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Wavetrend strategy with trading session for any time chartHello there Today I am glad to provide you a strategy based on the wave trend oscillator. If you want to use it as an indicator, just disable long and short to not make any shops. It works on all time frames. The way it works its like an RSI . We have overbought and oversold levels, and together with a channel and length we calculate the wave trend. And then like in RSI, when we cross those lines we buy or sell depending on which lines we cross. For risk management, so far its not implemented, but it can be done in many ways. The only thing I applied is to always close a trade at the end of friday day. At the same time it can be applied the rule to sell when % of equity is lost, or at the end of a trading session like london,neywork and so on. For any questions or doubts, let me know. Hope you enjoy it :)
Strategi Pine Script®
oleh SoftKill21
1
Momentum ArrowsThis simple indicators paints the Momentum based on Stochastic, RSI or WaveTrend onto the Price Chart by showing Green or Red arrows. In the settings it can be selected which indicator is used, Stochastic is selected by default. Length of the arrows is determined by the strength of the momentum: Stochastic: Difference between D and K RSI: Difference from RSI-50 WaveTrend: Difference between the Waves (Thanks to @LazyBear for the WaveTrend inspiration) PS: If anyone has an idea how to conditionally change the color of the arrows, then please let me know - that would be the icing on the cake. Then it would be possible to indicate Overbought/Oversold levels with different colors. Unfortunately it currently seems not to be possible to dynamically change the arrow colour.
Penunjuk Pine Script®
oleh wugamlo
6
TradingGroundhog - Strategy & Fractal V1#-- Public Strategy - No Repaint - Fractals -- Short term Here I come with another script, more simple than Wavetrend V1. You will love it. #-- Synopsis -- Another simple idea, on a small time frame (15 min) we buy when the opening price goes below a Bottom fractals and sell when it goes over a Top fractals, but as this script do not use Wavetrends. You should stop by your self to use the script during long lasting downtrends. I developed the strategy using BTC /EUR 3 MIN BINANCE but it can be applied to many other cryptos, I don't know for forex or others. You can use it for short term (to a month of uptrend) and automated trading. #-- Graph reading -- And now, how to read it ? Fractals: Yellow Flags occur when the opening price goes below a Bottom fractal , it means Buy. White Flags appear when the opening price goes over a Top fractal , it means Sell. #-- Parameters -- *** Parameters have been intensively optimized using 10 cryptocurrency markets in order to have potent efficiency for each of them. I would recommend to only change the Can Be touch parameter. For the others, I don't recommend any modifications. The idea behind the script is to be able to switch between markets without having to optimize parameters, less work, easy to target active crypto and therefor limit the risks. *** Can be touch : 'Filter fractals' : Activate or Disable the filtering fractal operation. If Enable, buy during less risky periods. (Activate is often better) Can be touch but not necessary : 'VolumeMA' : The Volume corrector used by the fractals 'Extreme window' : The number of price individuals to look for if we want to remove extreme fractals. Not to touch : 'Long Sop Loss (%)' : The minimal difference of price between a Fractal bottom and the opening price to buy. #-- Time frame -- Should be used with the following time frames depending on the necessity: 1 MIN 3 MIN (Preferred with the parameters set) 5 MIN #-- Last words -- The script can be set up to send Tradingview signals to 3comma just by adding comment = " " in strategy.close_all() and strategy.entry(). Good trades ! Disclaimer (As it should always be one to any script) *** This script is intended for and only to be used for personal purposes only. No such information provided by it constitutes advice or a recommendation for any investment or trading strategy for any specific person. There is no guarantee presented or implied as to the accuracy of specific forecasts, projections, or predictive statements offered by the script. Users of the script agree that its original developer does not take responsibility for any of your investment decisions. Please seek professional advice before trading. *** # Here are the results from the 20rst of September 2021 with 100% of equity on the BTC /EUR 3 Min and with a capital of 10 000 EUR. So almost, one month. # As I saw, it goes from +30% to more than +160% (the great SHIB) depending on the selected crypto. It may be negative if you spot a downtrend.
Strategi Pine Script®
oleh UnknownUnicorn27666852
4
SB_Wavetrend_OscillatorA take on LazyBear's Wavetrend_Oscillator The idea is bit modified. Original Idea: When the oscillator is above the overbought band (red lines) and crosses down the signal (dotted line), it is usually a good SELL signal. Similarly, when the oscillator crosses above the signal when below the Oversold band (green lines), it is a good BUY signal. Modified Idea: Carrying the original idea, if the oscillator crosses the overbought band (red lines) and crosses down the signal (dotted line) twice without crossing the Oversold band (green lines) and crosses above the signal (dotted line), a buy or sell signal will take place when the oscillator crosses the dotted line and the value of oscillator is >0(if sell order is to be placed) and <0(if buy order is to be placed). For the original idea you can refer to: Let me know if any refinements could improve the oscillator.
Strategi Pine Script®
oleh SudeepBisht
2
MFx Radar (Money Flow x-Radar)Description: MFx Radar is a precision-built multi-timeframe analysis tool designed to identify high-probability trend shifts and accumulation/distribution events using a combination of WaveTrend dynamics, normalized money flow, RSI, BBWP, and OBV-based trend biasing. Multi-Timeframe Trend Scanner Analyze trend direction across 5 customizable timeframes using WaveTrend logic to produce a clear trend consensus. Smart Money Flow Detection Adaptive hybrid money flow combines CMF and MFI, normalized across lookback periods, to pinpoint shifts in accumulation or distribution with high sensitivity. Event-Based Labels & Alerts Minimalist "Accum" and "Distr" text labels appear at key inflection points, based on hybrid flow flips — designed to highlight smart money moves without clutter. Trigger & Pattern Recognition Built-in logic detects anchor points, trigger confirmations, and rare "Snake Eye" formations directly on WaveTrend, enhancing trade timing accuracy. Visual Dashboard Table A real-time table provides score-based insight into signal quality, trend direction, and volume behavior, giving you a full picture at a glance. MFx Radar helps streamline discretionary and system-based trading decisions by surfacing key confluences across price, volume, and momentum all while staying out of your way visually. How to Use MFx Radar MFx Radar is a multi-timeframe market intelligence tool designed to help you spot trend direction, momentum shifts, volume strength, and high-probability trade setups using confluence across price, flow, and timeframes. Where to find settings To see the full visual setup: After adding the script, open the Settings gear. Go to the Inputs tab and enable: Show Trigger Diamonds Show WT Cross Circles Show Anchor/Trigger/Snake Eye Labels Show Table Show OBV Divergence Show Multi-TF Confluence Show Signal Score Then, go to the Style tab to adjust colors and fills for the wave plots and hybrid money flow. (Use published chart as a reference.) What the Waves and Colors Mean Blue WaveTrend (WT1 / WT2). These are the main momentum waves. WT1 > WT2 = bullish momentum WT1 < WT2 = bearish momentum Above zero = bullish bias Below zero = bearish bias When WT1 crosses above WT2, it often marks the beginning of a move — these are shown as green trigger diamonds. VWAP-MACD Line The yellow fill helps spot volume-based momentum. Rising = trend acceleration Use together with BBWP (bollinger band width percentile) and hybrid money flow for confirmation. Hybrid Money Flow Combines CMF and MFI, normalized and smoothed. Green = accumulation Red = distribution Transitions are key — especially when price moves up, but money flow stays red (a divergence warning). This is useful for spotting fakeouts or confirming smart money shifts. Orange Vertical Highlights Shows when price is rising, but money flow is still red. Often a sign of hidden distribution or "exit pump" behavior. Table Dashboard (Bottom-Right) BBWP (Volatility Pulse) When BBWP is low (<20), it signals consolidation — a breakout is likely to follow. Use this with ADX and WaveTrend position to anticipate directional breakouts. Trend by ADX Shows whether the market is trending and in which direction. Combined with money flow and RSI, this gives strong confirmation on breakouts. OBV HTF Bias Gives higher timeframe pressure (bullish/bearish/neutral). Helps avoid taking counter-trend trades. Pattern Labels (WT-Based) A = Anchor Wave — WT hitting oversold T = Trigger Wave — WT turning back up after anchor 👀 = Snake Eyes — Rare pattern, usually signaling strong reversal potential These help in timing entries, especially when they align with other signals like BBWP breakouts, confluence, or smart money flow flips. Multi-Timeframe (MTF) Consensus The system checks WaveTrend on 5 different timeframes and gives: Color-coded signals on each TF A final score: “Mostly Up,” “Mostly Down,” or “Mixed” When MTFs align with wave crosses, BBWP expansion, and hybrid money flow shifts, the probability of sustained move is higher. Divergence Spotting (Advanced Tip) Watch for:Price rising while money flow is red → Possible trap / early exit Price dropping while money flow is green → Early accumulation Combine this with anchor-trigger patterns and MTF trend support for spotting bottoms or tops early. Final Tips Use WT trigger crosses as initial signal. Confirm with money flow direction + color flip Look at BBWP for breakout timing. Use table as your decision dashboard Favor trades that align with MTF consensus
Penunjuk Pine Script®
oleh renderingnature1
1
GT 5.1 Strategy═════════════════════════════════════════════════════════════════════════ █ OVERVIEW People often look an indicator in their technical analysis to enter a position. We may also need to look at the signals of one or more indicators to verify the signals given by some indicators. In this context, I developed a strategy to test whether it really works by choosing some of the indicators that capture trend changes with the same characteristics. Also, since the subject is to catch the trend change, I thought it would be right to include an indicator using the heikin ashi logic. By averaging and smoothing the market noise, Heiken Ashi makes it easier to detect the direction of the trend helps to see possible reversal points on the chart. However, it should be noted that Heiken Ashi is a lagging indicator. I picked 5 different indicators (but their purpose are similar) and combined them to produce buy and sell signals based on your choice(not repaint). First of all let's get some information about our indicators. So you will understand me why i picked these indicators and what is the meaning of their signals. 1 — Coral Trend Indicator by LazyBear Coral Trend Indicator is a linear combination of moving averages, all obtained by a triple or higher order exponential smoothing. The indicator comes with a trend indication which is based on the normalized slope of the plot. the usage of this indicator is simple. When the color of the line is green that means the market is in uptrend. But when the color is red that means the market is in downtrend. As you see the original indicator it is simple to find is it in uptrend or downtrend. So i added a code to find when the color of the line change. When it turns green to red my script giving sell signals, when it turns red to green it gives buy signals. I hide the candles to show you more clearly what is happening when you choose only Coral Strategy. But sometimes it is not enough only using itself. Even if green dots turn to red it continues in uptrend. So we need a to look another indicator to approve our signal. 2 — SSL channel by ErwinBeckers Known as the SSL , the Semaphore Signal Level channel is an indicator that combines moving averages to provide you with a clear visual signal of price movement dynamics. In short, it's designed to show you when a price trend is forming. This indicator creates a band by calculating the high and low values ​​according to the determined period. Simply if you decide 10 as period, it calculates a 10-period moving average on the latest 10 highs. Calculate a 10-period moving average on the latest 10 lows. If the price falls below the low band, the downtrend begins, if the price closes above the high band, the uptrend begins. Lets look the original form of indicator and learn how it using. If the red line is below and the green band is above, it means that we are in uptrend, and if it is on the opposite side, it means that we are in downtrend. Therefore, it would be logical to enter a position where the trend has changed. So i added a code to find when the crossover has occured. As you see in my strategy, it gives you signals when the trend has changed. But sometimes it is not enough only using this indicator itself. So lets look 2 indicator together in one chart. Look circle SSL is saying it is in downtrend but Coral is saying it has entered in uptrend. if we just look to coral signal it can misleads us. So it can be better to look another indicator for validating our signals. 3 — Heikin Ashi RSI Oscillator by JayRogers The Heikin-Ashi technique is used by technical traders to identify a given trend more easily. Heikin-Ashi has a smoother look because it is essentially taking an average of the movement. There is a tendency with Heikin-Ashi for the candles to stay red during a downtrend and green during an uptrend, whereas normal candlesticks alternate color even if the price is moving dominantly in one direction. This indicator actually recalculates the RSI indicator with the logic of heikin ashi. Due to smoothing, the bars are formed with a slight lag, reflecting the trend rather than the exact price movement. So lets look the original version to understand more clearly. If red bars turn to green bars it means uptrend may begin, if green bars turn to red it means downtrend may begin. As you see HARSI giving lots of signal some of them is really good but some of them are not very well. Because it gives so much signals Now i will change time period and lets look same chart again. Now results are better because of heikin ashi's logic. it is not suitable for day traders, it gives more accurate result when using the time period is longer. But it can be useful to use this indicator in short time periods using with other indicators. So you may catch the trend changes more accurately. 4 — MACD DEMA by ToFFF This indicator uses a double EMA and MACD algorithm to analyze the direction of the trend. Though it might seem a tough task to manage the trades with the help of MACD DEMA once you know how the proper way to interpret the signal lines, it will be an easy task. This indicator also smoothens the signal lines with the time series algorithm which eventually makes the higher time frame important. So, expecting better results in the lower time frame can result in big losses as the data reading from the MACD DEMA will not be accurate. In order to understand the function of this indicator, you have to know the functions of the EMA also. The exponential moving average tends to give more priority to the recent price changes. So, expecting better results when the volatility is very high is a very risky approach to trade the market. Moreover, the MACD has some lagging issues compared to the EMA, so it is super important to use a trading method that focuses on the higher time frame only. What does MACD 12 26 Close 9 mean? When the DEMA-9 crosses above the MACD(12,26), this is considered a bearish signal. It means the trend in the stock – its magnitude and/or momentum – is starting to shift course. When the MACD(12,26) crosses above the DEMA-9, this is considered a bullish signal. Lets see this indicator on Chart. When the blue line crossover red line it is good time to buy. As you see from the chart i put arrows where the crossover are appeared. When the red line crossover blue line it is good time to sell or exit from position. 5 — WaveTrend Oscillator by LazyBear This is a technical indicator that creates high and low bands between two values. It then creates a trend indicator that draws waves with highs and lows within these boundaries. WaveTrend is a widely used indicator for finding direction of an asset. Calculation period: number of candles used to calculate WaveTrend, defaults to 10. Averaging period: number of candles used to average WaveTrend, defaults to 21. As you see in chart when the lines crossover occured my strategy gives buy or sell signals. ═════════════════════════════════════════════════════════════════════════ █ HOW TO USE I hope you understand how the indicators I mentioned above work and what they are used for. Now, I will explain in detail how to use the strategy I have created. When you enter the settings section, you will see 5 types of indicators. If you want to use the signals of the indicators, simply tick the box next to the indicators. Also, under each option there is an area where you can set the "lookback". This setting is a field that will make the signals overlap when you select more than one option. If you are going to trade with only one option, you should make sure that this field is 0. Otherwise, it may continue to generate as many signals as you choose. Lets see in chart for easy understanding. As you see chart, if i chose only HARSI with lookback 0 (HARSI and CORAL should be 1 minumum because of algorithm-we looking 1 bar before, others 0 because we are looking crossovers), it will give signals only when harsı bar's color changed. But when i changed Lookback as 7 it will be like this in chart. Now i will choose 2 indicator with settings of their lookback 0. As you see it will give signals when both of them occurs same time. But HARSI is an indicator giving very early signal so we can enter position 5-6 bars after the first bar color change. So i will change HARSI Lookback settings as 7. Lets look what happens when we use lookback option. So it wil be useful to change lookback settings to find best signals in each time period and in each symbol. But it shouldnt be too high. Because you can be late to catch trend's starting. this is an image of MACD and WAVE trend used and lookback option are both 6. Now lets see an example with 3 options are chosen with lookback option 11-1-5 Now lets talk about indicators settings. After strategy options you will see each indicators settings, you can change their settings as you desired. So each indicators signal will be changed according to your adjustment. I left strategy options with default settings. You can change it manually as if you want. ═════════════════════════════════════════════════════════════════════════ █  LIMITATIONS: Don't rely on non-standard charts results. For example Heikin Ashi is a technical analysis method used with the traditional candlestick chart.Heikin Ashi vs. Candlestick Chart: The decisive visual difference between Heikin Ashi and the traditional chart is that Heikin Ashi flattens the traditional candlestick chart using a modified formula. The primary advantage of Heikin Ashi is that it makes the chart more reader-friendly and helps users identify and analyze trends . Because Heikin Ashi provides averaged price information rather than real-time price and reacts slowly to volatility — not suitable for scalpers and high-frequency traders. I added HARSI indicator as a supportive signal because it is useful with using CORAL and SSL channel indicators. If you change your candle types to Heikin Ashi , your profit will change in good way but dont rely on it. ═════════════════════════════════════════════════════════════════════════ █  THANKS: Special thanks to authors of the scripts that i used. @LazyBear and @ErwinBeckers and @JayRogers and @ToFFF ═════════════════════════════════════════════════════════════════════════ █  DISCLAIMER Any trade decisions you make are entirely your own responsibility.
Strategi Pine Script®
oleh iori86
3
Minimal Godmode 2.1// Acknowledgments: // Original Godmode Authors: // @Legion, @LazyBear, @Ni6HTH4wK, @xSilas // Drop a line if you use or modify this code. // Godmode 3.1.4: @SNOW_CITY // Godmode 3.2: @sco77m4r7in and @oh92 // Godmode3.2+LSMA: @scilentor // Godmode 4.0.0-4.0.1: @chrysopoetics // Jurik Moving Average: @everget // Constance Brown Composite Index RSI: @LazyBear // Wavetrend Oscillator: @fskrypt // TTM Squeeze: @Greeny // True TSI/RSI: @cI8DH and @chrysopoetics // Laguerre RSI (Self-Adjusting Alpha with Fractals Energy): @everget // RSI Shaded: @mortdiggiddy // Minimal Godmode v2.0: // 6 BTC pairs/exchanges (instead of 11) to reduce loading time from the pinescript security() function // Volume Composite for engine calculation // TTM Squeeze on Wavetrend Signal // Constance Brown Composite Index RSI (CBCI) // TrueTSI (Godmode 4.0.0 implementation) // Laguerre RSI (LRSI) // Minimal Godmode v2.1: // Removed TTM Squeeze and Volume Composite // EMA for Wavetrend Signal // Multi-exchange for BTC no longer the default // mg engine toggle for CBCI, Laguerre RSI, and TTSI // Wavetrend Histogram component toggle
Penunjuk Pine Script®
oleh auroagwei
8
NEURAL FLOW INDEX — Core Energy • Momentum Stream • Pulse SyncNeural Flow Index (NFI) — Advanced Triple-Layer Reversal Framework The Neural Flow Index (NFI) is a next-generation market oscillator designed to reveal the hidden synchronization between trend energy, cyclical momentum, and internal pulse dynamics. It merges three powerful analytical layers into a single, normalized view: Core Energy Curve (based on RSO logic) — captures structural trend bias and volatility expansion. Momentum Stream (WaveTrend algorithm) — visualizes cyclical motion of price waves. Pulse Sync (Stochastic RSI adaptation) — measures short-term momentum rhythm and overextension. Each layer feeds into a unified flow model that adapts to both trend-following and reversal conditions. The goal is not to chase every fluctuation, but to sense where momentum, direction, and volatility converge into true inflection points. Conceptual Mechanics The oscillator translates complex market behavior into an elegant, multi-phase signal system: Core Energy Curve (RSO foundation): A smoothed dynamic field representing the overall strength and direction of market pressure. Green energy indicates expansion (bullish dominance); red energy reflects contraction (bearish decay). Momentum Stream (WaveTrend): The teal line functions like an electro-wave, oscillating through phases of expansion and exhaustion. It provides the heartbeat of the market — smooth, rhythmic, and beautifully cyclic. Pulse Sync (Stochastic RSI): The purple line acts as the market’s nervous pulse, reacting to micro-momentum changes before the larger trend adjusts. It identifies micro-tops and micro-bottoms that precede major trend shifts. When these three forces align, they create high-probability reversal zones known as Neural Nodes — regions where energy, momentum, and rhythm converge. Trading Logic Potential Entry Zones: When the purple Pulse Sync line crosses the green Momentum Stream near the lower or upper bounds of the oscillator, a potential turning point forms. Yet, these crossovers are only validated when the Core Energy histogram (RSO) simultaneously supports the same direction — confirming that energy and rhythm are synchronized. Histogram Confirmation: The histogram is the “voice” of the oscillator. Rising green volume within the histogram during a Pulse-Momentum crossover suggests a legitimate upward reversal. Conversely, expanding red energy during an upper-band cross indicates momentum exhaustion and an early short-side opportunity. Neutral Zones: When all three layers flatten near the zero line, the market enters an equilibrium phase — no clear trend dominance, ideal for patience and re-entry planning. | Layer | Representation | Color | Function | | --------------------- | ------------------- | ----------------- | ------------------------------ | | **Core Energy Curve** | Area / Histogram | Lime-Red gradient | Trend bias & volatility energy | | **Momentum Stream** | WaveTrend line | Teal | Cyclical flow of price | | **Pulse Sync** | Stochastic RSI line | Purple | Short-term momentum rhythm | Interpretation Summary Converging Waves: Trend, momentum, and pulse move together → strong continuation. Diverging Waves: Pulse or Momentum decouple from Core Energy → early reversal warnings. Histogram Expansion: Confirms direction and strength of the new wave. Crossovers at Extremes: Potential entries, especially when confirmed by energy alignment. 🪶 Philosophy Behind NFI The Neural Flow Index is not just a technical indicator — it’s a behavioral visualization system. Instead of focusing on lagging confirmations, it captures the neural pattern of price motion: how liquidity flows, contracts, and expands through time. It bridges the gap between pure mathematics and market intuition — giving traders a cinematic, harmonic view of energy transition inside price structure.
Penunjuk Pine Script®
oleh ozgurzari
WT + Stoch RSI Reversal Combo📊MR.Z RSI : WT + Stochastic RSI Reversal Combo This custom indicator combines WaveTrend oscillator and Stochastic RSI to detect high-confidence market reversal points, filtering signals so they only appear when both indicators align. 🔍 Core Components: ✅ WaveTrend Oscillator Based on smoothed deviation from EMA (similar to TCI logic) Plots: WT1 (main line) WT2 (signal line = SMA of WT1) Uses overbought/oversold thresholds (default: ±53) to filter signals ✅ Stochastic RSI Momentum oscillator based on RSI's stochastic value Plots: %K: smoothed Stoch of RSI %D: smoothed version of %K Adjustable oversold/overbought thresholds (default: 20/80) 🔁 Combined Reversal Signal Logic: 🔼 Buy Signal WT1 crosses above WT2 below WT oversold level (e.g., -53) %K crosses above %D below Stoch RSI oversold level (e.g., 20) 🔽 Sell Signal WT1 crosses below WT2 above WT overbought level (e.g., 53) %K crosses below %D above Stoch RSI overbought level (e.g., 80) 🔔 Signals are only plotted and alerted if both conditions are true. 📌 Features: Toggle on/off: WaveTrend lines and histogram Stochastic RSI Combined Buy/Sell signals Horizontal reference lines (±100, OB/OS) Fully customizable smoothing lengths and thresholds Signal plots: ✅ Green up-triangle = Combo Buy ✅ Red down-triangle = Combo Sell Optional: Circle/cross markers for WT-only and Stoch-only signals 🔔 Built-in alerts for Buy/Sell signals 📈 Use Cases: Reversal Trading: Wait for both indicators to confirm momentum shift Entry Filter: Use in combination with trend indicators (like EMA) Scalping or Swing: Works on intraday and higher timeframes
Penunjuk Pine Script®
oleh grigory84
MLExtensions_CoreLibrary "MLExtensions_Core" A set of extension methods for a novel implementation of a Approximate Nearest Neighbors (ANN) algorithm in Lorentzian space, focused on computation. normalizeDeriv(src, quadraticMeanLength)   Returns the smoothed hyperbolic tangent of the input series.   Parameters:      src (float) : The input series (i.e., the first-order derivative for price).      quadraticMeanLength (int) : The length of the quadratic mean (RMS).   Returns: nDeriv The normalized derivative of the input series. normalize(src, min, max)   Rescales a source value with an unbounded range to a target range.   Parameters:      src (float) : The input series      min (float) : The minimum value of the unbounded range      max (float) : The maximum value of the unbounded range   Returns: The normalized series rescale(src, oldMin, oldMax, newMin, newMax)   Rescales a source value with a bounded range to anther bounded range   Parameters:      src (float) : The input series      oldMin (float) : The minimum value of the range to rescale from      oldMax (float) : The maximum value of the range to rescale from      newMin (float) : The minimum value of the range to rescale to      newMax (float) : The maximum value of the range to rescale to   Returns: The rescaled series getColorShades(color)   Creates an array of colors with varying shades of the input color   Parameters:      color (color) : The color to create shades of   Returns: An array of colors with varying shades of the input color getPredictionColor(prediction, neighborsCount, shadesArr)   Determines the color shade based on prediction percentile   Parameters:      prediction (float) : Value of the prediction      neighborsCount (int) : The number of neighbors used in a nearest neighbors classification      shadesArr (array) : An array of colors with varying shades of the input color   Returns: shade Color shade based on prediction percentile color_green(prediction)   Assigns varying shades of the color green based on the KNN classification   Parameters:      prediction (float) : Value (int|float) of the prediction   Returns: color color_red(prediction)   Assigns varying shades of the color red based on the KNN classification   Parameters:      prediction (float) : Value of the prediction   Returns: color tanh(src)   Returns the the hyperbolic tangent of the input series. The sigmoid-like hyperbolic tangent function is used to compress the input to a value between -1 and 1.   Parameters:      src (float) : The input series (i.e., the normalized derivative).   Returns: tanh The hyperbolic tangent of the input series. dualPoleFilter(src, lookback)   Returns the smoothed hyperbolic tangent of the input series.   Parameters:      src (float) : The input series (i.e., the hyperbolic tangent).      lookback (int) : The lookback window for the smoothing.   Returns: filter The smoothed hyperbolic tangent of the input series. tanhTransform(src, smoothingFrequency, quadraticMeanLength)   Returns the tanh transform of the input series.   Parameters:      src (float) : The input series (i.e., the result of the tanh calculation).      smoothingFrequency (int)      quadraticMeanLength (int)   Returns: signal The smoothed hyperbolic tangent transform of the input series. n_rsi(src, n1, n2)   Returns the normalized RSI ideal for use in ML algorithms.   Parameters:      src (float) : The input series (i.e., the result of the RSI calculation).      n1 (simple int) : The length of the RSI.      n2 (simple int) : The smoothing length of the RSI.   Returns: signal The normalized RSI. n_cci(src, n1, n2)   Returns the normalized CCI ideal for use in ML algorithms.   Parameters:      src (float) : The input series (i.e., the result of the CCI calculation).      n1 (simple int) : The length of the CCI.      n2 (simple int) : The smoothing length of the CCI.   Returns: signal The normalized CCI. n_wt(src, n1, n2)   Returns the normalized WaveTrend Classic series ideal for use in ML algorithms.   Parameters:      src (float) : The input series (i.e., the result of the WaveTrend Classic calculation).      n1 (simple int)      n2 (simple int)   Returns: signal The normalized WaveTrend Classic series. n_adx(highSrc, lowSrc, closeSrc, n1)   Returns the normalized ADX ideal for use in ML algorithms.   Parameters:      highSrc (float) : The input series for the high price.      lowSrc (float) : The input series for the low price.      closeSrc (float) : The input series for the close price.      n1 (simple int) : The length of the ADX. regime_filter(src, threshold, useRegimeFilter)   Parameters:      src (float)      threshold (float)      useRegimeFilter (bool) filter_adx(src, length, adxThreshold, useAdxFilter)   filter_adx   Parameters:      src (float) : The source series.      length (simple int) : The length of the ADX.      adxThreshold (int) : The ADX threshold.      useAdxFilter (bool) : Whether to use the ADX filter.   Returns: The ADX. filter_volatility(minLength, maxLength, sensitivityMultiplier, useVolatilityFilter)   filter_volatility   Parameters:      minLength (simple int) : The minimum length of the ATR.      maxLength (simple int) : The maximum length of the ATR.      sensitivityMultiplier (float) : Multiplier for the historical ATR to control sensitivity.      useVolatilityFilter (bool) : Whether to use the volatility filter.   Returns: Boolean indicating whether or not to let the signal pass through the filter.
Perpustakaan Pine Script®
oleh viorel8
Gaussian RSI For Loop [TrendX_]The Gaussian RSI For Loop indicator is a sophisticated tool designed for trend-following traders seeking to identify strong uptrends in the market. By integrating a Gaussian and Weighted-MA (GWMA) with the Relative Strength Index (RSI), this indicator employs a loop-based scoring system to provide clear signals for potential trading opportunities. The combination of Gaussian smoothing techniques and overbought/oversold filtering enhances the indicator's ability to capture significant price movements while reducing noise, making it an optimal choice for traders aiming to capitalize on robust upward trends. 💎 KEY FEATURES Gaussian Weighted Moving Average (GWMA): Smooths price data to reduce noise and enhance responsiveness to significant price changes. Filtered RSI: Applies the RSI to Gaussian-filtered data, allowing for more accurate momentum readings. Wavetrend Analysis: Calculates the difference between the Filtered RSI and its short-term moving average, providing additional insights into momentum shifts. Loop-Based Scoring System: Evaluates the strength and direction of uptrends through a systematic analysis of the Filtered RSI against defined thresholds. ⚙️ USAGES Identifying Strong Uptrends: Traders can use this indicator to pinpoint periods of strong upward momentum, helping them make informed decisions about entering long positions and its exits. Trend and Signal Confirmation: The Score confirms Long and Exit signals which traders can see through the Dots on the Gaussian RSI. 🔎 BREAKDOWN Gaussian-Filtered Data: The first component of the Gaussian RSI For Loop is the application of a GWMA to the sourced price data. This smoothing technique uses weighted averages based on a Gaussian distribution, which emphasizes more recent prices while diminishing the impact of older prices. This GWMA effectively reduces market noise, allowing traders to focus on significant price movements. By adjusting weights using sigma parameters, traders can fine-tune the sensitivity of the indicator, making it more responsive to genuine market trends while filtering out minor fluctuations that could lead to misleading signals. Filtered RSI: Next, the RSI is applied to the Gaussian-filtered data. The RSI measures the speed and change of price movements, providing insights into overbought or oversold conditions. By applying the RSI to smoothed price data, traders obtain a clearer view of momentum without the distortion caused by sudden price spikes or drops. This results in more reliable readings that help identify potential trend reversals or continuations. Wavetrend Analysis: The Wavetrend component calculates the difference between the Filtered RSI and its short-term moving average (MA). This difference serves as an additional momentum indicator. When the Filtered RSI is above its short-term MA, it suggests that upward momentum is strengthening; conversely, when it falls below, it indicates weakening momentum. This analysis helps traders confirm whether an uptrend is gaining strength or losing traction. Loop-Based Scoring System: Range Analysis: The system evaluates the Filtered RSI by comparing its current value against overbought (OB) and oversold (OS) thresholds over a defined range. This systematic approach ensures that each value within this range contributes to understanding overall trend strength. Score Calculation: As the loop iterates through values within the defined range, it adjusts a score based on whether the current Filtered RSI and its previous values are higher or lower than established OB and OS levels. This scoring mechanism quantifies trend strength and direction. Strong Uptrend Trigger: A strong uptrend signal is generated when the score exceeds a predefined Score Threshold (Long). This indicates that bullish momentum is robust enough to warrant entry into long positions. None Trend: Conversely, if the score falls below the Score Threshold (Short), it suggests that upward momentum has weakened significantly, signaling potential exit points and it can be consolidated or downtrend. DISCLAIMER This indicator is not financial advice, it can only help traders make better decisions. There are many factors and uncertainties that can affect the outcome of any endeavor, and no one can guarantee or predict with certainty what will occur. Therefore, one should always exercise caution and judgment when making decisions based on past performance.
Penunjuk Pine Script®
oleh TrendXvn
Mad_MATHLibrary "MAD_MATH" This is a mathematical library where I store useful kernels, filters and selectors for the different types of computations. This library also contains opensource code from other scripters. Future extensions are very likely, there are some functions I would like to add, but I have to wait for approvals so i can include them. Ehlers_EMA(_src, _length)   Calculates the Ehlers Exponential Moving Average (Ehlers_EMA)   Parameters:      _src (float) : The source series for calculation      _length (simple int) : The length for the Ehlers EMA   Returns: The Ehlers EMA value Ehlers_Gaussian(_src, _length)   Calculates the Ehlers Gaussian Filter   Parameters:      _src (float) : The source series for calculation      _length (simple int) : The length for the Ehlers Gaussian Filter   Returns: The Ehlers Gaussian Filter value Ehlers_supersmoother(_src, _length)   Calculates the Ehlers Supersmoother   Parameters:      _src (float) : The source series for calculation      _length (simple int) : The length for the Ehlers Supersmoother   Returns: The Ehlers Supersmoother value Ehlers_SMA_fast(_src, _length)   Calculates the Ehlers Simple Moving Average (SMA) Fast   Parameters:      _src (float) : The source series for calculation      _length (simple int) : The length for the Ehlers SMA Fast   Returns: The Ehlers SMA Fast value Ehlers_EMA_fast(_src, _length)   Calculates the Ehlers Exponential Moving Average (EMA) Fast   Parameters:      _src (float) : The source series for calculation      _length (simple int) : The length for the Ehlers EMA Fast   Returns: The Ehlers EMA Fast value Ehlers_RSI_fast(_src, _length)   Calculates the Ehlers Relative Strength Index (RSI) Fast   Parameters:      _src (float) : The source series for calculation      _length (simple int) : The length for the Ehlers RSI Fast   Returns: The Ehlers RSI Fast value Ehlers_Band_Pass_Filter(_src, _length)   Calculates the Ehlers BandPass Filter   Parameters:      _src (float) : The source series for calculation      _length (simple int) : The length for the Ehlers BandPass Filter   Returns: The Ehlers BandPass Filter value Ehlers_Butterworth(_src, _length)   Calculates the Ehlers Butterworth Filter   Parameters:      _src (float) : The source series for calculation      _length (simple int) : The length for the Ehlers Butterworth Filter   Returns: The Ehlers Butterworth Filter value Ehlers_Two_Pole_Gaussian_Filter(_src, _length)   Calculates the Ehlers Two-Pole Gaussian Filter   Parameters:      _src (float) : The source series for calculation      _length (simple int) : The length for the Ehlers Two-Pole Gaussian Filter   Returns: The Ehlers Two-Pole Gaussian Filter value Ehlers_Two_Pole_Butterworth_Filter(_src, _length)   Calculates the Ehlers Two-Pole Butterworth Filter   Parameters:      _src (float) : The source series for calculation      _length (simple int) : The length for the Ehlers Two-Pole Butterworth Filter   Returns: The Ehlers Two-Pole Butterworth Filter value Ehlers_Band_Stop_Filter(_src, _length)   Calculates the Ehlers Band Stop Filter   Parameters:      _src (float) : The source series for calculation      _length (simple int) : The length for the Ehlers Band Stop Filter   Returns: The Ehlers Band Stop Filter value Ehlers_Smoother(_src)   Calculates the Ehlers Smoother   Parameters:      _src (float) : The source series for calculation   Returns: The Ehlers Smoother value Ehlers_High_Pass_Filter(_src, _length)   Calculates the Ehlers High Pass Filter   Parameters:      _src (float) : The source series for calculation      _length (simple int) : The length for the Ehlers High Pass Filter   Returns: The Ehlers High Pass Filter value Ehlers_2_Pole_High_Pass_Filter(_src, _length)   Calculates the Ehlers Two-Pole High Pass Filter   Parameters:      _src (float) : The source series for calculation      _length (simple int) : The length for the Ehlers Two-Pole High Pass Filter   Returns: The Ehlers Two-Pole High Pass Filter value pr(_src, _length)   pr Calculates the percentage rank (PR) of a value within a range.   Parameters:      _src (float) : The source value for which the percentage rank is calculated. It represents the value to be ranked within the range.      _length (simple int) : The _length of the range over which the percentage rank is calculated. It determines the number of bars considered for the calculation.   Returns: The percentage rank (PR) of the source value within the range, adjusted by adding 50 to the result. smma(_src, _length)   Calculates the SMMA (Smoothed Moving Average)   Parameters:      _src (float) : The source series for calculation      _length (simple int)   Returns: The SMMA value hullma(_src, _length)   Calculates the Hull Moving Average (HullMA)   Parameters:      _src (float) : The source series for calculation      _length (simple int) : The _length of the HullMA   Returns: The HullMA value tma(_src, _length)   Calculates the Triple Moving Average (TMA)   Parameters:      _src (float) : The source series for calculation      _length (simple int) : The _length of the TMA   Returns: The TMA value dema(_src, _length)   Calculates the Double Exponential Moving Average (DEMA)   Parameters:      _src (float) : The source series for calculation      _length (simple int) : The _length of the DEMA   Returns: The DEMA value tema(_src, _length)   Calculates the Triple Exponential Moving Average (TEMA)   Parameters:      _src (float) : The source series for calculation      _length (simple int) : The _length of the TEMA   Returns: The TEMA value w2ma(_src, _length)   Calculates the Normalized Double Moving Average (N2MA)   Parameters:      _src (float) : The source series for calculation      _length (simple int) : The _length of the N2MA   Returns: The N2MA value wma(_src, _length)   Calculates the Normalized Moving Average (NMA)   Parameters:      _src (float) : The source series for calculation      _length (simple int) : The _length of the NMA   Returns: The NMA value nma(_open, _close, _length)   Calculates the Normalized Moving Average (NMA)   Parameters:      _open (float) : The open price series      _close (float) : The close price series      _length (simple int) : The _length for finding the highest and lowest values   Returns: The NMA value lma(_src, _length)   Parameters:      _src (float)      _length (simple int) zero_lag(_src, _length, gamma1, zl)   Calculates the Zero Lag Moving Average (ZeroLag)   Parameters:      _src (float) : The source series for calculation      _length (simple int) : The length for the moving average      gamma1 (simple int) : The coefficient for calculating 'd'      zl (simple bool) : Boolean flag for applying Zero Lag   Returns: An array containing the ZeroLag Moving Average and a boolean flag indicating if it's flat copyright HPotter, thanks for that great function chebyshevI(src, len, ripple)   Calculates the Chebyshev Type I Filter   Parameters:      src (float) : The source series for calculation      len (int) : The length of the filter      ripple (float) : The ripple factor for the filter   Returns: The output of the Chebyshev Type I Filter math from Pafnuti Lwowitsch Tschebyschow (1821–1894) Thanks peacefulLizard50262 for the find and translation chebyshevII(src, len, ripple)   Calculates the Chebyshev Type II Filter   Parameters:      src (float) : The source series for calculation      len (int) : The length of the filter      ripple (float) : The ripple factor for the filter   Returns: The output of the Chebyshev Type II Filter math from Pafnuti Lwowitsch Tschebyschow (1821–1894) Thanks peacefulLizard50262 for the find wavetrend(_src, _n1, _n2)   Calculates the WaveTrend indicator   Parameters:      _src (float) : The source series for calculation      _n1 (simple int) : The period for the first EMA calculation      _n2 (simple int) : The period for the second EMA calculation   Returns: The WaveTrend value f_getma(_type, _src, _length, ripple)   Calculates various types of moving averages   Parameters:      _type (simple string) : The type of indicator to calculate      _src (float) : The source series for calculation      _length (simple int) : The length for the moving average or indicator      ripple (simple float)   Returns: The calculated moving average or indicator value f_getfilter(_type, _src, _length)   Calculates various types of filters   Parameters:      _type (simple string) : The type of indicator to calculate      _src (float) : The source series for calculation      _length (simple int) : The length for the moving average or indicator   Returns: The filtered value f_getoszillator(_type, _src, _length)   Calculates various types of Deviations and other indicators   Parameters:      _type (simple string) : The type of indicator to calculate      _src (float) : The source series for calculation      _length (simple int) : The length for the moving average or indicator   Returns: The calculated moving average or indicator value
Perpustakaan Pine Script®
oleh djmad
5
MLExtensionsLibrary "MLExtensions" normalizeDeriv(src, quadraticMeanLength)   Returns the smoothed hyperbolic tangent of the input series.   Parameters:      src : The input series (i.e., the first-order derivative for price).      quadraticMeanLength : The length of the quadratic mean (RMS).   Returns: nDeriv The normalized derivative of the input series. normalize(src, min, max)   Rescales a source value with an unbounded range to a target range.   Parameters:      src : The input series      min : The minimum value of the unbounded range      max : The maximum value of the unbounded range   Returns: The normalized series rescale(src, oldMin, oldMax, newMin, newMax)   Rescales a source value with a bounded range to anther bounded range   Parameters:      src : The input series      oldMin : The minimum value of the range to rescale from      oldMax : The maximum value of the range to rescale from      newMin : The minimum value of the range to rescale to      newMax : The maximum value of the range to rescale to   Returns: The rescaled series color_green(prediction)   Assigns varying shades of the color green based on the KNN classification   Parameters:      prediction : Value (int|float) of the prediction   Returns: color color_red(prediction)   Assigns varying shades of the color red based on the KNN classification   Parameters:      prediction : Value of the prediction   Returns: color tanh(src)   Returns the the hyperbolic tangent of the input series. The sigmoid-like hyperbolic tangent function is used to compress the input to a value between -1 and 1.   Parameters:      src : The input series (i.e., the normalized derivative).   Returns: tanh The hyperbolic tangent of the input series. dualPoleFilter(src, lookback)   Returns the smoothed hyperbolic tangent of the input series.   Parameters:      src : The input series (i.e., the hyperbolic tangent).      lookback : The lookback window for the smoothing.   Returns: filter The smoothed hyperbolic tangent of the input series. tanhTransform(src, smoothingFrequency, quadraticMeanLength)   Returns the tanh transform of the input series.   Parameters:      src : The input series (i.e., the result of the tanh calculation).      smoothingFrequency      quadraticMeanLength   Returns: signal The smoothed hyperbolic tangent transform of the input series. n_rsi(src, n1, n2)   Returns the normalized RSI ideal for use in ML algorithms.   Parameters:      src : The input series (i.e., the result of the RSI calculation).      n1 : The length of the RSI.      n2 : The smoothing length of the RSI.   Returns: signal The normalized RSI. n_cci(src, n1, n2)   Returns the normalized CCI ideal for use in ML algorithms.   Parameters:      src : The input series (i.e., the result of the CCI calculation).      n1 : The length of the CCI.      n2 : The smoothing length of the CCI.   Returns: signal The normalized CCI. n_wt(src, n1, n2)   Returns the normalized WaveTrend Classic series ideal for use in ML algorithms.   Parameters:      src : The input series (i.e., the result of the WaveTrend Classic calculation).      n1      n2   Returns: signal The normalized WaveTrend Classic series. n_adx(highSrc, lowSrc, closeSrc, n1)   Returns the normalized ADX ideal for use in ML algorithms.   Parameters:      highSrc : The input series for the high price.      lowSrc : The input series for the low price.      closeSrc : The input series for the close price.      n1 : The length of the ADX. regime_filter(src, threshold, useRegimeFilter)   Parameters:      src      threshold      useRegimeFilter filter_adx(src, length, adxThreshold, useAdxFilter)   filter_adx   Parameters:      src : The source series.      length : The length of the ADX.      adxThreshold : The ADX threshold.      useAdxFilter : Whether to use the ADX filter.   Returns: The ADX. filter_volatility(minLength, maxLength, useVolatilityFilter)   filter_volatility   Parameters:      minLength : The minimum length of the ATR.      maxLength : The maximum length of the ATR.      useVolatilityFilter : Whether to use the volatility filter.   Returns: Boolean indicating whether or not to let the signal pass through the filter. backtest(high, low, open, startLongTrade, endLongTrade, startShortTrade, endShortTrade, isStopLossHit, maxBarsBackIndex, thisBarIndex)   Performs a basic backtest using the specified parameters and conditions.   Parameters:      high : The input series for the high price.      low : The input series for the low price.      open : The input series for the open price.      startLongTrade : The series of conditions that indicate the start of a long trade.`      endLongTrade : The series of conditions that indicate the end of a long trade.      startShortTrade : The series of conditions that indicate the start of a short trade.      endShortTrade : The series of conditions that indicate the end of a short trade.      isStopLossHit : The stop loss hit indicator.      maxBarsBackIndex : The maximum number of bars to go back in the backtest.      thisBarIndex : The current bar index.   Returns: A tuple containing backtest values init_table()   init_table()   Returns: tbl The backtest results. update_table(tbl, tradeStatsHeader, totalTrades, totalWins, totalLosses, winLossRatio, winrate, stopLosses)   update_table(tbl, tradeStats)   Parameters:      tbl : The backtest results table.      tradeStatsHeader : The trade stats header.      totalTrades : The total number of trades.      totalWins : The total number of wins.      totalLosses : The total number of losses.      winLossRatio : The win loss ratio.      winrate : The winrate.      stopLosses : The total number of stop losses.   Returns: Updated backtest results table.
Perpustakaan Pine Script®
oleh jdehorty
8
Tunç ŞatıroğluTunç Şatıroğlu's Technical Analysis Suite Description: This comprehensive Pine Script indicator, inspired by the technical analysis teachings of Tunç Şatıroğlu, integrates six powerful TradingView indicators into a single, user-friendly suite for robust trend, momentum, and divergence analysis. Each component has been carefully selected and enhanced by beytun to improve functionality, performance, and visual clarity, aligning with Şatıroğlu's approach to technical analysis. The default configuration is meticulously set to match the exact settings of the individual indicators as used by Tunç Şatıroğlu in his training, ensuring authenticity and ease of use for followers of his methodology. Whether you're a beginner or an experienced trader, this suite provides a versatile toolkit for analyzing markets across multiple timeframes. Included Indicators: 1. WaveTrend with Crosses (by LazyBear, modified): A momentum oscillator that identifies overbought/oversold conditions and trend reversals with clear buy/sell signals via crosses and bar color highlights. 2. Kaufman Adaptive Moving Average (KAMA) (by HPotter, modified): A dynamic moving average that adapts to market volatility, offering a smoother trend-following signal. 3. SuperTrend (by Alex Orekhov, modified): A trend-following indicator that plots dynamic support/resistance levels with buy/sell signals and optional wicks for enhanced accuracy. 4. Nadaraya-Watson Envelope (by LuxAlgo, modified): A non-linear envelope that highlights potential reversals with customizable repainting options for smoother outputs. 5. Divergence for Many Indicators v4 (by LonesomeTheBlue, modified): Detects regular and hidden divergences across multiple indicators (MACD, RSI, Stochastic, CCI, Momentum, OBV, VWMA, CMF, MFI, and more) for early reversal signals. 6. Ichimoku Cloud (TradingView built-in, modified): A multi-faceted indicator for trend direction, support/resistance, and momentum, with enhanced visuals for the Kumo Cloud. Key Features: - Authentic Default Settings : Pre-configured to mirror the exact parameters used by Tunç Şatıroğlu for each indicator, ensuring alignment with his proven technical analysis approach. - Customizable Settings : Enable/disable individual indicators and fine-tune parameters to suit your trading style while retaining the option to revert to Şatıroğlu’s defaults. - Enhanced User Experience : Modifications improve visual clarity, performance, and usability, with options like repainting smoothing for Nadaraya-Watson and adjustable Ichimoku projection periods. - Multi-Timeframe Analysis : Combines trend-following, momentum, and divergence tools for a holistic view of market dynamics. - Alert Conditions : Built-in alerts for SuperTrend direction changes, buy/sell signals, and divergence detections to keep you informed. - Visual Clarity : Overlays (KAMA, SuperTrend, Nadaraya-Watson, Ichimoku) and pane-based indicators (WaveTrend, Divergences) are clearly distinguished, with customizable colors and styles. Notes: - The Nadaraya-Watson Envelope and Ichimoku Cloud may repaint in their default modes. Use the "Repainting Smoothing" option for Nadaraya-Watson or adjust Ichimoku settings to mitigate repainting if preferred. - Published under the MIT License, with components licensed under GPL-3.0 (SuperTrend), CC BY-NC-SA 4.0 (Nadaraya-Watson), MPL 2.0 (Divergence), and TradingView's terms (Ichimoku Cloud). Usage: Add this indicator to your TradingView chart to leverage Tunç Şatıroğlu’s exact indicator configurations out of the box. Customize settings as needed to align with your strategy, and use the combined signals to identify trends, reversals, and divergences. Ideal for traders following Şatıroğlu’s methodologies or anyone seeking a powerful, all-in-one technical analysis tool. Credits: Original authors: LazyBear, HPotter, Alex Orekhov, LuxAlgo, LonesomeTheBlue, and TradingView. Modifications and integration by beytun . License: Published under the MIT License, incorporating code under GPL-3.0, CC BY-NC-SA 4.0, MPL 2.0, and TradingView’s terms where applicable.
Penunjuk Pine Script®
oleh beytun
5
Aethix Cipher Pro2Aethix Cipher Pro: AI-Enhanced Crypto Signal Indicator grok Ai made signal created for aethix users. Unlock the future of crypto trading with Aethix Cipher Pro—a powerhouse indicator inspired by Market Cipher A, turbocharged for Aethix.io users! Built on WaveTrend Oscillator, 8-EMA Ribbon, RSI+MFI, and custom enhancements like Grok AI confidence levels (70-100%), on-chain whale volume thresholds, and fun meme alerts ("To the moon! 🌕"). Key Features: no whale tabs WaveTrend Signals: Spot overbought/oversold with levels at ±53/60/100—crosses trigger red diamonds, blood diamonds, yellow X's for high-prob buy/sell entries. Neon Teal EMA Ribbon: Dynamic 5-34 EMA gradient (bullish teal/bearish red) for trend direction—crossovers plot green/red circles, blue triangles. RSI+MFI Fusion: Overbought (70+)/oversold (30-) with long snippets for sentiment edges.
Penunjuk Pine Script®
oleh axi13