4 WMA's4 WMA's plots four Weighted Moving Averages on the chart at once, giving a quick multi-timeframe view of trend direction and momentum.
By default the lengths are 21, 55, 100 and 200, so you get a short-term, medium-term and two longer-term averages in a single overlay indicator. Each length is fully configurable in the settings.
Unlike a simple moving average, a Weighted Moving Average (WMA) assigns more weight to recent prices, so it reacts faster to price changes while still smoothing out noise. This makes the WMA useful for spotting trend shifts a bit earlier than an SMA.
How to use it:
- When price is above all four WMAs and they are stacked in order (fastest on top), the trend is strongly bullish.
- When price is below all four and they are stacked in reverse, the trend is strongly bearish.
- Crossovers between the faster and slower WMAs can be used as trend-change signals.
All lengths, colors and line widths can be adjusted in the indicator settings. Works on any symbol and timeframe. インジケーター
Micro Momentum Oscillator [DYNA]Micro Momentum Oscillator is a purpose-built momentum tool for scalpers who need to know the instant short-term momentum shifts direction. It doesn't just tell you whether RSI is high or low -- it measures how fast RSI is changing and fires a signal the moment that rate of change flips in an extreme zone.
Most oscillators lag behind price on micro timeframes. By the time a standard RSI or MACD prints a crossover on a 1-minute chart, the move is already half over. Micro Momentum Oscillator solves this by applying a rate-of-change calculation directly to RSI and smoothing the result with a weighted moving average. The output is a fast, responsive line that turns teal when momentum is accelerating upward and red when it is accelerating downward -- giving you a clean visual read on who is in control right now.
Key Features
RSI Rate-of-Change Pipeline -- Measures how quickly RSI itself is changing, not just its level. This catches momentum shifts before the RSI line visually turns.
OB/OS Zone Flip Detection -- Signals only fire when momentum flips direction while RSI was in an extreme zone (oversold or overbought), filtering out noise in the middle range.
Color-Coded Momentum Line -- Teal for bullish acceleration, red for bearish acceleration. No interpretation needed -- the color tells you the direction at a glance.
Zone Shading -- Soft red and teal fills in the overbought and oversold momentum zones so you can instantly see when the oscillator is in an extreme area.
Confirmed-Bar Logic -- All signals reference the previous bar's values, so flip markers never repaint or disappear after they print.
How It Works
The oscillator computes a short-period RSI (default 5), then calculates the rate of change of that RSI over the last 3 bars. This raw ROC is smoothed with a 3-period weighted moving average to filter out single-bar noise while keeping the reading fast.
The result is plotted as a line that oscillates around zero. When the line is above zero and teal, momentum is pushing RSI higher -- buyers are gaining strength. When the line is below zero and red, momentum is dragging RSI lower -- sellers are in control.
The key signal is the momentum flip . When the oscillator crosses above zero and RSI was recently in the oversold zone (below 30), a bullish FLIP marker appears. When it crosses below zero and RSI was in the overbought zone (above 70), a bearish FLIP marker appears. These flips highlight the moments when exhausted momentum reverses direction at an extreme -- exactly the kind of micro-reversal scalpers look for.
Micro Momentum Oscillator on a 1-minute BTC chart showing bullish and bearish flip signals at momentum extremes.
Visual Elements
The oscillator pane shows a teal/red momentum line, a gray zero line, and soft zone shading in the overbought and oversold areas. A thin orange reference line tracks the underlying RSI (scaled to fit the pane) so you can see at a glance whether price is stretched. Triangle markers with "FLIP" text appear at momentum reversal points in extreme zones.
Zone shading highlights overbought and oversold momentum areas. The orange RSI reference line shows underlying conditions.
Settings
The core settings control the speed of the oscillator. RSI Length (default 5) sets the underlying RSI period -- lower values make it more reactive. ROC Length (default 3) controls how many bars of RSI change are measured. Smoothing (default 3) applies a WMA to the ROC output to remove noise without adding significant lag.
Overbought and Oversold levels (default 70 and 30) define the RSI thresholds for flip detection. Only momentum reversals that occur when RSI was beyond these levels generate flip markers. You can tighten these thresholds (e.g., 75/25) for fewer but higher-conviction signals, or widen them (e.g., 65/35) for more frequent signals.
Visual toggles let you show or hide zone shading and flip markers. Alert toggles let you enable or disable each alert type independently.
Alerts
Momentum Flip Bullish -- Fires when the smoothed ROC crosses above zero while RSI was in the oversold zone. "Micro Momentum Oscillator : Bullish momentum flip detected. RSI was oversold, ROC now accelerating upward."
Momentum Flip Bearish -- Fires when the smoothed ROC crosses below zero while RSI was in the overbought zone. "Micro Momentum Oscillator : Bearish momentum flip detected. RSI was overbought, ROC now decelerating downward."
To set up alerts: click the TradingView Alerts button, select "Micro Momentum Oscillator " from the indicator dropdown, choose "Any alert() function call" as the condition, and set your preferred notification method.
Best Practices
Use on 1-3 minute charts for best results. The default parameters are calibrated for micro-timeframe scalping.
Treat FLIP signals as timing cues, not standalone entries. Confirm with a supporting candle pattern, a volume spike, or a key support/resistance level.
Avoid trading flips during low-volume periods such as pre-market or lunch hours when momentum readings become noisy.
If moving to 5-minute charts, consider increasing RSI Length to 8-10 to maintain signal quality.
Pair with a volume indicator or tape reader for stronger confirmation on each flip.
Part of the DYNA Ecosystem
Micro Momentum Oscillator is a free indicator built with the same design standards as the DYNA premium suite. For complete trade management with automatic stop loss, break-even, trailing stops, and multi-target systems, explore the full DYNA indicator collection.
Disclaimer
This indicator is a technical analysis and educational tool only -- it is not financial advice and makes no guarantee of any outcome. Past performance does not predict future results. Always do your own research and use proper position sizing and risk management.
Created by Varun Nidhi · varunnidhi.com
A free DYNA indicator — self-contained, no repainting.
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Reverse AVWAP: Institutional Anchor DiscoveryStop guessing your anchors. Let the algorithm find them for you.
Most traders use the Anchored VWAP (AVWAP) the same way: they pick an obvious swing high, swing low, or earnings gap, anchor a line to it, and wait to see if price reacts. But what if we flipped the script? What if we took a significant current price level and mathematically scanned history to find exactly which hidden dates are defending it?
Introducing the Reverse AVWAP.
This indicator acts as an investigative tool for market structure and volume memory. By targeting a specific date or your current real-time chart bar, the script calculates backward, scanning thousands of bars to find the exact historical anchor points where an AVWAP drawn from them converges perfectly with your target price.
How It Works
Instead of projecting forward, this script reverse-engineers the volume profile:
Dynamic Target Selection: Choose to run the calculation from a fixed Target Date or toggle Use Last Chart Bar as Target to dynamically track live, real-time convergence on your current candle.
Historical Matrix Scan: The algorithm searches back in time, calculating the exact AVWAP from every single historical bar up to your target.
Threshold Matching: If a historical AVWAP lands within your custom proximity threshold (e.g., ±2.5% or ±3.5%) of the target price, it flags that date as a valid "Anchor."
Stitched Curve Generation: It draws the historical VWAP curves connecting those hidden anchors directly to your target.
Key Features
Macro First vs. Micro First Scanning: Choose your search direction. Macro First scans from the oldest historical data forward, prioritizing dominant multi-year structural pivots (like All-Time Highs or major cyclical bottoms). Micro First scans from recent data backward, focusing on short-term accumulation zones.
Smart Anti-Clustering: Includes a "Minimum Bars Between Anchors" filter. If the market forms a major rounded peak or flat consolidation, this prevents the script from grabbing 5 consecutive days on the same structure. It forces the algorithm to find distinct, uniquely significant pivot origins.
Up to 15 Historical Curves: Automatically color-codes and plots multiple unique historical AVWAP curves that converge on your target price.
Precision Divergence Labels: Drops clean visual tags on the discovered anchors, showing you exactly how close the historical AVWAP came to your target price down to the decimal percentage.
Under the Hood (Engine Optimizations)
Calculating thousands of historical AVWAPs iteratively would normally trigger a Pine Script timeout or cause massive lag. This indicator utilizes a heavily optimized architecture to bypass TradingView's native limitations:
O(1) Time Math: It uses rolling arrays to track the cumulative sums of Volume and Price × Volume. By subtracting cumulative historical values from current ones, it solves the AVWAP equations instantly in constant time per bar.
Bulletproof Line-Chain Renderer: TradingView’s standard polyline engine frequently suffers from canvas rendering drops when drawing long curves across thousands of bars. This script implements a custom, lightweight rendering engine that segments standard lines into roughly 80 dynamically downsampled links per anchor. The result is a buttery-smooth curve that never fails to render, no matter how far back the anchor sits.
Memory Management: Includes a dedicated garbage-collection routine that wipes and redraws canvas objects on live ticks, keeping your chart clean, responsive, and completely free of visual flickering.
Usage Tips
The History Loading Shortcut: Pine Script can only analyze data that is actively loaded into your browser session. If you are looking for a macro anchor from years ago, use the TradingView "Go to" shortcut (Alt + G on Windows, Option + G on Mac) and enter a past date. This forces the servers to load the historical bars instantly, allowing the script to find the anchor immediately.
Validation: If you see a breakout, run the Reverse AVWAP. If multiple historical volume anchors perfectly align with your current price, you have high-conviction proof of a major institutional volume node. You can then use those newly discovered anchor dates to project standard AVWAPs forward into the future. インジケーター
Bitcoin WMA Bands | Astral Vision Bitcoin WMA Bands | Astral Vision 💠🌠
This indicator constructs a volatility-adjusted band system around a Weighted Moving Average of price, using the standard deviation of logarithmic daily returns as the volatility measure rather than the standard deviation of price itself. The result is a channel whose width adapts dynamically to the current volatility regime, expanding during high-volatility periods and contracting during low-volatility ones, while remaining anchored to the WMA as the structural fair value reference.
Calculation ⚙️
The base reference line is a Weighted Moving Average of close over a configurable lookback in days. WMA weights recent bars more heavily than older ones using a linearly declining weight schedule, making it more responsive to recent price action than an SMA of the same length while being less erratic than an EMA.
The volatility measure is computed from logarithmic returns: for each bar, the log return is log(close / close ). The standard deviation of these log returns over a configurable lookback window is then multiplied by a configurable scale factor to produce the band half-width `s`. Using log returns rather than raw price changes ensures that the volatility measure is proportional across different price levels, making a 5% move at $10,000 and a 5% move at $100,000 contribute equally to the standard deviation.
The four bands are then computed as: band = WMA × exp(±n × s), where n is 1 or 2. The exponential transformation converts the log-space deviation back to price-space, ensuring the bands are multiplicatively symmetric around the WMA rather than additively symmetric. This means the upper and lower bands are equidistant in percentage terms rather than in absolute dollar terms.
The oscillator in the sub-panel is the log ratio of close to the WMA: log(close / WMA), which measures in log-space how far price has deviated from its trend. The same ±1σ and ±2σ levels are plotted in the sub-panel, allowing direct visual comparison of the oscillator's position within the band structure. Candles on the price chart are colored only when price is outside the ±1σ band, leaving them neutral in the fair value zone between the bands.
Crossover signals are generated when the oscillator crosses back inside the ±1σ boundary from outside: a triangle appears above the bar when the oscillator crosses back below the upper +1σ level from above, and below the bar when it crosses back above the lower -1σ level from below.
Plots 📊
WMA reference line on the price chart
Four volatility-adjusted bands at ±1σ and ±2σ on the price chart
Candle coloring on the price chart when price is outside the ±1σ band
Background color on the price chart between the ±1σ and ±2σ zones
Re-entry signals: triangle above bar on upper band exit, triangle below bar on lower band exit
Log-ratio oscillator in the sub-panel with matching ±1σ and ±2σ reference lines
Inputs 🎛️
STH Length: WMA lookback period in days
StDev Length: rolling window for the log return standard deviation
Band Scale: multiplier applied to the standard deviation before computing band width
Colors 🎨
5 Astral Vision presets + custom override. Default: Paradiso.
Purpose 🎯
Standard Bollinger Bands apply a fixed standard deviation multiple to a simple moving average computed on raw prices, which means the band width in percentage terms varies across different price levels and the bands do not correctly represent proportional deviations. This indicator applies the volatility measure in log-return space and converts back with the exponential function, producing bands that are geometrically consistent across Bitcoin's full price history. The WMA further reduces the lag of the central reference compared to an SMA, making the band system more responsive to trend changes without introducing the instability of shorter lookbacks.
Disclaimer ⭕️
This indicator is for informational and educational purposes only. It does not constitute financial advice. Past performance is not indicative of future results. Always do your own research before making investment decisions. インジケーター
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Iterative Periodic EnvelopeThe Iterative Periodic Envelope is a phase-conditioned kernel estimator with endogenous dispersion modeling, implemented as a Nadaraya–Watson estimator under a canonical periodic kernel.
The periodic kernel defines similarity through cyclical phase alignment rather than temporal proximity or multi-scale distance decay. Observations contribute to the estimator based on their position within a repeating cycle structure, emphasizing structural recurrence over linear time dependence.
The indicator computes a latent equilibrium using a kernel-weighted mean and a dispersion measure using kernel-weighted variance under the same weighting structure. The resulting envelope reflects cycle-consistent deviation, rather than a conventional volatility band. All values are computed exclusively on closed historical bars using a bounded lookback window, ensuring non-repainting behavior.
This indicator belongs to a broader class of iterative kernel-based envelopes that includes Gaussian and Rational Quadratic variants. All share a common Nadaraya–Watson estimation framework, differentiated by their kernel.
TRADING USES
The Iterative Periodic Envelope is best interpreted as a cycle-aware structural estimator rather than a volatility-based band.
Equilibrium Tracking
The latent equilibrium represents the phase-conditioned central tendency of price under periodic similarity weighting. Oscillations around this level reflect movement within a repeating structural cycle rather than directional drift.
Cycle Regime Structure
The envelope emphasizes repeating structural behavior through phase recurrence weighting. Changes in symmetry, amplitude, or persistence of oscillation around the latent equilibrium may indicate transitions between cyclical regimes.
Mean Reversion Within Cycles
When a stable periodic structure is present, deviations from the latent equilibrium may revert toward phase-consistent levels. This supports mean-reversion behavior that is conditioned on cycle structure rather than purely statistical dispersion.
Structural Extremes
Extreme deviations relative to the envelope correspond to phase-inconsistent states where cyclical structure becomes stretched or destabilized. These conditions often precede transitions such as cycle inversion, expansion, or compression.
State Estimation
The system defines a latent equilibrium as the inferred central cyclical state, with dispersion derived from kernel-weighted variance under identical periodic similarity constraints. This produces a structurally consistent representation of market state.
PERIODIC ENVELOPE CONSTRUCTION
The envelope is constructed using kernel-weighted variance under the same periodic similarity measure used to estimate the latent equilibrium. The latent equilibrium defines the central state estimate and kernel-weighted variance defines dispersion under identical weighting, producing an endogenously determined envelope. The band width is fixed at ±1 kernel standard deviation with no multiplier, ensuring dispersion remains an intrinsic property of the periodic similarity structure rather than an externally imposed scaling parameter.
THEORY
The periodic kernel defines similarity in terms of cyclical phase recurrence rather than linear temporal distance. Observations contribute to the estimator based on alignment within a repeating cycle structure.
The estimator is formulated as a Nadaraya–Watson kernel regression under a canonical periodic kernel, where weights are defined as:
k(i) = exp( -2 · sin²(πi / p) / L² )
Where:
p = period (cycle length)
L = lookback window (bandwidth parameter; effective smoothing scales with L²)
In this MacKay consistent formulation, the lookback window acts as a bandwidth control parameter, governing phase selectivity and structural smoothing. As L increases, the kernel becomes broader, producing stronger smoothing and reduced phase sensitivity. As L decreases, phase selectivity increases and the estimator becomes more locally sensitive to cyclical alignment.
This induces a cyclical similarity structure in which influence concentrates at recurring phase intervals. The resulting estimator defines a latent equilibrium governed by phase alignment rather than temporal proximity. This formulation can be interpreted as a periodic extension of kernel regression on a circular phase manifold.
CALIBRATION
Length (Lookback / Bandwidth)
Controls structural depth of the estimator and acts as the primary kernel bandwidth parameter.
- 50–100: high responsiveness, short-cycle sensitivity
- 150–250: balanced regime stability
- 300+: strong structural smoothing, reduced sensitivity to phase noise
Period (Cycle Length)
Defines the recurrence interval of the kernel and governs phase alignment and cyclical structure. Commonly aligns with dominant market rhythms such as intraday or macro-cycle structure.
- Lower values: faster cycle sensitivity
- Higher values: slower, broader structural cycles
Start At Bar
Offsets the kernel window backward from the most recent bars and excludes newer observations from the estimator. This ensures all calculations are based strictly on closed historical data and preserves non-repainting behavior.
MARKET USAGE
Stock, Forex, Crypto, Commodities, and Indices.
Performance is dependent on the presence of stable cyclical structure; in regimes lacking periodic coherence, the estimator converges toward a smoother, low-information state. インジケーター
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Rhokeo-VW-RSI Histogram for Cumulative Delta by ZeiirmanRhokeo-VW-RSI Histogram: Volume-Weighted Momentum (use with Cumulative Delta from Zeiierman) Note that Cumulative Delta is a paid indicator.
Overview: The Rhokeo-VW-RSI Histogram is a momentum oscillator designed to filter out market noise by integrating volume directly into the RSI calculation. Unlike a standard RSI, which only considers price change, this indicator weights those changes by the volume occurring at the time.
It creates a momentum profile in the form of a Histogram. If the price moves on high volume, the indicator reflects that strong market interest through its volume-weighted gain and loss calculations. It is particularly effective as a complementary filter for “Cumulative Delta” from Zeiierman to confirm the strength behind a move before you enter a trade.
How It Works The indicator operates on a normalized scale of -1.0 to +1.0 for easier visual interpretation and compatibility with Cumulative Delta indicator:
• The Volume-Weighted Core: Gains and losses are calculated by multiplying the price change by volume to ensure the "Relative Strength" reflects true capital flow.
• Smoothing for Clarity: The raw Volume Weighted RSI (VW-RSI) is processed through a customizable Moving Average—such as SMA, EMA, SMMA, WMA, or VWMA—to produce the smooth histogram.
• Four-Zone Coloring System: The histogram changes color dynamically based on momentum intensity:
o Strong Bull: Price is trending up with high-volume conviction.
o Weak Bull: Positive momentum, but not yet overextended.
o Weak Bear: Negative momentum starting to build.
o Strong Bear: Heavy selling pressure with high-volume conviction.
Key Features
• Shading: The background features optional red and green shading in the "Extreme" zones to warn traders of potential exhaustion areas.
• Dynamic Zero Line: The center line flips color between Green and Red based on whether the VW-RSI is positive or negative.
• Customization: Traders can adjust the smoothing length, source price, and the specific levels for overbought/oversold zones.
Best Use Case for New Traders: New traders often get "faked out" by price spikes that have no volume behind them. This indicator helps confirm and time better entries:
1. Wait for your Cumulative Delta indicator to give a signal.
2. Check the VW-RSI Histogram and whether it confirms or not.
3. Long Entry: Only enter if the histogram is positive and rising (above 0).
4. Short Entry: Only enter if the histogram is negative and decreasing (below 0).
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Disclaimer
Financial Risk:
• Trading involves significant risk, and most traders lose money.
• This indicator is a tool for technical analysis and does not constitute financial, investment, or trading advice.
• Past performance is not indicative of future results; never trade with money you cannot afford to lose.
Usage & Reliability:
• The Rhokeo-VW-RSI Histogram is provided "as-is" for educational and informational purposes only.
• While volume-weighting aims to filter market noise, no indicator can guarantee 100% accuracy or predict future market movements with certainty.
• This script is intended to be a complementary tool that works well with other indicators in this case the Cumulative Delta from Zeiirman; it should be used in conjunction with other forms of analysis, risk management, and your own due diligence.
Commercial Notice:
• If you are using this alongside a third-party paid indicator, please note that I am not responsible for the performance or support of external products.
• Users are responsible for their own trade execution and account management.
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WMA MAD Trend | RakoQuantWMA MAD Trend | RakoQuant is a robust volatility-regime trend system built on Weighted Moving Average structure and Median Absolute Deviation dispersion, engineered to produce clean directional states while suppressing wick-driven noise and unstable ATR distortions.
This tool belongs to the RakoQuant protected research line, combining a smooth WMA baseline, statistically robust volatility envelopes (MAD bands), SuperTrend-style regime logic, and a strength-aware visualization layer designed for consistent performance across trending, mean-reverting, and mixed market environments.
Core Concept
This indicator answers one fundamental question:
Is price holding a statistically meaningful deviation from its WMA baseline, or reverting back into range?
Unlike classic SuperTrend variants that rely on ATR (highly sensitive to spikes and wicks), WMA MAD Trend uses Median Absolute Deviation as its volatility engine — a robust dispersion measure that remains stable in the presence of outliers.
How It Works
1) WMA Baseline (Directional Structure)
At its core, the indicator defines the market’s structural center using a Weighted Moving Average:
* WMA Baseline tracks directional bias with smoother, trend-weighted responsiveness
* The baseline can optionally be smoothed further in intraday mode to reduce micro-chop
This provides a stable anchor for dispersion-based regime classification.
2) MAD Volatility Engine (Robust Dispersion Core)
Instead of ATR, volatility is measured via Median Absolute Deviation (MAD) around the baseline:
* Compute absolute deviation:
|Close − Baseline|
* Take rolling median of deviation over madLen
* Optional normalization scales MAD toward a stdev-like measure (via constant factor)
This makes volatility estimation:
* Outlier-resistant
* Wick-resistant
* Regime-stable during abnormal price spikes
3) MAD Bands + SuperTrend Trailing Logic (Regime State Model)
Bands are built as:
* Upper Band = Baseline + Factor × MAD
* Lower Band = Baseline − Factor × MAD
Then classic SuperTrend-style trailing constraints are applied so the active band persists until a true regime break occurs.
That produces a state engine:
* Bull regime when price breaks above the trailing upper logic (transition into trend-up state)
* Bear regime when price breaks below the trailing lower logic (transition into trend-down state)
This behaves like a structural market regime model, not a reactive oscillator.
4) Strength Engine (Deviation-Based Intensity)
A defining layer of this tool is the MAD Z-score intensity system:
* Compute Z-score:
z = |Close − Baseline| / MAD
* Map into a 0 → 1 strength scale
Interpretation:
* Low deviation = weak regime confidence (likely chop / mean reversion)
* High deviation = strong regime confidence (trend expansion)
5) Intensity Visual Engine (Signal Clarity Layer)
WMA MAD Trend includes a protected visual engine that scales opacity with strength:
* Strong expansion = solid trend band
* Weak deviation = faded band
This gives immediate clarity:
Not all flips are equal — strength is displayed structurally.
6) Optional Institutional Filters
Two optional confirmation modules allow institutional-grade filtering:
Baseline Confirmation
* Bull flips only accepted if price is above baseline
* Bear flips only accepted if price is below baseline
EMA Stack Filter
* Bull only when Fast EMA > Slow EMA
* Bear only when Fast EMA < Slow EMA
These modules make the tool suitable for:
* Directional portfolio bias frameworks (RSPS)
* Regime classification overlays
* Trend confirmation filters for execution systems
7) Strong Flip Tier Alerts
Signal quality is tiered:
* Standard flip alerts
* Strong flip alerts only when deviation strength exceeds a threshold
This produces a higher-confidence regime transition model for swing positioning and exposure scaling.
How To Use
✅ Trend regime overlay
✅ Wick-resistant volatility trend filter
✅ MAD-based deviation strength engine
✅ Directional bias tool for portfolio systems
Best use cases:
* 1H–1D trend frameworks
* Regime filters for signal stacking
* Chop suppression in volatile markets
Suggested workflow:
* Bull bias when the regime is bullish and strength is rising
* Reduce risk / defensive when strength fades or a bearish flip occurs
* Pair with execution tools (breakout/mean-reversion entries) for timing
Screenshot Placement
📸 Example chart / screenshot: snapshot
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6 Moving Averages (SMA, WMA, EMA etc.)6 Moving Averages is a simple and flexible overlay indicator that lets you plot up to six moving averages on the price chart. Each moving average can be customized by type (SMA, EMA, WMA, etc.), length, color, and visibility, making it ideal for trend analysis, dynamic support and resistance, and moving-average confluence across any market or timeframe. インジケーター
VIOP Scalping - OriginalVIOP Scalping – Original is a rule-based scalping strategy ported from an original C# logic set. It aims to trade only when trend direction, momentum, and trend strength align, then manages the position using fixed take-profit/stop-loss percentages with an optional trailing mechanism to protect gains during favorable moves.
This strategy is provided for educational and backtesting purposes only. It is not financial advice and does not guarantee profitability. Always test thoroughly before any live usage.
Core Concept
Follow the dominant WMA trend, confirm momentum with EMA separation, filter conditions with RSI + ADX, then exit using fixed TP/SL with trailing behavior after a defined profit threshold.
How the Strategy Works
Trend Direction is defined by WMA: above WMA = long bias, below WMA = short bias.
Momentum is measured via Fast EMA vs Slow EMA and the EMA difference.
Trend Strength is confirmed using ADX (must exceed a threshold).
RSI filters trades to avoid entering when momentum is likely overextended or weak.
A no-trade session blocks entries during a predefined time window (default 09:30–10:05).
Exit logic uses fixed percent TP/SL, with an optional trailing mechanism that activates after a profit threshold.
Inputs and Settings
Trend and Indicator Settings
Main Trend WMA: Determines directional bias (price above = long, price below = short).
Fast EMA / Slow EMA: Used to measure momentum and directional separation.
RSI Period: Filters entries based on RSI range constraints.
ADX Period: Measures trend strength (must exceed threshold to allow entries).
Threshold Settings
EMA Difference Threshold: Minimum EMA separation required to validate momentum.
ADX Threshold: Minimum ADX required to confirm trend strength.
RSI Long Ceiling: RSI must remain below this value for long entries.
RSI Short Floor: RSI must remain above this value for short entries.
Risk Management Settings
Take Profit %: Default TP distance in percent.
Strong Trend Take Profit %: Higher TP used when a “strong trend” condition is detected.
Stop Loss %: Fixed SL distance in percent.
Trailing Activation %: Profit threshold at which trailing starts.
Trailing Distance %: Trailing offset distance used once trailing is active.
Time Filter
No-Trade Hours: Default session is 09:30–10:05. During this window, the strategy does not open new trades.
Entry Logic
No-Trade Time Filter
If the current bar falls inside the no-trade session, entries are blocked.
Long Entry Conditions
Price is above the WMA trend line.
EMA difference is positive and greater than the EMA Difference Threshold.
EMA momentum is increasing (current EMA diff > previous EMA diff).
RSI is within the defined range (RSI > 48 and RSI < RSI Long Ceiling).
Close is higher than the previous close.
ADX is above the ADX Threshold.
Short Entry Conditions
Price is below the WMA trend line.
EMA difference is negative and lower than -EMA Difference Threshold.
Bearish momentum is increasing (current EMA diff < previous EMA diff).
RSI is within the defined range (RSI < 52 and RSI > RSI Short Floor).
Close is lower than the previous close.
ADX is above the ADX Threshold.
Strong Trend Logic (Dynamic TP Selection)
If price is far from the WMA (absolute distance > 20 points) AND EMA separation is strong (absolute EMA diff > 1.5 points), the strategy treats the environment as a strong trend.
In strong trend mode, the strategy uses “Strong Trend Take Profit %” instead of the default “Take Profit %”.
Exit Management (TP/SL + Trailing)
The strategy uses fixed percentage-based TP and SL levels.
Trailing logic is enabled via strategy.exit and activates only after price moves in profit by the defined Trailing Activation %.
Once activated, trailing follows price using the defined Trailing Distance % offset.
This is designed to secure partial gains during extended moves while still allowing room for continuation.
What You See on the Chart
WMA Trend Line (Main Trend Filter).
Fast EMA and Slow EMA (Momentum Confirmation).
Strategy entry/exit markers generated by TradingView.
Recommended Use
Scalping systems that rely on trend-following and momentum confirmation.
Markets where ADX filtering helps avoid choppy conditions.
Traders who want a simple, parameter-driven TP/SL system with trailing after confirmation.
Important Notes
The no-trade session depends on your chart/session settings. Ensure your symbol/session configuration matches your intended market hours.
Percent-based exits scale with price; results will vary across instruments and volatility regimes.
Always validate behavior using bar replay, forward testing, and realistic commission/slippage assumptions.
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Hyper Insight MA Strategy [Universal]Hyper Insight MA Strategy ** is a comprehensive trend-following engine designed for traders who require precision and flexibility. Unlike standard indicators that lock you into a single calculation method, this strategy serves as a "Universal Adapter," allowing you to **Mix & Match 13 different Moving Average types** for both the Fast and Slow trend lines independently.
Whether you need the smoothness of T3, the responsiveness of HMA, or the classic reliability of SMA, this script enables you to backtest thousands of combinations to find the perfect edge for your specific asset class.
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🔬 Deep Dive: Calculation Logic of Included MAs
This strategy includes 13 distinct calculation methods. Understanding the math behind them will help you choose the right tool for your specific market conditions.
#### 1. Standard Averages
* **SMA (Simple Moving Average):** The unweighted mean of the previous $n$ data points.
* *Logic:* Treats every price point in the period with equal importance. Good for identifying long-term macro trends but reacts slowly to recent volatility.
* **WMA (Weighted Moving Average):** A linear weighted average.
* *Logic:* Assigns heavier weight to current data linearly (e.g., $1, 2, 3... n$). It reacts faster than SMA but is still relatively smooth.
* **SWMA (Symmetrically Weighted Moving Average):**
* *Logic:* Uses a fixed-length window (usually 4 bars) with symmetrical weights $ $. It prioritizes the center of the recent data window.
#### 2. Exponential & Lag-Reducing Averages
* **EMA (Exponential Moving Average):**
* *Logic:* Applies an exponential decay weighting factor. Recent prices have significantly more impact on the average than older prices, reducing lag compared to SMA.
* **RMA (Running Moving Average):** Also known as Wilder's Smoothing (used in RSI).
* *Logic:* It is essentially an EMA but with a slower alpha weight of $1/length$. It provides a very smooth, stable line that filters out noise effectively.
* **DEMA (Double Exponential Moving Average):**
* *Logic:* Calculated as $2 \times EMA - EMA(EMA)$. By subtracting the "lag" (the smoothed EMA) from the original EMA, DEMA provides a much faster reaction to price changes with less noise than a standard EMA.
* **TEMA (Triple Exponential Moving Average):**
* *Logic:* Calculated as $3 \times EMA - 3 \times EMA(EMA) + EMA(EMA(EMA))$. This effectively eliminates the lag inherent in single and double EMAs, making it an extremely fast-tracking indicator for scalping.
#### 3. Advanced & Adaptive Averages
* **HMA (Hull Moving Average):**
* *Logic:* A composite formula involving Weighted Moving Averages: ASX:WMA (2 \times Integer(n/2)) - WMA(n)$. The result is then smoothed by a $\sqrt{n}$ WMA.
* *Effect:* It eliminates lag almost entirely while managing to improve curve smoothness, solving the traditional trade-off between speed and noise.
* **ZLEMA (Zero Lag Exponential Moving Average):**
* *Logic:* This calculation attempts to remove lag by modifying the data source before smoothing. It calculates a "lag" value $(length-1)/2$ and applies an EMA to the data: $Source + (Source - Source )$. This creates a projection effect that tracks price tightly.
* **T3 (Tillson T3 Moving Average):**
* *Logic:* A complex smoothing technique that runs an EMA through a filter multiple times using a "Volume Factor" (set to 0.7 in this script).
* *Effect:* It produces a curve that is incredibly smooth and free of "overshoot," making it excellent for filtering out market chop.
* **ALMA (Arnaud Legoux Moving Average):**
* *Logic:* Uses a Gaussian distribution (bell curve) to assign weights. It allows the user to offset the moving average (moving the peak of the weight) to align it perfectly with the price, balancing smoothness and responsiveness.
* **LSMA (Least Squares Moving Average):**
* *Logic:* Calculates the endpoint of a Linear Regression line for the lookback period. It essentially guesses where the price "should" be based on the best-fit line of the recent trend.
* **VWMA (Volume Weighted Moving Average):**
* *Logic:* Weights the closing price by the volume of that bar.
* *Effect:* Prices on high volume days pull the MA harder than prices on low volume days. This is excellent for validating true trend strength (i.e., a breakout on high volume will move the VWMA significantly).
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### 🛠 Features & Settings
* **Universal Switching:** Change the `Fast MA` and `Slow MA` types instantly via the settings menu.
* **Trend Cloud:** A dynamic background fill (Green/Red) highlights the crossover zone for immediate visual trend identification.
* **Strategy Mode:** Built-in Backtesting logic triggers `LONG` entries when Fast MA crosses over Slow MA, and `EXIT` when Fast MA crosses under.
### ⚠️ Disclaimer
This script is intended for educational and research purposes. The wide variety of MA combinations can produce vastly different results. Past performance is not indicative of future results. Please use proper risk management. ストラテジー
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