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Relative Falling three Methods IndicatorAbstract This script measure the related speed between rising and falling. This script can replace binary Falling Three Methods detector and, report continuous value and estimate potential trend direction. My suggestion of using this script is combining it with trading emotion. Introduction Falling Three Methods (F3M) is a candlestick pattern. Many trading courses say traders can regard it as predicting falling will continue. However, it is not easy to see perfect Falling Three Methods pattern from charts. Therefore, we need an alternative method to measure it. We can use the observation that falling is faster than rising during those time. When falling is faster than rising, some long ( buy , call , higher , upper ) position owners may worry the price will fall very much suddenly. When rising is faster than falling, some traders may worry they may miss buy opportunities. Computing Related Falling Three Methods Indicator (1) The value of rising and falling In this script, open price is replaced with previous close price. If the previous price is equal to the close price, than both rising and falling are equal to high-low. If the previous price is lower than the close price, than the falling value becomes smaller, high-close+previous-low. If the previous price is higher than the close price, than the rising value becomes smaller, high-previous+close-low. (2) Area of value (aov) Area of value is equal to highest-lowest. The previous close price is included. (3) Compute weight and filter noise We need a threshold for the noise filter. The default setting is aov/length, where length means how many days are counted. When a rising or falling value <= threshold, it is not counted. When a rising or falling value > threshold, the counted value = original value - threshold and its weight = min ( counted value , threshold ) (4) compute speed Rising speed = sum ( counted rising value ) / sum ( rising weight ) Falling speed = sum ( counted falling value ) / sum ( falling weight ) (5) Final result Final result = Rising speed / ( Rising speed + Falling speed ) * 100 - 50 I move the middle level to 0 because 0 axis is always visible unless you cannot see negative values or you cannot see positive values. Parameters Length : how many days are counted. The default value is 16 just because 16=4*4, using binary characteristic. Multi : the multiplier of noise threshold. Threshold applied = default threshold * multi src : current not used Conclusion Related Falling Three Methods Indicator can measure the related speed between rising and falling. I hope this indicator can help us to evaluate the possibility of trend continue or reversal and potential breakout direction. After all, we care how trading emotion control the price movement and therefore we can take advantage to it. Reference How to trade with Falling Three Methods pattern How to trade with Related Strength Indicator
Pine Script®指標
由clocks156t174提供
4 in 1 Stoch Indicators as used by HG (Stoch, SRSIx2, DMIStoch)By using this indicator you can better view the Stoch indicators used by this strategy which are: - Stochastic (14,3,3) - Stochastic RSI (14,14,3,3) - Stochastic RSI (6,6,3,3) - DMI Stochastic This is best used alongside: - Evan Cabral binary strategy 2 - Binary with Temito The analisis is: - When all lines in the indicator are above or below the overbough/oversold lines - When the bollinger bands are broken - A support or resistance is reached That means a change of Trend.
Pine Script®指標
由AngelRChaconM提供
1
Edge-Preserving FilterIntroduction Edge-preserving smoothing is often used in image processing in order to preserve edge information while filtering the remaining signal. I introduce two concepts in this indicator, edge preservation and an adaptive cumulative average allowing for fast edge-signal transition with period increase over time. This filter have nothing to do with classic filters for image processing, those filters use kernels convolution and are most of the time in a spatial domain. Edge Detection Method We want to minimize smoothing when an edge is detected, so our first goal is to detect an edge. An edge will be considered as being a peak or a valley, if you recall there is one of my indicator who aim to detect peaks and valley (reference at the bottom of the post) , since this estimation return binary outputs we will use it to tell our filter when to stop filtering. Filtering Increase By Using Multi Steps Cumulative Average The edge detection is a binary output, using a exponential smoothing could be possible and certainly more efficient but i wanted instead to try using a cumulative average approach because it smooth more and is a bit more original to use an adaptive architecture using something else than exponential averaging. A cumulative average is defined as the sum of the price and the previous value of the cumulative average and then this result is divided by n with n = number of data points. You could say that a cumulative average is a moving average with a linear increasing period. So lets call CMA our cumulative average and n our divisor. When an edge is detected CMA = close price and n = 1 , else n is equal to previous n+1 and the CMA act as a normal cumulative average by summing its previous values with the price and dividing the sum by n until a new edge is detected, so there is a "no filtering state" and a "filtering state" with linear period increase transition, this is why its multi-steps. The Filter The filter have two parameters, a length parameter and a smooth parameter, length refer to the edge detection sensitivity, small values will detect short terms edges while higher values will detect more long terms edges. Smooth is directly related to the edge detection method, high values of smooth can avoid the detection of some edges. smooth = 200 smooth = 50 smooth = 3 Conclusion Preserving the price edges can be useful when it come to allow for reactivity during important price points, such filter can help with moving average crossover methods or can be used as a source for other indicators making those directly dependent of the edge detection. Rsi with a period of 200 and our filter as source, will cross triggers line when an edge is detected Feel free to share suggestions ! Thanks for reading ! References Peak/Valley estimator used for the detection of edges in price.
Pine Script®指標
由alexgrover提供
18
Heiken Ashi zero lag EMA v1.1 by JustUncleLI originally wrote this script earlier this year for my own use. This released version is an updated version of my original idea based on more recent script ideas. As always with my Alert scripts please do not trade the CALL/PUT indicators blindly, always analyse each position carefully. Always test indicator in DEMO mode first to see if it profitable for your trading style. DESCRIPTION: This Alert indicator utilizes the Heiken Ashi with non lag EMA was a scalping and intraday trading system that has been adapted also for trading with binary options high/low. There is also included filtering on MACD direction and trend direction as indicated by two MA: smoothed MA(11) and EMA(89). The the Heiken Ashi candles are great as price action trending indicator, they shows smooth strong and clear price fluctuations. Financial Markets: any. Optimsed settings for 1 min, 5 min and 15 min Time Frame; Expiry time for Binary options High/Low 3-6 candles. Indicators used in calculations: - Exponential moving average, period 89 - Smoothed moving average, period 11 - Non lag EMA, period 20 - MACD 2 colour (13,26,9) Generate Alerts use the following Trading Rules Heiken Ashi with non lag dot Trade only in direction of the trend. UP trend moving average 11 period is above Exponential moving average 89 period, Doun trend moving average 11 period is below Exponential moving average 89 period, CALL Arrow appears when: Trend UP SMA11>EMA89 (optionally disabled), Non lag MA blue dot and blue background. Heike ashi green color. MACD 2 Colour histogram green bars (optional disabled). PUT Arrow appears when: Trend UP SMA11<EMA89 (optionally disabled), Heike ashi red color. Non lag MA red dot and red background. MACD 2 colour histogram red bars (optionally disabled). HINTS: - Good positions occur when MACD crosses the Zero line. - Switch between Heikin Ashi and Normal candles as part of your analysis of the price action. - Large Heikin Ashi candles with small wicks in direction of trend are good strong trends.
Pine Script®指標
由JustUncleL提供
32
MLActivationFunctionsLibrary "MLActivationFunctions" Activation functions for Neural networks. binary_step(value) Basic threshold output classifier to activate/deactivate neuron.   Parameters:      value : float, value to process.   Returns: float linear(value) Input is the same as output.   Parameters:      value : float, value to process.   Returns: float sigmoid(value) Sigmoid or logistic function.   Parameters:      value : float, value to process.   Returns: float sigmoid_derivative(value) Derivative of sigmoid function.   Parameters:      value : float, value to process.   Returns: float tanh(value) Hyperbolic tangent function.   Parameters:      value : float, value to process.   Returns: float tanh_derivative(value) Hyperbolic tangent function derivative.   Parameters:      value : float, value to process.   Returns: float relu(value) Rectified linear unit (RELU) function.   Parameters:      value : float, value to process.   Returns: float relu_derivative(value) RELU function derivative.   Parameters:      value : float, value to process.   Returns: float leaky_relu(value) Leaky RELU function.   Parameters:      value : float, value to process.   Returns: float leaky_relu_derivative(value) Leaky RELU function derivative.   Parameters:      value : float, value to process.   Returns: float relu6(value) RELU-6 function.   Parameters:      value : float, value to process.   Returns: float softmax(value) Softmax function.   Parameters:      value : float array, values to process.   Returns: float softplus(value) Softplus function.   Parameters:      value : float, value to process.   Returns: float softsign(value) Softsign function.   Parameters:      value : float, value to process.   Returns: float elu(value, alpha) Exponential Linear Unit (ELU) function.   Parameters:      value : float, value to process.      alpha : float, default=1.0, predefined constant, controls the value to which an ELU saturates for negative net inputs. .   Returns: float selu(value, alpha, scale) Scaled Exponential Linear Unit (SELU) function.   Parameters:      value : float, value to process.      alpha : float, default=1.67326324, predefined constant, controls the value to which an SELU saturates for negative net inputs. .      scale : float, default=1.05070098, predefined constant.   Returns: float exponential(value) Pointer to math.exp() function.   Parameters:      value : float, value to process.   Returns: float function(name, value, alpha, scale) Activation function.   Parameters:      name : string, name of activation function.      value : float, value to process.      alpha : float, default=na, if required.      scale : float, default=na, if required.   Returns: float derivative(name, value, alpha, scale) Derivative Activation function.   Parameters:      name : string, name of activation function.      value : float, value to process.      alpha : float, default=na, if required.      scale : float, default=na, if required.   Returns: float
Pine Script®腳本庫
由RicardoSantos提供
2
Stochastic with Outlier Labels/MTFTL;DR This indicator is an update to a simple stochastic ('Stoch_MTF' by binarytrader666) that provides a novel outlier highlighting feature Improvements on stochastic: 1. Novel outlier highlighting that points out crosses that are the Nth consecutive cross or greater. 2. Allowing for multiple timeframes to be shown on the same chart 3. Highlighting/Labelling crosses and providing labels for alerts A cross of the stochastics in the high or low zones establishes a trend. Successive crosses in the same region seem to indicate a continuation of that trend. The outlier functionality here provides a signal for when X number of crosses have been in the same trend, signaling further strength of that signal. I also provided the necessary code for converting this to a strategy if you so wish at the bottom.
Pine Script®指標
由on2valhalla提供
1
Linear Regression Trend Channel with Entries & AlertsPlease Use this Indicator If you understand the risk posed by linear regression trend channel Features Provides trend channel (best value for period is 40 on 5 minute timeframe Provides BUY/SELL entries based on current channel Provides custom color for channel Best used with MattyPips strategy indicators Risks : Please note, this script is the likes of Bollinger bands and poses a risk of falling in a trend range. Entries may keep running on the same direction while the market is moving.
Pine Script®指標
由MrTuanDoan提供
23
Benchmark Above MA SignalBenchmark Above MA Signal (Configurable Visual) This tool provides a simple ON/OFF signal showing whether a selected benchmark asset (e.g., SPY, BTC, QQQ, etc.) is currently trading above a specified moving average. 🔧 Customizable Settings: Choose the benchmark symbol Set the timeframe (e.g., daily, 4H, weekly) Select SMA or EMA type Define the MA length (e.g., 21, 50, 200) Pick between two display modes: Stepline (default): plots a clean binary signal in the lower pane Background Only: visually highlights confluence periods without a line plot ✅ Ideal for macro filters, trend confirmation, or dashboard-style layouts 📊 Common use case: staying aware of the daily trend of SPY while trading lower intraday timeframes
Pine Script®指標
由kondor_trades提供
RS Triple MA Confluence Signal (Lower Pane)This indicator outputs a binary signal (1 or 0) based on triple moving average confluence of an asset’s relative strength vs a benchmark (e.g., SPY, BTC, etc). ✅ A value of 1 indicates full confluence, where the asset's relative strength is above three customizable moving averages (short, medium, and long). ❌ A value of 0 indicates confluence is off. This version is designed to be used in a lower pane for: Quick visual scanning Dashboard-style layouts Systematic filtering or alerting Pairs perfectly with the main overlay tool: 👉 Relative Strength Triple MA Confluence Use that version for candle coloring and price-level signals, and this version for clean signal tracking and screening support.
Pine Script®指標
由kondor_trades提供
AWR R & LR Oscillator with plots & tableHello trading viewers ! I'm glad to share with you one of my favorite indicator. It's the aggregate of many things. It is partly based on an indicator designed by gentleman goat. Many thanks to him. 1. Oscillator and Correlation Calculations Overview and Functionality: This part of the indicator computes up to 10 Pearson correlation coefficients between a chosen source (typically the close price, though this is user-configurable) and the bar index over various periods. Starting with an initial period defined by the startPeriod parameter and increasing by a set increment (periodIncrement), each correlation coefficient is calculated using the built-in ta.correlation function over successive ranges. These coefficients are stored in an array, and the indicator calculates their average (avgPR) to provide a complete view of the market trend strength. Display Features: Each individual coefficient, as well as the overall average, is plotted on the chart using a specific color. Horizontal lines (both dashed and solid) are drawn at levels 0, ±0.8, and ±1, serving as visual thresholds. Additionally, conditional fills in red or blue highlight when values exceed these thresholds, helping the user quickly identify potential extreme conditions (such as overbought or oversold situations). 2. Visual Signals and Automated Alerts Graphical Signal Enhancements: To reinforce the analysis, the indicator uses graphical elements like emojis and shape markers. For example: If all 10 curves drop below -0.79, a 🌋 emoji appears at the bottom of the chart; When curves 2 through 10 are below -0.79, a ⛰️ emoji is displayed below the bar, potentially serving as a buy signal accompanied by an alert condition; Likewise, symmetrical conditions for correlations exceeding 0.79 produce corresponding emojis (🤿 and 🏖️) at the top or bottom of the chart. Alerts and Notifications: Using these visual triggers, several alertcondition statements are defined within the script. This allows users to set up TradingView alerts and receive real-time notifications whenever the market reaches these predefined critical zones identified by the multi-period analysis. 3. Regression Channel Analysis Principles and Calculations: In addition to the oscillator, the indicator implements an analysis of regression channels. For each of the 8 configurable channels, the user can set a range of periods (for example, min1 to max1, etc.). The function calc_regression_channel iterates through the defined period range to find the optimal period that maximizes a statistical measure derived from a regression parameter calculated by the function r(p). Once this optimal period is identified, the indicator computes two key points (A and B) which define the main regression line, and then creates a channel based on the calculated deviation (an RMSE multiplied by a user-defined factor). The regression channels are not displayed on the chart but are used to plot shapes & fullfilled a table. Blue shapes are plotted when 6th channel or 7th channel are lower than 3 deviations Yellow shapes are plotted when 6th channel or 7th channel are higher than 3 deviations 4. Scores, Conditions, and the Summary Table Scoring System: The indicator goes further by assigning scores across multiple analytical categories, such as: 1. BigPear Score What It Represents: This score is based on a longer-term moving average of the Pearson correlation values (SMA 100 of the average of the 10 curves of correlation of Pearson). The BigPear category is designed to capture where this longer-term average falls within specific ranges. Conditions: The script defines nine boolean conditions (labeled BigPear1up through BigPear9up for the “up” direction). Here's the rules : BigPear1up = (bigsma_avgPR <= 0.5 and bigsma_avgPR > 0.25) BigPear2up = (bigsma_avgPR <= 0.25 and bigsma_avgPR > 0) BigPear3up = (bigsma_avgPR <= 0 and bigsma_avgPR > -0.25) BigPear4up = (bigsma_avgPR <= -0.25 and bigsma_avgPR > -0.5) BigPear5up = (bigsma_avgPR <= -0.5 and bigsma_avgPR > -0.65) BigPear6up = (bigsma_avgPR <= -0.65 and bigsma_avgPR > -0.7) BigPear7up = (bigsma_avgPR <= -0.7 and bigsma_avgPR > -0.75) BigPear8up = (bigsma_avgPR <= -0.75 and bigsma_avgPR > -0.8) BigPear9up = (bigsma_avgPR <= -0.8) Conditions: The script defines nine boolean conditions (labeled BigPear1down through BigPear9down for the “down” direction). BigPear1down = (bigsma_avgPR >= -0.5 and bigsma_avgPR < -0.25) BigPear2down = (bigsma_avgPR >= -0.25 and bigsma_avgPR < 0) BigPear3down = (bigsma_avgPR >= 0 and bigsma_avgPR < 0.25) BigPear4down = (bigsma_avgPR >= 0.25 and bigsma_avgPR < 0.5) BigPear5down = (bigsma_avgPR >= 0.5 and bigsma_avgPR < 0.65) BigPear6down = (bigsma_avgPR >= 0.65 and bigsma_avgPR < 0.7) BigPear7down = (bigsma_avgPR >= 0.7 and bigsma_avgPR < 0.75) BigPear8down = (bigsma_avgPR >= 0.75 and bigsma_avgPR < 0.8) BigPear9down = (bigsma_avgPR >= 0.8) Weighting: If BigPear1up is true, 1 point is added; if BigPear2up is true, 2 points are added; and so on up to 9 points from BigPear9up. Total Score: The positive score (posScoreBigPear) is the sum of these weighted conditions. Similarly, there is a negative score (negScoreBigPear) that is calculated using a mirrored set of conditions (named BigPear1down to BigPear9down), each contributing a negative weight (from -1 to -9). In essence, the BigPear score tells you—in a weighted cumulative way—where the longer-term correlation average falls relative to predefined thresholds. 2. Pear Score What It Represents: This category uses the immediate average of the Pearson correlations (avgPR) rather than a longer-term smoothed version. It reflects a more current picture of the market’s correlation behavior. How It’s Calculated: Conditions: There are nine conditions defined for the “up” scenario (named Pear1up through Pear9up), which partition the range of avgPR into intervals. For instance: Pear1up = (avgPR > -0.2 and avgPR <= 0) Pear2up = (avgPR > -0.4 and avgPR <= -0.2) Pear3up = (avgPR > -0.5 and avgPR <= -0.4) Pear4up = (avgPR > -0.6 and avgPR <= -0.5) Pear5up = (avgPR > -0.65 and avgPR <= -0.6) Pear6up = (avgPR > -0.7 and avgPR <= -0.65) Pear7up = (avgPR > -0.75 and avgPR <= -0.7) Pear8up = (avgPR > -0.8 and avgPR <= -0.75) Pear9up = (avgPR > -1 and avgPR <= -0.8) There are nine conditions defined for the “down” scenario (named Pear1down through Pear9down), which partition the range of avgPR into intervals. For instance: Pear1down = (avgPR >= 0 and avgPR < 0.2) Pear2down = (avgPR >= 0.2 and avgPR < 0.4) Pear3down = (avgPR >= 0.4 and avgPR < 0.5) Pear4down = (avgPR >= 0.5 and avgPR < 0.6) Pear5down = (avgPR >= 0.6 and avgPR < 0.65) Pear6down = (avgPR >= 0.65 and avgPR < 0.7) Pear7down = (avgPR >= 0.7 and avgPR < 0.75) Pear8down = (avgPR >= 0.75 and avgPR < 0.8) Pear9down = (avgPR >= 0.8 and avgPR <= 1) Weighting: Each condition has an associated weight, such as 0.9 for Pear1up, 1.9 for Pear2up, and so on, up to 9 for Pear9up. Sum up : Pear1up = 0.9 Pear2up = 1.9 Pear3up = 2.9 Pear4up = 3.9 Pear5up = 4.99 Pear6up = 6 Pear7up = 7 Pear8up = 8 Pear9up = 9 Total Score: The positive score (posScorePear) is the sum of these values for each condition that returns true. A corresponding negative score (negScorePear) is calculated using conditions for when avgPR falls on the positive side, with similar weights in the negative direction. This score quantifies the current correlation reading by translating its relative level into a numeric score through a weighted sum. 3. Trendpear Score What It Represents: The Trendpear score is more dynamic as it compares the current avgPR with its short-term moving average (sma_avgPR / 14 periods ) and also considers its relationship with an even longer moving average (bigsma_avgPR / 100 periods). It is meant to capture the trend or momentum in the correlation behavior. How It’s Calculated: Conditions: Nine conditions (from Trendpear1up to Trendpear9up) are defined to check: Whether avgPR is below, equal to, or above sma_avgPR by different margins; Whether it is trending upward (i.e., it is higher than its previous value). Here are the rules Trendpear1up = (avgPR <= sma_avgPR -0.2) and (avgPR >= avgPR ) Trendpear2up = (avgPR > sma_avgPR -0.2) and (avgPR <= sma_avgPR -0.07) and (avgPR >= avgPR ) Trendpear3up = (avgPR > sma_avgPR -0.07) and (avgPR <= sma_avgPR -0.03) and (avgPR >= avgPR ) Trendpear4up = (avgPR > sma_avgPR -0.03) and (avgPR <= sma_avgPR -0.02) and (avgPR >= avgPR ) Trendpear5up = (avgPR > sma_avgPR -0.02) and (avgPR <= sma_avgPR -0.01) and (avgPR >= avgPR ) Trendpear6up = (avgPR > sma_avgPR -0.01) and (avgPR <= sma_avgPR -0.001) and (avgPR >= avgPR ) Trendpear7up = (avgPR >= sma_avgPR) and (avgPR >= avgPR ) and (avgPR <= bigsma_avgPR) Trendpear8up = (avgPR >= sma_avgPR) and (avgPR >= avgPR ) and (avgPR >= bigsma_avgPR -0.03) Trendpear9up = (avgPR >= sma_avgPR) and (avgPR >= avgPR ) and (avgPR >= bigsma_avgPR) Weighting: The weights here are not linear. For example, the lightest condition may add 0.1 point, whereas the most extreme condition (e.g., when avgPR is not only above the moving average but also reaches a high proportion relative to bigsma_avgPR) might add as much as 90 points. Trendpear1up = 0.1 Trendpear2up = 0.2 Trendpear3up = 0.3 Trendpear4up = 0.4 Trendpear5up = 0.5 Trendpear6up = 0.69 Trendpear7up = 7 Trendpear8up = 8.9 Trendpear9up = 90 Total Score: The positive score (posScoreTrendpear) is the sum of the weights from all conditions that are satisfied. A negative counterpart (negScoreTrendpear) exists similarly for when the trend indicates a downward bias. Trendpear integrates both the level and the direction of change in the correlations, giving a strong numeric indication when the market starts to diverge from its short-term average. 4. Deviation Score What It Represents: The “Écart” score quantifies how far the asset’s price deviates from the boundaries defined by the regression channels. This metric can indicate if the price is excessively deviating—which might signal an eventual reversion—or confirming a breakout. How It’s Calculated: Conditions: For each channel (with at least seven channels contributing to the scoring from the provided code), there are three levels of deviation: First tier (EcartXup): Checks if the price is below the upper boundary but above a second boundary. Second tier (EcartXup2): Checks if the price has dropped further, between a lower and a more extreme boundary. Third tier (EcartXup3): Checks if the price is below the most extreme limit. Weighting: Each tier within a channel has a very small weight for the lowest severities (for example, 0.0001 for the first tier, 0.0002 for the second, 0.0003 for the third) with weights increasing with the channel index. First channel : 0.0001 to 0.0003 (very short term) Second channel : 0.001 to 0.003 (short term) Third channel : 0.01 to 0.03 (short mid term) 4th channel : 0.1 to 0.3 ( mid term) 5th channel: 1 to 3 (long mid term) 6th channel : 10 to 30 (long term) 7th channel : 100 to 300 (very long term) Total Score: The overall positive score (posScoreEcart) is the sum of all the weights for conditions met among the first, second, and third tiers. The corresponding negative score (negScoreEcart) is calculated similarly (using conditions when the price is above the channel boundaries), with the weights being the same in magnitude but negative in sign. This layered scoring method allows the indicator to reflect both minor and major deviations in a gradated and cumulative manner. Example : Score + = 321.0001 Score - = -0.111 The asset price is really overextended in long term view, not for mid term & short term expect the in the very short term. Score + = 0.0033 Score - = -1.11 The asset price is really extended in short term view, not for mid term (even a bit underextended) & long term is neutral 5. Slope Score What It Represents: The Slope score captures the trend direction and steepness of the regression channels. It reflects whether the regression line (and hence the underlying trend) is sloping upward or downward. How It’s Calculated: Conditions: if the slope has a uptrend = 1 if the slope has a downtrend = -1 Weighting: First channel : 0.0001 to 0.0003 (very short term) Second channel : 0.001 to 0.003 (short term) Third channel : 0.01 to 0.03 (short mid term) 4th channel : 0.1 to 0.3 ( mid term) 5th channel: 1 to 3 (long mid term) 6th channel : 10 to 30 (long term) 7th channel : 100 to 300 (very long term) The positive slope conditions incrementally add weights from 0.0001 for the smallest positive slopes to 100 for the largest among the seven checks. And negative for the downward slopes. The positive score (posScoreSlope) is the sum of all the weights from the upward slope conditions that are met. The negative score (negScoreSlope) sums the negative weights when downward conditions are met. Example : Score + = 111 Score - = -0.1111 Trend is up for longterm & down for mid & short term The slope score therefore emphasizes both the magnitude and the direction of the trend as indicated by the regression channels, with an intentional asymmetry that flags strong downtrends more aggressively. Summary For each category—BigPear, Pear, Trendpear, Écart, and Slope—the indicator evaluates a defined set of conditions. Each condition is a binary test (true/false) based on different thresholds or comparisons (for example, comparing the current value to a moving average or a channel boundary). When a condition is true, its assigned weight is added to the cumulative score for that category. These individual scores, both positive and negative, are then displayed in a table, making it easy for the trader to see at a glance where the market stands according to each analytical dimension. This comprehensive, weighted approach allows the indicator to encapsulate several layers of market information into a single set of scores, aiding in the identification of potential trading opportunities or market reversals. 5. Practical Use and Application How to Use the Indicator: Interpreting the Signals: On your chart, observe the following components: The individual correlation curves and their average, plotted with visual thresholds; Visual markers (such as emojis and shape markers) that signal potential oversold or overbought conditions The summary table that aggregates the scores from each category, offering a quick glance at the market’s state. Trading Alerts and Decisions: Set your TradingView alerts through the alertcondition functions provided by the indicator. This way, you receive immediate notifications when critical conditions are met, allowing you to react as soon as the market reaches key levels. This tool is especially beneficial for advanced traders who want to combine multiple technical dimensions to optimize entry and exit points with a confluence of signals. Conclusion and Additional Insights In summary, this advanced indicator innovatively combines multi-scale Pearson correlation analysis (via multiple linear regressions) with robust regression channel analysis. It offers a deep and nuanced view of market dynamics by delivering clear visual signals and a comprehensive numerical summary through a built-in score table. Combine this indicator with other tools (e.g., oscillators, moving averages, volume indicators) to enhance overall strategy robustness.
Pine Script®指標
由AlwwAl提供
PhenLabs - Market Fluid Dynamics📊 Market Fluid Dynamics - Version: PineScript™ v6 📌 Description The Market Fluid Dynamics - Phen indicator is a new thinking regarding market analysis by modeling price action, volume, and volatility using a fluid system. It attempts to offer traders control over more profound market forces, such as momentum (speed), resistance (thickness), and buying/selling pressure. By visualizing such dynamics, the script allows the traders to decide on the prevailing market flow, its power, likely continuations, and zones of calmness and chaos, and thereby allows improved decision-making. This measure avoids the usual difficulty of reconciling multiple, often contradictory, market indications by including them within a single overarching model. It moves beyond traditional binary indicators by providing a multi-dimensional view of market behavior, employing fluid dynamic analogs to describe complex interactions in an accessible manner. 🚀 Points of Innovation Integrated Fluid Dynamics Model: Combines velocity, viscosity, pressure, and turbulence into a single indicator. Normalized Metrics: Uses ATR and other normalization techniques for consistent readings across different assets and timeframes. Dynamic Flow Visualization: Main flow line changes color and intensity based on direction and strength. Turbulence Background: Visually represents market stability with a gradient background, from calm to turbulent. Comprehensive Dashboard: Provides an at-a-glance summary of key fluid dynamic metrics. Multi-Layer Smoothing: Employs several layers of EMA smoothing for a clearer, more responsive main flow line. 🔧 Core Components Velocity Component: Measures price momentum (first derivative of price), normalized by ATR. It indicates the speed and direction of price changes. Viscosity Component: Represents market resistance to price changes, derived from ATR relative to its historical average. Higher viscosity suggests it’s harder for prices to move. Pressure Component: Quantifies the force created by volume and price range (close - open), normalized by ATR. It reflects buying or selling pressure. Turbulence Detection: Calculates a Reynolds number equivalent to identify market stability, ranging from laminar (stable) to turbulent (chaotic). Main Flow Indicator: Combines the above components, applying sensitivity and smoothing, to generate a primary signal of market direction and strength. 🔥 Key Features Advanced Smoothing Algorithm: Utilizes multiple EMA layers on the raw flow calculation for a fluid and responsive main flow line, reducing noise while maintaining sensitivity. Gradient Flow Coloring: The main flow line dynamically changes color from light to deep blue for bullish flow and light to deep red for bearish flow, with intensity reflecting flow strength. This provides an immediate visual cue of market sentiment and momentum. Turbulence Level Background: The chart background changes color based on calculated turbulence (from calm gray to vibrant orange), offering an intuitive understanding of market stability and potential for erratic price action. Informative Dashboard: A customizable on-screen table displays critical metrics like Flow State, Flow Strength, Market Viscosity, Turbulence, Pressure Force, Flow Acceleration, and Flow Continuity, allowing traders to quickly assess current market conditions. Configurable Lookback and Sensitivity: Users can adjust the base lookback period for calculations and the sensitivity of the flow to viscosity, tailoring the indicator to different trading styles and market conditions. Alert Conditions: Pre-defined alerts for flow direction changes (positive/negative crossover of zero line) and detection of high turbulence states. 🎨 Visualization Main Flow Line: A smoothed line plotted below the main chart, colored blue for bullish flow and red for bearish flow. The intensity of the color (light to dark) indicates the strength of the flow. This line crossing the zero line can signal a change in market direction. Zero Line: A dotted horizontal line at the zero level, serving as a baseline to gauge whether the market flow is positive (bullish) or negative (bearish). Turbulence Background: The indicator pane’s background color changes based on the calculated turbulence level. A calm, almost transparent gray indicates low turbulence (laminar flow), while a more vibrant, semi-transparent orange signifies high turbulence. This helps traders visually assess market stability. Dashboard Table: An optional table displayed on the chart, showing key metrics like ‘Flow State’, ‘Flow Strength’, ‘Market Viscosity’, ‘Turbulence’, ‘Pressure Force’, ‘Flow Acceleration’, and ‘Flow Continuity’ with their current values and qualitative descriptions (e.g., ‘Bullish Flow’, ‘Laminar (Stable)’). 📖 Usage Guidelines Setting Categories Show Dashboard - Default: true; Range: true/false; Description: Toggles the visibility of the Market Fluid Dynamics dashboard on the chart. Enable to see key metrics at a glance. Base Lookback Period - Default: 14; Range: 5 - (no upper limit, practical limits apply); Description: Sets the primary lookback period for core calculations like velocity, ATR, and volume SMA. Shorter periods make the indicator more sensitive to recent price action, while longer periods provide a smoother, slower signal. Flow Sensitivity - Default: 0.5; Range: 0.1 - 1.0 (step 0.1); Description: Adjusts how much the market viscosity dampens the raw flow. A lower value means viscosity has less impact (flow is more sensitive to raw velocity/pressure), while a higher value means viscosity has a greater dampening effect. Flow Smoothing - Default: 5; Range: 1 - 20; Description: Controls the length of the EMA smoothing applied to the main flow line. Higher values result in a smoother flow line but with more lag; lower values make it more responsive but potentially noisier. Dashboard Position - Default: ‘Top Right’; Range: ‘Top Right’, ‘Top Left’, ‘Bottom Right’, ‘Bottom Left’, ‘Middle Right’, ‘Middle Left’; Description: Determines the placement of the dashboard on the chart. Header Size - Default: ‘Normal’; Range: ‘Tiny’, ‘Small’, ‘Normal’, ‘Large’, ‘Huge’; Description: Sets the text size for the dashboard header. Values Size - Default: ‘Small’; Range: ‘Tiny’, ‘Small’, ‘Normal’, ‘Large’; Description: Sets the text size for the metric values in the dashboard. ✅ Best Use Cases Trend Identification: Identifying the dominant market flow (bullish or bearish) and its strength to trade in the direction of the prevailing trend. Momentum Confirmation: Using the flow strength and acceleration to confirm the conviction behind price movements. Volatility Assessment: Utilizing the turbulence metric to gauge market stability, helping to adjust position sizing or avoid choppy conditions. Reversal Spotting: Watching for divergences between price and flow, or crossovers of the main flow line above/below the zero line, as potential reversal signals, especially when combined with changes in pressure or viscosity. Swing Trading: Leveraging the smoothed flow line to capture medium-term market swings, entering when flow aligns with the desired trade direction and exiting when flow weakens or reverses. Intraday Scalping: Using shorter lookback periods and higher sensitivity to identify quick shifts in flow and turbulence for short-term trading opportunities, particularly in liquid markets. ⚠️ Limitations Lagging Nature: Like many indicators based on moving averages and lookback periods, the main flow line can lag behind rapid price changes, potentially leading to delayed signals. Whipsaws in Ranging Markets: During periods of low volatility or sideways price action (high viscosity, low flow strength), the indicator might produce frequent buy/sell signals (whipsaws) as the flow oscillates around the zero line. Not a Standalone System: While comprehensive, it should be used in conjunction with other forms of analysis (e.g., price action, support/resistance levels, other indicators) and not as a sole basis for trading decisions. Subjectivity in Interpretation: While the dashboard provides quantitative values, the interpretation of “strong” flow, “high” turbulence, or “significant” acceleration can still have a subjective element depending on the trader’s strategy and risk tolerance. 💡 What Makes This Unique Fluid Dynamics Analogy: Its core strength lies in translating complex market interactions into an intuitive fluid dynamics framework, making concepts like momentum, resistance, and pressure easier to visualize and understand. Market View: Instead of focusing on a single aspect (like just momentum or just volatility), it integrates multiple factors (velocity, viscosity, pressure, turbulence) to provide a more comprehensive picture of market conditions. Adaptive Visualization: The dynamic coloring of the flow line and the turbulence background provide immediate, adaptive visual feedback that changes with market conditions. 🔬 How It Works Price Velocity Calculation: The indicator first calculates price velocity by measuring the rate of change of the closing price over a given ‘lookback’ period. The raw velocity is then normalized by the Average True Range (ATR) of the same lookback period. Normalization enables comparison of momentum between assets or timeframes by scaling for volatility. This is the direction and speed of initial price movement. Viscosity Calculation: Market ‘viscosity’ or resistance to price movement is determined by looking at the current ATR relative to its longer-term average (SMA of ATR over lookback * 2). The further the current ATR is above its average, the lower the viscosity (less resistance to price movement), and vice-versa. The script inverts this relationship and bounds it so that rising viscosity means more resistance. Pressure Force Measurement: A ‘pressure’ variable is calculated as a function of the ratio of current volume to its simple moving average, multiplied by the price range (close - open) and normalized by ATR. This is designed to measure the force behind price movement created by volume and intraday price thrusts. This pressure is smoothed by an EMA. Turbulence State Evaluation: A equivalent ‘Reynolds number’ is calculated by dividing the absolute normalized velocity by the viscosity. This is the proclivity of the market to move in a chaotic or orderly fashion. This ‘reynoldsValue’ is smoothed with an EMA to get the ‘turbulenceState’, which indicates if the market is laminar (stable), transitional, or turbulent. Main Flow Derivation: The ‘rawFlow’ is calculated by taking the normalized velocity, dampening its impact based on the ‘viscosity’ and user-input ‘sensitivity’, and orienting it by the sign of the smoothed ‘pressureSmooth’. The ‘rawFlow’ is then put through multiple layers of exponential moving average (EMA) smoothing (with ‘smoothingLength’ and derived values) to reach the final ‘mainFlow’ line. The extensive smoothing is designed to give a smooth and clear visualization of the overall market direction and magnitude. Dashboard Metrics Compilation: Additional metrics like flow acceleration (derivative of mainFlow), and flow continuity (correlation between close and volume) are calculated. All primary components (Flow State, Strength, Viscosity, Turbulence, Pressure, Acceleration, Continuity) are then presented in a user-configurable dashboard for ease of monitoring. 💡 Note: The “Market Fluid Dynamics - Phen” indicator is designed to offer a unique perspective on market behavior by applying principles from fluid dynamics. It’s most effective when used to understand the underlying forces driving price rather than as a direct buy/sell signal generator in isolation. Experiment with the settings, particularly the ‘Base Lookback Period’, ‘Flow Sensitivity’, and ‘Flow Smoothing’, to find what best suits your trading style and the specific asset you are analyzing. Always combine its insights with robust risk management practices.
Pine Script®指標
由PhenLabs提供
2
SynchroTrend Oscillator (STO) [PhenLabs]📊 SynchroTrend Oscillator Version: PineScript™ v5 📌 Description The SynchroTrend Oscillator (STO) is a multi-timeframe synchronization tool that combines trend information from three distinct timeframes into a single, easy-to-interpret oscillator ranging from -100 to +100. This indicator solves the common problem of having to analyze multiple timeframe charts separately by consolidating trend direction and strength across different time horizons. The STO helps traders identify when markets are truly synchronized across timeframes, potentially indicating stronger trend conditions and higher probability trading opportunities. Using either Moving Average crossovers or RSI analysis as the trend definition metric, the STO provides a comprehensive view of market structure that adapts to various trading strategies and market conditions. 🚀 Points of Innovation Triple-timeframe synchronization in a single view eliminates chart switching Dual trend detection methods (MA vs Price or RSI) for flexibility across different markets Dynamic color intensity that automatically increases with signal strength Scaled oscillator format (-100 to +100) for intuitive trend strength interpretation Customizable signal thresholds to match your risk tolerance and trading style Visual alerts when markets reach full synchronization states 🔧 Core Components Trend Scoring System: Calculates a binary score (+1, -1, or 0) for each timeframe based on selected metrics, providing clear trend direction Multi-Timeframe Synchronization: Combines and scales trend scores from all three timeframes into a single oscillator Dynamic Visualization: Adjusts color transparency based on signal strength, creating an intuitive visual guide Threshold System: Provides customizable levels for identifying potentially significant trading opportunities 🔥 Key Features Triple Timeframe Analysis: Synchronizes three user-defined timeframes (default: 60min, 15min, 5min) into one view Dual Trend Detection Methods: Choose between Moving Average vs Price or RSI-based trend determination Adjustable Signal Smoothing: Apply EMA, SMA, or no smoothing to the oscillator output for your preferred signal responsiveness Dynamic Color Intensity: Colors become more vibrant as signal strength increases, helping identify strongest setups Customizable Thresholds: Set your own buy/sell threshold levels to match your trading strategy Comprehensive Alerts: Six different alert conditions for crossing thresholds, zero line, and full synchronization states 🎨 Visualization Oscillator Line: The main line showing the synchronized trend value from -100 to +100 Dynamic Fill: Area between oscillator and zero line changes transparency based on signal strength Threshold Lines: Optional dotted lines indicating buy/sell thresholds for visual reference Color Coding: Green for bullish synchronization, red for bearish synchronization 📖 Usage Guidelines Timeframe Settings Timeframe 1: Default: 60 (1 hour) - Primary higher timeframe for trend definition Timeframe 2: Default: 15 (15 minutes) - Intermediate timeframe for trend definition Timeframe 3: Default: 5 (5 minutes) - Lower timeframe for trend definition Trend Calculation Settings Trend Definition Metric: Default: “MA vs Price” - Method used to determine trend on each timeframe MA Type: Default: EMA - Moving Average type when using MA vs Price method MA Length: Default: 21 - Moving Average period when using MA vs Price method RSI Length: Default: 14 - RSI period when using RSI method RSI Source: Default: close - Price data source for RSI calculation Oscillator Settings Smoothing Type: Default: SMA - Applies smoothing to the final oscillator Smoothing Length: Default: 5 - Period for the smoothing function Visual & Threshold Settings Up/Down Colors: Customize colors for bullish and bearish signals Transparency Range: Control how transparency changes with signal strength Line Width: Adjust oscillator line thickness Buy/Sell Thresholds: Set levels for potential entry/exit signals ✅ Best Use Cases Trend confirmation across multiple timeframes Finding high-probability entry points when all timeframes align Early detection of potential trend reversals Filtering trade signals from other indicators Market structure analysis Identifying potential divergences between timeframes ⚠️ Limitations Like all indicators, can produce false signals during choppy or ranging markets Works best in trending market conditions Should not be used in isolation for trading decisions Past performance is not indicative of future results May require different settings for different markets or instruments 💡 What Makes This Unique Combines three timeframes in a single visualization without requiring multiple chart windows Dynamic transparency feature that automatically emphasizes stronger signals Flexible trend definition methods suitable for different market conditions Visual system that makes multi-timeframe analysis intuitive and accessible 🔬 How It Works 1. Trend Evaluation: For each timeframe, the indicator calculates a trend score (+1, -1, or 0) using either: MA vs Price: Comparing close price to a moving average RSI: Determining if RSI is above or below 50 2. Score Aggregation: The three trend scores are combined and then scaled to a range of -100 to +100 A value of +100 indicates all timeframes show bullish conditions A value of -100 indicates all timeframes show bearish conditions Values in between indicate varying degrees of alignment 3. Signal Processing: The raw oscillator value can be smoothed using EMA, SMA, or left unsmoothed The final value determines line color, fill color, and transparency settings Threshold levels are applied to identify potential trading opportunities 💡 Note: The SynchroTrend Oscillator is most effective when used as part of a comprehensive trading strategy that includes proper risk management techniques. For best results, consider using the oscillator in conjunction with support/resistance levels, price action analysis, and other complementary indicators that align with your trading style.
Pine Script®指標
由PhenLabs提供
Ultimate Moving Average Crossover Indicator by SAMQUANT📈 Ultimate Moving Average Crossover Indicator | All-in-One MA Strategy Unlock the power of multiple moving averages in one versatile indicator designed to give you clear, actionable signals in any market condition. 📌 Key Features: - Supports **all major moving averages**: - **SMA, EMA, WMA, HMA, RMA, DEMA, TEMA**, and more. - Each MA is **fully customizable** with different lengths and types for ultimate flexibility. - **Binary Long/Short signals** based on crossover logic—perfect for alerts, strategies, or discretionary trading. - **Dynamic background coloring**: - **Green** for bullish trends - **Red** for bearish trends Quickly gauge market direction at a glance. --- 🚀 Why Use This Indicator? ✅ Combines the strength of all major MA types ✅ Customizable to fit any trading style—scalping, swing, or trend following ✅ Built-in alerts ready for your next trade ✅ Visually intuitive with built-in signal clarity ✅ Excellent tool for **confluence-based** strategies --- Great trades start with great tools. Clarity, precision, and flexibility—this indicator brings it all to your charts. Trade smarter, not harder. --- > ⚠️ **Disclaimer:** This script is intended for **educational and informational purposes only**. It does not constitute financial advice. Past performance is not indicative of future results. Always practice sound risk management and test strategies thoroughly before using real capital.
Pine Script®指標
由samxx_05提供