homodyne (Hilbert) dominant period, or ACF (autocorrelation) dominant period This compresses distances for bars that are one or more full cycles apart, improving smoothing without lagging trends. Adaptive scales: Price/volume bandwidths use Robust MAD, Stdev, or ATR. Optional Super Smoother center reduces noise before measuring distances. Visual regime coloring: Short above Long → teal (bullish). Short below Long → orange (bearish). Optional fill highlights the spread. How to read it Trend filter: Trade in the direction of the color (teal bullish, orange bearish). Crossovers: Short crossing above Long often marks early trend continuation after pullbacks; crossing below can warn of weakening momentum. Spread width: A widening gap suggests strengthening trend; a shrinking gap hints at consolidation or a possible regime change. Key settings Lengths Short/Long window: Lookback for each radial MA. Short reacts faster; Long stabilizes the regime. Kernel & Metric Kernel: Gaussian, Laplacian, or Cauchy (default). Cauchy is heavier-tailed (keeps more outliers), Gaussian is tighter. Axis weights (αₜ, αₚ, αᵥ): Importance of time/price/volume distances. Increase a weight to make that axis matter more. Ignore weights below: Hard cutoff for tiny kernel weights to speed up/clean contributions. Time Folding Topology: Linear (standard MA behavior) or Circular (Homodyne/ACF) (cycle-aware). Cycle floor/ceil: Bounds for the dominant period search. σₜ mode: Auto sets time bandwidth from the detected period (or length in Linear mode) × multiplier; Manual fixes σₜ in bars. Price/Volume Scaling Price scale: Robust MAD (outlier-resistant), Stdev, or ATR (trend-aware). σₚ/σᵥ multipliers: Bandwidths for price/volume axes. Larger values = looser matching (smoother, more lag). Use log(volume): Stabilizes volume’s scale across regimes; recommended. Kernel Center Price center: Raw (close) or Super Smoother to reduce noise before measuring price distance. Plotting Plot source: Show/hide the input source. Fill between lines: Visual emphasis of the short/long spread. Tips Start with defaults: Cauchy, Circular (Homodyne), Robust MAD, log-volume on. For choppy/cyclical symbols, Circular time folding often reduces false flips. If signals feel too twitchy, either increase Short/Long lengths or raise σₚ/σᵥ multipliers (looser kernel). For strong trends with regime shifts, try ATR price scaling.
Pine Script® indicator
by Cmo22
Fib Swing Counter [A@J]Fib Swing Counter — Trade the Rhythm of the Market This indicator automatically marks swing highs and lows with Fibonacci numbers (1, 1, 2, 3, 5, 8, 13, …), helping you track market structure, count price legs, and identify hidden order behind price movement. Core Features: Auto-detects pivots and labels them with the Fibonacci sequence. Alternates between highs and lows — no repeats, no noise. Custom reset time — start your count at the New York session open, a major news event, or your own strategic point. Clean and simple visual display, adaptable to your chart style. How Traders Use It: Liquidity cycles: Spot when price is expanding or contracting in Fibonacci-driven waves. Entry timing: Wait for setups to align with a key Fib count. Confluence with other tools: Combine with ICT concepts, SMT divergence, supply/demand blocks, or Fibonacci retracements. Session-based analysis: Restart the sequence everyMarket Open, Midnight, New York or London open to study price behavior from a fresh anchor point. Whether you're into smart money concepts, price action, or algorithmic patterns, this tool adds a rhythmic layer to your analysis — because markets move with sequence, not randomness.
Pine Script® indicator
by ArraisJesus
Altcoin Season Index - AdamThe "Altcoin Season Index" is a powerful tool for understanding market dynamics between Bitcoin and altcoins. This indicator helps traders identify whether the market is favoring Bitcoin or if it has shifted to favor altcoins. Understanding this can be crucial for making informed decisions about allocating your investments within the crypto market. Overview of the Altcoin Season Index The Altcoin Season Index calculates how well the top 10 altcoins are performing compared to Bitcoin over a given period. It helps traders determine if they are currently in an "Altcoin Season" or a "Bitcoin Season." The indicator gives a score from 0 to 100, representing the percentage of altcoins outperforming Bitcoin over a specific time window. When many altcoins are performing better than Bitcoin, it suggests a possible "Altcoin Season," whereas the opposite may indicate a period of Bitcoin dominance. Key Features: 1. Top 10 Altcoin Performance Comparison: The indicator evaluates the performance of the top 10 altcoins compared to Bitcoin. It provides a clear view of how well altcoins are doing relative to the market leader, Bitcoin. 2. Customizable Performance Period: The period of analysis is adjustable, allowing users to set a specific timeframe, typically in days, to evaluate the relative performance of altcoins versus Bitcoin. 3. Dynamic Replacement of Altcoins: The indicator includes a feature to replace the last coin in the list, ensuring that the data stays relevant as market conditions change. For example, when a new altcoin enters the top 10 in terms of market cap, the indicator can replace an older coin that is falling out of the top ranks. 4. Threshold Indicators: The indicator uses predefined thresholds to determine and visualize whether it is an "Altcoin Season" or a "Bitcoin Season": - A value above 75 indicates an Altcoin Season, suggesting that altcoins are outperforming Bitcoin. - A value below 25 suggests Bitcoin dominance, where Bitcoin is outperforming the majority of altcoins. How the Indicator Works: 1. Performance Calculation: The indicator calculates the percentage change in price for each of the top 10 altcoins and Bitcoin over a given number of days. The comparison is made by looking at how much each asset's price has changed over the specified period. 2. Altcoin Season Calculation: The indicator counts the number of altcoins that have outperformed Bitcoin during the given period. The result is then expressed as a percentage, known as the Altcoin Season Index. If 8 out of 10 altcoins are outperforming Bitcoin, the index will be 80%, signaling a strong altcoin season. 3. Visual Representation: The indicator is visualized on a separate panel within TradingView, showing the Altcoin Season Index over time. Additionally, thresholds are marked on the chart, and background colors are applied to provide visual cues: - Red Background: When the Altcoin Season Index is above 75, indicating a strong altcoin season. - Blue Background: When the Altcoin Season Index is below 25, indicating Bitcoin dominance. Practical Use: - Identify Market Cycles: Traders can use this indicator to identify when the market is moving into or out of an altcoin season. This can help traders decide whether to rotate capital into altcoins or Bitcoin. - Investment Strategy Adjustment: During altcoin seasons, altcoins tend to outperform Bitcoin. Traders might allocate more of their portfolio to promising altcoins. Conversely, during Bitcoin-dominant periods, shifting investments towards Bitcoin could provide more stability. - Support Technical Analysis: This indicator complements other forms of technical analysis by providing macro-level insights about market direction and which asset classes might be favored. Example Usage: Imagine that the Altcoin Season Index is currently at 80%. This means that 8 of the top 10 altcoins have performed better than Bitcoin over the selected period. This strong altcoin performance suggests that the market has entered an "Altcoin Season." A trader observing this might consider reallocating funds towards altcoins to capitalize on the positive momentum. Alternatively, if the index is at 20%, only 2 out of the top 10 altcoins are outperforming Bitcoin, indicating that Bitcoin is currently the stronger player. In this scenario, traders may choose to prioritize Bitcoin or maintain a more conservative portfolio allocation. Note: This indicator includes a feature to replace the bottom-ranked altcoin (typically a coin that falls out of the top 10) with a new altcoin when market conditions change. This ensures that the analysis remains relevant by focusing on the top-performing assets by market capitalization. Conclusion: The Altcoin Season Index is a helpful tool for understanding broader trends in the cryptocurrency market and making strategic investment decisions. By monitoring which assets are performing better, traders can adapt their strategies and make more informed choices, particularly during shifts in market sentiment. Please leave your feedback or contributions if there are any inaccuracies in my indicator. Thank you!
Pine Script® indicator
by Adam_Nguyen
4
GKD-C PA Adaptive Fisher Transform [Loxx]The Giga Kaleidoscope GKD-C PA Adaptive Fisher Transform is a confirmation module included in Loxx's "Giga Kaleidoscope Modularized Trading System." █ GKD-C PA Adaptive Fisher Transform Phase Accumulation Adaptive Fisher Transform is an adaptive Fisher Transform using a modified version of Ehlers Phase Accumulation Cycle Period. This version of Phase Accumulation Cylce Period accepts as inputs: 1) total number of cycles you wish to inject into the calculation, this works as a multiplier so the higher this number, the longer the period output; 2) filter is to change the alpha value of the final smother before returning the period output. What is the Phase Accumulation Cycle? The phase accumulation method of computing the dominant cycle is perhaps the easiest to comprehend. In this technique, we measure the phase at each sample by taking the arctangent of the ratio of the quadrature component to the in-phase component. A delta phase is generated by taking the difference of the phase between successive samples. At each sample we can then look backwards, adding up the delta phases.When the sum of the delta phases reaches 360 degrees, we must have passed through one full cycle, on average.The process is repeated for each new sample. The phase accumulation method of cycle measurement always uses one full cycle’s worth of historical data.This is both an advantage and a disadvantage.The advantage is the lag in obtaining the answer scales directly with the cycle period.That is, the measurement of a short cycle period has less lag than the measurement of a longer cycle period. However, the number of samples used in making the measurement means the averaging period is variable with cycle period. longer averaging reduces the noise level compared to the signal.Therefore, shorter cycle periods necessarily have a higher out- put signal-to-noise ratio. What is Fisher Transform? The Fisher Transform is a technical indicator created by John F. Ehlers that converts prices into a Gaussian normal distribution. The indicator highlights when prices have moved to an extreme, based on recent prices. This may help in spotting turning points in the price of an asset. It also helps show the trend and isolate the price waves within a trend. █ Giga Kaleidoscope Modularized Trading System Core components of an NNFX algorithmic trading strategy The NNFX algorithm is built on the principles of trend, momentum, and volatility. There are six core components in the NNFX trading algorithm: 1. Volatility - price volatility; e.g., Average True Range, True Range Double, Close-to-Close, etc. 2. Baseline - a moving average to identify price trend 3. Confirmation 1 - a technical indicator used to identify trends 4. Confirmation 2 - a technical indicator used to identify trends 5. Continuation - a technical indicator used to identify trends 6. Volatility/Volume - a technical indicator used to identify volatility/volume breakouts/breakdown 7. Exit - a technical indicator used to determine when a trend is exhausted 8. Metamorphosis - a technical indicator that produces a compound signal from the combination of other GKD indicators* *(not part of the NNFX algorithm) What is Volatility in the NNFX trading system? In the NNFX (No Nonsense Forex) trading system, ATR (Average True Range) is typically used to measure the volatility of an asset. It is used as a part of the system to help determine the appropriate stop loss and take profit levels for a trade. ATR is calculated by taking the average of the true range values over a specified period. True range is calculated as the maximum of the following values: -Current high minus the current low -Absolute value of the current high minus the previous close -Absolute value of the current low minus the previous close ATR is a dynamic indicator that changes with changes in volatility. As volatility increases, the value of ATR increases, and as volatility decreases, the value of ATR decreases. By using ATR in NNFX system, traders can adjust their stop loss and take profit levels according to the volatility of the asset being traded. This helps to ensure that the trade is given enough room to move, while also minimizing potential losses. Other types of volatility include True Range Double (TRD), Close-to-Close, and Garman-Klass What is a Baseline indicator? The baseline is essentially a moving average, and is used to determine the overall direction of the market. The baseline in the NNFX system is used to filter out trades that are not in line with the long-term trend of the market. The baseline is plotted on the chart along with other indicators, such as the Moving Average (MA), the Relative Strength Index (RSI), and the Average True Range (ATR). Trades are only taken when the price is in the same direction as the baseline. For example, if the baseline is sloping upwards, only long trades are taken, and if the baseline is sloping downwards, only short trades are taken. This approach helps to ensure that trades are in line with the overall trend of the market, and reduces the risk of entering trades that are likely to fail. By using a baseline in the NNFX system, traders can have a clear reference point for determining the overall trend of the market, and can make more informed trading decisions. The baseline helps to filter out noise and false signals, and ensures that trades are taken in the direction of the long-term trend. What is a Confirmation indicator? Confirmation indicators are technical indicators that are used to confirm the signals generated by primary indicators. Primary indicators are the core indicators used in the NNFX system, such as the Average True Range (ATR), the Moving Average (MA), and the Relative Strength Index (RSI). The purpose of the confirmation indicators is to reduce false signals and improve the accuracy of the trading system. They are designed to confirm the signals generated by the primary indicators by providing additional information about the strength and direction of the trend. Some examples of confirmation indicators that may be used in the NNFX system include the Bollinger Bands, the MACD (Moving Average Convergence Divergence), and the MACD Oscillator. These indicators can provide information about the volatility, momentum, and trend strength of the market, and can be used to confirm the signals generated by the primary indicators. In the NNFX system, confirmation indicators are used in combination with primary indicators and other filters to create a trading system that is robust and reliable. By using multiple indicators to confirm trading signals, the system aims to reduce the risk of false signals and improve the overall profitability of the trades. What is a Continuation indicator? In the NNFX (No Nonsense Forex) trading system, a continuation indicator is a technical indicator that is used to confirm a current trend and predict that the trend is likely to continue in the same direction. A continuation indicator is typically used in conjunction with other indicators in the system, such as a baseline indicator, to provide a comprehensive trading strategy. What is a Volatility/Volume indicator? Volume indicators, such as the On Balance Volume (OBV), the Chaikin Money Flow (CMF), or the Volume Price Trend (VPT), are used to measure the amount of buying and selling activity in a market. They are based on the trading volume of the market, and can provide information about the strength of the trend. In the NNFX system, volume indicators are used to confirm trading signals generated by the Moving Average and the Relative Strength Index. Volatility indicators include Average Direction Index, Waddah Attar, and Volatility Ratio. In the NNFX trading system, volatility is a proxy for volume and vice versa. By using volume indicators as confirmation tools, the NNFX trading system aims to reduce the risk of false signals and improve the overall profitability of trades. These indicators can provide additional information about the market that is not captured by the primary indicators, and can help traders to make more informed trading decisions. In addition, volume indicators can be used to identify potential changes in market trends and to confirm the strength of price movements. What is an Exit indicator? The exit indicator is used in conjunction with other indicators in the system, such as the Moving Average (MA), the Relative Strength Index (RSI), and the Average True Range (ATR), to provide a comprehensive trading strategy. The exit indicator in the NNFX system can be any technical indicator that is deemed effective at identifying optimal exit points. Examples of exit indicators that are commonly used include the Parabolic SAR, and the Average Directional Index (ADX). The purpose of the exit indicator is to identify when a trend is likely to reverse or when the market conditions have changed, signaling the need to exit a trade. By using an exit indicator, traders can manage their risk and prevent significant losses. In the NNFX system, the exit indicator is used in conjunction with a stop loss and a take profit order to maximize profits and minimize losses. The stop loss order is used to limit the amount of loss that can be incurred if the trade goes against the trader, while the take profit order is used to lock in profits when the trade is moving in the trader's favor. Overall, the use of an exit indicator in the NNFX trading system is an important component of a comprehensive trading strategy. It allows traders to manage their risk effectively and improve the profitability of their trades by exiting at the right time. What is an Metamorphosis indicator? The concept of a metamorphosis indicator involves the integration of two or more GKD indicators to generate a compound signal. This is achieved by evaluating the accuracy of each indicator and selecting the signal from the indicator with the highest accuracy. As an illustration, let's consider a scenario where we calculate the accuracy of 10 indicators and choose the signal from the indicator that demonstrates the highest accuracy. The resulting output from the metamorphosis indicator can then be utilized in a GKD-BT backtest by occupying a slot that aligns with the purpose of the metamorphosis indicator. The slot can be a GKD-B, GKD-C, or GKD-E slot, depending on the specific requirements and objectives of the indicator. This allows for seamless integration and utilization of the compound signal within the GKD-BT framework. How does Loxx's GKD (Giga Kaleidoscope Modularized Trading System) implement the NNFX algorithm outlined above? Loxx's GKD v2.0 system has five types of modules (indicators/strategies). These modules are: 1. GKD-BT - Backtesting module (Volatility, Number 1 in the NNFX algorithm) 2. GKD-B - Baseline module (Baseline and Volatility/Volume, Numbers 1 and 2 in the NNFX algorithm) 3. GKD-C - Confirmation 1/2 and Continuation module (Confirmation 1/2 and Continuation, Numbers 3, 4, and 5 in the NNFX algorithm) 4. GKD-V - Volatility/Volume module (Confirmation 1/2, Number 6 in the NNFX algorithm) 5. GKD-E - Exit module (Exit, Number 7 in the NNFX algorithm) 6. GKD-M - Metamorphosis module (Metamorphosis, Number 8 in the NNFX algorithm, but not part of the NNFX algorithm) (additional module types will added in future releases) Each module interacts with every module by passing data to A backtest module wherein the various components of the GKD system are combined to create a trading signal. That is, the Baseline indicator passes its data to Volatility/Volume. The Volatility/Volume indicator passes its values to the Confirmation 1 indicator. The Confirmation 1 indicator passes its values to the Confirmation 2 indicator. The Confirmation 2 indicator passes its values to the Continuation indicator. The Continuation indicator passes its values to the Exit indicator, and finally, the Exit indicator passes its values to the Backtest strategy. This chaining of indicators requires that each module conform to Loxx's GKD protocol, therefore allowing for the testing of every possible combination of technical indicators that make up the six components of the NNFX algorithm. What does the application of the GKD trading system look like? Example trading system: Backtest: Multi-Ticker CC Backtest Baseline: Hull Moving Average Volatility/Volume: Hurst Exponent Confirmation 1: Advance Trend Pressure as shown on the chart above Confirmation 2: uf2018 Continuation: Coppock Curve Exit: Rex Oscillator Metamorphosis: Baseline Optimizer Each GKD indicator is denoted with a module identifier of either: GKD-BT, GKD-B, GKD-C, GKD-V, GKD-M, or GKD-E. This allows traders to understand to which module each indicator belongs and where each indicator fits into the GKD system. ? Giga Kaleidoscope Modularized Trading System Signals Standard Entry 1. GKD-C Confirmation gives signal 2. Baseline agrees 3. Price inside Goldie Locks Zone Minimum 4. Price inside Goldie Locks Zone Maximum 5. Confirmation 2 agrees 6. Volatility/Volume agrees 1-Candle Standard Entry 1a. GKD-C Confirmation gives signal 2a. Baseline agrees 3a. Price inside Goldie Locks Zone Minimum 4a. Price inside Goldie Locks Zone Maximum Next Candle 1b. Price retraced 2b. Baseline agrees 3b. Confirmation 1 agrees 4b. Confirmation 2 agrees 5b. Volatility/Volume agrees Baseline Entry 1. GKD-B Baseline gives signal 2. Confirmation 1 agrees 3. Price inside Goldie Locks Zone Minimum 4. Price inside Goldie Locks Zone Maximum 5. Confirmation 2 agrees 6. Volatility/Volume agrees 7. Confirmation 1 signal was less than 'Maximum Allowable PSBC Bars Back' prior 1-Candle Baseline Entry 1a. GKD-B Baseline gives signal 2a. Confirmation 1 agrees 3a. Price inside Goldie Locks Zone Minimum 4a. Price inside Goldie Locks Zone Maximum 5a. Confirmation 1 signal was less than 'Maximum Allowable PSBC Bars Back' prior Next Candle 1b. Price retraced 2b. Baseline agrees 3b. Confirmation 1 agrees 4b. Confirmation 2 agrees 5b. Volatility/Volume agrees Volatility/Volume Entry 1. GKD-V Volatility/Volume gives signal 2. Confirmation 1 agrees 3. Price inside Goldie Locks Zone Minimum 4. Price inside Goldie Locks Zone Maximum 5. Confirmation 2 agrees 6. Baseline agrees 7. Confirmation 1 signal was less than 7 candles prior 1-Candle Volatility/Volume Entry 1a. GKD-V Volatility/Volume gives signal 2a. Confirmation 1 agrees 3a. Price inside Goldie Locks Zone Minimum 4a. Price inside Goldie Locks Zone Maximum 5a. Confirmation 1 signal was less than 'Maximum Allowable PSVVC Bars Back' prior Next Candle 1b. Price retraced 2b. Volatility/Volume agrees 3b. Confirmation 1 agrees 4b. Confirmation 2 agrees 5b. Baseline agrees Confirmation 2 Entry 1. GKD-C Confirmation 2 gives signal 2. Confirmation 1 agrees 3. Price inside Goldie Locks Zone Minimum 4. Price inside Goldie Locks Zone Maximum 5. Volatility/Volume agrees 6. Baseline agrees 7. Confirmation 1 signal was less than 7 candles prior 1-Candle Confirmation 2 Entry 1a. GKD-C Confirmation 2 gives signal 2a. Confirmation 1 agrees 3a. Price inside Goldie Locks Zone Minimum 4a. Price inside Goldie Locks Zone Maximum 5a. Confirmation 1 signal was less than 'Maximum Allowable PSC2C Bars Back' prior Next Candle 1b. Price retraced 2b. Confirmation 2 agrees 3b. Confirmation 1 agrees 4b. Volatility/Volume agrees 5b. Baseline agrees PullBack Entry 1a. GKD-B Baseline gives signal 2a. Confirmation 1 agrees 3a. Price is beyond 1.0x Volatility of Baseline Next Candle 1b. Price inside Goldie Locks Zone Minimum 2b. Price inside Goldie Locks Zone Maximum 3b. Confirmation 1 agrees 4b. Confirmation 2 agrees 5b. Volatility/Volume agrees Continuation Entry 1. Standard Entry, 1-Candle Standard Entry, Baseline Entry, 1-Candle Baseline Entry, Volatility/Volume Entry, 1-Candle Volatility/Volume Entry, Confirmation 2 Entry, 1-Candle Confirmation 2 Entry, or Pullback entry triggered previously 2. Baseline hasn't crossed since entry signal trigger 4. Confirmation 1 agrees 5. Baseline agrees 6. Confirmation 2 agrees
Pine Script® indicator
by loxx
APA-Adaptive, Ehlers Early Onset Trend [Loxx]APA-Adaptive, Ehlers Early Onset Trend is Ehlers Early Onset Trend but with Autocorrelation Periodogram Algorithm dominant cycle period input. What is Ehlers Early Onset Trend? The Onset Trend Detector study is a trend analyzing technical indicator developed by John F. Ehlers , based on a non-linear quotient transform. Two of Mr. Ehlers' previous studies, the Super Smoother Filter and the Roofing Filter, were used and expanded to create this new complex technical indicator. Being a trend-following analysis technique, its main purpose is to address the problem of lag that is common among moving average type indicators. The Onset Trend Detector first applies the EhlersRoofingFilter to the input data in order to eliminate cyclic components with periods longer than, for example, 100 bars (default value, customizable via input parameters) as those are considered spectral dilation. Filtered data is then subjected to re-filtering by the Super Smoother Filter so that the noise (cyclic components with low length) is reduced to minimum. The period of 10 bars is a default maximum value for a wave cycle to be considered noise; it can be customized via input parameters as well. Once the data is cleared of both noise and spectral dilation, the filter processes it with the automatic gain control algorithm which is widely used in digital signal processing. This algorithm registers the most recent peak value and normalizes it; the normalized value slowly decays until the next peak swing. The ratio of previously filtered value to the corresponding peak value is then quotiently transformed to provide the resulting oscillator. The quotient transform is controlled by the K coefficient: its allowed values are in the range from -1 to +1. K values close to 1 leave the ratio almost untouched, those close to -1 will translate it to around the additive inverse, and those close to zero will collapse small values of the ratio while keeping the higher values high. Indicator values around 1 signify uptrend and those around -1, downtrend. What is an adaptive cycle, and what is Ehlers Autocorrelation Periodogram Algorithm? From his Ehlers' book Cycle Analytics for Traders Advanced Technical Trading Concepts by John F. Ehlers , 2013, page 135: "Adaptive filters can have several different meanings. For example, Perry Kaufman’s adaptive moving average ( KAMA ) and Tushar Chande’s variable index dynamic average ( VIDYA ) adapt to changes in volatility . By definition, these filters are reactive to price changes, and therefore they close the barn door after the horse is gone.The adaptive filters discussed in this chapter are the familiar Stochastic , relative strength index ( RSI ), commodity channel index ( CCI ), and band-pass filter.The key parameter in each case is the look-back period used to calculate the indicator. This look-back period is commonly a fixed value. However, since the measured cycle period is changing, it makes sense to adapt these indicators to the measured cycle period. When tradable market cycles are observed, they tend to persist for a short while.Therefore, by tuning the indicators to the measure cycle period they are optimized for current conditions and can even have predictive characteristics. The dominant cycle period is measured using the Autocorrelation Periodogram Algorithm. That dominant cycle dynamically sets the look-back period for the indicators. I employ my own streamlined computation for the indicators that provide smoother and easier to interpret outputs than traditional methods. Further, the indicator codes have been modified to remove the effects of spectral dilation.This basically creates a whole new set of indicators for your trading arsenal."
Pine Script® indicator
by loxx
1
Adaptive, Double Jurik Filter Moving Average (AJFMA) [Loxx]Adaptive, Double Jurik Filter Moving Average (AJFMA) is moving average like Jurik Moving Average but with the addition of double smoothing and adaptive length (Autocorrelation Periodogram Algorithm) and power/volatility {Juirk Volty) inputs to further reduce noise and identify trends. What is Jurik Volty? One of the lesser known qualities of Juirk smoothing is that the Jurik smoothing process is adaptive. "Jurik Volty" (a sort of market volatility ) is what makes Jurik smoothing adaptive. The Jurik Volty calculation can be used as both a standalone indicator and to smooth other indicators that you wish to make adaptive. What is the Jurik Moving Average? Have you noticed how moving averages add some lag (delay) to your signals? ... especially when price gaps up or down in a big move, and you are waiting for your moving average to catch up? Wait no more! JMA eliminates this problem forever and gives you the best of both worlds: low lag and smooth lines. Ideally, you would like a filtered signal to be both smooth and lag-free. Lag causes delays in your trades, and increasing lag in your indicators typically result in lower profits. In other words, late comers get what's left on the table after the feast has already begun. That's why investors, banks and institutions worldwide ask for the Jurik Research Moving Average ( JMA ). You may apply it just as you would any other popular moving average. However, JMA's improved timing and smoothness will astound you. What is adaptive Jurik volatility? One of the lesser known qualities of Juirk smoothing is that the Jurik smoothing process is adaptive. "Jurik Volty" (a sort of market volatility ) is what makes Jurik smoothing adaptive. The Jurik Volty calculation can be used as both a standalone indicator and to smooth other indicators that you wish to make adaptive. What is an adaptive cycle, and what is Ehlers Autocorrelation Periodogram Algorithm? From his Ehlers' book Cycle Analytics for Traders Advanced Technical Trading Concepts by John F. Ehlers , 2013, page 135: "Adaptive filters can have several different meanings. For example, Perry Kaufman’s adaptive moving average ( KAMA ) and Tushar Chande’s variable index dynamic average ( VIDYA ) adapt to changes in volatility . By definition, these filters are reactive to price changes, and therefore they close the barn door after the horse is gone.The adaptive filters discussed in this chapter are the familiar Stochastic , relative strength index ( RSI ), commodity channel index ( CCI ), and band-pass filter.The key parameter in each case is the look-back period used to calculate the indicator. This look-back period is commonly a fixed value. However, since the measured cycle period is changing, it makes sense to adapt these indicators to the measured cycle period. When tradable market cycles are observed, they tend to persist for a short while.Therefore, by tuning the indicators to the measure cycle period they are optimized for current conditions and can even have predictive characteristics. The dominant cycle period is measured using the Autocorrelation Periodogram Algorithm. That dominant cycle dynamically sets the look-back period for the indicators. I employ my own streamlined computation for the indicators that provide smoother and easier to interpret outputs than traditional methods. Further, the indicator codes have been modified to remove the effects of spectral dilation.This basically creates a whole new set of indicators for your trading arsenal." Included - Double calculation of AJFMA for even smoother results
Pine Script® indicator
by loxx
6
Adaptive Look-back/Volatility Phase Change Index on Jurik [Loxx]Adaptive Look-back, Adaptive Volatility Phase Change Index on Jurik is a Phase Change Index but with adaptive length and volatility inputs to reduce phase change noise and better identify trends. This is an invese indicator which means that small values on the oscillator indicate bullish sentiment and higher values on the oscillator indicate bearish sentiment What is the Phase Change Index? Based on the M.H. Pee's TASC article "Phase Change Index". Prices at any time can be up, down, or unchanged. A period where market prices remain relatively unchanged is referred to as a consolidation. A period that witnesses relatively higher prices is referred to as an uptrend, while a period of relatively lower prices is called a downtrend. The Phase Change Index (PCI) is an indicator designed specifically to detect changes in market phases. This indicator is made as he describes it with one deviation: if we follow his formula to the letter then the "trend" is inverted to the actual market trend. Because of that an option to display inverted (and more logical) values is added. What is the Jurik Moving Average? Have you noticed how moving averages add some lag (delay) to your signals? ... especially when price gaps up or down in a big move, and you are waiting for your moving average to catch up? Wait no more! JMA eliminates this problem forever and gives you the best of both worlds: low lag and smooth lines. Ideally, you would like a filtered signal to be both smooth and lag-free. Lag causes delays in your trades, and increasing lag in your indicators typically result in lower profits. In other words, late comers get what's left on the table after the feast has already begun. That's why investors, banks and institutions worldwide ask for the Jurik Research Moving Average ( JMA ). You may apply it just as you would any other popular moving average. However, JMA's improved timing and smoothness will astound you. What is adaptive Jurik volatility One of the lesser known qualities of Juirk smoothing is that the Jurik smoothing process is adaptive. "Jurik Volty" (a sort of market volatility ) is what makes Jurik smoothing adaptive. The Jurik Volty calculation can be used as both a standalone indicator and to smooth other indicators that you wish to make adaptive. What is an adaptive cycle, and what is Ehlers Autocorrelation Periodogram Algorithm? From his Ehlers' book Cycle Analytics for Traders Advanced Technical Trading Concepts by John F. Ehlers, 2013, page 135: "Adaptive filters can have several different meanings. For example, Perry Kaufman’s adaptive moving average (KAMA) and Tushar Chande’s variable index dynamic average (VIDYA) adapt to changes in volatility. By definition, these filters are reactive to price changes, and therefore they close the barn door after the horse is gone.The adaptive filters discussed in this chapter are the familiar Stochastic, relative strength index (RSI), commodity channel index (CCI), and band-pass filter.The key parameter in each case is the look-back period used to calculate the indicator. This look-back period is commonly a fixed value. However, since the measured cycle period is changing, it makes sense to adapt these indicators to the measured cycle period. When tradable market cycles are observed, they tend to persist for a short while.Therefore, by tuning the indicators to the measure cycle period they are optimized for current conditions and can even have predictive characteristics. The dominant cycle period is measured using the Autocorrelation Periodogram Algorithm. That dominant cycle dynamically sets the look-back period for the indicators. I employ my own streamlined computation for the indicators that provide smoother and easier to interpret outputs than traditional methods. Further, the indicator codes have been modified to remove the effects of spectral dilation.This basically creates a whole new set of indicators for your trading arsenal." Included -Your choice of length input calculation, either fixed or adaptive cycle -Invert the signal to match the trend -Bar coloring to paint the trend Happy trading!
Pine Script® indicator
by loxx
1
Bitcoin Power Law [LuxAlgo]The Bitcoin Power Law tool is a representation of Bitcoin prices first proposed by Giovanni Santostasi, Ph.D. It plots BTCUSD daily closes on a log10-log10 scale, and fits a linear regression channel to the data. This channel helps traders visualise when the price is historically in a zone prone to tops or located within a discounted zone subject to future growth. 🔶 USAGE Giovanni Santostasi, Ph.D. originated the Bitcoin Power-Law Theory; this implementation places it directly on a TradingView chart. The white line shows the daily closing price, while the cyan line is the best-fit regression. A channel is constructed from the linear fit root mean squared error (RMSE), we can observe how price has repeatedly oscillated between each channel areas through every bull-bear cycle. Excursions into the upper channel area can be followed by price surges and finishing on a top, whereas price touching the lower channel area coincides with a cycle low. Users can change the channel areas multipliers, helping capture moves more precisely depending on the intended usage. This tool only works on the daily BTCUSD chart. Ticker and timeframe must match exactly for the calculations to remain valid. 🔹 Linear Scale Users can toggle on a linear scale for the time axis, in order to obtain a higher resolution of the price, (this will affect the linear regression channel fit, making it look poorer). 🔶 DETAILS One of the advantages of the Power Law Theory proposed by Giovanni Santostasi is its ability to explain multiple behaviors of Bitcoin. We describe some key points below. 🔹 Power-Law Overview A power law has the form y = A·xⁿ , and Bitcoin’s key variables follow this pattern across many orders of magnitude. Empirically, price rises roughly with t⁶, hash-rate with t¹² and the number of active addresses with t³. When we plot these on log-log axes they appear as straight lines, revealing a scale-invariant system whose behaviour repeats proportionally as it grows. 🔹 Feedback-Loop Dynamics Growth begins with new users, whose presence pushes the price higher via a Metcalfe-style square-law. A richer price pool funds more mining hardware; the Difficulty Adjustment immediately raises the hash-rate requirement, keeping profit margins razor-thin. A higher hash rate secures the network, which in turn attracts the next wave of users. Because risk and Difficulty act as braking forces, user adoption advances as a power of three in time rather than an unchecked S-curve. This circular causality repeats without end, producing the familiar boom-and-bust cadence around the long-term power-law channel. 🔹 Scale Invariance & Predictions Scale invariance means that enlarging the timeline in log-log space leaves the trajectory unchanged. The same geometric proportions that described the first dollar of value can therefore extend to a projected million-dollar bitcoin, provided no catastrophic break occurs. Institutional ETF inflows supply fresh capital but do not bend the underlying slope; only a persistent deviation from the line would falsify the current model. 🔹 Implications The theory assigns scarcity no direct role; iterative feedback and the Difficulty Adjustment are sufficient to govern Bitcoin’s expansion. Long-term valuation should focus on position within the power-law channel, while bubbles—sharp departures above trend that later revert—are expected punctuations of an otherwise steady climb. Beyond about 2040, disruptive technological shifts could alter the parameters, but for the next order of magnitude the present slope remains the simplest, most robust guide. Bitcoin behaves less like a traditional asset and more like a self-organising digital organism whose value, security, and adoption co-evolve according to immutable power-law rules. 🔶 SETTINGS 🔹 General Start Calculation: Determine the start date used by the calculation, with any prior prices being ignored. (default - 15 Jul 2010) Use Linear Scale for X-Axis: Convert the horizontal axis from log(time) to linear calendar time 🔹 Linear Regression Show Regression Line: Enable/disable the central power-law trend line Regression Line Color: Choose the colour of the regression line Mult 1: Toggle line & fill, set multiplier (default +1), pick line colour and area fill colour Mult 2: Toggle line & fill, set multiplier (default +0.5), pick line colour and area fill colour Mult 3: Toggle line & fill, set multiplier (default -0.5), pick line colour and area fill colour Mult 4: Toggle line & fill, set multiplier (default -1), pick line colour and area fill colour 🔹 Style Price Line Color: Select the colour of the BTC price plot Auto Color: Automatically choose the best contrast colour for the price line Price Line Width: Set the thickness of the price line (1 – 5 px) Show Halvings: Enable/disable dotted vertical lines at each Bitcoin halving Halvings Color: Choose the colour of the halving lines
Pine Script® indicator
by LuxAlgo
4
Global M2 YoY % Increase signalThe script produces a signal each time the global M2 increases more than 2.5%. This usually coincides with bitcoin prices pumps, except when it is late in the business cycle or the bitcoin price / halving cycle. It leverages dylanleclair Global M2 YoY % change, with several modifications: adding a 10 week lead at the YoY Change plot for better visibility, so that the bitcoin pump moreless coincides with the YoY change. signal increases > 2.5 in Global M2 at the point at which they occur with a green triangle up.
Pine Script® indicator
by UnderstandingBitcoinPrice
1