Volatility Stop trading with risk managementQuick coding of a trading system based on the Volatility Stop (VStop) indicator. In addition to that I added the possibility to calculate the position size based on the amount that you want to risk. Beware, this is the amount you want to risk per trade. The total draw-down might be higher, as you can have multiple loosing trades.
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[TH] Volatility BreakoutVolatility Breakout Strategy for TradingHook.
This strategy is not for backtesting but for forward-testing starting when added to chart.
It can make and send a formatted message string for buy and sell order using alert.
Volatility Breakout Strategy [Angel Algo]As traders, we're always looking for opportunities to profit from sudden price breakouts, and the Volatility Breakout Strategy aims to do just that.
This script is the perfect starting point for traders who want to experiment with capturing price movements resulting from increased volatility. The script plots the Average True Range (ATR) on the chart, which is a measure of the asset's volatility over a specified period. By setting the "Length" parameter, you can customize the period over which the volatility is measured.
Using the ATR, the strategy calculates upper and lower breakout levels and plots them on the chart. The signals for long and short positions are generated when the price crosses above the upper breakout level or below the lower breakout level, respectively. They are confirmed by checking the current bar state.
The strategy also fills the space between the upper and lower breakout levels with a color that indicates the latest signal direction. This feature helps traders quickly identify the prevailing trend.
The strategy uses the generated signals to enter trades. When a long or short signal is confirmed, and there is no open position in the direction of the signal, the strategy enters a long or short trade, respectively.
Choice of parameters.
Choosing the right value for the Length input parameter is crucial for tailoring the Volatility Breakout Strategy to suit your trading preferences. In general, a higher Length value implies a focus on capturing longer price moves. For instance, in this script, we have set the Length value to 20, resulting in trades that span approximately 100 candles. These trades encompass price trends consisting of multiple swings.
However, if your goal is to trade individual swings rather than longer trends, it's advisable to experiment with smaller values for the Length parameter. By reducing the Length, you can target shorter-term price movements and potentially increase the frequency of trades.
It's important to note that while a higher Length value tends to lead to longer trades, there is no strict correlation between the Length parameter and the average length of trades. This can vary across different markets. Therefore, it's essential to conduct thorough experimentation with various Length values and closely observe the length of trades they generate. Comparing these trade lengths with the average trend or swing length in the specific market can provide valuable insights.
Ideally, you should aim to select a Length value that aligns with the average trend or swing length observed in the market you are trading. This way, you can optimize the strategy to capture price movements that closely match the prevailing market conditions.
Remember, finding the optimal Length value is a process of trial and error, combined with careful observation of trade lengths and their correlation with market trends. So, don't be afraid to experiment and refine the Length parameter to maximize the effectiveness of the Volatility Breakout Strategy in your chosen market.
Disclaimer: This trading strategy is provided for educational and informational purposes only.Trading involves risk, and past performance is not indicative of future results.
Volatility Stop Strategy (by Coinrule)Traders often use the volatility stop to protect trades dynamically, adjusting the stop price gradually based on the asset's volatility.
Just like the volatility stop is a great way to capture trend reversals on the downside, the opposite applies as well. Therefore, another useful application of the volatility stop is to add it to a trading system to signal potential trend reversals to catch a good buy opportunity.
ENTRY
- When the price crosses above the Volatility Stop
EXIT
- When the price crosses below the Volatility Stop
For this strategy, the Volatility stop's multiplier is set to 3 to allow more flexibility to the trade. The strategy is designed for medium-term trades.
Based on the backtest result from a sample of crypto trading pairs, the most profitable time frame is the 2-hr.
The strategy works well with both crypto-to-crypto and crypto-to-fiat pairs. To make results more realistic, a trading fee of 0.1% is added to the script. The fee is aligned to the base fee applied on Binance.
Volatility SkewThis indicator measure the historical skew of actual volatility for an individual security. It measure the volatility of up moves versus down moves over the period and gives a ratio. When the indicator is greater than one, it indicators that volatility is greater to the upside, when it is below 1 it indicates that volatility is skewed to the downside.
This is not comparable to the SKEW index, since that measures the implied volatility across option strikes, rather than using historical volatility.
Volatility RegimeThis is a useful volatility indicator to be used on a Daily time Frame
and paired with the Market Regime indicator.
Gray means that the markets have low volatility (calm) and might be consolidating before resuming or reversing the trend.
Teal means that volatility is somewhere around the average.
And Yellow means it has spiked up and we are in a high volatility regime.
When you pair it with the Market Regime filter for Bull/Bear markets you will
find that the best bull markets start from low volatility and mature on high volatility.
More often than not, the top comes when The Market Regime is very strong (Super Bull)
and volatility is high.
Similarly, the bottom arrives when the Market Regime is very bearish (Super Bear)
and volatility is high.
Volatility Index of Range Verification█ OVERVIEW
This is a volatility indicator created by extending concepts from Tushar Chande's Range Action Verification Index (RAVI).
█ CONCEPTS
This indicator constructs range of the RAVI indicator. It uses this range to build a histogram that represents how fast the range is changing, or a measure of volatility. A line is then constructed, either from a moving average or standard deviation depending on the settings that can serve as an action trigger.
█ INPUTS
• Fast MA Period: the period of the quickest moving average that is used to build the RAVI indicator line
• Slow MA Period: the period of the slowest moving average that is used to build the RAVI indicator line
• MA Type: the type of moving average to use, either Simple or Exponential
• Price Source: the type of price source to use; close, high, low, hlc3, etc.
• Lookback Period: how far back to construct the minimum and maximum of the range
• Standard Range: the standard range of the indicator. a smaller range will exaggerate differences in the columns, and vice-versa
• Volatility Period: the period used for the trigger line moving average
• Std. Deviation Mode?: Whether the trigger line will plot using a moving average or a multiple of Standard Deviation.
• Deviation Multiplier: How many deviations to use if the trigger line is in Std. Deviation Mode
K's Volatility BandsVolatility bands come in all shapes and forms contrary to what is believed. Bollinger bands remain the principal indicator in the volatility bands family. K's Volatility bands is an attempt at optimizing the original bands. Below is the method of calculation:
* We must first start by calculating a rolling measure based on the average between the highest high and the lowest low in the last specified lookback window. This will give us a type of moving average that tracks the market price. The specificity here is that when the market does not make higher highs nor lower lows, the line will be flat. A flat line can also be thought of as a magnet of the price as the ranging property could hint to a further sideways movement.
* The K’s volatility bands assume the worst with volatility and thus will take the maximum volatility for a given lookback period. Unlike the Bollinger bands which will take the latest volatility calculation every single step of time, K’s volatility bands will suppose that we must be protected by the maximum of volatility for that period which will give us from time to time stable support and resistance levels.
Therefore, the difference between the Bollinger bands and K's volatility bands are as follows:
* Bollinger Bands' formula calculates a simple moving average on the closing prices while K's volatility bands' formula calculates the average of the highest highs and the lowest lows.
* Bollinger Bands' formula calculates a simple standard deviation on the closing prices while K's volatility bands' formula calculates the highest standard deviation for the lookback period.
Applying the bands is similar to applying any other volatility bands. We can list the typical strategies below:
* The range play strategy : This is the usual reversal strategy where we buy whenever the price hits the lower band and sell short whenever it hits the upper band.
* The band re-entry strategy : This strategy awaits the confirmation that the price has recognized the band and has shaped a reaction around it and has reintegrated the whole envelope. It may be slightly lagging in nature but it may filter out bad trades.
* Following the trend strategy : This is a controversial strategy that is the opposite of the first one. It assumes that whenever the upper band is surpassed, a buy signal is generated and whenever the lower band is broken, a sell signal is generated.
* Combination with other indicators : The bands can be combined with other technical indicators such as the RSI in order to have more confirmation. This is however no guarantee that the signals will improve in quality.
* Specific strategy on K’s volatility bands : This one is similar to the first range play strategy but it adds the extra filter where the trade has a higher conviction if the median line is flat. The reason for this is that a flat line means that no higher highs nor lower lows have been made and therefore, we may be in a sideways market which is a fertile ground for mean-reversion strategies.
Volatility-Volume Index (VVI)Volatility-Volume Index (VVI) – Indicator Description
The Volatility-Volume Index (VVI) is a custom trading indicator designed to identify market consolidation and anticipate breakouts by combining volatility (ATR) and trading volume into a single metric.
How It Works
Measures Volatility : Uses a 14-period Average True Range (ATR) to gauge price movement intensity.
Tracks Volume : Monitors trading activity to identify accumulation or distribution phases.
Normalization : ATR and volume are normalized using their respective 20-period Simple Moving Averages (SMA) for a balanced comparison.
Interpretation
VVI < 1: Low volatility and volume → Consolidation phase (range-bound market).
VVI > 1: Increased volatility and/or volume → Potential breakout or trend continuation.
How to Use VVI
Detect Consolidation:
Look for extended periods where VVI remains below 1.
Confirm with sideways price movement in a narrow range.
Anticipate Breakouts:
A spike above 1 signals a possible trend shift or breakout.
Why Use VVI?
Unlike traditional volatility indicators (ATR, Bollinger Bands) or volume-based tools (VWAP), VVI combines both elements to provide a clearer picture of consolidation zones and breakout potential.
Volatility Arbitrage Spread Oscillator Model (VASOM)The Volatility Arbitrage Spread Oscillator Model (VASOM) is a systematic approach to capitalizing on price inefficiencies in the VIX futures term structure. By analyzing the differential between front-month and second-month VIX futures contracts, we employ a momentum-based oscillator (Relative Strength Index, RSI) to signal potential market reversion opportunities. Our research builds upon existing financial literature on volatility risk premia and contango/backwardation dynamics in the volatility markets (Zhang & Zhu, 2006; Alexander & Korovilas, 2012).
Volatility derivatives have become essential tools for managing risk and engaging in speculative trades (Whaley, 2009). The Chicago Board Options Exchange (CBOE) Volatility Index (VIX) measures the market’s expectation of 30-day forward-looking volatility derived from S&P 500 option prices (CBOE, 2018). Term structures in VIX futures often exhibit contango or backwardation, depending on macroeconomic and market conditions (Alexander & Korovilas, 2012).
This strategy seeks to exploit the spread between the front-month and second-month VIX futures as a proxy for term structure dynamics. The spread’s momentum, quantified by the RSI, serves as a signal for entry and exit points, aligning with empirical findings on mean reversion in volatility markets (Zhang & Zhu, 2006).
• Entry Signal: When RSI_t falls below the user-defined threshold (e.g., 30), indicating a potential undervaluation in the spread.
• Exit Signal: When RSI_t exceeds a threshold (e.g., 70), suggesting mean reversion has occurred.
Empirical Justification
The strategy aligns with findings that suggest predictable patterns in volatility futures spreads (Alexander & Korovilas, 2012). Furthermore, the use of RSI leverages insights from momentum-based trading models, which have demonstrated efficacy in various asset classes, including commodities and derivatives (Jegadeesh & Titman, 1993).
References
• Alexander, C., & Korovilas, D. (2012). The Hazards of Volatility Investing. Journal of Alternative Investments, 15(2), 92-104.
• CBOE. (2018). The VIX White Paper. Chicago Board Options Exchange.
• Jegadeesh, N., & Titman, S. (1993). Returns to Buying Winners and Selling Losers: Implications for Stock Market Efficiency. The Journal of Finance, 48(1), 65-91.
• Zhang, C., & Zhu, Y. (2006). Exploiting Predictability in Volatility Futures Spreads. Financial Analysts Journal, 62(6), 62-72.
• Whaley, R. E. (2009). Understanding the VIX. The Journal of Portfolio Management, 35(3), 98-105.
Volatility Range Breakout Strategy [wbburgin]The "Volatility Range Breakout Strategy" uses deviations of high-low volatility to determine bullish and bearish breakouts.
HOW IT WORKS
The volatility function uses the high-low range of a lookback period, divided by the average of that range, to determine the likelihood that price will break in a specific direction.
High and low ranges are determined by the relative volatility compared to the current closing price. The high range, for example, is the (volatility * close) added to the close, the low range is this value subtracted by the close.
A volatility-weighted moving average is taken of these high and low ranges to form high and low bands.
Finally, breakouts are identified once the price closes above or below these bands. An upwards breakout (bullish) occurs when the price breaks above the upper band, while a downwards breakout (bearish) occurs when the price breaks below the lower band. Positions can be closed either by when the price falls out of its current band ("Range Crossover" in settings under 'Exit Type') or when the price falls below or above the volatility MA (default because this allows us to catch trends for longer).
INPUTS/SETTINGS
The AVERAGE LENGTH is the period for the volatility MA and the weighted volatility bands.
The VOLATILITY LENGTH is how far the lookback should be for highs/lows for the volatility calculation.
Enjoy! Let me know if you have any questions.
Volatility Percentile🎲 Volatility is an important measure to be included in trading plan and strategy. Strategies have varied outcome based on volatility of the instruments in hand.
For example,
🚩 Trend following strategies work better on low volatility instruments and reversal patterns work better in high volatility instruments. It is also important for us to understand the median volatility of an instrument before applying particular strategy strategy on them.
🚩 Different instrument will have different volatility range. For instance crypto currencies have higher volatility whereas major currency pairs have lower volatility with respect to their price. It is also important for us to understand if the current volatility of the instrument is relatively higher or lower based on the historical values.
This indicator is created to study and understand more about volatility of the instruments.
⬜ Process
▶ Volatility metric used here is ATR as percentage of price. Other things such as bollinger bandwidth etc can also be used with few changes.
▶ We use array based counters to count ATR values in different range. For example, if we are measuring ATR range based on precision 2, we will use array containing 10000 values all initially set to 0 which act as 10000 buckets to hold counters of different range. But, based on the ATR percentage range, they will be incremented. Let's say, if atr percent is 2, then 200th element of the array is increased by 1.
▶ When we do this for every bar, we have array of counters which has the division on how many bars had what range of atr percent.
▶ Using this array, we can calculate how many bars had atr percent more than current value, how many had less than current value, and how many bars in history has same atr percent as current value.
▶ With these information, we can calculate the percentile of atr percentage value. We can also plot a detailed table mentioning what percentile each range map to.
⬜ Settings
▶ ATR Parameters - this include Moving average type and Length for atr calculation.
▶ Rounding type refers to rounding ATR percentage value before we put into certain bucket. For example, if ATR percentage 2.7, round or ceil will make it 3, whereas floor will make it 2 which may fall into different buckets based on the precision selected.
▶ Precision refers to how much detailed the range should be. If precision set to 0, then we get array of 100 to collect the range where each value will represent a range of 1%. Similarly precision of 1 will lead to array of 1000 with each item representing range of 0.1. Default value used is 2 which is also the max precision possible in this script. This means, we use array of 10000 to track the range and percentile of the ATR.
▶ Display Settings - Inverse when applied track percentile with respect to lowest value of ATR instead of high. By default this is set to false. Other two options allow users to enable stats table. When detailed stats are enabled, ATR Percentile as plot is hidden.
▶ Table Settings - Allows users to select set size and coloring options.
▶ Indicator Time Window - Allow users to select particular timeframe instead of all available bars to run the study. By default windows are disabled. Users can chose start and end time individually.
Indicator display components can be described as below:
Volatility & Momentum Nexus (VMN)Volatility & Momentum Nexus (VMN)
This indicator was designed to solve a common trader's problem: chart clutter from dozens of indicators that often contradict each other. The Volatility & Momentum Nexus ( VMN ) is not just another indicator; it's a complete analysis system that synthesizes four essential market pillars into a single, clean, and intuitive visual signal.
The goal of VMN is to identify high-probability moments where a period of accumulation (low volatility) is about to erupt into an explosive move, confirmed by trend, momentum, and volume.
VMN analyzes the real-time confluence of four critical elements:
The Trend (The Main Filter): A 100-period Exponential Moving Average (EMA) sets the overall context. The indicator will only look for buy signals above this line (in an uptrend) and sell signals below it (in a downtrend). The line's color changes for quick visualization.
Volatility (Energy Accumulation): Using Bollinger Bands Width (BBW), the indicator identifies "Squeeze" periods—when the price contracts and builds up energy. These zones are marked with a yellow background on the chart, signaling that a major move is imminent.
Momentum (The Trigger): An RSI (Relative Strength Index) acts as the trigger. A signal is only validated if momentum confirms the direction of the breakout (e.g., RSI > 55 for a buy), ensuring we enter the market with force.
Volume (The Final Confirmation): No breakout move is credible without volume. VMN checks if the volume at the time of the signal is significantly higher than its recent average, adding a vital layer of confirmation.
Green Arrow (Buy Signal): Appears ONLY when ALL the following conditions are met simultaneously:
Price is above the 100 EMA (Bullish Trend).
The chart is exiting a Squeeze zone (yellow background on the previous bar).
Price breaks above the upper Bollinger Band.
RSI is above the buy threshold (default 55).
Volume is above average.
Red Arrow (Sell Signal): Appears ONLY when all the opposite conditions are met.
Do not treat signals as blind commands to trade. They are high-probability confirmations.
Look for signals near key Support/Resistance levels for an even higher success rate.
Always set a Stop Loss (e.g., below the low of the signal candle or below the lower Bollinger Band for a buy).
All parameters (EMA, RSI, Bollinger Bands lengths, thresholds, etc.) can be customized from the settings menu to adapt the indicator to any financial asset or timeframe.
Disclaimer: This indicator is a tool for educational and analytical purposes. It does not constitute and should not be interpreted as financial advice. Trading involves significant risk. Always perform your own analysis and backtesting before risking real capital.
Volatility IndexThis indicator is based on Historical Volatility (HV) built-in indicator with minor tweaks to match the Bitcoin Volatility Index (from Bybt).
Also, you can select a symbol to compare its volatility with the volatility of the currently selected symbol.
Volatility of Volatility MA - LayeringProvides a volatility of volatility moving average to show trends in Vol of Vol. Meant to be used with Volume MA, and Volatility MA, layered on top of eachother.
Volatility GuppyBased on my previous script "Turtle N Normalized," this script plots the CM SuperGuppy on the value of N to identify changing trends in the volatility of any instrument.
Turtle rules taken from an online PDF:
"The Turtles used a concept that Richard Dennis and Bill Eckhardt called N to represent the underlying volatility of a particular market.
N is simply the 20-day exponential moving average of the True Range, which is now more commonly known as the ATR. Conceptually, N represents the average range in price movement that a particular market makes in a single day, accounting for opening gaps. N was measured in the same points as the underlying contract.
The Turtles built positions in pieces which we called Units. Units were sized so that 1 N represented 1% of the account equity. Thus, a unit for a given market or commodity can be calculated using the following formula:
Unit = 1% of Account/(N x Dollars per Point)"
To normalize the Unit formula, this script instead takes the value of (close/N). Dollars per point = 1 for stocks and crypto, but will change depending on the contract specifications for individual futures .
"Since the Turtles used the Unit as the base measure for position size, and since those units were volatility risk adjusted, the Unit was a measure of both the risk of a position, and of the entire portfolio of positions."
When the EMA's are green, volatility is decreasing.
When the EMA's are red, volatility is increasing.
When the EMA's are grey, the trend is changing.
Volatility Across CoinsCompare the recent volatility of 8 cryptocurrencies, based on percentage change per candle.
Useful for volatility strategies to find the highest volatility coins over recent periods or to get an at-a-glance view of volatility correlations.
Options to change the resolution and find average % change per candle over user defined length.
Key:
BTC = Yellow/Gold
ETH = Purple
LTC = Gray
NEO = Green
IOTA = Light Blue
XMR = Orange
BCH = Red
Dash = Blue
Volatility Strategy 01a quantitative volatility strategy (especially effective in trend direction on the 15min chart on the s&p-index)
the strategy is a rule-based setup, which dynamically adapts to the implied volatility structure (vx1!–vx2!)
context-dependent mean reversion strategy based on multiple timeframes in the vix index
a signal is provided under following conditions:
1. the vvix/vix spread has deviated significantly beyond one standard deviation
2. the vix is positioned above or below 3 moving averages on 3 minor timeframes
3. the trade direction is derived from the projected volatility regime, measured via vx1! and vx2! (cboe)
Volatility Adjusted Grid [Gann]█ OVERVIEW
Gann Square of 9 is one of the many brilliant concepts from W.D.Gann himself where it revolves around the idea that price is moving in a certain geometrical pattern. Numbers on the Square of 9 spiral tables, especially those lie in every 45degree in the chart act as key vibration levels where prices have tendency to react to (more on the table below).
There are few square of 9 related scripts here in Tradingview and while there's nothing wrong with them, it doesn't address 1 particular issue that i have: The numbers can be too rigid even when scaled based on current price because the levels are fixed, which makes them not tradable on certain timeframes depending on where the price currently sitting.
Heres 5min and 1hour Bitcoin chart to illustrate what i mean: Grey line on the left is based on Volatility Adjusted levels, while red/blue on the right are the standard Gann levels.
You can see that on 1hour chart, it provides a good levels (both Volatility Adjusted and the standard one happened to share the same multiplier in this case),
1Hour Chart:
On 5 min chart tells a different story as the range between blue/red levels can be deemed as to big for a short term trade, while the grey line is adjusted to suit that particular timeframe (You can still adjust to make it bigger/smaller from the settings, more on this below)
5Min Chart:
█ Little bit on Gann Square of 9 table
This is the square of nine table, the numbers highlighted in Red are known as Cardinal Cross and considered to be a major Support/Resistance while those in Blue color are known as Ordinal Cross considered as minor (but still important) Support/Resistance levels
Similarly, this script use these numbers (and certain multipliers) to print out the levels, with Cardinal numbers represented by solid lines and Ordinal numbers by dotted lines.
█ How it Works and Limitations
The Volatility Adjusted grid will go through several iterations of different multipliers to find the Gann number range that is at least bigger than times ATR. Because it's using ATR to determine the range, occasionally you'll notice that the line become smaller as ATR contracting (and vice versa). To overcome this, you can change the size range multiplier from the settings to retrieve the previous range size.
Use the size guide at the bottom left to find the multiplier that suits your need:
1st Row -> Previous Range -- Change Range Size to number lower than this to get a smaller range
2nd Row -> Next Range -- Change Range Size to number higher than this to get a larger range
Example:
Before:
After:
As you'll soon realise, the key here is to find the range that fits the historical structure and suits your own strategy. Enjoy :)
█ Disclaimer
Past performance is not an indicator of future results.
My opinions and research are my own and do not constitute financial advice in any way whatsoever.
Nothing published by me constitutes an investment recommendation, nor should any data or Content published by me be relied upon for any investment/trading activities.
I strongly recommends that you perform your own independent research and/or speak with a qualified investment professional before making any financial decisions.
Any ideas to further improve this indicator are welcome :)
Volatility IndicatorThe Volatility Index measures the market volatility by plotting a smoothed average of the True Range.
Based on HPotter's idea (),
it returns an average of the TrueRange over a specific number of bars.
Here the result is passed through the Fisher's transform and normalized to 0/1-range.
This indicator may be used to identify stretches in the price movements, suitable for entry.
Volatility SystemDespite its crude name, the volatility system strategy, described by Richard Bookstaber in 1984, follows the simple premise that once there is a big volatile movement, the market tends to follow it. Thus, it uses the ATR to measure the volatility, and issues orders when the current change of the closing price exceeds the threshold, calculated by the ATR times a configurable constant.
It yields good results for some very specific charts, as you can see. However, I doubt it would work in the current market conditions, since it has no stop loss and no take profit , and the current noise levels obliterate this strategy, especially in small time frames. Maybe their integration to the strategy would yield better results, so feel free to add your own modifications.
Volatility MeasureThis indicator is super simple, it gives you the average amount of volatility (IN PERCENT) in any given asset over any given timeframe over the last 100 periods. Adjustable. This is useful for gauging volatility, risk, reward, opportunity set, and more. It can help you set stop losses, tell how much risk you are actually taking based on historical measures, and how much of what you do is based on skill or luck. Enjoy!
Pholesolus
Simplest volatility bandsVolatility bands based on average candle percentage spread. Tested on BTCUSD charts only.
Based on the 68-95-99.7 rule, it seems that the spread, for daily and 4-H candles, follows a normal distribution: that means, around 85% of candles have a %-spread within sma(low/high, some_len) and sma(high/low, some_len) , and around 95% of candles within the pow2 of that range.
If you take the mean between the boundaries of the first %-spreads band, and calculate the 1.5 standard deviation of past some_len candles (I'm speaking from memory, it has been a while since I did them), the 1.5 standard deviation bands match similarly the %-spread bands, and around 85% of the candles are within these %-spread bands.
If you then take the pow2 of the bands, it will be similar to the 2 * std of the original bands, with around 95% of data within the pow2 bands.
You can take ema or other similar means with similar results, and the same for different lengths, but it seems that sma with a len of 14 is the more stable ones for both daily and 4-H, and taken other average calculations doesn't cause too many differences respect to the sma. I haven't tested too much for lower or higher timeframes.
With those %-spread bands, I multiple and divide those spreads to the open value of a new candle to get the two bands.
So, in short, you know that 85% of candles are within the closer bands, and around 95% of candles, around the bigger one. Once a new candle is born, the bands won't move (the bands are calculated from the previous candle, so the current candle's price movement doesn't move the band).
Going out the bands implies a sudden increase in volality, which usually causes rejection. They happen mostly at breakouts and ends of heavy trends. If a candle closes above the bigger band, you have probably got a breakout (a rejection rarely happens if the candle have already closed), although a breakout can happen without closing above the bands if volatility was already high.
If a trend is already stablished and is healthy, you won't probably see candles going out the bands, not even with a wick. When the trend is parabolic, and goes above the candle, the trend has probably ended, although the trend can be exhausted without going out the bands as well.
Heavy but not yet exhausted trends (specially recently started heavy downtrends), usually reach the bottom of the bigger bands during 4 o 5 contiguous candles (check visually looking at bitcoin history though, I'm speaking from memory).
So, the possibilities are multiple and you cannot use the bands to form a strategy, as usual. It can be comfortable enough psycologically for going to sleep, by moving your stop-loss to a point out of the bands in the opposite direction of your trade, and adjusting your position size accordingly; or just to check momentum looking at how close are the candle limits to the bands.
But, as usual, you are responsible of what you do with your money :)
