Truly Iterative Gaussian ChannelOVERVIEW
The Truly Iterative Gaussian Channel is a robust channeling system that integrates a Gaussian smoothing kernel with a rolling standard deviation to create dynamically adaptive upper and lower boundaries around price. This indicator provides a smooth, yet responsive representation of price movements while minimizing lag and dynamically adjusting channel width to reflect real-time market volatility. Its versatility makes it effective across various timeframes and trading styles, offering significant potential for experimentation and integration into advanced trading systems.
TRADING USES
The Gaussian indicator can be used for multiple trading strategies. Trend following relies on the middle Gaussian line to gauge trend direction: prices above this line indicate bullish momentum, while prices below signal bearish momentum. The upper and lower boundaries act as dynamic support and resistance levels, offering breakout or pullback entry opportunities. Mean reversion focuses on identifying reversal setups when price approaches or breaches the outer boundaries, aiming for a return to the Gaussian centerline. Volatility filtering helps assess market conditions, with narrow channels indicating low volatility or consolidation and suggesting fewer trading opportunities or an impending breakout. Adaptive risk management uses channel width to adjust for market volatility, with wider channels signaling higher risk and tighter channels indicating lower volatility and potentially safer entry points.
THEORY
Gaussian kernel smoothing, derived from the Gaussian normal distribution, is a cornerstone of probability and statistics, valued for its ability to reduce noise while preserving critical signal features. In this indicator, it ensures price movements are smoothed with precision, minimizing distortion while maintaining responsiveness to market dynamics.
The rolling standard deviation complements this by dynamically measuring price dispersion from the mean, enabling the channel to adapt in real time to changing market conditions. This combination leverages the mathematical correctness of both tools to balance smoothness and adaptability.
An iterative framework processes data efficiently, bar by bar, without recalculating historical value to ensure reliability and preventing repainting to create a mathematically grounded channel system suitable for a wide range of market environments.
The Gaussian channel excels at filtering noise while remaining responsive to price action, providing traders with a dependable tool for identifying trends, reversals, and volatility shifts with consistency and precision.
CALIBRATION
Calibration of the Gaussian channel involves adjusting its length to modify sensitivity and adaptability based on trading style. Shorter lengths (e.g., 50-100) are ideal for intraday traders seeking quick responses to price fluctuations. Medium lengths (e.g., 150-200) cater to swing traders aiming to capture broader market trends. Longer lengths (e.g., 250-400+) are better suited for positional traders focusing on long-term price movements and stability.
MARKET USAGE
Stock, Forex, Crypto, Commodities, and Indices.
Standarddevation
Dema Percentile Standard DeviationDema Percentile Standard Deviation
The Dema Percentile Standard Deviation indicator is a robust tool designed to identify and follow trends in financial markets.
How it works?
This code is straightforward and simple:
The price is smoothed using a DEMA (Double Exponential Moving Average).
Percentiles are then calculated on that DEMA.
When the closing price is below the lower percentile, it signals a potential short.
When the closing price is above the upper percentile and the Standard Deviation of the lower percentile, it signals a potential long.
Settings
Dema/Percentile/SD/EMA Length's: Defines the period over which calculations are made.
Dema Source: The source of the price data used in calculations.
Percentiles: Selects the type of percentile used in calculations (options include 60/40, 60/45, 55/40, 55/45). In these settings, 60 and 55 determine percentile for long signals, while 45 and 40 determine percentile for short signals.
Features
Fully Customizable
Fully Customizable: Customize colors to display for long/short signals.
Display Options: Choose to show long/short signals as a background color, as a line on price action, or as trend momentum in a separate window.
EMA for Confluence: An EMA can be used for early entries/exits for added signal confirmation, but it may introduce noise—use with caution!
Built-in Alerts.
Indicator on Diffrent Assets
INDEX:BTCUSD 1D Chart (6 high 56 27 60/45 14)
CRYPTO:SOLUSD 1D Chart (24 open 31 20 60/40 14)
CRYPTO:RUNEUSD 1D Chart (10 close 56 14 60/40 14)
Remember no indicator would on all assets with default setting so FAFO with setting to get your desired signal.
STANDARD DEVIATION INDICATOR BY WISE TRADERWISE TRADER STANDARD DEVIATION SETUP: The Ultimate Volatility and Trend Analysis Tool
Unlock the power of STANDARD DEVIATIONS like never before with the this indicator, a versatile and comprehensive tool designed for traders who seek deeper insights into market volatility, trend strength, and price action. This advanced indicator simultaneously plots three sets of customizable Deviations, each with unique settings for moving average types, standard deviations, and periods. Whether you’re a swing trader, day trader, or long-term investor, the STANDARD DEVIATION indicator provides a dynamic way to spot potential reversals, breakouts, and trend-following opportunities.
Key Features:
STANDARD DEVIATIONS Configuration : Monitor three different Bollinger Bands at the same time, allowing for multi-timeframe analysis within a single chart.
Customizable Moving Average Types: Choose from SMA, EMA, SMMA (RMA), WMA, and VWMA to calculate the basis of each band according to your preferred method.
Dynamic Standard Deviations: Set different standard deviation multipliers for each band to fine-tune sensitivity for various market conditions.
Visual Clarity: Color-coded bands with adjustable thicknesses provide a clear view of upper and lower boundaries, along with fill backgrounds to highlight price ranges effectively.
Enhanced Trend Detection: Identify potential trend continuation, consolidation, or reversal zones based on the position and interaction of price with the three bands.
Offset Adjustment: Shift the bands forward or backward to analyze future or past price movements more effectively.
Why Use Triple STANDARD DEVIATIONS ?
STANDARD DEVIATIONS are a popular choice among traders for measuring volatility and anticipating potential price movements. This indicator takes STANDARD DEVIATIONS to the next level by allowing you to customize and analyze three distinct bands simultaneously, providing an unparalleled view of market dynamics. Use it to:
Spot Volatility Expansion and Contraction: Track periods of high and low volatility as prices move toward or away from the bands.
Identify Overbought or Oversold Conditions: Monitor when prices reach extreme levels compared to historical volatility to gauge potential reversal points.
Validate Breakouts: Confirm the strength of a breakout when prices move beyond the outer bands.
Optimize Risk Management: Enhance your strategy's risk-reward ratio by dynamically adjusting stop-loss and take-profit levels based on band positions.
Ideal For:
Forex, Stocks, Cryptocurrencies, and Commodities Traders looking to enhance their technical analysis.
Scalpers and Day Traders who need rapid insights into market conditions.
Swing Traders and Long-Term Investors seeking to confirm entry and exit points.
Trend Followers and Mean Reversion Traders interested in combining both strategies for maximum profitability.
Harness the full potential of STANDARD DEVIATIONS with this multi-dimensional approach. The "STANDARD DEVIATIONS " indicator by WISE TRADER will become an essential part of your trading arsenal, helping you make more informed decisions, reduce risks, and seize profitable opportunities.
Who is WISE TRADER ?
Wise Trader is a highly skilled trader who launched his channel in 2020 during the COVID-19 pandemic, quickly building a loyal following. With thousands of paid subscribed members and over 70,000 YouTube subscribers, Wise Trader has become a trusted authority in the trading world. He is known for his ability to navigate significant events, such as the Indian elections and stock market crashes, providing his audience with valuable insights into market movements and volatility. With a deep understanding of macroeconomics and its correlation to global stock markets, Wise Trader shares informed strategies that help traders make better decisions. His content covers technical analysis, trading setups, economic indicators, and market trends, offering a comprehensive approach to understanding financial markets. The channel serves as a go-to resource for traders who want to enhance their skills and stay informed about key market developments.
Panoramic VWAP### Panoramic VWAP Indicator Overview
The Panoramic VWAP indicator provides a way to display up to four Volume Weighted Average Price (VWAP) lines on a chart, each anchored to different timeframes. This indicator also includes options for displaying standard deviation bands and close lines, offering a comprehensive view of price action across multiple time horizons.
### Key Features
Quad VWAPs : The indicator allows for the display of four VWAP lines simultaneously. Each line can be set to a different timeframe, enabling traders to analyze market conditions across various periods on a single chart.
Standard Deviation Bands : Users can enable bands around each VWAP line, which represent standard deviations or percentage levels from the VWAP. These bands help in assessing volatility and identifying potential overbought or oversold conditions.
Close Lines : The indicator includes an option to show close lines, marking the price's closing level relative to the VWAP. This feature is useful for examining how the market closes in relation to VWAP, which can be important for understanding trend strength or potential reversals.
### How It Looks
VWAP Lines : Multiple VWAP lines are displayed, each reflecting different timeframes. The lines change color depending on whether the price is above or below the VWAP, indicating bullish or bearish momentum.
Bands : Optional bands around the VWAP lines provide a visual indication of volatility, with the potential to identify overbought or oversold areas.
Close Lines : These lines represent the price's closing level relative to the VWAP and can be displayed to add further context to the analysis.
### How to Use It
Trend Analysis :
- Price above a VWAP line indicates bullish momentum .
- Price below a VWAP line suggests bearish momentum .
Support and Resistance :
- VWAP lines often act as dynamic support and resistance. Price approaching a VWAP line from above may find support, while approaching from below may encounter resistance.
Volatility Assessment :
- Bands around the VWAP lines can signal areas of potential reversal. Upper bands may indicate overbought conditions, while lower bands may indicate oversold conditions.
Multiple Timeframe Analysis :
- The ability to display VWAPs from different timeframes simultaneously allows for the identification of confluence zones, where multiple VWAP levels align, indicating potentially significant support or resistance levels.
Customization :
- The indicator settings are customizable, allowing users to choose which VWAP lines, bands, and close lines to display, along with adjustments for visual preferences like line thickness and colors.
### Practical Application
Intraday Trading : Traders can use the VWAPs and bands to identify potential entry and exit points during the trading day based on price interactions with these levels.
Swing Trading : Monitoring VWAP lines across different timeframes can help identify key levels where price might reverse or gain momentum, aiding in decisions about holding or exiting positions.
Long-Term Analysis : VWAP lines on higher timeframes can serve as dynamic support or resistance levels, providing context for long-term trend analysis and investment decisions.
The Panoramic VWAP indicator allows for a detailed analysis of price trends and levels across multiple timeframes, combining VWAPs, standard deviation bands, and close lines in a single, customizable tool.
Options Overlay [Pro] IVR IV Skew Delta Exp.mv MurreyMath Expiry
𝗧𝗵𝗲 𝗳𝗶𝗿𝘀𝘁 𝗿𝗲𝗮𝗹 𝗼𝗽𝘁𝗶𝗼𝗻𝘀 𝗱𝗮𝘁𝗮 𝗶𝗻𝗱𝗶𝗰𝗮𝘁𝗼𝗿 𝗼𝗻 𝗧𝗿𝗮𝗱𝗶𝗻𝗴𝗩𝗶𝗲𝘄, 𝗮𝘃𝗮𝗶𝗹𝗮𝗯𝗹𝗲 𝗳𝗼𝗿 𝗼𝘃𝗲𝗿 𝟭𝟱𝟬+ 𝗹𝗶𝗾𝘂𝗶𝗱 𝗨𝗦 𝗺𝗮𝗿𝗸𝗲𝘁 𝘀𝘆𝗺𝗯𝗼𝗹𝘀.
🔃 Auto-Updating Option Metrics without refresh!
🍒 Developed and maintained by option traders for option traders.
📈 Specifically designed for TradingView users who trade options.
Our indicator provides essential key metrics such as:
✅ IVRank
✅ IVx
✅ 5-Day IVx Change
✅ Delta curves and interpolated distances
✅ Expected move curve
✅ Standard deviation (STD1) curve
✅ Vertical Pricing Skew
✅ Horizontal IVx Skew
✅ Delta Skew
like TastyTrade, TOS, IBKR etc, but in a much more visually intuitive way. See detailed descriptions below.
If this isn't enough, we also include a unique grid system designed specifically for options traders. This package features our innovative dynamic grid system:
✅ Enhanced Murrey Math levels (horizontal scale)
✅ Options expirations (vertical scale)
Designed to help you assess market conditions and make well-informed trading decisions, this tool is an essential addition for every serious options trader!
Ticker Information:
This indicator is currently implemented for more than 150 liquid US market tickers and we are continuously expanding the list:
SP:SPX AMEX:SPY NASDAQ:QQQ NASDAQ:TLT AMEX:GLD
NYSE:AA NASDAQ:AAL NASDAQ:AAPL NYSE:ABBV NASDAQ:ABNB NASDAQ:AMD NASDAQ:AMZN AMEX:ARKK NASDAQ:AVGO NYSE:AXP NYSE:BA NYSE:BABA NYSE:BAC NASDAQ:BIDU AMEX:BITO NYSE:BMY NYSE:BP NASDAQ:BYND NYSE:C NYSE:CAT NYSE:CCJ NYSE:CCL NASDAQ:COIN NYSE:COP NASDAQ:COST NYSE:CRM NASDAQ:CRWD NASDAQ:CSCO NYSE:CVNA NYSE:CVS NYSE:CVX NYSE:DAL NASDAQ:DBX AMEX:DIA NYSE:DIS NASDAQ:DKNG NASDAQ:EBAY NASDAQ:ETSY NASDAQ:EXPE NYSE:F NYSE:FCX NYSE:FDX AMEX:FXI AMEX:GDX AMEX:GDXJ NYSE:GE NYSE:GM NYSE:GME NYSE:GOLD NASDAQ:GOOG NASDAQ:GOOGL NYSE:GPS NYSE:GS NASDAQ:HOOD NYSE:IBM NASDAQ:IEF NASDAQ:INTC AMEX:IWM NASDAQ:JD NYSE:JNJ NYSE:JPM NYSE:JWN NYSE:KO NYSE:LLY NYSE:LOW NYSE:LVS NYSE:MA NASDAQ:MARA NYSE:MCD NYSE:MET NASDAQ:META NYSE:MGM NYSE:MMM NYSE:MPC NYSE:MRK NASDAQ:MRNA NYSE:MRO NASDAQ:MRVL NYSE:MS NASDAQ:MSFT AMEX:MSOS NYSE:NCLH NASDAQ:NDX NYSE:NET NASDAQ:NFLX NYSE:NIO NYSE:NKE NASDAQ:NVDA NASDAQ:ON NYSE:ORCL NYSE:OXY NASDAQ:PEP NYSE:PFE NYSE:PINS NYSE:PLTR NASDAQ:PTON NASDAQ:PYPL NASDAQ:QCOM NYSE:RBLX NYSE:RCL NASDAQ:RIOT NASDAQ:RIVN NASDAQ:ROKU NASDAQ:SBUX NYSE:SHOP AMEX:SLV NASDAQ:SMCI NASDAQ:SMH NYSE:SNAP NYSE:SQ NYSE:T NYSE:TGT NASDAQ:TQQQ NASDAQ:TSLA NYSE:TSM NASDAQ:TTD NASDAQ:TXN NYSE:U NASDAQ:UAL NYSE:UBER AMEX:UNG NYSE:UPS NASDAQ:UPST AMEX:USO NYSE:V AMEX:VXX NYSE:VZ NASDAQ:WBA NYSE:WFC NYSE:WMT NASDAQ:WYNN NYSE:X AMEX:XHB AMEX:XLE AMEX:XLF AMEX:XLI AMEX:XLK AMEX:XLP AMEX:XLU AMEX:XLV AMEX:XLY NYSE:XOM NYSE:XPEV CBOE:XSP NASDAQ:ZM
How does the indicator work and why is it unique?
This Pine Script indicator is a complex tool designed to provide various option metrics and visualization tools for options market traders. The indicator extracts raw options data from an external data provider (ORATS), processes and refines the delayed data package using pineseed, and sends it to TradingView, visualizing the data using specific formulas (see detailed below) or interpolated values (e.g., delta distances). This method of incorporating options data into a visualization framework is unique and entirely innovative on TradingView.
The indicator aims to offer a comprehensive view of the current state of options for the implemented instruments, including implied volatility (IV), IV rank (IVR), options skew, and expected market movements, which are objectively measured as detailed below.
The options metrics we display may be familiar to options traders from various major brokerage platforms such as TastyTrade, IBKR, TOS, Tradier, TD Ameritrade, Schwab, etc.
🟨 𝗗𝗘𝗧𝗔𝗜𝗟𝗘𝗗 𝗗𝗢𝗖𝗨𝗠𝗘𝗡𝗧𝗔𝗧𝗜𝗢𝗡 🟨
🔶 Auto-Updating Option Metrics and Curved Lines
🔹 Interpolated DELTA Curves (16,20,25,30,40)
In our indicator, the curve layer settings allow you to choose the delta value for displaying the delta curve: 16, 20, 25, 30, or even 40. The color of the curve can be customized, and you can also hide the delta curve by selecting the "-" option.
It's important to mention that we display interpolated deltas from the actual option chain of the underlying asset using the Black-Scholes model. This ensures that the 16 delta truly reflects the theoretical, but accurate, 16 delta distance. (For example, deltas shown by brokerages for individual strikes are rounded; a 0.16 delta might actually be 0.1625.)
🔹 Expected Move Curve (Exp.mv)
The expected move is the predicted dollar change in the underlying stock's price by a given option's expiration date, with 68% certainty. It is calculated using the expiration's pricing and implied volatility levels. We chose the TastyTrade method for calculating expected move, as we found it to be the most expressive.
Expected Move Calculation
Expected Move = (ATM straddle price x 0.6) + (1st OTM strangle price x 0.3) + (2nd OTM strangle price x 0.1)
For example , if stock XYZ is trading at 121 and the ATM straddle is 4.40, the 120/122 strangle is 3.46, and the 119/123 strangle is 2.66, the expected move is calculated as follows: 4.40 x 0.60 = 2.64; 3.46 x 0.30 = 1.04; 2.66 x 0.10 = 0.27; Expected move = 2.64 + 1.04 + 0.27 = ±3.9
In this example below, the TastyTrade platform indicates the expected move on the option chain with a brown color, and the exact value is displayed behind the ± symbol for each expiration. By default, we also use brown for this indication, but this can be changed or the curve display can be turned off.
🔹 Standard Deviation Curve (1 STD)
One standard deviation of a stock encompasses approximately 68.2% of outcomes in a distribution of occurrences based on current implied volatility.
We use the expected move formula to calculate the one standard deviation range of a stock. This calculation is based on the days-to-expiration (DTE) of our option contract, the stock price, and the implied volatility of a stock:
Calculation:
Standard Deviation = Closing Price * Implied Volatility * sqrt(Days to Expiration / 365)
According to options literature, there is a 68% probability that the underlying asset will fall within this one standard deviation range at expiration.
If the 1 STD and Exp.mv displays are both enabled, the indicator fills the area between them with a light gray color. This is because both represent probability distributions that appear as a "bell curve" when graphed, making it visually appealing.
Tip and Note:
The 1 STD line might appear jagged at times , which does not indicate a problem with the indicator. This is normal immediately after market open (e.g., during the first data refresh of the day) or if the expirations are illiquid (e.g., weekly expirations). The 1 STD value is calculated based on the aggregated IVx for the expirations, and the aggregated IVx value for weekly expirations updates less frequently due to lower trading volume. In such cases, we recommend enabling the "Only Monthly Expirations" option to smooth out the bell curve.
∑ Quant Observation:
The values of the expected move and the 1st standard deviation (1STD) will not match because they use different calculation methods, even though both are referred to as representing 68% of the underlying asset's movement in options literature. The expected move is based on direct market pricing of ATM options. The 1STD, on the other hand, uses the averaged implied volatility (IVX) for the given expiration to determine its value. Based on our experience, it is better to consider the area between the expected move and the 1STD as the true representation of the original 68% rule.
🔶 IVR Dashboard Panel Rows
🔹 IVR (IV Rank)
The Implied Volatility Rank (IVR) indicator helps options traders assess the current level of implied volatility (IV) in comparison to the past 52 weeks. IVR is a useful metric to determine whether options are relatively cheap or expensive. This can guide traders on whether to buy or sell options. We calculate IVrank, like TastyTrade does.
IVR Calculation:
IV Rank = (current IV - 52 week IV low) / (52 week IV high - 52 week IV low)
IVR Levels and Interpretations:
IVR 0-10 (Green): Very low implied volatility rank. Options might be "cheap," potentially a good time to buy options.
IVR 10-35 (White): Normal implied volatility rank. Options pricing is relatively standard.
IVR 35-50 (Orange): Almost high implied volatility rank.
IVR 50-75 (Red): Definitely high implied volatility rank. Options might be "expensive," potentially a good time to sell options for higher premiums.
IVR above 75 (Highlighted Red): Ultra high implied volatility rank. Indicates very high levels, suggesting a favorable time for selling options.
The panel refreshes automatically if the symbol is implemented. You can hide the panel or change the position and size.
🔹IVx (Implied Volatility Index)
The Implied Volatility Index (IVx) displayed in the option chain is calculated similarly to the VIX. The Cboe uses standard and weekly SPX options to measure the expected volatility of the S&P 500. A similar method is utilized to calculate IVx for each option expiration cycle.
For our purposes on the IVR Panel, we aggregate the IVx values specifically for the 35-70 day monthly expiration cycle . This aggregated value is then presented in the screener and info panel, providing a clear and concise measure of implied volatility over this period.
IVx Color coding:
IVx above 30 is displayed in orange.
IVx above 60 is displayed in red
IVx on curve:
The IVx values for each expiration can be viewed by hovering the mouse over the colored tooltip labels above the Curve.
IVx avg on IVR panel :
If the option is checked in the IVR panel settings, the IVR panel will display the average IVx values up to the optimal expiration.
Important Note:
The IVx value alone does not provide sufficient context. There are stocks that inherently exhibit high IVx values. Therefore, it is crucial to consider IVx in conjunction with the Implied Volatility Rank (IVR), which measures the IVx relative to its own historical values. This combined view helps in accurately assessing the significance of the IVx in relation to the specific stock's typical volatility behavior.
This indicator offers traders a comprehensive view of implied volatility, assisting them in making informed decisions by highlighting both the absolute and relative volatility measures.
🔹IVx 5 days change %
We are displaying the five-day change of the IV Index (IVx value). The IV Index 5-Day Change column provides quick insight into recent expansions or decreases in implied volatility over the last five trading days.
Traders who expect the value of options to decrease might view a decrease in IVX as a positive signal. Strategies such as Strangle and Ratio Spread can benefit from this decrease.
On the other hand, traders anticipating further increases in IVX will focus on the rising IVX values. Strategies like Calendar Spread or Diagonal Spread can take advantage of increasing implied volatility.
This indicator helps traders quickly assess changes in implied volatility, enabling them to make informed decisions based on their trading strategies and market expectations.
🔹 Vertical Pricing Skew
At TanukiTrade, Vertical Pricing Skew refers to the difference in pricing between put and call options with the same expiration date at the same distance (at expected move). We analyze this skew to understand market sentiment. This is the same formula used by TastyTrade for calculations.
We calculate the interpolated strike price based on the expected move , taking into account the neighboring option prices and their distances. This allows us to accurately determine whether the CALL or PUT options are more expensive.
PUT Skew (red): Put options are more expensive than call options, indicating the market expects a downward move (▽). If put options are more expensive by more than 20% at the same expected move distance, we color it lighter red.
CALL Skew (green): Call options are more expensive than put options, indicating the market expects an upward move (△). If call options are priced more than 30% higher at the examined expiration, we color it lighter green.
Vertical Skew on Curve:
The degree of vertical pricing skew for each expiration can be viewed by hovering over the points above the curve. Hover with mouse for more information.
Vertical Skew on IVR panel:
We focus on options with 35-70 days to expiration (DTE) for optimal analysis in case of vertical skew. Hover with mouse for more information.
This approach helps us gauge market expectations accurately, providing insights into potential price movements. Remember, we always evaluate the skew at the expected move using linear interpolation to determine the theoretical pricing of options.
🔹 Delta Skew 🌪️ (Twist)
We have a new metric that examines which monthly expiration indicates a "Delta Skew Twist" where the 16 delta deviates from the monthly STD. This is important because, under normal circumstances, the 16 delta is positioned between the expected move and the standard deviation (STD1) line (see Exp.mv & 1STD exact definitions above). However, if the interpolated 16 delta line exceeds the STD1 line either upwards or downwards, it represents a special case of vertical skew on the option chain.
Normal case : exp.move < delta16 < std1
Delta Skew Twist: exp.move < std1 < delta16
We indicate this with direction-specific colors (red/green) on the delta line. We also color the section of the delta curve affected by the delta skew in this case, even if you choose to display a lower delta, such as 30, instead of 16.
If "Colored Labels with Tooltips" is enabled, we also display a 🌪️ symbol in the tooltip for the expirations affected by Delta Skew.
If you have enabled the display of 'Vertical Pricing Skew' on the IVR Panel, a 🌪️ symbol will also appear next to the value of the vertical skew, and the tooltip will indicate from which expiration Delta Skew is observed.
🔹 Horizontal IVx Skew
In options pricing, it is typically expected that the implied volatility (IVx) increases for options with later expiration dates. This means that options further out in time are generally more expensive. At TanukiTrade, we refer to the phenomenon where this expectation is reversed—when the IVx decreases between two consecutive expirations—as Horizontal Skew or IVx Skew.
Horizontal IVx Skew occurs when: Front Expiry IVx < Back Expiry IVx
This scenario can create opportunities for traders who prefer diagonal or calendar strategies . Based on our experience, we categorize Horizontal Skew into two types:
Weekly Horizontal Skew:
When IVx skew is observed between two consecutive non-monthly expirations, the displayed value is the rounded-up percentage difference. On hover, the approximate location of this skew is also displayed. The precise location can be seen on this indicator.
Monthly Horizontal Skew:
When IVx skew is observed between two consecutive monthly expirations , the displayed value is the rounded-up percentage difference. On hover, the approximate location of this skew is also displayed. The precise location can be seen on our Overlay indicator.
The Monthly Vertical IVx skew is consistently more liquid than the weekly vertical IVx skew. Weekly Horizontal IVx Skew may not carry relevant information for symbols not included in the 'Weeklies & Volume Masters' preset in our Options Screener indicator.
If the options chain follows the normal IVx pattern, no skew value is displayed.
Color codes or tooltip labels above curve:
Gray - No horizontal skew;
Purple - Weekly horizontal skew;
BigBlue - Monthly horizontal skew
The display of monthly and weekly IVx skew can be toggled on or off on the IVR panel. However, if you want to disable the colored tooltips above the curve, this can only be done using the "Colored labels with tooltips" switch.
We indicate this range with colorful information bubbles above the upper STD line.
🔶 The Option Trader’s GRID System: Adaptive MurreyMath + Expiry Lines
At TanukiTrade, we utilize Enhanced MurreyMath and Expiry lines to create a dynamic grid system, unlike the basic built-in vertical grids in TradingView, which provide no insight into specific price levels or option expirations.
These grids are beneficial because they provide a structured layout, making important price levels visible on the chart. The grid automatically resizes as the underlying asset's volatility changes, helping traders identify expected movements for various option expirations.
The Option Trader’s GRID System part of this indicator can be used without limitations for all instruments . There are no type or other restrictions, and it automatically scales to fit every asset. Even if we haven't implemented the option metrics for a particular underlying asset, the GRID system will still function!
🔹 SETUP OF YOUR OPTIONS GRID SYSTEM
You can setup your new grid system in 3 easy steps!
STEP1: Hide default horizontal grid lines in TradingView
Right-click on an empty area of your chart, then select “Settings.” In the Chart settings -> Canvas -> Grid lines section, disable the display of horizontal lines to avoid distraction.
SETUP STEP2: Scaling fix
Right-click on the price scale on the right side, then select "Scale price chart only" to prevent the chart from scaling to the new horizontal lines!
STEP3: Enable Tanuki Options Grid
As a final step, make sure that both the vertical (MurreyMath) and horizontal (Expiry) lines are enabled in the Grid section of our indicator.
You are done, enjoy the new grid system!
🔹 HORIZONTAL: Enhanced MurreyMath Lines
Murrey Math lines are based on the principles observed by William Gann, renowned for his market symmetry forecasts. Gann's techniques, such as Gann Angles, have been adapted by Murrey to make them more accessible to ordinary investors. According to Murrey, markets often correct at specific price levels, and breakouts or returns to these levels can signal good entry points for trades.
At TanukiTrade, we enhance these price levels based on our experience , ensuring a clear display. We acknowledge that while MurreyMath lines aren't infallible predictions, they are useful for identifying likely price movements over a given period (e.g., one month) if the market trend aligns.
Our opinion: MurreyMath lines are not crystal balls (like no other tool). They should be used to identify that if we are trading in the right direction, the price is likely to reach the next unit step within a unit time (e.g. monthly expiration).
One unit step is the distance between Murrey Math lines, such as between the 0/8 and 1/8 lines. This interval helps identify different quadrants and is crucial for recognizing support and resistance levels.
Some option traders use Murrey Math lines to gauge the movement speed of an instrument over a unit time. A quadrant encompasses 4 unit steps.
Key levels, according to TanukiTrade, include:
Of course, the lines can be toggled on or off, and their default color can also be changed.
🔹 VERTICAL: Expiry Lines
The indicator can display monthly and weekly expirations as dashed lines, with customizable colors. Weekly expirations will always appear in a lighter shade compared to monthly expirations.
Monthly Expiry Lines:
You can turn off the lines indicating monthly expirations, or set the direction (past/future/both) and the number of lines to be drawn.
Weekly Expiry Lines:
You can display weekly expirations pointing to the future. You can also turn them off or specify how many weeks ahead the lines should be drawn.
Of course, the lines can be toggled on or off, and their default color can also be changed.
TIP: Hide default vertical grid lines in TradingView
Right-click on an empty area of your chart, then select “Settings.” In the Chart settings -> Canvas -> Grid lines section, disable the display of vertical lines to avoid distraction. Same, like steps above at MurreyMath lines.
🔶 ADDITIONAL IMPORTANT COMMENTS
- U.S. market only:
Since we only deal with liquid option chains: this option indicator only works for the USA options market and do not include future contracts; we have implemented each selected symbol individually.
- Why is there a slight difference between the displayed data and my live brokerage data? There are two reasons for this, and one is beyond our control.
- Brokerage Calculation Differences:
Every brokerage has slight differences in how they calculate metrics like IV and IVx. If you open three windows for TOS, TastyTrade, and IBKR side by side, you will notice that the values are minimally different. We had to choose a standard, so we use the formulas and mathematical models described by TastyTrade when analyzing the options chain and drawing conclusions.
- Option-data update frequency:
According to TradingView's regulations and guidelines, we can update external data a maximum of 5 times per day. We strive to use these updates in the most optimal way:
(1st update) 15 minutes after U.S. market open
(2nd, 3rd, 4th updates) 1.5–3 hours during U.S. market open hours
(5th update) 10 minutes before market close.
You don’t need to refresh your window, our last refreshed data-pack is always automatically applied to your indicator , and you can see the time elapsed since the last update at the bottom of your indicator.
- Skewed Curves:
The delta, expected move, and standard deviation curves also appear relevantly on a daily or intraday timeframe. Data loss is experienced above a daily timeframe: this is a TradingView limitation.
- Weekly illiquid expiries:
Especially for instruments where weekly options are illiquid: the weekly expiration STD1 data is not relevant. In these cases, we recommend checking in the "Display only Monthly labels" checkbox to avoid displaying not relevant weekly options expirations.
-Timeframe Issues:
Our option indicator visualizes relevant data on a daily resolution. If you see strange or incorrect data (e.g., when the options data was last updated), always switch to a daily (1D) timeframe. If you still see strange data, please contact us.
Disclaimer:
Our option indicator uses approximately 15min-3 hour delayed option market snapshot data to calculate the main option metrics. Exact realtime option contract prices are never displayed; only derived metrics and interpolated delta are shown to ensure accurate and consistent visualization. Due to the above, this indicator can only be used for decision support; exclusive decisions cannot be made based on this indicator . We reserve the right to make errors.This indicator is designed for options traders who understand what they are doing. It assumes that they are familiar with options and can make well-informed, independent decisions. We work with public data and are not a data provider; therefore, we do not bear any financial or other liability.
Stochastic Z-Score Oscillator Strategy [TradeDots]The "Stochastic Z-Score Oscillator Strategy" represents an enhanced approach to the original "Buy Sell Strategy With Z-Score" trading strategy. Our upgraded Stochastic model incorporates an additional Stochastic Oscillator layer on top of the Z-Score statistical metrics, which bolsters the affirmation of potential price reversals.
We also revised our exit strategy to when the Z-Score revert to a level of zero. This amendment gives a much smaller drawdown, resulting in a better win-rate compared to the original version.
HOW DOES IT WORK
The strategy operates by calculating the Z-Score of the closing price for each candlestick. This allows us to evaluate how significantly the current price deviates from its typical volatility level.
The strategy first takes the scope of a rolling window, adjusted to the user's preference. This window is used to compute both the standard deviation and mean value. With these values, the strategic model finalizes the Z-Score. This determination is accomplished by subtracting the mean from the closing price and dividing the resulting value by the standard deviation.
Following this, the Stochastic Oscillator is utilized to affirm the Z-Score overbought and oversold indicators. This indicator operates within a 0 to 100 range, so a base adjustment to match the Z-Score scale is required. Post Stochastic Oscillator calculation, we recalibrate the figure to lie within the -4 to 4 range.
Finally, we compute the average of both the Stochastic Oscillator and Z-Score, signaling overpriced or underpriced conditions when the set threshold of positive or negative is breached.
APPLICATION
Firstly, it is better to identify a stable trading pair for this technique, such as two stocks with considerable correlation. This is to ensure conformance with the statistical model's assumption of a normal Gaussian distribution model. The ideal performance is theoretically situated within a sideways market devoid of skewness.
Following pair selection, the user should refine the span of the rolling window. A broader window smoothens the mean, more accurately capturing long-term market trends, while potentially enhancing volatility. This refinement results in fewer, yet precise trading signals.
Finally, the user must settle on an optimal Z-Score threshold, which essentially dictates the timing for buy/sell actions when the Z-Score exceeds with thresholds. A positive threshold signifies the price veering away from its mean, triggering a sell signal. Conversely, a negative threshold denotes the price falling below its mean, illustrating an underpriced condition that prompts a buy signal.
Within a normal distribution, a Z-Score of 1 records about 68% of occurrences centered at the mean, while a Z-Score of 2 captures approximately 95% of occurrences.
The 'cool down period' is essentially the number of bars that await before the next signal generation. This feature is employed to dodge the occurrence of multiple signals in a short period.
DEFAULT SETUP
The following is the default setup on EURAUD 1h timeframe
Rolling Window: 80
Z-Score Threshold: 2.8
Signal Cool Down Period: 5
Stochastic Length: 14
Stochastic Smooth Period: 7
Commission: 0.01%
Initial Capital: $10,000
Equity per Trade: 40%
FURTHER IMPLICATION
The Stochastic Oscillator imparts minimal impact on the current strategy. As such, it may be beneficial to adjust the weightings between the Z-Score and Stochastic Oscillator values or the scale of Stochastic Oscillator to test different performance outcomes.
Alternative momentum indicators such as Keltner Channels or RSI could also serve as robust confirmations of overbought and oversold signals when used for verification.
RISK DISCLAIMER
Trading entails substantial risk, and most day traders incur losses. All content, tools, scripts, articles, and education provided by TradeDots serve purely informational and educational purposes. Past performances are not definitive predictors of future results.
Price Prediction With Rolling Volatility [TradeDots]The "Price Prediction With Rolling Volatility" is a trading indicator that estimates future price ranges based on the volatility of price movements within a user-defined rolling window.
HOW DOES IT WORK
This indicator utilizes 3 types of user-provided data to conduct its calculations: the length of the rolling window, the number of bars projecting into the future, and a maximum of three sets of standard deviations.
Firstly, the rolling window. The algorithm amasses close prices from the number of bars determined by the value in the rolling window, aggregating them into an array. It then calculates their standard deviations in order to forecast the prospective minimum and maximum price values.
Subsequently, a loop is initiated running into the number of bars into the future, as dictated by the second parameter, to calculate the maximum price change in both the positive and negative direction.
The third parameter introduces a series of standard deviation values into the forecasting model, enabling users to dictate the volatility or confidence level of the results. A larger standard deviation correlates with a wider predicted range, thereby enhancing the probability factor.
APPLICATION
The purpose of the indicator is to provide traders with an understanding of the potential future movement of the price, demarcating maximum and minimum expected outcomes. For instance, if an asset demonstrates a substantial spike beyond the forecasted range, there's a significantly high probability of that price being rejected and reversed.
However, this indicator should not be the sole basis for your trading decisions. The range merely reflects the volatility within the rolling window and may overlook significant historical price movements. As with any trading strategies, synergize this with other indicators for a more comprehensive and reliable analysis.
Note: In instances where the number of predicted bars is exceedingly high, the lines may become scattered, presumably due to inherent limitations on the TradingView platform. Consequently, when applying three SD in your indicator, it is advised to limit the predicted bars to fewer than 80.
RISK DISCLAIMER
Trading entails substantial risk, and most day traders incur losses. All content, tools, scripts, articles, and education provided by TradeDots serve purely informational and educational purposes. Past performances are not definitive predictors of future results.
Bandwidth Volatility - Silverman Rule of thumb EstimatorOverview
This indicator calculates volatility using the Rule of Thumb bandwidth estimator and incorporating the standard deviations of returns to get historical volatility. There are two options: one for the original rule of thumb bandwidth estimator, and another for the modified rule of thumb estimator. This indicator comes with the bandwidth , which is shown with the color gradient columns, which are colored by a percentile of the bandwidth, and the moving average of the bandwidth, which is the dark shaded area.
The rule of thumb bandwidth estimator is a simple and quick method for estimating the bandwidth parameter in kernel density estimation (KSE) or kernel regression. It provides a rough approximation of the bandwidth without requiring extensive computation resources or fine-tuning. One common rule of thumb estimator is Silverman rule, which is given by
h = 1.06*σ*n^(-1/5)
where
h is the bandwidth
σ is the standard deviation of the data
n is the number of data points
This rule of thumb is based on assuming a Gaussian kernel and aims to strike a balance between over-smoothing and under-smoothing the data. It is simple to implement and usually provides reasonable bandwidth estimates for a wide range of datasets. However , it is important to note that this rule of thumb may not always have optimal results, especially for non-Gaussian or multimodal distributions. In such cases, a modified bandwidth selection, such as cross-validation or even applying a log transformation (if the data is right-skewed), may be preferable.
How it works:
This indicator computes the bandwidth volatility using returns, which are used in the standard deviation calculation. It then estimates the bandwidth based on either the Silverman rule of thumb or a modified version considering the interquartile range. The percentile ranks of the bandwidth estimate are then used to visualize the volatility levels, identify high and low volatility periods, and show them with colors.
Modified Rule of thumb Bandwidth:
The modified rule of thumb bandwidth formula combines elements of standard deviations and interquartile ranges, scaled by a multiplier of 0.9 and inversely with a number of periods. This modification aims to provide a more robust and adaptable bandwidth estimation method, particularly suitable for financial time series data with potentially skewed or heavy-tailed data.
Formula for Modified Rule of Thumb Bandwidth:
h = 0.9 * min(σ, (IQR/1.34))*n^(-1/5)
This modification introduces the use of the IQR divided by 1.34 as an alternative to the standard deviation. It aims to improve the estimation, mainly when the underlying distribution deviates from a perfect Gaussian distribution.
Analysis
Rule of thumb Bandwidth: Provides a broader perspective on volatility trends, smoothing out short-term fluctuations and focusing more on the overall shape of the density function.
Historical Volatility: Offers a more granular view of volatility, capturing day-to-day or intra-period fluctuations in asset prices and returns.
Modelling Requirements
Rule of thumb Bandwidth: Provides a broader perspective on volatility trends, smoothing out short-term fluctuations and focusing more on the overall shape of the density function.
Historical Volatility: Offers a more granular view of volatility, capturing day-to-day or intra-period fluctuations in asset prices and returns.
Pros of Bandwidth as a volatility measure
Robust to Data Distribution: Bandwidth volatility, especially when estimated using robust methods like Silverman's rule of thumb or its modifications, can be less sensitive to outliers and non-normal distributions compared to some other measures of volatility
Flexibility: It can be applied to a wide range of data types and can adapt to different underlying data distributions, making it versatile for various analytical tasks.
How can traders use this indicator?
In finance, volatility is thought to be a mean-reverting process. So when volatility is at an extreme low, it is expected that a volatility expansion happens, which comes with bigger movements in price, and when volatility is at an extreme high, it is expected for volatility to eventually decrease, leading to smaller price moves, and many traders view this as an area to take profit in.
In the context of this indicator, low volatility is thought of as having the green color, which indicates a low percentile value, and also being below the moving average. High volatility is thought of as having the yellow color and possibly being above the moving average, showing that you can eventually expect volatility to decrease.
Bandwidth Bands - Silverman's rule of thumbWhat are Bandwidth Bands?
This indicator uses Silverman Rule of Thumb Bandwidth to estimate the width of bands around the rolling moving average which takes in the log transformation of price to remove most of price skewness for the rest of the volatility calculations and then a exp() function is performed to convert it back to a right skewed distribution. These bandwidths bands could offer insights into price volatility and trading extremes.
Silverman rule of thumb bandwidth:
The Silverman Rule of Thumb Bandwidth is a heuristic method used to estimate the optimal bandwidth for kernel density estimation, a statistical technique for estimating the probability density function of a random variable. In the context of financial analysis, such as in this indicator, it helps determine the width of bands around a moving average, providing insights into the level of volatility in the market. This method is particularly useful because it offers a quick and straightforward way to estimate bandwidth without requiring extensive computational resources or complex mathematical calculation
The bandwidth estimator automatically adjust to the characteristics of the data, providing a flexible and dynamic measure of dispersion that can capture variations in volatility over time. Standard deviations alone may not be as adaptive to changes in data distributions. The Bandwidth considers the overall shape and structure of the data distribution rather than just focusing on the spread of data points.
Settings
Source
Sample length
1-4 SD options to disable or enable each band
Linear Regression MTF + Bands
Multiple Time Frames (MTFs): The indicator allows you to view linear regression trends over three different time frames (TF1, TF2, TF3) simultaneously. This means a trader can observe short, medium, and long-term trends on a single chart, which is valuable for understanding overall market direction and making cross-timeframe comparisons.
Linear Regression Bands: For each time frame, the indicator calculates linear regression bands. These bands represent the expected price range based on past prices. The middle line is the linear regression line, and the upper and lower lines are set at a specified deviation from this line. Traders can use these bands to spot potential overbought or oversold conditions, or to anticipate future price movements.
History Bands: Looking at linear regression channels can be deceiving if the user does not understand the calculation. In order to see where the channel was at in history the user can display the history bands to see where price actual was in a non-repainting fashion.
Customization Options: Traders can customize various aspects of the indicator, such as whether to display each time frame, the length of the linear regression (how many past data points it considers), and the deviation for the bands. This flexibility allows traders to adapt the indicator to their specific trading style and the asset they are analyzing.
Alerts: The script includes functionality to set alerts based on the price crossing the upper or lower bands of any time frame. This feature helps traders to be notified of potential trading opportunities or risks without constantly monitoring the chart.
Examples
The 15minute linear regression is overlayed onto a 5 minute chart. We are able to see higher timeframe average and extremes. The average is the middle of the channel and the extremes are the outer edges of the bands. The bands are non-repainting meaning that is the actual value of the channel at that place in time.
Here multiple channels are shown at once. We have a linear regression for the 5, 15, and 60 minute charts. If your strategy uses those timeframes you can see the average and overbought/oversold areas without having to flip through charts.
In this example we show just the history bands. The bands could be thought of as a "don't diddle in the middle" area if your strategy is looking for reversals
You can extend the channel into the future via the various input settings.
Z-Score - AsymmetrikZ-Score-Asymmetrik User Manual
Introduction
The Z-Score Indicator is a powerful tool used in technical analysis to measure how far a data point is from the mean value of a dataset, measured in terms of standard deviations. This indicator helps traders identify potential overbought or oversold conditions in the market.
This user manual provides a comprehensive guide on how to use the Z-Score Indicator in TradingView.
0. Quickstart
- Set the thresholds based on your asset (number of standard deviations that you consider being extreme for this asset / timeframe).
- Red background indicates a possible overbought situation, green background an oversold one.
- The color and direction of the Z-Score Line acts as a confirmation of the trend reversal.
1. Indicator Overview
The Z-Score Indicator, also known as the Z-Score Oscillator, is designed to display the Z-Score of a selected financial instrument on your TradingView chart. The Z-Score measures how many standard deviations an asset's price is from its mean (average) price over a specified period.
The indicator consists of the following components:
- Z-Score Line: This line represents the Z-Score value and is displayed on the indicator panel.
- Background Color: The background color of the indicator panel changes based on user-defined thresholds.
2. Inputs
The indicator provides several customizable inputs to tailor it to your specific trading preferences:
- Number of Periods: This input allows you to define the number of periods over which the Z-Score will be calculated. A longer period will provide a smoother Z-Score line but may be less responsive to recent price changes.
- Z-Score Low Threshold: Sets the lower threshold value for the Z-Score. When the Z-Score crosses below this threshold, the background color of the indicator panel changes accordingly.
- Z-Score High Threshold: Sets the upper threshold value for the Z-Score. When the Z-Score crosses above this threshold, the background color of the indicator panel changes accordingly.
3. How to Use the Indicator
Here are the steps to use the Z-Score Indicator:
- Adjust Parameters: Modify the indicator's inputs as needed. You can change the number of periods for the Z-Score calculation and set your desired low and high thresholds.
- Interpret the Indicator: Observe the Z-Score line on the indicator panel. It fluctuates above and below zero. Pay attention to the background color changes when the Z-Score crosses your specified thresholds.
4. Interpreting the Indicator
- Z-Score Line: The Z-Score line represents the current Z-Score value. When it is above zero, it suggests that the asset's price is above the mean, indicating potential overvaluation. When below zero, it suggests undervaluation.
- Background Color: The background color of the indicator panel changes based on the Z-Score's position relative to the specified thresholds. Green indicates the Z-Score is below the low threshold (potential undervaluation), while red indicates it is above the high threshold (potential overvaluation).
- Z-Score Line Color: The color of the Z-Score line shows that the Z-Score is trending up compared to its moving average. This can be used as a validation of the background color.
5. Customization Options
You can customize the Z-Score Indicator in the following ways:
- Adjust Inputs: Modify the number of periods and the Z-Score thresholds.
- Change Line and Background Colors: You can customize the colors of the Z-Score line and background by editing the indicator's script.
6. Troubleshooting
If you encounter any issues while using the Z-Score Indicator, make sure to check the following:
- Ensure that the indicator is applied correctly to your chart.
- Verify that the indicator's inputs match your intended settings.
- Contact me for more support if needed
7. Conclusion
The Z-Score Indicator is a valuable tool for traders and investors to identify potential overbought and oversold conditions in the market. By understanding how the Z-Score works and customizing it to your preferences, you can integrate it into your trading strategy to make informed decisions.
Remember that trading involves risk, and it's essential to combine technical indicators like the Z-Score with other analysis methods and risk management strategies for successful trading.
Signal to Noise TrendSignal to Noise Ratio
The Signal to Noise Ratio or SNR is used to assess the quality of information or data by comparing the strength of a useful signal to the presence of background noise or random variations.
In Finance the SNR refers to the ratio of strength of a trading signal to the background noise. A high SNR suggest a clear and reliable signal, meanwhile a low SNR indicates more noise (random fluctuations, volatility, or randomness).
Signal To Noise Trend
This indicator basically calculates the signal to noise of returns and then gets the Z-Score of the signal to noise ratio to find extremes levels of signal and noise. The Lines basically are standard deviations from the mean. 1,2,3 Are standard deviations same with the -1,-2,-3 Lines.
The signal is expressed as the positive Z-Score value, and the Noise is the negative Z-Score Value.
The moving average enhances the indicator ability to display the trend of returns and the trend strength. It provides a smooth representation of the Signal to Nose Ratio values.
There are more trending conditions when there is a higher signal, and there is more "ranging" conditions when there is more noise present in the markets.
The Standard deviations help find extreme levels of signal and noise. If the noise reaches the standard deviation of -3 then that means that there is a extreme negative deviation from the mean, and this would be a rare occurrence, with a lot of noise. This could indicate a potential reversion in market states, and could be followed by a trending move.
Another example is that if the Z-Score value reaches a Standard deviation of 3, this could mean that there is extremely strong and rare signal, and could potentially mean a change to a more noisy environment soon.
dharmatech : Standard Deviation ChannelDESCRIPTION
Based on version by leojez.
Adds a 3rd standard deviation level.
Twice as fast as original version.
Refactored and simplified source code.
HOW TO USE
Load your chart
Adjust the timeframe and zoom of the chart so that the trend you're interested in is in view.
Add the indicator
Use the measuring tool to measure the number of bars from the start of the trend to the latest candle.
Open settings for the indicator.
Set the length value to the number of bars that you noted.
Complete Discrete Fourier Transform ToolkitThis is an expansion from my Discrete Fourier Transform Overlay indicator which offers various features that may be useful for traders wishing to apply frequency analysis or integral transform to their trading. For those unfamiliar with the concept, the discrete Fourier transform decomposes wave or wave-like data into functions depending on frequency. This can be helpful in demonstrating or interpreting trends and periodic frequencies in time-series price data, or oscillating indicators.
This toolkit has the following features:
Fourier bands (deviation cloud): The deviation cloud expresses the uncertainty in the DFT algorithm, as well as the relative change in frequency of the curve.
Fourier supertrend: The supertrend is applied as a product of the DFT algorithm, instead of onto the price data itself. This filters the supertrend from infrequent periodicities. For trading, this means that the supertrend will not be affected by false breakouts or breakdowns. See the image below for an example:
Future updates may include:
Projection of the probabilistic uncertainty principle. In a nutshell, the concept can be used to project uncertainties forwards through price data to forecast the path of least resistance, or, the most probable frequency.
Machine learning capabilities. Justin Doherty has done the Pine Script community a great service in introducing kNN algorithms with Lorentzian distance calculations; however, this is only the start of relativistic mechanics that can be applied to time series data. The DFT algorithm essentially filters data into its periodicities; this data can be inserted into a relativistic kNN algorithm - Lorenz or otherwise - to possibly improve accuracy.
Weekly Range Support & Resistance Levels [QuantVue]Weekly Range Support & Resistance Levels
Description:
The Weekly Range Support & Resistance Levels analyzes weekly ranges and takes the average range of the last 30 weeks (default setting).
It also takes the average +/- a standard deviation, and creates support & resistance levels/zones based on the weekly opening price.
The levels will update each week, and previous weekly levels can be toggled on or off.
Settings:
🔹Averaging Period
🔹Standard Deviation Multiplier
🔹Toggle Support & Resistance Prices
🔹Show Weekly Open Line
🔹Show Previous Levels
Don't hesitate to reach out with any questions or concerns. We hope you enjoy!
Cheers.
Inter-Exchanges Crypto Price Spread Deviation (Tartigradia)Measures the deviation of price metrics between various exchanges. It's a kind of realized volatility indicator, as the idea is that in times of high volatility (high emotions, fear, uncertainty), it's more likely that market inefficiencies will appear for the same asset between different market makers, ie, the price can temporarily differ a lot. This indicator will catch these instants of high differences between exchanges, even if they lasted only an instant (because we use high and low values).
Both standard deviation and median absolute deviation (more robust to outliers, ie, exchanges with a very different price from others won't influence the median absolute deviation, but the standard deviation yes).
Compared to other inter-exchanges spread indicators, this one offers two major features:
* The symbol automatically adapts to the symbol currently selected in user's chart. Hence, switching between tickers does not require the user to modify any option, everything is dynamically updated behind the scenes.
* It's easy to add more exchanges (requires some code editing because PineScript v5 does not allow dynamical request.security() calls).
Limitations/things to know:
* History is limited to what the ticker itself display. Ie, even if the exchanges specified in this indicator have more data than the ticker currently displayed in the user's chart, the indicator will show only a timeperiod as long as the chart.
* The indicator can manage multiple exchanges of different historical length (ie, some exchanges having more data going way earlier in the past than others), in which case they will simply be ignored from calculations when far back in the past. Hence, you should be aware that the further you go in the past, the less exchanges will have such data, and hence the less accurate the measures will be (because the deviation will be calculated from less sources than more recent bars). This is thanks to how the array.* math functions behave in case of na values, they simply skip them from calculations, contrary to math.* functions.
TheATR™: Volatility Extremes (VolEx)Volatility is a crucial aspect of financial markets that is closely monitored by traders and investors alike. The traditional Average True Range (ATR) oscillator is a widely used technical indicator for measuring volatility in financial markets. However, there are limitations to the ATR oscillator, as it does not account for changing market conditions and may not adequately reflect extreme price movements. To address these limitations, TheATR has developed the VolEx indicator, which aims to identify extremes in the ATR oscillator by building dynamic thresholds using either a 'percentage' or 'standard deviation' based comparison with the value of the ATR.
The VolEx indicator utilizes a dynamic approach to measure volatility by considering the current level of the ATR oscillator relative to the dynamically generated thresholds. The dynamic thresholds are calculated based on the current ATR value and the chosen method of comparison (either 'percentage' or 'standard deviation'). If the ATR value exceeds the upper dynamic threshold, the market is experiencing high volatility, while a value below the lower dynamic threshold indicates low volatility.
The VolEx indicator offers several advantages over traditional volatility indicators, such as the ATR oscillator. First, it takes into account the changing market conditions and adjusts the thresholds accordingly. Second, it offers flexibility in the choice of the comparison method, allowing traders to tailor the indicator to their specific trading strategies. Finally, it provides clear signals for identifying extremes in volatility, which can be used to inform trading decisions.
In summary, the VolEx indicator developed by TheATR is a dynamic and flexible technical indicator that offers a robust approach to measuring volatility in financial markets. By utilizing dynamic thresholds and allowing for different comparison methods, the VolEx indicator provides a valuable tool for traders and investors seeking to identify extremes in market volatility..
NOTE: It is important to note that volatility, as measured by the VolEx indicator, does not provide any directional bias for the market movement. Rather, it simply indicates the degree to which the market is moving, regardless of direction. Traders and investors must use other technical or fundamental analysis tools to determine the direction of the market and make informed trading decisions based on their individual strategies and risk tolerance.
SFC Smart Money - VolatilityIn statistics, a normal distribution is a type of continuous probability distribution for a real-valued random variable. Normal distributions are important in statistics and are often used in the natural and social sciences to represent real-valued random variables whose distributions are not known.
The indicator provide a deep statistic for the specified period. It calculate the normal distribution of all candles in the particular period, in order to measure the volatility and the probabilities. Also it separate bull from bear candles and calculate the normal distribution of each group. The calculations are mode based on open-open data and high-low data.
Volatility
Volatility is a statistical measure of the dispersion of returns for a given security or market index. In most cases, the higher the volatility , the riskier the security. Volatility is often measured from either the standard deviation or variance between returns from that same security or market index.
Volatility often refers to the amount of uncertainty or risk related to the size of changes in a security's value. A higher volatility means that a security's value can potentially be spread out over a larger range of values. This means that the price of the security can change dramatically over a short time period in either direction. A lower volatility means that a security's value does not fluctuate dramatically, and tends to be more steady.
While variance captures the dispersion of returns around the mean of an asset in general, volatility is a measure of that variance bounded by a specific period of time. Thus, we can report daily volatility , weekly, monthly, or annualized volatility .
This statistic gives very accurate information how the price moved in the past and what are normal movements and spikes. From this information, a future actions can be taken.
For better understanding, all data is calculated in pips.
Features:
- Mean - Mean is the one we are most used to, i.e. the average.
- Median -Sometimes, the data set values can have a few values which are at the extreme ends, and this might cause the mean of the data set to portray an incorrect picture.
Thus, we use the median, which gives the middle value of the sorted data set.
- Mode - In a given dataset, the mode will be the number which is occurring the most.
- Max - Maximum volatility for a given range.
- Min - Minimum volatility for a given range.
- Standard Deviation - The standard deviation tells us how far the value deviates from the mean.
- Range - Range simply gives the difference between the min and max values of the data set.
- ATR - Average True Range measures volatility, taking into account any gaps in the price movement.
- Normal Distribution - The basic premise is that given a range of observations, it is found that most of the values center around the mean and within one standard deviation
away from the mean.
- Probability - probability of outcomes.
We all know that the banks and professional traders do not trade with charts, but with different statistical methods, math. models and macroeconomics. This statistical indicator shows one of these methods.
It is recommended to use the indicator on daily timeframe . It also works on other timeframes, for example 1H for intraday analysis.
For more information how the normal distribution works, please search in internet.
MeanReversion by VolatilityMean reversion is a financial term for the assumption that an asset will return to its mean value.
This indicator calculate the volatility of an asset over a period of time and show the values of logRerturn, mean and standart deviations.
The default time period for volatility calculation is 252 bars at a "Daily" chart. At a "Daily" chart 252 bar means one trading-year.
See also:
MeanReversion by Logarithmic Returns
Slope NormalizerBrief:
This oscillator style indicator takes another indicator as its source and measures the change over time (the slope). It then isolates the positive slope values from the negative slope values to determine a 'normal' slope value for each.
** A 'normal' value of 1.0 is determined by the average slope plus the standard deviation of that slope.
The Scale
This indicator is not perfectly linear. The values are interpolated differently from 0.0 - 1.0 than values greater than 1.0.
From values 0.0 to 1.0 (positive or negative): it means that the value of the slope is less than 'normal' **.
Any value above 1.0 means the current slope is greater than 'normal' **.
A value of 2.0 means the value is the average plus 2x the standard deviation.
A value of 3.0 means the value is the average plus 3x the standard deviation.
A value greater than 4.0 means the value is greater than the average plus 4x the standard deviation.
Because the slope value is normalized, the meaning of these values can remain generally the same for different symbols.
Potential Usage Examples/b]
Using this in conjunction with an SMA or WMA may indicate a change in trend, or a change in trend-strength.
Any values greater than 4 indicate a very strong (and unusual) trend that may not likely be sustainable.
Any values cycling between +1.0 and -1.0 may mean indecision.
A value that is decreasing below 0.5 may predict a change in trend (slope may soon invert).
StDev BandsThis is a "bands"-type indicator. It was developed out of my Sharpe Ratio indicator . It uses the standard deviation of returns as basis for drawing the bands. I'm going to update this indicator as the other indicator evolves. Please be sure you know how to calculate Sharpe Ratio and check out the Sharpe Ratio indicator as well. This will help you understand the purpose of this indicator a bit more.
As a very short introduction. Many investors use the standard deviation of returns as risk measurement . I admit the defaults of this indicator aren't perfect. Normally investors use the standard deviation over a 1 year period. Traditional finance uses 265 days, and because crypto never sleeps, we could use 365. I defaulted it to 20.
Strength Volatility Killer - The Quant ScienceStrength Volatility Killer - The Quant Science™ is based on a special version of RSI (Relative Strength Index), created with the simple average and standard deviation.
DESCRIPTION
The algorithm analyses the market and opens positions following three different volatility entry conditions. Each entry has a specific and personal exit condition. The user can setting trailing stop loss from user interface.
USER INTERFACE SETTING
Configures the algorithm from the user interface.
AUTO TRADING COMPLIANT
With the user interface, the trader can easily set up this algorithm for automatic trading.
BACKTESTING INCLUDED
The trader can adjust the backtesting period of the strategy before putting it live. Analyze large periods such as years or months or focus on short-term periods.
NO LIMIT TIMEFRAME
This algorithm can be used on all timeframes.
GENERAL FEATURES
Multi-strategy: the algorithm can apply long strategy or short strategy.
Built-in alerts: the algorithm contains alerts that can be customized from the user interface.
Integrated indicator: indicator is included.
Backtesting included: quickly automatic backtesting of the strategy.
Auto-trading compliant: functions for auto trading are included.
ABOUT BACKTESTING
Backtesting refers to the period 13 June 2022 - today, ticker: AVAX/USDT, timeframe 5 minutes.
Initial capital: $1000.00
Commission per trade: 0.03%
Crypto Portfolio ManagementCrypto Portfolio Management
This is an indicator not like the other ones that you regularly see in tradingview. The main difference is that this indicator does not plot a value for each candle bar like you would see with RSI or MACD. Actually it is table and it just uses tradingview great database of assets to plot some valuebale information that can not be found elsewhere easily. These metrics are some basic one that is used by portfolio managers to decide what they want to hold in their portfolio. The basic idea is that you should hold assets in your basket that are less correlated to the benchmark.
Benchmark in traditional context refers to main market indices like S&P 500 of US market. But they already have a lot of tools available. My effort was for crypto investors who are trying to rebalance their portfolio every month or week to have some good metrics to make decision. Because of this I used Bitcoin as crypto market benchmark. So, everything is compared to bitcoin in this script. I’m gonna explain the terms that is used in the table’s columns below.
MAKE SURE YOU PUT YOUR CHART AT DAILY AND AT THE MAXIMUM AVAILABLE DATA EXCHANGE.
Y-Exp
This is yearly expected return of the asset. It is simply the mean of the yearly returns of the asset. (these calculations are not typical in Tradingview because mainly we calculate on each bar and give value at the same bar but here this value to change once a year). Remember that the higher this value is the better it is because historically the asset have shown good returns but there is a tip: Always check the available historical data in any asset that you are adding if you add an asset that has only 1 year of data available or you use an exchange data that recently added the coin you will get unsignificant results and the results can not be trusted. You should always selects coins and market (coins can be changed in setting) that have the largest data available.
Y-SDev
This is a little bit complicated than the previous. This is the standard deviation of the yearly returns. This is a classic measure of RISK in financial markets. The higher the value, the more risk is involved with the asset that you have added. If you added two assets that have same returns but different Standard deviations, the rational thinker should choose the asset with lower Standard deviation.
The standard deviation is a good place to start but there are some considerations to have -it is getting complicated and average user should not be involved with these terms and can ignore the next phrases- standard deviation and mean of the yearly returns are random variables, these variables have a theoretical probability density function and these functions are not gaussian normal distribution. Because of this in the professional usage these returns should be transformed to a normal distribution and have all these terms calculated there and then transform back to its own normal state and then be used for any serious investment decision. I think these calculations can be done on Tradingview but I need you support to do this in the form of like and share of my scripts and ideas.
M-Exp and M-SDev
These terms are like the previous ones but it is calculated on monthly returns. As it goes for yearly return, the monthly returns change once a monthly candle closes. So be patient to use this indicator.
I highly recommend not to make decisions on monthly data due to a lot of noise involved with this market but in long run it is ok. So go with yearly returns and wait at least for 3 years to see your results.
CorToBTC
Basically you want to buy something that is less correalted with the benchmark. this is the correlation of the asset to bitcoin.
Sharpe Ratio
This is one of the most used metric as a risk adjusted return measurment. you can google it for more information. The higher this value the better. remmeber with any invenstment it is important to understand risks associated with the assets that you are buying.
DownFromATH
This metric that I didn't see anywhere in the tradingview and is familiar in the platforms like coinmarketcap. this is a real calculation of precentage down from ATH (All Time High). it means how much percentage a coin is down from the maximum price that the asset has experienced until now.
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Remember you can change all the asset except main asset. If you like this script to 500 I will update this continuously.
