Return Volatility (σ) — auto-annualized [v6]Overview
This indicator calculates and visualizes the return-based volatility (standard deviation) of any asset, automatically adjusting for your chart's timeframe to provide both absolute and annualized volatility values.
It’s designed for traders who want to filter trades, adjust position sizing, and detect volatility events based on statistically significant changes in market activity.
Key Features
Absolute Volatility (abs σ%) – Standard deviation of returns for the current timeframe (e.g., 1H, 4H, 1D).
Annualized Volatility (ann σ%) – Converts abs σ% into an annualized figure for easier cross-timeframe and cross-asset comparison.
Relative Volatility (rel σ) – Ratio of current volatility to the long-term average (default: 120 periods).
Z-Score – Number of standard deviations the current volatility is above or below its historical average.
Auto-Timeframe Adjustment – Detects your chart’s bar size (seconds per bar) and calculates bars/year automatically for crypto’s 24/7 market.
Highlight Mode – Optional yellow background when volatility exceeds set thresholds (rel σ ≥ threshold OR z-score ≥ threshold).
Alert Conditions – Alerts trigger when relative volatility or z-score exceed defined limits.
How It Works
Return Calculation
Log returns: ln(Pt / Pt-1) (default)
or Simple returns: (Pt / Pt-1) – 1
Volatility Measurement
Standard deviation of returns over the lookback period N (default: 20 bars).
Absolute volatility = σ × 100 (% per bar).
Annualization
Uses: σₐₙₙ = σ × √(bars/year) × 100 (%)
Bars/year auto-calculated based on timeframe:
1H = 8,760 bars/year
4H ≈ 2,190 bars/year
1D = 365 bars/year
Relative and Statistical Context
Relative σ = Current σ / Historical average σ (baseLen, default: 120)
Z-score = (Current σ – Historical average σ) / Std. dev. of σ over baseLen
Trading Applications
Volatility Filter – Only allow trade entries when volatility exceeds historical norms (trend traders often benefit from this).
Risk Management – Reduce position size during high volatility spikes to manage risk; increase size in low-volatility trending environments.
Market Scanning – Identify assets with the highest relative volatility for momentum or breakout strategies.
Event Detection – Highlight significant volatility surges that may precede large moves.
Suggested Settings
Lookback (N): 20 bars for short/medium-term trading.
Base Length (M): 120 bars to establish long-term volatility baseline.
Relative Threshold: 1.5× baseline σ.
Z-score Threshold: ≥ 2.0 for statistically significant volatility shifts.
Use Log Returns: Recommended for more consistent scaling across prices.
Notes & Limitations
Volatility measures movement magnitude, not direction. Combine with trend or momentum filters for directional bias.
Very low volatility may still produce false breakouts; combine with volume and market structure analysis.
Crypto markets trade 24/7 — annualization assumes no market closures; adjust for other asset classes if needed.
💡 Best Practice: Use this indicator as a pre-trade filter for breakout or trend-following strategies, or as a risk control overlay in mean-reversion systems.
Cerca negli script per "Volatility"
[LeonidasCrypto]EMA with Volatility GlowEMA Volatility Glow - Advanced Moving Average with Dynamic Volatility Visualization
Overview
The EMA Volatility Glow indicator combines dual exponential moving averages with a sophisticated volatility measurement system, enhanced by dynamic visual effects that respond to real-time market conditions.
Technical Components
Volatility Calculation Engine
BB Volatility Curve: Utilizes Bollinger Band width normalized through RSI smoothing
Multi-stage Noise Filtering: 3-layer exponential smoothing algorithm reduces market noise
Rate of Change Analysis: Dual-timeframe RoC calculation (14/11 periods) processed through weighted moving average
Dynamic Normalization: 100-period lookback for relative volatility assessment
Moving Average System
Primary EMA: Default 55-period exponential moving average with volatility-responsive coloring
Secondary EMA: Default 100-period exponential moving average for trend confirmation
Trend Analysis: Real-time bullish/bearish determination based on EMA crossover dynamics
Visual Enhancement Framework
Gradient Band System: Multi-layer volatility bands using Fibonacci ratios (0.236, 0.382, 0.618)
Dynamic Color Mapping: Five-tier color system reflecting volatility intensity levels
Configurable Glow Effects: Customizable transparency and intensity settings
Trend Fill Visualization: Directional bias indication between moving averages
Key Features
Volatility States:
Ultra-Low: Minimal market movement periods
Low: Reduced volatility environments
Medium: Normal market conditions
High: Increased volatility phases
Extreme: Exceptional market stress periods
Customization Options:
Adjustable EMA periods
Configurable glow intensity (1-10 levels)
Variable transparency controls
Toggleable visual components
Customizable gradient band width
Technical Calculations:
ATR-based gradient bands with noise filtering
ChartPrime-inspired multi-layer fill system
Real-time volatility curve computation
Smooth color gradient transitions
Applications
Trend Identification: Dual EMA system for directional bias assessment
Volatility Analysis: Real-time market stress evaluation
Risk Management: Visual volatility cues for position sizing decisions
Market Timing: Enhanced visual feedback for entry/exit consideration
Volatility-Adjusted Momentum Score (VAMS) [QuantAlgo]🟢 Overview
The Volatility-Adjusted Momentum Score (VAMS) measures price momentum relative to current volatility conditions, creating a normalized indicator that identifies significant directional moves while filtering out market noise. It divides annualized momentum by annualized volatility to produce scores that remain comparable across different market environments and asset classes.
The indicator displays a smoothed VAMS Z-Score line with adaptive standard deviation bands and an information table showing real-time metrics. This dual-purpose design enables traders and investors to identify strong trend continuation signals when momentum persistently exceeds normal levels, while also spotting potential mean reversion opportunities when readings reach statistical extremes.
🟢 How It Works
The indicator calculates annualized momentum using a simple moving average of logarithmic returns over a specified period, then measures annualized volatility through the standard deviation of those same returns over a longer timeframe. The raw VAMS score divides momentum by volatility, creating a risk-adjusted measure where high volatility reduces scores and low volatility amplifies them.
This raw VAMS value undergoes Z-Score normalization using rolling statistical parameters, converting absolute readings into standardized deviations that show how current conditions compare to recent history. The normalized Z-Score receives exponential moving average smoothing to create the final VAMS line, reducing false signals while preserving sensitivity to meaningful momentum changes.
The visualization includes dynamically calculated standard deviation bands that adjust to recent VAMS behavior, creating statistical reference zones. The information table provides real-time numerical values for VAMS Z-Score, underlying momentum percentages, and current volatility readings with trend indicators.
🟢 How to Use
1. VAMS Z-Score Bands and Signal Interpretation
Above Mean Line: Momentum exceeds historical averages adjusted for volatility, indicating bullish conditions suitable for trend following
Below Mean Line: Momentum falls below statistical norms, suggesting bearish conditions or downward pressure
Mean Line Crossovers: Primary transition signals between bullish and bearish momentum regimes
1 Standard Deviation Breaks: Strong momentum conditions indicating statistically significant directional moves worth following
2 Standard Deviation Extremes: Rare momentum readings that often signal either powerful breakouts or exhaustion points
2. Information Table and Market Context
Z-Score Values: Current VAMS reading displayed in standard deviations (σ), showing how far momentum deviates from its statistical norm
Momentum Percentage: Underlying annualized momentum displayed as percentage return, quantifying the directional strength
Volatility Context: Current annualized volatility levels help interpret whether VAMS readings occur in high or low volatility environments
Trend Indicators: Directional arrows and change values provide immediate feedback on momentum shifts and market transitions
3. Strategy Applications and Alert System
Trend Following: Use sustained readings beyond the mean line and 1σ band penetrations for directional trades, especially when VAMS maintains position in upper or lower statistical zones
Mean Reversion: Focus on 2σ extreme readings for contrarian opportunities, particularly effective in sideways markets where momentum tends to revert to statistical norms
Alert Notifications: Built-in alerts for mean crossovers (regime changes), 1σ breaks (strong signals), and 2σ touches (extreme conditions) help monitor multiple instruments for both continuation and reversal setups
Volatility Breaker Blocks [BigBeluga]The Volatility Breaker Blocks indicator identifies key market levels based on significant volatility at pivot highs and lows. It plots blocks that act as potential support and resistance zones, marked in green (support) and blue (resistance). Even after a breakout, these blocks leave behind shadow boxes that continue to impact price action. The sensitivity of block detection can be adjusted in the settings, allowing traders to customize the identification of volatility breakouts. The blocks print triangle labels (up or down) after breakouts, indicating potential areas of interest.
🔵 IDEA
The Volatility Breaker Blocks indicator is designed to highlight key areas in the market where volatility has created significant price action. These blocks, created at pivot highs and lows with increased volatility, act as potential support and resistance levels.
The idea is that even after price breaks through these blocks, the remaining shadow boxes continue to influence price movements. By focusing on volatility-driven pivot points, traders can better anticipate how price may react when it revisits these areas. The indicator also captures the natural tendency for price to retest broken resistance or support levels.
🔵 KEY FEATURES & USAGE
◉ High Volatility Breaker Blocks:
The indicator identifies areas of high volatility at pivot highs and lows, plotting blocks that represent these zones. Green blocks represent support zones (identified at pivot lows), while blue blocks represent resistance zones (identified at pivot highs).
Support:
Resistance:
◉ Shadow Blocks after Breakouts:
When price breaks through a block, the block doesn't disappear. Instead, it leaves behind a shadow box, which can still influence future price action. These shadow blocks act as secondary support or resistance levels.
If the price crosses these shadow blocks, the block stops extending, and the right edge of the box is fixed at the point where the price crosses it. This feature helps traders monitor important price levels even after the initial breakout has occurred.
◉ Triangle Labels for Breakouts:
After the price breaks through a volatility block, the indicator prints triangle labels (up or down) at the breakout points.
◉ Support and Resistance Retests:
One of the key concepts in this indicator is the retesting of broken blocks. After breaking a resistance block, price often returns to the shadow box, which then acts as support. Similarly, after breaking a support block, price tends to return to the shadow box, which becomes a resistance level. This concept of price retesting and bouncing off these levels is essential for understanding how the indicator can be used to identify potential entries and exits.
The natural tendency of price to retest broken resistance or support levels.
Additionaly indicator can display retest signals of broken support or resistance
◉ Customizable Sensitivity:
The sensitivity of volatility detection can be adjusted in the settings. A higher sensitivity captures fewer but more significant breakouts, while a lower sensitivity captures more frequent volatility breakouts. This flexibility allows traders to adapt the indicator to different trading styles and market conditions.
🔵 CUSTOMIZATION
Calculation Window: Defines the window of bars over which the breaker blocks are calculated. A larger window will capture longer-term levels, while a smaller window focuses on more recent volatility areas.
Volatility Sensitivity: Adjusts the threshold for volatility detection. Lower sensitivity captures smaller breakouts, while higher sensitivity focuses on larger, more significant moves.
Retest Signals: Display or hide retest signals of shadow boxes
Volatility Projection Levels (VPL)### Indicator Name: **Volatility Projection Levels (VPL)**
### Description:
The **Volatility Projection Levels (VPL)** indicator is a powerful tool designed to help traders anticipate key support and resistance levels for the E-mini S&P 500 (ES) by leveraging the CBOE Volatility Index (^VIX). This indicator utilizes historical volatility data to project potential price movements for the upcoming month, offering clear visual cues that enhance swing trading strategies.
### Key Features:
- **Volatility-Based Projections**: The VPL indicator uses the previous month’s closing value of the VIX, normalizing it for monthly analysis by dividing by the square root of 12. This calculated percentage is then applied to the E-mini S&P 500’s closing price from the last day of the previous month.
- **Upper and Lower Projection Levels**: The indicator calculates two essential levels:
- **Upper Projection Level**: The previous month’s closing price of the E-mini S&P 500 plus the calculated volatility percentage.
- **Lower Projection Level**: The previous month’s closing price of the E-mini S&P 500 minus the calculated volatility percentage.
- **Continuous Visualization**: The VPL indicator plots these projection levels on the chart throughout the entire month, providing traders with a consistent reference for potential support and resistance zones. This continuous visualization allows for better anticipation of market movements.
- **Previous Month's Close Reference**: Additionally, the indicator plots the previous month’s closing price as a reference point, offering further context for current price action.
### Use Cases:
- **Swing Trading**: The VPL indicator is ideal for swing traders looking to exploit predicted price ranges within a monthly timeframe.
- **Support & Resistance Identification**: It aids traders in identifying critical levels where the market may encounter support or resistance, thus informing entry and exit decisions.
- **Risk Management**: By forecasting potential price levels, traders can set more strategic stop-loss and take-profit levels, enhancing risk management.
### Summary:
The **Volatility Projection Levels (VPL)** indicator equips traders with a forward-looking tool that incorporates volatility data into market analysis. By projecting key price levels based on historical VIX data, the VPL indicator enhances decision-making, helping traders anticipate market movements and optimize their trading strategies.
Made by Serpenttrading
Volatility Estimator - YZ & RSThe Yang-Zheng Volatility Estimator (YZVE) integrates both intra-candle and inter-candle dynamics, such as overnight and weekend price changes, offering a more detailed analysis compared to traditional methods. The YZVE is proposed to improve over the standard deviation by accounting for the open, high, low, and close prices of trading periods, instead of only the close prices, and attempts to supplant the Parkinson's Volatility Estimator (PVE) by a also capturing inter-candle dynamics. The YZVE is calculated by this formula:
YZ Volatility Squared σ_YZ² = k * σ_o² + σ_rs² + (1 - k) * σ_c²
where k is a weighting factor that adjusts the emphasis between the overnight and close-to-close components, popularly estimated as:
k = 0.34 / (1.34 + (N+1) / (N-1))
where N is the lookback period. Optionally, users may opt to override this calculation with a specified constant (off by default). Next, the
Overnight Volatility Squared σ_o² = (log(O_t / C_(t-1)))²
measures the volatility associated with overnight price changes, from the previous candle's closing price C_(t-1) to the current candle's opening price O_t. It captures the market's reaction to news and events that occur outside of regular trading hours to reflect risk associated with holding positions over non-trading hours and gaps.
Next, the The Rogers-Satchell Volatility Estimator (RSVE) serves as an intermediary step in the computation of YZVE. It aggregates the logarithmic ratios between high, low, open, and close prices within each trading period, focusing on intra-candle volatility without assuming zero inter-candle drift as commonly implicitly assumed in other volatility models:
Rogers-Satchell Volatility Squared σ_rs² = (log(H_t / C_t) * log(H_t / O_t)) + (log(L_t / C_t) * log(L_t / O_t))
Finally,
Close-to-Close Volatility Squared σ_c² = (log(C_t / C_(t-1)))²
measures the volatility from the close of one candle to the close of the next. It reflects the typical candle volatility, similar to naive standard deviation.
This script also includes an option for users to apply the simpler RS Volatility exclusively, focusing on intraday price movements. Additionally, it offers a choice for normalization between 0 and 1, turning the estimator into an oscillator for comparing current volatility to recent levels. Horizontal lines at user-defined levels are also available for clearer visualization. Both are off by default.
References:
Yang, D., & Zhang, Q. (2000). Drift-independent volatility estimation based on high, low, open, and close prices. The Journal of Business, 73(3), 477-491.
Rogers, L.C.G., & Satchell, S.E. (1991). Estimating variance from high, low and closing prices. Annals of Applied Probability, 1(4), 504-512.
L&S Volatility IndexOverview
L&S Volatility Index is a tool designed to helps traders identify overpriced or underpriced moments in the market and adjust their trading strategies accordingly.
Calculations
This tool calculates how far the price is from the 21-period simple moving average as a ratio of the average historical volatility calculated over the last 21 candles.
How It Works
A L&S Volatility Index with a value greater than 30% may indicate that the asset is overpriced or underpriced relative to its average price.
How To Use
If the L&S Volatility Index > 30, the asset is overpriced or underpriced. This means that there is a good probability of initiating a mean reversion.
If the L&S Volatility Index < 30, the asset is in a fair price region. This means that it is acceptable to buy or sell in that price region.
Where To Use
Mean Reversion Strategy
Breakout Strategy
What Makes it Original
There is already an indicator that use a normalized calculation and a different approach to calculate historical volatility, whereas this script calculation is non-normalized and historical volatility is calculated using Don Fishback's formula. All calculations are used as originally described.
Credits
The L&S Volatility Index indicator was originally written by L&S Educação Financeira.
Historical Volatility calculation is based on the book "Odds: The Key to 90% Winners" written by Don Fishback.
Volatility Weighted Moving AverageVolatility Weighted Moving Average (VAWMA) :
The Volatility Weighted Moving Average is a short and long term trend filter that weightes asset price buy "volatility significance" (percentages of total volatility over specified period) unlike that of the WMA which formulates an average based on the product of asset price and a deceding period significance . The result is a less noisy average which weights price based on its potential significance in trend, VAWMA tends to price when volatility is high and conversaly tends away from price when volatility is low.
Example :
As seen above the VAWMA tends to price more than both the SMA and EMA. The high volatility weightings allow for the VWMA to act as a potential trailing stop.
Dynamics :
- symbol volatility watchlist, change the ticker and corrosponding exchange to watch volatility over other markets.
The Amplifier - Two Day Historical Bitcoin Volatility PlotThe 3rd piece to the other two pieces to our CoT study. This is the Amplifier, which turns select signals into 'Super' Buys/Sells
The other two being the 'Bitcoin Insider CoT Delta', and the on chart Price indicator most will have, if no others the 'Hunt Bitcoin CoT Buy/Sell Signals' that will indicate the key signals, ave 4 a year on the chart as they occur.
Why Bother another CoT signal?
Its different & focused on the Insider's.
Performance -
This Indicator provided a
1. Signal 1 = 26th March 2019 = SUPER LONG at $4,500 that saw a near $14,000 run up
2. Signal 2 = 18th & 24th June 2019 = SHORT at the second & final level $11,700 after repeated attempts & failure in the $13K range, the mini Echo Bitcoin Bull of 2019
3. Signal 3 = 17th December 2019 = LONG $6,900, Bitcoin rallied to Mid $10,500's
4. Signal 4 = 18th Feb 2020 = SUPER SHORT from $9,700's to a final extreme Low of $3,000, calling the CV-19 collapse
5. Signal 5 = 17th March 2020 = LONG from $5,400 no closure point yet
6. Signal 6 = 29th June 2020 = SUPER LONG reiterate from $10,700 no closure sell signal yet
7. Signal 7 = 17th May 2020 = LONG another accumulate LONG with no sell signal yet generated at Post H&S's low of $33,000
Note - This indicator only commences March 2019, as Bitcoin futures were a recent introduction and needed to settle for 6 months in both use and data, no signals were meaningful prior & data was light.
What is Provided. - Please note the need to also add the Hunt Bitcoin Historical Volatility Indicator for full understanding.
We provide 3 things with the 3 indicators.
'Insider' indications from Largest players in the futures market.
1. Bitcoin Macro Buy Signals.
a) The Bitcoin Commitment of Traders results see us focus solely on Largest 4 Short Open Interest & Largest 4 Long Open Interest aspects of the CoT Release data.
When the difference - is tight, a kind of pinch, these have been great Buy signals in Bitcoin.
We call this difference the Delta & When Delta is 5% or less Bitcoin is a Buy.
2. Bitcoin Macro Sells.
a) A sell signal is Triggered in Bitcoin at any point the Largest 4 short OI > or = to 70
3. AMPLIFIER Trade signals 'Super' Longs or Shorts -
Extreme low volatility events leads to highly impulsive & volatile subsequent moves, if either of 1 or 2 above occur, combined with extreme low volatility
a 'Super Long' or 'SUPER SELL' is generated. In the case of the short side, given Bitcoins general expansive and MACRO Bull trend since inception, we seek an additional component
that is an extreme differential/Delta reading between 4 biggest Longs & Shorts OI.
Namely CoT Delta also must be > 47.5%
We also have a Cautionary level, where it is not necessarily a good idea to accumulate Bitcon, as a better opportunity lower may avail itself, see conditions below.
So the required logic explicitly stated below for all Signals.
1. Long - Hunt Bitcoin CoT Delta < or = 5
2. SUPER Long - Hunt Bitcoin CoT Delta < or = 5; and 2 Day Historical Bitcoin Volatility = or < 20
3. Short - Largest 4 Sellers OI = or > 70
4. SUPER Short - Largest 4 Sellers OI = or > 70; AND..
Hunt Bitcoin CoT Delta = or > 47.5 AND 2 Day Historical BTC Volatility = or < 20
5. Caution - Largest 4 Sellers OI = or > 67.5 AND Hunt Bitcoin CoT Delta = or > 45
WARNING SEE Notes Below
Note 1 - = Largest 4 Open Interest Shorts
Note 2 - = Largest 4 Open Interest Longs
Note 3 - = Hunt Cot Delta = (Largest 4 sellers OI) -( Largest 4 Buyers OI)
Caution = Avoid new Bitcoin Accumulation Right Now, A sell signal might follow Enter on next Long
Note 4 - The Hunt Bitcoin COT Delta signal is a Largest 'Insider' Tracking tool based on a segment of Commitment of Traders data on Bitcoin Futures, released once a week on a Friday.
It is a Macro Timeframe signal , and should not be used for Day trading and Short Timeframe analysis , Entries may be optimised after a Hunt Bitcoin CoT Signal is generated by separate shorter Timeframe analysis.
Note 5 - The Historical Bitcoin Volatility is an additional 'Amplifier' component to the 'Hunt Bitcoin Cot Delta' Insider Signal
Note 6 - The Historical Bitcoin Volatility criteria varies by timeframe, the above levels are those applying on a Two Day TF Chart, select this custom timeframe in Trading View.
if additional criteria are met for LONG & SHORT insider signals, they may become 'Super Longs/Shorts', see conditions box above.
Volatility Switch Indicator [LazyBear]The Volatility Switch (VOLSWITCH) indicator, by Ron McEwan, estimates current volatility in respect to historical data, thus indicating whether the market is trending or in mean reversion mode. Range is normalized to 0 - 1.
When Volatility Switch rises above the 0.5 level, volatility in the market is increasing, thus the price action can be expected to become choppier with abrupt moves. When the indicator falls below the 0.5 level from recent high readings, volatility decreases, which may be considered a sign of trend formation.
Trading strategy as suggested by Ron McEwan is:
- If VOLSWITCH is less than 0.5, volatility decreases, which may be considered a sign of trend formation
- If VOLSWITCH is greater than 0.5, market is in high volatility mode. Can be choppy. Use RSI to look for OB/OS levels.
I have implemented support for 2 lengths (14 and 21) Note that, Pine doesn't support loops. Once it is introduced, I will publish an updated version.
Building a strategy out of this is straightforward (refer to my strategy explanation above), I strongly encourage new Pinescript coders to try to a plotarrow() based overlay indicator to get more familiar with Pine.
More info:
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The Volatility (Regime) Switch Indicator : traders.com
Complete list of my indicators:
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docs.google.com
Volatility BandsThe Volatility Bands script is a custom indicator designed to help traders visualize volatility levels in the market. It calculates dynamic bands around a central moving average, providing insights into potential support and resistance levels based on recent price action.
The script calculates multiple volatility bands (u0, u1, u2, d0, d1, d2) that adjust based on recent price movements. The outer bands (u2 and d2) represent extreme volatility levels, while the inner bands (u0, u1, d0, d1) indicate more immediate support and resistance.
Look for price reactions at the band levels. A touch of the upper bands may indicate overbought conditions, while a touch of the lower bands may indicate oversold conditions.
Central Moving Average: A smoothed moving average that adapts to price changes, providing a clear trend direction.
The script has no input parameters.
Script Functions:
erf(x): Calculates the error function for a given input x. Used in the calculation of the smoothing factor for the UMA.
uma(input): Provides a smoothed average that adapts to recent price changes, reducing lag compared to traditional moving averages.
dev(input, mu): Used to calculate the volatility bands around the central moving average.
Volatility Percentile (H-LINES)A simple script that adjusts the Volatility Percentile Indicator visibly in order to better accommodate entries/exits and certain trading setups/strategies.
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TL;DR - Remember after a full reset, we are looking for initial crosses UP on the UpperSwingline and crosses DOWN on the LowerSwingline for primary and secondary signal derivation.
Vice versa also works great but the prior method mentioned is a little more consistent in my experience, but you should mess around and optimise this for your own setups and strategies anyway.
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ORIGINAL SCRIPT HERE:
^Click image for a redirect to that script.
ALL CREDIT GOES TO: www.tradingview.com
He wrote everything so give credit where it's due, good bit of kit this here script is.
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HOW I USE MY VISUALLY ALTERED VERSION OF THIS SCRIPT
First of all, the alterations I've made seem only to be consistently viable with renko charts though if you can get the sought after results using candles or any other chart type then perfect, but be wary. All my back-testing done only with LinReg, HMA and SWMA - ATR type settings exclusively on renko charts. The changes I've made to the original script essentially just turns it visibly into an oscillator and uses a couple horizontal lines to generate signals, very simple - absolutely nothing has changed in the actual code of calculating this indicator.
What I believe my adjustments have achieved is quite simple. A full reset/oscillation on the indicator tries to map the strongest parts of a move or at least the part of the move where volume and the rate of transactions is at its peak to even facilitate said move. *take this statement with a pinch of salt though I do believe it's interacting with accumulation/distribution patterns, which is expected of volatility*
For ease of communication let's refer to the area between the the first UpperSwingline cross to the subsequent LowerSwingline cross, as the primary move. Then afterwards when it crosses the UpperSwingline again to make the full reset, the area in between those two points referred to as the secondary move.
Though more interestingly/practically the indicator ends up giving you two signals. In order for this to work we have to first decide that a spike up in volatility which crosses the UpperSwingline implies a significant level of interest at that price level. Usually that means a reversal is brewing, if price has already moved, trended and is approaching a certain area of value; which causes a spike of new positions to be taken, then you know that this is a level where contrarians are looking to enter. Now here's the tricky part, when volatility crosses the LowerSwingline price action becomes a little more open for interpretation, the way I personally like to look at this secondary signal is the potential for an exhaustion period to prolong itself a little longer. I know that's not the perfect analysis for what's going on, a more in-depth look into what's going on would best be described using Elliott Wave Theory, if a cross on the UpperSwingline near a significant area of value gives us a reversal trade lets just assume for the sake of argument that a new Elliott Wave can begin forming here. Making the move from that initial UpperSwngline cross to the cross on the LowerSwingline, the area that encompasses those two points: the impulse wave. After this point my analogy kind of falls apart and sadly my knowledge just isn't what it needs to be in order for me to properly analyse what's going on here but I must digress. Price after crossing the LowerSwingline up until the point where it makes a full reset by crossing the UpperSwingline again, within this area price seems to do either one of two things:
Situation 1 - Most likely occurs after a major trend reversal from major support/resistance or area of value (price has trended to new territory, maybe spent time a little time consolidating but hasn't broken the key level, momentum shifts, price action breaks current structure and you get the signal that primary move is a reversal) = Exhaustion Period, price will continue in direction of primary move during the secondary move. This here is for our trend-followers, you wanna take a continuation trade? Just wait for the pullback/rally to hit a FiB retracement level and enter - or any other means to find a decent support/resistance to enter.
Situation 2 - Most likely occurs when market enters a range or consolidation (price was previously seen as being at either a discount or premium so Situation 1 could have already played out and now you're looking at a full reset after that, imagine this spot to be the centre line of a linear regression channel or bang in the middle of your range, could even occur if price breaks a key moving average and decides it ought to consolidate around it for a while. Basically at any point where a somewhat prolonged consolidation is expected and not a quick reversal) = Corrective Wave, price will move against the direction of primary move during the secondary move. Now you might be expecting me to say this ones for you reversal traders but not really, if this is occurring then there probably isn't a definitive direction the market has chosen so you can use this opportunity to take range trades in the direction or against the direction of whatever the current trend or latest trend was depending on whatever slight bias you may have. <--- Situation 2 is very useful for finding cleaner entries if you do have a trend bias, say price underwent Situation 1, is now at key moving average but your bias is that it will break and continue up, so you wait and allow the secondary move of Situation 2 to take your entry to a much better R:R before entering a position.
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Volatility Trackerhi there, fellows.
this is a very simple and quite straightforward indicator.
so far the simplest we've built.
on what it does
in regard to current chart and timeframe it plots
a. Open - Close as a percentage of the Open (we regard open as more relevant than close, for as you can use latest estimates in current candle) in daily change coloring (so one may have an idea if there is a trend or sideways move unfolding)
b. High - Low as a percentage of the Open, so one may compare extreme moves with final ones in the period
c. Volume as a percentage distance from its WMA200 (always this one, a way better reference for normalcy). (e. g. a positive value x means Volume is x% above its WMA200)
on what it means
to the best of our imperfect and incomplete understanding, we believe that low volatility periods lead to high volatility periods, so one might want to enter the market in low volatility periods to enjoy wild rides afterwards. such a trade of course would be, for the sake of making sense, a long volatility one.
the timing for entrance could be once that the volatility waves fades to chart minimums.
we're open to critics, suggestions and comments.
best regards.
Full Volatility Statistics and Forecast
This is a tool designed to translate the data from the expected volatility of different assets, such as for example VIX, which measures the volatility of SP500 index.
Once get the data from the volatility asset we want to measure(for this test I have used VIX), we are going to translate it the required timeframe expected move by dividing the initial value into :
252 = if we want to use the daily timeframe, since there are ~252 aproximative daily trading days
52 = if we want to use the weekly timeframe, since there 52 trading weeks in a year
12 = if we want to use the monthly timeframe, since there are 12 months in a year
For this example I have used 252 with the daily timeframe.
In this scenario, we can see that we had 5711 total cnadles which we analysed, and in this case, we had 942 crosses, where the daily movement ended up either above or below the channel made from the opening daily candle value + expected movement from the volatility, giving as a total of 16.5% of occurances that volatility was higher than expected, and in 83.5% of the times, we can see that the price stayed within our channel.
At the same time, we can see that we had 6 max losses in a row ( OUT) AND 95 max wins in a row (IN), and at the same time in those moments when the volatility crosses happen we had a 0.51% avg movements when the top crossed happened, and 0.67% avg movements when the bot happened.
Lastly on the second part of the panel, we had E which means the expected movement of today, for example it has 61.056$ , so lets say price opened on 4083, our top is 4083 + 61 and our bot is 4083 - 61 ( giving us the daily channel). At continuation we can see that overall the avg bull candle os 0.714% and avg bear candle was 0.805% .
I hope this tool will help you with your future analysis and trades !
If you have any questions please let me know !
Candle Volatility Index [by NicoadW]This is the migration of the CandleVolatilitIndex from MT4.
The indicator works as following:
Step 1: The "Volatility Value" is calculated by applying a moving average to the change of the selected source (default: 10-Period-SMA applied to the change from last close to this close -> SMA(close-close , 10) )
Step 2: The signal line is calculated by applying a moving average onto the "Volatility Value" calculated in step 1.
The default settings are the same as in the original MT4 version.
Visualization:
The histogram shows the "Volatility Value" calculated in step 1.
Case 1:
The value is above the signal line (blue bar) -> Volatility is given
Case 2:
The value is below the signal line (grey bar) -> Volatility is not there
This is intended to be used as a Volume/Volatility Indicator for a NNFX-System but can be used in any strategy.
BTC Volatility Band StrategyThis script/strategy is a pullback system designed for securities with high volatility so naturally Bitcoin is an excellent choice for trading this. This could be used both on a daily chart or on lower timeframes (I found good results on 3hr timeframe but haven't tested it on anything under 1hr).
A volatility band is created by comparing the candle close price of the previous 2 candles and and it uses this change in price to create a moving average. A band is wrapped around the moving average with a standard deviation of 1 for the inner band and 2 for the outer band. If the price is above a pre-set MA (moving average filter) then it is determined we are in an uptrend so the strategy will issue a buy signal when we are in an uptrend and there is a pullback which causes the lower inner deviation band to be spiked, but if the price continues and falls through the outer deviation band then a buy signal will not issue as this detriments that the volatility spike is to great. You can see a spike "buy" event occur on the indicator where the background is coloured green. For a short/sell then there will be a spike on the upper inner band and we are below the pre-set MA filter, for this it shows with red background on the indicator.
The user can change the date range they wish to test, the moving average period for the volatility tracking and the inner and outer band deviations. On BTC I left the inner deviation and outer deviation bands on standard settings but found the 3 period volatility tracking to be good for trading 1 day chart and the 5 period volatility tracking good for the 3hr chart. Since this is not a buy and hold strategy then for trading you would probably want to stick with the most liquid coins so you can get in and out very fast on any exchange. If you wanted to tray this on less volatile markets then changing the inner deviation band to ~0.75 would work okay in various futures markets likely stocks as well. The take profit and stop loss levels are based on a multiple of the trading range looking back the past 7 candles.
Attached result is trading 1 BTCUSDT contract on Binance.
ka66: Volatility MomentumThis is a 'monitoring' indicator to see if an instrument is viable enough to be traded, by virtue of volatility (or lack of volatility in context may lead to a break out), or may become so. It shows the following information:
Price Range (high - low) averaged across a set of bars: Useful gauging potential trading profits. This was its initial goal, to not measure bars manually!
ATR : As a comparison point for the price range above. Divergence between true range (TR) and plain price range might signal volatility changes occurring in the instrument.
Signal volatility line : a moving average of the larger of the average price range and ATR. This takes inspiration from other indicators like MACD and Stochastic, and is a way of comparing change in recent volatility --- this achieves the momentum part. The larger was chosen to keep things simple, and not have a signal line per range!
avgRange = movingAvg(high - low, avgPeriod)
atr = movingAvg(trueRange, avgPeriod)
signal = movingAvg(max(avgRange, atr), avgPeriod)
Configurable periods and averaging mechanism.
Daily Historical Volatility StdDev LevelsDescription:
This indicator plots Daily Standard deviation levels on price chart based on Historical Volatility (HV). It uses the most common approach for calculating historical volatility as standard deviation of logarithmic returns, based on daily closing/settlement prices.
Assets: Currency Pairs, Commodities, also works on stocks, some indices.
Time Frames: 5min to 60min. This will also work on Daily Chart, by setting "DaystoExpire" to 21
Options:
Use Daily Data to Calculate StdDev HV (default), otherwise use the charts Time Frame
Lookback = number of days/periods to calculate stddev of HV (21 by default)
Annual = number of trading days in a calender year (252 by default)
Days to Expiry = number of days for the life of this option ( for auto calculation
this is 1 for intraday, 21 for daily and annual when chart TF used)
Settlement Source = close price by default, can use another source.
Settlement Volume Weighted Average Length = by setting this to >1 then an average
is used for settlement.
Display ### Standard Deviation Levels = select what levels are to be displayed.
References:
How To Use Standard Deviation In Your Trading Day: www.youtube.com
Deviation Levels Indicator: www.youtube.com
www.macroption.com
Historical Volatility based Standard Deviation_V2 by ucsgears
Historical Volatility Strategy by Hpotter
Trend Volatility Tops and Bottoms
Big Picture:
Overall what this script try's to capture is bounces off of moving trend lines.
What you will see when using this script
one Green line, one red line, two gray lines and circles in colors blue, green, red, and purple.
RED AND GREEN LINES:
There are two trend lines, an upper and a lower line that are 1 to 2 standard deviations from the linear regression line formed by the closing price for a look back period. The green is the distance from the close price and the lower line. The red is the list from the close and the upper line. (you don't see the lower and upper lines, but yo do see the green and red lines)
The goal is too easily see when price is approaching those support and resistance levels.
GRAY LINES:
GRAY lines are a form of volatility metric. GRAYS represent the distance from the RED and GREEN lines talked about above. low volatility mean the two GRAY lines will be close and times of high volatility will be father apart.
COLORED CIRCLES:
the color circles represent possible bounce zones, when price is high or low for for a given time period.
PURPLE is caution that there could be a possible price drop
RED is a critical zone for rejection and price drop
BLUE is caution that there could be a possible price increase
GREEN is a critical zone for bounce and price increase
how its used
feel free to play around and Try new things but, how its intended to be used is on 4hr time Frame looking for longer term trends on assets that tend to be less volatile on average.
settings
some settings:
buy deviation, this will say how many standard deviations do you want the lower bounce line to be from the linear regression line
sell deviation, this will say how many standard deviations do you want the upper bounce line to be from the linear regression line
dist to zero buy: how close dose the price has to be to put out a possible bounce.
Recap
-red and purple = possible upcoming price drop... red is more critical than purple
-green and blue = possible upcoming price increase... green is more critical than blue
-use on less volatile assents and on 4hr timeframe
good luck!
Market Trend using First Derivative of MAs + Volatility Based on Smooth First Derivative Indicator by tbiktag
Volatility also from another public TV script, forgot which one though, sorry if this is yours and I haven't credited your work, let me know if it is and I'll reference it properly.
About this indicator:
Estimates whether market is trending up, down or sideways by adding the slope (first derivatives) of a fast & slow MA. Uptrend = Green, Downtrend = Red, Sideways = Yellow
Uses a minimum slope percentile to determine threshold for uptrend, downtrend & sideways. Definitely adjust this when changing timeframes, for BTCUSD at 1 hour timeframe a value of 25 is decent
Also has a measure of Volatility if you're into that
Explanation of inputs:
Bandwidth - for derivative function
Fastma - period for fast Moving Average
Slowma - period for slow Moving Average
Derivmalength - smooths out the signal, reducing single contrasting bars, but delays the signal. Use 1 if don't want to use
V length - ema of volatility if you want to smooth it
Min Slope Percentile - slope should exceed this percentile to be classified as uptrend (green) or downtrend (red) anything in this bottom percentile will be considered sideways
Mine Slope Lookback Period - # of bars back to calculate Slope Percentile
Annualised Price Volatility %Annualised Price Volatility in percent, also called Instrument Risk, as outlined by Rob Carver in his excellent books, 'Systematic Trading' and 'Leveraged Trading'.
This is written for those who have read one of his books and want to use this tool on TradingView.
Trend strength, oscillators, and volume indicators are all the rage. Finding a great setup is, of course, key. You've decided to go long. Great!
But how much is your capital at risk?
How does that compare with your level of risk tolerance?
When trading, it's key to understand just how risky a certain instrument is. An uptrend is an uptrend, but is it at an annualised volatility of 2% per year or 500% per year? If it's the former, I know I can put a good chunk of capital into trading it. But if its the latter, I don't want to put so much money at risk. Volatility is rarely in a straight line. It's usually up and down.
I won't give the whole game away. To find out more about how to use this concept of risk, I'd highly recommend the books 'Leveraged Trading' and 'Systematic Trading' by Rob Carver.
Do you have any thoughts, ideas, or questions? Let me know in the comments or send me a message! I'd be glad to help you out.
Bitcoin Implied VolatilityThis simple script collects data from FTX:BVOLUSD to plot BTC’s implied volatility as a standalone indicator instead of a chart.
Implied volatility is used to gauge future volatility and often used in options trading.
Best Volatility Calculator (Multi Instruments)Hello traders
A bit of context
Definition: Volatility is defined as the close of current candle - close of the previous N candle
This is an alternative version of my Best Volatility Calculator
The other version is displayed on a panel below. This one overlays on the chart using the "overlay=true" setting
This indicator shows the average volatility, of last N Periods, for the selected time frames and for 2 selected instruments.
You can select up to 2 timeframes with this version
Presented as Currency, Pip, percentage labels in a panel below.
Will calculate in real-time only for the current instrument on the chart.
The indicator is coded to not be repainting
Example
In the indicator screenshot, I used a lookback period of 1.
That compares the current candle close versus the previous one for the daily and weekly timeframe
Showing how the results look like using FOREX instruments (where using the PIPS labels make more sense than with cryptocurrency assets)
Best regards
Dave
