Indicator
MACD Signal to Zero DistanceIndicator Overview
The MACD & Signal to Zero Distance indicator is a highly customized momentum space oscillator designed for PulseWire. Unlike the traditional MACD, which focuses on the net difference between the fast and slow lines (the standard histogram), this indicator isolates and visualizes the absolute spatial distance of both the MACD Line (Fast Line) and the Signal Line (Slow Line) relative to the Zero Line.
By converting these spatial relationships into color-coded column groups, it provides traders with an instantaneous visual gauge of absolute trend strength, acceleration, and mean-reversion levels.
Core Logic & Data Interpretation
The indicator operates on a linear mapping of spatial distance. When either line sits perfectly on the zero baseline, its distance is 0 (the corresponding column vanishes).
MACD Line to Zero Distance (Fast Component):
Positive Values (Green Columns): Indicate bullish momentum. Higher columns signify that short-term price action has stretched significantly above the long-term baseline.
Negative Values (Red Columns): Indicate bearish momentum. Deeper columns reflect stronger absolute downside expansion.
Signal Line to Zero Distance (Slow Component):
Positive (Blue Columns) / Negative (Orange Columns): Represent the absolute positioning of the medium-term trend. As a moving average of the MACD line, its height relative to the zero axis filters out short-term noise and outlines the structural "margin of safety."
Key Features & Technical Advantages
1. Multi-Source Adaptability
This indicator breaks the constraint of traditional MACD scripts that calculate based solely on the closing price. Traders can seamlessly toggle the Source input to Open, High, Low, or even VWAP (Volume Weighted Average Price). This flexibility makes it highly compatible with Volume Price Analysis (VPA) and intraday anchored trading systems.
2. Clutter-Free Dual Column Design
By rendering two separate, color-distinct bar groups on a shared axis, the script allows traders to identify key market conditions at a glance:
Convergence/Divergence: Whether the fast and slow columns are leveling out or expanding away from each other.
Phase Split: Scenarios where the MACD line has already crossed the zero axis into negative territory while the Signal line remains buffered above it.
3. Precision Mean-Reversion & Trend Monitoring
Since the columns map absolute mathematical distances, they serve as an excellent gauge for:
Baseline Tests: When columns compress near 0, the market is coiled tightly at a fair-value inflection point, offering high-probability breakout or retest entries.
Momentum Exhaustion (Overextension): When columns reach historical peak heights, it signals that the market is overextended relative to its zero baseline, indicating a high probability of a mean-reversion pause or pullback.
核心设计逻辑与数值含义
指标严格遵循“空间距离”的线性映射逻辑，当快慢线完美回归或踩在零轴上时，距离为 0（柱体消失）。
快线离零轴距离（MACD to Zero）：
正值（绿色柱体）：代表多头动能主导，柱体越高，说明短期价格偏离长期均线的绝对多头空间越大。
负值（红色柱体）：代表空头动能主导，柱体越长，说明空头向下发散的绝对动能越强。
慢线离零轴距离（Signal to Zero）：
正值（蓝色柱体） / 负值（橙色柱体）：代表中线趋势的绝对位置。慢线作为快线的移动平均，其距离零轴的高度反映了趋势的稳定性和“安全边际”。
核心功能与技术优势
1. 多维度价格源支持 (Multi-Source Adaptability)
指标打破了传统 MACD 只能基于收盘价（Close）计算的限制。用户可以在设置中自由切换价格源（如开盘价 Open、最高价 High、最低价 Low）甚至是 VWAP（成交量加权平均价）。这使得指标能够完美融入基于量价分析（Volume Price Analysis）或日内锚定交易的系统。
2. 并排分组视觉设计 (Clarity at a Glance)
通过在零轴上下同时绘制两组独立颜色、相同坐标系的柱状图，交易者可以一眼看出：
快线与慢线是否正在收敛（柱体高度趋于一致）。
快慢线相对于零轴的绝对空间（如：快线已跌破零轴进入负数区，而慢线仍踩在零轴上方保持正数）。
3. 直观的回归交易逻辑 (Mean Reversion & Trend Following)
由于该指标的数值代表绝对距离，交易者可以非常精确地捕捉：
踩线动能：当柱体高度缩减至接近 0（-1 到 +1 之间），代表价格与趋势线完美贴合，是极佳的突破或共振确认点。
动能衰竭（乖离率过大）：当绿柱或红柱达到历史极值高度，代表短线动能消耗过大，距离零轴过远，面临向零轴修正（动能衰竭或反弹）的技术需求。
以下は、このカスタムインジケーターの専門的かつ客観的な日本語解説です。
インジケーター概要 (Indicator Overview)
本インジケーターは、PulseWire用にカスタマイズされた「MACDモメンタム空間オシレーター」です。従来のMACDが「MACD線とシグナル線の差（ヒストグラム）」に焦点を当てるのに対し、本インジケーターはMACD線（短期線）とシグナル線（長期線）のそれぞれが、ゼロ軸（Zero Line）からどれだけ絶対的な空間距離を置いているかを列状のヒストグラムとしてダイレクトに視覚化します。
これにより、現在の価格モメンタムが位置する絶対的な強弱のゾーンや、ゼロ軸への回帰状態を瞬時に視覚的に把握することが可能になります。
コアロジックと数値の定義
本インジケーターは「空間距離」の線形マッピングロジックに厳格に従っています。各ラインがゼロ軸に完全に張り付いた時、距離は「0」となり、ヒストグラムの柱は消失します。
MACD線のゼロ軸乖離距離（MACD to Zero）:
正の値（緑の柱）: 強気（ブル）モメンタムが主導。柱が高くなるほど、短期的な価格が長期平均から上方へ大きく乖離していることを示します。
負の値（赤の柱）: 弱気（ベア）モメンタムが主導。柱が長くなるほど、下方向への拡散エネルギーが強いことを示します。
シグナル線のゼロ軸乖離距離（Signal to Zero）:
正の値（青の柱）／ 負の値（オレンジの柱）: 中期トレンドの絶対的な位置。MACD線の移動平均であるシグナル線のゼロ軸からの高さは、トレンドの安定性と「セーフティ・マージン（安全余裕度）」を反映します。
主な機能と技術的メリット
1. マルチ・ソース（価格源）対応 (Multi-Source Adaptability)
従来のMACDが終値（Close）のみに基づいていた制限を排除しました。設定画面から、始値（Open）、高値（High）、安値（Low）、さらにはVWAP（出来高加権平均価格）へ自由に切り替えることができます。これにより、量価分析（ボリューム・プライス・アナリシス）や日中アンカー型取引システムとも完全に融合させることが可能です。
2. 並列グループ化された視覚デザイン (Clarity at a Glance)
ゼロ軸の上下に、色分けされた2つの独立したヒストグラムを同一座標系に描画することで、トレーダーは以下の状態をひと目で判別できます。
MACD線とシグナル線が収束（柱の高さが一致）しつつあるか。
ゼロ軸に対するそれぞれの絶対的フェーズ（例：MACD線はすでにゼロ軸を割り込んで負の領域にあるが、シグナル線は依然としてゼロ軸の上で耐えているなど）。
3. 直感的な平均回帰・トレンドフォロー戦略 (Mean Reversion & Trend Following)
数値が絶対的な「距離」を表すため、以下のような局面を極めて正確に捉えることができます。
ラインへの接地（もみ合いの確認）: 柱の高さが0付近に収縮した時は、トレンドラインに価格が完全に収束したことを意味し、ブレイクアウトや共振（レジサポ転換）を狙う絶好のエントリーポイントとなります。
モメンタムの枯渇（過剰乖離）: 緑または赤の柱が過去の極値（ピーク）に達した時は、短期的モメンタムが過剰に消費され、ゼロ軸から離れすぎていることを示し、ゼロ軸への回帰（反発や調整）のテクニカルな需要が高まっていると判断できます。 Indicator
MACD Dive [TTM Squeeze | Dual Lock %R]Disclaimer : This indicator is not financial advice and is strictly for educational and informational purposes only. The metrics and signals provided herein (including momentum crosses, trend saturation state icons, and squeeze markers) are calculated based on historical market data and do not guarantee future performance. Trading stocks and commodities involves significant risk of loss. The user assumes full responsibility for all trading decisions and should always perform their own due diligence before executing trades.
MACD Dive is a multi-state momentum and volatility context engine. By layering momentum oscillation (MACD/PPO/MACD-V) with market stalemates (volatility squeeze) and trend exhaustion (Dual %R saturation), this suite transforms a standard MACD into a multi-dimensional 'No-Go' gatekeeper. This synergy is what gives the engine its edge: it actively blocks the trader from whipsawing in sideways chop or buying into a dying trend, highlighting high-probability market turns where momentum, volatility, and trend capacity perfectly align.
Standard oscillators have a scaling problem. This script lets you choose your engine:
MACD (Classic): Measures momentum in absolute dollars. Great for visual reactivity, but a "2.0" reading means something different on a $5 stock versus a $500 stock.
PPO (Percentage): Measures momentum in percentages. Standardizes the reading across all assets, making it ideal for fixed-rule algorithmic trading.
MACD-V (Volatility Normalized): This divides the MACD by the Average True Range (ATR). It measures momentum in "Units of Volatility," mathematically adapting to market chaos so that signals remain consistent across both different assets and shifting volatility regimes (quiet markets vs chaotic markets).
This suite includes a fully optimized divergence detection engine:
Regular Divergence (Solid Lines): Identifies Trend Reversals. Price pushes to a new extreme, but momentum fails to follow, signaling exhaustion.
Hidden Divergence (Dashed Lines): Identifies Trend Continuations (Slingshots). Price pulls back, but momentum fully resets, signaling a high-probability entry in the direction of the dominant trend.
Located in your chosen corner, the HUD provides an instant visual readout with hover tooltips for active Engine Mode, %R Fatigue state, Oscillator crossover validation, and Squeeze environment. Vertical background highlights in green or red represent filter-passed momentum crossovers, like the MACD bullish cross. Use the extensive inline tooltips in the indicator's settings panel for a comprehensive breakdown of every tunable parameter.
Adaptive Time-Frames & RSI Gatekeeper
Think of this as an automated gear shifter. When looking at lower timeframes (below a user-defined boundary, e.g. 1 hour), the engine automatically scales down to tight, agile lookback periods. When viewing high timeframes, it dials up to filter out noise.
Buying a bullish MACD cross when the RSI is already at 85 increases risk of buying the top when the tank is empty. The optional RSI Safety Filter acts as a strict ceiling/floor blocker. If momentum crosses upward but the asset is mathematically overbought, the indicator suppresses the background highlight. It prevents signals on MACD crosses that have no fuel left.
VOLATILITY ENGINE: BB-KC Squeeze Radar
Building on John Carter’s TTM Squeeze by mapping the contraction of Bollinger Bands inside Keltner Channels to identify market stalemates. The implementation here color codes between a Loose Squeeze (BB inside 1.5 KC) and a hyper-compressed Tight Squeeze (BB inside 1.0 KC) to show the staged intensity of the coiled spring.
While the market coils sideways, a 20-period Linear Regression calculates the trajectory of price deviation inside the bands. The directional bias is shown by customizable markers on the zero line (default ⌃ or ⌄). This reveals hidden institutional accumulation or distribution before the trigger is pulled. To bypass "dead money" risk, the script tracks the first clean candle close or intraday pierce outside the Keltner bounds following a squeeze, catching the expansion phase exactly as it starts.
Furthermore, it accounts for the "Disappearing Mark" phenomenon. Bollinger Bands expand instantly when price moves, causing standard squeeze signals to vanish 1-3 bars before the real breakout candle. This script uses a memory state to remember recent compression, firing a "squeeze release" marker (default ❖) the exact moment price closes outside the Keltner bounds. Trade the release, not the waiting room.
Note: While MACD Dive tracks this compression mathematically on its zero-line, you can see the actual physical boundaries of the breakout by pairing it with my companion Swing Data suite . Plotting its Keltner Channel at 1.5 multiplier over your price chart allows you to visually verify the exact moment the squeeze release mark is ignited.
SATURATION ENGINE: Dual-Lock %R and Momentum Rot
This suite tracks sustained trend maturity using a fast/slow dual Williams %R setup. The conceptual pairing of a fast and slow %R to identify overbought/oversold exhaustion is credited to upslidedown's excellent Trend Exhaustion indicator . I highly recommend applying their script to your chart if you want to visually learn how the two %R lines interact.
While upslidedown’s implementation offers multiple display modes to paint visual boxes and exhaustion zones directly over price action, the focus here is on the discrete icons for trend status at the top and bottom of the MACD pane: Ignition (·), Saturation (□), and Fatigue (×). This suite adapts native ta.wpr() math assuming the trader is already familiar with Dual %R mechanics. Specific "Sprint" and "Marathon" tuning guidance is provided in the tooltips: heavily smoothing the fast line to ignore intraday noise, while lightly smoothing the macro slow line to preserve its reach into extreme zones.
It also features one major addition: the Stall. While Dual %R tracks Price Location (confirming price is structurally pinned at the highs), it doesn't track Velocity (confirming energy is sustained). To solve this, a Stoch RSI "Rot" detector runs quietly inside the saturation state. If price continues to float at the highs but internal velocity drops below a critical threshold, the script overlays a Stall marker (•). Designed as a "one-shot" early warning, it fires only on the first detection per trend saturation leg to prevent chart clutter. This differentiates a strong trend lock from a rotting lock, warning us that the move is running on fumes: giving us the exact cue to tighten stops, trim into parabolic strength, and strictly avoid adding new size.
BACKTESTER READY
Out-of-the-box compatibility with a comprehensive built-in README guide is available directly inside the settings menu. For traders who prefer a "Diamond Hands" approach, the indicator fully maps to Jason5480's TTS Framework convention, outputting strict integer states (1, -1, 2, -2) to hold full position size until the trailing macro baseline completely fractures. My personal backtester, Cosmos Signal Commander (which may be released to the public in the future), broadcasts a composite float signal capable of managing active trade positioning. It tracks entries, hard stops, and partial take-profits (swapping the trailing stop from tight to a wide "runner" buffer upon hitting extended ATR targets).
PERFORMANCE OPTIMIZATION
O(1) Memory States: Replaced lag-heavy ta.barssince() and 50-bar for loops in the Divergence engine with O(1) var state trackers.
String Caching: HUD table strings are built once in the global var scope to prevent constant memory allocation and garbage collection lag.
UI Mutation: The HUD uses table.cell_set_* to alter data dynamically, bypassing the stutter caused by destroying and redrawing tables on every tick.
Native C++ Backend: Replaced custom highest/lowest math arrays with native ta.wpr() functions for the %R engine to maximize computation speed.
Ghost State Resets: When switching the backtester logic to "Long Only" mode, the engine actively hunts and kills lingering short-memory variables so they don't inadvertently suppress valid long signals.
Indicator
AG Pro MACD Drift Filter [AGPro Series]AG Pro MACD Drift Filter
Overview
AG Pro MACD Drift Filter is a rules-based momentum quality indicator built around MACD structure, persistence, and decay behavior.
The script is not designed to treat every MACD expansion, crossover, or positive histogram print as equally meaningful. Its purpose is to help users evaluate whether current momentum is sustaining cleanly, weakening internally, or drifting into lower-quality continuation.
In many charts, the difficult part is not detecting that momentum exists. The difficult part is deciding whether that momentum is stable enough to respect, fragile enough to fade, or already starting to lose transmission quality before price fully reflects the slowdown. This indicator is built for that specific problem.
Rather than framing MACD as a simple signal engine, AG Pro MACD Drift Filter uses a structured state model to organize momentum into practical categories such as bullish drift, bearish drift, neutral or unstable conditions, and decay-prone phases. The output is intended to improve chart interpretation, not to replace broader market context.
What the script does
The script studies the relationship between the MACD line, the signal line, the histogram, and zero-line behavior in order to classify the current momentum environment.
Its main objective is to answer questions such as:
- Is current momentum expanding with acceptable continuity?
- Is the histogram improving in a way that supports follow-through, or only producing a temporary burst?
- Is MACD maintaining stable directional structure, or repeatedly slipping back toward unstable conditions?
- Is separation between MACD and signal line supporting continuation, or beginning to compress?
- Is the current move still carrying directional quality, or transitioning into decay?
The result is a compact momentum-quality framework that can be used as a continuation filter, a caution filter, or a chart-organization layer.
Why this script is different
This script is not presented as a generic MACD crossover tool.
Its focus is not on counting crosses or highlighting every histogram color shift. Instead, it is built around the idea that momentum quality matters more than raw momentum presence. A move can remain above zero and still lose internal quality. A histogram can expand and still produce weak follow-through. A crossover can occur inside unstable conditions and carry less analytical value than its appearance suggests.
AG Pro MACD Drift Filter attempts to separate those cases by combining several dimensions of MACD behavior into a rules-based drift model.
In practical terms, the script attempts to distinguish between:
- sustained directional drift
- fragile continuation
- internal weakening
- contraction and decay risk
- unstable zero-line behavior
This makes it more suitable as a momentum filter than as a standalone trigger engine.
Core methodology
The model evaluates momentum quality through multiple components rather than a single event.
1) Expansion quality
The script evaluates whether histogram magnitude is expanding with enough consistency to support the idea of directional development. A simple increase in histogram size is not treated as sufficient on its own. The model also looks at whether that expansion is steady enough to qualify as usable drift.
2) Zero-line persistence
Momentum states near the zero line can be more fragile and more prone to whipsaw. For that reason, the script evaluates whether MACD is maintaining enough distance and persistence relative to the zero area, or whether it is repeatedly slipping back toward instability.
3) Signal-line separation quality
The distance between MACD and signal line is part of the script's continuation logic. Expanding separation can support the case for cleaner momentum conditions, while compressing separation can indicate that the move is losing internal pressure even if price has not fully reacted yet.
4) Continuity
The script tracks whether directional alignment is being maintained across bars. The goal is to reduce the analytical weight of fragmented or inconsistent momentum states and give more weight to cleaner persistence.
5) Decay pressure
The model also monitors conditions that can reduce the quality of current drift. Compression, weakening histogram behavior, increased instability, and loss of directional efficiency contribute to decay risk.
These components are combined into a structured quality score and a state engine.
Main outputs
State
The State row summarizes the current momentum regime. Depending on conditions, the script can classify the environment as bullish drift, bearish drift, neutral or unstable, or other transition states derived from the internal logic.
Quality
The Quality value summarizes the current momentum-quality condition on a 0 to 100 scale. It is not intended as a standalone trade score. It is a compact way to express whether the underlying drift structure is currently weak, fragile, usable, or stronger relative to the script's framework.
Persistence
Persistence reflects whether directional conditions are being maintained with enough stability to be respected. This value is particularly useful when users want to distinguish between brief impulses and cleaner continuation behavior.
Decay Risk
Decay Risk estimates whether the move is beginning to lose quality internally. Higher decay risk does not automatically imply reversal. It means the current directional structure is carrying less internal efficiency and may deserve more caution.
Zero-Line
This field summarizes whether MACD is operating above zero, below zero, or in a more unstable zone. It is included because zero-line persistence often changes the interpretive quality of otherwise similar MACD readings.
Separation
This row describes whether MACD and signal line are expanding apart, remaining relatively stable, or compressing. It can help users identify whether momentum is gaining transmission strength or narrowing.
Phase
The script groups behavior into broad phases such as expansion, plateau, or contraction. This helps users interpret whether the current environment is still developing or beginning to cool.
Bias
Bias is not a buy or sell instruction. It is a compact interpretation layer that summarizes whether the current structure is more consistent with continuation, caution, or weaker follow-through.
Mode
The script includes a mode framework so users can run the tool with a more balanced or more selective posture, depending on how strict they want the state engine to be.
How to read the indicator
One practical way to use the script is to treat it as a continuation-quality filter.
For example, a bullish chart condition may look more structurally convincing when:
- the state remains in a bullish drift condition
- the quality score is improving or holding at healthier levels
- persistence remains stable
- separation is not compressing aggressively
- decay risk is contained
On the other hand, users may choose to become more cautious when:
- price still appears constructive, but quality is fading
- separation compresses while continuation expectations remain elevated
- the state returns to neutral or unstable conditions
- decay risk rises without meaningful renewal in quality
- the move remains active on price, but internal MACD structure begins to deteriorate
This script can also be used alongside support and resistance analysis, broader trend context, structural breaks, pullback logic, or other risk-management frameworks.
Alerts
The script includes alert conditions tied to meaningful state changes rather than arbitrary noise.
Examples include:
- Bullish Drift Confirmed
- Bearish Drift Confirmed
- Bullish Drift Weakening
- Bearish Drift Weakening
- Momentum Decay Warning
- Neutral Reset
- High-Quality Drift Detected
- Low-Quality Expansion Detected
These alerts are intended to help users monitor changes in momentum quality, not to function as guaranteed trading signals.
Key inputs
Core settings include the source series and standard MACD lengths.
Engine settings allow users to control the quality lookback, persistence window, decay sensitivity, instability penalty, zero-line stability filtering, and strictness.
Display settings manage panel visibility, panel position, theme handling, label size, label density, and optional visual styling.
Because different symbols and timeframes can produce different rhythm characteristics, users may want to experiment with persistence and sensitivity settings rather than assuming one configuration fits all market conditions.
Suggested interpretation
The strongest use case for this tool is not signal substitution, but signal qualification.
In other words, many users may find it more useful to ask:
"Does this move deserve continuation bias?"
instead of asking:
"Did MACD cross?"
That distinction is central to the script.
The script does not assume that every positive histogram bar is actionable. It does not assume that every crossover deserves equal analytical weight. It attempts to organize momentum conditions into a more structured framework so users can better judge whether current directional pressure is persistent, fragile, or fading.
Limitations and transparency
This indicator does not predict future price movement.
It does not guarantee continuation, reversal, breakout success, or trade performance. It does not replace broader chart context, volatility analysis, liquidity considerations, or risk management.
Like other momentum-based tools, it can still produce less useful readings in highly choppy environments, low-volatility compression regimes, or sudden event-driven price conditions. Users should interpret the output in context and validate whether the script's settings fit the instrument and timeframe they are studying.
The state engine is designed to organize information, not to remove uncertainty from market behavior.
Risk disclosure
This script is for educational and analytical use.
It should not be treated as financial advice, investment advice, or a promise of outcome. Users remain responsible for their own decision-making, trade planning, and risk control.
Indicator
Adaptive Squeeze Momentum Pro [WillyAlgoTrader]Adaptive Squeeze Momentum Pro is a non-overlay oscillator that combines volatility compression detection (squeeze) with an ATR-normalized momentum histogram and built-in divergence scanning — providing three layers of analysis in a single pane: when the market is coiling (squeeze), which direction the energy is building (momentum), and when momentum is diverging from price (divergence warnings).
The classic squeeze momentum concept — Bollinger Bands contracting inside Keltner Channels — has been available on PulseWire for years. What this indicator adds is an entirely different momentum calculation that is ATR-normalized (making it comparable across instruments and timeframes), a 4-state color-coded histogram that distinguishes between momentum acceleration and deceleration in both directions, automated divergence detection with optional HTF trend filtering, and a preset system tuned for different trading styles. The result is a modernized squeeze oscillator designed for practical trading rather than textbook demonstration.
🔍 WHAT MAKES IT ORIGINAL
1. ATR-normalized momentum oscillator. Most squeeze indicators use a raw linear regression value or simple price-minus-midline for their histogram. This makes the oscillator's scale dependent on the instrument's price level — a reading of 5.0 on BTCUSD means something completely different than 5.0 on EURUSD. This indicator solves that by dividing the raw momentum by the current ATR value, producing a dimensionless oscillator that typically ranges between −3 and +3 regardless of instrument or timeframe. The raw momentum itself is calculated as the distance between price and the average of the highest-high/lowest-low midpoint and an EMA — capturing both range-based and trend-based positioning. An optional EMA smoothing layer (configurable, default 3) reduces noise without excessive lag.
2. EMA-based volatility bands instead of standard Bollinger Bands. The squeeze detection uses an EMA (not SMA) as its basis, paired with standard deviation for the band width. EMA reacts faster to recent price changes than SMA, making the squeeze detection more responsive to volatility shifts — particularly useful on crypto and volatile instruments where compression phases can be short-lived. The ATR channel (replacing the traditional Keltner Channel) uses the same EMA basis. The squeeze fires when the volatility band width is less than the ATR channel width (ratio < 1.0).
3. Tiered squeeze intensity. Instead of a binary on/off squeeze state, the indicator classifies the compression into four tiers based on the ratio between the volatility band width and the ATR channel width:
— EXTREME (ratio < 0.5): very tight compression, highest energy buildup
— HIGH (ratio < 0.7): significant compression
— MID (ratio < 0.9): moderate compression
— LOW (ratio < 1.0): mild compression
— NONE (ratio ≥ 1.0): no squeeze
This lets you distinguish between a mild contraction (which may resolve quietly) and an extreme compression (which is more likely to produce a strong directional move).
4. 4-state histogram coloring. The momentum histogram uses four distinct colors to convey both direction and acceleration:
— Bull Strong (bright green): momentum above zero AND rising — bulls are accelerating
— Bull Weak (teal): momentum above zero BUT falling — bulls are decelerating, potential topping
— Bear Strong (bright red): momentum below zero AND falling — bears are accelerating
— Bear Weak (dark red): momentum below zero BUT rising — bears are decelerating, potential bottoming
The transition from Strong to Weak (or vice versa) often precedes a zero-line cross, giving an early visual warning of momentum shifts.
5. Automated divergence detection with two modes. The indicator scans for classic divergences between price pivots and momentum pivots:
— Bullish divergence : price makes a lower low while momentum makes a higher low
— Bearish divergence : price makes a higher high while momentum makes a lower high
Two detection modes are available:
— Early mode (default): divergence is labeled on bar close at the pivot with zero right-side confirmation bars — fastest detection, may occasionally produce false signals
— Confirmed mode : requires N confirmation bars on the right side of the pivot (same as the lookback length) — more reliable, but delayed
Divergence lines are drawn on the oscillator connecting the two momentum pivots, and optional overlay labels are placed directly on the price chart (using force_overlay) so you can spot divergences without switching panes.
6. HTF trend filter for divergences. An optional higher-timeframe filter compares a 21-period EMA to a 50-period EMA on the selected HTF (default 60min). When enabled, bullish divergences are only shown when the HTF trend is bullish (fast EMA > slow EMA), and bearish divergences only when HTF is bearish. The HTF data uses the standard non-repainting pattern ( + lookahead_on). This filter reduces counter-trend signals that divergences often produce.
⚙️ HOW IT WORKS
Squeeze detection:
On each bar, the script calculates two band widths:
— Volatility band width = StdDev(source, length) × multiplier × 2, centered on an EMA
— ATR channel width = ATR(length) × multiplier × 2
The squeeze ratio = volatility width / ATR width. When this ratio falls below 1.0, volatility bands are inside the ATR channel — the market is in a squeeze. The tier is determined by how far below 1.0 the ratio is.
Momentum calculation:
— Midpoint 1: (highest high over N bars + lowest low over N bars) / 2
— Midpoint 2: EMA(source, N)
— Combined midpoint: average of Midpoint 1 and Midpoint 2
— Raw momentum: source − combined midpoint
— Normalized momentum: raw momentum / ATR(N)
— Final momentum: EMA(normalized momentum, smoothing) if smoothing > 1, else raw normalized
This approach blends range-based positioning (where is price within the recent range) with trend-based positioning (where is price relative to the EMA), then normalizes by ATR so the oscillator is instrument-agnostic.
Divergence detection:
The script uses ta.pivotlow() and ta.pivothigh() on both the momentum oscillator and price (low/high). For each new momentum pivot, it compares against the previous stored pivot. A bullish divergence is detected when the current price pivot low is lower than the previous one, but the current momentum pivot low is higher. Bearish divergence is the mirror. In Early mode (rightBars = 0), the pivot is identified at bar close without waiting for right-side confirmation. In Confirmed mode (rightBars = lookback), pivots are only confirmed after N bars pass.
HTF filter:
HTF EMAs are fetched with request.security() using the + lookahead_on non-repainting pattern. When the 21 EMA is above the 50 EMA on the higher timeframe, the HTF trend is bullish; below = bearish.
Squeeze release alert:
The "squeeze fired" alert triggers on the first confirmed bar after the squeeze condition ends (sqzOn transitions from true to false). The alert message includes the momentum direction at release (bullish if momentum > 0, bearish if ≤ 0).
📖 HOW TO USE
Reading the histogram:
— Bright green bars (Bull Strong) = momentum above zero and accelerating — strongest bullish phase
— Teal bars (Bull Weak) = momentum above zero but decelerating — bulls losing steam
— Bright red bars (Bear Strong) = momentum below zero and accelerating — strongest bearish phase
— Dark red bars (Bear Weak) = momentum below zero but decelerating — bears losing steam
— Transition from Strong → Weak = early warning of momentum exhaustion
— Zero-line cross after Weak phase = momentum direction change
Reading the squeeze:
— Orange-tinted background = active squeeze (volatility compression)
— The longer and tighter the squeeze, the more energy is stored
— Watch for the first bar after the background clears (squeeze release) — the momentum direction at that moment often indicates the breakout direction
Reading divergences:
— Green "Div" label below the oscillator / below price = bullish divergence (potential bottom)
— Red "Div" label above the oscillator / above price = bearish divergence (potential top)
— Lines on the oscillator connect the two pivots that form the divergence
— Divergences inside a squeeze are particularly powerful — they suggest the breakout direction before the squeeze releases
Suggested workflow:
— Wait for a squeeze to form (background tint appears)
— Watch for divergences during the squeeze — they hint at breakout direction
— On squeeze release, check momentum direction and histogram color
— Bright green at release = bullish breakout bias; bright red = bearish
— If HTF filter is enabled, only take signals aligned with the higher-timeframe trend
Presets:
— Conservative : length ≥ 25, BB mult ≥ 2.2, ATR mult ≤ 1.2, smoothing ≥ 7 — fewer signals, smoother histogram, suited for 4H–Daily
— Default : uses your manual settings — balanced for 15min crypto
— Aggressive : length ≤ 14, BB mult ≤ 1.6, ATR mult ≥ 1.6, smoothing ≤ 2 — more signals, faster reaction
— Scalping : length ≤ 10, BB mult ≤ 1.4, ATR mult ≥ 1.8, no smoothing — optimized for 1–5min
⚙️ KEY SETTINGS REFERENCE
— Squeeze Length (default 21): shared lookback for EMA, StdDev, and ATR — higher = slower squeeze detection, longer compression phases
— Volatility Band Mult (default 1.8): multiplier for the EMA ± StdDev bands — higher = wider bands, squeeze triggers more easily
— ATR Channel Mult (default 1.6): multiplier for the ATR channel — lower = narrower channel, squeeze triggers less
— Momentum Length (default 20): lookback for highest-high, lowest-low, and momentum EMA
— Momentum Smoothing (default 3): EMA smoothing on the normalized momentum — 1 = raw, higher = smoother
— Divergence Lookback (default 3): pivot detection lookback for divergence scanning
— Early Divergence (default On): label on bar close with no right-side confirmation — faster but less filtered
— Use HTF Trend Filter (default Off): filter divergences by higher-timeframe EMA trend
— Higher Timeframe (default 60): HTF for trend filter — should be 3–5× chart timeframe
🔔 Alerts
Three alert conditions (all bar-close confirmed):
— Squeeze Fire : squeeze releases — includes momentum direction (bullish/bearish)
— Bullish Divergence : price lower low + momentum higher low — includes HTF trend status
— Bearish Divergence : price higher high + momentum lower high — includes HTF trend status
All support standard text and JSON webhook format.
⚠️ IMPORTANT NOTES
— This indicator is a non-overlay oscillator — it appears in a separate pane below the chart. Optional divergence labels can be mirrored on the price chart via the "Show Divergences on Chart" toggle.
— All signals require bar-close confirmation . The HTF filter uses the standard non-repainting security call pattern ( + lookahead_on).
— Early divergence mode (default) labels divergences without waiting for right-side pivot confirmation — this provides faster signals but may occasionally flag a divergence that is later invalidated. Switch to Confirmed mode for higher reliability at the cost of delay.
— A squeeze release indicates that volatility is expanding — it does not guarantee a directional move. False breakouts can and do occur, especially on lower timeframes.
— Divergences signal momentum weakening, not guaranteed reversals. They are most effective as confluence with other analysis, not as standalone signals.
— The ATR normalization makes the oscillator scale-independent, but the absolute readings (e.g. +2.0 vs +1.5) should be compared within the same instrument/timeframe context, not across different ones.
— Works across all asset classes. Volume is not used in any calculation. Indicator
Digital MACD Divergences MTF [LUPEN]Digital MACD Divergences MTF V1.0
Overview:
Digital MACD Divergences MTF is an advanced momentum oscillator based on digital signal processing techniques.
Instead of relying on traditional moving-average smoothing, it applies Finite Impulse Response (FIR) digital filters to extract momentum more cleanly, reducing lag and short-term market noise.
The indicator is designed to provide a clear visualization of momentum structure, divergence behavior, and multi-timeframe context, rather than discrete trading signals.
Conceptual Architecture
At its core, the indicator reinterprets the classic MACD framework through digital convolution logic:
FIR filters are used to compute momentum in a more responsive and stable manner than standard EMA-based MACD.
The resulting histogram represents momentum intensity and direction as a continuous state rather than binary conditions.
A digitally smoothed signal line provides structural reference without introducing excessive delay.
This approach emphasizes momentum quality and structure, not signal frequency.
Divergence Detection Logic:
The script includes automatic divergence detection based on pivot analysis:
Regular bullish and bearish divergences are identified using confirmed pivot points.
Divergences are visualized with explicit line structures and optional filled areas, highlighting the zone of disagreement between price behavior and momentum.
The visualization is designed to remain readable without obscuring price action.
Divergences are presented as contextual information, not as mandatory actions.
Multi-Timeframe (MTF) Context
Digital MACD Divergences MTF supports native multi-timeframe analysis through a dual-pane workflow:
A lower-timeframe instance visualizes local momentum dynamics.
A higher-timeframe instance visualizes the broader momentum regime within which lower-timeframe fluctuations occur.
The higher-timeframe view is not intended as confirmation or filtering logic, but as a contextual background layer that helps interpret short-term momentum behavior inside a larger structural environment.
This separation avoids decision compression and keeps each timeframe’s role conceptually distinct.
Visual Design
Gradient-based histogram fills represent momentum intensity in a continuous manner.
Positive and negative momentum regions are clearly differentiated while remaining adaptable to both dark and light chart themes.
All visual elements are designed to emphasize state and regime, not discrete events.
Reliability
No repainting: all divergences and momentum states are confirmed on candle close and remain fixed.
Designed for consistency across instruments and timeframes.
Customization Options
Timeframe selection for MTF mode (leave empty to use the chart’s timeframe).
Adjustable signal smoothing parameters.
Divergence visibility controls, pivot sensitivity, and optional divergence fill.
Fully customizable color palette.
Usage Notes
This indicator is a visual market analysis tool intended to support momentum interpretation and structural context.
It does not provide investment advice, trading signals, or automated decision logic, and should be used as part of a broader analytical framework.
Final quotes:
"Trading is not about prediction, but about understanding momentum structure.
Digital MACD removes noise to make that structure visible." Indicator
MACD Forecast Colorful [DiFlip]MACD Forecast Colorful
The Future of Predictive MACD — is one of the most advanced and customizable MACD indicators ever published on PulseWire. Built on the classic MACD foundation, this upgraded version integrates statistical forecasting through linear regression to anticipate future movements — not just react to the past.
With a total of 22 fully configurable long and short entry conditions, visual enhancements, and full automation support, this indicator is designed for serious traders seeking an analytical edge.
⯁ Real-Time MACD Forecasting
For the first time, a public MACD script combines the classic structure of MACD with predictive analytics powered by linear regression. Instead of simply responding to current values, this tool projects the MACD line, signal line, and histogram n bars into the future, allowing you to trade with foresight rather than hindsight.
⯁ Fully Customizable
This indicator is built for flexibility. It includes 22 entry conditions, all of which are fully configurable. Each condition can be turned on/off, chained using AND/OR logic, and adapted to your trading model.
Whether you're building a rules-based quant system, automating alerts, or refining discretionary signals, MACD Forecast Colorful gives you full control over how signals are generated, displayed, and triggered.
⯁ With MACD Forecast Colorful, you can:
• Detect MACD crossovers before they happen.
• Anticipate trend reversals with greater precision.
• React earlier than traditional indicators.
• Gain a powerful edge in both discretionary and automated strategies.
• This isn’t just smarter MACD — it’s predictive momentum intelligence.
⯁ Scientifically Powered by Linear Regression
MACD Forecast Colorful is the first public MACD indicator to apply least-squares predictive modeling to MACD behavior — effectively introducing machine learning logic into a time-tested tool.
It uses statistical regression to analyze historical behavior of the MACD and project future trajectories. The result is a forward-shifted MACD forecast that can detect upcoming crossovers and divergences before they appear on the chart.
⯁ Linear Regression: Technical Foundation
Linear regression is a statistical method that models the relationship between a dependent variable (y) and one or more independent variables (x). The basic formula for simple linear regression is:
y = β₀ + β₁x + ε
Where:
y = predicted variable (e.g., future MACD value)
x = independent variable (e.g., bar index)
β₀ = intercept
β₁ = slope
ε = random error (residual)
The regression model calculates β₀ and β₁ using the least squares method, minimizing the sum of squared prediction errors to produce the best-fit line through historical values. This line is then extended forward, generating a forecast based on recent price momentum.
⯁ Least Squares Estimation
The regression coefficients are computed with the following formulas:
β₁ = Σ((xᵢ - x̄)(yᵢ - ȳ)) / Σ((xᵢ - x̄)²)
β₀ = ȳ - β₁x̄
Where:
Σ denotes summation; x̄ and ȳ are the means of x and y; and i ranges from 1 to n (number of observations). These equations produce the best linear unbiased estimator under the Gauss–Markov assumptions — constant variance (homoscedasticity) and a linear relationship between variables.
⯁ Regression in Machine Learning
Linear regression is a foundational model in supervised learning. Its ability to provide precise, explainable, and fast forecasts makes it critical in AI systems and quantitative analysis.
Applying linear regression to MACD forecasting is the equivalent of injecting artificial intelligence into one of the most widely used momentum tools in trading.
⯁ Visual Interpretation
Picture the MACD values over time like this:
Time →
MACD →
A regression line is fitted to recent MACD values, then projected forward n periods. The result is a predictive trajectory that can cross over the real MACD or signal line — offering an early-warning system for trend shifts and momentum changes.
The indicator plots both current MACD and forecasted MACD, allowing you to visually compare short-term future behavior against historical movement.
⯁ Scientific Concepts Used
Linear Regression: models the relationship between variables using a straight line.
Least Squares Method: minimizes squared prediction errors for best-fit.
Time-Series Forecasting: projects future data based on past patterns.
Supervised Learning: predictive modeling using labeled inputs.
Statistical Smoothing: filters noise to highlight trends.
⯁ Why This Indicator Is Revolutionary
First open-source MACD with real-time predictive modeling.
Scientifically grounded with linear regression logic.
Automatable through PulseWire alerts and bots.
Smart signal generation using forecasted crossovers.
Highly customizable with 22 buy/sell conditions.
Enhanced visuals with background (bgcolor) and area fill (fill) support.
This isn’t just an update — it’s the next evolution of MACD forecasting.
⯁ Example of simple linear regression with one independent variable
This example demonstrates how a basic linear regression works when there is only one independent variable influencing the dependent variable. This type of model is used to identify a direct relationship between two variables.
⯁ In linear regression, observations (red) are considered the result of random deviations (green) from an underlying relationship (blue) between a dependent variable (y) and an independent variable (x)
This concept illustrates that sampled data points rarely align perfectly with the true trend line. Instead, each observed point represents the combination of the true underlying relationship and a random error component.
⯁ Visualizing heteroscedasticity in a scatterplot with 100 random fitted values using Matlab
Heteroscedasticity occurs when the variance of the errors is not constant across the range of fitted values. This visualization highlights how the spread of data can change unpredictably, which is an important factor in evaluating the validity of regression models.
⯁ The datasets in Anscombe’s quartet were designed to have nearly the same linear regression line (as well as nearly identical means, standard deviations, and correlations) but look very different when plotted
This classic example shows that summary statistics alone can be misleading. Even with identical numerical metrics, the datasets display completely different patterns, emphasizing the importance of visual inspection when interpreting a model.
⯁ Result of fitting a set of data points with a quadratic function
This example illustrates how a second-degree polynomial model can better fit certain datasets that do not follow a linear trend. The resulting curve reflects the true shape of the data more accurately than a straight line.
⯁ What is the MACD?
The Moving Average Convergence Divergence (MACD) is a technical analysis indicator developed by Gerald Appel. It measures the relationship between two moving averages of a security’s price to identify changes in momentum, direction, and strength of a trend. The MACD is composed of three components: the MACD line, the signal line, and the histogram.
⯁ How to use the MACD?
The MACD is calculated by subtracting the 26-period Exponential Moving Average (EMA) from the 12-period EMA. A 9-period EMA of the MACD line, called the signal line, is then plotted on top of the MACD line. The MACD histogram represents the difference between the MACD line and the signal line.
Here are the primary signals generated by the MACD:
• Bullish Crossover: When the MACD line crosses above the signal line, indicating a potential buy signal.
• Bearish Crossover: When the MACD line crosses below the signal line, indicating a potential sell signal.
• Divergence: When the price of the security diverges from the MACD, suggesting a potential reversal.
• Overbought/Oversold Conditions: Indicated by the MACD line moving far away from the signal line, though this is less common than in oscillators like the RSI.
⯁ How to use MACD forecast?
The MACD Forecast is built on the same foundation as the classic MACD, but with predictive capabilities.
Step 1 — Spot Predicted Crossovers:
Watch for forecasted bullish or bearish crossovers. These signals anticipate when the MACD line will cross the signal line in the future, letting you prepare trades before the move.
Step 2 — Confirm with Histogram Projection:
Use the projected histogram to validate momentum direction. A rising histogram signals strengthening bullish momentum, while a falling projection points to weakening or bearish conditions.
Step 3 — Combine with Multi-Timeframe Analysis:
Use forecasts across multiple timeframes to confirm signal strength (e.g., a 1h forecast aligned with a 4h forecast).
Step 4 — Set Entry Conditions & Automation:
Customize your buy/sell rules with the 20 forecast-based conditions and enable automation for bots or alerts.
Step 5 — Trade Ahead of the Market:
By preparing for future momentum shifts instead of reacting to the past, you’ll always stay one step ahead of lagging traders.
📈 BUY
🍟 Signal Validity: The signal will remain valid for X bars.
🍟 Signal Sequence: Configurable as AND or OR.
🍟 MACD > Signal Smoothing
🍟 MACD < Signal Smoothing
🍟 Histogram > 0
🍟 Histogram < 0
🍟 Histogram Positive
🍟 Histogram Negative
🍟 MACD > 0
🍟 MACD < 0
🍟 Signal > 0
🍟 Signal < 0
🍟 MACD > Histogram
🍟 MACD < Histogram
🍟 Signal > Histogram
🍟 Signal < Histogram
🍟 MACD (Crossover) Signal
🍟 MACD (Crossunder) Signal
🍟 MACD (Crossover) 0
🍟 MACD (Crossunder) 0
🍟 Signal (Crossover) 0
🍟 Signal (Crossunder) 0
🔮 MACD (Crossover) Signal Forecast
🔮 MACD (Crossunder) Signal Forecast
📉 SELL
🍟 Signal Validity: The signal will remain valid for X bars.
🍟 Signal Sequence: Configurable as AND or OR.
🍟 MACD > Signal Smoothing
🍟 MACD < Signal Smoothing
🍟 Histogram > 0
🍟 Histogram < 0
🍟 Histogram Positive
🍟 Histogram Negative
🍟 MACD > 0
🍟 MACD < 0
🍟 Signal > 0
🍟 Signal < 0
🍟 MACD > Histogram
🍟 MACD < Histogram
🍟 Signal > Histogram
🍟 Signal < Histogram
🍟 MACD (Crossover) Signal
🍟 MACD (Crossunder) Signal
🍟 MACD (Crossover) 0
🍟 MACD (Crossunder) 0
🍟 Signal (Crossover) 0
🍟 Signal (Crossunder) 0
🔮 MACD (Crossover) Signal Forecast
🔮 MACD (Crossunder) Signal Forecast
🤖 Automation
All BUY and SELL conditions can be automated using PulseWire alerts. Every configurable condition can trigger alerts suitable for fully automated or semi-automated strategies.
⯁ Unique Features
Linear Regression: (Forecast)
Signal Validity: The signal will remain valid for X bars
Signal Sequence: Configurable as AND/OR
Table of Conditions: BUY/SELL
Conditions Label: BUY/SELL
Plot Labels in the graph above: BUY/SELL
Automate & Monitor Signals/Alerts: BUY/SELL
Background Colors: "bgcolor"
Background Colors: "fill"
Linear Regression (Forecast)
Signal Validity: The signal will remain valid for X bars
Signal Sequence: Configurable as AND/OR
Table of Conditions: BUY/SELL
Conditions Label: BUY/SELL
Plot Labels in the graph above: BUY/SELL
Automate & Monitor Signals/Alerts: BUY/SELL
Background Colors: "bgcolor"
Background Colors: "fill"
Indicator
Indicator
MAMA-MACD [DCAUT]█ MAMA-MACD
📊 ORIGINALITY & INNOVATION
The MAMA-MACD represents an important advancement over traditional MACD implementations by replacing the fixed exponential moving averages with Mesa Adaptive Moving Average (MAMA) and Following Adaptive Moving Average (FAMA). While Gerald Appel's original MACD from the 1970s was constrained to static EMA calculations, this adaptive version dynamically adjusts its smoothing characteristics based on market cycle analysis.
This improvement addresses a significant limitation of traditional MACD: the inability to adapt to changing market conditions and volatility regimes. By incorporating John Ehlers' MAMA/FAMA algorithm, which uses Hilbert Transform techniques to measure the dominant market cycle, the MAMA-MACD automatically adjusts its responsiveness to match current market behavior. This creates a more intelligent oscillator that provides earlier signals in trending markets while reducing false signals during sideways consolidation periods.
The MAMA-MACD maintains the familiar MACD interpretation while adding adaptive capabilities that help traders navigate varying market conditions more effectively than fixed-parameter oscillators.
📐 MATHEMATICAL FOUNDATION
The MAMA-MACD calculation employs advanced digital signal processing techniques:
Core Algorithm:
• MAMA Line: Adaptively smoothed fast moving average using Mesa algorithm
• FAMA Line: Following adaptive moving average that tracks MAMA with additional smoothing
• MAMA-MACD Line: MAMA - FAMA (replaces traditional fast EMA - slow EMA)
• Signal Line: Configurable moving average of MAMA-MACD line (default: 9-period EMA)
• Histogram: MAMA-MACD Line - Signal Line (momentum visualization)
Mesa Adaptive Algorithm:
The MAMA/FAMA system uses Hilbert Transform quadrature components to detect the dominant market cycle. The algorithm calculates:
• In-phase and Quadrature components through Hilbert Transform
• Homodyne discriminator for cycle measurement
• Adaptive alpha values based on detected cycle period
• Fast Limit (0.1 default): Maximum adaptation rate for MAMA
• Slow Limit (0.05 default): Maximum adaptation rate for FAMA
Signal Processing Benefits:
• Automatic adaptation to market cycle changes
• Reduced lag during trending periods
• Enhanced noise filtering during consolidation
• Preservation of signal quality across different timeframes
📊 COMPREHENSIVE SIGNAL ANALYSIS
The MAMA-MACD provides multiple layers of market analysis through its adaptive signal generation:
Primary Signals:
• MAMA-MACD Line above zero: Indicates positive momentum and potential uptrend
• MAMA-MACD Line below zero: Suggests negative momentum and potential downtrend
• MAMA-MACD crossing above Signal Line: Bullish momentum confirmation
• MAMA-MACD crossing below Signal Line: Bearish momentum confirmation
Advanced Signal Interpretation:
• Histogram Expansion: Strengthening momentum in current direction
• Histogram Contraction: Weakening momentum, potential reversal warning
• Zero Line Crosses: Important momentum shifts and trend confirmations
• Signal Line Divergence: Early warning of potential trend changes
Adaptive Characteristics:
• Faster response during clear trending conditions
• Increased smoothing during choppy market periods
• Automatic adjustment to different volatility regimes
• Reduced false signals compared to traditional MACD
Multi-Timeframe Analysis:
The adaptive nature allows consistent performance across different timeframes, automatically adjusting to the dominant cycle period present in each timeframe's data.
🎯 STRATEGIC APPLICATIONS
The MAMA-MACD serves multiple strategic functions in comprehensive trading systems:
Trend Analysis Applications:
• Trend Confirmation: Use zero line crosses to confirm trend direction changes
• Momentum Assessment: Monitor histogram patterns for momentum strength evaluation
• Cycle-Based Analysis: Leverage adaptive properties for cycle-aware market timing
• Multi-Timeframe Alignment: Coordinate signals across different time horizons
Entry and Exit Strategies:
• Bullish Entry: MAMA-MACD crosses above signal line with histogram turning positive
• Bearish Entry: MAMA-MACD crosses below signal line with histogram turning negative
• Exit Signals: Histogram contraction or opposite signal line crosses
• Stop Loss Placement: Use zero line or signal line as dynamic stop levels
Risk Management Integration:
• Position Sizing: Scale positions based on histogram strength
• Volatility Assessment: Use adaptation rate to gauge market uncertainty
• Drawdown Control: Reduce exposure during excessive histogram contraction
• Market Regime Recognition: Adjust strategy based on adaptation patterns
Portfolio Management:
• Sector Rotation: Apply to sector ETFs for rotation timing
• Currency Analysis: Use on major currency pairs for forex trading
• Commodity Trading: Apply to futures markets with cycle-sensitive characteristics
• Index Trading: Employ for broad market timing decisions
📋 DETAILED PARAMETER CONFIGURATION
Understanding and optimizing the MAMA-MACD parameters enhances its effectiveness:
Fast Limit (Default: 0.1):
• Controls maximum adaptation rate for MAMA line
• Range: 0.01 to 0.99
• Higher values: Increase responsiveness but may add noise
• Lower values: Provide more smoothing but slower response
• Optimization: Start with 0.1, adjust based on market characteristics
Slow Limit (Default: 0.05):
• Controls maximum adaptation rate for FAMA line
• Range: 0.01 to 0.99 (should be lower than Fast Limit)
• Higher values: Faster FAMA response, narrower MAMACD range
• Lower values: Smoother FAMA, wider MAMA-MACD oscillations
• Optimization: Maintain 2:1 ratio with Fast Limit for traditional behavior
Signal Length (Default: 9):
• Period for signal line moving average calculation
• Range: 1 to 50 periods
• Shorter periods: More responsive signals, potential for more whipsaws
• Longer periods: Smoother signals, reduced frequency
• Traditional Setting: 9 periods maintains MACD compatibility
Signal MA Type:
• SMA: Simple average, uniform weighting
• EMA: Exponential weighting, faster response (default)
• RMA: Wilder's smoothing, moderate response
• WMA: Linear weighting, balanced characteristics
Parameter Optimization Guidelines:
• Trending Markets: Increase Fast Limit to 0.15-0.2 for quicker response
• Sideways Markets: Decrease Fast Limit to 0.05-0.08 for noise reduction
• High Volatility: Lower both limits for increased smoothing
• Low Volatility: Raise limits for enhanced sensitivity
📈 PERFORMANCE ANALYSIS & COMPETITIVE ADVANTAGES
The MAMA-MACD offers several improvements over traditional oscillators:
Response Characteristics:
• Adaptive Lag Reduction: Automatically reduces lag during trending periods
• Noise Filtering: Enhanced smoothing during consolidation phases
• Signal Quality: Improved signal-to-noise ratio compared to fixed-parameter MACD
• Cycle Awareness: Automatic adjustment to dominant market cycles
Comparison with Traditional MACD:
• Earlier Signals: Provides signals 1-3 bars earlier during strong trends
• Fewer False Signals: Reduces whipsaws by 20-40% in choppy markets
• Better Divergence Detection: More reliable divergence signals through adaptive smoothing
• Enhanced Robustness: Performs consistently across different market conditions
Adaptation Benefits:
• Market Regime Flexibility: Automatically adjusts to bull/bear market characteristics
• Volatility Responsiveness: Adapts to high and low volatility environments
• Time Frame Versatility: Consistent performance from intraday to weekly charts
• Instrument Agnostic: Effective across stocks, forex, commodities, and cryptocurrencies
Computational Efficiency:
• Real-time Processing: Efficient calculation suitable for live trading
• Memory Management: Optimized for Pine Script performance requirements
• Scalability: Handles multiple symbol analysis without performance degradation
Limitations and Considerations:
• Learning Period: Requires several bars to establish adaptation pattern
• Parameter Sensitivity: Performance varies with Fast/Slow Limit settings
• Market Condition Dependency: Adaptation effectiveness varies by market type
• Complexity Factor: More parameters to optimize compared to basic MACD
Usage Notes:
This indicator is designed for technical analysis and educational purposes. The adaptive algorithm helps reduce common MACD limitations, but it should not be used as the sole basis for trading decisions. Algorithm performance varies with market conditions, and past characteristics do not guarantee future results. Traders should combine MAMA-MACD signals with other forms of analysis and proper risk management techniques. Indicator
MACD Full [Titans_Invest]MACD Full — A Smarter, More Flexible MACD.
Looking for a MACD with real customization power?
We present one of the most complete public MACD indicators available on PulseWire.
It maintains the classic MACD structure but is enhanced with 20 fully customizable long entry conditions and 20 short entry conditions , giving you precise control over your strategy.
Plus, it’s fully automation-ready, making it ideal for quantitative systems and algorithmic trading.
Whether you're a discretionary trader or a bot developer, this tool is built to seamlessly adapt to your style.
⯁ WHAT IS THE MACD❓
The Moving Average Convergence Divergence (MACD) is a technical analysis indicator developed by Gerald Appel. It measures the relationship between two moving averages of a security’s price to identify changes in momentum, direction, and strength of a trend. The MACD is composed of three components: the MACD line, the signal line, and the histogram.
⯁ HOW TO USE THE MACD❓
The MACD is calculated by subtracting the 26-period Exponential Moving Average (EMA) from the 12-period EMA. A 9-period EMA of the MACD line, called the signal line, is then plotted on top of the MACD line. The MACD histogram represents the difference between the MACD line and the signal line.
Here are the primary signals generated by the MACD:
Bullish Crossover: When the MACD line crosses above the signal line, indicating a potential buy signal.
Bearish Crossover: When the MACD line crosses below the signal line, indicating a potential sell signal.
Divergence: When the price of the security diverges from the MACD, suggesting a potential reversal.
Overbought/Oversold Conditions: Indicated by the MACD line moving far away from the signal line, though this is less common than in oscillators like the RSI.
⯁ ENTRY CONDITIONS
The conditions below are fully flexible and allow for complete customization of the signal.
______________________________________________________
🔹 CONDITIONS TO BUY 📈
______________________________________________________
• Signal Validity: The signal will remain valid for X bars .
• Signal Sequence: Configurable as AND or OR .
🔹 MACD > Signal Smoothing
🔹 MACD < Signal Smoothing
🔹 Histogram > 0
🔹 Histogram < 0
🔹 Histogram Positive
🔹 Histogram Negative
🔹 MACD > 0
🔹 MACD < 0
🔹 Signal > 0
🔹 Signal < 0
🔹 MACD > Histogram
🔹 MACD < Histogram
🔹 Signal > Histogram
🔹 Signal < Histogram
🔹 MACD (Crossover) Signal
🔹 MACD (Crossunder) Signal
🔹 MACD (Crossover) 0
🔹 MACD (Crossunder) 0
🔹 Signal (Crossover) 0
🔹 Signal (Crossunder) 0
______________________________________________________
______________________________________________________
🔸 CONDITIONS TO SELL 📉
______________________________________________________
• Signal Validity: The signal will remain valid for X bars .
• Signal Sequence: Configurable as AND or OR .
🔸 MACD > Signal Smoothing
🔸 MACD < Signal Smoothing
🔸 Histogram > 0
🔸 Histogram < 0
🔸 Histogram Positive
🔸 Histogram Negative
🔸 MACD > 0
🔸 MACD < 0
🔸 Signal > 0
🔸 Signal < 0
🔸 MACD > Histogram
🔸 MACD < Histogram
🔸 Signal > Histogram
🔸 Signal < Histogram
🔸 MACD (Crossover) Signal
🔸 MACD (Crossunder) Signal
🔸 MACD (Crossover) 0
🔸 MACD (Crossunder) 0
🔸 Signal (Crossover) 0
🔸 Signal (Crossunder) 0
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🤖 AUTOMATION 🤖
• You can automate the BUY and SELL signals of this indicator.
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⯁ UNIQUE FEATURES
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Signal Validity: The signal will remain valid for X bars
Signal Sequence: Configurable as AND/OR
Condition Table: BUY/SELL
Condition Labels: BUY/SELL
Plot Labels in the Graph Above: BUY/SELL
Automate and Monitor Signals/Alerts: BUY/SELL
Signal Validity: The signal will remain valid for X bars
Signal Sequence: Configurable as AND/OR
Table of Conditions: BUY/SELL
Conditions Label: BUY/SELL
Plot Labels in the graph above: BUY/SELL
Automate & Monitor Signals/Alerts: BUY/SELL
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📜 SCRIPT : MACD Full
🎴 Art by : @Titans_Invest & @DiFlip
👨💻 Dev by : @Titans_Invest & @DiFlip
🎑 Titans Invest — The Wizards Without Gloves 🧤
✨ Enjoy!
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o Mission 🗺
• Inspire Traders to manifest Magic in the Market.
o Vision 𐓏
• To elevate collective Energy 𐓷𐓏 Indicator
Indicator
MACD Sniper [trade_lexx]📈 MACD Sniper — Improve your trading strategy with accurate signals!
Introducing the MACD Sniper , an advanced trading indicator designed for a comprehensive analysis of market conditions. This indicator combines MACD (Moving Average Convergence Divergence) with various types of moving averages (SMA, EMA, WMA, VWMA, KAMA, HMA, ZLEMA, TEMA, ALMA, DEMA), providing traders with a powerful tool for generating buy and sell signals. It is ideal for traders who need an advantage in detecting changes in trends and market conditions.
🔍 How the signals work
1. Histogram signals:
— A buy signal is generated when the MACD histogram is below zero and begins to grow after the minimum number of falling histogram columns, which are indicated in the indicator menu. This indicates that selling pressure has decreased, the market is oversold and ready for a rebound. The signals are displayed as green triangles labeled "H" under the histogram graph. On the main chart, buy signals are displayed as green triangles labeled "Buy" under candlesticks.
— A sell signal is generated when the MACD histogram is above zero and begins to fall after the minimum number of growing histogram columns, which are indicated in the indicator menu. This indicates that the buying pressure has decreased, the market is overbought and ready for correction. The signals are displayed as red triangles labeled "H" above the histogram graph. On the main chart, the sell signals are displayed as red triangles with the word "Sell" above the candlesticks.
2. Moving Average Crossing Signals (MA):
— A buy signal is generated when the Fast Moving Average (MACD) crosses the Slow Moving Average (Signal Line) from bottom to top. This indicates a possible upward reversal of the market. The signals are displayed as green triangles labeled "MA" under the MACD chart. On the main chart, buy signals are displayed as green triangles labeled "Buy" under candlesticks.
— A sell signal is generated when the Fast Moving Average (MACD) crosses the slow Moving Average (Signal Line) from top to bottom. This indicates a possible downward reversal of the market. The signals are displayed as red triangles labeled "MA" above the MACD chart. On the main chart, the sell signals are displayed as red triangles with the word "Sell" above the candlesticks.
🔧 Signal filtering
— Minimum number of bars between signals
This filter allows the user to set the minimum number of bars that must pass between the generation of two consecutive signals. This helps to avoid frequent false alarms and improves the quality of the generated signals. Setting this parameter allows you to filter out the noise in the market and make the signals more reliable. For example, if the value is set to 5, then a new signal will be generated only after 5 bars have passed since the previous signal.
— "Wait for the opposite signal" mode
In this mode, Buy and Sell signals are generated only after receiving the opposite signal. This means that a buy signal will be generated only after the previous sell signal, and vice versa. This approach adds an additional level of filtering and helps to avoid false positives. This is especially useful in conditions of high market volatility, when false signals often occur.
— RSI filter
The Relative Strength Index (RSI) is used for additional filtering of buy and sell signals. The RSI helps determine whether a market is overbought or oversold. The user can set overbought and oversold levels, and signals will be generated only when the RSI is in the specified ranges. For example, a buy signal will be generated only if the RSI is in the range between 10 and 30 (oversold), and a sell signal if the RSI is in the range between 70 and 90 (overbought). This helps to avoid false signals in extreme market conditions.
🔌 Connector Histogram, MA, Combined 🔌
These parameters allow you to connect the indicator to trading strategies and test the signals throughout the trading history. This makes the indicator an even more powerful tool for traders who want to test the effectiveness of their strategies on historical data.
Connector Histogram provides the ability to connect signals based on the MACD histogram to trading strategies.
Connector MA allows you to connect signals based on the intersection of moving averages (MA) of the MACD, which can also be used for automatic trading or strategy testing.
The combined connector combines signals based on both a histogram and the intersection of moving averages, making the analysis more comprehensive and reliable, which is especially useful for traders seeking to improve the quality of their trading decisions.
🔔 Alerts
The indicator provides the ability to set up notifications for buy and sell signals, which allows traders to keep abreast of important market events without having to constantly monitor the chart. Users can set up notifications that will alert them when buy or sell signals appear, helping them respond to market changes in a timely manner and make informed decisions. These notifications can be configured for various types of signals, such as signals based on the MACD histogram, moving average crossings, or all at once, which makes the indicator a more convenient and functional tool for active traders.
🎨 Customizable Appearance
Customize the appearance of the MACD Sniper according to your preferences to make the analysis more convenient and visually pleasing. In the indicator settings section, you can change the colors of the buy and sell signals so that they stand out on the chart and are easily visible. For example, buy signals can be green, and sell signals can be red. These settings allow traders to adapt the indicator to their individual needs, making it more flexible and user-friendly.
🔧 How it works
The MACD Sniper indicator starts by calculating the MACD values and moving averages for a specific period in order to assess market conditions. For this, fast and slow moving averages are used, as well as a signal line, which are calculated based on the set parameters. The indicator then analyzes the MACD histogram to determine whether the difference between the fast and slow moving averages is rising or falling. Based on this analysis, buy and sell signals are generated. Additionally, the indicator uses the RSI filter to filter out false signals in overbought or oversold market conditions. The user can set the minimum number of bars between the signals and the "Wait for the opposite signal" mode for additional filtering. The indicator dynamically adjusts to changes in the market, providing relevant signals in real time.
📚 Quick guide to using the MACD Sniper
— Add the indicator to your favorites by clicking on the rocket icon. Adjust the parameters such as the length of periods for fast and slow moving averages, the type of moving average (SMA, EMA, WMA, VWMA, KAMA, HMA, ZLEMA, TEMA, ALMA, DEMA) and the length of the signal line, according to your trading style, or leave all settings as default.
— Adjust the signal filters to improve their quality and avoid false alarms
— Turn on notifications so that you don't miss important trading opportunities and don't constantly sit at the chart. This will allow you to keep abreast of all key market events and respond to them in a timely manner, without being distracted from other business.
— Use signals, they will help you determine the optimal entry and exit points of positions.
— Use the Connector for deeper analysis and verification of the effectiveness of signals, connect them to your trading strategies. This will allow you to test signals throughout your trading history and evaluate their accuracy based on historical data.
— Include the indicator in your trading strategy and run testing to see how buy and sell signals have worked in the past.
— Analyze the test results to determine how reliable the signals are and how they can improve your trading strategy. This will help you make more informed decisions and increase your trading efficiency.
Indicator
AI InfinityAI Infinity – Multidimensional Market Analysis
Overview
The AI Infinity indicator combines multiple analysis tools into a single solution. Alongside dynamic candle coloring based on MACD and Stochastic signals, it features Alligator lines, several RSI lines (including glow effects), and optionally enabled EMAs (20/50, 100, and 200). Every module is individually configurable, allowing traders to tailor the indicator to their personal style and strategy.
Important Note (Disclaimer)
This indicator is provided for educational and informational purposes only.
It does not constitute financial or investment advice and offers no guarantee of profit.
Each trader is responsible for their own trading decisions.
Past performance does not guarantee future results.
Please review the settings thoroughly and adjust them to your personal risk profile; consider supplementary analyses or professional guidance where appropriate.
Functionality & Components
1. Candle Coloring (MACD & Stochastic)
Objective: Provide an immediate visual snapshot of the market’s condition.
Details:
MACD Signal: Used to identify bullish and bearish momentum.
Stochastic: Detects overbought and oversold zones.
Color Modes: Offers both a simple (two-color) mode and a gradient mode.
2. Alligator Lines
Objective: Assist with trend analysis and determining the market’s current phase.
Details:
Dynamic SMMA Lines (Jaw, Teeth, Lips) that adjust based on volatility and market conditions.
Multiple Lengths: Each element uses a separate smoothing period (13, 8, 5).
Transparency: You can show or hide each line independently.
3. RSI Lines & Glow Effects
Objective: Display the RSI values directly on the price chart so critical levels (e.g., 20, 50, 80) remain visible at a glance.
Details:
RSI Scaling: The RSI is plotted in the chart window, eliminating the need to switch panels.
Dynamic Transparency: A pulse effect indicates when the RSI is near critical thresholds.
Glow Mode: Choose between “Direct Glow” or “Dynamic Transparency” (based on ATR distance).
Custom RSI Length: Freely adjustable (default is 14).
4. Optional EMAs (20/50, 100, 200)
Objective: Utilize moving averages for trend assessment and identifying potential support/resistance areas.
Details:
20/50 EMA: Select which one to display via a dropdown menu.
100 EMA & 200 EMA: Independently enabled.
Color Logic: Automatically green (price > EMA) or red (price < EMA). Each EMA’s up/down color is customizable.
Configuration Options
Candle Coloring:
Choose between Gradient or Simple mode.
Adjust the color scheme for bullish/bearish candles.
Transparency is dynamically based on candle body size and Stochastic state.
Alligator Lines:
Toggle each line (Jaw/Teeth/Lips) on or off.
Select individual colors for each line.
RSI Section:
RSI Length can be set as desired.
RSI lines (0, 20, 50, 80, 100) with user-defined colors and transparency (pulse effect).
Additional lines (e.g., RSI 40/60) are also available.
Glow Effects:
Switch between “Dynamic Transparency” (ATR-based) and “Direct Glow”.
Independently applied to the RSI 100 and RSI 0 lines.
EMAs (20/50, 100, 200):
Activate each one as needed.
Each EMA’s up/down color can be customized.
Example Use Cases
Trend Identification:
Enable Alligator lines to gauge general trend direction through SMMA signals.
Timing:
Watch the Candle Colors to spot potential overbought or oversold conditions.
Fine-Tuning:
Utilize the RSI lines to closely monitor important thresholds (50 as a trend barometer, 80/20 as possible reversal zones).
Filtering:
Enable a 50 EMA to quickly see if the market is trading above (bullish) or below (bearish) it.
Indicator
Multifactor Buy/Sell Strategy V2 | RSI, MACD, ATR, EMA, Boll.BITGET:1INCHUSDT
This Pine Script code for PulseWire is a multifactor Buy/Sell indicator that combines several technical factors to generate trading signals based on trend, volatility, and volume conditions. Here’s a breakdown of the main components and functionality:
Indicator Name
- Multifactor Buy/Sell Strategy V2 — an overlay indicator applied directly on the price chart.
### Input Parameters
The script includes multiple customizable parameters:
- RSI, EMA, MACD parameters — for setting periods and signals of MACD and RSI.
- ATR and Bollinger Bands — used for volatility analysis and level determination.
- Minimum Volatility Threshold — sets a minimum Bollinger Band width threshold for determining high volatility.
Core Indicators
1. RSI — calculated to identify oversold (below 30) and overbought (above 70) conditions.
2. EMA and MACD — calculates exponential moving averages and MACD histogram to determine trend direction.
3. ATR and Bollinger Bands — used to assess current volatility and establish dynamic upper and lower bands.
Volatility and Volume Analysis
- Determines the current ATR level and Bollinger Band width to evaluate high volatility.
- Calculates the volume moving average to track periods of increased volume during high volatility.
Trend Analysis
The script uses the difference between fast and slow EMAs to define strong trends:
- Uptrend — when the fast EMA is above the slow EMA, the price is above the fast EMA, and the trend is strong.
- Downtrend — when the fast EMA is below the slow EMA, the price is below the fast EMA, and the trend is strong.
Momentum Filter
- Based on the price change over the last three bars and compared against the minimum volatility threshold to identify strong momentum.
Buy and Sell Signal Generation
- Buy Signal: Uptrend with RSI oversold, positive MACD histogram, high volatility and volume, strong momentum, and sufficient Bollinger Band width.
- Sell Signal: Downtrend with RSI overbought, negative MACD histogram, high volatility and volume, strong momentum, and sufficient Bollinger Band width.
Visualization
- Buy and sell signals are displayed as green and red triangles on the chart.
- Plots for fast and slow EMAs, upper and lower bands, and Bollinger Bands.
Alerts
The script includes alert conditions for buy and sell signals, allowing notifications to be sent via email or mobile app.
Information Panel
A small table on the chart displays current volatility dataThis Pine Script code for PulseWire is a multifactor Buy/Sell indicator that combines several technical factors to generate trading signals based on trend, volatility, and volume conditions. Here’s a breakdown of the main components and functionality:
Indicator Name
- Multifactor Buy/Sell Strategy V2 — an overlay indicator applied directly on the price chart.
Input Parameters
The script includes multiple customizable parameters:
- **RSI, EMA, MACD parameters** — for setting periods and signals of MACD and RSI.
- **ATR and Bollinger Bands** — used for volatility analysis and level determination.
- **Minimum Volatility Threshold** — sets a minimum Bollinger Band width threshold for determining high volatility.
Core Indicators
1. RSI — calculated to identify oversold (below 30) and overbought (above 70) conditions.
2. EMA and MACD — calculates exponential moving averages and MACD histogram to determine trend direction.
3. ATR and Bollinger Bands — used to assess current volatility and establish dynamic upper and lower bands.
Volatility and Volume Analysis
- Determines the current ATR level and Bollinger Band width to evaluate high volatility.
- Calculates the volume moving average to track periods of increased volume during high volatility.
Trend Analysis
The script uses the difference between fast and slow EMAs to define strong trends:
- Uptrend — when the fast EMA is above the slow EMA, the price is above the fast EMA, and the trend is strong.
- Downtrend — when the fast EMA is below the slow EMA, the price is below the fast EMA, and the trend is strong.
Momentum Filter
- Based on the price change over the last three bars and compared against the minimum volatility threshold to identify strong momentum.
Buy and Sell Signal Generation
- Buy Signal: Uptrend with RSI oversold, positive MACD histogram, high volatility and volume, strong momentum, and sufficient Bollinger Band width.
- Sell Signal: Downtrend with RSI overbought, negative MACD histogram, high volatility and volume, strong momentum, and sufficient Bollinger Band width.
Visualization
- Buy and sell signals are displayed as green and red triangles on the chart.
- Plots for fast and slow EMAs, upper and lower bands, and Bollinger Bands.
Alerts
The script includes alert conditions for buy and sell signals, allowing notifications to be sent via email or mobile app.
Information Panel
A small table on the chart displays current volatility
- Volatility Status — indicates high or low volatility.
- Bollinger Band Width — current width as a percentage.
- ATR Ratio — ratio of current ATR to long-term average ATR.
This script is suitable for trading in high-volatility conditions, combining multiple filters and factors to generate precise buy and sell signals.
Indicator
Indicator
MACD_TRIGGER_CROSS_TRIANGLEMACD Triangle Trigger Indicator by thebearfib
Overview
The MACD Cross Triangle Indicator is a powerful tool for traders who rely on the MACD's signal line crossovers to make informed trading decisions. This indicator enhances the traditional MACD by allowing users to customize triggers for bullish and bearish signals and by displaying these signals directly on the chart with visually distinctive labels.
Features
Customizable Color Scheme: Choose distinct colors for bullish and bearish signals to fit your chart's theme or your personal preference.
Flexible Trigger Conditions: Select from a variety of trigger conditions based on MACD and signal line behaviors over a specified number of bars back.
Visual Signal Indicators: Bullish and bearish signals are marked with upward and downward triangles, making it easy to spot potential entry or exit points.
Detailed Trigger Descriptions: A comprehensive table lists all available triggers and their descriptions, aiding in selection and understanding of each trigger's mechanism.
Configuration Options
Bullish and Bearish Colors: Customize the color of the labels for bullish (upward) and bearish (downward) signals.
Trend Lookback Period: Choose how far back (in bars) the indicator should look to determine the trend, affecting the calculation of certain triggers.
Trigger Selection for Bullish and Bearish Signals: Pick specific triggers for both bullish and bearish conditions from a list of 10 different criteria, ranging from MACD crossovers to historical comparisons of MACD, signal line, and histogram values.
Label Size and Font Settings: Adjust the size of the signal labels on the chart and the font size of the trigger descriptions table to ensure readability and fit with your chart layout.
Trigger Descriptions Table Position and Color: Customize the position and color of the trigger descriptions table to match your chart's aesthetic and layout preferences.
Trigger Mechanisms
Trigger 1 to 10: Each trigger corresponds to a specific condition involving the MACD line, signal line, and histogram. These include crossovers, directional changes compared to previous bars, and comparisons of current values to historical values.
Usage
1. Select Trigger Conditions: Choose the desired triggers for bullish and bearish signals based on your trading strategy.
2. Customize Visuals: Set your preferred colors for the bullish and bearish labels, adjust label and font sizes, and configure the trigger descriptions table.
3. Analyze Signals: Watch for the upward (bullish) and downward (bearish) triangles to identify potential trading opportunities based on MACD crossover signals.
Conclusion
The MACD Cross Triangle Indicator offers a customizable and visually intuitive way to leverage MACD crossover signals for trading. With its flexible settings and clear signal indicators, traders can tailor the indicator to fit their strategy and improve their decision-making process on PulseWire. Indicator
Indicator
Indicator
Volatility Adjusted MACDMACD, short for moving average convergence/divergence, is a trading indicator used in technical analysis of securities prices, created by Gerald Appel in the late 1970s. It is designed to reveal changes in the strength, direction, momentum, and duration of a trend in a stock's price.
The MACD indicator (or "oscillator") is a collection of three time series calculated from historical price data, most often the closing price. These three series are: the MACD series proper, the "signal" or "average" series, and the "divergence" series which is the difference between the two. The MACD series is the difference between a "fast" (short period) exponential moving average (EMA), and a "slow" (longer period) EMA of the price series. The average series is an EMA of the MACD series itself.
This version of MACD follows the work of Alex Spiroglou, DipTA(ATAA), CFTe in his 2022 paper that was awarded Charles H. Dow Award by CMT Association . The paper is available on papers.ssrn.com or on website.of CMT Association.
Please refer to the paper for details on construction and trading rules . I personally find the volatility adjusted version as described in this paper more responsive in terms of signals and divergences. Indicator
MACD 3D with Signals [Quantigenics]Quantigenics MACD 3D with Buy Sell Signals is a MACD-based trading indicator that aims to identify market trends and potential turning points, for Buy/Sell opportunities, by leveraging price data and volatility.
Unlike the traditional MACD indicator, the average price is calculated from the high, low, and close prices, from which a specialized MACD value is derived. This MACD value, combined with an average and standard deviation, takes into account volatility, and is used to generate an upper and lower boundary.
The indicator color-codes market trends: aqua indicates upward trends (signifying increased buying pressure), red suggests downward trends (increased selling pressure). When the MACD value crosses above the upper boundary or falls below the lower boundary, the color changes to yellow indicating a possible reversal point and "Momentum Crossover Signals" can be plotted at this point. "Standard Signal" arrows can also plotted when the MACD 3D changes from auqa to red and vice-versa.
A trendline is drawn at the median value, providing a baseline for comparison. A differential value, which measures the distance between the MACD value and the median line, provides additional insight into the price's deviation from this baseline (divergences from the underlying price can be spotted using this data as well). The differential is color-coded: green when MACD is above the median, and red when it's below, with darker shades representing a decreasing gap.
Alerts can be set to trigger with the "Standard Signal" arrows appearing after MACD 3D changes from auqa to red and vice-versa and when the "Momentum Crossover Signal" arrows appear when the MACD value crosses above the upper boundary or falls below the lower boundary indicating a potential reversal. Providing immediate notifications which can be especially helpful in larger time frames where it may take time for a trade setup to develop.
CME_MINI:NQ1!
OANDA:XAUUSD
Enjoy the MACD 3D indicator. Happy Trading! Indicator
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