Day of Week - Volatility Report█ OVERVIEW
The indicator analyses the volatility and reports statistics by the days of the week.
█ CONCEPTS
On business days and weekends, different market participants get involved in the markets. How does this affect the markets during the week?
Here are some ideas to explore:
When are the best days for trading?
Which day of the week is the market the most volatile?
Should you trade on business days? Is it worth trading during the weekend?
How does this relate to your most profitable trades?
Is there a confluence with the days having the highest win rate?
Which days of the week should you stop trading?
Ethereum
USDCAD
NZDUSD
█ FEATURES
Configurable outputs
Output the report statistics as mean or median.
█ HOW TO USE
Plot the indicator and visit the 1D, 24H, or 1440 minutes timeframe.
█ NOTES
Gaps
The indicator includes the volatility from gaps.
Calculation
The statistics are not reported from absolute prices (does not favor trending markets) nor percentage prices (does not depict the different periods of volatility that markets can go through). Instead, the script uses the prices relative to the average range of previous weeks (weekly ATR).
Trading session
The indicator analyses weekdays from the daily chart, defined by the exchange trading session (see Symbol Info).
Extended trading session
The indicator can include the extended hours when activated on the chart, using the 24H or 1440 minutes timeframe.
Overnight session
The indicator supports overnight sessions (open and close on different calendar days). For example, EURUSD will report Monday’s volatility from Sunday open at 17:00 to Monday close at 17:00.
This is a PREMIUM indicator. In complement, you might find useful my free Time of Day - Volatility Report .
Tìm kiếm tập lệnh với "Volatility"
Relative Bi-Directional Volatility RangeThe basic math behind this Indicator is very similar to the math behind the Relative Strength Index without using a standard deviation as used for the Relative Volatility Index. The Volatility Range is calculated by utilizing the highs and lows. However not in the same way as in the Relative Volatility Index. This approach leads to different values, but the overall result clearly reveals the intrinsic Volatility of the chart, so the user can be aware, when something fundamentally is going on behind the scenes. If the Volatility rises on positive and negative range (-100 to 100) it implies that something fundamental is changing.
An advantage of using this kind of calculation is the possibility of separating the data into positive (buy pressure) and negative (sell pressure) components. The bi-directional character shows a slightly overhang in one of the directions, which can be used to detect a trend. A Moving Average of the users choice shell smoothen the overhang of the Relative Bi-Directional Volatility and show a trend direction. Similar to the math of the Relative Strength Index as standard a Relative Moving Average is preferred. If the Moving Average is in the positive range (0 to 100) it indicates a bullish trend, else if the Moving Average is in the negative range (0 to -100) it indicates a bearish trend. External Indicators can use a provided Trend Shift Signal which switches from 0 to 1, if the trend becomes bullish or from 0 to -1, if the trend becomes bearish.
The user should know, that in this Indicator the starting point of the Moving Averages always begins at the first bar, because the starting progress is approximated appropriately. Most Moving Averages require a minimum number of bars to be calculated, which is chosen with the Moving Average Length. In this cases the length used will be automatically reduced in the background until the number of bars is sufficient to match the chosen length. So if data history is very short, the Indicator can be used never the less as good as possible.
It is feasible to switch the Indicator on a higher timeframe, while staying in a lower timeframe on the chart. This can be useful for making the indication cleaner, if the Moving Average is to choppy and shows too many false signals. On the other hand the benefit of a higher timeframe (or a higher Moving Average Length) is paid with higher latency of the signaling. So the user has to decide what the best setting in his case is.
This Indicator can be used with all kinds of charts. Even charts with percentage or negative values should work fine.
Parkinson's Historical Volatility Bands [Loxx]Parkinson's Historical Volatility Bands are constructed using:
Average as the middle line.
Upper and lower bands using the Parkinson's historical volatility (instead of "regular" Historical Volatility) for bands calculation.
What is Parkinson's Historical Volatility?
The Parkinson's number, or High Low Range Volatility developed by the physicist, Michael Parkinson in 1980, aims to estimate the Volatility of returns for a random walk using the High and Low in any particular period. IVolatility.com calculates daily Parkinson values. Prices are observed on a fixed time interval: n = 10, 20, 30, 60, 90, 120, 150, 180 days.
SH is stock's High price in t day.
SL is stock's Low price in t day.
High/Low Return (xt^HL) is calculated as the natural logarithm of the ratio of a stock's High price to stock's Low price.
Return:
And Parkinson's number: 1 / (4 * math.log(2)) * 252 / n * Σ (n, t =1) {math.log(Ht/Lt)^2}
An important use of the Parkinson's number is the assessment of the distribution prices during the day as well as a better understanding of the market dynamics. Comparing the Parkinson's number and periodically sampled volatility helps traders understand the tendency towards mean reversion in the market as well as the distribution of stop-losses.
The color of the middle line, unlike the bands colors, has 3 colors. When colors of the bands are the same, then the middle line has the same color, otherwise it's white.
Included
Alerts
Signals
Loxx's Expanded Source Types
Bar coloring
Directional Volatility Index (DVI) - SoldiDirectional Volatility Oscillator
What the DVI does is it measure 9 different volatility models based on their directional correlation and then scores that. While it calculated the volatility it also measures and scores 5 different indicators to find the likeliness of a retail position. That way the Oscillated value being plotted is that of an accurate modelled nature. This indicator aims to measure and score the directional volatility across the 9 different volatility models and then plots it as an oscillator. Included in that calculation is a measure of the likeliness of a retail traders position.
This can be used to gauge liquidity sweeps in a strategy like Smart Money Concepts. As, all the retail money is long - expect a sweep of the lows or equal highs. etc. more so you can also use this as a market meter like RSI , if the market is Over bought or Over sold, the DVI value will be over 100 or under -100 - or this tool can be used to gauge the underlaying trend!
Examples
Here is an example on BTCUSD - 1d
- as you can see there is significant trend when the DVI is crossed
Here is that same example on BTCUSD - 1d zoomed into 4h
- as you can see there is significant trend when the DVI is crossed
Nasdaq VXN Volatility Warning IndicatorToday I am sharing with the community a volatility indicator that uses the Nasdaq VXN Volatility Index to help you or your algorithms avoid black swan events. This is a similar the indicator I published last week that uses the SP500 VIX, but this indicator uses the Nasdaq VXN and can help inform strategies on the Nasdaq index or Nasdaq derivative instruments.
Variance is most commonly used in statistics to derive standard deviation (with its square root). It does have another practical application, and that is to identify outliers in a sample of data. Variance is defined as the squared difference between a value and its mean. Calculating that squared difference means that the farther away the value is from the mean, the more the variance will grow (exponentially). This exponential difference makes outliers in the variance data more apparent.
Why does this matter?
There are assets or indices that exist in the stock market that might make us adjust our trading strategy if they are behaving in an unusual way. In some instances, we can use variance to identify that behavior and inform our strategy.
Is that really possible?
Let’s look at the relationship between VXN and the Nasdaq100 as an example. If you trade a Nasdaq index with a mean reversion strategy or algorithm, you know that they typically do best in times of volatility . These strategies essentially attempt to “call bottom” on a pullback. Their downside is that sometimes a pullback turns into a regime change, or a black swan event. The other downside is that there is no logical tight stop that actually increases their performance, so when they lose they tend to lose big.
So that begs the question, how might one quantitatively identify if this dip could turn into a regime change or black swan event?
The Nasdaq Volatility Index ( VXN ) uses options data to identify, on a large scale, what investors overall expect the market to do in the near future. The Volatility Index spikes in times of uncertainty and when investors expect the market to go down. However, during a black swan event, historically the VXN has spiked a lot harder. We can use variance here to identify if a spike in the VXN exceeds our threshold for a normal market pullback, and potentially avoid entering trades for a period of time (I.e. maybe we don’t buy that dip).
Does this actually work?
In backtesting, this cut the drawdown of my index reversion strategies in half. It also cuts out some good trades (because high investor fear isn’t always indicative of a regime change or black swan event). But, I’ll happily lose out on some good trades in exchange for half the drawdown. Lets look at some examples of periods of time that trades could have been avoided using this strategy/indicator:
Example 1 – With the Volatility Warning Indicator, the mean reversion strategy could have avoided repeatedly buying this pullback that led to this asset losing over 75% of its value:
Example 2 - June 2018 to June 2019 - With the Volatility Warning Indicator, the drawdown during this period reduces from 22% to 11%, and the overall returns increase from -8% to +3%
How do you use this indicator?
This indicator determines the variance of VXN against a long term mean. If the variance of the VXN spikes over an input threshold, the indicator goes up. The indicator will remain up for a defined period of bars/time after the variance returns below the threshold. I have included default values I’ve found to be significant for a short-term mean-reversion strategy, but your inputs might depend on your risk tolerance and strategy time-horizon. The default values are for 1hr VXN data/charts. It will pull in variance data for the VXN regardless of which chart the indicator is applied to.
Disclaimer: Open-source scripts I publish in the community are largely meant to spark ideas or be used as building blocks for part of a more robust trade management strategy. If you would like to implement a version of any script, I would recommend making significant additions/modifications to the strategy & risk management functions. If you don’t know how to program in Pine, then hire a Pine-coder. We can help!
Squeeze Momentum + Volatility [LeonidasCrypto]Based on Squeeze Momentum indicator by LazyBear
This custom version of SQ is part of my Trading System.
How to use it.
Please read the description of the original author of this indicator here.
Volatility .
When the market is contracting or sideways usually you will see red or blue dots.
Blue dots. the market is in sideways and the volatility is low.
Red dots. the market is in the climax of volatility usually after of a big move this is a potential signal the peak of the move is near.
I added volatility to SQ because I consider volatility is a key factor for trading to anticipate the moves.
UCS_Price Action Normalized VolatilityFor Stock, Futures and Forex traders this may not be a replacement for MACD . But for an Option Trader, this would make sense 1000 times.
So, What is this?
This is the MACD for OPTIONS traders, remove the smoothness and adjust for volatility . Thats all it is.
Why is it important?
No one, ABSOLUTELY no one should be buying options in high volatility period for a long haul. So, this indicator takes that out of your guess work and only spits out price movement with relation to volatility .
You can use this exactly like a MACD for any options ( aka , volatility driven market).
Few things I have added, since I created and used it privately.
1. Chop Zone - Trade the Extremes of any Product
2. Buyers Zone - Shorts reconsider
3. Sellers Zone - Longs reconsider
Why did I create this?
Volatility dictates the market movement. That is an indepth conversation. If you are curious you can research on how shorts are squeezed, what are market makers obligations, how they maintain profitability. How NITE got burned, are some starting point for your own research.
So, if you are an options trader, I highly recommend to use this/test it and share your thoughts and how you use it.
- Good Luck Everyone.
@WACC Volatility Weighted PUT/CALL Positions [SPX]This indicator is based on Volatility and Market Sentiment. When volatility is high, and market sentiment is positive, the indicator is in a low or 'buy state'. When volatility is low and market sentiment is poor, the indicator is high.
The indicator uses the VIX as it's volatility input.
The indicator uses the spread between the Call Volume on SPX/SPY and the Put Volume.
This is pulled from CVSPX and PVSPX.
When volatility and put/call reaches a critical level, such as the levels present in a crisis or a sell off, the line will be green. See Sept 2015, 2008, and Feb 2018.
This level can be edited in the source code.
As the indicator is based on Put/Call, the indicator works best on larger time frames as the put/call ratio becomes a more discernible measure of sentiment over time.
Historical Volatility Strategy Strategy buy when HVol above BuyBand and close position when HVol below CloseBand.
Markets oscillate from periods of low volatility to high volatility
and back. The author`s research indicates that after periods of
extremely low volatility, volatility tends to increase and price
may move sharply. This increase in volatility tends to correlate
with the beginning of short- to intermediate-term moves in price.
They have found that we can identify which markets are about to make
such a move by measuring the historical volatility and the application
of pattern recognition.
The indicator is calculating as the standard deviation of day-to-day
logarithmic closing price changes expressed as an annualized percentage.
Historical Volatility Markets oscillate from periods of low volatility to high volatility
and back. The author`s research indicates that after periods of
extremely low volatility, volatility tends to increase and price
may move sharply. This increase in volatility tends to correlate
with the beginning of short- to intermediate-term moves in price.
They have found that we can identify which markets are about to make
such a move by measuring the historical volatility and the application
of pattern recognition.
The indicator is calculating as the standard deviation of day-to-day
logarithmic closing price changes expressed as an annualized percentage.
Vasyl Ivanov | Volatility with MAThis indicator calculates and displays the volatility value for each bar.
The main line shows the relative range (spread) of the current bar compared to its closing price.
This allows you to quickly assess how much the price fluctuated within the bar relative to where it closed.
The Simple Moving Average (SMA) with a length of 9 smooths the main indicator values, helping to identify volatility trends and filter out random spikes.
Practical Application:
The indicator can be useful for assessing current market volatility and identifying periods with unusually wide or narrow ranges.
The smoothed line helps track medium-term changes in volatility and can be used to confirm trading signals related to range expansion or contraction.
Simple Volatility MomentumOverview:
The Simple Volatility Momentum indicator calculates the mean and standard deviation of the changes of price (returns) using various types of moving averages (Incremental, Rolling, and Exponential). With quantifying the dispersion of price data around the mean, statistical insights are provided on the volatility and the movements of price and returns. The indicator also ranks the mean absolute value of the changes of price over a specified time period which helps you assess the strength of the "trend" and "momentum" regardless of the direction of returns.
Simple Volatility Momentum
This indicator can be used for mean reversion strategies and "momentum" or trend based strategies.
The indicator calculates the average return as the momentum metric and then gets the moving average of the average return and standard deviations from average return average. On the options you can determine if you want to use 1 or 2 standard deviation bands or have both of them enabled.
Settings:
Source: By default it's at close.
M Length: This is the length of the "momentum".
Rank Length: This is the length of the rank calculation of absolute value of the average return
MA Type: This is the different type of calculations for the mean and standard deviation. By default its at incremental.
Smoothing factor: (Only used if you choose the exponential MA type.)
The absolute value of the average return helps you see the strength of the "momentum" and trend. If there is a low ranking of the absolute value of the average return then you can eventually expect it to increase which means that the average return is trending, leading to trending price moves. If the Mean ABS rank value is at or near the maximum value 100 and the average return is at -2 standard deviation from the mean, you can see it as the negative momentum or trend being "finished". Similarly, if the Mean ABS value is near or at the maximum value 100 and the average return is at +2 standard deviation from the mean, you can view the uptrend, as "finished" and the Mean ABS rank can't really go higher than 100.
Moving Average Calculations type:
Incremental: Incremental moving averages use an incremental approach to update the moving average by adding the newest data point and subtracting the oldest one.
Exponential: The exponential moving average gives more weight to recent data points while still considering older ones. This is achieved by applying a smooth factor to the previous EMA value and the current data point. EMA's react more quickly to recent changes in the data compared to simple moving averages, making them useful for short term trends and momentum in financial markets.
Rolling: The moving average is calculated by taking the average of a fixed number of data points within a defined window. As new data becomes available, the window moves forward and the average is recalculated. Rolling Moving Averages are useful for smoothing out short-fluctuations and identifying trends over time.
Important thing to note about indicators involving bands and "momentum" or "trend" or prices:
For the explanation we will assume that stock returns follow a normal distribution and price follows a log normal distribution. Please note that in the live market this assumption isn't always true. Many people incorrectly use standard deviations on prices and trade them as mean reversion strategies or overbought or oversold levels which is not what standard deviations are meant for. Assuming you have applied the log transformation on the standard deviation bands (if your input is raw price then you should use a log transformation to remove the skewness of price), and you have a range of 2 standard deviations from the mean, under the empirical rule with enough occurrences 95% of the values will be within the 2 standard deviation range. This doesn't mean that if price falls to the bottom of the 2 standard deviation bound, there is a 95% chance it will revert back to mean, this is incorrect and not how standard deviations or mean reversion works.
"MOMENTUM"
In finance "momentum" refers to the rate of change of a time series data point. It shows the persistence or tendency for a data series to continue moving in its current direction. In finance, "momentum" based strategies capitalize on the observed tendency of assets that have performed well (or poorly) in the recent past to continue performing well (or poorly) in the near future. This persistence is often observed in various financial instruments including stocks, currencies and commodities.
"Momentum" is commonly calculated with the average return, and relies on the assumption that assets with positive "momentum" or a positive average return will likely continue to perform well in the short to medium term, while assets with a negative average return are expected to continue underperforming. This average return or expected value is derived from historical observations and statistical analysis of previous price movements. However, real markets are subject to levels of efficiencies, market fluctuations, randomness, and may not always produce consistent returns over time involving momentum based strategies.
Mean Reversion:
In finance, the average return is an important parameter in mean reversion strategies. Using statistical methodologies, mean reversion strategies aim to exploit the deviations from the historical average return by identifying instances where current prices and their changes diverge from their expected levels based on past performance. This approach involves statistical analysis and predictive modelling techniques to check where and when the average rate of change is likely to revert towards the mean. It's important to know that mean reversion is a temporary state and will not always be present in a specific timeseries.
Using the average return over price offers several advantages in finance and trading since it is less sensitive to extreme price movements or outliers compared to raw price data. Price itself contains a distribution that is usually positively-skewed and has no upper bound. Mean reversion typically occurs in distributions where extreme values are followed by a tendency for the variable to return towards its mean over time, however the probability distribution of price has no tendency for values to revert towards any specific level. Instead, values may continue to increase without a bound. Returns themself contain more stationary behavior than price levels. Mean reversion strategies rely on the assumption that deviations from the mean will eventually revert back to the mean. Returns, being more likely to exhibit stationary, are better suited for mean reversion based strategies.
The distribution of returns are often more symmetrically distributed around their mean compared to price distributions. This symmetry makes it easier to identify deviations from the mean and assess the likelihood of mean reversion occurrence. Returns are also less sensitive to trends and long-term price movements compared to price levels. Mean reversion strategies aim to exploit deviations from mean, which can be obscured when analyzing raw price data since raw price is almost always trending. Returns can filter out the trend component of price movements, making it easier to identify opportunities.
Stationary Process: Implication that properties like mean and variance remain relatively constant over time.
Time of Day - Volatility Report█ OVERVIEW
The indicator analyses the volatility and reports statistics by the time of day.
█ CONCEPTS
Around the world and at various times, different market participants get involved in the markets. How does this affect the market?
Knowing this gets you better prepared and improves your trading. Here are some ideas to explore:
When is the market busy and quiet?
What time is it the most volatile?
Which pairs in your watchlist are moving while you are actively trading?
Should you adjust your trading time? Should you change your trading pairs?
When does your strategy perform the best?
What entry times do your winners have in common? What about the exit times of your losers?
Is it worth keeping your trade open overnight?
Bitcoin (UTC+0)
Gold (UTC+0)
Tesla, Inc. (UTC+0)
█ FEATURES
Selectable time zones
Display the statistics in your geographical time zone (or other market participants), the exchange time zone, or UTC+0.
Configurable outputs
Output the report statistics as mean or median.
█ HOW TO USE
Plot the indicator and visit the 1H timeframe.
█ NOTES
Gaps
The indicator includes the volatility from gaps.
Calculation
The statistics are not reported from absolute prices (does not favor trending markets) nor percentage prices (does not depict the different periods of volatility that markets can go through). Instead, the script uses the prices relative to the average range of previous days (daily ATR).
Extended trading session
The script analyses extended hours when activated on the chart.
Daylight Saving Time (DST)
The exchange time or geographical time zone selected may observe Daylight Saving Time. For example, NASDAQ:TSLA always opens at 9:30 AM New York time but may see different opening times in another part of the globe (New York time corresponds to UTC-4 and UTC-5 during the year).
Artharjan INDIA VIX v/s Nifty Volatility DashboardHi,
I have created Artharjan INDIA VIX v/s Nifty Volatility Dashboard to forecast the Annual, Quarterly, Monthly, Weekly, Daily and Hourly Volatility of NIFTY Benchmark Index based on current value of INDIA VIX. This will help Index Options Sellers to decide the range of Nifty for the given period based on current level of volatility indicated by INDIA VIX.
Options Sellers may make use of the Min Range and Max Range values for the Strike Price Selection.
Regards
Rahul Desai
@Artharjan
Historical Volatility OscilattorHistorical Volatility Oscilattor is a tool that helps us to identify changes in the volatility regime. The histogram is the result of the substraction of the fast historical volatility to the slow historical volatility
VolatWave‴ | Volatility Wave‴What does it do?
This indicator allows you to identify possible asset top and bottom reversals by having a prior Volatility acting among the price movement with a sequential positive (top reversal) or negative (bottom reversal) waves.
How does it work?
Everytime the wave starts showing a curved top movement (ascending price movment) or a curved bottom movement (descending price movment), it might be signing that a price reversal is on its way. It is possible to adjust the wave shape by increasing/decreasing its gradient value analysis, but it's so easy to use that most of the times no reconfiguration is needed, just add it and let it guide you.
Important to mention that the positive wave band, histogram bars and moving average line are calculate totally separete from the the negative wave.
What's my filling?
I'm still testing this indicator for only a week and so far still trying to understand its signs. I'm using it in conjunction with Volume Wave (VolWave) and Price Spread Wave (PSWave).
Indicator attributes:
- generally waves formation makes a symmetrical arc
- when the second half of a wave is elongated (compared to its first half), it suggests a lack of directional force of the current movement
- peak / bottom formation suggests reversal of the current movement
- smaller amplitude of a wave (compared to the previous wave) suggests loss of power, and vice-verse
- indicates divergence indication between peaks / bottoms
- when the volatility bar touches the volatility wave band, it suggests imminent reversal of the current movement
- wave band opening suggests movement increasing strength in that direction
- wavelengths (distance between two peaks / bottoms) tend to be similar
- subsequent wave rarely occurs
Technical information:
- the calculation of the positive movement is independent of the calculation of the positive movement
- the black line in the upper and lower zone is the average of the wave that is overcome, suggests strength in movement
- bands suggest delimitation of a wave's peak / bottom
To have access to this indicator, please DM me.
Don't contact me in the comment area.
G-Bollinger bands volatility breakout v.1This is my frist publish scrpit. I developed this indicator origin is BB. It make from easy idea but powerful for sideway to breakout
1. I findout volatility by upper band of BB - lower band of BB (I called "Aline")
2. I created SMA of Aline (I called Bline)
3. I created the special line is "Cline" from Aline - Bline
4. I created 0 line " Baseline "
G-BBvB is the very good indicator to detect low volatility to begin the volatility = Buy signal
Now I can't find the sell signal form indicator. I try backtest sell at Cline cross zeroline but it not work.
I'll develop "G" indicator for free .
Goodluck :D
[TVExtBot]Volatility Breakout Indicator(With Alerts)Volatility Breakout Indicator(With Alerts)
It is based on the legendary trader Larry R. Williams' volatility breakout strategy.
The volatility breakout strategy is a short-term trading strategy that realizes rapid profits on a daily basis, following the upward trend of a strong upward trend that exceeds a certain level on a daily basis.
변동성 돌파 지표란 전설적인 트레이더 래리 윌리엄스(Larry R. Williams)의 변동성 돌파 전략을 기본으로 개발한 지표입니다.
변동성 돌파 전략은 일일 단위로 일정 수준 이상의 범위를 뛰어넘는 강한 상승세를 돌파 신호로 상승하는 추세를 따라가며 일 단위로 빠르게 수익을 실현하는 단기매매 전략입니다.
Relative Candle Volatility & Directionality IndexThis is an enhanced (closed-source) implementation of the Relative Candle Volatility Index (RCVI), with a Relative Candles Directionality Index (RCDI) added.
When the RCVI switch significantly positive, it indicates a sudden increase in volatility ; whereas, when the RCVI switch significantly negative, it indicates a sudden decrease in volatility -- in relative to the (just prior) market trend.
A positive (green) RCDI indicates a net positive price trend, while a negative (red) RCDI indicates a net negative price trend.
Buy/Sell strategy circle-markers, derived base on the interaction between the RCVI and the RCDI , are also introduced in this edition.
The parameters should be manually "history-matched", for a particular chart and time-frame, for the best result.
RCVI QUICK GUIDE:
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Note:
In no way is this intended as a financial/investment/trading advice. You are responsible for your own investment decisions and trades.
Please exercise your own judgement for your own trades base on your own risk-aversion level and goals as an investor or a trader. The use of OTHER indicators and analysis in conjunction (tailored to your own style of investing/trading) will help improve confidence of your analysis, for you to determine your own trade decisions.
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Please check out my other indicators sets and series, e.g.
LIVIDITIUM (dynamic levels),
AEONDRIFT (multi-levels standard deviation bands),
FUSIONGAPS (MA based oscillators),
MAJESTIC (Momentum/Acceleration/Jerk Oscillators),
PRISM (pSAR based oscillator, with RSI/StochRSI as well as Momentum/Acceleration/Jerk indicators),
PDF (parabolic SAR /w HighLow Trends Indicator/Bar-color-marking + Dynamic Fib Retrace and Extension Level)
and more to come.
Constructive feedback and suggestions are welcome.
~ JuniAiko
(=^~^=)v~
Relative Candle Volatility IndexI am not certain if something similar is already available out there. However, here's my own implementation of my simple idea of using the length of the candle-body, or wicks (high-low), to derive a Relative Volatility Index / Oscillator.
In summary: When the R.CVI is significantly positive, it indicates a sudden increase in volatility; whereas, when the R.CVI drops significantly negative, it indicates a sudden decrease in volatility -- in relative to the (just prior) market trend.
If you do wish to copy, modify, and publish an alternate version base on this script, please do not plagiarize and kindly reference/link back to this original script. =D
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Note:
In no way is this intended as a financial/investment/trading advice. You are responsible for your own investment decisions and trades.
Please exercise your own judgement for your own trades base on your own risk-aversion level and goals as an investor or a trader. The use of OTHER indicators and analysis in conjunction (tailored to your own style of investing/trading) will help improve confidence of your analysis, for you to determine your own trade decisions.
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Please check out my other indicators sets and series, e.g.
LIVIDITIUM (dynamic levels),
AEONDRIFT (multi-levels standard deviation bands),
FUSIONGAPS (MA based oscillators),
MAJESTIC (Momentum/Acceleration/Jerk Oscillators),
PRISM (pSAR based oscillator, with RSI/StochRSI as well as Momentum/Acceleration/Jerk indicators),
PDF (parabolic SAR /w HighLow Trends Indicator/Bar-color-marking + Dynamic Fib Retrace and Extension Level)
and more to come.
Constructive feedback and suggestions are welcome.
~ JuniAiko
(=^~^=)v~
Relative Volatility IndexCorrected Relative Volatility Index. This indicator was originally developed by Donald Dorsey (Stocks & Commodities V.11:6 (253-256): The Relative Volatility Index).
The indicator was revised by Dorsey in 1995 (Stocks & Commodities V.13:09 (388-391): Refining the Relative Volatility Index).
I suggest the refined RVI with optional settings. If you disabled Wilder's Smoothing and Refined RVI you will get the original version of RVI (1993, as built-in).
Also, you can choose an algorithm for calculating Standard Deviation.
EyeOn VolatilityEyeOn Volatility tracks how market volatility affects trading spreads. It adapts dynamically using recent price fluctuations and shows symmetric bid/ask bands around the chart. A live info box displays the current spread in percent, and an optional panel lets you review spread history over time.
Smart Volatility Squeeze + Trend Filter📌 Purpose
This indicator detects volatility squeeze conditions when Bollinger Bands contract inside Keltner Channels and signals potential breakout opportunities.
It also includes an optional EMA-based trend filter to align signals with the dominant market direction.
🧠 How It Works
1. Squeeze Condition
Bollinger Bands (BB): Length = 20, StdDev = 2.0 (default)
Keltner Channels (KC): EMA Length = 20, ATR Multiplier = 1.5 (default)
Squeeze ON: Occurs when BB Upper < KC Upper and BB Lower > KC Lower (low volatility zone).
2. Breakout Signals
Long Breakout: Price crosses above BB Upper after squeeze.
Short Breakout: Price crosses below BB Lower after squeeze.
3. Trend Filter (optional)
EMA(50) used to confirm breakout direction:
Long signals allowed only if price > EMA(50)
Short signals allowed only if price < EMA(50)
Toggle Use Trend Filter to enable/disable.
4. Visual & Alerts
Green circle at chart bottom indicates Squeeze ON.
Green/Red triangles mark breakouts.
Background gradually brightens during squeeze buildup.
Alerts available for long and short breakouts.
📈 How to Use
Look for Squeeze ON → then wait for breakout arrows.
Trade in breakout direction, preferably with trend filter ON.
Works best on higher timeframes (1h, 4h, D) and trending markets.
Markets: Crypto, Forex, Stocks — effective in volatile assets.
⚙️ Inputs
BB Length / StdDev
KC EMA Length / ATR Multiplier
Use Trend Filter
Trend EMA Length
⚠️ Disclaimer
This script is for educational purposes only. It does not constitute financial advice.
Always test thoroughly before live trading.
