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Quantitative Easing and Tightening PeriodsThis indicator visually highlights historical and current U.S. Federal Reserve monetary policy regimes on any chart: • Green transparent background: Quantitative Easing (QE) periods – when the Fed is expanding its balance sheet (money printer active). • Red transparent background: Quantitative Tightening (QT) periods – when the Fed is shrinking its balance sheet. Includes all major cycles: - QE1 (2008–2010), QE2 (2010–2011), QE3 (2012–2014), COVID QE (2020–2022) - QT1 (2017–2019), QT2 (2022–Dec 1, 2025) - New QE phase starting Dec 8, 2025 – marked as ongoing Ideal for macro traders, helping to quickly identify liquidity environments that often influence risk assets, bonds, and the dollar. Overlay-friendly with high transparency – works on any timeframe and symbol.
Pine Script® indicator
by Crypto-KDuB
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
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
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® indicatorPaid script
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
2
WJ | Vegas Channels OnlyOverview The Vegas Channels is a clean, optimized indicator based on the classic Vegas Tunnel trading theory. It utilizes three sets of Exponential Moving Average (EMA) pairs to create "tunnels" that help traders identify trend direction, dynamic support/resistance levels, and potential trend reversals. This version is written in Pine Script v6, ensuring the best performance and compatibility with the latest TradingView features. How it Works The indicator plots three distinct tunnels, each representing a different trend horizon: V1 Tunnel (144 / 169 EMAs): The "Fast" tunnel. It represents short-to-medium-term momentum. Traders often look for price action around this tunnel for entry signals in a trending market. V2 Tunnel (288 / 338 EMAs): The "Medium" tunnel. It acts as a significant level of support or resistance. V3 Tunnel (576 / 676 EMAs): The "Slow" tunnel. This represents the long-term cycle and serves as the ultimate trend filter. Key Trading Strategies Trend Identification: * Bullish: Price is above the tunnels, and tunnels are stacked in order (V1 > V2 > V3). Bearish: Price is below the tunnels, and tunnels are stacked in order (V3 > V2 > V1). Support & Resistance: During a strong trend, price pullbacks often find "value" within these tunnels. A bounce off the V1 or V2 tunnel is a classic trend-following entry. Trend Reversal: A crossover between the V1 tunnel and the V3 tunnel often signals a major shift in the market cycle. Features Fully Customizable: Easily adjust the EMA lengths for each tunnel to suit different assets (Crypto, FX, or Stocks). Visual Clarity: Distinct colors for each tunnel with adjustable opacity to keep your charts clean and readable. Modern Code: Optimized using Pine Script v6 for faster loading and calculation. Disclaimer This indicator is for educational purposes only and does not constitute financial advice. Always use proper risk management and combine this tool with other indicators (like RSI or Volume) for better confirmation.
Pine Script® indicator
by wjwang
Skylark Digital Assets Monthly Financial Liquidity IndexThe Monthly Financial Liquidity Proxy (FLP) is a standardized, oscillator-style measure of broad financial conditions. Seasons 2.0 is the public-facing framework that translates the FLP into four regime “seasons” to help describe where liquidity sits within a recurring cycle. What “Seasons 2.0” does Converts the monthly FLP into a clear regime map (Winter / Spring / Summer / Fall). Uses explicit thresholds + persistence rules to reduce noise and avoid one-month regime “blips.” Designed for macro framing and cycle context (not a single-indicator trading system).
Pine Script® indicator
by Skylark_Digital_Assets
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
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
Moon+Lunar Cycle Vertical Delineation & Projection Automatically highlights the exact candle in which Moonphase shifts occur. Optionally including shifts within the Microphases of the total Lunar Cycle. This allow traders to pre-emptively identify time-based points of volatility, focusing on mean-reversion; further simplified via the use of projections. Projections are calculated via candle count, values displayed in "Debug"; these are useful in understanding the function & underlying mechanics.
Pine Script® indicator
by Ergotsalad
CCI with Signals & Divergence [AIBitcoinTrend]👽 CCI with Signals & Divergence (AIBitcoinTrend) The Hilbert Adaptive CCI with Signals & Divergence takes the traditional Commodity Channel Index (CCI) to the next level by dynamically adjusting its calculation period based on real-time market cycles using Hilbert Transform Cycle Detection. This makes it far superior to standard CCI, as it adapts to fast-moving trends and slow consolidations, filtering noise and improving signal accuracy. Additionally, the indicator includes real-time divergence detection and an ATR-based trailing stop system, helping traders identify potential reversals and manage risk effectively. 👽 What Makes the Hilbert Adaptive CCI Unique? Unlike the traditional CCI, which uses a fixed-length lookback period, this version automatically adjusts its lookback period using Hilbert Transform to detect the dominant cycle in the market. ✅ Hilbert Transform Adaptive Lookback – Dynamically detects cycle length to adjust CCI sensitivity. ✅ Real-Time Divergence Detection – Instantly identifies bullish and bearish divergences for early reversal signals. ✅ Implement Crossover/Crossunder signals tied to ATR-based trailing stops for risk management 👽 The Math Behind the Indicator 👾 Hilbert Transform Cycle Detection The Hilbert Transform estimates the dominant market cycle length based on the frequency of price oscillations. It is computed using the in-phase and quadrature components of the price series: tp = (high + low + close) / 3 smooth = (tp + 2 * tp + 2 * tp + tp ) / 6 detrender = smooth - smooth quadrature = detrender - detrender inPhase = detrender + quadrature outPhase = quadrature - inPhase instPeriod = 0.0 deltaPhase = math.abs(inPhase - inPhase ) + math.abs(outPhase - outPhase ) instPeriod := nz(3.25 / deltaPhase, instPeriod ) dominantCycle = int(math.min(math.max(instPeriod, cciMinPeriod), 500)) Where: In-Phase & Out-Phase Components are derived from a detrended version of the price series. Instantaneous Frequency measures the rate of cycle change, allowing the CCI period to adjust dynamically. The result is bounded within a user-defined min/max range, ensuring stability. 👽 How Traders Can Use This Indicator 👾 Divergence Trading Strategy Bullish Divergence Setup: Price makes a lower low, while CCI forms a higher low. Buy signal is confirmed when CCI shows upward momentum. Bearish Divergence Setup: Price makes a higher high, while CCI forms a lower high. Sell signal is confirmed when CCI shows downward momentum. 👾 Trailing Stop & Signal-Based Trading Bullish Setup: ✅ CCI crosses above -100 → Buy signal. ✅ A bullish trailing stop is placed at Low - (ATR × Multiplier). ✅ Exit if the price crosses below the stop. Bearish Setup: ✅ CCI crosses below 100 → Sell signal. ✅ A bearish trailing stop is placed at High + (ATR × Multiplier). ✅ Exit if the price crosses above the stop. 👽 Why It’s Useful for Traders Hilbert Adaptive Period Calculation – No more fixed-length periods; the indicator dynamically adapts to market conditions. Real-Time Divergence Alerts – Helps traders anticipate market reversals before they occur. ATR-Based Risk Management – Stops automatically adjust based on volatility. Works Across Multiple Markets & Timeframes – Ideal for stocks, forex, crypto, and futures. 👽 Indicator Settings Min & Max CCI Period – Defines the adaptive range for Hilbert-based lookback. Smoothing Factor – Controls the degree of smoothing applied to CCI. Enable Divergence Analysis – Toggles real-time divergence detection. Lookback Period – Defines the number of bars for detecting pivot points. Enable Crosses Signals – Turns on CCI crossover-based trade signals. ATR Multiplier – Adjusts trailing stop sensitivity. Disclaimer: This indicator is designed for educational purposes and does not constitute financial advice. Please consult a qualified financial advisor before making investment decisions.
Pine Script® indicator
by aibitcointrend
1
AHR999X IndexAHR999X Index - A Tool to Watch BITSTAMP:BTCUSD Bitcoin Tops The AHR999X Index is designed as an extension of the well-known AHR999 Index, specifically to help identify Bitcoin's market tops. This index combines two critical components: 200-Day Fixed Investment Cost: The average cost if you invested a fixed amount into Bitcoin every day over the last 200 days (using a geometric mean). Growth Estimate: A price estimate derived from a logarithmic regression model based on Bitcoin's age. The formula for AHR999X is: AHR999X = (Bitcoin Price ÷ 200-Day Fixed Investment Cost) × (Bitcoin Price ÷ Growth Estimate) × 3 How to Interpret AHR999X Above 8: Accumulation Zone – Bitcoin is historically undervalued. Between 0.45 and 8: Neutral Zone – Bitcoin is within a reasonable price range. Below 0.45: Exit Zone – Historically signals market tops and high-risk areas. A Cycle Observation One important point to note: The bottom value of AHR999X increases with every Bitcoin market cycle. This reflects Bitcoin's long-term price appreciation and diminishing volatility over time.
Pine Script® indicator
by jiyo1014
1
Altcoins vs BTC Market Cap HeatmapAltcoins vs BTC Market Cap Heatmap "Ground control to major Tom" 🌙 👨‍🚀 🚀 This indicator provides a visual heatmap for tracking the relationship between the market cap of altcoins (TOTAL3) and Bitcoin (BTC). The primary goal is to identify potential market cycle tops and bottoms by analyzing how the TOTAL3 market cap (all cryptocurrencies excluding Bitcoin and Ethereum) compares to Bitcoin’s market cap. Key Features: • Market Cap Ratio: Plots the ratio of TOTAL3 to BTC market caps to give a clear visual representation of altcoin strength versus Bitcoin. • Heatmap: Colors the background red when altcoins are overheating (TOTAL3 market cap equals or exceeds BTC) and blue when altcoins are cooling (TOTAL3 market cap is half or less than BTC). • Threshold Levels: Includes horizontal lines at 1 (Overheated), 0.75 (Median), and 0.5 (Cooling) for easy reference. • Alerts: Set alert conditions for when the ratio crosses key levels (1.0, 0.75, and 0.5), enabling timely notifications for potential market shifts. How It Works: • Overheated (Ratio ≥ 1): Indicates that the altcoin market cap is on par or larger than Bitcoin's, which could signal a top in the cycle. • Cooling (Ratio < 0.5): Suggests that the altcoin market cap is half or less than Bitcoin's, potentially signaling a market bottom or cooling phase. • Median (Ratio ≈ 0.75): A midpoint that provides insight into the market's neutral zone. Use this tool to monitor market extremes and adjust your strategy accordingly when the altcoin market enters overheated or cooling phases.
Pine Script® indicator
by KevinSvenson_
9
SeasonsThis code represents a seasonal indicator that has a number of unique functions to help traders better understand the market and make informed decisions. Let's take a closer look at each of them: 1. **Chart background shading for each season:** This function allows you to visually see seasonal changes in the market. You'll be able to easily track how the market changes in different seasons, thanks to the color labeling: blue for winter, green for summer, orange for autumn, and yellow for spring. 2. **Vertical markings for each month:** Additional markers on the chart help you orient yourself in time and better understand price dynamics throughout the year. This is especially useful when analyzing seasonal changes and identifying market cyclicality. 3. **Halving timers:** Connecting halving timers on the chart allows you to track important events, such as the reduction of bitcoin mining rewards. Knowing the timing of halving can be a key moment for decision-making and can affect asset prices. These functions help traders better analyze the market, identify trends and cyclicality, and optimize their trading strategy. Use this indicator in your trading practice to unleash its full potential and reach new heights in your trading career. Don't miss the opportunity to improve your results - apply the seasonal indicator today! The seasonal indicator is a powerful tool for traders, helping them analyze the market and make informed decisions based on seasonal and cyclical changes. Here are a few reasons why using this indicator can be advantageous: 1. **Identifying seasonal trends:** The seasonal indicator helps identify seasonal trends in the market, such as changes in activity during different seasons or months. For example, some markets may be more volatile or predictable at certain times of the year, and knowing these trends can help in making decisions about entering or exiting positions. 2. **Optimizing trading strategy:** Understanding seasonal changes in the market allows traders to optimize their trading strategy based on the time of year. For example, they may adjust their risk management approaches or choose specific types of trades according to the current season. 3. **Predicting market cyclicality:** The seasonal indicator can also help in predicting market cyclicality and identifying recurring price movement patterns. This enables traders to build their strategies based on past market behavior within specific time intervals. How to use the seasonal indicator: 1. **Study seasonal changes:** Use the indicator to analyze how the market changes throughout the year. Pay attention to changes in volatility, trading volumes, and price directions depending on the season. 2. **Optimize trading strategy:** Use the data obtained to optimize your trading strategy. Consider entering or exiting positions within specific time intervals to account for seasonal factors. 3. **Predict cyclicality:** Analyze past market behavior using the seasonal indicator to identify cyclicality and recurring patterns. This will help you make more informed decisions based on expected price movements in the future. Ultimately, using the seasonal indicator allows traders to better understand the market, adapt their strategies, and make more informed decisions based on seasonal and cyclical changes. All elements on the chart of a particular color will be attributed to the corresponding season. For example, trend lines or levels marked in blue will be associated with winter. ______________________________________________________ Winter Explanation of price movement during the winter season: 1. Number 1 and the blue line denote the maximum price of Bitcoin. Note that they always form at the peaks, which is consistent. 2. Number 2 and the blue line represent the minimum price specifically during the winter period. This is indeed the minimum price and the bottom point in the cycle. 3. Number 3 and the blue line indicate a local maximum after the breakthrough, after which the price starts to rise towards line number 1, which acts as global resistance. 4. Number 4 denotes the last winter cycle before the breakthrough of the global maximum. It should be noted that in 2017, the resistance was not broken immediately - first in spring, and then at the beginning of 2018, the maximum was set, and the asset growth occurred in winter. Additionally, it's worth noting that numbers 1 form the maximum, numbers 2 form the minimum, and since the trend is descending, I have marked its line in blue. ______________________________________________________ Summer Now let's consider the price behavior chart for the summer. To make the situation clearer, I've left a descending trend in blue on the graph. I reiterate that the elements shown in green on the graph pertain specifically to the summer period. 1. Number 1 on the graph denotes the first summer period! The price during this period remains within a narrow range 90% of the time; however, it's worth noting that impulsive movements can occur at the beginning, middle, or end. Thus, 90% of the time the price is in a low volatility zone, while the remaining percentage is in a high volatility zone. 2. Number 2 on the graph represents the second summer period, where a pattern is observed: the price tends to rise at the beginning of the summer period and fall towards the end. Therefore, I've marked this time with an arc, and there's a pattern to it. It's worth noting that during the period of the descending trend from 2014 to 2016, the situation after the downward trend differs from the situation in 2018 and 2023, when changes in the arrangement of this situation occur after the breakout of the descending trend based on wave analysis and the price of the asset itself. 3. Number 3 represents the third summer period! During this period, the price movement direction is upward and then downward, forming a correction in the upward trend. It should be noted that in this movement, all lows gradually rise, while highs renew all previous local highs of the asset price. This period exhibits increased volatility and impulsive movements, with the asset price mostly staying within a range of minimal volatility, with volatility not exceeding 1-2% on some stretches. 4. Under number 4, the fourth summer period is indicated, which has an overall upward direction. In this period, the movement is aggressively upward. Starting from the first month until the middle of summer, the price moves downward, forming a correction in the upward trend. Then, during the next month, the price moves aggressively upward, renewing price highs. Volatility in this period is anomalously high, resembling a hot July summer. Additionally, based on the price movement in the summer period, we can assume that fractals are evident here, which we can use to our advantage for profit. ______________________________________________________ Shark Trading - We urge all traders to delve deeper into this indicator and incorporate it into their trading practices. It can become an invaluable aid in market analysis and help traders reach new heights in their trading endeavors.
Pine Script® indicator
by SHARK1318
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
Obsidians Gold RevengeMany traders (including institutional desks) track lunar cycles on Gold (XAUUSD) because of the psychological impact on market sentiment. The common theory—often attributed to methods like Gann analysis—is: ​🌑 New Moon: Often correlates with Market Bottoms (Buy Signals) or "New Beginnings." ​🌕 Full Moon: Often correlates with Market Tops (Sell Signals) or "Exhaustion." ​Here is a script that mathematically calculates the Moon Phase based on the lunar synodic month (approx. 29.53 days). It will plot these events on your chart so you can visually backtest if Gold respects these cycles. How to use this for testing ​Add it to your Chart: Apply it to the XAUUSD (Gold) chart. ​Timeframe: This works best on 4-Hour (4H) or Daily (1D) charts. (On 15m charts, the moon phase covers many candles, so the label will appear on the specific candle where the phase officially "switched"). ​What to look for: ​Look at the Dark Blue (New Moon) areas. Did price form a bottom or start a rally there? ​Look at the Yellow (Full Moon) areas. Did price peak and reverse downward there? ​Note: Lunar cycles are considered a "timing tool" rather than a directional indicator. They often indicate when a reversal might happen, but you should combine this with your Institutional Candle zones to confirm the direction!
Pine Script® indicator
by LilyObsidianArc
Custom Date MarkersCustom Date Markers - Pine Script Indicator This indicator provides a powerful visual tool for technical and pattern analysis by allowing traders to mark up to 10 specific historical dates with customizable vertical lines on any chart. Each date can be assigned its own unique color, making it easy to categorize and distinguish between different types of events or market catalysts. Primary Use Cases: The indicator excels at identifying cyclical patterns and recurring market behavior. By marking significant dates such as earnings announcements, Federal Reserve meetings, dividend ex-dates, or seasonal events, traders can quickly visualize whether stocks consistently react in similar ways around these recurring dates. This is particularly valuable for discovering hidden patterns that might not be obvious from price action alone. Practical Applications: Earnings Analysis: Mark historical earnings dates to see if a stock tends to rally or sell-off before/after announcements Macro Events: Identify how assets respond to FOMC meetings, CPI releases, or other economic data Seasonal Patterns: Track dates that show recurring volatility or directional moves (like tax deadline periods, end-of-quarter re balancing, etc.) Event Studies: Analyze the impact of company-specific events like product launches, FDA approvals, or leadership changes Advanced Insights: What makes this tool particularly interesting is its ability to reveal non-obvious correlations. For example, you might discover that a retail stock consistently experiences volume spikes 2-3 weeks before Black Friday across multiple years, or that certain tech stocks show weakness during specific conference dates. The color-coding feature allows you to layer multiple event types simultaneously—perhaps using red for bearish catalysts and green for bullish ones—creating a visual heat map of historical market reactions. The indicator's 6-month default spacing (covering 4.5 years) is strategically designed to capture multiple business cycles while maintaining clarity on the chart. This timeframe is long enough to identify genuine patterns rather than coincidences, yet focused enough to remain relevant to current market conditions. Pro Tip: Combine this indicator with volume analysis or other technical indicators to validate whether the patterns you observe are accompanied by meaningful market participation or if they're statistical noise.
Pine Script® indicator
by parkerberlinger
SZN - Altcoin OscillatorSZN Altcoin Oscillator – Identify Market Phases with Precision What is the SZN Altcoin Oscillator? The SZN Altcoin Oscillator is a multi-layered analysis indicator specifically developed for the altcoin market. It combines different signal groups (trend, relative strength, volume, market environment, and overheating filters) into a unified oscillator in the 0–100 range. --> The goal is to make major market movements visible while separating short-term fluctuations from broader trends. Why not just use RSI or MACD? Classic single indicators like RSI or MACD often react too sensitively to short-term fluctuations. This leads to many false signals – especially during volatile altcoin phases. --> The SZN Altcoin Oscillator solves this problem by combining and filtering multiple signal sources. --> This smooths out overreactions and identifies true trend movements more reliably. ----- How does it work? The oscillator consists of five signal groups: Price & Trend Momentum checks the relative position of fast and slow moving averages detects whether an altcoin is in a confirmed uptrend or downtrend Relative Strength vs. Bitcoin & Ethereum measures performance compared to the two market leaders shows whether capital is rotating into altcoins or staying in majors Volume and Breakout Filter detects whether breakouts are confirmed by increased volume prevents short “fakeouts” from appearing as buy signals Market Environment (Regime Filter) includes overall market data such as BTC dominance or TOTAL3 ensures that buy signals only trigger in suitable market phases Overheating & Oversold Filter marks statistically extreme zones upward cross from oversold → buy signal downward cross from overheated → sell signal --> All results are displayed in a 0–100 oscillator. Buy signal: upward cross from oversold zones Sell signal: downward cross from overheated zones ----- Variants (selection in the settings menu) The indicator offers 5 preconfigured variants, optimized for different altcoin groups: Default The neutral standard configuration – balanced between sensitivity and stability. Suitable for a wide range of altcoins with medium to large market capitalization. Large Caps More conservative parameters with stronger smoothing. Designed for established projects (Top 20), where trends develop more slowly but with higher reliability. Mid Caps A balanced approach for mid-sized market caps. More sensitive than the Large-Cap variant, but filters more noise than the Small-Cap settings. Small Caps Higher sensitivity, optimized for more volatile coins (Top 100–200). Detects dynamic moves faster, but with higher risk of false signals. Meme Coins Adapted for highly speculative tokens. Accounts for extreme volatility and shorter cycles to better highlight overheating phases. --> This allows each user to select the variant best suited to the asset category being analyzed. ----- Recommended Usage Timeframe: Daily chart (highest precision). For very new projects, the 8h chart can be used. Asset selection: Coins with sufficient history (at least 200 trading days). ----- Interpretation: Oscillator rising from oversold → potential bottom / upward trend reversal Oscillator falling from overheated → potential top / profit-taking zone Movements in between indicate interim rallies or correction phases The indicator is not a day-trading tool, but optimized for cyclical moves and swing trading. ----- Notes: The SZN Altcoin Oscillator is an additional analysis tool and does not replace independent trading decisions. All signals are probabilistic; there is no guarantee of profits. Effectiveness depends on the specific altcoin and the current market phase. The indicator provides insights into broader market phases, not short-term price moves.
Pine Script® indicator
by SZN_Labs
Trend Titan Neutronstar [QuantraSystems]Trend Titan NEUTRONSTAR Credits The Trend Titan NEUTRONSTAR is a comprehensive aggregation of nearly 100 unique indicators and custom combinations, primarily developed from unique and public domain code. We'd like to thank our TradingView community members: @IkKeOmar for allowing us to add his well-built "Normalized KAMA Oscillator" and "Adaptive Trend Lines " indicators to the aggregation, as well as @DojiEmoji for his valuable "Drift Study (Inspired by Monte Carlo Simulations with BM)". Introduction The Trend Titan NEUTRONSTAR is a robust trend following algorithm meticulously crafted to meet the demands of crypto investors. Designed with a multi layered aggregation approach, NEUTRONSTAR excels in navigating the unique volatility and rapid shifts of the cryptocurrency market. By stacking and refining a variety of carefully selected indicators, it combines their individual strengths while reducing the impact of noise or false signals. This "aggregation of aggregators" approach enables NEUTRONSTAR to produce a consistently reliable trend signal across assets and timeframes, making it an exceptional tool for investors focused on medium to long term market positioning. NEUTRONSTAR ’s powerful trend following capabilities provide investors with straightforward, data driven analysis. It signals when tokens exhibit sustained upward momentum and systematically removes allocations from assets showing signs of weakness. This structure aids investors in recognizing peak market phases. In fact, one of NEUTRONSTAR ’s most valuable applications is its potential to help investors time exits near the peak of bull markets. This aims to maximize gains while mitigating exposure to downturns. Ultimately, NEUTRONSTAR equips investors with a high precision, adaptable framework for strategic decision making. It offers robust support to identify strong trends, manage risk, and navigate the dynamic crypto market landscape. With over a year of rigorous forward testing and live trading, NEUTRONSTAR demonstrates remarkable robustness and effectiveness, maintaining its performance without succumbing to overfitting. The system has been purposefully designed to avoid unnecessary optimization to past data, ensuring it can adapt as market conditions evolve. By focusing on aggregating valuable trend signals rather than tuning to historical performance, the NEUTRONSTAR serves as a reliable universal trend following system that aligns with the natural market cycles of growth and correction. Core Methodology The foundation of the NEUTRONSTAR lies in its multi aggregated structure, where five custom developed trend models are combined to capture the dominant market direction. Each of these aggregates has been carefully crafted with a specific trend signaling period in mind, allowing it to adapt seamlessly across various timeframes and asset classes. Here’s a breakdown of the key components: FLARE - The original Quantra Signaling Matrix (QSM) model, best suited for timeframes above 12 hours. It forms the foundation of long term trend detection, providing stable signals. FLAREV2 - A refined and more sophisticated model that performs well across both high and low timeframes, adding a layer of adaptability to the system. NEBULA - An advanced model combining FLARE and FLAREV2. NEBULA brings the advantages of both components together, enhancing reliability and capturing smoother, more accurate trends. SPARK - A high speed trend aggregator based on the QSM Universal model. It focuses on fast moving trends, providing early signals of potential shifts. SUNBURST - A balanced aggregate that combines elements of SPARK and FLARE, confirming SPARK’s signals while minimizing false positives. Each of these models contributes its own unique perspective on market movement. By layering fast, medium, and slower trend following signals, NEUTRONSTAR can confirm strong trends while filtering out shorter term noise. The result is a comprehensive tool that signals clear market direction with minimized false signals. A Unique Approach to Trend Aggregation One of the defining characteristics of NEUTRONSTAR is its deliberate choice to avoid perfectly time coherent indicators within its aggregation. In simpler terms, NEUTRONSTAR purposefully incorporates trend following indicators with slightly different signal periods, rather than synchronizing all components to a single signaling period. This choice brings significant benefits in terms of diversification, adaptability, and robustness of the overall trend signal. When aggregating multiple trend following components, if all indicators were perfectly time coherent - meaning they responded to market changes in exactly the same way and over the time periods - the resulting signal would effectively be no different from a single trend following indicator. This uniformity would limit the system’s ability to capture a variety of market conditions, leaving it vulnerable to the same noise or false signals that any single indicator might encounter. Instead, NEUTRONSTAR leverages a balanced mix of indicators with varied timing: some fast, some slower, and some in the medium range. This choice allows the system to extract the unique strengths of each component, creating a combined signal that is stronger and more reliable than any single indicator. By incorporating different signal periods, NEUTRONSTAR achieves what can be thought of as a form of edge accumulation. The fast components within NEUTRONSTAR , for example, are highly sensitive to quick shifts in market direction. These indicators excel at identifying early trend signals, enabling NEUTRONSTAR to react swiftly to emerging momentum. However, these fast indicators alone would be prone to reacting to market noise, potentially generating too many premature signals. This is where the medium term indicators come into play. These components operate with a slower reaction time, filtering out the short term fluctuations and confirming the direction of the trend established by the faster indicators. The combination of these varying signal speeds results in a balanced, adaptive response to market changes. This approach also allows NEUTRONSTAR to adapt to different market regimes seamlessly. In fast moving, volatile markets, the faster indicators provide an early alert to potential trend shifts, while the slower components offer a stabilizing influence, preventing overreaction to temporary noise. Conversely, in steadier or trending markets, the medium and slower indicators sustain the trend signal, reducing the likelihood of premature exits. This flexible design enhances NEUTRONSTAR ’s ability to operate effectively across multiple asset classes and timeframes, from short term fluctuations to longer term market cycles. The result is a powerful, multi-layered trend following tool that remains adaptive, capturing the benefits of both fast and medium paced reactions without becoming overly sensitive to short term noise. This unique aggregation methodology also supports NEUTRONSTAR ’s robustness, reducing the risk of overfitting to historical data and ensuring that the system can perform reliably in forward testing and live trading environments. The slightly staggered signal periods provide a greater degree of resilience, making NEUTRONSTAR a dependable choice for traders looking to capitalize on sustained trends while minimizing exposure during periods of market uncertainty. In summary, the lack of perfect time coherence among NEUTRONSTAR ’s sub components is not a flaw - but a deliberate, robust design choice. Risk Management through Market Mode Analysis An essential part of NEUTRONSTAR is its ability to assess the market's underlying behavior and adapt accordingly. It employs a Market Mode Analysis mechanism that identifies when the market is either in a “Trending State” or a “Mean Reverting State.” When enough confidence is established that the market is trending, the system confirms and signals a “Trending State,” which is optimal for maintaining positions in the direction of the trend. Conversely, if there’s insufficient confidence, it labels the market as “Mean Reverting,” alerting traders to potentially avoid trend trades during likely sideways movement. This distinction is particularly valuable in crypto, where asset prices often oscillate between aggressive trends and consolidation periods. The Market Mode Analysis keeps traders aligned with the broader market conditions, minimizing exposure during periods of potential whipsaws and maximizing gains during sustained trends. Zero Overfitting: Design and Testing for Real World Resilience Unlike many trend following indicators that rely heavily on backtesting and optimization, NEUTRONSTAR was built to perform well in forward testing and live trading without post design adjustments. Over a year of live market exposure has all but proven its robustness, with the system’s methodology focused on universal applicability and simplicity rather than curve fitting to past data. This approach ensures the aggregator remains effective across different market cycles and maintains relevance as new data unfolds. By avoiding overfitting, NEUTRONSTAR is inherently more resistant to the common issue of strategy degradation over time, making it a valuable tool for traders seeking reliable market analysis you can trust for the long term. Settings and Customization Options To accommodate a range of trading styles and market conditions, NEUTRONSTAR includes adjustable settings that allow for fine tuning sensitivity and signal generation: Calculation Method - Users can choose between calculating the NEUTRONSTAR score based on aggregated scores or by using the state of individual aggregates (long, neutral, short). The score method provides faster signals with slightly more noise, while the state based approach offers a smoother signal. Sensitivity Threshold - This setting adjusts the system’s sensitivity, defining the width of the neutral zone. Higher thresholds reduce sensitivity, allowing for a broader range of volatility before triggering a trend reversal. Market Regime Sensitivity - A sensitivity adjustment, ranging from 0 to 100, that affects the sensitivity of the sub components in market regime calculation. These settings offer flexibility for users to tailor NEUTRONSTAR to their specific needs, whether for medium term investment strategies or shorter term trading setups. Visualization and Legend For intuitive usability, NEUTRONSTAR uses color coded bar overlays to indicate trend direction: Green - indicates an uptrend. Gray - signals a neutral or transition phase. Purple - denotes a downtrend. An optional background color can be enabled for market mode visualization, indicating the overall market state as either trending or mean reverting. This feature allows traders to assess trend direction and strength at a glance, simplifying decision making. Additional Metrics Table To support strategic decision making, NEUTRONSTAR includes an additional metrics table for in depth analysis: Performance Ratios - Sharpe, Sortino, and Omega ratios assess the asset’s risk adjusted returns. Volatility Insights - Provides an average volatility measure, valuable for understanding market stability. Beta Measurement - Calculates asset beta against BTC, offering insight into asset volatility in the context of the broader market. These metrics provide deeper insights into individual asset behavior, supporting more informed trend based allocations. The table is fully customizable, allowing traders to adjust the position and size for a seamless integration into their workspace. Final Summary The Trend Titan NEUTRONSTAR indicator is a powerful and resilient trend following system for crypto markets, built with a unique aggregation of high performance models to deliver dependable, noise reduced trend signals. Its robust design, free from overfitting, ensures adaptability across various assets and timeframes. With customizable sensitivity settings, intuitive color coded visualization, and an advanced risk metrics table, NEUTRONSTAR provides traders with a comprehensive tool for identifying and riding profitable trends, while safeguarding capital during unfavorable market phases.
Pine Script® indicator
by Cryptosystems
HSI - Halving Seasonality Index for Bitcoin (BTC) [Logue]Halving Seasonality Index (HSI) for Bitcoin (BTC) - The HSI takes advantage of the consistency of BTC cycles. Past cycles have formed macro tops around 538 days after each halving. Past cycles have formed macro bottoms every 948 days after each halving. Therefore, a linear "risk" curve can be created between the bottom and top dates to measure how close BTC might be to a bottom or a top. The default triggers are set at 98% risk for tops and 5% risk for bottoms. Extensions are also added as defaults to allow easy identification of the dates of the next top or bottom according to the HSI.
Pine Script® indicator
by Da_Prof
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