Range Zones ATR Range Zones ATR
Range Zones ATR is an open-source indicator designed to detect, validate, score, and maintain sideways price zones using ATR-normalized structure analysis.
The script is built for one specific purpose: identifying areas where price is behaving like a genuine horizontal range rather than a brief pause inside an ongoing trend. Instead of marking every local consolidation, it evaluates whether price is compressed relative to current volatility, whether directional pressure remains limited, whether the market is interacting with both sides of the structure, and whether internal movement stays balanced enough to justify treating the area as a meaningful zone of acceptance.
In practical terms, this indicator highlights parts of the chart where price is rotating within a contained area instead of moving cleanly in one direction. That makes it useful for studying balance, consolidation, containment, and possible expansion after compression.
What this indicator is
This indicator is a volatility-adjusted range structure detector.
Its main task is to answer a structural question:
Is price actually trading inside a valid sideways regime, or is the apparent consolidation too directional, too unstable, or too impulsive to be treated as a real range?
To answer that, the script does not rely on a single condition. It combines multiple filters and measurements into one process. A visible zone is only created after the candidate structure survives tests related to compression, trend pressure, slope behavior, duration, touch activity, oscillation, drift, and local expansion.
What this indicator shows
The script draws zones directly on the chart as horizontal boxes representing areas where price is being accepted inside a relatively contained environment.
The indicator can classify zones in three different ways:
Base Range
A confirmed sideways zone that passed the core validation logic.
Prime Range
A higher-quality confirmed zone with a stronger final score. These zones generally show cleaner balance, stronger containment, and better internal structure than a standard range.
HTF Confluence
A confirmed local zone that also overlaps with a valid higher-timeframe range context when the optional multi-timeframe feature is enabled.
These labels are structural descriptions, not trade commands. They are intended to help the user understand the character and quality of the detected range.
What the script measures
The indicator is built around the idea that a valid range should appear compressed, balanced, and relatively non-directional. To evaluate that, it measures several parts of market behavior.
Range width relative to ATR
The script compares the width of recent price envelopes to ATR. This allows the indicator to interpret range width relative to current volatility instead of using a fixed distance. A narrow range on one symbol may be wide on another, and a usable range on one timeframe may be insignificant on another. ATR normalization helps the script stay adaptive across different chart conditions.
Multiple internal envelopes
The script builds short-, medium-, and long-lookback envelopes from recent highs and lows. It then compares those candidates and selects the one that provides the best structural fit. This makes the detection process more flexible than relying on only one fixed lookback.
ADX trend pressure
A stable range normally should not exist in a strongly directional environment. The script uses ADX as part of its filter and scoring process to reduce the chance of classifying strong directional movement as sideways structure.
EMA slope and linear regression slope
A market can appear flat while still drifting directionally. To reduce that problem, the script checks both EMA slope and linear regression slope. This helps filter out sloped price action that does not behave like a clean horizontal range.
Minimum persistence
A valid range should remain stable for a meaningful number of bars before it is trusted. The script therefore includes minimum-bar confirmation logic so that very brief pauses do not become fully confirmed zones too early.
Touch behavior
A healthy range usually shows repeated interaction with its boundaries. The script tracks touches near the upper and lower edges of the candidate zone to confirm that price is actually rotating through the structure rather than clustering on one side.
Internal oscillation
A sideways regime should contain some back-and-forth movement. The script evaluates oscillatory behavior within the candidate zone to avoid treating a slow directional drift as balanced consolidation.
Drift and efficiency
The script checks how directly price is moving from one point to another. If movement becomes too efficient or too directional, that is less consistent with a true range. If movement is choppier and more rotational, the structure is more likely to qualify.
Impulsive movement
Strong impulsive candles can weaken or invalidate the idea of a stable range. The script uses expansion and impulse-related checks to reject candidates that are behaving too aggressively.
Higher-timeframe overlap
When the optional MTF context feature is enabled, the script checks whether the local zone overlaps a confirmed higher-timeframe range area. If the overlap is meaningful, the zone can receive a score boost and be classified with higher structural context.
How the detection process works
At a high level, the script follows this workflow:
First, it builds recent envelopes from highs and lows using several internal lookbacks.
Second, it measures whether those envelopes are sufficiently compressed relative to ATR.
Third, it combines that compression with trend and slope conditions such as ADX, EMA slope, and linear regression slope.
Fourth, if the environment looks suitable, it starts tracking a candidate zone instead of drawing a confirmed zone immediately.
Fifth, while the candidate is active, it evaluates persistence, touch count, oscillation, drift, path efficiency, and impulsive behavior.
Sixth, if the candidate survives enough structural tests, it becomes a visible zone on the chart.
Seventh, once a zone is active, it can continue, refine, merge with a nearby compatible zone, or terminate if price no longer behaves like the same sideways regime.
Finally, if breakout alerts are enabled, the script only considers a breakout confirmed after price closes beyond the zone edge plus an ATR-based buffer.
This process is important because the indicator is not designed to draw every small pause. It is designed to identify consolidations that behave like actual balance.
How to read the zones
A visible zone should be interpreted as an area where the script sees containment, acceptance, and relatively balanced price behavior.
That can help the user evaluate:
whether the market is still consolidating rather than trending,
whether price is continuing to rotate inside the same area,
whether one side of the structure is weakening,
whether the range remains healthy,
or whether the market may be transitioning from compression into expansion.
A Base Range means the structure passed the standard confirmation requirements.
A Prime Range means the same structure passed with a stronger overall score.
An HTF Confluence zone means the local structure also aligns with a broader higher-timeframe range area.
These classifications describe current market structure. They do not guarantee that price will remain inside the zone or that the next movement will occur in a particular direction.
How to use this indicator
This indicator is best used as a market-structure and chart-context tool.
One practical use is to study where price is being accepted inside a contained area. When price remains inside a confirmed zone and continues to interact with both edges, the market may still be operating in a balanced regime.
Another use is to monitor edge behavior. The upper and lower zone boundaries can serve as structural reference areas. Repeated rejection near one side, repeated return toward the middle, or clean acceptance outside the zone may help the user judge whether the range is still functioning or beginning to fail.
The breakout logic can also be used for structure monitoring. Because the script requires price to move beyond the zone edge with an ATR-based buffer, it is more selective than a simple boundary touch. This helps reduce reactions to small wick-only violations and shallow overshoots.
The optional higher-timeframe context can be used to compare local balance with broader structure. A local range that overlaps a confirmed higher-timeframe range may be more relevant than an isolated local pause.
The script can also be used to filter low-quality consolidation. Many apparent ranges are only temporary slowdowns inside a directional move. This indicator tries to reject many of those cases by requiring better balance, persistence, touch behavior, and non-directional structure before a zone is confirmed.
What makes this indicator different
This script differs from simpler range tools in several ways.
ATR-normalized detection
The indicator evaluates range width relative to ATR instead of using fixed-width boxes. This helps the same logic adapt to different volatility conditions, symbols, and timeframes.
Multi-factor validation
The script does not rely on a single trigger. It combines compression, trend pressure, slope analysis, persistence, touch activity, oscillation, drift, and efficiency into one structural decision process.
Candidate-to-confirmation workflow
Many range tools mark a zone as soon as price becomes temporarily narrow. This script first tracks a candidate, then confirms it only if the structure continues to behave like a true sideways regime.
Quality classification
The script separates normal confirmed ranges from stronger confirmed ranges. This helps distinguish ordinary structure from zones that achieve better internal scores.
Zone merge logic
Nearby zones that belong to the same horizontal regime can be merged. This is useful because real consolidations are often fragmented by minor interruptions or short empty gaps that still belong to the same broader balance area.
Higher-timeframe confluence
The optional MTF feature is used as structural context rather than as a separate signal engine. This allows local zones to be strengthened when they align with a broader confirmed range.
Active zone maintenance
Once confirmed, a zone is not simply frozen in place. The script can continue refining and extending the zone while price remains compatible with the same range logic.
Input overview
Mode
Conservative, Balanced, and Aggressive modes control how selective the detection process is. Conservative mode generally favors fewer and stricter zones. Aggressive mode allows broader coverage.
Preset
Scalping, Intraday, and Swing presets adjust internal lookbacks and structural behavior for different trading horizons.
Price Series
The script can use close, hl2, hlc3, or ohlc4 as its selected price source in parts of the scoring and filtering process, while envelopes remain based on highs and lows.
Sensitivity
Sensitivity changes how tightly or loosely candidate structures are interpreted.
Min Bars and Min Score
These settings define how much persistence and quality a candidate needs before it can qualify as a visible zone.
Trend Filter
This filter reduces the chance of labeling strong directional movement as sideways structure.
Merge controls
Merge Zones, Merge Threshold, Merge Gap Bars, and Bridge Merge control whether nearby compatible zones should be combined into one broader regime.
MTF controls
MTF Context, Higher TF, and MTF Boost allow local structure to be compared against confirmed higher-timeframe range structure.
Visual controls
The script includes settings for fill, borders, labels, theme handling, and score visibility.
Alerts
Optional alerts are available for newly confirmed zones and for breakout events beyond an active zone.
Best use cases
This indicator is designed for users who want to study consolidation structure rather than only directional trend behavior.
It can be useful for identifying balanced price areas, monitoring acceptance inside a horizontal regime, watching for continuation or breakdown of an existing range, studying compression before expansion, and comparing local structure with higher-timeframe context.
Important limitations
This script is an indicator, not a strategy. It does not execute trades and it does not provide backtest results.
Like any range-based method, it can become less effective in environments dominated by persistent directional expansion, abrupt trend transitions, or sudden volatility shocks. A detected zone is the script’s structural interpretation of current price behavior, not a guarantee that price will remain contained.
Open-source note
This script is published as open-source so users can inspect the logic, understand how the methodology works, and build on the idea in accordance with PulseWire’s publication and reuse rules.
Indicator
Indicator
Indicator
Squeeze Momentum Strategy [LazyBear] Buy Sell TP SL Alerts-Modified version of Squeeze Momentum Indicator by @LazyBear.
-Converted to version 5,
-Taken inspiration from @KivancOzbilgic for its buy sell calculations,
-Used @Bunghole strategy template with Take Profit, Stop Loss and Enable/Disable Toggles
-Added Custom Date Backtesting Module
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All credit goes to above
Problem with original version:
The original Squeeze Momentum Strategy did not have buy sell signals and there was alot of confusion as to when to enter and exit.
There was no proper strategy that would allow backtesting on which further analysis could be carried out.
There are 3 aspects this strategy:
1 ) Strategy Logic (easily toggleable from the dropdown menu from strategy settings)
- LazyBear (I have made this simple by using Kivanc technique of Momentums Moving Average Crossover, BUY when MA cross above signal line, SELL when crossdown signal line)
- Zero Crossover Line (BUY signal when crossover zero line, and SELL crossdown zero line)
2) Long Short TP and SL
- In strategies there is usually only 1 SL and 1 TP, and it is assumed that if a 2% SL giving a good profit %, then it would be best for both long and short. However this is not the case for many. Many markets/pairs, go down with much more speed then they go up with. Hence once we have a profitable backtesting setting, then we should start optimizing Long and Short SL's seperately. Once that is done, we should start optimizing for Long and Short TP's separately, starting with Longs first in both cases.
3) Enable and Disable Toggles of Long and Short Trades
- Many markets dont allow short trades, or are not suitable for short trades. In this case it would be much more feasible to disable "Short" Trading and see results of Long Only as a built in graphic view of backtestor provides a more easy to understand data feed as compared to the performance summary in which you have to review long and short profitability separately.
4) Custom Data Backtesting
- One of most crucial aspects while optimizing for backtesting is to check a strategies performance on uptrends, downtrend and sideways markets seperately as to understand the weak points of strategy.
- Once you enable custom date backtesting, you will see lines on the chart which can be dragged left right based on where you want to start and end the backtesting from and to.
Note:
- Not a financial advise
- Open to feedback, questions, improvements, errors etc.
- More info on how the squeeze momentum works visit LazyBear indicator link:
Happy Trading!
Cheers
M Tahreem Alam @mtahreemalam Strategy
Volatility Risk Premium (VRP) 1.0ENGLISH
This indicator (V-R-P) calculates the (one month) Volatility Risk Premium for S&P500 and Nasdaq-100.
V-R-P is the premium hedgers pay for over Realized Volatility for S&P500 and Nasdaq-100 index options.
The premium stems from hedgers paying to insure their portfolios, and manifests itself in the differential between the price at which options are sold (Implied Volatility) and the volatility the S&P500 and Nasdaq-100 ultimately realize (Realized Volatility).
I am using 30-day Implied Volatility (IV) and 21-day Realized Volatility (HV) as the basis for my calculation, as one month of IV is based on 30 calendaristic days and one month of HV is based on 21 trading days.
At first, the indicator appears blank and a label instructs you to choose which index you want the V-R-P to plot on the chart. Use the indicator settings (the sprocket) to choose one of the indices (or both).
Together with the V-R-P line, the indicator will show its one year moving average within a range of +/- 15% (which you can change) for benchmarking purposes. We should consider this range the “normalized” V-R-P for the actual period.
The Zero Line is also marked on the indicator.
Interpretation
When V-R-P is within the “normalized” range, … well... volatility and uncertainty, as it’s seen by the option market, is “normal”. We have a “premium” of volatility which should be considered normal.
When V-R-P is above the “normalized” range, the volatility premium is high. This means that investors are willing to pay more for options because they see an increasing uncertainty in markets.
When V-R-P is below the “normalized” range but positive (above the Zero line), the premium investors are willing to pay for risk is low, meaning they see decreasing uncertainty and risks in the market, but not by much.
When V-R-P is negative (below the Zero line), we have COMPLACENCY. This means investors see upcoming risk as being lower than what happened in the market in the recent past (within the last 30 days).
CONCEPTS:
Volatility Risk Premium
The volatility risk premium (V-R-P) is the notion that implied volatility (IV) tends to be higher than realized volatility (HV) as market participants tend to overestimate the likelihood of a significant market crash.
This overestimation may account for an increase in demand for options as protection against an equity portfolio. Basically, this heightened perception of risk may lead to a higher willingness to pay for these options to hedge a portfolio.
In other words, investors are willing to pay a premium for options to have protection against significant market crashes even if statistically the probability of these crashes is lesser or even negligible.
Therefore, the tendency of implied volatility is to be higher than realized volatility, thus V-R-P being positive.
Realized/Historical Volatility
Historical Volatility (HV) is the statistical measure of the dispersion of returns for an index over a given period of time.
Historical volatility is a well-known concept in finance, but there is confusion in how exactly it is calculated. Different sources may use slightly different historical volatility formulas.
For calculating Historical Volatility I am using the most common approach: annualized standard deviation of logarithmic returns, based on daily closing prices.
Implied Volatility
Implied Volatility (IV) is the market's forecast of a likely movement in the price of the index and it is expressed annualized, using percentages and standard deviations over a specified time horizon (usually 30 days).
IV is used to price options contracts where high implied volatility results in options with higher premiums and vice versa. Also, options supply and demand and time value are major determining factors for calculating Implied Volatility.
Implied Volatility usually increases in bearish markets and decreases when the market is bullish.
For determining S&P500 and Nasdaq-100 implied volatility I used their volatility indices: VIX and VXN (30-day IV) provided by CBOE.
Warning
Please be aware that because CBOE doesn’t provide real-time data in Tradingview, my V-R-P calculation is also delayed, so you shouldn’t use it in the first 15 minutes after the opening.
This indicator is calibrated for a daily time frame.
ESPAŇOL
Este indicador (V-R-P) calcula la Prima de Riesgo de Volatilidad (de un mes) para S&P500 y Nasdaq-100.
V-R-P es la prima que pagan los hedgers sobre la Volatilidad Realizada para las opciones de los índices S&P500 y Nasdaq-100.
La prima proviene de los hedgers que pagan para asegurar sus carteras y se manifiesta en el diferencial entre el precio al que se venden las opciones (Volatilidad Implícita) y la volatilidad que finalmente se realiza en el S&P500 y el Nasdaq-100 (Volatilidad Realizada).
Estoy utilizando la Volatilidad Implícita (IV) de 30 días y la Volatilidad Realizada (HV) de 21 días como base para mi cálculo, ya que un mes de IV se basa en 30 días calendario y un mes de HV se basa en 21 días de negociación.
Al principio, el indicador aparece en blanco y una etiqueta le indica que elija qué índice desea que el V-R-P represente en el gráfico. Use la configuración del indicador (la rueda dentada) para elegir uno de los índices (o ambos).
Junto con la línea V-R-P, el indicador mostrará su promedio móvil de un año dentro de un rango de +/- 15% (que puede cambiar) con fines de evaluación comparativa. Deberíamos considerar este rango como el V-R-P "normalizado" para el período real.
La línea Cero también está marcada en el indicador.
Interpretación
Cuando el V-R-P está dentro del rango "normalizado",... bueno... la volatilidad y la incertidumbre, como las ve el mercado de opciones, es "normal". Tenemos una “prima” de volatilidad que debería considerarse normal.
Cuando V-R-P está por encima del rango "normalizado", la prima de volatilidad es alta. Esto significa que los inversores están dispuestos a pagar más por las opciones porque ven una creciente incertidumbre en los mercados.
Cuando el V-R-P está por debajo del rango "normalizado" pero es positivo (por encima de la línea Cero), la prima que los inversores están dispuestos a pagar por el riesgo es baja, lo que significa que ven una disminución, pero no pronunciada, de la incertidumbre y los riesgos en el mercado.
Cuando V-R-P es negativo (por debajo de la línea Cero), tenemos COMPLACENCIA. Esto significa que los inversores ven el riesgo próximo como menor que lo que sucedió en el mercado en el pasado reciente (en los últimos 30 días).
CONCEPTOS:
Prima de Riesgo de Volatilidad
La Prima de Riesgo de Volatilidad (V-R-P) es la noción de que la Volatilidad Implícita (IV) tiende a ser más alta que la Volatilidad Realizada (HV) ya que los participantes del mercado tienden a sobrestimar la probabilidad de una caída significativa del mercado.
Esta sobreestimación puede explicar un aumento en la demanda de opciones como protección contra una cartera de acciones. Básicamente, esta mayor percepción de riesgo puede conducir a una mayor disposición a pagar por estas opciones para cubrir una cartera.
En otras palabras, los inversores están dispuestos a pagar una prima por las opciones para tener protección contra caídas significativas del mercado, incluso si estadísticamente la probabilidad de estas caídas es menor o insignificante.
Por lo tanto, la tendencia de la Volatilidad Implícita es de ser mayor que la Volatilidad Realizada, por lo cual el V-R-P es positivo.
Volatilidad Realizada/Histórica
La Volatilidad Histórica (HV) es la medida estadística de la dispersión de los rendimientos de un índice durante un período de tiempo determinado.
La Volatilidad Histórica es un concepto bien conocido en finanzas, pero existe confusión sobre cómo se calcula exactamente. Varias fuentes pueden usar fórmulas de Volatilidad Histórica ligeramente diferentes.
Para calcular la Volatilidad Histórica, utilicé el enfoque más común: desviación estándar anualizada de rendimientos logarítmicos, basada en los precios de cierre diarios.
Volatilidad Implícita
La Volatilidad Implícita (IV) es la previsión del mercado de un posible movimiento en el precio del índice y se expresa anualizada, utilizando porcentajes y desviaciones estándar en un horizonte de tiempo específico (generalmente 30 días).
IV se utiliza para cotizar contratos de opciones donde la alta Volatilidad Implícita da como resultado opciones con primas más altas y viceversa. Además, la oferta y la demanda de opciones y el valor temporal son factores determinantes importantes para calcular la Volatilidad Implícita.
La Volatilidad Implícita generalmente aumenta en los mercados bajistas y disminuye cuando el mercado es alcista.
Para determinar la Volatilidad Implícita de S&P500 y Nasdaq-100 utilicé sus índices de volatilidad: VIX y VXN (30 días IV) proporcionados por CBOE.
Precaución
Tenga en cuenta que debido a que CBOE no proporciona datos en tiempo real en Tradingview, mi cálculo de V-R-P también se retrasa, y por este motivo no se recomienda usar en los primeros 15 minutos desde la apertura.
Este indicador está calibrado para un marco de tiempo diario.
Indicator
Indicator
IFR2The IFR2 strategy is based on the RSI indicator.
If the two period RSI is less than the overbought level (25 is the default, but you can configure it to be lower), a long position is placed at the close of the candle. If you are doing it live, you'd have to enter the market ~ 10 minutes before it closes, check the RSI, and buy if it is lower than your overbought level. This generates a discrepancy in the backtesting, but since it is a very small difference, it can be disregarded. Higher overbought levels generate more signals, but they mostly are unreliable. Lower values generates better yields, but they won't occur very often. This strategy is designed to be used in a daily graph, and I don't recommend using it in intraday periods, since you'll make too little money to compensate for the operational cost.
The strategy exits when the high price of two previous candles is reached. If the exit price is higher than the closing price of when you entered, you'll be at a profit, otherwise you'll be at a loss. The exit price is plotted in the graph and it's colors depends on the current open profit: positive values will be green, negative will be red.
This strategy completely disregards the current trend. Long orders will be placed even if you are at a strong down trend. This may seem odd, but you have to keep in mind that this is a volatility based strategy , not a trend following one.
This setup was designed by Alexandre Wolwacz, a.k.a. Stormer. Strategy
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