3 Zigzag for MTF Fib Alert [MsF]Japanese below / 日本語説明は英文の後にあります。
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This indicator that automatically displays Fibonacci from each High & Low based on 3 Zigzags. It's useful for multi-timeframe analysis.
For example, Fibonacci calculated from the high and low prices (Zigzag 3 Period=100) of the upper timeframe can be displayed on the lower timeframe.
Also, you can set alerts for each Fibonacci point. It is useful when you are waiting for the price to return to the discount (50% or less) or the premium (50% or more) of the upper timeframe.
"Fib 1 - Crossing 0.00" … Trigger an alert when crossing the 0% line in Fibonacci of Zigzag1
"Fib 1 - Crossing 100.0" … Trigger an alert when crossing the 100% line in Fibonacci of Zigzag1
"Fib 1 - Crossing 23.6" … Trigger an alert when crossing the 23.6% line in Fibonacci of Zigzag1
"Fib 1 - Crossing 38.2" … Trigger an alert when crossing the 38.2% line in Fibonacci of Zigzag1
"Fib 1 - Crossing 50.0" … Trigger an alert when crossing the 50.0% line in Fibonacci of Zigzag1
"Fib 1 - Crossing 61.8" … Trigger an alert when crossing the 61.8% line in Fibonacci of Zigzag1
"Fib 1 - Crossing 76.4" … Trigger an alert when crossing the 76.4% line in Fibonacci of Zigzag1
*Same as Zigzag 1 and Zigzag 2 too.
"Choose Zig Zag Leg for fib" parameter means...
Latest : Calculate Fibonacci based on "the most recent Zigzag line".
Previous : Calculate Fibonacci based on "the previous Zigzag line".
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3つのZigzagを元に各High＆Lowからフィボナッチを自動で表示するインジケーターです。
Zigzagの期間を工夫することで、マルチタイムフレーム分析に役立ちます。
例えば、以下の設定とした場合：
Zigzag 1 Period … 8
Zigzag 2 Period … 25
Zigzag 3 Period … 100
上位時間足Zigzag（Period=100）の高値安値から形成されるフィボナッチを下位時間足に表示することができるのです。
また、このインジケーターではフィボナッチのポイント毎にアラートの設定が可能です。
上位時間足の割安価格（50％以下）や割高価格（50％以上）に価格が戻ってくるのを待っている時などに力を発揮してくれます。
"Fib 1 - Crossing 0.00" … Zigzag1のフィボナッチにおいて、0%ラインとクロスした場合にアラートを発報します
"Fib 1 - Crossing 100.0" … Zigzag1のフィボナッチにおいて、100%ラインとクロスした場合にアラートを発報します
"Fib 1 - Crossing 23.6" … Zigzag1のフィボナッチにおいて、23.6%ラインとクロスした場合にアラートを発報します
"Fib 1 - Crossing 38.2" … Zigzag1のフィボナッチにおいて、38.2%ラインとクロスした場合にアラートを発報します
"Fib 1 - Crossing 50.0" … Zigzag1のフィボナッチにおいて、50.0%ラインとクロスした場合にアラートを発報します
"Fib 1 - Crossing 61.8" … Zigzag1のフィボナッチにおいて、61.8%ラインとクロスした場合にアラートを発報します
"Fib 1 - Crossing 76.4" … Zigzag1のフィボナッチにおいて、76.4%ラインとクロスした場合にアラートを発報します
※Zigzag1およびZigzag2のフィボナッチも同様
"Choose Zig Zag Leg for fib"パラメータについて：
Latest … 一番新しいZigzagのライン（UpまたはDown）を元にフィボナッチを計算します。
Previous … ひとつ前のZigzagのライン（UpまたはDown）を元にフィボナッチを計算します。
Cerca negli script per "mtf"
[blackcat] L3 SupertrendX MTFLevel: 3
Background
A supertrend is a trend-following indicator, similar to moving averages. It is plotted against price and the current trend can be determined simply by its placement against price. It is a very simple indicator and is constructed with only two parameters - period and multiplier.
Function
This is my private version of supertrend, so I named it supertrend X. My intention was improving the inherent lag issue of supertrend indicator. It may be improved under some scenarios and may be the same as TradingView official supertrend with the same set of parameters.
Remarks
I use different color to scoring trend strength with scores ranging from 0 to 100.
0 exhibits blue color
25 exhibits green color
50 exhibits yellow color
75 exhibits red color
100 exhibits fuchsia color
others exhibit gradient color
Feedbacks are appreciated.
MACD MTF LinesThe indicator shows the MACD histogram sign (positive or negative) for several timeframes at once. You can see at a glance how the price is trending across higher and lower timeframes.
The code uses recursive calculations for the SMA and EMA to avoid lookahead errors and repainting on higher timeframes.
Note that, for lower timeframes, the line becomes yellow to the left because history is limited and there are not enough bars to calculate.
RSI Multi Alerts MTFThis indicator won't plot anything to the chart.
Please follow steps below to set your alarms based on RSI oversold and overbought levels:
1) Add indicator to the chart
2) Go to settings
3) Choose up to 8 different symbols to get alert notification
4) Choose up to 4 different timeframes
5) Set overbought and oversold levels
6) Once all is set go back to the chart and click on 3 dots to set alert in this indicator, rename your alert and confirm
7) You can remove indicator after alert is set and it'll keep working as expected
What is does:
This indicator will generate alerts based on symbols, timeframes and RSI levels settings.
It will consider overbought and oversold levels to alert in each symbol and each timeframe selected. Once these levels are achieved it will send an alert with the following information:
- Symbol name (BTC, ETH, LTC)
- Specific RSI level achieved (e.g: RSI 30, RSI 70 or any custom level)
- Timeframe (e.g: 5m, 1h, 1D)
- Current symbol price
This script will request RSI OB/OS information through request.security() function from all different symbols and timeframes settings. It also requests symbols' price (close).
Due to Tradingview limitation (40 requests calls) it can only request information for 8 symbols for this script (8 symbols X 4 timeframes = 32 + 8 symbols' price (close) = 40)
Standard symbols are Binance USDT-M Futures but you can choose any symbol from Tradingview.
Standard timeframes are 5m|15m|1h|4h but you can choose from a list.
Standard overbought and oversold levels are 70 and 30 but you can change it to other integer values.
Feel free to give feedbacks on comments section below.
Enjoy!
Bender Stochastic MTF With Buy & Sell SignalsA stochastic indicator is a technical analysis tool that uses random data points to forecast price changes in a financial security. It compares the closing price of a security to its price range over a set period of time. The indicator is designed to indicate when a security is overbought or oversold by comparing the closing price to the price range over a certain number of periods. A stochastic indicator can be used to identify potential buying or selling opportunities. It is often used in conjunction with other technical analysis tools to provide a more comprehensive analysis of market conditions.
Configurable Indicator Signals
Signal on k & d Stochastic Line Crosses
Invalidate Signal if not in a overbought or oversold pressure zone
Invalidate signal on neutral zone breach
Invalidate signal on reverse cross
Invalidate signal after a user set number of bars
Delay signal until the cross is considered strong by calculating the distance between the stochastic lines the a user set threshold
Please Note:
This indicator is also embedded in the Bender Bot strategy script. Signals and confluence identified by this indicator can be used to autonomously mange strategies. The below settings will not have any effect on this indicator's functionality when used as a stand alone indicator.
Bender Bot Strategy Confluence
Close any open trade on reverse k & d Stochastic line crosses
Require any signal and Stochastic directional confluence before opening any trade
Require any signal and Stochastic pressure to be in confluence before opening any trade
Require any signal to be in directional confluence with the Stochastic signal
Squeeze Momentum MTF [LPWN]//ENGLISH
Squeeze momentum of lazy bear, multiple time frames, It gives you information if the cycles with high temporality momentums are in harmony, by default two more momentums are shown, I prefer to use only one extra, in the options you can change the time frame of the momentums, in addition to the momentums you can add the RSI and ADX, if the momentum look small, you can change the value of general scale to make them bigger, the table gives us information on how the momentums and the adx are, in the options you can set the candles to color according to the harmony of the momentums
// SPANISH
Squeeze momentum de lazy bear, multiple time frames, te da informacion si los ciclos con momentums de temporalidad alta estan en armonia,por defecto se muestran dos momentums mas, yo prefiero usar solo uno extra, en las opcoines puedes cambiar la temporalidad de los momentums, ademas de los momentums puedes agregar el RSI y el ADX, si el momentum se ve pequeño, puedes cambiar el valor de general scale para hacerlos mas grandes, la tabla nos da infomracion de como estan los momentums y el adx, en las opciones puedes poner que las velas se pongan del color de acuerdo a la armonia de los momentums
NSDT Double MA ShadingThis script is an interesting take on Convergence and Divergence of Moving Averages. With the built-in MACD Indicator, you cannot make these adjustments to the settings.
DESCRIPTION
The top Moving Average is calculated on the High of the candle.
The bottom Move Average is calculated on the Low of the candle.
If the two are moving apart (Divergence), the shaded area between them turns Green.
If the two are moving together (Convergence), the shaded area between them turns Red.
This may help identify when a trend is becoming stronger or weaker, based on the shaded area and Moving Average direction.
POSSIBLE USAGE
For example:
If the MA's are pointing downward and the shaded area is Green - it means that average distance between the candle High and Low is getting wider, which may indicate a stronger downward movement. Then, when the shaded area turns Red, signaling the average distance between the candle High and Low are getting narrower, this may indicate that the downward movement is weakening, and may be the end of that downward trend.
SETTINGS
You can choose from EMA, SMA, WMA, RMA, HMA, TMA, and VWMA.
Although you can choose the MA Source, it is highly recommended to keep one source on the High of the candle and the other on the Low of the candle, for measure Convergence and Divergence.
All indicator settings are editable.
It can be used on Multi Timeframes (MTF).
This script is free and open source.
Fixed Fibonacci Support ResistanceI took the formula of the fibonacci from LonesomeTheBlue and made this script. You can take a look at his indicator here:
When you first add the indicator on the chart, click on the chart to select the first date and then the second date. It will then calculate the fibonacci support and resistance of the range you choose. You can also choose the date inside the inputs.
Be sure the first date is before the second date, otherwise it won't be able to show the fibonacci. If that happen, choose a correct date in the inputs.
True Accumulation/Distribution (TG fork)An accumulation/distribution indicator that works better against gaps and with trend coloring.
Accumulation/Distribution was developed by Marc Chaikin to provide insight into strength of a trend by measuring flow of buy and sell volume .
The fact that A/D only factors current period's range for calculating the volume multiplier causes problem with price gaps. They are ignored or even misinterpreted.
True Accumulation/Distribution solves the problem by using True Range instead of only relying on current period's high and low.
Most of the time, True A/D reverts to producing the same values as the original A/D. The difference between True A/D and original A/D can be better seen when a gap has occurred, True A/D has handles it better than Accumulation/Distribution which a bearish close in period's range cause it to misinterpret the strong buy pressure as sell volume
The Moving Average Cloud is simply the filling between the moving average and the True A/D. This feature was inspired by D7R ACC/DIST closed-source indicator, kudos to D7R for making such neat visual indicators (but unfortunately all closed source!).
This indicator was made to extend the original work by adding MTF support and a moving average cloud and coloring.
If you like this indicator, please show the original author RezzaHmt some love:
Liquidations by volume (TG fork)Shows actual liquidations on a per-candle basis by using the difference in volume between spot and futures markets.
i.e. volume on a futures market will be much higher if there are many liquidations.
By default, green represents short liquidations (hence a bullish move, hence why it's green), whereas red is for long liquidations (bearish move). The colors can be changed in the settings if you prefer an inverted theme.
Long liquidation data should in theory be more accurate than short liquidation data due to the inability to short on a spot market.
This indicator should be able to help identify trends by determining liquidation points in the chart.
Extended by Tartigradia to automatically detect the symbol (only for crypto assets found on Binance with a USDTPERP pair, so it works for ETH, BNB, etc) and add multi-timeframe support (MTF).
If you like the indicator, please show the original author Thomas_Davison some love:
Rule Of 20 - Fair Value Estimation by Inflation & Earnings (TG)The Rule Of 20 is a heuristic calculation to find the fair value of an asset or market given its earnings and current inflation.
Its calculation is straightforward: the fair multiple of the price or price-to-earnings ratio of a stock should be 20 minus the rate of inflation.
In math terms: fair_price-to-earnings_ratio = (20 - inflation) ; fair_value = current_price * fair_price-to-earnings_ratio / real_price-to-earnings_ratio
For example, if a stock or index was trading on 11 times earnings and inflation was 2%, then the theory would be that the fair price-to-earnings ratio would be 20-2 = 18, which is much higher than the real price-to-earnings ratio of 11, and hence the asset would be undervalued.
Conversely, a market or company that was trading on 18 times price-to-earnings ration when inflation was 8% was seen as overvalued, because of the fair price-to-earnings ratio being 20-8=12, hence much lower than the real price-to-earnings ratio of 18.
We can then project the delta between the fair PE and real PE onto the asset's value to obtain the projected fair value, which may be a target of future value the asset may reach or hover around.
For example, as of 1st November 2022, SPX stood at 3871.97, with a PE ratio of 20.14 and an inflation in the US of 7.70. Using the Rule Of 20, we find that the fair PE ratio is 20-7.7=12.3, which is much lower than the current PE ratio of 20.14 by 39%! This may indicate a future possibility of a further downside risk by 39% from current valuation levels.
The origins of this rule are unknown, although the legendary US fund manager Peter Lynch is said to have been an active proponent when he was directing the Fidelity’s Magellan fund from 1977 to 1990.
For more infos about the Rule Of 20, reading this article is recommended: www.sharesmagazine.co.uk
This indicator implements the Rule Of 20 on any asset where the Financials are availble to TradingView, and also for the entire SP:SPX index as a way to assess the wider US stock market. Technically, the calculation is a bit different for the latter, as we cannot access earnings of SPX through Financials on TradingView, so we access it using the QUANDL:MULTPL/SP500_PE_RATIO_MONTH ticker instead.
By default are displayed:
current asset value in red
fair asset value according to the Rule Of 20 in white for SPX, or different shades of purple/maroon for other assets. Note that for SPX there is only one calculation, whereas for other assets there are multiple different ways to calculate earnings, so different fair values can be computed.
fair price-to-earnings ratio (PE ratio) in light grey.
real price-to-earnings ratio in darker grey.
This indicator can be used on SP:SPX ticker, and on most NASDAQ:* tickers, since they have Financials integrated in TradingView. Stocks tickers from other exchanges may not provide Financials data, so this indicator won't work then. If this happens, try to find the same ticker on NASDAQ instead.
Note that by default, only the US stock market is considered. If you want to consider stocks or assets in other regions of the world, please change the inflation ticker to a ticker that reflect the target region's inflation.
Also adding a table to ease interpretation was considered, but then the Timeframe MTF parameter would not work, and since the big advantage of this indicator is to allow for historical comparisons, the table was dropped.
Enjoy, and keep in mind that all models are wrong, but some are useful.
Trade safely!
TG
WaveTrend 3D█ OVERVIEW
WaveTrend 3D (WT3D) is a novel implementation of the famous WaveTrend (WT) indicator and has been completely redesigned from the ground up to address some of the inherent shortcomings associated with the traditional WT algorithm.
█ BACKGROUND
The WaveTrend (WT) indicator has become a widely popular tool for traders in recent years. WT was first ported to PineScript in 2014 by the user @LazyBear, and since then, it has ascended to become one of the Top 5 most popular scripts on TradingView.
The WT algorithm appears to have origins in a lesser-known proprietary algorithm called Trading Channel Index (TCI), created by AIQ Systems in 1986 as an integral part of their commercial software suite, TradingExpert Pro. The software’s reference manual states that “TCI identifies changes in price direction” and is “an adaptation of Donald R. Lambert’s Commodity Channel Index (CCI)”, which was introduced to the world six years earlier in 1980. Interestingly, a vestige of this early beginning can still be seen in the source code of LazyBear’s script, where the final EMA calculation is stored in an intermediate variable called “tci” in the code.
█ IMPLEMENTATION DETAILS
WaveTrend 3D is an alternative implementation of WaveTrend that directly addresses some of the known shortcomings of the indicator, including its unbounded extremes, susceptibility to whipsaw, and lack of insight into other timeframes.
In the canonical WT approach, an exponential moving average (EMA) for a given lookback window is used to assess the variability between price and two other EMAs relative to a second lookback window. Since the difference between the average price and its associated EMA is essentially unbounded, an arbitrary scaling factor of 0.015 is typically applied as a crude form of rescaling but still fails to capture 20-30% of values between the range of -100 to 100. Additionally, the trigger signal for the final EMA (i.e., TCI) crossover-based oscillator is a four-bar simple moving average (SMA), which further contributes to the net lag accumulated by the consecutive EMA calculations in the previous steps.
The core idea behind WT3D is to replace the EMA-based crossover system with modern Digital Signal Processing techniques. By assuming that price action adheres approximately to a Gaussian distribution, it is possible to sidestep the scaling nightmare associated with unbounded price differentials of the original WaveTrend method by focusing instead on the alteration of the underlying Probability Distribution Function (PDF) of the input series. Furthermore, using a signal processing filter such as a Butterworth Filter, we can eliminate the need for consecutive exponential moving averages along with the associated lag they bring.
Ideally, it is convenient to have the resulting probability distribution oscillate between the values of -1 and 1, with the zero line serving as a median. With this objective in mind, it is possible to borrow a common technique from the field of Machine Learning that uses a sigmoid-like activation function to transform our data set of interest. One such function is the hyperbolic tangent function (tanh), which is often used as an activation function in the hidden layers of neural networks due to its unique property of ensuring the values stay between -1 and 1. By taking the first-order derivative of our input series and normalizing it using the quadratic mean, the tanh function performs a high-quality redistribution of the input signal into the desired range of -1 to 1. Finally, using a dual-pole filter such as the Butterworth Filter popularized by John Ehlers, excessive market noise can be filtered out, leaving behind a crisp moving average with minimal lag.
Furthermore, WT3D expands upon the original functionality of WT by providing:
First-class support for multi-timeframe (MTF) analysis
Kernel-based regression for trend reversal confirmation
Various options for signal smoothing and transformation
A unique mode for visualizing an input series as a symmetrical, three-dimensional waveform useful for pattern identification and cycle-related analysis
█ SETTINGS
This is a summary of the settings used in the script listed in roughly the order in which they appear. By default, all default colors are from Google's TensorFlow framework and are considered to be colorblind safe.
Source: The input series. Usually, it is the close or average price, but it can be any series.
Use Mirror: Whether to display a mirror image of the source series; for visualizing the series as a 3D waveform similar to a soundwave.
Use EMA: Whether to use an exponential moving average of the input series.
EMA Length: The length of the exponential moving average.
Use COG: Whether to use the center of gravity of the input series.
COG Length: The length of the center of gravity.
Speed to Emphasize: The target speed to emphasize.
Width: The width of the emphasized line.
Display Kernel Moving Average: Whether to display the kernel moving average of the signal. Like PCA, an unsupervised Machine Learning technique whereby neighboring vectors are projected onto the Principal Component.
Display Kernel Signal: Whether to display the kernel estimator for the emphasized line. Like the Kernel MA, it can show underlying shifts in bias within a more significant trend by the colors reflected on the ribbon itself.
Show Oscillator Lines: Whether to show the oscillator lines.
Offset: The offset of the emphasized oscillator plots.
Fast Length: The length scale factor for the fast oscillator.
Fast Smoothing: The smoothing scale factor for the fast oscillator.
Normal Length: The length scale factor for the normal oscillator.
Normal Smoothing: The smoothing scale factor for the normal frequency.
Slow Length: The length scale factor for the slow oscillator.
Slow Smoothing: The smoothing scale factor for the slow frequency.
Divergence Threshold: The number of bars for the divergence to be considered significant.
Trigger Wave Percent Size: How big the current wave should be relative to the previous wave.
Background Area Transparency Factor: Transparency factor for the background area.
Foreground Area Transparency Factor: Transparency factor for the foreground area.
Background Line Transparency Factor: Transparency factor for the background line.
Foreground Line Transparency Factor: Transparency factor for the foreground line.
Custom Transparency: Transparency of the custom colors.
Total Gradient Steps: The maximum amount of steps supported for a gradient calculation is 256.
Fast Bullish Color: The color of the fast bullish line.
Normal Bullish Color: The color of the normal bullish line.
Slow Bullish Color: The color of the slow bullish line.
Fast Bearish Color: The color of the fast bearish line.
Normal Bearish Color: The color of the normal bearish line.
Slow Bearish Color: The color of the slow bearish line.
Bullish Divergence Signals: The color of the bullish divergence signals.
Bearish Divergence Signals: The color of the bearish divergence signals.
█ ACKNOWLEDGEMENTS
@LazyBear - For authoring the original WaveTrend port on TradingView
@PineCoders - For the beautiful color gradient framework used in this indicator
@veryfid - For the inspiration of using mirrored signals for cycle analysis and using multiple lookback windows as proxies for other timeframes
Expected Move w/ Volatility Panel (advanced) [Loxx]This indicator shows the expected range of movement of price given the assumption that price is log-normally distributed. This includes 3 multiples of standard deviation and 1 user selected level input as a multiple of standard deviation. Expected assumes that volatility remains static on the next bar. In reality, this may or may not be the case, so use caution when making broad assumptions about the levels shown when using this indicator. However, these levels match the same levels on Loxx's backtests and Multi-Panel indicator. These static levels are used as the take profit targets and stoploss on all Loxx's scripts previously posted.
This indicator can be be used on all timeframes, but the internal timeframe must be higher than the current timeframe or an error is thrown. The purpose for internal MTF is so that you can track the deviation range from higher timeframes on lower timeframes. When "current bar" is selected, this indicator will change with live prices changes. This is useful if you wish to enter a trade before the current bar closes and need to know the deviation ranges before the close. Current bar is also useful to see the past ranges of literally that bar. When "past bar" is selected, then the values shown on the current bar are values that were calculated on the last bar. The previous bar setting is useful to track price changes with the assumption that you entered a trade at the close of the previous bar. The default set to the previous bar. (careful, this default setting won't match Loxx's Muti-Panel tool since the Multi-Panel is built using the current bar. To make them match, you must change this setting to current bar)
I've included the ability for you to smooth the output around a moving average. Included are Loxx's Moving Averages. There are 41 to choose from. See more details here:
Smoothing applied yielding Keltner Channels
Also included are various UI options to manipulate line styling and colors.
Volatility Panel
Shows information about user selected volatility included confidence range of the chosen volatility. The following volatility types are included with additional volatility types to added in future releases.
Close-to-Close
Close-to-Close volatility is a classic and most commonly used volatility measure, sometimes referred to as historical volatility .
Volatility is an indicator of the speed of a stock price change. A stock with high volatility is one where the price changes rapidly and with a bigger amplitude. The more volatile a stock is, the riskier it is.
Close-to-close historical volatility calculated using only stock's closing prices. It is the simplest volatility estimator. But in many cases, it is not precise enough. Stock prices could jump considerably during a trading session, and return to the open value at the end. That means that a big amount of price information is not taken into account by close-to-close volatility .
Despite its drawbacks, Close-to-Close volatility is still useful in cases where the instrument doesn't have intraday prices. For example, mutual funds calculate their net asset values daily or weekly, and thus their prices are not suitable for more sophisticated volatility estimators.
Parkinson
Parkinson volatility is a volatility measure that uses the stock’s high and low price of the day.
The main difference between regular volatility and Parkinson volatility is that the latter uses high and low prices for a day, rather than only the closing price. That is useful as close to close prices could show little difference while large price movements could have happened during the day. Thus Parkinson's volatility is considered to be more precise and requires less data for calculation than the close-close volatility .
One drawback of this estimator is that it doesn't take into account price movements after market close. Hence it systematically undervalues volatility . That drawback is taken into account in the Garman-Klass's volatility estimator.
Garman-Klass
Garman Klass is a volatility estimator that incorporates open, low, high, and close prices of a security.
Garman-Klass volatility extends Parkinson's volatility by taking into account the opening and closing price. As markets are most active during the opening and closing of a trading session, it makes volatility estimation more accurate.
Garman and Klass also assumed that the process of price change is a process of continuous diffusion (geometric Brownian motion). However, this assumption has several drawbacks. The method is not robust for opening jumps in price and trend movements.
Despite its drawbacks, the Garman-Klass estimator is still more effective than the basic formula since it takes into account not only the price at the beginning and end of the time interval but also intraday price extremums.
Researchers Rogers and Satchel have proposed a more efficient method for assessing historical volatility that takes into account price trends. See Rogers-Satchell Volatility for more detail.
Rogers-Satchell
Rogers-Satchell is an estimator for measuring the volatility of securities with an average return not equal to zero.
Unlike Parkinson and Garman-Klass estimators, Rogers-Satchell incorporates drift term (mean return not equal to zero). As a result, it provides a better volatility estimation when the underlying is trending.
The main disadvantage of this method is that it does not take into account price movements between trading sessions. It means an underestimation of volatility since price jumps periodically occur in the market precisely at the moments between sessions.
A more comprehensive estimator that also considers the gaps between sessions was developed based on the Rogers-Satchel formula in the 2000s by Yang-Zhang. See Yang Zhang Volatility for more detail.
Yang-Zhang
Yang Zhang is a historical volatility estimator that handles both opening jumps and the drift and has a minimum estimation error.
We can think of the Yang-Zhang volatility as the combination of the overnight (close-to-open volatility ) and a weighted average of the Rogers-Satchell volatility and the day’s open-to-close volatility . It considered being 14 times more efficient than the close-to-close estimator.
Garman-Klass-Yang-Zhang
Garman Klass is a volatility estimator that incorporates open, low, high, and close prices of a security.
Garman-Klass volatility extends Parkinson's volatility by taking into account the opening and closing price. As markets are most active during the opening and closing of a trading session, it makes volatility estimation more accurate.
Garman and Klass also assumed that the process of price change is a process of continuous diffusion (geometric Brownian motion). However, this assumption has several drawbacks. The method is not robust for opening jumps in price and trend movements.
Despite its drawbacks, the Garman-Klass estimator is still more effective than the basic formula since it takes into account not only the price at the beginning and end of the time interval but also intraday price extremums.
Researchers Rogers and Satchel have proposed a more efficient method for assessing historical volatility that takes into account price trends. See Rogers-Satchell Volatility for more detail.
Exponential Weighted Moving Average
The Exponentially Weighted Moving Average (EWMA) is a quantitative or statistical measure used to model or describe a time series. The EWMA is widely used in finance, the main applications being technical analysis and volatility modeling.
The moving average is designed as such that older observations are given lower weights. The weights fall exponentially as the data point gets older – hence the name exponentially weighted.
The only decision a user of the EWMA must make is the parameter lambda. The parameter decides how important the current observation is in the calculation of the EWMA. The higher the value of lambda, the more closely the EWMA tracks the original time series.
Standard Deviation of Log Returns
This is the simplest calculation of volatility . It's the standard deviation of ln(close/close(1))
Pseudo GARCH(2,2)
This is calculated using a short- and long-run mean of variance multiplied by θ.
θavg(var ;M) + (1 − θ) avg (var ;N) = 2θvar/(M+1-(M-1)L) + 2(1-θ)var/(M+1-(M-1)L)
Solving for θ can be done by minimizing the mean squared error of estimation; that is, regressing L^-1var - avg (var; N) against avg (var; M) - avg (var; N) and using the resulting beta estimate as θ.
Average True Range
The average true range (ATR) is a technical analysis indicator, introduced by market technician J. Welles Wilder Jr. in his book New Concepts in Technical Trading Systems, that measures market volatility by decomposing the entire range of an asset price for that period.
The true range indicator is taken as the greatest of the following: current high less the current low; the absolute value of the current high less the previous close; and the absolute value of the current low less the previous close. The ATR is then a moving average, generally using 14 days, of the true ranges.
True Range Double
A special case of ATR that attempts to correct for volatility skew.
Chi-squared Confidence Interval:
Confidence interval of volatility is calculated using an inverse CDF of a Chi-Squared Distribution. You can change the volatility input used to either realized, upper confidence interval, or lower confidence interval. This is included in case you'd like to see how far price can extend if volatility hits it's upper or lower confidence levels. Generally, you'd just used realized volatility , so I wouldn't change this setting.
Inverse CDF of a Chi-Squared Distribution
The chi-square distribution is a one-parameter family of curves. The parameter ν is the degrees of freedom.
The icdf of the chi-square distribution is
x=F^−1(p∣ν) = {x:F(x∣ν) = p}
where
p=F(x∣ν)= ∫ (t^(v-2)/2 * e^t/2) / (2^(v/2) / Γ(v/2))
ν is the degrees of freedom, and Γ( · ) is the Gamma function. The result p is the probability that a single observation from the chi-square distribution with ν degrees of freedom falls in the interval .
Related Indicators
Multi-Panel: Trade-Volatility-Probability
Variety Distribution Probability Cone
Liquidity Levels MTF - SonarlabThis indicator uses Pivot Points to identify Liquidity Levels in the market. Liquidity Levels are levels in the market where you would expect price to be pulled towards.
Liquidity Levels by Sonarlab also has an option to show Higher Timeframe Liquidity Levels.
Below are the indicators settings:
Liquidity Mitigation Options
The Indicator has options for you to choose what happens to the Liquidity line/boxes once it has been mitigated. Either Keep them on the chart, or remove them.
Display Styles
Choose how the levels are displayed, either with Lines or Boxes.
Set the your Extension options, by keeping the lines/boxes "short" or extend to current price, or maximum to the right
Colors and Styles
Set colors and styles for all lines and boxes
Dashboard With Strength Trend & Phase MarketThis is a multi timeframe (MTF) MACDV Dashboard and comes with additional features to show you whether there is currently a bullish or bearish cross for the EMA period you have selected in the settings menu, and identify the state of the market phase.
original Code : @KP_House & @JustInNovel
SFC Smart Money Manipulation - MTF ZonesThis indicator shows the most important manipulated zones - true support and resistance.
The indicator can show the zones from different time frames - 1H, 4H, D and the current TF.
Order Block definition - small candle or few consecutive candles, where banks place buy and sell orders in order to manipulate the price. After price is manipulated and moved in one direction, the banks are in draw down, that is why they manipulate the price one more time before the true move, retesting these candles (closing losing positions).
FU candles
FU candles are most manipulated candles and create very strong reaction zones. These are the true zones, where the banks place their orders.
Why they are so strong? The answer is very simple - these candles clear the liquidity from the previous ones. After the liquidity is cleared ( all stop losses/pending orders are triggered), price reveal the true direction and move very fast.
FU candles are type of Order Blocks - the most powerful one.
Because the most volume is in the body of the order block. The indicator shows not only the FU candle, but the body of the order block.
There are two types of FU candles :
(only full FU candles are displayed as zones, because they are much significant)
1) Full fu, where the current candle completely engulf the previous one, after taking the liquidity. (displayed as F)
2) Current candle only take liquidity from the previous one, but failed to engulf it. (displayed as A)
9 day simple moving average is also displayed. When the price form Fu candle above/under the MA, there is a better chance for reversal.
When FU candles are retested the transparency will change, showing that the zones may have less impact.
Order Blocks
Only the current order blocks are displayed. Price react very often from the 50% level, that is why this level is also displayed.
Rejections
Rejections are doji candles or candles with big wicks. These rejections very often lead to reversals or deep pullbacks. But before the true move, price test the rejection levels. The retest is not always, but very often of the 50% of the wick.
The rejections are very important price zone.
The indicator can show the zones from different time frames - 1H, 4H, D and the current TF. When wicks are retested the transparency and colour will change, showing that the wicks may have less impact or no more impact.
Settings
-The colour and transparency of the zones can be changed.
- Multi time frames zones could be disabled.
- Doji settings
- Length of the moving average
How to use
If price reach one of the displayed zones. The trader should be prepared for price reaction. This reaction could lead to reversal, pull back or trading range.
The trader should have bias from the higher time frames and watch for signs of manipulations on smaller time frames.
