Intraday Volatility Bands [Honestcowboy]The Intraday Volatility Bands aims to provide a better alternative to ATR in the calculation of targets or reversal points.
How are they different from ATR based bands?
While ATR and other measures of volatility base their calculations on the previous bars on the chart (for example bars 1954 to 1968). The volatility used in these bands measure expected volatility during that time of the day.
Why would you take this approach?
Markets behave different during certain times of the day, also called sessions.
Here are a couple examples.
Asian Session (generally low volatility)
London Session (bigger volatility starts)
New York Session (overlap of New York with London creates huge volatility)
Generally when using bands or channel type indicators intraday they do not account for the upcoming sessions. On London open price will quickly spike through a bollinger band and it will take some time for the bands to adjust to new volatility.
This script will show expected volatility targets at the start of each new bar and will not adjust during the bar. It already knows what price is expected to do at this time of day.
Script also plots arrows when price breaches either the top or bottom of the bands. You can also set alerts for when this occurs. These are non repainting as the script knows the level at start of the bar and does not change.
🔷 CALCULATION
Think of this script like an ATR but instead it uses past days data instead of previous bars data. Charts below should visualise this more clearly:
The scripts measure of volatility is based on a simple high-low.
The script also counts the number of bars that exist in a day on your current timeframe chart. After knowing that number it creates the matrix used in it's calculations and data storage.
See how it works perfectly on a lower timeframe chart below:
Getting this right was the hardest part, check the coding if you are interested in this type of stuff. I commented every step in the coding process.
🔷 SETTINGS
Every setting of the script has a tooltip but I provided a breakdown here:
Some more examples of different charts:
Cerca negli script per "bands"
Rolling Volatility BandsMake sure to view it from the 1D candlestick chart.
The Rolling Volatility Bands indicator provides a statistically-driven approach to visualizing expected daily price movements using true volatility calculations employed by professional options traders. Unlike traditional Bollinger Bands which use price standard deviation around a moving average, this indicator calculates actual daily volatility from log returns over customizable rolling periods (20-day and 60-day), then annualizes the volatility using the standard √252 formula before projecting forward-looking probability bands. The 1 Standard Deviation bands represent a ~68% probability zone where price is expected to trade the following day, while the 2 Standard Deviation bands capture ~95% of expected movements. This methodology mirrors how major exchanges calculate expected moves for earnings and FOMC events, making it invaluable for options strategies like iron condors during low-volatility periods (narrow bands) or directional plays when volatility expands. The indicator works on any timeframe while always utilizing daily candle data via security() calls, ensuring consistent volatility calculations regardless of your chart resolution, and includes real-time annualized volatility percentages plus daily expected range statistics for comprehensive market analysis.
Super-Elliptic BandsThe core of the "Super-Elliptic Bands" indicator lies in its use of a super-ellipse mathematical model to create dynamic price bands around a central Simple Moving Average (SMA). Here's a concise breakdown of its essential components:
Central Moving Average (MA):
A Simple Moving Average (ta.sma(close, maLen)) serves as the baseline, anchoring the bands to the average price over a user-defined period (default: 50 bars).
Super-Ellipse Formula:
The bands are generated using the super-ellipse equation: |y/b| = (1 - |x/a|^p)^(1/p), where:
x is a normalized bar index based on a user-defined cycle period (periodBase, default: 64), scaled to range from -1 to +1.
a = 1 (fixed semi-major axis).
b is the volatility-based semi-minor axis, calculated as volRaw * mult, where volRaw comes from ta.stdev, ta.atr, or ta.tr (user-selectable).
p (shapeP, default: 2.0) controls the band shape:
p = 2: Elliptical bands.
p < 2: Pointier, diamond-like shapes.
p > 2: Flatter, rectangular-like shapes.
This formula creates bands that dynamically adjust their width and shape based on price volatility and a cyclical component.
enjoy....
ka66: Bar Range BandsThis tool takes a bar's range, and reflects it above the high and below the low of that bar, drawing upper and lower bands around the bar. Repeated for each bar. There's an option to then multiply that range by some multiple. Use a value greater than 1 to get wider bands, and less than one to get narrower bands.
This tool stems out of my frustration from the use of dynamic bands (like Keltner Channels, or Bollinger Bands), in particular for estimating take profit points.
Dynamic bands work great for entries and stop loss, but their dynamism is less useful for a future event like taking profit, in my experience. We can use a smaller multiple, but then we can often lose out on a bigger chunk of gains unnecessarily.
The inspiration for this came from a friend explaining an ICT/SMC concept around estimating the magnitude of a trend, by calculating the Asian Session Range, and reflecting it above or below on to the New York and London sessions. He described this as standard deviation of the Asian Range, where the range can thus be multiplied by some multiple for a wider or narrower deviation.
This, in turn, also reminded me of the Measured Move concept in Technical Analysis. We then consider that the market is fractal in nature, and this is why patterns persist in most timeframes. Traders exist across the spectrum of timeframes. Thus, a single bar on a timeframe, is made up of multiple bars on a lower timeframe . In other words, when we reflect a bar's range above or below itself, in the event that in a lower timeframe, that bar fit a pattern whose take profit target could be estimated via a Measured Move , then the band's value becomes a more valid estimate of a take profit point .
Yet another way to think about it, by way of the fractal nature above, is that it is essentially a simplified dynamic support and resistance mechanism , even simpler than say the various Pivot calculations (e.g. Classical, Camarilla, etc.).
This tool in general, can also be used by those who manually backtest setups (and certainly can be used in an automated setting too!). It is a research tool in that regard, applicable to various setups.
One of the pitfalls of manual backtesting is that it requires more discipline to really determine an exit point, because it's easy to say "oh, I'll know more or less where to exit when I go live, I just want to see that the entry tends to work". From experience, this is a bad idea, because our mind subconsciously knows that we haven't got a trained reflex on where to exit. The setup may be decent, but without an exit point, we will never have truly embraced and internalised trading it. Again, I speak from experience!
Thus, to use this to research take profit/exit points:
Have a setup in mind, with all the entry rules.
Plot your setup's indicators, mark your signals.
Use this indicator to get an idea of where to exit after taking an entry based on your signal.
Credits:
@ICT_ID for providing the idea of using ranges to estimate how far a trend move might go, in particular he used the Asian Range projected on to the London and New York market sessions.
All the technicians who came up with the idea of the Measured Move.
Vollinger BandsI'm happy to present to you... VOLLINGER BANDS. Loosely based on bollinger bands, this indicator uses the new Up/Down Volume indicator from tradingview, which I have add moving averages, and a width calculation between them to determine squeeze. Essentially I have created a volume squeeze bollinger band derivative, hence the term "Vollinger Band".
The bands are NOT a deviation of any middle line or moving average, but rather their own moving averages of the volume delta, respectively.
Blue background = Volume Squeeze (vollinger bands width is less than the squeeze strength line), meaning consolidation, and a big move may happen soon.
Top line = A moving average of the Up Volume delta
Bottom line = A moving average of the Down Volume delta
Vol MA = the moving average length of both the top/bottom line
> If you zoom in, you can see a white line, which is the squeeze represented as a single line, calculated using bollinger bands width. The squeeze strength is a moving average of the squeeze line, which then determines if the width is below that moving average, then the squeeze will occur (white line below purple)
The bands are colored based on the sum of the Up/Down volume over the specified number of bars (preset at 5). If the volume is more buying than selling over that amount of bars, then the line is colored green, and vice versa.
[blackcat] L1 Vitali Apirine Exponential Deviation BandsLevel 1
Background
Vitali Apirine’s articles in the July issues on 2019,“Exponential Deviation Bands”
Function
In “Exponential Deviation Bands” in this issue, author Vitali Apirine introduces a price band indicator based on exponential deviation rather than the more traditional standard deviation, such as is used in the well-known Bollinger Bands. As compared to standard deviation bands, the author’s exponential deviation bands apply more weight to recent data and generate fewer breakouts. Apirine describes using the bands as a tool to assist in identifying trends.
Remarks
Feedbacks are appreciated.
BBSS - Bollinger Bands Scalping SignalsModified Bollinger Bands Indicator
Added:
- color change divergence (green) and narrowing (red) of the upper and lower bands
- color change of the moving average - upward trend (green) and downward trend (red)
- the appearance of a potential signal for long and short positions when the candle closes behind the upper or lower bands.
How to use the indicator:
Long conditions:
- the price breaks through the upper band
- Bollinger bands are expanding and should be green
- the mid-line is green
- the trigger candle should be green
Short conditions:
- the price breaks through the lower band
- Bollinger bands are expanding and should be red
- the mid-line is red
- the trigger candle should be red
MTF VWAP & StDev BandsMulti Timeframe Volume Weighted Average Price with Standard Deviation Bands
I used the script "Koalafied VWAP D/W/M/Q/Y" by Koalafied_3 and made some changes, such as adding more standard deviation bands.
The script can display the daily, weekly, monthly, quarterly and yearly VWAP.
Standard deviation bands values can be changed (default values are 0.618, 1, 1.618, 2, 2.618, 3).
Also the previous standard deviation bands can be displayed.
Zarattini Intra-day Threshold Bands (ZITB)This indicator implements the intraday threshold band methodology described in the research paper by Carlo Zarattini et al.
Overview:
Plots intraday threshold bands based on daily open/close levels.
Supports visualization of BaseUp/BaseDown levels and Threshold Upper/Lower bands.
Optional shading between threshold bands for easier interpretation.
Usage Notes / Limitations:
Originally studied on SPY (US equities), this implementation is adapted for NSE intraday market timing, specifically the NIFTY50 index.
Internally, 2-minute candles are used if the chart timeframe is less than 2 minutes.
Values may be inaccurate if the chart timeframe is more than 1 day.
Lookback days are auto-capped to avoid exceeding TradingView’s 5000-bar limit.
The indicator automatically aligns intraday bars across multiple days to compute average deltas.
For better returns, it is recommended to use this indicator in conjunction with VWAP and a volatility-based position sizing mechanism.
Can be used as a reference for Open Range Breakout (ORB) strategies.
Customizations:
Toggle plotting of base levels and thresholds.
Toggle shading between thresholds.
Line colors and styles can be adjusted in the Style tab.
Intended for educational and research purposes only.
This indicator implements the approach described in the research paper by Zarattini et al.
Note: This implementation is designed for the NSE NIFTY50 index. While Zarattini’s original study was conducted on SPY, this version adapts the methodology for the Indian market.
Methodology Explanation
This indicator is primarily designed for Open Range Breakout (ORB) strategies.
Base Levels
BaseUp = Maximum of today’s open and previous day’s close
BaseDown = Minimum of today’s open and previous day’s close
Delta Calculation
For the past 14 trading days (lookbackDays), the delta for each intraday candle is calculated as the ab
solute difference from the close of the first candle of that day.
Average Delta
For a given intraday time/candle today, deltaAvg is computed as the average of the deltas at the same time across the previous 14 days.
Threshold Bands
ThresholdUp = BaseUp + deltaAvg
ThresholdDown = BaseDown − deltaAvg
Signals
Spot price moving above ThresholdUp → Long signal
Spot price moving below ThresholdDown → Short signal
Tip: For better returns, combine this indicator with VWAP and a volatility-based position sizing mechanism.
PulseRPO Zero-Lag BandsPulseRPO is a momentum and volatility timing suite built on a zero-lag Relative Price Oscillator. It pairs an RPO (fast vs slow MA spread, in %) with adaptive volatility envelopes that tighten or widen as conditions change, so you can spot true momentum bursts, exhaustion and “quiet-before-the-move” squeezes—without the usual MA lag.
What it shows
Zero-Lag RPO: Choose EMA, SMA, WMA, RMA, HMA or ZLEMA for the base, then apply ZLEMA/DEMA/TEMA/HMA zero-lag smoothing to cut delay.
Adaptive Bands: StdDev, ATR, Range or Hybrid volatility; bands auto-tighten in high vol and widen in quiet regimes.
Dynamic OB/OS: Levels scale with current regime so extremes mean something even as volatility shifts.
Signal & Histogram: Classic signal cross plus histogram for quick read of acceleration vs deceleration.
Squeeze Paint: Subtle background highlight when band width compresses below its average.
Divergences & Triggers: Optional bullish/bearish divergence tags, plus band-cross and signal-cross alerts out of the box.
How to use it (general guide)
Momentum entries: Look for RPO crossing up its signal from below or snapping out of a squeeze; extra weight if it also re-enters from below the lower band.
Trend continuation: RPO riding outside the upper (or lower) band with rising histogram = power move; trail risk on pullbacks to the signal line.
Exhaustion / fades: Taps beyond dynamic OB/OS or band re-entries can mark mean-revert windows—confirm with price/volume.
Risk filter: During squeeze, size down and prepare for expansion; after expansion, respect extremes.
Tweak the MA type, band method and zero-lag strength to match your timeframe. PulseRPO is designed to be a self-contained read: regime → setup → trigger → alert.
VWAP with Prev. Session BandsVWAP with Prev. Session Bands is an advanced indicator based on TradingView’s original VWAP. It adds configurable standard deviation or percentage-based bands, both for the current and previous session. You can anchor the VWAP to various timeframes or events (like Sessions, Weeks, Months, Earnings, etc.) and selectively show up to three bands.
The unique feature of this script is the ability to display the VWAP and bands from the previous session, helping traders visualize mean reversion levels or historical volatility ranges.
Built on top of the official TradingView VWAP implementation, this version provides enhanced flexibility and visual clarity for intraday and swing traders alike.
Ethereum Logarithmic Regression Bands (Fine-Tuned)This indicator, "Ethereum Logarithmic Regression Bands (Fine-Tuned)," is my attempt to create a tool for estimating long-term trends in Ethereum (ETH/USD) price action using logarithmic regression bands. Please note that I am not an expert in financial modeling or coding—I developed this as a personal project to serve as a rough estimation rather than a precise or professional trading tool. The data was fitted to non-bubble periods of Ethereum's history to provide a general trendline, but it’s far from perfect.
I’m sharing this because I couldn’t find a similar indicator available, and I thought it might be useful for others who are also exploring ETH’s long-term behavior. The bands start from Ethereum’s launch price and are adjustable via input parameters, but they are based on my best effort to align with historical data. With some decent coding experience, I’m sure someone could refine this further—perhaps by optimizing the coefficients or incorporating more advanced fitting techniques. Feel free to tweak the code, suggest improvements, or use it as a starting point for your own projects!
How to Use:
** THIS CHART IS SPECIFICALLY CODED FOR ETH/USD (KRAKEN) ON THE WEEKLY TIMEFRAME IN LOG VIEW**
The main band (blue) represents the logarithmic regression line.
The upper (red) and lower (green) bands provide a range around the main trend, adjustable with multipliers.
Adjust the "Launch Price," "Base Coefficient," "Growth Coefficient," and other inputs to experiment with different fits.
Disclaimer:
This is not financial advice. Use at your own risk, and always conduct your own research before making trading decisions.
Bollinger Bands + RSI StrategyThe Bollinger Bands + RSI strategy combines volatility and momentum indicators to spot trading opportunities in intraday settings. Here’s a concise summary:
Components:
Bollinger Bands: Measures market volatility. The lower band signals potential buying opportunities when the price is considered oversold.
Relative Strength Index (RSI): Evaluates momentum to identify overbought or oversold conditions. An RSI below 30 indicates oversold, suggesting a buy, and above 70 indicates overbought, suggesting a sell.
Strategy Execution:
Buy Signal : Triggered when the price falls below the lower Bollinger Band while the RSI is also below 30.
Sell Signal : Activated when the price exceeds the upper Bollinger Band with an RSI above 70.
Exit Strategy : Exiting a buy position is considered when the RSI crosses back above 50, capturing potential rebounds.
Advantages:
Combines price levels with momentum for more reliable signals.
Clearly defined entry and exit points help minimize emotional trading.
Considerations:
Can produce false signals in very volatile or strongly trending markets.
Best used in markets without a strong prevailing trend.
This strategy aids traders in making decisions based on technical indicators, enhancing their ability to profit from short-term price movements.
Bollinger Bands Weighted Alert System (BBWAS)The idea of this indicator is very similar to my previous published script called BBAS (Bollinger Bands Alert System).
Just with little additions. In this case, we're using a Weighted Moving Average (ta.wma) instead of Simple Moving Average to calculate the basis line.
A breakout in trading refers to a situation where the price of a security or asset moves beyond a defined level of support or resistance, which is typically indicated by technical analysis tools like Bollinger Bands. Bollinger Bands consist of three lines: the upper band, the lower band, and the middle band (or basis). The upper and lower bands are set at a specified number of standard deviations away from the middle band, and they help to define the range within which the price of an asset is expected to fluctuate.
When the price of the asset moves beyond the upper or lower band, it is said to have "broken out" of the range. If the price closes below the lower band, it is considered a bearish breakout, and if it closes above the upper band, it is considered a bullish breakout.
Once a breakout occurs, traders may look for a confirmation signal before entering a trade. In this case, crossing the middle line (or basis) after a breakout may signal a potential trend reversal and a good opportunity to enter a long or short trade, depending on the direction of the breakout.
Dear traders, while we strive to provide you with the best trading tools and resources, we want to remind you to exercise caution and diligence in your investing decisions.
It is important to always do your own research and analysis before making any trades. Remember, the responsibility for your investments ultimately lies with you.
Happy trading!
DEMA Supertrend Bands [Misu]█ Indicator based on DEMA (Double Exponential Moving Average) & Supertrend to show Bands .
DEMA attempts to remove the inherent lag associated with Moving Averages by placing more weight on recent values.
Supertrend aims to detect price trends, it's also used to set protective stops.
█ Usages:
Combining Dema to calculate Supertrend results in nice lower and upper bands.
This can be used to identify potential supports and resistances and set protective stops.
█ Parameters:
Length DEMA: Double Ema lenght used to calculate DEMA. Dema is used by Supertrend indicator.
Length Atr: Atr lenght used to calculate Atr. Atr is used by Supertrend indicator.
Band Mult: Used to calculate Supertrend Bands width.
█ Other Applications:
The mid band can be used to filter bad signals in the manner of a more classical Moving Average.
Bollinger Bands color candlesThis Pine Script indicator applies Bollinger Bands to the price chart and visually highlights candles based on their proximity to the upper and lower bands. The script plots colored candles as follows:
Bullish Close Above Upper Band: Candles are colored green when the closing price is above the upper Bollinger Band, indicating strong bullish momentum.
Bearish Close Below Lower Band: Candles are colored red when the closing price is below the lower Bollinger Band, signaling strong bearish momentum.
Neutral Candles: Candles that close within the bands remain their default color.
This visual aid helps traders quickly identify potential breakout or breakdown points based on Bollinger Band dynamics.
BOLLY BandsThis is a strategy using Bollinger Bands. The strategy is predicated around having low volatility in price action and then looking to capture a move when price starts to trend outside of the Bollinger bands. This strategy has only been backtested for 1 month but it has promising results so I will be sharing it looking for feedback. I run this strategy on the ERUSD 1 min chart.
Percentile Rank of Bollinger BandsThis simple indicator provides you three useful information with Bollinger Bands:
How wide the current width (standard deviation) of the Bollinger Band is.
Compared to the widths in the past, is the current width relatively small or big? Value is expressed in percentile format.
What the "relative position of current price" to the current Bollinger Band is.
This indicator can be useful to identify whether the Bollinger Band has substantially "expanded" or "squeezed."
First, divide the current standard deviation by the current price, we get the current width. The current width is displayed by the columns at the bottom. When the current width becomes wider, the column becomes taller, and the color is dark green. On the contrary, if the width becomes narrower, the column becomes shorter and the color is light green.
Next, compare the current width with the previous N widths, we get the percentile rank for the current width. The percentile rank is shown by the thicker line graph. When the percentile rank grows, it is green; whereas when the rank declines, the color is red.
Lastly, calculate (close - lower)/(upper - lower) and we get an idea of the relative height of the current price, compared to the upper and lower band. This is displayed by the thinner line graph. When the relative position becomes higher, the color is in aqua. It is in blue when the relative position becomes lower. Note that since closing prices can go above the upper band or go below the lower band, the values may be greater than 100 or less than 0.
EMA Bollinger Bands with customized std dev and moving averageTo use EMA with band you need to set input parameter named as "TypeOfMa" to 1.
If you set TypeOfMa = 1 then it will use EMA average for Bollinger bands.
If you set TypeOfMa = 0 then it will use MA average for Bollinger bands.
Z-Score Bands + SignalsZ-Score Statistical Market Analyzer
A multi-dimensional market structure indicator based on standardized deviation & regime logic
English Description
Concept
This indicator builds a statistical model of price behaviour by converting every candle’s movement into a Z-score — how many standard deviations each close is away from its moving average.
It visualizes the normal distribution structure of returns and provides adaptive entry signals for both Mean Reversion and Breakout regimes.
Rather than predicting price direction, it measures statistical displacement from equilibrium and dynamically adjusts the decision logic according to the market’s volatility regime.
⚙️ Main Components
Z-Score Bands (±1σ, ±2σ, ±3σ)
– The core structure visualizes volatility boundaries based on rolling mean and standard deviation.
– Price outside ±2σ often indicates statistical extremes.
Dual Signal Systems
Mean Reversion (MRL / MRS): when price (or return z-score) crosses back inside ±2σ bands.
Breakout (BOL / BOS): when price continues to expand beyond ±2σ.
Volatility Regime Classification
The indicator detects whether the market is currently in a low-vol or high-vol regime using percentile statistics of σ.
Low vol → Mean Reversion preferred
High vol → Breakout preferred
🧠 Adaptive Switches
A. Freeze MA/σ - Use previous-bar stats to avoid repainting and lag.
B. Confirm on Close - Only generate signals once the base-timeframe bar closes (eliminates look-ahead bias).
C. Return-based Signal - Use log-return Z-score instead of price deviation — normalizes volatility across assets.
D. Outlier Filter - Exclude bars with abnormal single-bar returns (e.g., >20%). Reduces false spikes.
E. Regime Gating - Automatically switch between Mean Reversion and Breakout logic depending on volatility percentile.
Each module can be toggled individually to test different statistical behaviours or tailor to a specific market condition.
📊 Interpretation
When the histogram of returns approximates a normal distribution, mean-reversion logic is often more effective.
When price persistently drifts beyond ±2σ or ±3σ, the distribution becomes leptokurtic (fat-tailed) — a breakout structure dominates.
Hence, this tool can help you:
Identify whether an asset behaves more “Gaussian” or “fat-tailed”;
Select the correct trading regime (MR or BO);
Quantitatively measure market tension and volatility clusters.
🧩 Recommended Use
Works on any timeframe and any asset.
Best used on liquid instruments (e.g., XAU/USD, indices, major FX pairs).
Combine with volume, sentiment or structural filters to confirm signals.
For strategy automation, pair with the companion script:
🧠 “Z-Score Strategy • Multi-Source Confirm (MRL/MRS/BOL/BOS)”.
⚠️ Disclaimer
This script is designed for educational and research purposes.
Statistical deviation ≠ directional prediction — use with sound risk management.
Past distribution patterns may shift under new volatility regimes.
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中文说明（简体）
概念简介
该指标基于价格的统计分布原理，将每根 K 线的波动转化为标准化的 Z-Score（标准差偏离值），用于刻画市场处于均衡或偏离状态。
它同时支持 均值回归（Mean Reversion） 与 突破延展（Breakout） 两种逻辑，并可根据市场波动结构自动切换策略模式。
⚙️ 主要功能模块
Z-Score 通道（±1σ / ±2σ / ±3σ）
用滚动均值与标准差动态绘制的统计波动带，价格超出 ±2σ 区域通常意味着极端偏离。
双信号系统
MRL / MRS（均值回归多空）：价格重新回到 ±2σ 以内时触发。
BOL / BOS（突破延展多空）：价格持续运行在 ±2σ 之外时触发。
波动率分层
自动识别市场处于高波动还是低波动区间：
低波动期 → 适合均值回归逻辑；
高波动期 → 适合突破趋势逻辑。
🧠 A–E 模块说明
A. 固定统计参数：使用上一根 K 线的均值和标准差，防止重绘。
B. 收盘确认信号：仅在当前时间框架收盘后生成信号，避免前视偏差。
C. 收益率信号模式：采用对数收益率的 Z-Score，更具普适性。
D. 异常波过滤：忽略单根极端波动（如 >20%）的噪声信号。
E. 波动率调节逻辑：根据市场处于高/低波动区间，自动切换 MRL/MRS 或 BOL/BOS。
📊 应用解读
如果收益率分布接近正态分布 → 市场倾向震荡，MRL/MRS 效果较佳；
若价格频繁偏离 ±2σ 或 ±3σ → 市场呈现“肥尾”分布，趋势延展占主导。
因此，该指标的核心目标是：
识别当前市场的统计结构类型；
根据波动特征自动切换交易逻辑；
提供结构化、可量化的市场状态刻画。
💡 使用建议
适用于所有时间框架与金融品种。
建议结合成交量或结构性指标过滤。
若用于策略回测，可搭配同名 “Z-Score Strategy • Multi-Source Confirm” 策略脚本。
⚠️ 免责声明
本指标仅用于研究与教学，不构成任何投资建议。
统计偏离 ≠ 趋势预测，实际市场行为可能在不同波动结构下改变。
Floating Bands of the Argentine Peso (Sebastian.Waisgold)
The BCRA ( Central Bank of the Argentine Republic ) announced that as of Monday, April 15, 2025, the Argentine Peso (USDARS) will float within a system of divergent exchange rate bands.
The upper band was set at ARS 1400 per USD on 15/04/2025, with a +1% monthly adjustment distributed daily, rising by a fraction each day.
The lower band was set at ARS 1000 per USD on 15/04/2025, with a –1% monthly adjustment distributed daily, falling by a fraction each day.
This indicator is crucial for anyone trading USDARS, since the BCRA will only intervene in these situations:
- Selling : if the Peso depreciates against the USD above the upper band .
- Buying : if the Peso appreciates against the USD below the lower band .
Therefore, this indicator can be used as follows:
- If USDARS is above the upper band , it is “expensive” and you may sell .
- If USDARS is below the lower band , it is “cheap” and you may buy .
It can also be applied to other assets such as:
- USDTARS
- Dollar Cable / CCL (Contado con Liquidación) , derived from the BCBA:YPFD / NYSE:YPF ratio.
A mid band —exactly halfway between the upper and lower bands—has also been added.
Once added, the indicator should look like this:
In the following image you can see:
- Upper Floating Band
- Lower Floating Band
- Mid Floating Band
User Configuration
By double-clicking any line you can adjust:
- Start day (Dia de incio), month (Mes de inicio), and year (Año de inicio)
- Initial upper band value (Valor inicial banda superior)
- Initial lower band value (Valor inicial banda inferior)
- Monthly rate Tasa mensual %)
It is recommended not to modify these settings for the Argentine Peso, as they reflect the BCRA’s official framework. However, you may customize them—and the line colors—for other assets or currencies implementing a similar band scheme.
M2 GLI SD BandsHighly customizable M2 Global Liquidity Index with adaptive standard deviation bands.
The SD bands incorporate data from M2 with varying lags to capture M2's full impact on the price of Bitcoin spread across multiple weeks.
EMAs are used for smoothing. Offset, smoothing, and other features are customizable.
Swing BandsThis indicator is a result of experimentation with price action of candle high and lows for quantifying reversals and trend continuation.
The band area shows trend reversal incoming and possible chop.
Middle line is the trend reversal price level. Candle colors change if the close price is above or below the middle line.
Long and short positions can be taken when above or below the bands.
Trend continuations are in effect when price retraces into the bands and breaks above or below in the same direction of the trend.
