Step Channel Momentum Trend [ChartPrime]OVERVIEW
Step Channel Momentum Trend is a momentum-based price filtering system that adapts to market structure using pivot levels and ATR volatility. It builds a dynamic channel around a stepwise midline derived from swing highs and lows. The system colors price candles based on whether price remains inside this channel (low momentum) or breaks out (strong directional flow). This allows traders to clearly distinguish ranging conditions from trending ones and take action accordingly.
⯁ STRUCTURAL MIDLNE (STEP CHANNEL CORE)
The midline acts as the backbone of the trend system and is based on structure rather than smoothing.
Calculated as the average of the most recent confirmed Pivot High and Pivot Low.
The result is a step-like horizontal line that only updates when new pivot points are confirmed.
This design avoids lag and makes the line "snap" to recent structural shifts.
It reflects the equilibrium level between recent bullish and bearish control.
This unique step logic creates clear regime shifts and prevents noise from distorting trend interpretation.
⯁ DYNAMIC VOLATILITY BANDS (ATR FILTERING)
To detect momentum strength, the script constructs upper and lower bands using the ATR (Average True Range):
The distance from the midline is determined by ATR × multiplier (default: 200-period ATR × 0.6).
These bands adjust dynamically to volatility, expanding in high-ATR environments and contracting in calm markets.
The area between upper and lower bands represents a neutral or ranging market state.
Breakouts outside the bands are treated as significant momentum shifts.
This filtering approach ensures that only meaningful breakouts are visually emphasized — not every candle fluctuation.
⯁ MOMENTUM-BASED CANDLE COLORING
The system visually transforms price candles into momentum indicators:
When price (hl2) is above the upper band, candles are green → bullish momentum.
When price is below the lower band, candles are red → bearish momentum.
When price is between the bands, candles are orange → low or no momentum (range).
The candle body, wick, and border are all colored uniformly for visual clarity.
This gives traders instant feedback on when momentum is expanding or fading — ideal for breakout, pullback, or trend-following strategies.
⯁ PIVOT-BASED SWING ANCHORS
Each confirmed pivot is plotted as a label ⬥ directly on the chart:
They also serve as potential manual entry zones, SL/TP anchors, or confirmation points.
⯁ MOMENTUM STATE LABEL
To reinforce the current market mode, a live label is displayed at the most recent candle:
Displays either:
“ Momentum Up ” when price breaks above the upper band.
“ Momentum Down ” when price breaks below the lower band.
“ Range ” when price remains between the bands.
Label color matches the candle color for quick identification.
Automatically updates on each bar close.
This helps discretionary traders filter trades based on market phase.
USAGE
Use the green/red zones to enter with momentum and ride trending moves.
Use the orange zone to stay out or fade ranges.
The step midline can act as a breakout base, pullback anchor, or bias reference.
Combine with other indicators (e.g., order blocks, divergences, or volume) to build high-confluence systems.
CONCLUSION
Step Channel Momentum Trend gives traders a clean, adaptive framework for identifying trend direction, volatility-based breakouts, and ranging environments — all from structural logic and ATR responsiveness. Its stepwise midline provides clarity, while its dynamic color-coded candles make momentum shifts impossible to miss. Whether you’re scalping intraday momentum or managing swing entries, this tool helps you trade with the market’s rhythm — not against it.
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Volume Momentum [BackQuant]Volume Momentum
The Volume Momentum indicator is designed to help traders identify shifts in market momentum based on volume data. By analyzing the relative volume momentum, this indicator provides insights into whether the market is gaining strength (uptrend) or losing momentum (downtrend). The strategy uses a combination of percentile-based volume normalization, weighted moving averages (WMA), and exponential moving averages (EMA) to assess volume trends.
The system focuses on the relationship between price and volume, utilizing normalized volume data to highlight key market changes. This approach allows traders to focus on volume-driven price movements, helping them to capture momentum shifts early.
Key Features
1. Volume Normalization and Percentile Calculation:
The signed volume (positive when the close is higher than the open, negative when the close is lower) is normalized against the rolling average volume. This normalized volume is then subjected to a percentile interpolation, allowing for a robust statistical measure of how the current volume compares to historical data. The percentile level is customizable, with 50 representing the median.
2. Weighted and Smoothed Moving Averages for Trend Detection:
The normalized volume is smoothed using weighted moving averages (WMA) and exponential moving averages (EMA). These smoothing techniques help eliminate noise, providing a clearer view of the underlying momentum. The WMA filters out short-term fluctuations, while the EMA ensures that the most recent data points have a higher weight, making the system more responsive to current market conditions.
3. Trend Reversal Detection:
The indicator detects momentum shifts by evaluating whether the volume momentum crosses above or below zero. A positive volume momentum indicates a potential uptrend, while a negative momentum suggests a possible downtrend. These trend reversals are identified through crossover and crossunder conditions, triggering alerts when significant changes occur.
4. Dynamic Trend Background and Bar Coloring:
The script offers customizable background coloring based on the trend direction. When volume momentum is positive, the background is colored green, indicating a bullish trend. When volume momentum is negative, the background is colored red, signaling a bearish trend. Additionally, the bars themselves can be colored based on the trend, further helping traders quickly visualize market momentum.
5. Alerts for Momentum Shifts:
The system provides real-time alerts for traders to monitor when volume momentum crosses a critical threshold (zero), signaling a trend reversal. The alerts notify traders when the market momentum turns bullish or bearish, assisting them in making timely decisions.
6. Customizable Parameters for Flexible Usage:
Users can fine-tune the behavior of the indicator by adjusting various parameters:
Volume Rolling Mean: The period used to calculate the average volume for normalization.
Percentile Interpolation Length: Defines the range over which the percentile is calculated.
Percentile Level: Determines the percentile threshold (e.g., 50 for the median).
WMA and Smoothing Periods: Control the smoothing and response time of the indicator.
7. Trend Background Visualization and Trend-Based Bar Coloring:
The background fill is shaded according to whether the volume momentum is positive or negative, providing a visual cue to indicate market strength. Additionally, bars can be color-coded to highlight the trend, making it easier to see the trend’s direction without needing to analyze numerical data manually.
8. Note on Mean-Reversion Strategy:
If you take the inverse of the signals, this indicator can be adapted for a mean-reversion strategy. Instead of following the trend, the strategy would involve buying assets that are underperforming and selling assets that are overperforming, based on volume momentum. However, it’s important to note that this approach may not work effectively on highly correlated assets, as their price movements may be too similar, reducing the effectiveness of the mean-reversion strategy.
Final Thoughts
The Volume Momentum indicator offers a comprehensive approach to analyzing volume-based momentum shifts in the market. By using volume normalization, percentile interpolation, and smoothed moving averages, this system helps identify the strength and direction of market trends. Whether used for trend-following or adapted for mean-reversion, this tool provides traders with actionable insights into the market’s volume-driven movements, improving decision-making and portfolio management.
PCA Regime-Adjusted MomentumSummary
The PCA Regime-Adjusted Momentum (PCA-RAM) is an advanced market analysis tool designed to provide nuanced insights into market momentum and structural stability. It moves beyond traditional indicators by using Principal Component Analysis (PCA) to deconstruct market data into its most essential patterns.
The indicator provides two key pieces of information:
A smoothed momentum signal based on the market's dominant underlying trend.
A dynamic regime filter that gauges the stability and clarity of the market's structure, advising you when to trust or fade the momentum signals.
This allows traders to not only identify potential shifts in momentum but also to understand the context and confidence behind those signals.
Core Concepts & Methodology
The strength of this indicator lies in its sound, data-driven methodology.
1. Principal Component Analysis (PCA)
At its core, the indicator analyzes a rolling window (default 50 periods) of standardized market data (Open, High, Low, Close, and Volume). PCA is a powerful statistical technique that distills this complex, 5-dimensional data into its fundamental, uncorrelated components of variance. We focus on the First Principal Component (PC1), which represents the single most dominant pattern or "theme" driving the market's behavior in the lookback window.
2. The Momentum Signal
Instead of just looking at price, we project the current market data onto this dominant underlying pattern (PC1). This gives us a raw "projection score" that measures how strongly the current bar aligns with the historically dominant market structure. This raw score is then smoothed using two an exponential moving averages (a fast and a slow line) to create a clear, actionable momentum signal, similar in concept to a MACD.
3. The Dynamic Regime Filter
This is arguably the indicator's most powerful feature. It answers the question: "How clear is the current market picture?"
It calculates the Market Concentration Ratio, which is the percentage of total market variance explained by PC1 alone.
A high ratio indicates that the market is moving in a simple, one-dimensional way (e.g., a clear, strong trend).
A low ratio indicates the market is complex, multi-dimensional, and choppy, with no single dominant theme.
Crucially, this filter is dynamic. It compares the current concentration ratio to its own recent average, allowing it to adapt to any asset or timeframe. It automatically learns what "normal" and "choppy" look like for the specific chart you are viewing.
How to Interpret the Indicator
The indicator is displayed in a separate pane with two key visual elements:
The Momentum Lines (White & Gold)
White Line: The "Fast Line," representing the current momentum.
Gold Line: The "Slow Line," acting as the trend confirmation.
Bullish Signal: A crossover of the White Line above the Gold Line suggests a shift to positive momentum.
Bearish Signal: A crossover of the White Line below the Gold Line suggests a shift to negative momentum.
The Regime Filter (Purple & Dark Red Background)
This is your confidence gauge.
Navy Blue Background (High Concentration): The market structure is stable, simple, and trending. Momentum signals are more reliable and should be given higher priority.
Dark Red Background (Low Concentration): The market structure is complex, choppy, or directionless. Momentum signals are unreliable and prone to failure or "whipsaws." This is a signal to be cautious, tighten stops, or potentially stay out of the market.
Potential Trading Strategies
This tool is versatile and can be used in several ways:
1. Primary Signal Strategy
Condition: Wait for the background to turn Purple, confirming a stable, high-confidence regime.
Entry: Take the next crossover signal from the momentum lines (White over Gold for long, White under Gold for short).
Exit/Filter: Consider exiting positions or ignoring new signals when the background turns Navy.
2. As a Confirmation or Filter for Your Existing Strategy
Do you have a trend-following system? Only enable its long and short signals when the PCA-RAM background is Purple.
Do you have a range-trading or mean-reversion system? It might be most effective when the PCA-RAM background is Navy, indicating a lack of a clear trend.
3. Advanced Divergence Analysis
Look for classic divergences between price and the momentum lines. For example, if the price is making a new high, but the Gold Line is making a lower high, it may indicate underlying weakness in the trend, even on a Purple background. This divergence signal is more powerful because it shows that the new price high is not being confirmed by the market's dominant underlying pattern.
Money Flow Pulse💸 In markets where volatility is cheap and structure is noisy, what matters most isn’t just the move — it’s the effort behind it. Money Flow Pulse (MFP) offers a compact, color-coded readout of real-time conviction by scoring volume-weighted price action on a five-tier scale. It doesn’t try to predict reversals or validate trends. Instead, it reveals the quality of the move in progress: is it fading , driving , exhausting , or hollow ?
🎨 MFP draws from the traditional Money Flow Index (MFI), a volume-enhanced momentum oscillator, but transforms it into a modular “pressure readout” that fits seamlessly into any structural overlay. Rather than oscillating between extremes with little interpretive guidance, MFP discretizes the flow into clean, color-coded regimes ranging from strong inflow (+2) to strong outflow (–2). The result is a responsive diagnostic layer that complements, rather than competes with, tools like ATR and/or On-Balance Volume.
5️⃣ MFP uses a normalized MFI value smoothed over 13 periods and classified into a 5-tier readout of Volume-Driven Conviction :
🍆 Exhaustion Inflow — usually a top or blowoff; not strength, but overdrive (+2)
🥝 Active Inflow — supportive of trend continuation (+1)
🍋 Neutral — chop, coil, or fakeouts (0)
🍑 Selling Intent — weakening structure, possible fade setups (-1)
🍆 Exhaustion Outflow — often signals forced selling or accumulation traps (-2)
🎭 These tiers are not arbitrary. Each one is tuned to reflect real capital behavior across timeframes. For instance, while +1 may support continuation, +2 often precedes exhaustion — especially on the lower timeframes. Similarly, a –1 reading during a pullback suggests sell-side pressure is building, but a shift to –2 may mean capitulation is already underway. The difference between the two can define whether a move is tradable continuation or strategic exhaustion .
🌊 The MFI ROC (Rate of Change) feature can be toggled to become a volatility-aware pulse monitor beneath the derived MFI tier. Instead of scoring direction or structure, ROC reveals how fast conviction is changing — not just where it’s headed, but how hard it's accelerating or decaying. It measures the raw Δ between the current and previous MFI values, exposing bursts of energy, fading pressure, or transitional churn .
🎢 Visually, ROC appears as a low-opacity area fill, anchored to a shared lemon-yellow zero line. When the green swell rises, buying pressure is accelerating; when the red drops, flow is actively deteriorating. A subtle bump may signal early interest — while a steep wave hints at an emotional overreaction. The ROC value itself provides numeric insight alongside the raw MFI score. A reading of +3.50 implies strong upside momentum in the flow — often supporting trend ignition. A score of –6.00 suggests rapid deceleration or full exhaustion — often preceding reversals or failed breakouts.
・ MFI shows you where the flow is
・ ROC tells you how it’s behaving
😎 This blend reveals not just structure or intent — but also urgency . And in flow-based trading, urgency often precedes outcome.
🧩 Divergence isn’t delay — it’s disagreement . One of the most revealing features of MFP is how it exposes momentum dissonance — situations where price and flow part ways. These divergences often front-run pivots , traps , or velocity stalls . Unlike RSI-style divergence, which whispers of exhaustion, MFI divergence signals a breakdown in conviction. The structure may extend — but the effort isn’t there.
・ Price ▲ MFI ▼ → Effortless Markup : Often signals distribution or a grind into liquidity. Without rising MFI, the rally lacks true flow participation — a warning of fragility.
・ Price ▼ MFI ▲ → Absorption or Early Accumulation : Price breaks down, but money keeps flowing in — a hidden bid. Watch for MFI tier shifts or ROC bursts to confirm a reversal.
🏄♂️ These moments don’t require signal overlays or setup hunting. MFP narrates the imbalance. When price breaks structure but flow does not — or vice versa — you’re not seeing trend, you’re seeing disagreement, and that's where edge begins.
💤 MFP is especially effective on intraday charts where volume dislocations matter most. On the 1H or 15m chart, it helps distinguish between breakouts with conviction versus those lacking flow. On higher timeframes, its resolution softens — it becomes more of a drift indicator than a trigger device. That’s by design: MFP prioritizes pulse, not position. It’s not the fire, it’s the heat.
📎 Use MFP in confluence with structural overlays to validate price behavior. A ribbon expansion with rising MFP is real. A compression breakout without +1 flow is "fishy". Watch how MFP behaves near key zones like anchored VWAP, MAs or accumulation pivots. When MFP rises into a +2 and fails to sustain, the reversal isn’t just technical — it’s flow-based.
🪟 MFP doesn’t speak loudly, but it never whispers without reason. It’s the pulse check before action — the breath of the move before the breakout. While it stays visually minimal on the chart, the true power is in the often overlooked Data Window, where traders can read and interpret the score in real time. Once internalized, these values give structure-aware traders a framework for conviction, continuation, or caution.
🛜 MFP doesn’t chase momentum — it confirms conviction. And in markets defined by noise, that signal isn’t just helpful — it’s foundational.
Stochastic Order Flow Momentum [ScorsoneEnterprises]This indicator implements a stochastic model of order flow using the Ornstein-Uhlenbeck (OU) process, combined with a Kalman filter to smooth momentum signals. It is designed to capture the dynamic momentum of volume delta, representing the net buying or selling pressure per bar, and highlight potential shifts in market direction. The volume delta data is sourced from TradingView’s built-in functionality:
www.tradingview.com
For a deeper dive into stochastic processes like the Ornstein-Uhlenbeck model in financial contexts, see these research articles: arxiv.org and arxiv.org
The SOFM tool aims to reveal the momentum and acceleration of order flow, modeled as a mean-reverting stochastic process. In markets, order flow often oscillates around a baseline, with bursts of buying or selling pressure that eventually fade—similar to how physical systems return to equilibrium. The OU process captures this behavior, while the Kalman filter refines the signal by filtering noise. Parameters theta (mean reversion rate), mu (mean level), and sigma (volatility) are estimated by minimizing a squared-error objective function using gradient descent, ensuring adaptability to real-time market conditions.
How It Works
The script combines a stochastic model with signal processing. Here’s a breakdown of the key components, including the OU equation and supporting functions.
// Ornstein-Uhlenbeck model for volume delta
ou_model(params, v_t, lkb) =>
theta = clamp(array.get(params, 0), 0.01, 1.0)
mu = clamp(array.get(params, 1), -100.0, 100.0)
sigma = clamp(array.get(params, 2), 0.01, 100.0)
error = 0.0
v_pred = array.new(lkb, 0.0)
array.set(v_pred, 0, array.get(v_t, 0))
for i = 1 to lkb - 1
v_prev = array.get(v_pred, i - 1)
v_curr = array.get(v_t, i)
// Discretized OU: v_t = v_{t-1} + theta * (mu - v_{t-1}) + sigma * noise
v_next = v_prev + theta * (mu - v_prev)
array.set(v_pred, i, v_next)
v_curr_clean = na(v_curr) ? 0 : v_curr
v_pred_clean = na(v_next) ? 0 : v_next
error := error + math.pow(v_curr_clean - v_pred_clean, 2)
error
The ou_model function implements a discretized Ornstein-Uhlenbeck process:
v_t = v_{t-1} + theta (mu - v_{t-1})
The model predicts volume delta (v_t) based on its previous value, adjusted by the mean-reverting term theta (mu - v_{t-1}), with sigma representing the volatility of random shocks (approximated in the Kalman filter).
Parameters Explained
The parameters theta, mu, and sigma represent distinct aspects of order flow dynamics:
Theta:
Definition: The mean reversion rate, controlling how quickly volume delta returns to its mean (mu). Constrained between 0.01 and 1.0 (e.g., clamp(array.get(params, 0), 0.01, 1.0)).
Interpretation: A higher theta indicates faster reversion (short-lived momentum), while a lower theta suggests persistent trends. Initial value is 0.1 in init_params.
In the Code: In ou_model, theta scales the pull toward \mu, influencing the predicted v_t.
Mu:
Definition: The long-term mean of volume delta, representing the equilibrium level of net buying/selling pressure. Constrained between -100.0 and 100.0 (e.g., clamp(array.get(params, 1), -100.0, 100.0)).
Interpretation: A positive mu suggests a bullish bias, while a negative mu indicates bearish pressure. Initial value is 0.0 in init_params.
In the Code: In ou_model, mu is the target level that v_t reverts to over time.
Sigma:
Definition: The volatility of volume delta, capturing the magnitude of random fluctuations. Constrained between 0.01 and 100.0 (e.g., clamp(array.get(params, 2), 0.01, 100.0)).
Interpretation: A higher sigma reflects choppier, noisier order flow, while a lower sigma indicates smoother behavior. Initial value is 0.1 in init_params.
In the Code: In the Kalman filter, sigma contributes to the error term, adjusting the smoothing process.
Summary:
theta: Speed of mean reversion (how fast momentum fades).
mu: Baseline order flow level (bullish or bearish bias).
sigma: Noise level (variability in order flow).
Other Parts of the Script
Clamp
A utility function to constrain parameters, preventing extreme values that could destabilize the model.
ObjectiveFunc
Defines the objective function (sum of squared errors) to minimize during parameter optimization. It compares the OU model’s predicted volume delta to observed data, returning a float to be minimized.
How It Works: Calls ou_model to generate predictions, computes the squared error for each timestep, and sums it. Used in optimization to assess parameter fit.
FiniteDifferenceGradient
Calculates the gradient of the objective function using finite differences. Think of it as finding the "slope" of the error surface for each parameter. It nudges each parameter (theta, mu, sigma) by a small amount (epsilon) and measures the change in error, returning an array of gradients.
Minimize
Performs gradient descent to optimize parameters. It iteratively adjusts theta, mu, and sigma by stepping down the "hill" of the error surface, using the gradients from FiniteDifferenceGradient. Stops when the gradient norm falls below a tolerance (0.001) or after 20 iterations.
Kalman Filter
Smooths the OU-modeled volume delta to extract momentum. It uses the optimized theta, mu, and sigma to predict the next state, then corrects it with observed data via the Kalman gain. The result is a cleaner momentum signal.
Applied
After initializing parameters (theta = 0.1, mu = 0.0, sigma = 0.1), the script optimizes them using volume delta data over the lookback period. The optimized parameters feed into the Kalman filter, producing a smoothed momentum array. The average momentum and its rate of change (acceleration) are calculated, though only momentum is plotted by default.
A rising momentum suggests increasing buying or selling pressure, while a flattening or reversing momentum indicates fading activity. Acceleration (not plotted here) could highlight rapid shifts.
Tool Examples
The SOFM indicator provides a dynamic view of order flow momentum, useful for spotting directional shifts or consolidation.
Low Time Frame Example: On a 5-minute chart of SEED_ALEXDRAYM_SHORTINTEREST2:NQ , a rising momentum above zero with a lookback of 5 might signal building buying pressure, while a drop below zero suggests selling dominance. Crossings of the zero line can mark transitions, though the focus is on trend strength rather than frequent crossovers.
High Time Frame Example: On a daily chart of NYSE:VST , a sustained positive momentum could confirm a bullish trend, while a sharp decline might warn of exhaustion. The mean-reverting nature of the OU process helps filter out noise on longer scales. It doesn’t make the most sense to use this on a high timeframe with what our data is.
Choppy Markets: When momentum oscillates near zero, it signals indecision or low conviction, helping traders avoid whipsaws. Larger deviations from zero suggest stronger directional moves to act on, this is on $STT.
Inputs
Lookback: Users can set the lookback period (default 5) to adjust the sensitivity of the OU model and Kalman filter. Shorter lookbacks react faster but may be noisier; longer lookbacks smooth more but lag slightly.
The user can also specify the timeframe they want the volume delta from. There is a default way to lower and expand the time frame based on the one we are looking at, but users have the flexibility.
No indicator is 100% accurate, and SOFM is no exception. It’s an estimation tool, blending stochastic modeling with signal processing to provide a leading view of order flow momentum. Use it alongside price action, support/resistance, and your own discretion for best results. I encourage comments and constructive criticism.
JW Momentum IndicatorJW Momentum Indicator
This indicator provides clear and actionable buy/sell signals based on a combination of volume-enhanced momentum, divergence detection, and volatility adjustment. It's designed to identify potential trend reversals and momentum shifts with a focus on high-probability setups.
Key Features:
Volume-Enhanced Momentum: The indicator calculates a custom oscillator that combines momentum with volume, giving more weight to momentum when volume is significant. This helps to identify strong momentum moves.
Divergence Detection: It detects bullish and bearish divergences using pivot highs and lows, highlighting potential trend reversals.
Volatility-Adjusted Signals: The indicator adjusts signal sensitivity based on the Average True Range (ATR), making it more reliable in varying market conditions.
Clear Visuals: Buy and sell signals are clearly indicated with up and down triangles, while divergences are highlighted with distinct labels.
How to Use:
Buy Signals: Look for green up triangles or bullish divergence labels.
Sell Signals: Look for red down triangles or bearish divergence labels.
Oscillator and Thresholds: Use the plotted oscillator and thresholds to confirm signal strength.
Parameters:
Momentum Period: Adjusts the length of the momentum calculation.
Volume Average Period: Adjusts the length of the volume average calculation.
Volatility Period: Adjusts the length of the ATR calculation.
Volatility Multiplier: Adjusts the sensitivity of the volatility-adjusted signals.
Disclaimer:
This indicator is for informational purposes only and should not be considered financial advice. Always conduct 1 thorough research and use appropriate risk management techniques when trading.
TMO (True Momentum Oscillator)TMO ((T)rue (M)omentum (O)scilator)
Created by Mobius V01.05.2018 TOS Convert to TV using Claude 3.7 and ChatGPT 03 Mini :
TMO calculates momentum using the delta of price. Giving a much better picture of trend, tend reversals and divergence than momentum oscillators using price.
True Momentum Oscillator (TMO)
The True Momentum Oscillator (TMO) is a momentum-based technical indicator designed to identify trend direction, trend strength, and potential reversal points in the market. It's particularly useful for spotting overbought and oversold conditions, aiding traders in timing their entries and exits.
How it Works:
The TMO calculates market momentum by analyzing recent price action:
Momentum Calculation:
For a user-defined length (e.g., 14 bars), TMO compares the current closing price to past open prices. It assigns:
+1 if the current close is greater than the open price of the past bar (indicating bullish momentum).
-1 if it's less (indicating bearish momentum).
0 if there's no change.
The sum of these scores gives a raw momentum measure.
EMA Smoothing:
To reduce noise and false signals, this raw momentum is smoothed using Exponential Moving Averages (EMAs):
First, the raw data is smoothed by an EMA over a short calculation period (default: 5).
Then, it undergoes additional smoothing through another EMA (default: 3 bars), creating the primary "Main" line of the indicator.
Lastly, a "Signal" line is derived by applying another EMA (also default: 3 bars) to the main line, adding further refinement.
Trend Identification:
The indicator plots two lines:
Main Line: Indicates current momentum strength and direction.
Signal Line: Acts as a reference line, similar to a moving average crossover system.
When the Main line crosses above the Signal line, it suggests strengthening bullish momentum. Conversely, when the Main line crosses below the Signal line, it indicates increasing bearish momentum.
Overbought/Oversold Levels:
The indicator identifies key levels based on the chosen length parameter:
Overbought zone (positive threshold): Suggests the market might be overheated, and a potential bearish reversal or pullback could occur.
Oversold zone (negative threshold): Suggests the market might be excessively bearish, signaling a potential bullish reversal.
Clouds visually mark these overbought/oversold areas, making it easy to see potential reversal zones.
Trading Applications:
Trend-following: Traders can enter positions based on crossovers of the Main and Signal lines.
Reversals: The overbought and oversold areas highlight high-probability reversal points.
Momentum confirmation: Use TMO to confirm price action or other technical signals, improving trade accuracy and timing.
The True Momentum Oscillator provides clarity in identifying momentum shifts, making it a valuable addition to various trading strategies.
Bollinger Momentum Deviation | QuantEdgeBIntroducing Bollinger Momentum Deviation (BMD) by QuantEdgeB
🛠️ Overview
Bollinger Momentum Deviation (BMD) is a trend-following momentum indicator designed to identify strong price movements while also detecting overbought and oversold conditions in ranging markets.
By normalizing a simple moving average (SMA) with standard deviation, BMD captures momentum shifts, helping traders make data-driven entries and exits. In trending conditions, it acts as a momentum confirmation tool, while in ranging markets, it highlights mean-reversion opportunities for profit-taking or re-accumulation.
BMD combines the best of both worlds—a robust trend-following framework with an integrated volatility-based overbought/oversold detection system.
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✨ Key Features
🔹 Momentum & Trend-Following Core
Built upon a normalized SMA with standard deviation filtering, BMD efficiently tracks price movements while reducing lag.
🔹 Overbought/Oversold Market Detection
By dynamically adjusting its thresholds based on standard deviation, it identifies high-probability reversion zones in sideways markets.
🔹 Adaptive Normalization Mechanism
Ensures consistent signal reliability across different assets and timeframes by standardizing momentum fluctuations.
🔹 Customizable Visual & Signal Settings
Includes multiple color modes, extra plots, and trend labels, making it easy to align with different trading styles.
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📊 How It Works
1️⃣ Normalized Momentum Calculation
BMD computes a normalized momentum score using a simple moving average (SMA) combined with a standard deviation (SD) filter to create dynamic upper and lower bands. The final momentum score is derived by normalizing the price within this volatility-adjusted range. This normalization makes momentum readings comparable across different price levels and timeframes.
2️⃣ Standard Deviation Filtering
Unlike traditional approaches where standard deviation is derived from price as is the first SD, BMDs second SD is driven from the normalized momentum oscillator itself. This allows for a volatility-adjusted smoothing mechanism that adapts to momentum shifts rather than raw price fluctuations. This ensures that the trend signals remain dynamic and responsive, filtering out short-term noise while keeping the core momentum structure intact. By applying standard deviation directly to the oscillator, BMD achieves a self-regulating feedback loop, improving accuracy in both trending and range-bound conditions.
3️⃣ Signal Generation
✅ Long Signal → Upper BMD SD > Long Threshold (83)
❌ Short Signal → Lower BMD SD < Short Threshold (60)
📌 Additional Features:
- Overbought Zone → Values above 130 indicate price extension.
- Oversold Zone → Values below -10 suggest potential accumulation.
- Momentum Labels → Optional "Long" and "Short" markers for clear trade identification.
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👥 Who Should Use It?
✅ Trend Traders & Momentum Followers → Use BMD as a confirmation tool for strong directional trends.
✅ Range & Mean Reversion Traders → Identify reversal opportunities at extreme BMD levels.
✅ Swing & Position Traders → Utilize normalized momentum shifts for data-driven entries & exits.
✅ Systematic & Quant Traders → Implement BMD within algorithmic frameworks for adaptive market detection.
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⚙️ Customization & Default Settings
🔧 Key Custom Inputs:
- Base Length (Default: 40) → Defines the SMA calculation period.
- Standard Deviation Length (Default: 50) → Controls the volatility filter strength.
- SD Multiplier (Default: 0-7) → Adjusts the sensitivity of the momentum filter.
- Long Threshold (Default: 83) → Above this level, momentum is bullish.
- Short Threshold (Default: 60) → Below this level, momentum weakens.
- Visual Customizations → Multiple color themes, extra plots, and trend labels available.
🚀 By default, BMD is optimized for trend-following and momentum filtering while remaining adaptable to various trading strategies.
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📌 How to Use Bollinger Momentum Deviation (BMD) in Trading
1️⃣ Trend-Following Strategy (Momentum Confirmation)
✔ Enter long positions when BMD crosses above the long threshold (83), confirming upward momentum.
✔ Enter short positions when BMD crosses below the short threshold (60), confirming downward momentum.
✔ Stay in trades as long as BMD remains in trend direction, filtering out noise.
2️⃣ Mean Reversion Strategy (Overbought/Oversold Conditions)
✔ Take profits or hedge when BMD crosses above 130 (overbought).
✔ Re-accumulate positions when BMD drops below -10 (oversold).
📌 Why?
- In trending markets, follow BMD’s momentum confirmation.
- In ranging markets, use BMD’s normalized bands to buy at deep discounts and sell into strength.
_____
📌 Conclusion
Bollinger Momentum Deviation (BMD) is a versatile momentum indicator that combines trend-following mechanics with volatility-adjusted mean reversion zones. By normalizing SMA-based momentum shifts, BMD ensures robust signal reliability across different assets and timeframes.
🔹 Key Takeaways:
1️⃣ Momentum Confirmation & Trend Detection – Captures directional strength with dynamic filtering.
2️⃣ Overbought/Oversold Conditions – Identifies reversal opportunities in sideways markets.
3️⃣ Adaptive & Customizable – Works across different timeframes and trading styles.
🔹 Disclaimer: Past performance is not indicative of future results. No trading strategy can guarantee success in financial markets.
🔹 Strategic Advice: Always backtest, optimize, and align parameters with your trading objectives and risk tolerance before live trading.
Balance Price Range (BPR) IndicatorOverview
The BPR with Directional Momentum-Filtered Breakouts indicator is designed to identify Balanced Price Ranges (BPR) and d etect high-probability breakouts and breakdowns with directional momentum confirmation . By leveraging historical BPR structures, EMA-based momentum filtering , and a trade cooldown mechanism , this script provides a structured approach to identifying potential trading opportunities while reducing false signals.
This invite-only indicator is ideal for traders who seek precise breakout confirmation, reduced noise, and trend-following logic while maintaining flexibility through adjustable parameters.
How It Works
The script follows a multi-step breakout detection process by integrating multiple key technical components:
1. Balanced Price Range (BPR) Detection:
• A Balanced Candle is identified when the price remains within a specific percentage of its range midpoint.
• These BPR zones represent areas of equilibrium , where a breakout or breakdown is likely to occur.
• The script historically tracks BPR levels across the entire chart to monitor price action around key areas.
2. Momentum-Filtered Breakout & Breakdown Logic:
• Bullish Breakout: Occurs when the price breaks above the historical BPR high with bullish momentum.
• Bearish Breakdown: Occurs when the price breaks below the historical BPR low with bearish momentum.
• Momentum Confirmation: Each breakout requires a strong directional move, measured against the Exponential Moving Average (EMA) .
• Only confirmed breakouts are marked, reducing the likelihood of false signals in choppy markets.
3. Candle-Based Background Visualization:
• Grey Background: Represents a Balanced Price Range (BPR), indicating potential breakout zones.
• Green Background: Indicates a Bullish Breakout when the price successfully breaks and holds above the BPR high.
• Red Background: Indicates a Bearish Breakdown when the price drops below the BPR low.
4. Trade Cooldown Mechanism:
• Prevents consecutive signals from triggering too frequently.
• Default cooldown period: 5 bars (adjustable).
• Ensures that trades are not clustered, improving signal quality.
5. EMA for Trend Direction & Confirmation:
• A 20-period EMA (default, adjustable) is used to confirm trade direction.
• Breakouts above the EMA align with uptrend continuation.
• Breakdowns below the EMA align with downtrend momentum.
Key Features
✔️ Historical BPR Detection – Tracks past BPR levels across the entire chart for structured breakout zones.
✔️ Momentum-Based Breakouts – Ensures breakouts are confirmed by directional price movement before generating signals.
✔️ Candle-Based Background Logic – Subtle candle highlights rather than full background fills, for better chart clarity.
✔️ Trade Cooldown Period – Prevents consecutive buy/sell signals within a defined period, improving signal efficiency.
✔️ Dynamic EMA Confirmation – Ensures trades align with the overall trend, reducing counter-trend trades.
✔️ Customizable Inputs – Adjust breakout thresholds, EMA length, and cooldown periods as per trading style.
✔️ Works Across Multiple Timeframes – Can be applied to intraday, swing, and positional trading strategies.
How to Use
1. Look for Balanced Price Ranges ( BPR )
• These zones highlight equilibrium areas where price is likely to break out.
• Grey-shaded candles indicate potential breakout zones.
2. Monitor for Bullish or Bearish Breakouts
• A green candle background signals a bullish breakout above BPR.
• A red candle background signals a bearish breakdown below BPR.
• The EMA filter helps confirm whether the breakout aligns with the prevailing trend.
3. Follow the Cooldown Logic
• After a breakout signal, wait for the cooldown period before another trade is allowed.
• This helps filter out noisy price action and prevents excessive trading.
4. Use Alongside Other Indicators
• Works well with volume analysis, support/resistance levels, and price action strategies.
• Can be combined with other momentum indicators for further trade confirmation.
Why This Combination?
Unlike generic breakout indicators, this script uniquely combines:
• BPR historical structures for defining potential breakout zones.
• Momentum-based breakout filtering using EMA confirmation.
• Trade cooldown logic to avoid excessive trading signals.
• Subtle candle-based highlights instead of cluttered full-background fills.
This structured approach makes the indicator more robust, adaptive, and reliable in different market conditions.
Why It’s Worth Using?
🔹 Avoid False Breakouts: Built-in momentum confirmation prevents weak or fake breakouts.
🔹 Clean Visualization: No excessive overlays—just precise, meaningful background coloring for breakouts.
🔹 Works in Any Market: Use on stocks, crypto, forex, indices, and commodities across different timeframes.
🔹 User-Friendly & Customizable: Fine-tune parameters to match individual trading styles.
⚠️ Note: This is an Invite-Only script. Access is granted to selected users.
✅ If you find it useful, consider incorporating it into your trend-following & breakout trading strategies.
🚀 Optimize your trading with structured breakout detection! 🚀
Blockchain Fundamentals: Liquidity Cycle MomentumLiquidity Cycle Momentum Indicator
Overview:
This indicator analyzes global liquidity trends by calculating a unique Liquidity Index and measuring its year-over-year (YoY) percentage change. It then applies a momentum oscillator to the YoY change, providing insights into the cyclical momentum of liquidity. The indicator incorporates a limited historical data workaround to ensure accurate calculations even when the chart’s history is short.
Features Breakdown:
1. Limited Historical Data Workaround
Function: The limit(length) function adjusts the lookback period when there isn’t enough historical data (i.e., near the beginning of the chart), ensuring that calculations do not break due to insufficient data.
2. Global Liquidity Calculation
Data Sources:
TVC:CN10Y (10-year yield from China)
TVC:DXY (US Dollar Index)
ECONOMICS:USCBBS (US Central Bank Balance Sheet)
FRED:JPNASSETS (Japanese assets)
ECONOMICS:CNCBBS (Chinese Central Bank Balance Sheet)
FRED:ECBASSETSW (ECB assets)
Calculation Methodology:
A ratio is computed (cn10y / dxy) to adjust for currency influences.
The Liquidity Index is then derived by multiplying this ratio with the sum of the other liquidity components.
3. Year-over-Year (YoY) Percent Change
Computation:
The indicator determines the number of bars that approximately represent one year.
It then compares the current Liquidity Index to its value one year ago, calculating the YoY percentage change.
4. Momentum Oscillator on YoY Change
Oscillator Components:
1. Calculated using the Chande Momentum Oscillator (CMO) applied to the YoY percent change with a user-defined momentum length.
2. A weighted moving average (WMA) that smooths the momentum signal.
3. Overbought and Oversold zones
Signal Generation:
Buy Signal: Triggered when the momentum crosses upward from an oversold condition, suggesting a potential upward shift in liquidity momentum.
Sell Signal: Triggered when crosses below an overbought condition, indicating potential downward momentum.
State Management:
The indicator maintains a state variable to avoid repeated signals, ensuring that a new buy or sell signal is only generated when there’s a clear change in momentum.
5. Visual Presentation and Alerts
Plots:
The oscillator value and signalline are plotted for visual analysis.
Overbought and oversold levels are marked with dashed horizontal lines.
Signal Markers:
Buy and sell signals are marked with green and maroon circles, respectively.
Background Coloration:
Optionally, the chart’s background bars are colored (yellow for buy signals and fuchsia for sell signals) to enhance visual cues when signals are triggered.
Conclusion
In summary, the Liquidity Cycle Momentum Indicator provides a robust framework to analyze liquidity trends by combining global liquidity data, YoY changes, and momentum oscillation. This makes it an effective tool for traders and analysts looking to identify cyclical shifts in liquidity conditions and potential turning points in the market.
Cluster Reversal Zones📌 Cluster Reversal Zones – Smart Market Turning Point Detector
📌 Category : Public (Restricted/Closed-Source) Indicator
📌 Designed for : Traders looking for high-accuracy reversal zones based on price clustering & liquidity shifts.
🔍 Overview
The Cluster Reversal Zones Indicator is an advanced market reversal detection tool that helps traders identify key turning points using a combination of price clustering, order flow analysis, and liquidity tracking. Instead of relying on static support and resistance levels, this tool dynamically adjusts to live market conditions, ensuring traders get the most accurate reversal signals possible.
📊 Core Features:
✅ Real-Time Reversal Zone Mapping – Detects high-probability market turning points using price clustering & order flow imbalance.
✅ Liquidity-Based Support/Resistance Detection – Identifies strong rejection zones based on real-time liquidity shifts.
✅ Order Flow Sensitivity for Smart Filtering – Filters out weak reversals by detecting real market participation behind price movements.
✅ Momentum Divergence for Confirmation – Aligns reversal zones with momentum divergences to increase accuracy.
✅ Adaptive Risk Management System – Adjusts risk parameters dynamically based on volatility and trend state.
🔒 Justification for Mashup
The Cluster Reversal Zones Indicator contains custom-built methodologies that extend beyond traditional support/resistance indicators:
✔ Smart Price Clustering Algorithm: Instead of plotting fixed support/resistance lines, this system analyzes historical price clustering to detect active reversal areas.
✔ Order Flow Delta & Liquidity Shift Sensitivity: The tool tracks real-time order flow data, identifying price zones with the highest accumulation or distribution levels.
✔ Momentum-Based Reversal Validation: Unlike traditional indicators, this tool requires a momentum shift confirmation before validating a potential reversal.
✔ Adaptive Reversal Filtering Mechanism: Uses a combination of historical confluence detection + live market validation to improve accuracy.
🛠️ How to Use:
• Works well for reversal traders, scalpers, and swing traders seeking precise turning points.
• Best combined with VWAP, Market Profile, and Delta Volume indicators for confirmation.
• Suitable for Forex, Indices, Commodities, Crypto, and Stock markets.
🚨 Important Note:
For educational & analytical purposes only.
[COG] Adaptive Squeeze Intensity 📊 Adaptive Squeeze Intensity (ASI) Indicator
🎯 Overview
The Adaptive Squeeze Intensity (ASI) indicator is an advanced technical analysis tool that combines the power of volatility compression analysis with momentum, volume, and trend confirmation to identify high-probability trading opportunities. It quantifies the degree of price compression using a sophisticated scoring system and provides clear entry signals for both long and short positions.
⭐ Key Features
- 📈 Comprehensive squeeze intensity scoring system (0-100)
- 📏 Multiple Keltner Channel compression zones
- 📊 Volume analysis integration
- 🎯 EMA-based trend confirmation
- 🎨 Proximity-based entry validation
- 📱 Visual status monitoring
- 🎨 Customizable color schemes
- ⚡ Clear entry signals with directional indicators
🔧 Components
1. 📐 Squeeze Intensity Score (0-100)
The indicator calculates a total squeeze intensity score based on four components:
- 📊 Band Convergence (0-40 points): Measures the relationship between Bollinger Bands and Keltner Channels
- 📍 Price Position (0-20 points): Evaluates price location relative to the base channels
- 📈 Volume Intensity (0-20 points): Analyzes volume patterns and thresholds
- ⚡ Momentum (0-20 points): Assesses price momentum and direction
2. 🎨 Compression Zones
Visual representation of squeeze intensity levels:
- 🔴 Extreme Squeeze (80-100): Red zone
- 🟠 Strong Squeeze (60-80): Orange zone
- 🟡 Moderate Squeeze (40-60): Yellow zone
- 🟢 Light Squeeze (20-40): Green zone
- ⚪ No Squeeze (0-20): Base zone
3. 🎯 Entry Signals
The indicator generates entry signals based on:
- ✨ Squeeze release confirmation
- ➡️ Momentum direction
- 📊 Candlestick pattern confirmation
- 📈 Optional EMA trend alignment
- 🎯 Customizable EMA proximity validation
⚙️ Settings
🔧 Main Settings
- Base Length: Determines the calculation period for main indicators
- BB Multiplier: Sets the Bollinger Bands deviation multiplier
- Keltner Channel Multipliers: Three separate multipliers for different compression zones
📈 Trend Confirmation
- Four customizable EMA periods (default: 21, 34, 55, 89)
- Optional trend requirement for entry signals
- Adjustable EMA proximity threshold
📊 Volume Analysis
- Customizable volume MA length
- Adjustable volume threshold for signal confirmation
- Option to enable/disable volume analysis
🎨 Visualization
- Customizable bullish/bearish colors
- Optional intensity zones display
- Status monitor with real-time score and state information
- Clear entry arrows and background highlights
💻 Technical Code Breakdown
1. Core Calculations
// Base calculations for EMAs
ema_1 = ta.ema(close, ema_length_1)
ema_2 = ta.ema(close, ema_length_2)
ema_3 = ta.ema(close, ema_length_3)
ema_4 = ta.ema(close, ema_length_4)
// Proximity calculation for entry validation
ema_prox_raw = math.abs(close - ema_1) / ema_1 * 100
is_close_to_ema_long = close > ema_1 and ema_prox_raw <= prox_percent
```
### 2. Squeeze Detection System
```pine
// Bollinger Bands setup
BB_basis = ta.sma(close, length)
BB_dev = ta.stdev(close, length)
BB_upper = BB_basis + BB_mult * BB_dev
BB_lower = BB_basis - BB_mult * BB_dev
// Keltner Channels setup
KC_basis = ta.sma(close, length)
KC_range = ta.sma(ta.tr, length)
KC_upper_high = KC_basis + KC_range * KC_mult_high
KC_lower_high = KC_basis - KC_range * KC_mult_high
```
### 3. Scoring System Implementation
```pine
// Band Convergence Score
band_ratio = BB_width / KC_width
convergence_score = math.max(0, 40 * (1 - band_ratio))
// Price Position Score
price_range = math.abs(close - KC_basis) / (KC_upper_low - KC_lower_low)
position_score = 20 * (1 - price_range)
// Final Score Calculation
squeeze_score = convergence_score + position_score + vol_score + mom_score
```
### 4. Signal Generation
```pine
// Entry Signal Logic
long_signal = squeeze_release and
is_momentum_positive and
(not use_ema_trend or (bullish_trend and is_close_to_ema_long)) and
is_bullish_candle
short_signal = squeeze_release and
is_momentum_negative and
(not use_ema_trend or (bearish_trend and is_close_to_ema_short)) and
is_bearish_candle
```
📈 Trading Signals
🚀 Long Entry Conditions
- Squeeze release detected
- Positive momentum
- Bullish candlestick
- Price above relevant EMAs (if enabled)
- Within EMA proximity threshold (if enabled)
- Sufficient volume confirmation (if enabled)
🔻 Short Entry Conditions
- Squeeze release detected
- Negative momentum
- Bearish candlestick
- Price below relevant EMAs (if enabled)
- Within EMA proximity threshold (if enabled)
- Sufficient volume confirmation (if enabled)
⚠️ Alert Conditions
- 🔔 Extreme squeeze level reached (score crosses above 80)
- 🚀 Long squeeze release signal
- 🔻 Short squeeze release signal
💡 Tips for Usage
1. 📱 Use the status monitor to track real-time squeeze intensity and state
2. 🎨 Pay attention to the color gradient for trend direction and strength
3. ⏰ Consider using multiple timeframes for confirmation
4. ⚙️ Adjust EMA and proximity settings based on your trading style
5. 📊 Use volume analysis for additional confirmation in liquid markets
📝 Notes
- 🔧 The indicator combines multiple technical analysis concepts for robust signal generation
- 📈 Suitable for all tradable markets and timeframes
- ⭐ Best results typically achieved in trending markets with clear volatility cycles
- 🎯 Consider using in conjunction with other technical analysis tools for confirmation
⚠️ Disclaimer
This technical indicator is designed to assist in analysis but should not be considered as financial advice. Always perform your own analysis and risk management when trading.
Simple Trend Strength & MomentumThis indicator will show a combination of Trend Strength, Volatility using an Adaptive Moving Average (AMA), and Market Momentum.
You can use this indicator to identify trends, volatility, and momentum shifts in real-time, making it an excellent tool for both trend-following and breakout strategies.
The three main features of this indicator are:
Adaptive Moving Average (AMA): Tracks the trend direction with a dynamic smoothing factor that adjusts based on market volatility. The AMA line changes color based on trend strength (green for bullish, red for bearish). I manually compute the Adaptive Moving Average (AMA) using a smoothing factor derived from the market's efficiency ratio. I have used fastLength and slowLength to control the responsiveness of the AMA.
Volatility Bands: Plots upper and lower bands around the AMA line, indicating price volatility. These bands dynamically adjust based on ATR, with a color gradient that changes intensity based on market volatility.
Momentum Circles: Positive momentum (ROC above the threshold) is shown as a green circle below the bar, while negative momentum is marked by a red circle above the bar. This makes it easy to spot momentum shifts.
The green dots in the indicator represent positive momentum. Specifically, they are displayed when the Rate of Change (ROC) of the price exceeds a predefined threshold (set as threshold in the input). This indicates that the market is experiencing upward price movement at a rate faster than the defined threshold.
How it works:
Rate of Change (ROC) measures the percentage change in price over a specified period (in this case, 14 periods).
When the ROC is greater than the set threshold (1.5 by default), a green circle (dot) is plotted below the price bar to signal that there is significant positive momentum.
This can be seen as an indicator of bullish momentum, where price is increasing at a relatively fast pace compared to previous periods.
The green dots help you spot when the price is moving upward rapidly, potentially signaling a good time to enter a long position or watch for further price action.
NOTE: It is vice versa for red dots.
MAG 7 - Weighted Multi-Symbol Momentum + ExtrasOverview
This indicator aggregates the percentage change of multiple symbols into a single “weighted momentum” value. You can set individual weights to emphasize or de-emphasize particular stocks. The script plots two key items:
The default tickers in the script are:
AAPL (Apple)
AMZN (Amazon)
NVDA (NVIDIA)
MSFT (Microsoft)
GOOGL (Alphabet/Google)
TSLA (Tesla)
META (Meta Platforms/Facebook)
Raw Weighted Momentum (Histogram):
Each bar represents the combined (weighted) percentage change across your chosen symbols for that bar.
Bars are colored green if the momentum is above zero, or red if below zero.
Smoothed Momentum (Yellow Line):
An Exponential Moving Average (EMA) of the raw momentum for a smoother trend view.
Helps visualize when short-term momentum is accelerating or decelerating relative to its average.
Features
Symbol Inputs: Up to seven user-defined tickers, with weights for each symbol.
Smoothing Period: Set a custom lookback length to calculate the EMA (or switch to SMA in the code if you prefer).
Table Display: A built-in table in the top-right corner lists each symbol’s real-time percentage change, plus the total weighted momentum.
Alerts:
Configure alerts for when the weighted momentum crosses above or below user-defined thresholds.
Helps you catch major shifts in sentiment across multiple symbols.
How To Use
Select Symbols & Weights: In the indicator’s settings, specify the tickers you want to monitor and their corresponding weights. Weights default to 1 (equal weighting).
Watch the Bars vs. Zero:
Bars above zero mean a positive weighted momentum (the basket is collectively moving up).
Bars below zero mean negative weighted momentum (the basket is collectively under pressure).
Check the Yellow Line: The EMA of momentum.
If the bars consistently stay above the line, short-term momentum is stronger than its recent average.
If the bars dip below the line, momentum is weakening relative to its average.
Review the Table: Quick snapshot of each symbol’s daily percentage change plus the total basket momentum, all color-coded red or green.
Caution & Tips
This indicator measures rate of change, not absolute price levels. A rising momentum can still be part of a larger downtrend.
Always combine momentum readings with other technical and/or fundamental signals for confirmation.
For better reliability, experiment with different smoothing lengths to suit your trading style (shorter for scalping, longer for swing or positional approaches).
Multi-Feature IndicatorThe Multi-Feature Indicator combines three popular technical analysis tools — RSI, Moving Averages (MA), and MACD — into a single indicator to provide unified buy and sell signals. This script is designed for traders who want to filter out noise and focus on signals confirmed by multiple criteria.
Features:
RSI (Relative Strength Index):
Measures momentum and identifies overbought (70) and oversold (30) conditions.
A signal is triggered when RSI crosses these thresholds.
Moving Averages (MA):
Uses a short-term moving average (default: 9 periods) and a long-term moving average (default: 21 periods).
Buy signals occur when the short-term MA crosses above the long-term MA, indicating an uptrend.
Sell signals occur when the short-term MA crosses below the long-term MA, indicating a downtrend.
MACD (Moving Average Convergence Divergence):
A trend-following momentum indicator that shows the relationship between two moving averages of an asset's price.
Signals are based on the crossover of the MACD line and its signal line.
Unified Buy and Sell Signals:
Buy Signal: Triggered when:
RSI crosses above 30 (leaving oversold territory).
Short-term MA crosses above the long-term MA.
MACD line crosses above the signal line.
Sell Signal: Triggered when:
RSI crosses below 70 (leaving overbought territory).
Short-term MA crosses below the long-term MA.
MACD line crosses below the signal line.
Visualization:
The indicator plots the short-term and long-term moving averages on the price chart.
Green "BUY" labels appear below price bars when all buy conditions are met.
Red "SELL" labels appear above price bars when all sell conditions are met.
Parameters:
RSI Length: Default is 14. This controls the sensitivity of the RSI.
Short MA Length: Default is 9. This determines the short-term trend.
Long MA Length: Default is 21. This determines the long-term trend.
Use Case:
The Multi-Feature Indicator is ideal for traders seeking higher confirmation before entering or exiting trades. By combining momentum (RSI), trend (MA), and momentum shifts (MACD), it reduces false signals and enhances decision-making.
How to Use:
Apply the indicator to your chart in TradingView.
Look for "BUY" or "SELL" signals, which appear when all conditions align.
Use this tool in conjunction with other analysis techniques for best results.
Note:
The default settings are suitable for many assets, but you may need to adjust them for different timeframes or market conditions.
This indicator is meant to assist in trading decisions and should not be used as the sole basis for trading.
Bidirectional Momentum Aggregator w/ Time Weighting Intrabar Data Extraction:
The script optionally harnesses lower time frame data (e.g., per-second intervals) for high and low prices within each primary bar. You can set it to the current chart time but if you want to use intrabar data it uses the request.security_lower_tf() to properly pull intrabar data.
This fine-grained data enables an in-depth examination of the price action that occurs within a standard timeframe, enhancing the ability to detect subtle market movements.
A key threshold based on Average True Range (ATR) is used to measure significant price changes intrabar, adding a robust filter for volatility sensitivity.
Cumulative Time-to-Threshold Analysis:
The indicator tracks how long it takes for price changes to reach specified thresholds, marking critical time points when upward or downward price movements exceed these levels. This approach provides insights into the speed and intensity of directional shifts within the market.
The calculated time-to-threshold values act as temporal markers that influence subsequent momentum weighting.
Bidirectional Momentum Calculation:
Momentum is assessed in two directions (upward and downward) using a comprehensive array of price changes.
Adaptive Weighting Mechanism:
Each momentum value is weighted by the calculated time-to-threshold, giving preference to momentum that occurs more rapidly and aligning with potential breakout conditions.
The script also factors in correlations between momentum and price change, ensuring that only the most relevant signals contribute to the final analysis.
Iterative Length Analysis:
By iterating over a range of lengths (e.g., 100 to 200 periods), the script aggregates data to assess momentum across different time scales. This provides a more holistic view of market behavior, accommodating both short-term fluctuations and longer-term trends.
Each length is evaluated using moving averages and correlations to determine its contribution to the total weighted momentum.
Final Aggregated Output:
The weighted sums of upward and downward momentum are normalized by the total weight to produce a final composite metric.
The indicator plots these results as separate upward and downward momentum lines, offering traders a visual representation of which direction holds more momentum strength over various intervals.
Practical Application:
This indicator's advanced design is tailored for traders who require a deeper understanding of price movement dynamics and the underlying forces driving market momentum. By incorporating intrabar data, adaptive time-to-threshold calculations, and iterative analysis, this tool seeks to provide a clearer view of potential market direction shifts and their timing.
The indicator can be used to:
Identify potential breakout or reversal points by observing significant shifts in weighted momentum.
Gauge the relative strength of uptrends and downtrends through the plotted momentum lines.
Enhance decision-making with an additional layer of granularity from intrabar data.
In essence, this script is an ambitious attempt to blend multi-scale analysis, momentum dynamics, and time-weighted evaluation, creating a unique approach to understanding market behavior beyond conventional indicators.
NASI +The NASI + indicator is an advanced adaptation of the classic McClellan Oscillator, a tool widely used to gauge market breadth. It calculates the McClellan Oscillator by measuring the difference between the 19-day and 39-day EMAs of net advancing issues, which are optionally adjusted to account for the relative strength of advancing vs. declining stocks.
To enhance this analysis, NASI + applies the Relative Strength Index (RSI) to the cumulative McClellan Oscillator values, generating a unique momentum-based view of market breadth. Additionally, two extra EMAs—a 10-day and a 4-day EMA—are applied to the RSI, providing further refinement to signals for overbought and oversold conditions.
With NASI +, users benefit from:
-A deeper analysis of market momentum through cumulative breadth data.
-Enhanced sensitivity to trend shifts with the applied RSI and dual EMAs.
-Clear visual cues for overbought and oversold conditions, aiding in intuitive signal identification.
Kurutoga Histogram with HTF and LTF
Kurutoga Histogram:
The Kurutoga Histogram is a technical analysis indicator designed to measure price divergence from the 50% level of a recent price range. By calculating how far the current price is from the midpoint of a selected base length of candles, the histogram provides insight into the momentum, strength, and potential reversals in the market. Additionally, it can be applied across multiple timeframes to provide a comprehensive view of both short- and long-term market dynamics.
Key Components:
Base Length:
The base length is the number of candles (bars) over which the high and low prices are observed. The default base length is typically 14 periods, but it can be adjusted according to the trader's preference.
This base length defines the range from which the 50% level, or midpoint, is calculated.
50% Level (Midpoint):
The midpoint is the average of the highest high and the lowest low over the selected base length. This 50% level acts as an equilibrium point around which the price fluctuates.
Formula:
Midpoint = (Highest High + Lowest Low) / 2
The price’s distance from this midpoint is an indicator of how strong the current trend or divergence is.
Price Divergence:
The main calculation of the histogram is the difference between the current closing price and the midpoint of the price range.
Formula:
Divergence = Close Price − Midpoint
A positive divergence (price above the midpoint) indicates bullish strength, while a negative divergence (price below the midpoint) indicates bearish strength.
Multi-Timeframe Analysis:
The Kurutoga Histogram can be applied to both the current timeframe and a higher timeframe (HTF), allowing traders to gauge price movement in both short-term and long-term contexts.
By comparing the histograms of multiple timeframes, traders can determine if there is alignment (confluence) between trends, which can strengthen trade signals or provide additional confirmation.
Color-Coded Histogram:
Blue Bars (Positive Divergence): Represent that the price is above the 50% level, indicating bullish momentum. Taller blue bars suggest stronger upward momentum, while shrinking bars suggest weakening strength.
Red Bars (Negative Divergence): Represent that the price is below the 50% level, indicating bearish momentum. Taller red bars suggest stronger downward momentum, while shrinking bars suggest a potential reversal or consolidation.
The histogram’s color intensity and transparency can be adjusted to enhance the visual effect, distinguishing between current timeframe (LTF) and higher timeframe (HTF) divergence.
Interpretation:
Bullish Signals: When the histogram bars are blue and growing, the price is gaining momentum above the midpoint of its recent range. This could signal an ongoing uptrend.
Bearish Signals: When the histogram bars are red and growing, the price is gaining momentum below the midpoint, signaling an ongoing downtrend.
Momentum Shifts: When the histogram bars shrink in size (whether blue or red), it could indicate that the current trend is losing strength and may reverse or enter consolidation.
Neutral or Sideways Movement: When the histogram bars hover around zero, it means the price is trading near the midpoint of its recent range, often signaling a lack of strong momentum in either direction.
Multi-Timeframe Confluence:
When the current timeframe (LTF) histogram aligns with the higher timeframe (HTF) histogram (e.g., both are showing strong bullish or bearish divergence), it may provide stronger confirmation of the trend's strength.
Divergence between timeframes (e.g., bullish on LTF but bearish on HTF) may suggest that price movements on lower timeframes are not yet reflected in the broader trend, signaling caution.
Applications:
Trend Identification: The Kurutoga Histogram is highly useful for detecting when the price is trending away from its equilibrium point, providing insight into the strength of ongoing trends.
Momentum Analysis: By measuring the divergence from the 50% level, the histogram helps traders identify when momentum is increasing or decreasing.
Reversal Detection: Shrinking histogram bars can signal weakening momentum, which often precedes trend reversals.
Consolidation and Breakouts: When the histogram remains near zero for an extended period, it suggests consolidation, which often precedes a breakout in either direction.
Advantages:
Clear Visuals: The use of a color-coded histogram makes it easy to visually assess whether the market is gaining bullish or bearish momentum.
Multi-Timeframe Utility: The ability to compare current timeframe signals with higher timeframe signals adds an extra layer of confirmation, reducing false signals.
Dynamic Adjustment: By adjusting the base length, traders can fine-tune the sensitivity of the indicator to match different markets or trading styles.
Limitations:
Lagging Indicator: Like most divergence indicators, the Kurutoga Histogram may lag slightly behind actual price movements, especially during fast, volatile markets.
Requires Confirmation: This indicator works best when used in conjunction with other technical tools like moving averages, support/resistance levels, or volume indicators, to avoid relying on divergence alone.
Conclusion:
The Kurutoga Histogram is a versatile and visually intuitive tool for measuring price divergence from a key equilibrium point, helping traders to assess the strength of trends and identify potential reversal points. Its use across multiple timeframes provides deeper insights, making it a valuable addition to any trading strategy that emphasizes momentum and trend following.
Burst PowerThe Burst Power indicator is to be used for Indian markets where most stocks have a maximum price band limit of 20%.
This indicator is intended to identify stocks with high potential for significant price movements. By analysing historical price action over a user-defined lookback period, it calculates a Burst Power score that reflects the stock's propensity for rapid and substantial moves. This can be helpful for stock selection in strategies involving momentum bursts, swing trading, or identifying stocks with explosive potential.
Key Components
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Significant Move Counts:
5% Moves: Counts the number of days within the lookback period where the stock had a positive close-to-close move between 5% and 10%.
10% Moves: Counts the number of days with a positive close-to-close move between 10% and 19%.
19% Moves: Counts the number of days with a positive close-to-close move of 19% or more.
Maximum Price Move (%):
Identifies the largest positive close-to-close percentage move within the lookback period, along with the date it occurred.
Burst Power Score:
A composite score calculated using the counts of significant moves: Burst Power =(Count5%/5) +(Count10%/2) + (Count19%/0.5)
The score is then rounded to the nearest whole number.
A higher Burst Power score indicates a higher frequency of significant price bursts.
Visual Indicators:
Table Display: Presents all the calculated data in a customisable table on the chart.
Markers on Chart: Plots markers on the chart where significant moves occurred, aiding visual analysis.
Using the Lookback Period
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The lookback period determines how much historical data the indicator analyses. Users can select from predefined options:
3 Months
6 Months
1 Year
3 Years
5 Years
A shorter lookback period focuses on recent price action, which may be more relevant for short-term trading strategies. A longer lookback period provides a broader historical context, useful for identifying long-term patterns and behaviors.
Interpreting the Burst Power Score
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High Burst Power Score (≥15):
Indicates the stock frequently experiences significant price moves.
Suitable for traders seeking quick momentum bursts and swing trading opportunities.
Stocks with high scores may be more volatile but offer potential for rapid gains.
Moderate Burst Power Score (10 to 14):
Suggests occasional significant price movements.
May suit traders looking for a balance between volatility and stability.
Low Burst Power Score (<10):
Reflects fewer significant price bursts.
Stocks are more likely to exhibit longer, sustainable, but slower price trends.
May be preferred by traders focusing on steady growth or longer-term investments.
Note: Trading involves uncertainties, and the Burst Power score should be considered as one of many factors in a comprehensive trading strategy. It is essential to incorporate broader market analysis and risk management practices.
Customisation Options
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The indicator offers several customisation settings to tailor the display and functionality to individual preferences:
Display Mode:
Full Mode: Shows the detailed table with all components, including significant move counts, maximum price move, and the Burst Power score.
Mini Mode: Displays only the Burst Power score and its corresponding indicator (green, orange, or red circle).
Show Latest Date Column:
Toggle the display of the "Latest Date" column in the table, which shows the most recent occurrence of each significant move category.
Theme (Dark Mode):
Switch between Dark Mode and Light Mode for better visual integration with your chart's color scheme.
Table Position and Size:
Position: Place the table at various locations on the chart (top, middle, bottom; left, center, right).
Size: Adjust the table's text size (tiny, small, normal, large, huge, auto) for optimal readability.
Header Size: Customise the font size of the table headers (Small, Medium, Large).
Color Settings:
Disable Colors in Table: Option to display the table without background colors, which can be useful for printing or if colors are distracting.
Bullish Closing Filter:
Another customisation here is to count a move only when the closing for the day is strong. For this, we have an additional filter to see if close is within the chosen % of the range of the day. Closing within the top 1/3, for instance, indicates a way more bullish day tha, say, closing within the bottom 25%.
Move Markers on chart:
The indicator also marks out days with significant moves. You can choose to hide or show the markers on the candles/bars.
Practical Applications
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Momentum Trading: High Burst Power scores can help identify stocks that are likely to experience rapid price movements, suitable for momentum traders.
Swing Trading: Traders looking for short- to medium-term opportunities may focus on stocks with moderate to high Burst Power scores.
Positional Trading: Lower Burst Power scores may indicate steadier stocks that are less prone to volatility, aligning with long-term investment strategies.
Risk Management: Understanding a stock's propensity for significant moves can aid in setting appropriate stop-loss and take-profit levels.
Disclaimer: Trading involves significant risk, and past performance is not indicative of future results. The Burst Power indicator is intended for educational purposes and should not be construed as financial advice. Always conduct thorough research and consult with a qualified financial professional before making investment decisions.
Price-Shift Oscillator (PSO)The PSOscillator calculates an oscillator value based on price movements over a specific period. Oscillators like this one are typically used to identify momentum shifts, and trend direction. Here's a breakdown of how the logic behind it works:
Key Concepts for Beginners:
Oscillators:
In this case, the PSOscillator helps indicate whether the market momentum is positive (price might rise) or negative (price might fall).
Input Parameters:
oscPeriod: This is the number of bars (or candles) used to calculate the oscillator. It affects how sensitive the oscillator is to price changes. A lower period makes it more sensitive to short-term movements, while a higher period smoothens it out.
smaPeriod: This is a simple moving average (SMA) applied to the oscillator for additional smoothing, further reducing noise.
Calculation Logic:
The JpOscillator uses recent price data to calculate its value. Specifically, it looks at the closing prices of the current and previous bars (candles). periods ago).
This calculation aims to identify how much recent price action is deviating from past price behavior.
Essentially, it tells us whether the current price is higher or lower relative to the past, and how the trend is evolving over recent periods.
Smoothing:
After calculating the oscillator values, we apply optional smoothing to make it less "jumpy." This is useful in reducing the noise caused by small, insignificant price movements.
The sma_from_array function averages out the recent oscillator values to make the signal smoother, depending on the oscPeriod.
Oscillator Levels:
Above Zero:
If the oscillator is above 0, it means the price is gaining momentum upwards (bullish signal), which is why we color the histogram green.
Below Zero: If the oscillator is below 0, it indicates downward momentum (bearish signal), which is why we color the histogram red.
You can think of the zero line as a "neutral zone." Crossing above it means momentum is shifting to the upside, and crossing below it means momentum is shifting to the downside.
Histogram Plotting:
The values of the oscillator are plotted as a histogram (bars). The color changes based on whether the oscillator is above or below zero (green for positive and red for negative momentum).
The moving average (SMA) of the oscillator is plotted as a line to help identify trends over time.
Using two different coloring methods for a histogram in a trading strategy can provide a trader with distinct, layered information about market conditions, trends, and momentum shifts. Each coloring method can highlight different aspects of the price action or the oscillator behavior. Here’s how a trader might use both methods to their advantage:
ETHUSDT Daily
1. Color Based on Oscillator Position Relative to Zero
This method colors the histogram green when the oscillator value is above zero and red when it's below zero. This coloring strategy is straightforward and helps a trader quickly identify whether the market's momentum is generally bullish or bearish.
Advantages:
Trend Confirmation: When the oscillator remains above zero and green, it can confirm a bullish trend, and vice versa for a bearish trend with red colors below zero.
Quick Visual Reference: Easy to see at a glance, helping in fast decision-making processes.
2. Color Based on the Change of the Oscillator
This method changes the color based on whether the oscillator is increasing or decreasing compared to its previous value. For instance, a darker shade of green might be used if the oscillator value is rising from one period to the next, indicating increasing bullish momentum, and a darker red if declining, indicating increasing bearish momentum.
Advantages:
Momentum Insight: This coloring method gives insights into the strength of the movement. An oscillator that is increasing (even below zero) might suggest a weakening of a bearish trend or the start of a bullish reversal.
Detecting Reversals: Seeing the oscillator rise from negative to less negative or drop from positive to less positive can alert traders to potential early reversals before they cross the zero line.
Strategic Use in Trading:
A trader can use these two methods together by applying a multi-layered approach to analyze the oscillator:
Overall Trend Assessment:
Above Zero (Green): Considered bullish; look for buy opportunities, especially if the color gets brighter (indicating strengthening).
Below Zero (Red): Considered bearish; look for sell opportunities, especially if the color gets darker (indicating strengthening).
Short-Term Momentum and Entries:
Brightening Green: Could indicate a good time to enter or add to long positions as bullish momentum increases.
Darkening Red: Could indicate a good time to enter or add to short positions as bearish momentum increases.
Lightening Color: If red starts to lighten (become less intense), it might suggest a bearish trend is losing steam, which could be an exit signal for shorts or an early warning for a potential long setup.
Risk Management:
Switch in Color Intensity: A sudden change in color intensity can be used as a trigger for tightening stops or taking partial profits, helping manage risk by responding to changes in market momentum.
Market Momentum @MaxMaseratiThe Market Momentum Indicator plots two essential lines on your chart: the Momentum Line and the Momentum Signal, enabling you to visualize price direction and detect potential shifts in that direction.
Momentum Line:
The Momentum Line is calculated by finding the highest and lowest prices over the last 14 periods and then determining the midpoint between them. This midpoint is what we call the Momentum Line.
Momentum Signal:
The Momentum Signal is simply the Momentum Line shifted upward by a small fixed amount called the tick_size, which is set to 0.25 in this script.
Why 0.25?: The 0.25 tick size is a standard increment in many markets. It creates a small but noticeable difference between the Momentum Line and the Momentum Signal, making it easier to spot changes in market momentum. It’s small enough to reflect minor shifts without distorting the indicator’s usefulness.
NB: The indicator was originally created to be use without smoothing, but I add it as an option for smoothing and moving average lovers.
Smoothing:
You have the option to smooth these lines using different types of moving averages, like SMA or EMA. Smoothing makes the lines less jagged and more gradual.
If you apply smoothing, the Momentum Line and Momentum Signal might cross each other depending on the market’s movement.
How to use it:
When both lines are below price, it might indicates a Bullish Momentum
When both lines are above the price, it could suggest a Bearish Momentum.
When the lines are within the price range, it indicates the market is in a consolidation phase, signaling the potential for a move in either direction.
snapshot
Users can view Momentum Line and Momentum Signal for two specific time frames of their choice. Additionally, they have the option to smooth the lines separately for each time frame. For example, if "TF1" is set to 15 minutes and the current chart time frame is 5 minutes, the table will display "TF1: 15" alongside "Current TF: 5." Another option, "TF2," could be set to 60 minutes. Both time frames will be plotted on the chart if selected.
This indicator can be use as a supporting tool alongside your chosen strategy. It’s not designed to be used on its own and should be part of a broader confluence approach.
KASPA Slope OscillatorKASPA Slope Oscillator for analyzing KASPA on the 1D (daily) chart.
The indicator is plotted in a separate pane below the price chart and uses a mathematical approach to calculate and visualize the momentum or "slope" of KASPA's price movements.
Input Parameters:
Slope Window (days):
Defines the period (66 days by default) over which the slope is calculated.
Normalization Window (days):
The window size (85 days) for normalizing the slope values between 0 and 100.
Smoothing Period:
The number of days (15 days) over which the slope values are smoothed to reduce noise.
Overbought and Oversold Levels:
Threshold levels set at 80 (overbought) and 20 (oversold), respectively.
Calculation of the Slope:
Logarithmic Price Calculation:
Converts the close price of KASPA into a logarithmic scale to account for exponential growth or decay.
Rolling Slope:
Computes the rate of change in logarithmic prices over the defined slope window.
Normalization:
The slope is normalized between 0 and 100, allowing easier identification of extreme values.
Smoothing and Visualization:
Smoothing the Slope:
A Simple Moving Average (SMA) is applied to the normalized slope for the specified smoothing period.
Plotting the Oscillator:
The smoothed slope is plotted on the oscillator chart. Horizontal lines indicate overbought (80), oversold (20), and the mid-level (50).
Background Color Indications:
Background colors (red or green) indicate when the slope crosses above the overbought or below the oversold levels, respectively, signaling potential buy or sell conditions.
Detection of Local Maxima and Minima:
The code identifies local peaks (maxima) above the overbought level and troughs (minima) below the oversold level.
Vertical background lines are highlighted in red or green at these points, signaling potential reversals.
Short Summary:
The oscillator line fluctuates between 0 and 100, representing the normalized momentum of the price.
Red background areas indicate periods when the oscillator is above the overbought level (80), suggesting a potential overbought condition or a sell signal.
Green background areas indicate periods when the oscillator is below the oversold level (20), suggesting a potential oversold condition or a buy signal.
The vertical lines on the background mark local maxima and minima where price reversals may occur.
(I also want to thank @ForgoWork for optimizing visuality and cleaning up the source code)
US Futures Momentum OverviewThe "US Futures Momentum Overview" indicator is designed to provide a comprehensive view of momentum across various U.S. futures markets. It calculates the Rate of Change (ROC) for multiple futures contracts and displays them as lines on a chart. Each futures market is plotted with a unique color for easy differentiation, allowing traders to quickly assess the momentum in different markets.
Features:
ROC Calculation: Measures the percentage change in price over a specified period, indicating the rate of change in momentum.
Futures Markets Covered: Includes major U.S. indices, commodities, and agricultural products.
How to Use:
Momentum Analysis: Observe the ROC lines for each futures market. A positive ROC indicates increasing momentum, while a negative ROC suggests decreasing momentum.
Trend Identification: Use the ROC values to identify strong trends in different markets. Markets with higher positive ROC values show stronger upward momentum.
Comparison: Compare momentum across various futures markets to identify which ones are showing stronger trends and might offer better trading opportunities.
