Market Zone Analyzer[BullByte]Understanding the Market Zone Analyzer
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1. Purpose of the Indicator
The Market Zone Analyzer is a Pine Script™ (version 6) indicator designed to streamline market analysis on TradingView. Rather than scanning multiple separate tools, it unifies four core dimensions—trend strength, momentum, price action, and market activity—into a single, consolidated view. By doing so, it helps traders:
• Save time by avoiding manual cross-referencing of disparate signals.
• Reduce decision-making errors that can arise from juggling multiple indicators.
• Gain a clear, reliable read on whether the market is in a bullish, bearish, or sideways phase, so they can more confidently decide to enter, exit, or hold a position.
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2. Why a Trader Should Use It
• Unified View: Combines all essential market dimensions into one easy-to-read score and dashboard, eliminating the need to piece together signals manually.
• Adaptability: Automatically adjusts its internal weighting for trend, momentum, and price action based on current volatility. Whether markets are choppy or calm, the indicator remains relevant.
• Ease of Interpretation: Outputs a simple “BULLISH,” “BEARISH,” or “SIDEWAYS” label, supplemented by an intuitive on-chart dashboard and an oscillator plot that visually highlights market direction.
• Reliability Features: Built-in smoothing of the net score and hysteresis logic (requiring consecutive confirmations before flips) minimize false signals during noisy or range-bound phases.
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3. Why These Specific Indicators?
This script relies on a curated set of well-established technical tools, each chosen for its particular strength in measuring one of the four core dimensions:
1. Trend Strength:
• ADX/DMI (Average Directional Index / Directional Movement Index): Measures how strong a trend is, and whether the +DI line is above the –DI line (bullish) or vice versa (bearish).
• Moving Average Slope (Fast MA vs. Slow MA): Compares a shorter-period SMA to a longer-period SMA; if the fast MA sits above the slow MA, it confirms an uptrend, and vice versa for a downtrend.
• Ichimoku Cloud Differential (Senkou A vs. Senkou B): Provides a forward-looking view of trend direction; Senkou A above Senkou B signals bullishness, and the opposite signals bearishness.
2. Momentum:
• Relative Strength Index (RSI): Identifies overbought (above its dynamically calculated upper bound) or oversold (below its lower bound) conditions; changes in RSI often precede price reversals.
• Stochastic %K: Highlights shifts in short-term momentum by comparing closing price to the recent high/low range; values above its upper band signal bullish momentum, below its lower band signal bearish momentum.
• MACD Histogram: Measures the difference between the MACD line and its signal line; a positive histogram indicates upward momentum, a negative histogram indicates downward momentum.
3. Price Action:
• Highest High / Lowest Low (HH/LL) Range: Over a defined lookback period, this captures breakout or breakdown levels. A closing price near the recent highs (with a positive MA slope) yields a bullish score, and near the lows (with a negative MA slope) yields a bearish score.
• Heikin-Ashi Doji Detection: Uses Heikin-Ashi candles to identify indecision or continuation patterns. A small Heikin-Ashi body (doji) relative to recent volatility is scored as neutral; a larger body in the direction of the MA slope is scored bullish or bearish.
• Candle Range Measurement: Compares each candle’s high-low range against its own dynamic band (average range ± standard deviation). Large candles aligning with the prevailing trend score bullish or bearish accordingly; unusually small candles can indicate exhaustion or consolidation.
4. Market Activity:
• Bollinger Bands Width (BBW): Measures the distance between BB upper and lower bands; wide bands indicate high volatility, narrow bands indicate low volatility.
• Average True Range (ATR): Quantifies average price movement (volatility). A sudden spike in ATR suggests a volatile environment, while a contraction suggests calm.
• Keltner Channels Width (KCW): Similar to BBW but uses ATR around an EMA. Provides a second layer of volatility context, confirming or contrasting BBW readings.
• Volume (with Moving Average): Compares current volume to its moving average ± standard deviation. High volume validates strong moves; low volume signals potential lack of conviction.
By combining these tools, the indicator captures trend direction, momentum strength, price-action nuances, and overall market energy, yielding a more balanced and comprehensive assessment than any single tool alone.
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4. What Makes This Indicator Stand Out
• Multi-Dimensional Analysis: Rather than relying on a lone oscillator or moving average crossover, it simultaneously evaluates trend, momentum, price action, and activity.
• Dynamic Weighting: The relative importance of trend, momentum, and price action adjusts automatically based on real-time volatility (Market Activity State). For example, in highly volatile conditions, trend and momentum signals carry more weight; in calm markets, price action signals are prioritized.
• Stability Mechanisms:
• Smoothing: The net score is passed through a short moving average, filtering out noise, especially on lower timeframes.
• Hysteresis: Both Market Activity State and the final bullish/bearish/sideways zone require two consecutive confirmations before flipping, reducing whipsaw.
• Visual Interpretation: A fully customizable on-chart dashboard displays each sub-indicator’s value, regime, score, and comment, all color-coded. The oscillator plot changes color to reflect the current market zone (green for bullish, red for bearish, gray for sideways) and shows horizontal threshold lines at +2, 0, and –2.
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5. Recommended Timeframes
• Short-Term (5 min, 15 min): Day traders and scalpers can benefit from rapid signals, but should enable smoothing (and possibly disable hysteresis) to reduce false whipsaws.
• Medium-Term (1 h, 4 h): Swing traders find a balance between responsiveness and reliability. Less smoothing is required here, and the default parameters (e.g., ADX length = 14, RSI length = 14) perform well.
• Long-Term (Daily, Weekly): Position traders tracking major trends can disable smoothing for immediate raw readings, since higher-timeframe noise is minimal. Adjust lookback lengths (e.g., increase adxLength, rsiLength) if desired for slower signals.
Tip: If you keep smoothing off, stick to timeframes of 1 h or higher to avoid excessive signal “chatter.”
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6. How Scoring Works
A. Individual Indicator Scores
Each sub-indicator is assigned one of three discrete scores:
• +1 if it indicates a bullish condition (e.g., RSI above its dynamically calculated upper bound).
• 0 if it is neutral (e.g., RSI between upper and lower bounds).
• –1 if it indicates a bearish condition (e.g., RSI below its dynamically calculated lower bound).
Examples of individual score assignments:
• ADX/DMI:
• +1 if ADX ≥ adxThreshold and +DI > –DI (strong bullish trend)
• –1 if ADX ≥ adxThreshold and –DI > +DI (strong bearish trend)
• 0 if ADX < adxThreshold (trend strength below threshold)
• RSI:
• +1 if RSI > RSI_upperBound
• –1 if RSI < RSI_lowerBound
• 0 otherwise
• ATR (as part of Market Activity):
• +1 if ATR > (ATR_MA + stdev(ATR))
• –1 if ATR < (ATR_MA – stdev(ATR))
• 0 otherwise
Each of the four main categories shares this same +1/0/–1 logic across their sub-components.
B. Category Scores
Once each sub-indicator reports +1, 0, or –1, these are summed within their categories as follows:
• Trend Score = (ADX score) + (MA slope score) + (Ichimoku differential score)
• Momentum Score = (RSI score) + (Stochastic %K score) + (MACD histogram score)
• Price Action Score = (Highest-High/Lowest-Low score) + (Heikin-Ashi doji score) + (Candle range score)
• Market Activity Raw Score = (BBW score) + (ATR score) + (KC width score) + (Volume score)
Each category’s summed value can range between –3 and +3 (for Trend, Momentum, and Price Action), and between –4 and +4 for Market Activity raw.
C. Market Activity State and Dynamic Weight Adjustments
Rather than contributing directly to the netScore like the other three categories, Market Activity determines how much weight to assign to Trend, Momentum, and Price Action:
1. Compute Market Activity Raw Score by summing BBW, ATR, KCW, and Volume individual scores (each +1/0/–1).
2. Bucket into High, Medium, or Low Activity:
• High if raw Score ≥ 2 (volatile market).
• Low if raw Score ≤ –2 (calm market).
• Medium otherwise.
3. Apply Hysteresis (if enabled): The state only flips after two consecutive bars register the same high/low/medium label.
4. Set Category Weights:
• High Activity: Trend = 50 %, Momentum = 35 %, Price Action = 15 %.
• Low Activity: Trend = 25 %, Momentum = 20 %, Price Action = 55 %.
• Medium Activity: Use the trader’s base weight inputs (e.g., Trend = 40 %, Momentum = 30 %, Price Action = 30 % by default).
D. Calculating the Net Score
5. Normalize Base Weights (so that the sum of Trend + Momentum + Price Action always equals 100 %).
6. Determine Current Weights based on the Market Activity State (High/Medium/Low).
7. Compute Each Category’s Contribution: Multiply (categoryScore) × (currentWeight).
8. Sum Contributions to get the raw netScore (a floating-point value that can exceed ±3 when scores are strong).
9. Smooth the netScore over two bars (if smoothing is enabled) to reduce noise.
10. Apply Hysteresis to the Final Zone:
• If the smoothed netScore ≥ +2, the bar is classified as “Bullish.”
• If the smoothed netScore ≤ –2, the bar is classified as “Bearish.”
• Otherwise, it is “Sideways.”
• To prevent rapid flips, the script requires two consecutive bars in the new zone before officially changing the displayed zone (if hysteresis is on).
E. Thresholds for Zone Classification
• BULLISH: netScore ≥ +2
• BEARISH: netScore ≤ –2
• SIDEWAYS: –2 < netScore < +2
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7. Role of Volatility (Market Activity State) in Scoring
Volatility acts as a dynamic switch that shifts which category carries the most influence:
1. High Activity (Volatile):
• Detected when at least two sub-scores out of BBW, ATR, KCW, and Volume equal +1.
• The script sets Trend weight = 50 % and Momentum weight = 35 %. Price Action weight is minimized at 15 %.
• Rationale: In volatile markets, strong trending moves and momentum surges dominate, so those signals are more reliable than nuanced candle patterns.
2. Low Activity (Calm):
• Detected when at least two sub-scores out of BBW, ATR, KCW, and Volume equal –1.
• The script sets Price Action weight = 55 %, Trend = 25 %, and Momentum = 20 %.
• Rationale: In quiet, sideways markets, subtle price-action signals (breakouts, doji patterns, small-range candles) are often the best early indicators of a new move.
3. Medium Activity (Balanced):
• Raw Score between –1 and +1 from the four volatility metrics.
• Uses whatever base weights the trader has specified (e.g., Trend = 40 %, Momentum = 30 %, Price Action = 30 %).
Because volatility can fluctuate rapidly, the script employs hysteresis on Market Activity State: a new High or Low state must occur on two consecutive bars before weights actually shift. This avoids constant back-and-forth weight changes and provides more stability.
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8. Scoring Example (Hypothetical Scenario)
• Symbol: Bitcoin on a 1-hour chart.
• Market Activity: Raw volatility sub-scores show BBW (+1), ATR (+1), KCW (0), Volume (+1) → Total raw Score = +3 → High Activity.
• Weights Selected: Trend = 50 %, Momentum = 35 %, Price Action = 15 %.
• Trend Signals:
• ADX strong and +DI > –DI → +1
• Fast MA above Slow MA → +1
• Ichimoku Senkou A > Senkou B → +1
→ Trend Score = +3
• Momentum Signals:
• RSI above upper bound → +1
• MACD histogram positive → +1
• Stochastic %K within neutral zone → 0
→ Momentum Score = +2
• Price Action Signals:
• Highest High/Lowest Low check yields 0 (close not near extremes)
• Heikin-Ashi doji reading is neutral → 0
• Candle range slightly above upper bound but trend is strong, so → +1
→ Price Action Score = +1
• Compute Net Score (before smoothing):
• Trend contribution = 3 × 0.50 = 1.50
• Momentum contribution = 2 × 0.35 = 0.70
• Price Action contribution = 1 × 0.15 = 0.15
• Raw netScore = 1.50 + 0.70 + 0.15 = 2.35
• Since 2.35 ≥ +2 and hysteresis is met, the final zone is “Bullish.”
Although the netScore lands at 2.35 (Bullish), smoothing might bring it slightly below 2.00 on the first bar (e.g., 1.90), in which case the script would wait for a second consecutive reading above +2 before officially classifying the zone as Bullish (if hysteresis is enabled).
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9. Correlation Between Categories
The four categories—Trend Strength, Momentum, Price Action, and Market Activity—often reinforce or offset one another. The script takes advantage of these natural correlations:
• Bullish Alignment: If ADX is strong and pointed upward, fast MA is above slow MA, and Ichimoku is positive, that usually coincides with RSI climbing above its upper bound and the MACD histogram turning positive. In such cases, both Trend and Momentum categories generate +1 or +2. Because the Market Activity State is likely High (given the accompanying volatility), Trend and Momentum weights are at their peak, so the netScore quickly crosses into Bullish territory.
• Sideways/Consolidation: During a low-volatility, sideways phase, ADX may fall below its threshold, MAs may flatten, and RSI might hover in the neutral band. However, subtle price-action signals (like a small breakout candle or a Heikin-Ashi candle with a slight bias) can still produce a +1 in the Price Action category. If Market Activity is Low, Price Action’s weight (55 %) can carry enough influence—even if Trend and Momentum are neutral—to push the netScore out of “Sideways” into a mild bullish or bearish bias.
• Opposing Signals: When Trend is bullish but Momentum turns negative (for example, price continues up but RSI rolls over), the two scores can partially cancel. Market Activity may remain Medium, in which case the netScore lingers near zero (Sideways). The trader can then wait for either a clearer momentum shift or a fresh price-action breakout before committing.
By dynamically recognizing these correlations and adjusting weights, the indicator ensures that:
• When Trend and Momentum align (and volatility supports it), the netScore leaps strongly into Bullish or Bearish.
• When Trend is neutral but Price Action shows an early move in a low-volatility environment, Price Action’s extra weight in the Low Activity State can still produce actionable signals.
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10. Market Activity State & Its Role (Detailed)
The Market Activity State is not a direct category score—it is an overarching context setter for how heavily to trust Trend, Momentum, or Price Action. Here’s how it is derived and applied:
1. Calculate Four Volatility Sub-Scores:
• BBW: Compare the current band width to its own moving average ± standard deviation. If BBW > (BBW_MA + stdev), assign +1 (high volatility); if BBW < (BBW_MA × 0.5), assign –1 (low volatility); else 0.
• ATR: Compare ATR to its moving average ± standard deviation. A spike above the upper threshold is +1; a contraction below the lower threshold is –1; otherwise 0.
• KCW: Same logic as ATR but around the KCW mean.
• Volume: Compare current volume to its volume MA ± standard deviation. Above the upper threshold is +1; below the lower threshold is –1; else 0.
2. Sum Sub-Scores → Raw Market Activity Score: Range between –4 and +4.
3. Assign Market Activity State:
• High Activity: Raw Score ≥ +2 (at least two volatility metrics are strongly spiking).
• Low Activity: Raw Score ≤ –2 (at least two metrics signal unusually low volatility or thin volume).
• Medium Activity: Raw Score is between –1 and +1 inclusive.
4. Hysteresis for Stability:
• If hysteresis is enabled, a new state only takes hold after two consecutive bars confirm the same High, Medium, or Low label.
• This prevents the Market Activity State from bouncing around when volatility is on the fence.
5. Set Category Weights Based on Activity State:
• High Activity: Trend = 50 %, Momentum = 35 %, Price Action = 15 %.
• Low Activity: Trend = 25 %, Momentum = 20 %, Price Action = 55 %.
• Medium Activity: Use trader’s base weights (e.g., Trend = 40 %, Momentum = 30 %, Price Action = 30 %).
6. Impact on netScore: Because category scores (–3 to +3) multiply by these weights, High Activity amplifies the effect of strong Trend and Momentum scores; Low Activity amplifies the effect of Price Action.
7. Market Context Tooltip: The dashboard includes a tooltip summarizing the current state—e.g., “High activity, trend and momentum prioritized,” “Low activity, price action prioritized,” or “Balanced market, all categories considered.”
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11. Category Weights: Base vs. Dynamic
Traders begin by specifying base weights for Trend Strength, Momentum, and Price Action that sum to 100 %. These apply only when volatility is in the Medium band. Once volatility shifts:
• High Volatility Overrides:
• Trend jumps from its base (e.g., 40 %) to 50 %.
• Momentum jumps from its base (e.g., 30 %) to 35 %.
• Price Action is reduced to 15 %.
Example: If base weights were Trend = 40 %, Momentum = 30 %, Price Action = 30 %, then in High Activity they become 50/35/15. A Trend score of +3 now contributes 3 × 0.50 = +1.50 to netScore; a Momentum +2 contributes 2 × 0.35 = +0.70. In total, Trend + Momentum can easily push netScore above the +2 threshold on its own.
• Low Volatility Overrides:
• Price Action leaps from its base (30 %) to 55 %.
• Trend falls to 25 %, Momentum falls to 20 %.
Why? When markets are quiet, subtle candle breakouts, doji patterns, and small-range expansions tend to foreshadow the next swing more effectively than raw trend readings. A Price Action score of +3 in this state contributes 3 × 0.55 = +1.65, which can carry the netScore toward +2—even if Trend and Momentum are neutral or only mildly positive.
Because these weight shifts happen only after two consecutive bars confirm a High or Low state (if hysteresis is on), the indicator avoids constantly flipping its emphasis during borderline volatility phases.
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12. Dominant Category Explained
Within the dashboard, a label such as “Trend Dominant,” “Momentum Dominant,” or “Price Action Dominant” appears when one category’s absolute weighted contribution to netScore is the largest. Concretely:
• Compute each category’s weighted contribution = (raw category score) × (current weight).
• Compare the absolute values of those three contributions.
• The category with the highest absolute value is flagged as Dominant for that bar.
Why It Matters:
• Momentum Dominant: Indicates that the combined force of RSI, Stochastic, and MACD (after weighting) is pushing netScore farther than either Trend or Price Action. In practice, it means that short-term sentiment and speed of change are the primary drivers right now, so traders should watch for continued momentum signals before committing to a trade.
• Trend Dominant: Means ADX, MA slope, and Ichimoku (once weighted) outweigh the other categories. This suggests a strong directional move is in place; trend-following entries or confirming pullbacks are likely to succeed.
• Price Action Dominant: Occurs when breakout/breakdown patterns, Heikin-Ashi candle readings, and range expansions (after weighting) are the most influential. This often happens in calmer markets, where subtle shifts in candle structure can foreshadow bigger moves.
By explicitly calling out which category is carrying the most weight at any moment, the dashboard gives traders immediate insight into why the netScore is tilting toward bullish, bearish, or sideways.
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13. Oscillator Plot: How to Read It
The “Net Score” oscillator sits below the dashboard and visually displays the smoothed netScore as a line graph. Key features:
1. Value Range: In normal conditions it oscillates roughly between –3 and +3, but extreme confluences can push it outside that range.
2. Horizontal Threshold Lines:
• +2 Line (Bullish threshold)
• 0 Line (Neutral midline)
• –2 Line (Bearish threshold)
3. Zone Coloring:
• Green Background (Bullish Zone): When netScore ≥ +2.
• Red Background (Bearish Zone): When netScore ≤ –2.
• Gray Background (Sideways Zone): When –2 < netScore < +2.
4. Dynamic Line Color:
• The plotted netScore line itself is colored green in a Bullish Zone, red in a Bearish Zone, or gray in a Sideways Zone, creating an immediate visual cue.
Interpretation Tips:
• Crossing Above +2: Signals a strong enough combined trend/momentum/price-action reading to classify as Bullish. Many traders wait for a clear crossing plus a confirmation candle before entering a long position.
• Crossing Below –2: Indicates a strong Bearish signal. Traders may consider short or exit strategies.
• Rising Slope, Even Below +2: If netScore climbs steadily from neutral toward +2, it demonstrates building bullish momentum.
• Divergence: If price makes a higher high but the oscillator fails to reach a new high, it can warn of weakening momentum and a potential reversal.
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14. Comments and Their Necessity
Every sub-indicator (ADX, MA slope, Ichimoku, RSI, Stochastic, MACD, HH/LL, Heikin-Ashi, Candle Range, BBW, ATR, KCW, Volume) generates a short comment that appears in the detailed dashboard. Examples:
• “Strong bullish trend” or “Strong bearish trend” for ADX/DMI
• “Fast MA above slow MA” or “Fast MA below slow MA” for MA slope
• “RSI above dynamic threshold” or “RSI below dynamic threshold” for RSI
• “MACD histogram positive” or “MACD histogram negative” for MACD Hist
• “Price near highs” or “Price near lows” for HH/LL checks
• “Bullish Heikin Ashi” or “Bearish Heikin Ashi” for HA Doji scoring
• “Large range, trend confirmed” or “Small range, trend contradicted” for Candle Range
Additionally, the top-row comment for each category is:
• Trend: “Highly Bullish,” “Highly Bearish,” or “Neutral Trend.”
• Momentum: “Strong Momentum,” “Weak Momentum,” or “Neutral Momentum.”
• Price Action: “Bullish Action,” “Bearish Action,” or “Neutral Action.”
• Market Activity: “Volatile Market,” “Calm Market,” or “Stable Market.”
Reasons for These Comments:
• Transparency: Shows exactly how each sub-indicator contributed to its category score.
• Education: Helps traders learn why a category is labeled bullish, bearish, or neutral, building intuition over time.
• Customization: If, for example, the RSI comment says “RSI neutral” despite an impending trend shift, a trader might choose to adjust RSI length or thresholds.
In the detailed dashboard, hovering over each comment cell also reveals a tooltip with additional context (e.g., “Fast MA above slow MA” or “Senkou A above Senkou B”), helping traders understand the precise rule behind that +1, 0, or –1 assignment.
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15. Real-Life Example (Consolidated)
• Instrument & Timeframe: Bitcoin (BTCUSD), 1-hour chart.
• Current Market Activity: BBW and ATR both spike (+1 each), KCW is moderately high (+1), but volume is only neutral (0) → Raw Market Activity Score = +2 → State = High Activity (after two bars, if hysteresis is on).
• Category Weights Applied: Trend = 50 %, Momentum = 35 %, Price Action = 15 %.
• Trend Sub-Scores:
1. ADX = 25 (above threshold 20) with +DI > –DI → +1.
2. Fast MA (20-period) sits above Slow MA (50-period) → +1.
3. Ichimoku: Senkou A > Senkou B → +1.
→ Trend Score = +3.
• Momentum Sub-Scores:
4. RSI = 75 (above its moving average +1 stdev) → +1.
5. MACD histogram = +0.15 → +1.
6. Stochastic %K = 50 (mid-range) → 0.
→ Momentum Score = +2.
• Price Action Sub-Scores:
7. Price is not within 1 % of the 20-period high/low and slope = positive → 0.
8. Heikin-Ashi body is slightly larger than stdev over last 5 bars with haClose > haOpen → +1.
9. Candle range is just above its dynamic upper bound but trend is already captured, so → +1.
→ Price Action Score = +2.
• Calculate netScore (before smoothing):
• Trend contribution = 3 × 0.50 = 1.50
• Momentum contribution = 2 × 0.35 = 0.70
• Price Action contribution = 2 × 0.15 = 0.30
• Raw netScore = 1.50 + 0.70 + 0.30 = 2.50 → Immediately classified as Bullish.
• Oscillator & Dashboard Output:
• The oscillator line crosses above +2 and turns green.
• Dashboard displays:
• Trend Regime “BULLISH,” Trend Score = 3, Comment = “Highly Bullish.”
• Momentum Regime “BULLISH,” Momentum Score = 2, Comment = “Strong Momentum.”
• Price Action Regime “BULLISH,” Price Action Score = 2, Comment = “Bullish Action.”
• Market Activity State “High,” Comment = “Volatile Market.”
• Weights: Trend 50 %, Momentum 35 %, Price Action 15 %.
• Dominant Category: Trend (because 1.50 > 0.70 > 0.30).
• Overall Score: 2.50, posCount = (three +1s in Trend) + (two +1s in Momentum) + (two +1s in Price Action) = 7 bullish signals, negCount = 0.
• Final Zone = “BULLISH.”
• The trader sees that both Trend and Momentum are reinforcing each other under high volatility. They might wait one more candle for confirmation but already have strong evidence to consider a long.
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Disclaimer
This indicator is strictly a technical analysis tool and does not constitute financial advice. All trading involves risk, including potential loss of capital. Past performance is not indicative of future results. Traders should:
• Always backtest the “Market Zone Analyzer ” on their chosen symbols and timeframes before committing real capital.
• Combine this tool with sound risk management, position sizing, and, if possible, fundamental analysis.
• Understand that no indicator is foolproof; always be prepared for unexpected market moves.
Goodluck
-BullByte!
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True Range eXpansion🕯️ TRX — True Range eXpansion
Clean Candle Bodies · Volatility Bands · Adaptive Range Envelope System
Not your grandfather’s candles. Not your brokerage’s bands.
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TRX begins with a simple concept: visualize the true range of every candle, without the noise of flickering wicks.
From there, it grows into a fully adaptive price visualization framework.
What started as a candle-only visualizer evolved into a modular, user-controlled price engine.
From wickless candle clarity to dynamic volatility envelopes, TRX adapts to you.
There are plenty of band and channel indicators out there — Bollinger, Keltner, Donchian, Envelope, the whole crew.
But none of them are built on the true candle range, adaptive ATR shaping, and full user control like TRX.
This isn’t just another indicator — it’s a new framework.
Most bands and channels are based on close price and statistical deviation — useful, but limited.
TRX uses the full true range of each candle as its foundation, then applies customizable smoothing and directional ATR scaling to form a dynamic, volatility-reactive envelope.
The result? Bands that breathe with the market — not lag behind it.
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🔧 Core Features:
🕯️ True Range Candles — Each candle is plotted from low to high, body-only, colored by open/close.
📈 Adjustable High/Low Moving Averages — Select your smoothing style: SMA, EMA, WMA, RMA, or HMA.
🌬️ ATR-Based Expansion — Bands dynamically breathe based on market volatility.
🔀 Per-Band Multipliers — Fine-tune expansion individually for the upper and lower bands.
⚖️ Basis Line — Optional centerline between bands for structure tracking and equilibrium zones.
🎛️ Full Visual Control — Width, transparency, color, on/off toggles for each element.
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🧠 Default Use Case:
With the included default settings, TRX behaves like an evolved Bollinger Band system — based on True Range candle structure, not just close price and standard deviation.
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🔄 How to Zero Out the Bands (for Minimalist Use):
Want just candles? A clean MA? Single band? You got it.
➤ Use TRX like a clean moving average:
• Set ATR Multiplier to 0
• Set both Band ATR Adjustments to 0
• Leave the Basis Line ON or OFF — your call
➤ Show only candles (no bands at all):
• Turn off "Show High/Low MAs"
• Turn off Basis Line
➤ Single-line ceiling or floor tracking:
• Set one band’s Transparency to 100
• Use the remaining band as a price envelope or support/resistance guide
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🧬 Notes:
TRX can be made:
• Spiky or silky (via smoothing & ATR)
• Wide or tight (via multipliers)
• Subtle or aggressive (via color/transparency)
• Clean as a compass or dirty as a chaos meter
Built by accident. Tuned with intention.
Released to the world as one of the most adaptable and expressive visual overlays ever made.
Created by Sherlock_MacGyver
Adaptive Momentum Flow (AMF)Overview
The Adaptive Momentum Flow (AMF) indicator is a powerful, multi-faceted tool designed to provide a comprehensive and adaptive view of market momentum and trend strength. Unlike traditional oscillators with fixed settings, AMF dynamically adjusts its calculations based on market volatility , ensuring its signals remain relevant across varying market conditions. By combining advanced Double Exponential Moving Averages (DEMA) with a powerful volume analysis component and a customizable scoring system, AMF offers a unique perspective on price action and underlying buying/selling pressure.
Key Features & How It Works
1. Adaptive DEMA Trend Strength:
At its core, AMF utilizes three DEMA lines (Fast, Medium, Slow) to assess the current trend's alignment and strength.
The indicator dynamically adjusts the lengths of these DEMA lines based on real-time market volatility, measured by Average True Range (ATR). This means AMF becomes more responsive in volatile markets and smoother in calmer periods.
A "Volatility Sensitivity" input allows you to fine-tune how aggressively the indicator adapts to these changes.
2. Volume Analysis (Buying/Selling Pressure):
AMF incorporates a dedicated volume analysis module to gauge whether volume is predominantly supporting upward or downward price movements. This helps identify periods of significant buying or selling pressure.
This volume analysis component is smoothed with an adjustable Moving Average (SMA, EMA, WMA, or DEMA) and contributes to the overall momentum score, adding a crucial layer of volume-driven confirmation to the analysis.
3. Comprehensive Scoring System:
The indicator generates a normalized "Oscillator Score" that ranges from -100 to 100. This score is a weighted sum of:
Price's relationship to the Fast DEMA.
The Fast DEMA's relationship to the Medium DEMA.
The Medium DEMA's relationship to the Slow DEMA.
The smoothed value from the volume analysis.
Each component's influence on the final score can be individually adjusted via input weights, allowing for deep customization.
Signal Line & Crossovers:
A smoothed "Signal Line" provides additional confirmation for momentum shifts. Crossovers between the main AMF line and its Signal Line can indicate potential changes in market direction.
Overbought/Oversold Levels:
Adjustable Overbought (default 70) and Oversold (default -70) levels visually highlight extreme momentum conditions.
These zones are enhanced with a color fill effect (bright red for overbought, bright cyan for oversold), making it easy to spot when the market is entering potentially exhausted states.
Crucially, these extreme zones can often be further validated by combining them with volatility bands (like Bollinger Bands or Keltner Channels as shown in the chart above) or other confluence indicators, offering stronger signals for potential reversals or exhaustion.
Benefits for Traders
Reduced Lag: DEMA's inherent design helps minimize lag compared to traditional moving averages, providing more timely signals.
Adaptive Intelligence: Automatically adjusts to market volatility, ensuring the indicator's sensitivity is appropriate for current conditions.
Holistic Momentum View: Combines price-based trend alignment with volume-based pressure for a more robust assessment of market flow.
Clear Visual Cues: Intuitive plots, signal line, and vibrant overbought/oversold zone fills make interpretation straightforward.
Customizable: Extensive input options allow traders to tailor the indicator to their specific trading style, asset, and timeframe.
How to Use
Trend Confirmation: Look for the AMF line and its Signal Line to align with the price trend.
Momentum Shifts: Crossovers between the AMF line and its Signal Line can indicate shifts in momentum.
Extreme Conditions: Pay attention when the AMF line enters the neon-highlighted overbought or oversold zones, signaling potential reversals or pauses in the current momentum. Always consider confirming these signals with other analysis tools, such as price action, chart patterns, support/resistance levels, or volatility indicators.
Customization: Experiment with the "Volatility Sensitivity," DEMA multipliers, and scoring weights to find the optimal settings for your trading strategy.
Ehlers Ultimate Bands (UBANDS)UBANDS: ULTIMATE BANDS
🔍 OVERVIEW AND PURPOSE
Ultimate Bands, developed by John F. Ehlers, are a volatility-based channel indicator designed to provide a responsive and smooth representation of price boundaries with significantly reduced lag compared to traditional Bollinger Bands. Bollinger Bands typically use a Simple Moving Average for the centerline and standard deviations from it to establish the bands, both of which can increase lag. Ultimate Bands address this by employing Ehlers' Ultrasmooth Filter for the central moving average. The bands are then plotted based on the volatility of price around this ultrasmooth centerline.
The primary purpose of Ultimate Bands is to offer traders a clearer view of potential support and resistance levels that react quickly to price changes while filtering out excessive noise, aiming for nearly zero lag in the indicator band.
🧩 CORE CONCEPTS
Ultrasmooth Centerline: Employs the Ehlers Ultrasmooth Filter as the basis (centerline) for the bands, aiming for minimal lag and enhanced smoothing.
Volatility-Adaptive Width: The distance between the upper and lower bands is determined by a measure of price deviation from the ultrasmooth centerline. This causes the bands to widen during volatile periods and contract during calm periods.
Dynamic Support/Resistance: The bands serve as dynamic levels of potential support (lower band) and resistance (upper band).
🧮 CALCULATION AND MATHEMATICAL FOUNDATION
Ehlers' Original Concept for Deviation:
John Ehlers describes the deviation calculation as: "The deviation at each data sample is the difference between Smooth and the Close at that data point. The Standard Deviation (SD) is computed as the square root of the average of the squares of the individual deviations."
This describes calculating the Root Mean Square (RMS) of the residuals:
Smooth = UltrasmoothFilter(Source, Length)
Residuals = Source - Smooth
SumOfSquaredResiduals = Sum(Residuals ^2) for i over Length
MeanOfSquaredResiduals = SumOfSquaredResiduals / Length
SD_Ehlers = SquareRoot(MeanOfSquaredResiduals) (This is the RMS of residuals)
Pine Script Implementation's Deviation:
The provided Pine Script implementation calculates the statistical standard deviation of the residuals:
Smooth = UltrasmoothFilter(Source, Length) (referred to as _ehusf in the script)
Residuals = Source - Smooth
Mean_Residuals = Average(Residuals, Length)
Variance_Residuals = Average((Residuals - Mean_Residuals)^2, Length)
SD_Pine = SquareRoot(Variance_Residuals) (This is the statistical standard deviation of residuals)
Band Calculation (Common to both approaches, using their respective SD):
UpperBand = Smooth + (NumSDs × SD)
LowerBand = Smooth - (NumSDs × SD)
🔍 Technical Note: The Pine Script implementation uses a statistical standard deviation of the residuals (differences between price and the smooth average). Ehlers' original text implies an RMS of these residuals. While both measure dispersion, they will yield slightly different values. The Ultrasmooth Filter itself is a key component, designed for responsiveness.
📈 INTERPRETATION DETAILS
Reduced Lag: The primary advantage is the significant reduction in lag compared to standard Bollinger Bands, allowing for quicker reaction to price changes.
Volatility Indication: Widening bands indicate increasing market volatility, while narrowing bands suggest decreasing volatility.
Overbought/Oversold Conditions (Use with caution):
• Price touching or exceeding the Upper Band may suggest overbought conditions.
• Price touching or falling below the Lower Band may suggest oversold conditions.
Trend Identification:
• Price consistently "walking the band" (moving along the upper or lower band) can indicate a strong trend.
• The Middle Band (Ultrasmooth Filter) acts as a dynamic support/resistance level and indicates the short-term trend direction.
Comparison to Ultimate Channel: Ehlers notes that the Ultimate Band indicator does not differ from the Ultimate Channel indicator in any major fashion.
🛠️ USE AND APPLICATION
Ultimate Bands can be used similarly to how Keltner Channels or Bollinger Bands are used for interpreting price action, with the main difference being the reduced lag.
Example Trading Strategy (from John F. Ehlers):
Hold a position in the direction of the Ultimate Smoother (the centerline).
Exit that position when the price "pops" outside the channel or band in the opposite direction of the trade.
This is described as a trend-following strategy with an automatic following stop.
⚠️ LIMITATIONS AND CONSIDERATIONS
Lag (Minimized but Present): While significantly reduced, some minimal lag inherent to averaging processes will still exist. Increasing the Length parameter for smoother bands will moderately increase this lag.
Parameter Sensitivity: The Length and StdDev Multiplier settings are key to tuning the indicator for different assets and timeframes.
False Signals: As with any band indicator, false signals can occur, particularly in choppy or non-trending markets.
Not a Standalone System: Best used in conjunction with other forms of analysis for confirmation.
Deviation Calculation Nuance: Be aware of the difference in deviation calculation (statistical standard deviation vs. RMS of residuals) if comparing directly to Ehlers' original concept as described.
📚 REFERENCES
Ehlers, J. F. (2024). Article/Publication where "Code Listing 2" for Ultimate Bands is featured. (Specific source to be identified if known, e.g., "Stocks & Commodities Magazine, Vol. XX, No. YY").
Ehlers, J. F. (General). Various publications on advanced filtering and cycle analysis. (e.g., "Rocket Science for Traders", "Cycle Analytics for Traders").
The VoVix Experiment The VoVix Experiment
The VoVix Experiment is a next-generation, regime-aware, volatility-adaptive trading strategy for futures, indices, and more. It combines a proprietary VoVix (volatility-of-volatility) anomaly detector with price structure clustering and critical point logic, only trading when multiple independent signals align. The system is designed for robustness, transparency, and real-world execution.
Logic:
VoVix Regime Engine: Detects pre-move volatility anomalies using a fast/slow ATR ratio, normalized by Z-score. Only trades when a true regime spike is detected, not just random volatility.
Cluster & Critical Point Filters: Price structure and volatility clustering must confirm the VoVix signal, reducing false positives and whipsaws.
Adaptive Sizing: Position size scales up for “super-spikes” and down for normal events, always within user-defined min/max.
Session Control: Trades only during user-defined hours and days, avoiding illiquid or high-risk periods.
Visuals: Aurora Flux Bands (From another Original of Mine (Options Flux Flow): glow and change color on signals, with a live dashboard, regime heatmap, and VoVix progression bar for instant insight.
Backtest Settings
Initial capital: $10,000
Commission: Conservative, realistic roundtrip cost:
15–20 per contract (including slippage per side) I set this to $25
Slippage: 3 ticks per trade
Symbol: CME_MINI:NQ1!
Timeframe: 15 min (but works on all timeframes)
Order size: Adaptive, 1–2 contracts
Session: 5:00–15:00 America/Chicago (default, fully adjustable)
Why these settings?
These settings are intentionally strict and realistic, reflecting the true costs and risks of live trading. The 10,000 account size is accessible for most retail traders. 25/contract including 3 ticks of slippage are on the high side for MNQ, ensuring the strategy is not curve-fit to perfect fills. If it works here, it will work in real conditions.
Forward Testing: (This is no guarantee. I've provided these results to show that executions perform as intended. Test were done on Tradovate)
ALL TRADES
Gross P/L: $12,907.50
# of Trades: 64
# of Contracts: 186
Avg. Trade Time: 1h 55min 52sec
Longest Trade Time: 55h 46min 53sec
% Profitable Trades: 59.38%
Expectancy: $201.68
Trade Fees & Comm.: $(330.95)
Total P/L: $12,576.55
Winning Trades: 59.38%
Breakeven Trades: 3.12%
Losing Trades: 37.50%
Link: www.dropbox.com
Inputs & Tooltips
VoVix Regime Execution: Enable/disable the core VoVix anomaly detector.
Volatility Clustering: Require price/volatility clusters to confirm VoVix signals.
Critical Point Detector: Require price to be at a statistically significant distance from the mean (regime break).
VoVix Fast ATR Length: Short ATR for fast volatility detection (lower = more sensitive).
VoVix Slow ATR Length: Long ATR for baseline regime (higher = more stable).
VoVix Z-Score Window: Lookback for Z-score normalization (higher = smoother, lower = more reactive).
VoVix Entry Z-Score: Minimum Z-score for a VoVix spike to trigger a trade.
VoVix Exit Z-Score: Z-score below which the regime is considered decayed (exit).
VoVix Local Max Window: Bars to check for local maximum in VoVix (higher = stricter).
VoVix Super-Spike Z-Score: Z-score for “super” regime events (scales up position size).
Min/Max Contracts: Adaptive position sizing range.
Session Start/End Hour: Only trade between these hours (exchange time).
Allow Weekend Trading: Enable/disable trading on weekends.
Session Timezone: Timezone for session filter (e.g., America/Chicago for CME).
Show Trade Labels: Show/hide entry/exit labels on chart.
Flux Glow Opacity: Opacity of Aurora Flux Bands (0–100).
Flux Band EMA Length: EMA period for band center.
Flux Band ATR Multiplier: Width of bands (higher = wider).
Compliance & Transparency
* No hidden logic, no repainting, no pyramiding.
* All signals, sizing, and exits are fully explained and visible.
* Backtest settings are stricter than most real accounts.
* All visuals are directly tied to the strategy logic.
* This is not a mashup or cosmetic overlay; every component is original and justified.
Disclaimer
Trading is risky. This script is for educational and research purposes only. Do not trade with money you cannot afford to lose. Past performance is not indicative of future results. Always test in simulation before live trading.
Proprietary Logic & Originality Statement
This script, “The VoVix Experiment,” is the result of original research and development. All core logic, algorithms, and visualizations—including the VoVix regime detection engine, adaptive execution, volatility/divergence bands, and dashboard—are proprietary and unique to this project.
1. VoVix Regime Logic
The concept of “volatility of volatility” (VoVix) is an original quant idea, not a standard indicator. The implementation here (fast/slow ATR ratio, Z-score normalization, local max logic, super-spike scaling) is custom and not found in public TradingView scripts.
2. Cluster & Critical Point Logic
Volatility clustering and “critical point” detection (using price distance from a rolling mean and standard deviation) are general quant concepts, but the way they are combined and filtered here is unique to this script. The specific logic for “clustered chop” and “critical point” is not a copy of any public indicator.
3. Adaptive Sizing
The adaptive sizing logic (scaling contracts based on regime strength) is custom and not a standard TradingView feature or public script.
4. Time Block/Session Control
The session filter is a common feature in many strategies, but the implementation here (with timezone and weekend control) is written from scratch.
5. Aurora Flux Bands (From another Original of Mine (Options Flux Flow)
The “glowing” bands are inspired by the idea of volatility bands (like Bollinger Bands or Keltner Channels), but the visual effect, color logic, and integration with regime signals are original to this script.
6. Dashboard, Watermark, and Metrics
The dashboard, real-time Sharpe/Sortino, and VoVix progression bar are all custom code, not copied from any public script.
What is “standard” or “common quant practice”?
Using ATR, EMA, and Z-score are standard quant tools, but the way they are combined, filtered, and visualized here is unique. The structure and logic of this script are original and not a mashup of public code.
This script is 100% original work. All logic, visuals, and execution are custom-coded for this project. No code or logic is directly copied from any public or private script.
Use with discipline. Trade your edge.
— Dskyz, for DAFE Trading Systems
Disparity Index with Volatility ZonesDisparity Index with Volatility Zones
is a momentum oscillator that measures the percentage difference between the current price and its simple moving average (SMA). This allows traders to identify overbought/oversold conditions, assess momentum strength, and detect potential trend reversals or continuations.
🔍 Core Concept:
The Disparity Index (DI) is calculated as:
DI = 100 × (Price − SMA) / SMA
A positive DI indicates the price is trading above its moving average (potential bullish sentiment), while a negative DI suggests the price is below the average (potential bearish sentiment).
This version of the Disparity Index introduces a dual-zone volatility framework, offering deeper insight into the market's current state.
🧠 What Makes This Version Unique?
1. High Volatility Zones
When DI crosses above +1.0% or below –1.0%, it often indicates the start or continuation of a strong trend.
Sustained readings beyond these thresholds typically align with trending phases, offering opportunities for momentum-based entries.
A reversal back within ±1.0% after exceeding these levels can suggest a shift in momentum — similar to how RSI exits the overbought/oversold zones before reversals.
These thresholds act as dynamic markers for breakout confirmation and potential trend exhaustion.
2. Low Volatility Zones
DI values between –0.5% and +0.5% define the low-volatility zone, shaded for visual clarity.
This area typically indicates market indecision, sideways price action, or consolidation.
Trading within this range may favor range-bound or mean-reversion strategies, as trend momentum is likely limited.
The logic is similar to interpreting a flat ADX, tight Bollinger Bands, or contracting Keltner Channels — all suggesting consolidation.
⚙️ Features:
Customizable moving average length and input source
Adjustable thresholds for overbought/oversold and low-volatility zones
Optional visual fill between low-volatility bounds
Clean and minimal chart footprint (non-essential plots hidden by default)
📈 How to Use:
1. Trend Confirmation:
A break above +1.0% can be used as a bullish continuation signal.
A break below –1.0% may confirm bearish strength.
Long periods above/below these thresholds support trend-following entries.
2. Reversal Detection:
If DI returns below +1.0% after exceeding it, bullish momentum may be fading.
If DI rises above –1.0% after falling below, bearish pressure may be weakening.
These shifts resemble overbought/oversold transitions in oscillators like RSI or Stochastic, and can be paired with divergence, volume, or price structure analysis for higher reliability.
3. Sideways Market Detection:
DI values within ±0.5% indicate low volatility or a non-trending environment.
Traders may avoid breakout entries during these periods or apply range-trading tactics instead.
Observing transitions out of the low-volatility zone can help anticipate breakouts.
4. Combine with Other Indicators:
DI signals can be enhanced using tools like MACD, Volume Oscillators, or Moving Averages.
For example, a DI breakout beyond ±1.0% supported by a MACD crossover or volume spike can help validate trend initiation.
This indicator is especially powerful when paired with Bollinger Bands:
A simultaneous price breakout from the Bollinger Band and DI moving beyond ±1.0% can help identify early trend inflection points.
This combination supports entering positions early in a developing trend, improving the efficiency of trend-following strategies and enhancing decision-making precision.
It also helps filter false breakouts when DI fails to confirm the move outside the band.
This indicator is designed for educational and analytical purposes and works across all timeframes and asset classes.
It is particularly useful for traders seeking a clear framework to identify momentum strength, filter sideways markets, and improve entry timing within a larger trading system.
Q Squeeze TrendQ Squeeze Trend
A sharp, signal-based trend tool that combines classic SuperTrend mechanics with configurable squeeze breakout logic and momentum confirmation. Built for clean entry points and minimalist charting — perfect for fast setups and real-time alerts.
🔧 Core Features
Configurable Squeeze Breakout Logic
• Detects low-volatility "squeeze" phases using customizable Bollinger Band vs. Keltner Channel logic
• Confirms breakouts only when momentum aligns with directional bias
SuperTrend Confirmation
• Filters noise and validates signals based on ATR-based trend logic
• Adds directional confidence before triggering signals
Alternating Signal Logic
• Ensures only one directional signal is active at a time
• Avoids repetitive entries and improves clarity
Clean Visual Feedback
• Directional arrows on confirmed buy/sell signals
• Optional colored fill between price and signal level
• Lightweight, non-intrusive label system
Real-Time Alerts
• Alerts for confirmed buy and sell setups
• Easy integration with webhooks, bots, or mobile notifications
⚙️ Configurable Inputs
• ATR Period & Multiplier – adjust SuperTrend sensitivity
• Squeeze Length, BB/KC Multipliers – fine-tune compression detection
• Signal Colors – customize arrow and background styling
✨ Highlights
• Designed for fast, visual trading with minimal clutter
• Non-repainting logic, effective across all timeframes
• Pairs well with structure, momentum, and volume strategies
📈 How to Use
• Enter on breakout arrows when trend, momentum, and squeeze align
• Use background fill to track current direction
• Exit on opposite signal, or combine with your own trade management logic
Institutional Quantum Momentum Impulse [BullByte]## Overview
The Institutional Quantum Momentum Impulse (IQMI) is a sophisticated momentum oscillator designed to detect institutional-level trend strength, volatility conditions, and market regime shifts. It combines multiple advanced technical concepts, including:
- Quantum Momentum Engine (Hilbert Transform + MACD Divergence + Stochastic Energy)
- Fractal Volatility Scoring (GARCH + Keltner-based volatility)
- Dynamic Adaptive Bands (Self-adjusting thresholds based on efficiency)
- Market Phase Detection (Volume + Momentum alignment)
- Liquidity & Cumulative Delta Analysis
The indicator provides a Z-score normalized momentum reading, making it ideal for mean-reversion and trend-following strategies.
---
## Key Features
### 1. Quantum Momentum Core
- Combines Hilbert Transform, MACD divergence, and Stochastic Energy into a single composite momentum score.
- Normalized using a Z-score for statistical significance.
- Smoothed with EMA/WMA/HMA for cleaner signals.
### 2. Dynamic Adaptive Bands
- Upper/Lower bands adjust based on volatility and efficiency ratio .
- Acts as overbought/oversold zones when momentum reaches extremes.
### 3. Market Phase Detection
- Identifies bullish , bearish , or neutral phases using:
- Volume-Weighted MA alignment
- Fractal momentum extremes
### 4. Volatility & Liquidity Filters
- Fractal Volatility Score (0-100 scale) shows market instability.
- Liquidity Check ensures trades are taken in favorable spread conditions.
### 5. Dashboard & Visuals
- Real-time dashboard with key metrics:
- Momentum strength, volatility, efficiency, cumulative delta, and market regime.
- Gradient coloring for intuitive momentum visualization .
---
## Best Trade Setups
### 1. Trend-Following Entries
- Signal :
- QM crosses above zero + Market Phase = Bullish + ADX > 25
- Cumulative Delta rising (buying pressure)
- Confirmation :
- Efficiency > 0.5 (strong momentum quality)
- Liquidity = High (tight spreads)
### 2. Mean-Reversion Entries
- Signal :
- QM touches upper band + Volatility expanding
- Market Regime = Ranging (ADX < 25)
- Confirmation :
- Efficiency < 0.3 (weak momentum follow-through)
- Cumulative Delta divergence (price high but delta declining)
### 3. Breakout Confirmation
- Signal :
- QM holds above zero after a pullback
- Market Phase shifts to Bullish/Bearish
- Confirmation :
- Volatility rising (expansion phase)
- Liquidity remains high
---
## Recommended Timeframes
- Intraday (5M - 1H): Works well for scalping & swing trades.
- Swing Trading (4H - Daily): Best for trend-following setups.
- Position Trading (Weekly+): Useful for macro trend confirmation.
---
## Input Customization
- Resonance Factor (1.0 - 3.618 ): Adjusts MACD divergence sensitivity.
- Entropy Filter (0.382/0.50/0.618) : Controls stochastic damping.
- Smoothing Type (EMA/WMA/HMA) : Changes momentum responsiveness.
- Normalization Period : Adjusts Z-score lookback.
---
The IQMI is a professional-grade momentum indicator that combines institutional-level concepts into a single, easy-to-read oscillator. It works across all markets (stocks, forex, crypto) and is ideal for traders who want:
✅ Early trend detection
✅ Volatility-adjusted signals
✅ Institutional liquidity insights
✅ Clear dashboard for quick analysis
Try it on TradingView and enhance your trading edge! 🚀
Happy Trading!
- BullByte
BB Breakout + Momentum Squeeze [Strategy]This Strategy is Based on 3 free indicators
- Bollinger Bands Breakout Oscillator: Link
- TTM Squeeze Pro: Link
- Rolling ATR Bands: Link
Bollinger Bands Breakout Oscillator - This tool shows how strong a market trend is by measuring how often prices move outside their normal Bollinger bands range. It helps you see whether prices are strongly moving in one direction or just moving sideways. By looking at how much and how frequently prices push beyond their typical boundaries, you can identify which direction the market is heading over your selected time period.
TM Squeeze Pro - This is a custom version of the TTM Squeeze indicator.
It's designed to help traders spot consolidation phases in the market (when price is coiling or "squeezing") and to catch breakouts early when volatility returns. The logic is based on the relationship between Bollinger Bands and Keltner Channels, combined with a momentum oscillator to show direction and strength.
Rolling ATR Bands - This indicator combines volatility bands (ATR) with momentum and trend signals to show where the market might be breaking out, retesting, or trending. It's highly visual and helpful for traders looking to time entries/exits during trending or volatile moves.
Logic Of the Strategy:
We are going to use the Bollinger Bands Breakout to determine the direction of the market. Than check the Volatility of the price by looking at the TTM Squeeze indicator. And use the ATR Bands to determine dynamic Stop Losses and based on the calculate the Take Profit targets and quantity for each position dynamically.
For the Long Setup:
1. We need to see the that Bull Power (Green line of the Bollinger Bands Breakout Oscilator) is crossing the level of 50.
2. Check the presence of volatility (Green dot based on the TTM Squeeze indicator)
For the Short Setup:
1. We need to see the that Bear Power (Red line of the Bollinger Bands Breakout Oscilator) is crossing the level of 50.
2. Check the presence of volatility (Green dot based on the TTM Squeeze indicator)
Stop Loss is determined by the Lower ATR Band (for the Long entry) and Upper ATR Band (For the Short entry)
Take Profit is 1:1.5 risk reward ration, which means if the Stop loss is 1% the TP target will be 1.5%
Move stop Loss to Breakeven: If the price will go in the direction of the trade for at least half of the Risk Reward target then the stop will automatically be adjusted to the entry price. For Example: the Stop Loss is 1%, the price has move at least 0.5% in the direction of your trade and that will move the Stop Loss level to the Entry point.
You can Adjust the parameters for each indicator used in that script and also adjust the Risk and Money management block to see how the PnL will change.
Elastic Volume-Weighted Student-T TensionOverview
The Elastic Volume-Weighted Student-T Tension Bands indicator dynamically adapts to market conditions using an advanced statistical model based on the Student-T distribution. Unlike traditional Bollinger Bands or Keltner Channels, this indicator leverages elastic volume-weighted averaging to compute real-time dispersion and location parameters, making it highly responsive to volatility changes while maintaining robustness against price fluctuations.
This methodology is inspired by incremental calculation techniques for weighted mean and variance, as outlined in the paper by Tony Finch:
📄 "Incremental Calculation of Weighted Mean and Variance" .
Key Features
✅ Adaptive Volatility Estimation – Uses an exponentially weighted Student-T model to dynamically adjust band width.
✅ Volume-Weighted Mean & Dispersion – Incorporates real-time volume weighting, ensuring a more accurate representation of market sentiment.
✅ High-Timeframe Volume Normalization – Provides an option to smooth volume impact by referencing a higher timeframe’s cumulative volume, reducing noise from high-variability bars.
✅ Customizable Tension Parameters – Configurable standard deviation multipliers (σ) allow for fine-tuned volatility sensitivity.
✅ %B-Like Oscillator for Relative Price Positioning – The main indicator is in form of a dedicated oscillator pane that normalizes price position within the sigma ranges, helping identify overbought/oversold conditions and potential momentum shifts.
✅ Robust Statistical Foundation – Utilizes kurtosis-based degree-of-freedom estimation, enhancing responsiveness across different market conditions.
How It Works
Volume-Weighted Elastic Mean (eμ) – Computes a dynamic mean price using an elastic weighted moving average approach, influenced by trade volume, if not volume detected in series, study takes true range as replacement.
Dispersion (eσ) via Student-T Distribution – Instead of assuming a fixed normal distribution, the bands adapt to heavy-tailed distributions using kurtosis-driven degrees of freedom.
Incremental Calculation of Variance – The indicator applies Tony Finch’s incremental method for computing weighted variance instead of arithmetic sum's of fixed bar window or arrays, improving efficiency and numerical stability.
Tension Calculation – There are 2 dispersion custom "zones" that are computed based on the weighted mean and dynamically adjusted standard student-t deviation.
%B-Like Oscillator Calculation – The oscillator normalizes the price within the band structure, with values between 0 and 1:
* 0.00 → Price is at the lower band (-2σ).
* 0.50 → Price is at the volume-weighted mean (eμ).
* 1.00 → Price is at the upper band (+2σ).
* Readings above 1.00 or below 0.00 suggest extreme movements or possible breakouts.
Recommended Usage
For scalping in lower timeframes, it is recommended to use the fixed α Decay Factor, it is in raw format for better control, but you can easily make a like of transformation to N-bar size window like in EMA-1 bar dividing 2 / decayFactor or like an RMA dividing 1 / decayFactor.
The HTF selector catch quite well Higher Time Frame analysis, for example using a Daily chart and using as HTF the 200-day timeframe, weekly or monthly.
Suitable for trend confirmation, breakout detection, and mean reversion plays.
The %B-like oscillator helps gauge momentum strength and detect divergences in price action if user prefer a clean chart without bands, this thanks to pineScript v6 force overlay feature.
Ideal for markets with volume-driven momentum shifts (e.g., futures, forex, crypto).
Customization Parameters
Fixed α Decay Factor – Controls the rate of volume weighting influence for an approximation EWMA approach instead of using sum of series or arrays, making the code lightweight & computing fast O(1).
HTF Volume Smoothing – Instead of a fixed denominator for computing α , a volume sum of the last 2 higher timeframe closed candles are used as denominator for our α weight factor. This is useful to review mayor trends like in daily, weekly, monthly.
Tension Multipliers (±σ) – Adjusts sensitivity to dispersion sigma parameter (volatility).
Oscillator Zone Fills – Visual cues for price positioning within the cloud range.
Posible Interpretations
As market within indicators relay on each individual edge, this are just some key ideas to glimpse how the indicator could be interpreted by the user:
📌 Price inside bands – Market is considered somehow "stable"; price is like resting from tension or "charging batteries" for volume spike moves.
📌 Price breaking outer bands – Potential breakout or extreme movement; watch for reversals or continuation from strong moves. Market is already in tension or generating it.
📌 Narrowing Bands – Decreasing volatility; expect contraction before expansion.
📌 Widening Bands – Increased volatility; prepare for high probability pull-back moves, specially to the center location of the bands (the mean) or the other side of them.
📌 Oscillator is just the interpretation of the price normalized across the Student-T distribution fitting "curve" using the location parameter, our Elastic Volume weighted mean (eμ) fixed at 0.5 value.
Final Thoughts
The Elastic Volume-Weighted Student-T Tension indicator provides a powerful, volume-sensitive alternative to traditional volatility bands. By integrating real-time volume analysis with an adaptive statistical model, incremental variance computation, in a relative price oscillator that can be overlayed in the chart as bands, it offers traders an edge in identifying momentum shifts, trend strength, and breakout potential. Think of the distribution as a relative "tension" rubber band in which price never leave so far alone.
DISCLAIMER:
The Following indicator/code IS NOT intended to be a formal investment advice or recommendation by the author, nor should be construed as such. Users will be fully responsible by their use regarding their own trading vehicles/assets.
The following indicator was made for NON LUCRATIVE ACTIVITIES and must remain as is, following TradingView's regulations. Use of indicator and their code are published for work and knowledge sharing. All access granted over it, their use, copy or re-use should mention authorship(s) and origin(s).
WARNING NOTICE!
THE INCLUDED FUNCTION MUST BE CONSIDERED FOR TESTING. The models included in the indicator have been taken from open sources on the web and some of them has been modified by the author, problems could occur at diverse data sceneries, compiler version, or any other externality.
VWAP + KCVolume Weighted Average Price (VWAP) is a technical analysis tool used to measure the average price weighted by volume. VWAP is typically used with intraday charts as a way to determine the general direction of intraday prices. It's similar to a moving average in that when price is above VWAP, prices are rising and when price is below VWAP, prices are falling. VWAP is primarily used by technical analysts to identify market trend.
The Keltner Channels (KC) indicator is a banded indicator similar to Bollinger Bands and Moving Average Envelopes. They consist of an Upper Envelope above a Middle Line as well as a Lower Envelope below the Middle Line. The Middle Line is a moving average of price over a user-defined time period. Either a simple moving average or an exponential moving average are typically used. The Upper and Lower Envelopes are set a (user-defined multiple) of a range away from the Middle Line. This can be a multiple of the daily high/low range, or more commonly a multiple of the Average True Range.
Range PolarityDescription:
This indicator is a "Rate of Change" style oscillator designed to measure market dynamics through the lens of price ranges. By utilizing the true range in conjunction with high and low separation, this script produces two distinct oscillators: one for positive price shifts and one for negative price shifts.
Key Features:
High/Low Isolation:
The script calculates the relative movement of upwards and downwards price movements over a user-defined period. This separation provides a nuanced view of market behavior, offering two separate signals for comparison.
Dynamic Transform Smoothing:
A smoothing transform is applied to the signals, ensuring better outlier handling while maintaining sensitivity to price extremes. This makes the oscillator especially suited for identifying overbought and oversold conditions.
Zero-Centered:
The zero line acts as a "gravity point," where shifts away or toward zero indicate market momentum. Signal crosses or reversals from extreme zones can signal potential entry or exit points.
Outlier Identification:
Unlike traditional ATR based strategies (e.g., Keltner Channels ), this indicator isolates high and low ranges, creating a more granular view of market extremes. These measurements can help identify shifts from the outlying positions and reversal opportunities.
Visual Enhancements:
Multiple layers enhance the visual distinction of the positive and negative transformations. Horizontal lines at key thresholds provide visual reference for overbought, oversold, and equilibrium zones.
How to Use:
Primary signals are shifts from outlying positions or a positive/negative cross. An extreme reading itself can reveal an incoming reversal when calibrated with other indicators or compared with higher timeframes. Pairing "Range Polarity" with volume and momentum can create a comprehensive strategy.
In conclusion, be aware the base length controls the window for high/low contributions while the transform smoothing enhances the raw data through normalization within a tempered range to filter out insignificant fluctuations.
Merry Christmas to all and have a Happy New Year!
Bull Bear Candles with Volume ProfileUser Guide for Bull Bear Candles Indicator with Keltner Channels
Author: NellyN
Introduction
This indicator helps identify potential bullish and bearish trends in the market by analyzing buying and selling volume over two configurable timeframes. It calculates the percentage of buying and selling volume and displays the current market condition based on two moving averages for 2 periods.
Key Features
• Volume Analysis : Calculates Buy and Sell Volume for two configurable timeframes (e.g., 5 min, 15 min, 15 min. and 1 hour, etc.) and displays them as percentages.
• Moving Averages : Uses one Moving Average (MA) for two different time periods to identify trends (uptrend when shorter-term MA is above longer-term MA). You can also choose other Moving Average types like SMA, EMA, WMA, RMA, VWMA, or HMA.
• Colored Candles : Candles are colored green for bullish conditions, red for bearish conditions, and gray for neutral conditions.
• Market Condition Labels : Displays labels in table-view indicating the current market condition based on Buy and Sell Volume (Very Bullish, Very Bearish, Bullish/Bearish Retracement, Chop).
• Alerts: Generates alerts for potential buy and sell signals based on indicator conditions (Note: Enable alerts in the indicator settings).
• Visual Signals: Provides visual signals through colored candles and market condition labels in addition to alerts.
Input Parameters
• Source: Close price (default) or Heikin Ashi
• Timeframe: Select the timeframe for price and volume data used in the indicator (e.g., Daily, Hourly).
• Colored Candles On: Enable (True) or disable (False) coloring candles based on market conditions.
• Enable Alerts: Enable (True) or disable (False) alerts for buy/sell signals.
• Length of MA: Sets the length for the MAs used in trend identification (minimum 1).
• Lookback Period Vol. 1 & 2: Define the timeframes used to calculate buying and selling volume and the MA calculation (e.g., 5 min, 15 min).
Understanding the Outputs
• Cloud Fill: The area between two MAs is filled with a color that reflects the trend (green for uptrend, red for downtrend).
• Table: Shows Buy Volume, Sell Volume, Buy Percentage, Sell Percentage, and the current Market Condition Labels. (If you decide to see them uncomment them from the code simply removing the // in front of the code)
• Colored Candles and Market Condition Labels: Look for green candles and bullish labels for potential buying opportunities, and vice versa for red candles and bearish labels.
Bullish green label appears when short-term MA is above long-term MA AND Buy Volume percentage is greater than 50%.
Red cross for exiting long entry appears when we have bearish volume OR bearish crossover of the MA for the 2 periods.
Bearish red label appears when short-term MA is below long-term MA AND Buy Volume percentage is less than 50%.
Green cross for exiting short entry appears when we have bullish volume OR bullish crossover of the MA for the 2 periods.
• Bullish/Bearish Retracement: The moving averages indicate a potential trend reversal, while the Buy Volume percentage suggests a continuation of the prior trend. The candle color may be green, red, or gray depending on the current price position relative to the moving averages.
• Chop (Gray Candle): The moving averages are flat and the Buy Volume percentage is not significantly above or below 50%.
• Buy/Sell Alerts: The indicator generates alerts based on specific conditions, but these should be used in conjunction with other trading strategies and careful risk management.
Important Notes
• This indicator is for informational purposes only and should not be considered financial advice. Back-test the indicator with historical data to understand its performance before using it for live trading.
• Combine this indicator with other technical analysis tools.
Honest Volatility Grid [Honestcowboy]The Honest Volatility Grid is an attempt at creating a robust grid trading strategy but without standard levels.
Normal grid systems use price levels like 1.01;1.02;1.03;1.04... and place an order at each of these levels. In this program instead we create a grid using keltner channels using a long term moving average.
🟦 IS THIS EVEN USEFUL?
The idea is to have a more fluid style of trading where levels expand and follow price and do not stick to precreated levels. This however also makes each closed trade different instead of using fixed take profit levels. In this strategy a take profit level can even be a loss. It is useful as a strategy because it works in a different way than most strategies, making it a good tool to diversify a portfolio of trading strategies.
🟦 STRATEGY
There are 10 levels below the moving average and 10 above the moving average. For each side of the moving average the strategy uses 1 to 3 orders maximum (3 shorts at top, 3 longs at bottom). For instance you buy at level 2 below moving average and you increase position size when level 6 is reached (a cheaper price) in order to spread risks.
By default the strategy exits all trades when the moving average is reached, this makes it a mean reversion strategy. It is specifically designed for the forex market as these in my experience exhibit a lot of ranging behaviour on all the timeframes below daily.
There is also a stop loss at the outer band by default, in case price moves too far from the mean.
What are the risks?
In case price decides to stay below the moving average and never reaches the outer band one trade can create a very substantial loss, as the bands will keep following price and are not at a fixed level.
Explanation of default parameters
By default the strategy uses a starting capital of 25000$, this is realistic for retail traders.
Lot sizes at each level are set to minimum lot size 0.01, there is no reason for the default to be risky, if you want to risk more or increase equity curve increase the number at your own risk.
Slippage set to 20 points: that's a normal 2 pip slippage you will find on brokers.
Fill limit assumtion 20 points: so it takes 2 pips to confirm a fill, normal forex spread.
Commission is set to 0.00005 per contract: this means that for each contract traded there is a 5$ or whatever base currency pair has as commission. The number is set to 0.00005 because pinescript does not know that 1 contract is 100000 units. So we divide the number by 100000 to get a realistic commission.
The script will also multiply lot size by 100000 because pinescript does not know that lots are 100000 units in forex.
Extra safety limit
Normally the script uses strategy.exit() to exit trades at TP or SL. But because these are created 1 bar after a limit or stop order is filled in pinescript. There are strategy.orders set at the outer boundaries of the script to hedge against that risk. These get deleted bar after the first order is filled. Purely to counteract news bars or huge spikes in price messing up backtest.
🟦 VISUAL GOODIES
I've added a market profile feature to the edge of the grid. This so you can see in which grid zone market has been the most over X bars in the past. Some traders may wish to only turn on the strategy whenever the market profile displays specific characteristics (ranging market for instance).
These simply count how many times a high, low, or close price has been in each zone for X bars in the past. it's these purple boxes at the right side of the chart.
🟦 Script can be fully automated to MT5
There are risk settings in lot sizes or % for alerts and symbol settings provided at the bottom of the indicator. The script will send alert to MT5 broker trying to mimic the execution that happens on tradingview. There are always delays when using a bridge to MT5 broker and there could be errors so be mindful of that. This script sends alerts in format so they can be read by tradingview.to which is a bridge between the platforms.
Use the all alert function calls feature when setting up alerts and make sure you provide the right webhook if you want to use this approach.
Almost every setting in this indicator has a tooltip added to it. So if any setting is not clear hover over the (?) icon on the right of the setting.
MTF Squeeze Analyzer - [tradeviZion]MTF Squeeze Analyzer
Multi-Timeframe Squeeze Pro Analyzer Tool
Overview:
The MTF Squeeze Analyzer is a comprehensive tool designed to help traders monitor the TTM Squeeze indicator across multiple timeframes in a streamlined and efficient manner. Built with Pine Script™ version 5, this indicator enhances your market analysis by providing detailed insights into squeeze conditions and momentum shifts, enabling you to make more informed trading decisions.
Key Features:
1. Multi-Timeframe Monitoring:
Comprehensive Coverage: Track squeeze conditions across multiple timeframes, including 1-minute, 5-minute, 15-minute, 30-minute, 1-hour, 2-hour, 4-hour, and daily charts.
Squeeze Counts: Keep count of the number of consecutive bars the price has been within each squeeze level (low, mid, high), helping you assess the strength and duration of consolidation periods.
2. Dynamic Table Display:
Customizable Appearance: Adjust table position, text size, and colors to suit your preferences.
Color-Coded Indicators: Easily identify squeeze levels and momentum shifts with intuitive color schemes.
Message Integration: Features rotating messages to keep you engaged and informed.
3. Alerts for Key Market Events:
Squeeze Start and Fire Alerts: Receive notifications when a squeeze starts or fires on your selected timeframes.
Custom Squeeze Count Alerts: Set thresholds for squeeze counts and get alerted when these levels are reached, allowing you to anticipate potential breakouts.
Fully Customizable: Choose which alerts you want to receive and tailor them to your trading strategy.
4. Momentum Analysis:
Momentum Oscillator: Visualize momentum using a histogram that changes color based on momentum shifts.
Detailed Insights: Determine whether momentum is increasing or decreasing to make more strategic trading decisions.
How It Works:
The indicator is based on the TTM Squeeze concept, which identifies periods of low volatility where the market is "squeezing" before a potential breakout. It analyzes the relationship between Bollinger Bands and Keltner Channels to determine squeeze conditions and uses linear regression to calculate momentum.
1. Squeeze Levels:
No Squeeze (Green): Market is not in a squeeze.
Low Compression Squeeze (Gray): Mild consolidation, potential for a breakout.
Mid Compression Squeeze (Red): Moderate consolidation, higher breakout potential.
High Compression Squeeze (Orange): Strong consolidation, significant breakout potential.
2. Squeeze Counts:
Tracks the number of consecutive bars in each squeeze condition.
Helps identify how long the market has been consolidating, providing clues about potential breakout timing.
3. Momentum Histogram:
Upward Momentum: Shown in aqua or blue, indicating increasing or decreasing upward momentum.
Downward Momentum: Displayed in red or yellow, representing increasing or decreasing downward momentum.
Using Alerts:
Stay ahead of market movements with customizable alerts:
1. Enable Alerts in Settings:
Squeeze Start Alert: Get notified when a new squeeze begins.
Squeeze Fire Alert: Be alerted when a squeeze ends, signaling a potential breakout.
Squeeze Count Alert: Set a specific number of bars for a squeeze condition, and receive an alert when this count is reached.
2. Set Up Alerts on Your Chart:
Click on the indicator name and select " Add Alert on MTF Squeeze Analyzer ".
Choose your desired alert conditions and customize the notification settings.
Click " Create " to activate the alerts.
How to Set It Up:
1. Add the Indicator to Your Chart:
Search for " MTF Squeeze Analyzer " in the TradingView Indicators library.
Add it to your chart.
2. Customize Your Settings:
Table Display:
Choose whether to show the table and select its position on the chart.
Adjust text size and colors to enhance readability.
Timeframe Selection:
Select the timeframes you want to monitor.
Enable or disable specific timeframes based on your trading strategy.
Colors & Styles:
Customize colors for different squeeze levels and momentum shifts.
Adjust header and text colors to match your chart theme.
Alert Settings:
Enable alerts for squeeze start, squeeze fire, and squeeze counts.
Set your preferred squeeze type and count threshold for alerts.
3. Interpret the Data:
Table Information:
The table displays the squeeze status and counts for each selected timeframe.
Colors indicate the type of squeeze, making it easy to assess market conditions at a glance.
Momentum Histogram:
Use the histogram to gauge the strength and direction of market momentum.
Observe color changes to identify shifts in momentum.
Why Use MTF Squeeze Analyzer ?
Enhanced Market Insight:
Gain a deeper understanding of market dynamics by monitoring multiple timeframes simultaneously.
Identify potential breakout opportunities by analyzing squeeze durations and momentum shifts.
Customizable and User-Friendly:
Tailor the indicator to fit your trading style and preferences.
Easily adjust settings without needing to delve into the code.
Time-Efficient:
Save time by viewing all relevant squeeze information in one place.
Reduce the need to switch between different charts and timeframes.
Stay Informed with Alerts:
Never miss a critical market movement with fully customizable alerts.
Focus on other tasks while the indicator monitors the market for you.
Acknowledgment:
This tool builds upon the foundational work of John Carter , who developed the TTM Squeeze concept. It also incorporates enhancements from LazyBear and Makit0 , providing a more versatile and powerful indicator. MTF Squeeze Analyzer extends these concepts by adding multi-timeframe analysis, squeeze counting, and advanced alerting features, offering traders a comprehensive solution for market analysis.
Note: Always practice proper risk management and test the indicator thoroughly to ensure it aligns with your trading strategy. Past performance is not indicative of future results.
Trade smarter with TradeVizion—unlock your trading potential today!
MTF SqzMom [tradeviZion]Credits:
John Carter for creating the TTM Squeeze and TTM Squeeze Pro.
Lazybear for the original interpretation of the TTM Squeeze: Squeeze Momentum Indicator.
Makit0 for evolving Lazybear's script by incorporating TTM Squeeze Pro upgrades – Squeeze PRO Arrows.
MTF SqzMom - Multi-Timeframe Squeeze & Momentum Tool
MTF SqzMom is a tool designed to help traders easily monitor squeeze and momentum signals across multiple timeframes in a simple, organized format. Built using Pine Script 5, it ensures that data remains consistent, even when switching between different time intervals on the chart.
Key Features:
Multi-Timeframe Monitoring: Track squeeze and momentum signals across various timeframes, all in one view. This includes key timeframes like 1-minute, 5-minute, hourly, and daily.
Dynamic Table Display: A color-coded table that automatically adjusts based on the selected timeframes, offering a clear view of market conditions.
Alerts for Key Market Events: Get notifications when a squeeze starts or fires across your chosen timeframes, so you can stay informed without needing to monitor the chart continuously.
Customizable Appearance: Tailor the look of the table by selecting colors for squeeze levels and momentum shifts, and choose the best position on your chart for easy access.
How It Works:
MTF SqzMom is based on the concept of the squeeze, which signals periods of lower volatility where price breakouts may occur. The tool tracks this by monitoring the contraction of Bollinger Bands within Keltner Channels. Along with this, it provides momentum analysis to help you gauge the potential direction of the market after a squeeze.
Squeeze Conditions: The script tracks four levels of squeeze conditions (no squeeze, low, mid, and high), each represented by a different color in the table.
Momentum Analysis: Momentum is visually represented by colors indicating four stages: up increasing, up decreasing, down increasing, and down decreasing. This color coding helps you quickly assess whether the market is gaining or losing momentum.
Using Alerts:
You can enable two types of alerts: when a squeeze starts (indicating consolidation) and when a squeeze fires (indicating a breakout). These alerts cover all timeframes you’ve selected, so you never miss important signals.
How to Set It Up:
1. Enable Alerts in Settings: Turn on "Alert for Squeeze Start" and "Alert for Squeeze Fire" in the settings.
2. Add Alerts to Your Chart:
Click the three dots next to the indicator name.
Select "Add alert on tradeviZion - MTF SqzMom."
3. Customize and Save: Adjust alert options, choose your notification type, and click "Create."
Why Use MTF SqzMom ?
Consistent Data: The tool ensures that squeeze and momentum data remain consistent, even when you switch between chart intervals.
Real-Time Alerts: Stay updated with alerts for squeeze conditions without needing to constantly watch the chart.
Simple to Use, Customizable to Fit: You can easily adjust the table’s look and choose the timeframes and colors that best suit your trading style.
Acknowledgment:
While this tool builds on the TTM Squeeze concept developed by John Carter of Simpler Trading, it offers added flexibility through multi-timeframe analysis, alerts, and customizability to make monitoring market conditions more accessible.
ka66: Bar Range BandsThis tool takes a bar's range, and reflects it above the high and below the low of that bar, drawing upper and lower bands around the bar. Repeated for each bar. There's an option to then multiply that range by some multiple. Use a value greater than 1 to get wider bands, and less than one to get narrower bands.
This tool stems out of my frustration from the use of dynamic bands (like Keltner Channels, or Bollinger Bands), in particular for estimating take profit points.
Dynamic bands work great for entries and stop loss, but their dynamism is less useful for a future event like taking profit, in my experience. We can use a smaller multiple, but then we can often lose out on a bigger chunk of gains unnecessarily.
The inspiration for this came from a friend explaining an ICT/SMC concept around estimating the magnitude of a trend, by calculating the Asian Session Range, and reflecting it above or below on to the New York and London sessions. He described this as standard deviation of the Asian Range, where the range can thus be multiplied by some multiple for a wider or narrower deviation.
This, in turn, also reminded me of the Measured Move concept in Technical Analysis. We then consider that the market is fractal in nature, and this is why patterns persist in most timeframes. Traders exist across the spectrum of timeframes. Thus, a single bar on a timeframe, is made up of multiple bars on a lower timeframe . In other words, when we reflect a bar's range above or below itself, in the event that in a lower timeframe, that bar fit a pattern whose take profit target could be estimated via a Measured Move , then the band's value becomes a more valid estimate of a take profit point .
Yet another way to think about it, by way of the fractal nature above, is that it is essentially a simplified dynamic support and resistance mechanism , even simpler than say the various Pivot calculations (e.g. Classical, Camarilla, etc.).
This tool in general, can also be used by those who manually backtest setups (and certainly can be used in an automated setting too!). It is a research tool in that regard, applicable to various setups.
One of the pitfalls of manual backtesting is that it requires more discipline to really determine an exit point, because it's easy to say "oh, I'll know more or less where to exit when I go live, I just want to see that the entry tends to work". From experience, this is a bad idea, because our mind subconsciously knows that we haven't got a trained reflex on where to exit. The setup may be decent, but without an exit point, we will never have truly embraced and internalised trading it. Again, I speak from experience!
Thus, to use this to research take profit/exit points:
Have a setup in mind, with all the entry rules.
Plot your setup's indicators, mark your signals.
Use this indicator to get an idea of where to exit after taking an entry based on your signal.
Credits:
@ICT_ID for providing the idea of using ranges to estimate how far a trend move might go, in particular he used the Asian Range projected on to the London and New York market sessions.
All the technicians who came up with the idea of the Measured Move.
Multi-Regression StrategyIntroducing the "Multi-Regression Strategy" (MRS) , an advanced technical analysis tool designed to provide flexible and robust market analysis across various financial instruments.
This strategy offers users the ability to select from multiple regression techniques and risk management measures, allowing for customized analysis tailored to specific market conditions and trading styles.
Core Components:
Regression Techniques:
Users can choose one of three regression methods:
1 - Linear Regression: Provides a straightforward trend line, suitable for steady markets.
2 - Ridge Regression: Offers a more stable trend estimation in volatile markets by introducing a regularization parameter (lambda).
3 - LOESS (Locally Estimated Scatterplot Smoothing): Adapts to non-linear trends, useful for complex market behaviors.
Each regression method calculates a trend line that serves as the basis for trading decisions.
Risk Management Measures:
The strategy includes nine different volatility and trend strength measures. Users select one to define the trading bands:
1 - ATR (Average True Range)
2 - Standard Deviation
3 - Bollinger Bands Width
4 - Keltner Channel Width
5 - Chaikin Volatility
6 - Historical Volatility
7 - Ulcer Index
8 - ATRP (ATR Percentage)
9 - KAMA Efficiency Ratio
The chosen measure determines the width of the bands around the regression line, adapting to market volatility.
How It Works:
Regression Calculation:
The selected regression method (Linear, Ridge, or LOESS) calculates the main trend line.
For Ridge Regression, users can adjust the lambda parameter for regularization.
LOESS allows customization of the point span, adaptiveness, and exponent for local weighting.
Risk Band Calculation:
The chosen risk measure is calculated and normalized.
A user-defined risk multiplier is applied to adjust the sensitivity.
Upper and lower bounds are created around the regression line based on this risk measure.
Trading Signals:
Long entries are triggered when the price crosses above the regression line.
Short entries occur when the price crosses below the regression line.
Optional stop-loss and take-profit mechanisms use the calculated risk bands.
Customization and Flexibility:
Users can switch between regression methods to adapt to different market trends (linear, regularized, or non-linear).
The choice of risk measure allows adaptation to various market volatility conditions.
Adjustable parameters (e.g., regression length, risk multiplier) enable fine-tuning of the strategy.
Unique Aspects:
Comprehensive Regression Options:
Unlike many indicators that rely on a single regression method, MRS offers three distinct techniques, each suitable for different market conditions.
Diverse Risk Measures: The strategy incorporates a wide range of volatility and trend strength measures, going beyond traditional indicators to provide a more nuanced view of market dynamics.
Unified Framework:
By combining advanced regression techniques with various risk measures, MRS offers a cohesive approach to trend identification and risk management.
Adaptability:
The strategy can be easily adjusted to suit different trading styles, timeframes, and market conditions through its various input options.
How to Use:
Select a regression method based on your analysis of the current market trend (linear, need for regularization, or non-linear).
Choose a risk measure that aligns with your trading style and the market's current volatility characteristics.
Adjust the length parameter to match your preferred timeframe for analysis.
Fine-tune the risk multiplier to set the desired sensitivity of the trading bands.
Optionally enable stop-loss and take-profit mechanisms using the calculated risk bands.
Monitor the regression line for potential trend changes and the risk bands for entry/exit signals.
By offering this level of customization within a unified framework, the Multi-Regression Strategy provides traders with a powerful tool for market analysis and trading decision support. It combines the robustness of regression analysis with the adaptability of various risk measures, allowing for a more comprehensive and flexible approach to technical trading.
Multiple Oscillator Conditions Final [siulian] v2This tool is created to gather multiple oscilators condition under the same umbrela and back-test your idea.
Basically the only intention of this tool is to used in combination with a back-tester indicator ( or manually ) where you get the entry based on the cumulative signals provided by this tool.
For example you can to combine RSI , MACD, CCI, Keltner Channels or whatever indicator you think it might give you an edge for an entry signal.
You can combine up to 7 indicators either by comparing them with a static value or with another indicator (for example you can compare RSI with RSI MA, Volume with Volume MA, etc)
There are two lines which will be printed.
1) Result(blue line) - it will print 1 when all the condition are met ( the same can be used for back-testing tools)
2) Condition Met count(yellow line) - which will count how many conditions from the ones selected are triggered ( for example you have 6 indicators that are matching the conditions and you still want to take a trade even if the condition number 7 is not met)
Alarms can be setup to check if more than defined conditions are present.
As a demo in the above image i have put several condition in order to possible catch bottoms.
Please understand this is just an example on how to integrate multiple condition into a single entity and should not be used as is.
1) price should close below KC
2) CCI < - 100
3) RSI < 30
4) Vol > Vol MA
Past performance do not guarantee future performance.
Stochastic Z-Score Oscillator Strategy [TradeDots]The "Stochastic Z-Score Oscillator Strategy" represents an enhanced approach to the original "Buy Sell Strategy With Z-Score" trading strategy. Our upgraded Stochastic model incorporates an additional Stochastic Oscillator layer on top of the Z-Score statistical metrics, which bolsters the affirmation of potential price reversals.
We also revised our exit strategy to when the Z-Score revert to a level of zero. This amendment gives a much smaller drawdown, resulting in a better win-rate compared to the original version.
HOW DOES IT WORK
The strategy operates by calculating the Z-Score of the closing price for each candlestick. This allows us to evaluate how significantly the current price deviates from its typical volatility level.
The strategy first takes the scope of a rolling window, adjusted to the user's preference. This window is used to compute both the standard deviation and mean value. With these values, the strategic model finalizes the Z-Score. This determination is accomplished by subtracting the mean from the closing price and dividing the resulting value by the standard deviation.
Following this, the Stochastic Oscillator is utilized to affirm the Z-Score overbought and oversold indicators. This indicator operates within a 0 to 100 range, so a base adjustment to match the Z-Score scale is required. Post Stochastic Oscillator calculation, we recalibrate the figure to lie within the -4 to 4 range.
Finally, we compute the average of both the Stochastic Oscillator and Z-Score, signaling overpriced or underpriced conditions when the set threshold of positive or negative is breached.
APPLICATION
Firstly, it is better to identify a stable trading pair for this technique, such as two stocks with considerable correlation. This is to ensure conformance with the statistical model's assumption of a normal Gaussian distribution model. The ideal performance is theoretically situated within a sideways market devoid of skewness.
Following pair selection, the user should refine the span of the rolling window. A broader window smoothens the mean, more accurately capturing long-term market trends, while potentially enhancing volatility. This refinement results in fewer, yet precise trading signals.
Finally, the user must settle on an optimal Z-Score threshold, which essentially dictates the timing for buy/sell actions when the Z-Score exceeds with thresholds. A positive threshold signifies the price veering away from its mean, triggering a sell signal. Conversely, a negative threshold denotes the price falling below its mean, illustrating an underpriced condition that prompts a buy signal.
Within a normal distribution, a Z-Score of 1 records about 68% of occurrences centered at the mean, while a Z-Score of 2 captures approximately 95% of occurrences.
The 'cool down period' is essentially the number of bars that await before the next signal generation. This feature is employed to dodge the occurrence of multiple signals in a short period.
DEFAULT SETUP
The following is the default setup on EURAUD 1h timeframe
Rolling Window: 80
Z-Score Threshold: 2.8
Signal Cool Down Period: 5
Stochastic Length: 14
Stochastic Smooth Period: 7
Commission: 0.01%
Initial Capital: $10,000
Equity per Trade: 40%
FURTHER IMPLICATION
The Stochastic Oscillator imparts minimal impact on the current strategy. As such, it may be beneficial to adjust the weightings between the Z-Score and Stochastic Oscillator values or the scale of Stochastic Oscillator to test different performance outcomes.
Alternative momentum indicators such as Keltner Channels or RSI could also serve as robust confirmations of overbought and oversold signals when used for verification.
RISK DISCLAIMER
Trading entails substantial risk, and most day traders incur losses. All content, tools, scripts, articles, and education provided by TradeDots serve purely informational and educational purposes. Past performances are not definitive predictors of future results.
Hybrid Overbought/Oversold OverlayIntroduction
This is a new representation of my well-known oscillator Hybrid Overbought/Oversold Detector overlaid on the chart. The script utilizes the following 12 different oscillators to bring forth a new indicator which I call it Hybrid OB/OS .
Utilized Oscillators
The utilized oscillators here are:
Bollinger Bands %B
Chaikin Money Flow (CMF)
Chande Momentum Oscillator (CMO)
Commodity Channel Index (CCI)
Disparity Index (DIX)
Keltner Channel %K
Money Flow Index (MFI)
Rate Of Change (ROC)
Relative Strength Index (RSI)
Relative Vigor Index (RVI/RVGI)
Stochastic
Twiggs Money Flow (TMF)
The challenging part of utilizing mentioned oscillators was that some of their formulas range are not similar and some of them does not have a mathematical range at all. So I used a normalization function to normalize all their output values to (0, 100) interval.
Overbought/Oversold Levels Calculation
I noticed that the levels which considered as OB/OS level by various traders for each of the utilized oscillators are so different, e.g., many traders consider 30 as OS level and 70 as OB level for RSI and some others take 20 and 80 as the levels, or some traders consider 20 and 80 as OS/OB levels for Stochastic oscillator. Also these levels could be different on different assets, e.g., OB/OS levels for CCI on EURUSD chart might be 80 and 20 while the levels on BTCUSDT chart might be 75 and 25, and so on.
So I decided to make a routine to automate the calculation of these levels using historical data. By this feature, my indicator would calculate the corresponding levels for the oscillators on current chart and then decide about the overbought/oversold situation of each one, which leads to a more accurate Hybrid OB/OS indication.
As the result, if all 12 individual oscillators say it's overbought/oversold, the Hybrid OB/OS shows 100% overbought/oversold, vice versa, if none of them say it's overbought/oversold, the Hybrid OB/OS shows 0, and so on.
The Overlaying Oscillator Problem!
A programming-related challenge here was that Pine Script assigns two separate spaces to the oscillators and the overlaid indicators, and the programmers are limited to use just one of them in each of their codes.
Knowing this, I was forced to simulate the oscillator space on the chart and display my oscillator as a diagram somehow. Of course it won't be as nice as the oscillator itself, because the relation between the main chart bars and the oscillator bars could not be obtained, but it's better than nothing!
Settings and Usage
The indicator settings contain some options about the calculations, the diagram display and the signals appearance. By default they are fine, but you could change them as you prefer.
This indicator is better to be used alongside other indicators as a confirmation (specially in counter-trend strategies I believe). Also it generates an external signal which you could use it in your own designed indicators as well.
Feel free to test it and also the former form of the Hybrid OB/OS . Good Luck!
Bullish Candlestick Patterns With Filters [TradeDots]The "Bullish Candlestick Patterns With Filters" is a trading indicator that identifies 6 core bullish candlestick patterns. This is further enhanced by applying channel indicator as filters, designed to further increase the accuracy of the recognized patterns.
6 CANDLESTICK PATTERNS
Hammer
Inverted Hammer
Bullish Engulfing
The Piercing Line
The Morning Star
The 3 White Soldiers
SIGNAL FILTERING
The indicator incorporates with 2 primary methodologies aimed at filtering out lower accuracy signals.
Firstly, it comes with a "Lowest period" parameter that examines whether the trough of the bullish candlestick configuration signifies the lowest point within a specified retrospective bar length. The longer the period, the higher the probability that the price will rebound.
Secondly, the channel indicators, the Keltner Channels or Bollinger Bands. This indicator examines whether the lowest point of the bullish candlestick pattern breaches the lower band, indicating an oversold signal. Users have the flexibility to modify the length and band multiplier, enabling them to custom-tune signal sensitivity.
Without Filtering:
With Filtering
RISK DISCLAIMER
Trading entails substantial risk, and most day traders incur losses. All content, tools, scripts, articles, and education provided by TradeDots serve purely informational and educational purposes. Past performances are not definitive predictors of future results.
Channels With NVI Strategy [TradeDots]The "Channels With NVI Strategy" is a trading strategy that identifies oversold market instances during a bullish trading market. Specifically, the strategy integrates two principal indicators to deliver profitable opportunities, anticipating potential uptrends.
2 MAIN COMPONENTS
1. Channel Indicators: This strategy gives users the flexibility to choose between Bollinger Band Channels or Keltner Channels. This selection can be made straight from the settings, allowing the traders to adjust the tool according to their preferences and strategies.
2. Negative Volume Indicator (NVI): An indicator that calculates today's price rate of change, but only when today's trading volume is less than the previous day's. This functionality enables users to detect potential shifts in the trading volume with time and price.
ENTRY CONDITION
First, the assets price must drop below the lower band of the channel indicator.
Second, NVI must ascend above the exponential moving average line, signifying a possible flood of 'smart money' (large institutional investors or savvy traders), indicating an imminent price rally.
EXIT CONDITION
Exit conditions can be customized based on individual trading styles and risk tolerance levels. Traders can define their ideal take profit or stop loss percentages.
Moreover, the strategy also employs an NVI-based exit policy. Specifically, if the NVI dips under the exponential moving average – suggestive of a fading trading momentum, the strategy grants an exit call.
RISK DISCLAIMER
Trading entails substantial risk, and most day traders incur losses. All content, tools, scripts, articles, and education provided by TradeDots serve purely informational and educational purposes. Past performances are not definitive predictors of future results.
