BB/KC Squeeze Channels (v6)Technical Specification for the BB/KC Squeeze Volatility Indicator in Algorithmic Cryptocurrency Trading
I. Theoretical Foundations of Volatility Dynamics
The "Contraction-Expansion" Principle (Volatility Contraction/Expansion)
The fundamental analysis of market volatility dynamics relies on the principle popularized by John Bollinger: periods of low volatility are inevitably followed by periods of high volatility. This phenomenon, known as the cyclical nature of volatility, is the cornerstone of trading strategies based on range breakouts (Breakout Strategy). In the context of technical analysis, volatility contraction manifests as a consolidation phase where the trading range narrows, preceding a strong, directional price impulse.
The essence of volatility contraction lies in a phase of market equilibrium that is inherently unstable. Most often, this reflects the covert activities of large market participants who are either accumulating or distributing a significant volume of the asset. These actions occur within a narrow price corridor to avoid sharp price movements until the entire position is acquired. As a result, activity decreases, the range narrows, and the market accumulates "energy" for the subsequent large-scale expansion. For the cryptocurrency market, characterized by high impulsivity and a tendency toward sharp trending moves, accurately identifying the deep contraction phase becomes a powerful algorithmic predictor.
Identifying Prerequisites: Distinguishing Pre-Breakout Contraction
To build a reliable indicator, it is crucial to distinguish a true pre-breakout squeeze from other types of volatility reduction that do not lead to a strong impulse. Specifically, volatility, measured by the Average True Range (ATR), will always decline after the completion of a strong vertical movement, as the market enters a pullback or deceleration phase. Such a decline is post-impulse and does not necessarily signal an imminent breakout.
It is necessary to find signs of abnormally low volatility that occurs precisely in the consolidation phase. The optimal time to look for a Squeeze signal is the formation of a distinct sideways channel. In this phase, the middle line of the channel indicator (e.g., EMA or SMA) should be relatively horizontal. This confirms that the market is currently in a ranging state (absence of a strong current trend), not in a deceleration phase after a trend. Therefore, the Squeeze indicator algorithm must include a check for confirmed sideways movement (e.g., through analyzing the slope of the middle line or its statistical deviation from the horizontal over the last X periods). Only abnormally low volatility during a range can be classified as a high-confidence pre-breakout contraction.
II. Instrument Selection: Justification for the Composite BB/KC Squeeze Approach
For effective algorithmic determination of the extreme contraction phase, it is necessary to use an indicator that combines the advantages of the two most reliable methods for measuring volatility: Bollinger Bands and Keltner Channels.
Comparative Analysis of Volatility Indicators
| Indicator | Base Metric | Volatility Response | Primary Role in Squeeze |
|---|---|---|---|
| Bollinger Bands (BB) | Standard Deviation (SD) | Fast, Highly Sensitive | Contraction sensor, Early breakout signal |
| Keltner Channels (KC) | Average True Range (ATR) | Smooth, Noise Filtering | Defines stable range, Filters false signals |
Bollinger Bands (BB)
Bollinger Bands are based on the Standard Deviation (SD) of the price from a moving average. This statistical metric makes BB highly sensitive, as they quickly react to sudden changes in volatility. Due to this sensitivity, BB are ideal for early registration of a contraction and for generating the breakout signal. However, their high sensitivity is also a drawback, as it can lead to false signals and premature expansion during market noise.
Keltner Channels (KC)
Keltner Channels, in the modern version developed by Linda Raschke, use the Average True Range (ATR) to calculate the channel width. ATR represents the averaged true range of fluctuations, which provides a smoother and more stable measure of volatility. KC react to market changes slower than BB, but their smoothness allows for better filtering of false signals and determination of the true direction of movement. Unlike fixed-width price channels or percentage envelopes, which perform poorly in dynamic environments, BB and KC automatically adapt to market conditions.
The Squeeze Mechanism: Synergy of Instruments
The BB/KC Squeeze indicator uses the synergy of BB and KC to achieve maximum accuracy in identifying the accumulation phase.
The technical Squeeze condition (Squeeze ON) is defined when the fast and statistically-oriented Bollinger Bands (BB) are inside the wider and smoother Keltner Channels (KC). This state represents quantitative confirmation of extremely low volatility.
In standard settings, BB use a multiplier of 2.0 for Standard Deviation (SD), and KC use a multiplier of 1.5 for ATR. For the statistical width of BB (based on price deviation from the average) to narrow inside the width of KC (based on the averaged range), the current statistical deviation of the price must fall to abnormally low values relative to the historical average range of fluctuations. This is not just low volatility, but its extreme contraction, indicating maximum accumulation of potential energy before an impulse.
III. Quantitative Analysis: How Much, Why, and How Volatility Contracts
How Much: Mathematical Definition of the Degree of Contraction
The degree of volatility contraction before a breakout is measured through a strict mathematical condition that ensures the current volatility is significantly below its averaged historical value.
The Squeeze Condition (Squeeze ON) requires both of the following mathematical formulas to be true :
To understand how much the movement should contract, we must consider the channel width formulas:
* Bollinger Bands Width (\text{BB}_{\text{Width}}):
\text{KC}_{\text{Width}} = 2 \times (\text{ATR} \times 1.5) = 3.0 \times \text{ATR}$$
The Squeeze ON state means that \text{BB}_{\text{Width}} < \text{KC}_{\text{Width}}. This condition is equivalent to \text{SD} \times 4.0 < \text{ATR} \times 3.0. As a result, the current Standard Deviation (SD) must fall below 75% of the Average True Range (ATR) for the contraction to be registered. This requirement for SD to decrease to a level significantly below ATR is the criterion for identifying the deep market calm that serves as the energy base for the subsequent directional movement.
Why and How: Qualitative Signs
Volatility decreases because large market participants are slowly and covertly accumulating positions. They keep the price within a narrow range to fully acquire the necessary volume before allowing the price to impulsively exit consolidation. This creates a sideways movement phase, minimizing risks for the trader and enabling timely tracking of a bullish or bearish breakout.
To enhance the algorithm's reliability and prevent entry into false ranges, the following qualitative signs accompanying a true squeeze must be considered:
* Squeeze Duration: The longer the price remains in the Squeeze ON state, the more energy is accumulated. Experience suggests a minimum duration of 4–8 periods. Extended contraction periods (over 10–12 bars) often precede the strongest impulsive movements in the crypto market.
* Price Position: During the contraction phase, the price should remain close to the middle line (EMA/SMA). This confirms that the market is in equilibrium, and accumulation is occurring around the "fair" price of the current range.
* Momentum Context: The volatility indicator (BB/KC) determines when a move will happen, but not its direction. To predict the direction (prerequisite), a momentum component must be used (e.g., a histogram, as in the TTM Squeeze variant ). The appearance of positive momentum during the contraction, even without price movement, signals potential bullish strength, increasing the likelihood of an upward breakout.
Squeeze State Logic Table
| State | Mathematical Condition (BB vs KC) | Market Interpretation |
|---|---|---|
| Squeeze ON | (\text{BB}_{\text{Upper}} < \text{KC}_{\text{Upper}}) AND (\text{BB}_{\text{Lower}} > \text{KC}_{\text{Lower}}) | Extreme volatility contraction, accumulation phase, breakout pending. |
| Squeeze OFF | \text{BB}_{\text{Upper}} \ge \text{KC}_{\text{Upper}} OR \text{BB}_{\text{Lower}} \le \text{KC}_{\text{Lower}} | Normal volatility, trending movement, or unstable range. |
IV. Technical Specification: Step-by-Step Algorithm for the Squeeze Indicator (BB/KC)
This algorithm represents the sequence of steps required to code the indicator, which captures the contraction state and generates breakout signals.
1. Initialization and Calculation of Basic Values
* Define Period N: Determine the period N (recommended value N=20) for calculating the moving averages, ATR, and Standard Deviation (SD).
* Calculate True Range (TR): For each bar, calculate \text{TR} as the maximum value of three metrics: (High – Low), \text{Abs}(\text{High} - \text{Close}_{\text{prev}}), \text{Abs}(\text{Low} - \text{Close}_{\text{prev}}).
2. Calculation of Keltner Channel (KC) Components
* Calculate KC Middle Line (EMA): Calculate the Exponential Moving Average (EMA) of the closing price (\text{Close}) over period N.
* Calculate ATR: Calculate the Average True Range (ATR) as the moving average of \text{TR} over period N.
* Calculate KC Boundaries: Calculate the Upper and Lower KC lines, using the ATR multiplier Y (recommended Y=1.5 ):
* * 3. Calculation of Bollinger Band (BB) Components
* Calculate BB Middle Line (SMA): Calculate the Simple Moving Average (SMA) of the closing price (\text{Close}) over period N.
* Calculate SD: Calculate the Standard Deviation (SD) of the closing price over period N.
* Calculate BB Boundaries: Calculate the Upper and Lower BB, using the SD multiplier X (recommended X=2.0 ):
* * 4. Algorithm for Determining the "Squeeze" State
* Check Squeeze ON Condition: For the current bar, check if both conditions are met: \text{BB}_{\text{Upper}} < \text{KC}_{\text{Upper}} AND \text{BB}_{\text{Lower}} > \text{KC}_{\text{Lower}}.
* Assign State: IF both conditions in step 9 are true, THEN assign the variable \text{SqueezeState} the value \text{ON} (e.g., 1). ELSE assign the value \text{OFF} (e.g., 0).
5. Algorithm for Generating Breakout Signals
* Identify Trigger: Check if \text{SqueezeState} has changed from \text{ON} to \text{OFF} on the current bar. This signifies that volatility has expanded after the contraction period.
* Bullish Breakout Signal: IF \text{SqueezeState}_{\text{prev}} = \text{ON} AND \text{SqueezeState}_{\text{current}} = \text{OFF}, AND the closing price (\text{Close}) of the current bar is above \text{BB}_{\text{Upper}}, THEN generate a BUY (Breakout Long) signal.
* Bearish Breakout Signal: IF \text{SqueezeState}_{\text{prev}} = \tex (start_span) (end_span)t{ON} AND \text{SqueezeState}_{\text{current}} = \text{OFF}, AND the closing price (\text{Close}) of the current bar is below \text{BB}_{\text{Lower}}, THEN generate a SELL (Breakout Short) signal.
* Additional Momentum Filtering: To increase reliability, the breakout signal should be valid only IF the breakout occurs in the direction confirmed by a momentum indicator (e.g., if Momentum > 0 for a Bullish breakout, and Momentum < 0 for a Bearish breakout).
The Role of Momentum in the Algorithm
A key addition to the volatility indicator is the momentum component. Defining the Squeeze ON/OFF state helps understand the potential for movement, but not its direction. The momentum indicator (often implemented as a histogram, as in TTM Squeeze ) measures whether accumulation of buying or selling pressure occurs during the contraction phase. Therefore, the indicator must include a sub-component that measures this pressure. Using momentum in conjunction with the BB breakout ensures that entry occurs not just after volatility expansion, but after expansion in a confirmed direction, significantly reducing the number of false breakouts.
V. Parameters, Optimization, and Nuances for the Cryptocurrency Market
Adapting Standard Settings (20, 2.0, 1.5)
The standard parameters N=20, X_{\text{BB}}=2.0, and Y_{\text{KC}}=1.5 are designed for stock markets and provide a reliable starting point. However, the high volatility and dynamics of the cryptocurrency market require fine-tuning to optimize performance.
1. Optimization of Period N
Reducing the period N (e.g., to 18 or 14) on lower timeframes (1-hour and below) increases the indicator's sensitivity to local, fast contractions, which is useful for scalping. However, this may also generate more signals, including false ones. For medium-term trading strategies (4h, Daily), a period of N=20 or N=21 provides an optimal balance between sensitivity and noise filtering.
2. Optimization of Multiplier Y_{\text{KC}}
The Keltner Channel multiplier (Y) defaults to 1.5. KC are smoother and more stable due to the use of ATR. If backtesting shows the indicator generates too many false Squeeze ON signals, it may indicate that the KC channel is too narrow. In this case, a slight increase in multiplier Y (e.g., to 1.6 or 1.7) widens the KC. This requires an even more extreme drop in Standard Deviation for the BB to narrow inside the KC, thereby increasing the strictness and reliability of the Squeeze ON signal.
Importance of Timeframe Selection
While some indicators like KC and BB show higher effectiveness in trending conditions for trading off channel boundaries , the Squeeze Play strategy is fundamentally different. It deliberately seeks a range (volatility contraction) with the goal of catching the start of a new strong trend.
In the cryptocurrency market, false breakouts and market noise (chop) can be particularly intense on low timeframes. Therefore, for the Squeeze strategy, it is recommended to use timeframes where consolidation is cleanest: 4-hour, Daily, or Weekly charts for major crypto pairs like BTC/USD or ETH/USD. On lower timeframes, multi-timeframe confirmation must be implemented, for example, using a trend filter from a higher timeframe.
VI. Strategic Application of Squeeze Play and Filtering
Using Momentum for Direction Determination
As noted, the volatility indicator (BB/KC) is not a directional indicator. The squeeze function (Squeeze ON) only identifies a high probability of a strong movement. Therefore, successful trading requires the integration of Momentum.
The breakout should be used as a trigger, but the direction must be confirmed by Momentum. For example, a BUY signal should only be generated if two conditions are met:
* Exit from the Squeeze ON state and the closing price breaking above the upper BB (\text{Close} > \text{BB}_{\text{Upper}}).
* The momentum indicator confirms upward pressure (Momentum value is positive).
This approach prevents entries into false breakouts where volatility expands but not in the direction of the accumulated market pressure.
Risk and Position Management
Since the Keltner Channel is based on ATR, which is a dynamic measure of volatility , ATR should be used for setting the Stop-Loss (SL) in the algorithmic strategy.
* Stop-Loss (SL) Setting: It is recommended to set the SL at a level determined by 1 \times \text{ATR} below the middle line (EMA/SMA) or beyond the KC boundary opposite the breakout. Using ATR ensures that the SL dynamically adapts to the current volatility, avoiding overly tight stops during periods of normal range.
* Take-Profit (TP) Setting: Since the goal of Squeeze Play is to catch a strong directional movement, the take-profit can be set based on a fixed Risk/Reward ratio (e.g., 2:1 or 3:1) or based on the price exiting the KC boundaries. Breaking the KC often indicates an extreme price move and can serve as a point for partial or full profit taking.
Filtering Against False Signals in a Range
The main drawback of breakout trading is the high percentage of false signals in wide but non-directional ranges. Using the composite BB/KC Squeeze indicator effectively addresses this problem.
KC, being based on smoothed ATR, is less susceptible to short-term volatility spikes than BB. The Squeeze filter requires the sensitive BB to narrow inside the smoothed KC. This ensures that we enter only those breakouts that were preceded by a prolonged and abnormally low volatility phase. The breakout must be confirmed by the price breaking the BB after the Squeeze ON state ends, signaling a sustained volatility expansion rather than a brief price spike.
VII. Conclusion
The analysis confirms that the user's observation about the relationship between volatility contraction and subsequent strong movements is a fundamentally sound principle, the best implementation of which in the cryptocurrency market is achieved using the composite BB/KC Squeeze indicator.
This indicator provides a precise quantitative definition of "how much" volatility must contract (SD must fall below 75% of ATR) and includes the necessary qualitative prerequisites ("why and how" — consolidation, confirmed by momentum). The presented step-by-step algorithm provides the technical foundation for coding a highly effective tool that identifies accumulation phases and generates breakout signals, adapted to the dynamics of the crypto market. The inclusion of momentum-based filtering and proper risk management tied to ATR are key factors for transitioning from a pure indicator to a profitable trading strategy.
Техническая Спецификация Индикатора Волатильности BB/KC Squeeze для Алгоритмической Торговли Криптовалютами
I. Теоретические Основы Динамики Волатильности
Принцип "Сжатие-Расширение" (Volatility Contraction/Expansion)
Фундаментальный анализ динамики рыночной волатильности опирается на принцип, популяризированный Джоном Боллинджером: периоды низкой волатильности неизбежно сменяются периодами высокой волатильности. Это явление, известное как цикличность волатильности, является краеугольным камнем торговых стратегий, основанных на пробое диапазона (Breakout Strategy). В контексте технического анализа сжатие волатильности проявляется как фаза консолидации, в которой торговый диапазон сужается, предшествуя сильному, направленному ценовому импульсу.
Смысл контракции волатильности заключается в фазе рыночного равновесия, которое, однако, является неустойчивым. Чаще всего это отражает скрытую деятельность крупных участников, которые либо накапливают (аккумуляция), либо распределяют (дистрибуция) значительный объем актива. Эти действия происходят в узком ценовом коридоре, чтобы избежать резкого движения цены, пока позиция не будет полностью набрана. В результате активность падает, диапазон сужается, и рынок накапливает «энергию» для последующего масштабного расширения. Для криптовалютного рынка, который характеризуется высокой импульсивностью и склонностью к резким трендовым движениям, точная идентификация фазы глубокого сжатия становится мощным алгоритмическим предиктором.
Идентификация Предпосылок: Отличие Пред-пробойного Сжатия
Для построения надежного индикатора критически важно уметь отличать истинное пред-пробойное сжатие от других типов снижения волатильности, которые не ведут к сильному импульсу. В частности, волатильность, измеряемая, например, индикатором Average True Range (ATR), всегда будет снижаться после завершения сильного вертикального движения, поскольку рынок переходит в фазу отката или замедления. Такое снижение является пост-импульсным и не обязательно сигнализирует о скором пробое.
Требуется найти признаки аномально низкой волатильности, которая возникает именно в фазе консолидации. Оптимальный момент для поиска сигнала Сжатия — это возникновение четкого бокового канала. В этой фазе средняя линия канального индикатора (например, EMA или SMA) должна быть относительно горизонтальной. Это подтверждает, что рынок в данный момент находится в состоянии рейнджа (отсутствие сильного текущего тренда), а не в фазе замедления после тренда. Таким образом, в алгоритм индикатора Squeeze необходимо заложить проверку на подтверждение бокового движения (например, через анализ наклона средней линии или ее статистического отклонения от горизонтали за последние X периодов). Только аномально низкая волатильность в фазе рейнджа может быть квалифицирована как высоконадежное пред-пробойное сжатие.
II. Выбор Инструмента: Обоснование Композитного Подхода BB/KC Squeeze
Для эффективного алгоритмического определения фазы экстремального сжатия необходимо использовать индикатор, который комбинирует преимущества двух наиболее надежных методов измерения волатильности: Полос Боллинджера и Каналов Кельтнера.
Сравнительный Анализ Индикаторов Волатильности
Полосы Боллинджера (Bollinger Bands, BB)
Полосы Боллинджера основаны на Стандартном Отклонении (SD) цены от скользящей средней. Эта статистическая метрика делает BB высокочувствительными, поскольку они быстро реагируют на внезапные изменения волатильности. Благодаря этой чувствительности, BB идеально подходят для ранней регистрации начавшегося сжатия и для генерации сигнала пробоя. Однако их высокая чувствительность также является недостатком, так как она может приводить к ложным срабатываниям и преждевременному расширению в условиях рыночного шума.
Каналы Кельтнера (Keltner Channels, KC)
Каналы Кельтнера, в современной версии, разработанной Линдой Рашке, используют Average True Range (ATR) для расчета ширины канала. ATR представляет собой усредненный истинный диапазон колебаний, что обеспечивает более сглаженную и устойчивую меру волатильности. KC реагируют на изменения рынка медленнее, чем BB, но их плавность позволяет лучше фильтровать ложные сигналы и определять истинное направление движения. В отличие от ценовых каналов с фиксированной шириной или процентными конвертами, которые плохо работают в динамичных средах, BB и KC автоматически адаптируются к рыночным условиям.
Механизм Squeeze: Синергия Инструментов
Индикатор BB/KC Squeeze использует синергию BB и KC для достижения максимальной точности в идентификации фазы накопления.
Техническое условие Сжатия (Squeeze ON) определяется, когда быстрые и статистически ориентированные Полосы Боллинджера (BB) оказываются внутри более широких и сглаженных Каналов Кельтнера (KC). Это состояние представляет собой количественное подтверждение экстремально низкой волатильности.
В стандартных настройках BB используют множитель 2.0 от Стандартного Отклонения (SD), а KC используют множитель 1.5 от ATR. Для того чтобы статистическая ширина BB (основанная на отклонении цены от средней) сузилась внутрь ширины KC (основанной на усредненном диапазоне), текущее статистическое отклонение цены должно упасть до аномально низких значений по отношению к историческому среднему диапазону колебаний. Это не просто низкая волатильность, а ее экстремальное сокращение, указывающее на максимальное накопление потенциальной энергии перед импульсом.
Таблица Сравнения Ключевых Индикаторов Волатильности
| Индикатор | Базовая Метрика | Реакция на Волатильность | Основная Роль в Squeeze |
|---|---|---|---|
| Bollinger Bands (BB) | Стандартное Отклонение (SD) | Быстрая, Высокочувствительная | Датчик сжатия, Ранний сигнал пробоя |
| Keltner Channels (KC) | Average True Range (ATR) | Плавная, Фильтрация шума | Определение устойчивого диапазона, Фильтр ложных сигналов |
III. Количественный Анализ: На Сколько, Почему и Как Сокращается Волатильность
На Сколько: Математическое Определение Степени Сжатия
Степень сокращения волатильности перед пробоем измеряется через строгое математическое условие, которое обеспечивает, что текущая волатильность значительно ниже ее усредненного исторического значения.
Условие Сжатия (Squeeze ON) требует выполнения обеих следующих математических формул :
Для понимания того, на сколько должно сократиться движение, необходимо рассмотреть формулы ширины каналов:
* Ширина Полос Боллинджера (\text{BB}_{\text{Width}}):
\text{KC}_{\text{Width}} = 2 \times (\text{ATR} \times 1.5) = 3.0 \times \text{ATR}$$
Состояние Squeeze ON означает, что \text{BB}_{\text{Width}} < \text{KC}_{\text{Width}}. Это условие эквивалентно \text{SD} \times 4.0 < \text{ATR} \times 3.0. В результате, текущее стандартное отклонение (SD) должно упасть ниже 75% от усредненного истинного диапазона (ATR), чтобы сжатие было зарегистрировано. Такое требование к снижению SD до уровня, значительно ниже ATR, является критерием для идентификации глубокого покоя рынка, который служит энергетической базой для последующего направленного движения.
Почему и Как: Качественные Признаки
Снижение волатильности происходит потому, что крупные участники рынка медленно и скрытно накапливают позиции. Они поддерживают цену в узком диапазоне, чтобы полностью набрать необходимый объем, прежде чем позволить цене импульсивно выйти из консолидации. Это создает фазу бокового движения, минимизируя риски для трейдера и позволяя оперативно отследить «бычий» или «медвежий» прорыв.
Для повышения надежности алгоритма и предотвращения входа в ложные диапазоны, необходимо учитывать следующие качественные признаки, сопровождающие истинное сжатие:
* Длительность Сжатия: Чем дольше цена находится в состоянии Squeeze ON, тем больше энергии накапливается. Опыт показывает, что минимальная длительность должна составлять 4–8 периодов. Длительные периоды сжатия (более 10–12 баров) часто предшествуют наиболее сильным импульсным движениям на крипторынке.
* Положение Цены: Во время фазы сжатия цена должна находиться в непосредственной близости к средней линии (EMA/SMA). Это подтверждает, что рынок находится в состоянии равновесия, и накопление происходит вокруг "справедливой" цены текущего диапазона.
* Контекст Моментума: Индикатор волатильности (BB/KC) определяет когда произойдет движение, но не его направление. Для предсказания направления (признак) необходимо использовать компонент моментума (например, гистограмму, как в варианте TTM Squeeze ). Появление положительного моментума во время сжатия, даже при отсутствии движения цены, является признаком потенциальной бычьей силы, усиливающей вероятность пробоя вверх.
Логика Определения Состояния "Сжатия" (Squeeze State Logic)
| Состояние | Математическое Условие (BB vs KC) | Интерпретация Рынка |
|---|---|---|
| Squeeze ON | (\text{BB}_{\text{Upper}} < \text{KC}_{\text{Upper}}) И (\text{BB}_{\text{Lower}} > \text{KC}_{\text{Lower}}) | Экстремальная контракция волатильности, фаза накопления, ожидание прорыва. |
| Squeeze OFF | \text{BB}_{\text{Upper}} \ge \text{KC}_{\text{Upper}} ИЛИ \text{BB}_{\text{Lower}} \le \text{KC}_{\text{Lower}} | Нормальная волатильность, трендовое движение или неустойчивый диапазон. |
IV. Техническая Спецификация: Пошаговый Алгоритм Индикатора Squeeze (BB/KC)
Данный алгоритм представляет собой последовательность шагов, необходимых для кодирования индикатора, фиксирующего состояние сжатия и генерирующего сигналы пробоя.
1. Инициализация и Расчет Базовых Величин
* Определение Периода N: Определить период N (рекомендуемое значение N=20) для расчета скользящих средних, ATR и Стандартного Отклонения (SD).
* Расчет Истинного Диапазона (True Range, TR): Для каждого бара рассчитать \text{TR} как максимальное значение из трех метрик: (High – Low), \text{Abs}(\text{High} - \text{Close}_{\text{prev}}), \text{Abs}(\text{Low} - \text{Close}_{\text{prev}}).
2. Расчет Компонентов Канала Кельтнера (KC)
* Расчет Средней Линии KC (EMA): Рассчитать экспоненциальную скользящую среднюю (EMA) цены закрытия (\text{Close}) за период N.
* Расчет ATR: Рассчитать Средний Истинный Диапазон (ATR) как скользящую среднюю \text{TR} за период N.
* Расчет Границ KC: Рассчитать Верхнюю и Нижнюю линии KC, используя множитель ATR Y (рекомендуется Y=1.5 ):
* * 3. Расчет Компонентов Полос Боллинджера (BB)
* Расчет Средней Линии BB (SMA): Рассчитать простую скользящую среднюю (SMA) цены закрытия (\text{Close}) за период N.
* Расчет SD: Рассчитать Стандартное Отклонение (SD) цены закрытия за период N.
* Расчет Границ BB: Рассчитать Верхнюю и Нижнюю полосы BB, используя множитель SD X (рекомендуется X=2.0 ):
* * 4. Алгоритм Определения Состояния "Squeeze"
* Проверка Условия Squeeze ON: Для текущего бара проверить, выполняются ли оба условия: \text{BB}_{\text{Upper}} < \text{KC}_{\text{Upper}} И \text{BB}_{\text{Lower}} > \text{KC}_{\text{Lower}}.
* Присвоение Состояния: ЕСЛИ оба условия в шаге 9 истинны, ТО присвоить переменной \text{SqueezeState} значение \text{ON} (например, 1). ИНАЧЕ присвоить значение \text{OFF} (например, 0).
5. Алгоритм Генерации Сигналов Пробоя
* Идентификация Триггера: Проверить, что \text{SqueezeState} изменился с \text{ON} на \text{OFF} на текущем баре. Это означает, что волатильность расширилась после периода сжатия.
* Сигнал Бычьего Пробоя: ЕСЛИ \text{SqueezeState}_{\text{prev}} = \text{ON} И \text{SqueezeState}_{\text{current}} = \text{OFF}, И цена закрытия (\text{Close}) текущего бара выше \text{BB}_{\text{Upper}}, ТО генерировать сигнал ПОКУПКА (Breakout Long).
* Сигнал Медвежьего Пробоя: ЕСЛИ \text{SqueezeState}_{\text{prev}} (start_span) (end_span)= \text{ON} И \text{SqueezeState}_{\text{current}} = \text{OFF}, И цена закрытия (\text{Close}) текущего бара ниже \text{BB}_{\text{Lower}}, ТО генерировать сигнал ПРОДАЖА (Breakout Short).
* Дополнительная Фильтрация Моментумом: Для повышения надежности, сигнал пробоя должен быть действителен только ЕСЛИ пробой происходит в направлении, подтвержденном моментум-индикатором (например, если Моментум > 0 для Бычьего пробоя, и Моментум < 0 для Медвежьего пробоя).
Роль Моментума в Алгоритме
Ключевым дополнением к индикатору волатильности является компонент моментума. Определение состояния Squeeze ON/OFF позволяет понять потенциал движения, но не его направление. Моментум-индикатор (часто реализованный в виде гистограммы, как в TTM Squeeze ) позволяет измерить, происходит ли накопление давления покупателей или продавцов во время фазы сжатия. Следовательно, индикатор должен включать подкомпонент, который измеряет это давление. Использование моментума в сочетании с пробоем BB гарантирует, что вход в позицию происходит не просто после расширения волатильности, а после ее расширения в подтвержденном направлении, что существенно снижает количество ложных пробоев.
V. Параметры, Оптимизация и Нюансы для Криптовалютного Рынка
Адаптация Стандартных Настроек (20, 2.0, 1.5)
Стандартные параметры N=20, X_{\text{BB}}=2.0 и Y_{\text{KC}}=1.5 разработаны для фондовых рынков и являются надежной отправной точкой. Однако высокая волатильность и динамика криптовалютного рынка требуют тонкой настройки для оптимизации производительности.
1. Оптимизация Периода N
Уменьшение периода N (например, до 18 или 14) на более низких таймфреймах (1-часовой и ниже) увеличит чувствительность индикатора к локальным, быстрым сжатиям, что полезно для скальпинга. Однако, это также может привести к генерации большего количества сигналов, в том числе ложных. Для среднесрочных торговых стратегий (4h, Daily) период N=20 или N=21 обеспечивает оптимальный баланс между чувствительностью и фильтрацией шума.
2. Оптимизация Множителя Y_{\text{KC}}
Множитель Каналов Кельтнера (Y) по умолчанию равен 1.5. KC более плавные и устойчивые благодаря использованию ATR. Если в процессе тестирования индикатор генерирует слишком много ложных сигналов Squeeze ON, это может указывать на то, что канал KC слишком узок. В этом случае, небольшое увеличение множителя Y (например, до 1.6 или 1.7) расширит KC. Это потребует еще более экстремального падения Стандартного Отклонения, чтобы BB сузились внутрь KC, тем самым повышая строгость и надежность сигнала Squeeze ON.
Важность Выбора Таймфрейма
Хотя некоторые индикаторы, такие как KC и BB, показывают более высокую эффективность в трендовом состоянии для торговли отскоками от границ , стратегия Squeeze Play принципиально иная. Она целенаправленно ищет рейндж (контракцию волатильности) с целью поймать начало нового сильного тренда.
На рынке криптовалют ложные пробои и рыночный шум (chop) могут быть особенно интенсивными на низких таймфреймах. Поэтому для стратегии Squeeze рекомендуется использовать таймфреймы, на которых консолидация наиболее чиста: 4-часовой, Daily или Weekly графики для основных криптопар, таких как BTC/USD или ETH/USD. На более низких таймфреймах необходимо внедрять мультитаймфреймовое подтверждение, используя, например, фильтр тренда с более высокого таймфрейма.
VI. Стратегическое Применение Squeeze Play и Фильтрация
Использование Momentum для Определения Направления
Как уже было отмечено, индикатор волатильности (BB/KC) не является индикатором направления. Функция сжатия (Squeeze ON) лишь идентифицирует высокую вероятность сильного движения. Следовательно, для успешной торговли необходимо интегрировать Моментум.
Прорыв следует использовать как триггер, но направление должно быть подтверждено Моментумом. Например, сигнал ПОКУПКА должен быть сгенерирован, только если соблюдены два условия:
* Выход из состояния Squeeze ON и пробитие ценой закрытия верхней полосы BB (\text{Close} > \text{BB}_{\text{Upper}}).
* Моментум-индикатор подтверждает восходящее давление (значение Моментума положительно).
Такой подход предотвращает входы в ложные пробои, когда волатильность расширяется, но не в направлении накопленного рыночного давления.
Управление Рисками и Позицией
Поскольку Канал Кельтнера основан на ATR, который является динамической мерой волатильности , именно ATR следует использовать для установки стоп-лосса (SL) в алгоритмической стратегии.
* Установка Стоп-Лосса (SL): Рекомендуется устанавливать SL на уровне, определяемом 1 \times \text{ATR} ниже средней линии (EMA/SMA) или за границей канала KC, противоположной пробою. Использование ATR обеспечивает, что SL динамически адаптируется к текущей волатильности, избегая слишком узких стопов в периоды нормального диапазона.
* Установка Тейк-Профита (TP): Поскольку цель Squeeze Play — поймать сильное направленное движение, тейк-профит может быть установлен на основе фиксированного соотношения Риск/Прибыль (например, 2:1 или 3:1) или на основе выхода цены за пределы KC. Пробитие KC часто указывает на экстремальное ценовое движение и может служить точкой для частичной или полной фиксации прибыли.
Фильтрация Против Ложных Сигналов в Рейндже
Основной недостаток торговли на пробой — высокий процент ложных сигналов в широких, но не направленных диапазонах. Использование композитного индикатора BB/KC Squeeze эффективно решает эту проблему.
KC, будучи основанным на сглаженном ATR, менее подвержен краткосрочным всплескам волатильности, чем BB. Фильтр Сжатия требует, чтобы чувствительные BB сузились внутрь сглаженных KC. Это гарантирует, что мы входим только в те прорывы, которым предшествовала длительная и аномально низкая фаза волатильности. Пробой должен быть подтвержден тем, что цена пробивает BB после завершения состояния Squeeze ON, что сигнализирует об устойчивом расширении волатильности, а не о кратковременном ценовом всплеске.
VII. Заключение
Анализ подтверждает, что наблюдение пользователя о связи между сокращением волатильности и последующими сильными движениями является фундаментально верным принципом, наилучшая реализация которого на рынке криптовалют достигается с помощью композитного индикатора BB/KC Squeeze.
Этот индикатор предоставляет точное количественное определение "на сколько" волатильность должна сократиться (SD должно упасть ниже 75% от ATR) и включает необходимые качественные предпосылки ("почему и как" — консолидация, подтвержденная моментумом). Представленный пошаговый алгоритм обеспечивает техническую основу для кодирования высокоэффективного инструмента, который идентифицирует фазы аккумуляции и генерирует сигналы пробоя, адаптированные к динамике крипторынка. Включение фильтрации на основе моментума и надлежащее управление риском, привязанное к ATR, являются ключевыми факторами для перехода от чистого индикатора к прибыльной торговой стратегии.
Bandas y canales
Daily Range Box (RIC)This indicator draws a blue-bordered box for each trading day, visible across all timeframes without alteration. The box's upper boundary is the day's highest price, the lower boundary is the day's lowest price, starting from the first trade of the day and ending at the last trade (including extended trading hours). A dashed horizontal line is drawn at the midpoint between the high and low within the box.
Swing Aurora v7.0 — The ExecutionerSwing Aurora v7.0 — The Executioner
Swing Aurora v7.0 is a multi-engine swing trading framework that combines trend-following, momentum, HTF confluence and SMC/Fibonacci structure in one script.
This version moves from a rigid gate logic to a scoring + state machine engine, so you can see not only if there is a signal, but how strong that signal really is.
🧠 1. Scoring Engine – A-Grade & B-Grade Signals
Instead of a single if (all conditions == true) check, v7.0 builds a score on every bar:
Trend score – position vs Baseline, slope, Supertrend direction.
Momentum score – MACD, RSI-Stoch triggers, ADX, local HH/LL.
HTF score – alignment with higher timeframe Baseline, Bias EMA, EMAs and RSI.
Confluence flags – divergences, ST flip/retest, SMC zones, VDub context.
Results:
A-Grade (Strong) signals → high score, strong trend + momentum + HTF alignment.
B-Grade (Speculative) signals → early/partial setups, clearly marked as higher risk.
You no longer lose good entries just because one minor filter disagrees, but you can clearly distinguish high-quality setups from speculative ones.
🔁 2. Strict Trade Cycle – State Machine
v7.0 uses a simple state machine:
0 = Flat, 1 = Long, -1 = Short.
When you are Long, the script only looks for exits or reversals, not new BUY entries.
Same for Short.
This enforces a clean, disciplined flow:
BUY → Hold → EXIT → wait for next setup, without label spam or conflicting signals while already in a position.
🛡️ 3. Quality Gates & Anti-FOMO Filters
To avoid buying local tops or chopping yourself to death:
RSI Gate – blocks BUY when RSI is already overbought (and vice-versa for SELL).
ATR Over-Extension filter – no entries when price is too far from the Baseline (parabolic moves).
No-Trade / Chop zone – combines ADX, ATR vs ATR-slow, distance to Baseline, Bollinger/Keltner squeeze and volume behavior.
Volume Gate – requires a real volume spike, not just random price wiggle.
Supertrend Gate – entries are synchronized with ST (flip / early / retest — configurable).
HTF Guardrails – optional: blocks entries against the dominant HTF regime.
📈 4. Visual Layer: Trend Map, Labels & Gradient
BUY/SELL labels with confidence percentage.
Background gradient based on trend direction and strength (ADX).
EMA 13/21 + Baseline with dynamic bull/bear colors.
Optional mini-legend showing: TS / RSI / ADX / HTF status at a glance.
🧩 5. Divergences, VDub & Macro Map
Full divergence engine (classic + hidden) on a basket of indicators (RSI, MACD, CCI, OBV, etc.), with optional lines and count labels.
VDub levels & signals – “smart levels” (solid/dotted) and add-on BUY/SELL signals filtered by market regime.
HTF Macro Map – higher timeframe Baseline, Bias EMA, fast EMAs, RSI and slope, using an auto or user-selected higher TF.
🧱 6. SMC Zones & Fibonacci (v7.0 Logic)
The SMC / Fibo component was refined so it is not hard-wired to the current bar’s entry signal:
Automatic HH / HL / LH / LL market structure labelling.
Demand / Supply zones:
derived from BOS with ATR buffer,
auto-update bar-by-bar,
auto-delete when broken or after a user-defined lifetime.
Fibonacci range:
built from the latest valid swing-high / swing-low,
shows 0 / 0.382 / 0.5 / 0.618 / 1 / 1.618 levels plus equilibrium line,
persists while the range is valid (independent of being in a trade).
AI zone boost (v7.0) – optional: zone opacity adapts dynamically to the underlying confidence score, highlighting higher-quality areas.
⚙️ 7. Modes & Configuration
Modes: Aggressive / Balanced / Conservative – adjust score thresholds and confidence requirements.
Risk & Quality: slope filter, min ATR distance, strict anti-chop, volume gate, HTF guardrails.
Visual toggles: labels on/off, baseline & EMAs, gradient, mini-legend, SMC boxes, Fibonacci.
This script does not trade for you – it provides a structured, consistent framework for reading trend, momentum and structure, plus graded signals so you can execute your own risk management and strategy.
Disclaimer
This script is provided strictly for educational and research purposes. It does not constitute financial advice, investment recommendation or any guarantee of profit. Historical performance, backtests and chart examples do not ensure future results.
Always use your own risk management rules, test the script on multiple instruments and timeframes, and never trade with money you cannot afford to lose. The author and contributors accept no responsibility for any trading decisions made based on this indicator.
AMORY Dashboard VIPAmory VIP Dashboard: Indicators visually display Trend (EMA), RSI, ADX, ATR, Volume and buy/sell signals right on the chart. Current volume is 100% accurate, STRONG/BUY/SELL classified signals, easy-to-read right-hand corner dashboard with distinguishing colors, updated according to the last candle.
Daily Gann Box — Prev Day H/L (1, 0.5, 0) — Gift Idea for trading within the previous days range as described by The Rumers on Youtube. Since it wasn't uploaded and I wanted it. I made basic script and am sharing for free with them.
I will delete once they upload theirs. I don't want any credit or follows from this.
21D EMA STRUCTUREAs an intermediate-term swing trader, the 21-day moving average is the backbone of my system. Over time, I’ve simplified my approach to the point where this is really the only indicator I keep on my charts — aside from a few key lines to help define structure and pivots.
Phenom（指標版：EMA 交叉訊號 v8.8 + 結構與風險）標題 (Title)： Phenom Intelligence: Trend & Risk Structure System (v8.8)
內文 (Description)：
Introduction Phenom Intelligence v8.8 is a comprehensive trading system designed to capture trends while strictly managing risk. It integrates Dynamic EMA Structures, Momentum Filters, and Risk Boundaries (ATR & Pivots) into one chart, providing a complete decision-making framework.
Key Features
Dynamic EMA Ribbon: Automatically adjusts EMA lengths based on the selected mode (Swing, Scalping, Trend-Following, or Long-Term Investment).
ATR Risk Channel: Visualizes volatility risk. A close below the lower ATR band signals a potential structure break and suggests defensive measures.
Pivot Points (Auto-Structure): Automatically plots Pivot (P), Resistance (R1), and Support (S1) levels to identify optimal take-profit and stop-loss zones.
Golden Confluence Signals: High-quality buy/sell signals are triggered only when Trend, Momentum (MACD), RSI, and Multi-Timeframe (MTF) conditions align.
Disclaimer This script is "Invite-Only" and intended for educational purposes. It does not constitute financial advice.
系統簡介 Phenom Intelligence v8.8 是一套專為捕捉波段趨勢與風險控管而設計的綜合交易系統。整合了「趨勢結構」、「動能濾網」與「風險邊界」，協助交易者在進場前具備完整的決策依據。
核心功能
智能趨勢均線 (Dynamic EMA)： 內建四種戰略模式，系統會根據選定的模式自動調整均線週期。
ATR 動態風險通道： 以均線為軸心繪製波動率通道。當價格跌破下通道時，視為結構破壞警訊，提供客觀的離場參考。
結構支撐壓力 (Pivots)： 自動計算關鍵結構點位。R1 (阻力) 可作為獲利調節目標，S1 (支撐) 作為防守區。
黃金共振訊號： 當 EMA 趨勢、MACD 動能、RSI 強度與多週期狀態完全共振時，才會觸發特定訊號，過濾雜訊。
免責聲明 本指標僅供技術分析參考與教育用途，不代表任何形式的投資建議。
Clean Day End TradingThis script visualizes the complete Clean Box Breakout framework.
It automatically detects the intraday boundary window, builds a dynamic High/Low box, and locks levels at boundary close.
Features include:
• Dynamic boundary High/Low with optional historical day-1 & day-2 levels
• Automatic box visualization and real-time level updates
Ideal for traders who want clean, visual confirmation of the breakout model without running a strategy.
EMA/SMA Crossover Signals📊 EMA/SMA Crossover Signals
A professional trading indicator that identifies golden and death crosses between a customizable EMA and SMA with clear BUY/SELL labels displayed directly on your chart.
🎯 Key Features:
✅ Customizable Moving Averages - Adjust both EMA and SMA periods to match your trading strategy
✅ Clear Signal Labels - Large, color-coded "BUY" and "SELL" labels that are impossible to miss
✅ Adjustable Label Positioning - Control the vertical distance of signal labels from price action
✅ Professional Color Customization - Change colors for both moving averages and signals to match your theme
✅ Label Size Options - Choose from 4 different sizes (Tiny, Small, Normal, Large)
✅ Audio Alerts - Get notified instantly when crossovers occur
✅ Overlay Display - Signals appear directly on your price chart for better context
📈 How It Works:
🟢 BUY Signal: Triggered when the EMA crosses above the SMA (bullish crossover)
🔴 SELL Signal: Triggered when the EMA crosses below the SMA (bearish crossover)
⚙️ Customizable Settings:
Moving Averages:
- EMA Period (Default: 8)
- SMA Period (Default: 200)
Colors:
- EMA Color
- SMA Color
- Buy Signal Color
- Sell Signal Color
Signal Settings:
- Signal Vertical Offset
- Label Vertical Offset
- Label Size
💡 Best For:
- Day Trading (1-5 min timeframes)
- Swing Trading (4H-Daily)
- Trend Following Strategies
- Identifying momentum shifts
- Confirming market structure changes
🔔 Perfect for traders using ICT, Wyckoff, and institutional trading methodologies
Use this indicator as part of your complete trading system. Always combine with proper risk management and additional confluence factors.
Yesterday High LineYesterdays High Line Green Dotted Line. Just a line at the high point reached in yesterdays trading cycle
TRK19121. Add the Script to TradingView
• Copy the Pine Script code I gave you.
• In TradingView, open the Pine Editor (bottom of the screen).
• Paste the code and click Add to Chart.
2. What You’ll See
• On your chart, Fibonacci retracement levels will be drawn automatically between the highest and lowest points in the last lookback bars (default = 100).
• Bollinger Bands (20-period SMA with ±2 standard deviations) will also appear.
• On the top-right corner, a table will show all Fibonacci levels (0%, 23.6%, 38.2%, 50%, 61.8%, 78.6%, 100%) with their exact price values.
• All text in the table is black for clarity.
3. How It Updates
• Every new candle, the script recalculates the highest and lowest points in the lookback window.
• The Fibonacci levels and the table update automatically.
• You don’t need to manually redraw fibo lines — the script does it for you.
4. How to Interpret
• Fibonacci levels act as potential support/resistance zones.
• Bollinger Bands show volatility and overbought/oversold conditions.
• If price is near a Fibonacci level and touches the Bollinger upper/lower band, that’s a strong signal area.
• Example:
• Price near 61.8% fibo + lower band → possible bounce (long).
• Price near 38.2% fibo + upper band → possible rejection (short).
5. Customization
• You can change the value (default 100 bars) to adjust how far back the script finds the high/low.
• You can change Bollinger settings (, ) to fit your trading style.
• The table always shows the current fibo levels clearly, so you don’t need to measure them manually.
Fibo + Bollinger + Fibo Tablosu1. Add the Script to TradingView
• Copy the Pine Script code I gave you.
• In TradingView, open the Pine Editor (bottom of the screen).
• Paste the code and click Add to Chart.
2. What You’ll See
• On your chart, Fibonacci retracement levels will be drawn automatically between the highest and lowest points in the last lookback bars (default = 100).
• Bollinger Bands (20-period SMA with ±2 standard deviations) will also appear.
• On the top-right corner, a table will show all Fibonacci levels (0%, 23.6%, 38.2%, 50%, 61.8%, 78.6%, 100%) with their exact price values.
• All text in the table is black for clarity.
3. How It Updates
• Every new candle, the script recalculates the highest and lowest points in the lookback window.
• The Fibonacci levels and the table update automatically.
• You don’t need to manually redraw fibo lines — the script does it for you.
4. How to Interpret
• Fibonacci levels act as potential support/resistance zones.
• Bollinger Bands show volatility and overbought/oversold conditions.
• If price is near a Fibonacci level and touches the Bollinger upper/lower band, that’s a strong signal area.
• Example:
• Price near 61.8% fibo + lower band → possible bounce (long).
• Price near 38.2% fibo + upper band → possible rejection (short).
5. Customization
• You can change the value (default 100 bars) to adjust how far back the script finds the high/low.
• You can change Bollinger settings (, ) to fit your trading style.
• The table always shows the current fibo levels clearly, so you don’t need to measure them manually.
Weekly & Monthly Thresholds + VIX-Based Dynamic TargetsWeekly & Monthly Thresholds + VIX-Based Dynamic Targets
Weekly & Monthly Thresholds + VIX-Based Dynamic TargetsWeekly & Monthly Thresholds + VIX-Based Dynamic Targets
Impulse Reactor RSI-SMA Trend Indicator [ApexLegion]Impulse Reactor RSI-SMA Trend Indicator
Introduction and Theoretical Background
Design Rationale
Standard indicators frequently generate binary 'BUY' or 'SELL' signals without accounting for the broader market context. This often results in erratic "Flip-Flop" behavior, where signals are triggered indiscriminately regardless of the prevailing volatility regime.
Impulse Reactor was engineered to address this limitation by unifying two critical requirements: Quantitative Rigor and Execution Flexibility.
The Solution
Composite Analytical Framework This script is not a simple visual overlay of existing indicators. It is an algorithmic synthesis designed to function as a unified decision-making engine. The primary objective was to implement rigorous quantitative analysis (Volatility Normalization, Structural Filtering) directly within an alert-enabled framework. This architecture is designed to process signals through strict, multi-factor validation protocols before generating real-time notifications, allowing users to focus on structurally validated setups without manual monitoring.
How It Works
This is not a simple visual mashup. It utilizes a cross-validation algorithm where the Trend Structure acts as a gatekeeper for Momentum signals:
Logic over Lag: Unlike simple moving average crossovers, this script uses a 15-layer Gradient Ribbon to detect "Laminar Flow." If the ribbon is knotted (Compression), the system mathematically suppresses all signals.
Volatility Normalization: The core calculation adapts to ATR (Average True Range). This means the indicator automatically expands in volatile markets and contracts in quiet ones, maintaining accuracy without constant manual tweaking.
Adaptive Signal Thresholding: It incorporates an 'Anti-Greed' algorithm (Dynamic Thresholding) that automatically adjusts entry criteria based on trend duration. This logic aims to mitigate the risk of entering positions during periods of statistical trend exhaustion.
Why Use It?
Market State Decoding: The gradient Ribbon visualizes the underlying trend phase in real-time.
◦ Cyan/Blue Flow: Strong Bullish Trend (Laminar Flow).
◦ Magenta/Pink Flow: Strong Bearish Trend.
◦ Compressed/Knotted: When the ribbon lines are tightly squeezed or overlapping, it signals Consolidation. The system filters signals here to avoid chop.
Noise Reduction: The goal is not to catch every pivot, but to isolate high-confidence setups. The logic explicitly filters out minor fluctuations to help maintain position alignment with the broader trend.
⚖️ Chapter 1: System Architecture
Introduction: Composite Analytical Framework
System Overview
Impulse Reactor serves as a comprehensive technical analysis engine designed to synthesize three distinct market dimensions—Momentum, Volatility, and Trend Structure—into a unified decision-making framework. Unlike traditional methods that analyze these metrics in isolation, this system functions as a central processing unit that integrates disparate data streams to construct a coherent model of market behavior.
Operational Objective
The primary objective is to transition from single-dimensional signal generation to a multi-factor assessment model. By fusing data from the Impulse Core (Volatility), Gradient Oscillator (Momentum), and Structural Baseline (Trend), the system aims to filter out stochastic noise and identify high-probability trade setups grounded in quantitative confluence.
Market Microstructure Analysis: Limitations of Conventional Models
Extensive backtesting and quantitative analysis have identified three critical inefficiencies in standard oscillator-based strategies:
• Bounded Oscillator Limitations (The "Oscillation Trap"): Traditional indicators such as RSI or Stochastics are mathematically constrained between fixed values (0 to 100). In strong trending environments, these metrics often saturate in "overbought" or "oversold" zones. Consequently, traders relying on static thresholds frequently exit structurally valid positions prematurely or initiate counter-trend trades against prevailing momentum, resulting in suboptimal performance.
• Quantitative Blindness to Quality: Standard moving averages and trend indicators often fail to distinguish the qualitative nature of price movement. They treat low-volume drift and high-velocity expansion identically. This inability to account for "Volatility Quality" leads to delayed responsiveness during critical market events.
• Fractal Dissonance (Timeframe Disconnect): Financial markets exhibit fractal characteristics where trends on lower timeframes may contradict higher timeframe structures. Manual integration of multi-timeframe analysis increases cognitive load and susceptibility to human error, often resulting in conflicting biases at the point of execution.
Core Design Principles
To mitigate the aforementioned systemic inefficiencies, Impulse Reactor employs a modular architecture governed by three foundational principles:
Principle A:
Volatility Precursor Analysis Market mechanics demonstrate that volatility expansion often functions as a leading indicator for directional price movement. The system is engineered to detect "Volatility Deviation" — specifically, the divergence between short-term and long-term volatility baselines—prior to its manifestation in price action. This allows for entry timing aligned with the expansion phase of market volatility.
Principle B:
Momentum Density Visualization The system replaces singular momentum lines with a "Momentum Density" model utilizing a 15-layer Simple Moving Average (SMA) Ribbon.
• Concept: This visualization represents the aggregate strength and consistency of the trend.
• Application: A fully aligned and expanded ribbon indicates a robust trend structure ("Laminar Flow") capable of withstanding minor counter-trend noise, whereas a compressed ribbon signals consolidation or structural weakness.
Principle C:
Adaptive Confluence Protocols Signal validity is strictly governed by a multi-dimensional confluence logic. The system suppresses signal generation unless there is synchronized confirmation across all three analytical vectors:
1. Volatility: Confirmed expansion via the Impulse Core.
2. Momentum: Directional alignment via the Hybrid Oscillator.
3. Structure: Trend validation via the Baseline. This strict filtering mechanism significantly reduces false positives in non-trending (choppy) environments while maintaining sensitivity to genuine breakouts.
🔍 Chapter 2: Core Modules & Algorithmic Logic
Module A: Impulse Core (Normalized Volatility Deviation)
Operational Logic The Impulse Core functions as a volatility-normalized momentum gauge rather than a standard oscillator. It is designed to identify "Volatility Contraction" (Squeeze) and "Volatility Expansion" phases by quantifying the divergence between short-term and long-term volatility states.
Volatility Z-Score Normalization
The formula implements a custom normalization algorithm. Unlike standard oscillators that rely on absolute price changes, this logic calculates the Z-Score of the Volatility Spread.
◦ Numerator: (atr_f - atr_s) captures the raw momentum of volatility expansion.
◦ Denominator: (std_f + 1e-6) standardizes this value against historical variance.
◦ Result: This allows the indicator scales consistently across assets (e.g., Bitcoin vs. Euro) without manual recalibration.
f_impulse() =>
atr_f = ta.atr(fastLen) // Fast Volatility Baseline
atr_s = ta.atr(slowLen) // Slow Volatility Baseline
std_f = ta.stdev(atr_f, devLen) // Volatility Standard Deviation
(atr_f - atr_s) / (std_f + 1e-6) // Normalized Differential Calculation
Algorithmic Framework
• Differential Calculation: The system computes the spread between a Fast Volatility Baseline (ATR-10) and a Slow Volatility Baseline (ATR-30).
• Normalization Protocol: To standardize consistency across diverse asset classes (e.g., Forex vs. Crypto), the raw differential is divided by the standard deviation of the volatility itself over a 30-period lookback.
• Signal Generation:
◦ Contraction (Squeeze): When the Fast ATR compresses below the Slow ATR, it registers a potential volatility buildup phase.
◦ Expansion (Release): A rapid divergence of the Fast ATR above the Slow ATR signals a confirmed volatility expansion, validating the strength of the move.
Module B: Gradient Oscillator (RSI-SMA Hybrid)
Design Rationale To mitigate the "noise" and "false reversal" signals common in single-line oscillators (like standard RSI), this module utilizes a 15-Layer Gradient Ribbon to visualize momentum density and persistence.
Technical Architecture
• Ribbon Array: The system generates 15 sequential Simple Moving Averages (SMA) applied to a volatility-adjusted RSI source. The length of each layer increases incrementally.
• State Analysis:
Momentum Alignment (Laminar Flow): When all 15 layers are expanded and parallel, it indicates a robust trend where buying/selling pressure is distributed evenly across multiple timeframes. This state helps filter out premature "overbought/oversold" signals.
• Consolidation (Compression): When the distance between the fastest layer (Layer 1) and the slowest layer (Layer 15) approaches zero or the layers intersect, the system identifies a "Non-Tradable Zone," preventing entries during choppy market conditions.
// Laminar Flow Validation
f_validate_trend() =>
// Calculate spread between Ribbon layers
ribbon_spread = ta.stdev(ribbon_array, 15)
// Only allow signals if Ribbon is expanded (Laminar Flow)
is_flowing = ribbon_spread > min_expansion_threshold
// If compressed (Knotted), force signal to false
is_flowing ? signal : na
Module C: Adaptive Signal Filtering (Behavioral Bias Mitigation)
This subsystem, operating as an algorithmic "Anti-Greed" Mechanism, addresses the statistical tendency for signal degradation following prolonged trends.
Dynamic Threshold Adjustment
• Win Streak Detection: The algorithm internally tracks the outcome of closed trade cycles.
• Sensitivity Multiplier: Upon detecting consecutive successful signals in the same direction, a Penalty_Factor is applied to the entry logic.
• Operational Impact: This effectively raises the Required_Slope threshold for subsequent signals. For example, after three consecutive bullish signals, the system requires a 30% steeper trend angle to validate a fourth entry. This enforces stricter discipline during extended trends to reduce the probability of entering at the point of trend exhaustion.
Anti-Greed Logic: Dynamic Threshold Calculation
f_adjust_threshold(base_slope, win_streak) =>
// Adds a 10% penalty to the difficulty for every consecutive win
penalty_factor = 0.10
risk_scaler = 1 + (win_streak * penalty_factor)
// Returns the new, harder-to-reach threshold
base_slope * risk_scaler
Module D: Trend Baseline (Triple-Smoothed Structure)
The Trend Baseline serves as the structural filter for all signals. It employs a Triple-Smoothed Hybrid Algorithm designed to balance lag reduction with noise filtration.
Smoothing Stages
1. Volatility Banding: Utilizes a SuperTrend-based calculation to establish the upper and lower boundaries of price action.
2. Weighted Filter: Applies a Weighted Moving Average (WMA) to prioritize recent price data.
3. Exponential Smoothing: A final Exponential Moving Average (EMA) pass is applied to create a seamless baseline curve.
Functionality
This "Heavy" baseline resists minor intraday volatility spikes while remaining responsive to sustained structural shifts. A signal is only considered valid if the price action maintains structural integrity relative to this baseline
🚦 Chapter 3: Risk Management & Exit Protocols
Quantitative Risk Management (TP/SL & Trailing)
Foundational Architecture: Volatility-Adjusted Geometry Unlike strategies relying on static nominal values, Impulse Reactor establishes dynamic risk boundaries derived from quantitative volatility metrics. This design aligns trade invalidation levels mathematically with the current market regime.
• ATR-Based Dynamic Bracketing:
The protocol calculates Stop-Loss and Take-Profit levels by applying Fibonacci coefficients (Default: 0.786 for SL / 1.618 for TP) to the Average True Range (ATR).
◦ High Volatility Environments: The risk bands automatically expand to accommodate wider variance, preventing premature exits caused by standard market noise.
◦ Low Volatility Environments: The bands contract to tighten risk parameters, thereby dynamically adjusting the Risk-to-Reward (R:R) geometry.
• Close-Validation Protocol ("Soft Stop"):
Institutional algorithms frequently execute liquidity sweeps—driving prices briefly below key support levels to accumulate inventory.
◦ Mechanism: When the "Soft Stop" feature is enabled, the system filters out intraday volatility spikes. The stop-loss is conditional; execution is triggered only if the candle closes beyond the invalidation threshold.
◦ Strategic Advantage: This logic distinguishes between momentary price wicks and genuine structural breakdowns, preserving positions during transient volatility.
• Step-Function Trailing Mechanism:
To protect unrealized PnL while allowing for normal price breathing, a two-phase trailing methodology is employed:
◦ Phase 1 (Activation): The trailing function remains dormant until the price advances by a pre-defined percentage threshold.
◦ Phase 2 (Dynamic Floor): Once armed, the stop level creates a moving floor, adjusting relative to price action while maintaining a volatility-based (ATR) buffer to systematically protect unrealized PnL.
• Algorithmic Exit Protocols (Dynamic Liquidity Analysis)
◦ Rationale: Inefficiencies of Static Targets Static "Take Profit" levels often result in suboptimal exits. They compel traders to close positions based on arbitrary figures rather than evolving market structure, potentially capping upside during significant trends or retaining positions while the underlying trend structure deteriorates.
◦ Solution: Structural Integrity Assessment The system utilizes a Dynamic Liquidity Engine to continuously audit the validity of the position. Instead of targeting a specific price point, the algorithm evaluates whether the trend remains statistically robust.
Multi-Factor Exit Logic (The Tri-Vector System)
The Smart Exit protocol executes only when specific algorithmic invalidation criteria are met:
• 1. Momentum Exhaustion (Confluence Decay): The system monitors a 168-hour rolling average of the Confluence Score. A significant deviation below this historical baseline indicates momentum exhaustion, signaling that the driving force behind the trend has dissipated prior to a price reversal. This enables preemptive exits before a potential drawdown.
• 2. Statistical Over-Extension (Mean Reversion): Utilizing the core volatility logic, the system identifies instances where price deviates beyond 2.0 standard deviations from the mean. While the trend may be technically bullish, this statistical anomaly suggests a high probability of mean reversion (elastic snap-back), triggering a defensive exit to capitalize on peak valuation.
• 3. Oscillator Rejection (Immediate Pivot): To manage sudden V-shaped volatility, the system monitors RSI pivots. If a sharp "Pivot High" or divergence is detected, the protocol triggers an immediate "Peak Exit," bypassing standard trend filters to secure liquidity during high-velocity reversals.
🎨 Chapter 4: Visualization Guide
Gradient Oscillator Ribbon
The 15-layer SMA ribbon visualized via plot(r1...r15) represents the "Momentum Density" of the market.
• Visuals:
◦ Cyan/Blue Ribbon: Indicates Bullish Momentum.
◦ Pink/Magenta Ribbon: Indicates Bearish Momentum.
• Interpretation:
◦ Laminar Flow: When the ribbon expands widely and flows in parallel, it signifies a robust trend where momentum is distributed evenly across timeframes. This is the ideal state for trend-following.
◦ Compression (Consolidation): If the ribbon becomes narrow, twisted, or knotted, it indicates a "Non-Tradable Zone" where the market lacks a unified direction. Traders are advised to wait for clarity.
◦ Over-Extension: If the top layer crosses the Overbought (85) or Oversold (15) lines, it visually warns of potential market overheating.
Trend Baseline
The thick, color-changing line plotted via plot(baseline) represents the Structural Backbone of the market.
• Visuals: Changes color based on the trend direction (Blue for Bullish, Pink for Bearish).
• Interpretation:
Structural Filter: Long positions are statistically favored only when price action sustains above this baseline, while short positions are favored below it.
Dynamic Support/Resistance: The baseline acts as a dynamic support level during uptrends and resistance during downtrends.
Entry Signals & Labels
Text labels ("Long Entry", "Short Entry") appear when the system detects high-probability setups grounded in quantitative confluence.
• Visuals: Labeled signals appear above/below specific candles.
• Interpretation:
These signals represent moments where Volatility (Expansion), Momentum (Alignment), and Structure (Trend) are synchronized.
Smart Exit: Labels such as "Smart Exit" or "Peak Exit" appear when the system detects momentum exhaustion or structural decay, prompting a defensive exit to preserve capital.
Dynamic TP/SL Boxes
The semi-transparent colored zones drawn via fill() represent the risk management geometry.
• Visuals: Colored boxes extending from the entry point to the Take Profit (TP) and Stop Loss (SL) levels.
• Function:
Volatility-Adjusted Geometry: Unlike static price targets, these boxes expand during high volatility (to prevent wicks from stopping you out) and contract during low volatility (to optimize Risk-to-Reward ratios).
SAR + MACD Glow
Small glowing shapes appearing above or below candles.
• Visuals: Triangle or circle glows near the price bars.
• Interpretation:
This visual indicates a secondary confirmation where Parabolic SAR and MACD align with the main trend direction. It serves as an additional confluence factor to increase confidence in the trade setup.
Support/Resistance Table
A small table located at the bottom-right of the chart.
• Function: Automatically identifies and displays recent Pivot Highs (Resistance) and Pivot Lows (Support).
• Interpretation: These levels can be used as potential targets for Take Profit or invalidation points for manual Stop Loss adjustments.
🖥️ Chapter 5: Dashboard & Operational Guide
Integrated Analytics Panel (Dashboard Overview)
To facilitate rapid decision-making without manual calculation, the system aggregates critical market dimensions into a unified "Heads-Up Display" (HUD). This panel monitors real-time metrics across multiple timeframes and analytical vectors.
A. Intermediate Structure (12H Trend)
• Function: Anchors the intraday analysis to the broader market structure using a 12-hour rolling window.
• Interpretation:
◦ Bullish (> +0.5%): Indicates a positive structural bias. Long setups align with the macro flow.
◦ Bearish (< -0.5%): Indicates structural weakness. Short setups are statistically favored.
◦ Neutral: Represents a ranging environment where the Confluence Score becomes the primary weighting factor.
B. Composite Confluence Score (Signal Confidence)
• Definition: A probability metric derived from the synchronization of Volatility (Impulse Core), Momentum (Ribbon), and Trend (Baseline).
• Grading Scale:
Strong Buy/Sell (> 7.0 / < 3.0): Indicates full alignment across all three vectors. Represents a "Prime Setup" eligible for standard position sizing.
Buy/Sell (5.0–7.0 / 3.0–5.0): Indicates a valid trend but with moderate volatility confirmation.
Neutral: Signals conflicting data (e.g., Bullish Momentum vs. Bearish Structure). Trading is not recommended ("No-Trade Zone").
C. Statistical Deviation Status (Mean Reversion)
• Logic: Utilizes Bollinger Band deviation principles to quantify how far price has stretched from the statistical mean (20 SMA).
• Alert States:
Over-Extended (> 2.0 SD): Warning that price is statistically likely to revert to the mean (Elastic Snap-back), even if the trend remains technically valid. New entries are discouraged in this zone.
Normal: Price is within standard distribution limits, suitable for trend-following entries.
D. Volatility Regime Classification
• Metric: Compares current ATR against a 100-period historical baseline to categorize the market state.
• Regimes:
Low Volatility (Lvl < 1.0): Market Compression. Often precedes volatility expansion events.
Mid Volatility (Lvl 1.0 - 1.5): Standard operating environment.
High Volatility (Lvl > 1.5): Elevated market stress. Risk parameters should be adjusted (e.g., reduced position size) to account for increased variance.
E. Performance Telemetry
• Function: Displays the historical reliability of the Trend Baseline for the current asset and timeframe.
• Operational Threshold: If the displayed Win Rate falls below 40%, it suggests the current market behavior is incoherent (choppy) and does not respect trend logic. In such cases, switching assets or timeframes is recommended.
Operational Protocols & Signal Decoding
Visual Interpretation Standards
• Laminar Flow (Trade Confirmation): A valid trend is visually confirmed when the 15-layer SMA Ribbon is fully expanded and parallel. This indicates distributed momentum across timeframes.
• Consolidation (No-Trade): If the ribbon appears twisted, knotted, or compressed, the market lacks a unified directional vector.
• Baseline Interaction: The Triple-Smoothed Baseline acts as a dynamic support/resistance filter. Long positions remain valid only while price sustains above this structure.
System Calibration (Settings)
• Adaptive Signal Filtering (Prev. Anti-Greed): Enabled by default. This logic automatically raises the required trend slope threshold following consecutive wins to mitigate behavioral bias.
• Impulse Sensitivity: Controls the reactivity of the Volatility Core. Higher settings capture faster moves but may introduce more noise.
⚙️ Chapter 6: System Configuration & Alert Guide
This section provides a complete breakdown of every adjustable setting within Impulse Reactor to assist you in tailoring the engine to your specific needs.
🌐 LANGUAGE SETTINGS (Localization)
◦ Select Language (Default: English):
Function: Instantly translates all chart labels, dashboard texts into your preferred language.
Supported: English, Korean, Chinese, Spanish
⚡ IMPULSE CORE SETTINGS (Volatility Engine)
◦ Deviation Lookback (Default: 30): The period used to calculate the standard deviation of volatility.
Role: Sets the baseline for normalizing momentum. Higher values make the core smoother but slower to react.
◦ Fast Pulse Length (Default: 10): The short-term ATR period.
Role: Detects rapid volatility expansion.
◦ Slow Pulse Length (Default: 30): The long-term ATR baseline.
Role: Establishes the background volatility level. The core signal is derived from the divergence between Fast and Slow pulses.
🎯 TP/SL SETTINGS (Risk Management)
◦ SL/TP Fibonacci (Default: 0.786 / 1.618): Selects the Fibonacci ratio used for risk calculation.
◦ SL/TP Multiplier (Default: 1.5 / 2): Applies a multiplier to the ATR-based bands.
Role: Expands or contracts the Take Profit and Stop Loss boxes. Increase these values for higher volatility assets (like Altcoins) to avoid premature stop-outs.
◦ ATR Length (Default: 14): The lookback period for calculating the Average True Range used in risk geometry.
◦ Use Soft Stop (Close Basis):
Role: If enabled, Stop Loss alerts only trigger if a candle closes beyond the invalidation level. This prevents being stopped out by wick manipulations.
🔊 RIBBON SETTINGS (Momentum Visualization)
◦ Show SMA Ribbon: Toggles the visibility of the 15-layer gradient ribbon.
◦ Ribbon Line Count (Default: 15): The number of SMA lines in the ribbon array.
◦ Ribbon Start Length (Default: 2) & Step (Default: 1): Defines the spread of the ribbon.
Role: Controls the "thickness" of the momentum density visualization. A wider step creates a broader ribbon, useful for higher timeframes.
📎 DISPLAY OPTIONS
◦ Show Entry Lines / TP/SL Box / Position Labels / S/R Levels / Dashboard: Toggles individual visual elements on the chart to reduce clutter.
◦ Show SAR+MACD Glow: Enables the secondary confirmation shapes (triangles/circles) above/below candles.
📈 TREND BASELINE (Structural Filter)
◦ Supertrend Factor (Default: 12) & ATR Period (Default: 90): Controls the sensitivity of the underlying Supertrend algorithm used for the baseline calculation.
◦ WMA Length (40) & EMA Length (14): The smoothing periods for the Triple-Smoothed Baseline.
◦ Min Trend Duration (Default: 10): The minimum number of bars the trend must be established before a signal is considered valid.
🧠 SMART EXIT (Dynamic Liquidity)
◦ Use Smart Exit: Enables the momentum exhaustion logic.
◦ Exit Threshold Score (Default: 3): The sensitivity level for triggering a Smart Exit. Lower values trigger earlier exits.
◦ Average Period (168) & Min Hold Bars (5): Defines the rolling window for momentum decay analysis and the minimum duration a trade must be held before Smart Exit logic activates.
🛡️ TRAILING STOP (Step)
◦ Use Trailing Stop: Activates the step-function trailing mechanism.
◦ Step 1 Activation % (0.5) & Offset % (0.5): The price must move 0.5% in your favor to arm the first trail level, which sets a stop 0.5% behind price.
◦ Step 2 Activation % (1) & Offset % (0.2): Once price moves 1%, the trail tightens to 0.2%, securing the position.
🌀 SAR & MACD SETTINGS (Secondary Confirmation)
◦ SAR Start/Increment/Max: Standard Parabolic SAR parameters.
◦ SAR Score Scaling (ATR): Adjusts how much weight the SAR signal has in the overall confluence score.
◦ MACD Fast/Slow/Signal: Standard MACD parameters used for the "Glow" signals.
🔄 ANTI-GREED LOGIC (Behavioral Bias)
◦ Strict Entry after Win: Enables the negative feedback loop.
◦ Strict Multiplier (Default: 1.1): Increases the entry difficulty by 10% after each win.
Role: Prevents overtrading and entering at the top of an extended trend.
🌍 HTF FILTER (Multi-Timeframe)
◦ Use Auto-Adaptive HTF Filter: Automatically selects a higher timeframe (e.g., 1H -> 4H) to filter signals.
◦ Bypass HTF on Steep Trigger: Allows an entry even against the HTF trend if the local momentum slope is exceptionally steep (catch powerful reversals).
📉 RSI PEAK & CHOPPINESS
◦ RSI Peak Exit (Instant): Triggers an immediate exit if a sharp RSI pivot (V-shape) is detected.
◦ Choppiness Filter: Suppresses signals if the Choppiness Index is above the threshold (Default: 60), indicating a flat market.
📐 SLOPE TRIGGER LOGIC
◦ Force Entry on Steep Slope: Overrides other filters if the price angle is extremely vertical (high velocity).
◦ Slope Sensitivity (1.5): The angle required to trigger this override.
⛔ FLAT MARKET FILTER (ADX & ATR)
◦ Use ADX Filter: Blocks signals if ADX is below the threshold (Default: 20), indicating no trend.
◦ Use ATR Flat Filter: Blocks signals if volatility drops below a critical level (dead market).
🔔 Alert Configuration Guide
Impulse Reactor is designed with a comprehensive suite of alert conditions, allowing you to automate your trading or receive real-time notifications for specific market events.
How to Set Up:
Click the "Alert" (Clock) icon in the TradingView toolbar.
Select "Impulse Reactor " from the Condition dropdown.
Choose one of the specific trigger conditions below:
🚀 Entry Signals (Trend Initiation)
Long Entry:
Trigger: Fires when a confirmed Bullish Setup is detected (Momentum + Volatility + Structure align).
Usage: Use this to enter new Long positions.
Short Entry:
Trigger: Fires when a confirmed Bearish Setup is detected.
Usage: Use this to enter new Short positions.
🎯 Profit Taking (Target Levels)
Long TP:
Trigger: Fires when price hits the calculated Take Profit level for a Long trade.
Usage: Automate partial or full profit taking.
Short TP:
Trigger: Fires when price hits the calculated Take Profit level for a Short trade.
Usage: Automate partial or full profit taking.
🛡️ Defensive Exits (Risk Management)
Smart Exit:
Trigger: Fires when the system detects momentum decay or statistical exhaustion (even if the trend hasn't fully reversed).
Usage: Recommended for tightening stops or closing positions early to preserve gains.
Overbought / Oversold:
Trigger: Fires when the ribbon extends into extreme zones.
Usage: Warning signal to prepare for a potential reversal or pullback.
💡 Secondary Confirmation (Confluence)
SAR+MACD Bullish:
Trigger: Fires when Parabolic SAR and MACD align bullishly with the main trend.
Usage: Ideal for Pyramiding (adding to an existing winning position).
SAR+MACD Bearish:
Trigger: Fires when Parabolic SAR and MACD align bearishly.
Usage: Ideal for adding to short positions.
⚠️ Chapter 7: Conclusion & Risk Disclosure
Methodological Synthesis
Impulse Reactor represents a shift from reactive price tracking to proactive energy analysis. By decomposing market activity into its atomic components — Volatility, Momentum, and Structure — and reconstructing them into a coherent decision model, the system aims to provide a quantitative framework for market engagement. It is designed not to predict the future, but to identify high-probability conditions where kinetic energy and trend structure align.
Disclaimer & Risk Warnings
◦ Educational Purpose Only
This indicator, including all associated code, documentation, and visual outputs, is provided strictly for educational and informational purposes. It does not constitute financial advice, investment recommendations, or a solicitation to buy or sell any financial instruments.
◦ No Guarantee of Performance
Past performance is not indicative of future results. All metrics displayed on the dashboard (including "Win Rate" and "P&L") are theoretical calculations based on historical data. These figures do not account for real-world trading factors such as slippage, liquidity gaps, spread costs, or broker commissions.
◦ High-Risk Warning
Trading cryptocurrencies, futures, and leveraged financial products involves a substantial risk of loss. The use of leverage can amplify both gains and losses. Users acknowledge that they are solely responsible for their trading decisions and should conduct independent due diligence before executing any trades.
◦ Software Limitations
The software is provided "as is" without warranty. Users should be aware that market data feeds on analysis platforms may experience latency or outages, which can affect signal generation accuracy.
Weekly & Monthly Thresholds + Targets (final, fixed)bullish and bearish weekly and monthly range for the whole audience
Weekly & Monthly Thresholds + Targets (final, fixed)with alerts the weekly and monthly bullish and bearish ranges
Opening Range + Prev/Pre/Post Market Hi/Lo
Tracks each day’s regular-session high/low and their bar_index.
On a new day, stores those as “prev day” values.
Draws the prev-day lines anchored at the actual high/low bars from yesterday, then extends them across today (and beyond).
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