Options Overlay [Lite] IVR IV Skew Delta Expmv MurreyMath Expiry𝗡𝗼𝗻-𝗼𝗳𝗳𝗶𝗰𝗶𝗮𝗹 𝗧𝗢𝗦 𝗮𝗻𝗱 𝗧𝗮𝘀𝘁𝘆𝗧𝗿𝗮𝗱𝗲 𝗹𝗶𝗸𝗲 𝗜𝗩𝗥 𝗢𝗽𝘁𝗶𝗼𝗻𝘀 𝘃𝗶𝘀𝘂𝗮𝗹𝗶𝘇𝗮𝘁𝗶𝗼𝗻 𝘁𝗼𝗼𝗹 𝘄𝗶𝘁𝗵 𝗱𝗲𝗹𝗮𝘆𝗲𝗱 𝗼𝗽𝘁𝗶𝗼𝗻 𝗰𝗵𝗮𝗶𝗻 𝗱𝗮𝘁𝗮
Are you an options trader who uses TradingView for technical analysis for the US market?
➡️ Do you want to see the IV Rank of an instrument on TradingView?
➡️ Can’t you check the key options metrics while charting?
➡️ Have you never visualized the options chain before?
➡️ Would you like to see how the IVx has changed for a specific ticker?
If you answered "yes" to any of these questions, then we have the solution for you!
🔃 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 5 liquid tickers: NASDAQ:AAPL NASDAQ:AMZN AMEX:DIA NYSE:ORCL and NASDAQ:TSLA
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.
Key Features:
IV Rank (IVR) : The implied volatility rank compares the current IV to the lowest and highest values over the past 52 weeks. The IVR indicator helps determine whether options are relatively cheap or expensive.
IV Average (IVx) : The implied volatility displayed in the options chain, calculated similarly to the VIX. IVx values are aggregated within the 35-70 day expiration cycle.
IV Change (5 days) : The change in implied volatility over the past five trading days. This indicator provides a quick insight into the recent changes in IV.
Expected Move (Exp. Move) : The expected movement for the options expiration cycle, calculated using the price of the ATM (at-the-money) straddle, the first OTM (out-of-the-money) strangle, and the second OTM strangle.
Options Skew : The price difference between put and call options with the same expiration date. Vertical and horizontal skew indicators help understand market sentiment and potential price movements.
Visualization Tools:
Informational IVR Panel : A tabular display mode that presents the selected indicators on the chart. The panel’s placement, size, and content are customizable, including color and tooltip settings.
1 STD, Delta, and Expected Move : Visualization of fundamental classic options metrics corresponding to expirations with bell curves.
Colored Label Tooltips : Detailed tooltips above the bell curves showing options metrics for each expiration.
Adaptive Murrey Math Lines : A horizontal line system based on the principles of Murrey Math Lines, helping identify important price levels and market structures.
Expiration Lines : Displays both monthly and weekly options expirations. The indicator supports various color and style settings, as well as the regulation of the number of expirations displayed.
🟨 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.
Desvio Padrão
HilalimSB Strategy HilalimSB A Wedding Gift 🌙
What is HilalimSB🌙?
First of all, as mentioned in the title, HilalimSB is a wedding gift.
HilalimSB - Revealing the Secrets of the Trend
HilalimSB is a powerful indicator designed to help investors analyze market trends and optimize trading strategies. Designed to uncover the secrets at the heart of the trend, HilalimSB stands out with its unique features and impressive algorithm.
Hilalim Algorithm and Fixed ATR Value:
HilalimSB is equipped with a special algorithm called "Hilalim" to detect market trends. This algorithm can delve into the depths of price movements to determine the direction of the trend and provide users with the ability to predict future price movements. Additionally, HilalimSB uses its own fixed Average True Range (ATR) value. ATR is an indicator that measures price movement volatility and is often used to determine the strength of a trend. The fixed ATR value of HilalimSB has been tested over long periods and its reliability has been proven. This allows users to interpret the signals provided by the indicator more reliably.
ATR Calculation Steps
1.True Range Calculation:
+ The True Range (TR) is the greatest of the following three values:
1. Current high minus current low
2. Current high minus previous close (absolute value)
3. Current low minus previous close (absolute value)
2.Average True Range (ATR) Calculation:
-The initial ATR value is calculated as the average of the TR values over a specified period
(typically 14 periods).
-For subsequent periods, the ATR is calculated using the following formula:
ATRt=(ATRt−1×(n−1)+TRt)/n
Where:
+ ATRt is the ATR for the current period,
+ ATRt−1 is the ATR for the previous period,
+ TRt is the True Range for the current period,
+ n is the number of periods.
Pine Script to Calculate ATR with User-Defined Length and Multiplier
Here is the Pine Script code for calculating the ATR with user-defined X length and Y multiplier:
//@version=5
indicator("Custom ATR", overlay=false)
// User-defined inputs
X = input.int(14, minval=1, title="ATR Period (X)")
Y = input.float(1.0, title="ATR Multiplier (Y)")
// True Range calculation
TR1 = high - low
TR2 = math.abs(high - close )
TR3 = math.abs(low - close )
TR = math.max(TR1, math.max(TR2, TR3))
// ATR calculation
ATR = ta.rma(TR, X)
// Apply multiplier
customATR = ATR * Y
// Plot the ATR value
plot(customATR, title="Custom ATR", color=color.blue, linewidth=2)
This code can be added as a new Pine Script indicator in TradingView, allowing users to calculate and display the ATR on the chart according to their specified parameters.
HilalimSB's Distinction from Other ATR Indicators
HilalimSB emerges with its unique Average True Range (ATR) value, presenting itself to users. Equipped with a proprietary ATR algorithm, this indicator is released in a non-editable form for users. After meticulous testing across various instruments with predetermined period and multiplier values, it is made available for use.
ATR is acknowledged as a critical calculation tool in the financial sector. The ATR calculation process of HilalimSB is conducted as a result of various research efforts and concrete data-based computations. Therefore, the HilalimSB indicator is published with its proprietary ATR values, unavailable for modification.
The ATR period and multiplier values provided by HilalimSB constitute the fundamental logic of a trading strategy. This unique feature aids investors in making informed decisions.
Visual Aesthetics and Clear Charts:
HilalimSB provides a user-friendly interface with clear and impressive graphics. Trend changes are highlighted with vibrant colors and are visually easy to understand. You can choose colors based on eye comfort, allowing you to personalize your trading screen for a more enjoyable experience. While offering a flexible approach tailored to users' needs, HilalimSB also promises an aesthetic and professional experience.
Strong Signals and Buy/Sell Indicators:
After completing test operations, HilalimSB produces data at various time intervals. However, we would like to emphasize to users that based on our studies, it provides the best signals in 1-hour chart data. HilalimSB produces strong signals to identify trend reversals. Buy or sell points are clearly indicated, allowing users to develop and implement trading strategies based on these signals.
For example, let's imagine you wanted to open a position on BTC on 2023.11.02. You are aware that you need to calculate which of the buying or selling transactions would be more profitable. You need support from various indicators to open a position. Based on the analysis and calculations it has made from the data it contains, HilalimSB would have detected that the graph is more suitable for a selling position, and by producing a sell signal at the most ideal selling point at 08:00 on 2023.11.02 (UTC+3 Istanbul), it would have informed you of the direction the graph would follow, allowing you to benefit positively from a 2.56% decline.
Technology and Innovation:
HilalimSB aims to enhance the trading experience using the latest technology. With its innovative approach, it enables users to discover market opportunities and support their decisions. Thus, investors can make more informed and successful trades. Real-Time Data Analysis: HilalimSB analyzes market data in real-time and identifies updated trends instantly. This allows users to make more informed trading decisions by staying informed of the latest market developments. Continuous Update and Improvement: HilalimSB is constantly updated and improved. New features are added and existing ones are enhanced based on user feedback and market changes. Thus, HilalimSB always aims to provide the latest technology and the best user experience.
Social Order and Intrinsic Motivation:
Negative trends such as widespread illegal gambling and uncontrolled risk-taking can have adverse financial effects on society. The primary goal of HilalimSB is to counteract these negative trends by guiding and encouraging users with data-driven analysis and calculable investment systems. This allows investors to trade more consciously and safely.
What is HilalimSB Strategy🌙?
HilalimSB Strategy is a strategy that is supported by the HilalimSB algorithm created by the creator of HilalimSB and continues transactions with take profit and stop loss levels determined by users who strategically and automatically open transactions as a result of the data it receives and automatically closes transactions under necessary conditions. It is a first in the tradingview world with its unique take profit and stop loss markings. HilalimSB Strategy is open to users' initiatives and is a trading strategy developed on BTC.
What does the HilalimSB Strategy target?
The main purpose of HilalimSB Strategy is to reduce the transaction load of traders and to be integrated into various brokerage firms and operated by automatic trading bots, and it is aimed to serve this purpose. In addition to the strategies currently available in the markets, HilalimSB Strategy offers a useful infrastructure to traders with its useful interface. HilalimSB Strategy, which was decided to be published as a result of various calculations, was offered to the users with its unique visual effects after the completion of the testing procedures under market conditions.
HilalimSB Strategy and Heikin Ashi
HilalimSB Strategy produces data in Heikin Ashi chart types, but since Heikin Ashi chart types have their own calculation method, HilalimSB Strategy has been published in a way that cannot produce data in this chart type due to HilalimSB Strategy's ideology of appealing to all types of users, and any confusion that may arise is prevented in this way.
After the necessary conditions determined by the creator of HilalimSB are met, HilalimSB Heikin Ashi will be shared exclusively with invited users only, upon request, to users who request an invitation.
Differences between HilalimSB Strategy and HilalimSB
HilalimSB Strategy has been shared as a strategy and its features have been explained above. HilalimSB is a trading indicator and this is the main difference between them.We can explain it briefly this way.
Here are the differences between indicators and strategies:
1.Purpose and Use:
Indicators: Analyze market data to provide information about price movements and trends. They typically generate buy and sell signals and give traders clues about when to make trades in the market.
Strategies: These are plans for trading based on specific rules. They use signals from indicators and other market data to execute buy and sell transactions.
2.Features:
Indicators: Operate independently and are based on specific mathematical formulas. Examples include moving averages, RSI, and MACD.
Strategies: Combine one or more indicators and other market analysis tools to create a comprehensive trading plan. This plan determines entry and exit points, risk management, and trade size.
3.Scope:
Indicators: Are single analysis tools focusing on specific time frames or price movements.
Strategies: Are comprehensive trading plans that typically involve multiple trades over a certain period.
4.Decision Making:
Indicators: Provide information to traders and help in the decision-making process.
Strategies: Are direct decision-making mechanisms that execute trades automatically according to predetermined rules.
5.Automation:
Indicators: Are mostly interpreted manually and used based on the trader’s discretion.
Strategies: Can be used in automated trading systems and execute trades automatically according to the set rules.
The shared image is a 1-hour chart of BTCUSDC.P determined by the user as 1 percent take profit and 1 percent stop loss. And transactions were opened on Binance with the commission rate determined as 0.017 for the USDC trading pair.
HilalimSB Strategy, which presents users with completely concrete data, has proven itself in testing processes and is a project of SB that aims to reach all user profiles.🌙
Trend Maestro - Linear Regression & Volatility BandsTrend Maestro - Linear Regression & Volatility Bands
Description:
The "Trend Maestro - Linear Regression & Volatility Bands" indicator is meticulously designed to provide traders with a clear understanding of market trends through the application of linear regression techniques and enhanced market data visualization. This tool is essential for traders looking to interpret long-term trends and market stability. Here's how the indicator functions and what makes it a unique addition to your trading toolkit:
1. Linear Regression Calculation:
At the heart of this indicator lies the linear regression calculation, which identifies the primary trend direction over a specified period. It does this by computing a line of best fit through the closing prices, helping to smooth out price fluctuations and highlight the prevailing trend direction. Users have the flexibility to adjust both the length of the regression and the offset period, enabling them to tailor the indicator's responsiveness to different market conditions.
2. Visualization Through Volatility Bands:
The volatility bands, plotted at half, one, two, and three standard deviations around the linear regression line, serve primarily as a visualization tool rather than a basis for investment decisions.
These bands:
Measure the dispersion of price from the trend line, providing a graphical representation of volatility.
Help traders visually assess the market's stability and the reliability of the current trend, with broader bands indicating higher volatility and narrower bands suggesting more stability.
3. Customization Features:
The indicator offers customization options including toggle switches for bar color and the display of SD bands, enhancing visual clarity. These settings allow traders to personalize the display according to their visual preferences and analysis requirements.
By incorporating these elements, the "Trend Maestro - Linear Regression & Volatility Bands" indicator offers a framework for understanding market trends through both quantitative calculations and qualitative visual aids. This makes it a valuable tool for those looking to make informed decisions based on longer-term market observations.
Bollinger Bands StrategyBollinger Bands Strategy :
INTRODUCTION :
This strategy is based on the famous Bollinger Bands. These are constructed using a standard moving average (SMA) and the standard deviation of past prices. The theory goes that 90% of the time, the price is contained between these two bands. If it were to break out, this would mean either a reversal or a continuation. However, when a reversal occurs, the movement is weak, whereas when a continuation occurs, the movement is substantial and profits can be interesting. We're going to use BB to take advantage of this strong upcoming movement, while managing our risks reasonably. There's also a money management method for reinvesting part of the profits or reducing the size of orders in the event of substantial losses.
BOLLINGER BANDS :
The construction of Bollinger bands is straightforward. First, plot the SMA of the price, with a length specified by the user. Then calculate the standard deviation to measure price dispersion in relation to the mean, using this formula :
stdv = (((P1 - avg)^2 + (P2 - avg)^2 + ... + (Pn - avg)^2) / n)^1/2
To plot the two Bollinger bands, we then add a user-defined number of standard deviations to the initial SMA. The default is to add 2. The result is :
Upper_band = SMA + 2*stdv
Lower_band = SMA - 2*stdv
When the price leaves this channel defined by the bands, we obtain buy and sell signals.
PARAMETERS :
BB Length : This is the length of the Bollinger Bands, i.e. the length of the SMA used to plot the bands, and the length of the price series used to calculate the standard deviation. The default is 120.
Standard Deviation Multipler : adds or subtracts this number of times the standard deviation from the initial SMA. Default is 2.
SMA Exit Signal Length : Exit signals for winning and losing trades are triggered by another SMA. This parameter defines the length of this SMA. The default is 110.
Max Risk per trade (in %) : It's the maximum percentage the user can lose in one trade. The default is 6%.
Fixed Ratio : This is the amount of gain or loss at which the order quantity is changed. The default is 400, meaning that for each $400 gain or loss, the order size is increased or decreased by a user-selected amount.
Increasing Order Amount : This is the amount to be added to or subtracted from orders when the fixed ratio is reached. The default is $200, which means that for every $400 gain, $200 is reinvested in the strategy. On the other hand, for every $400 loss, the order size is reduced by $200.
Initial capital : $1000
Fees : Interactive Broker fees apply to this strategy. They are set at 0.18% of the trade value.
Slippage : 3 ticks or $0.03 per trade. Corresponds to the latency time between the moment the signal is received and the moment the order is executed by the broker.
Important : A bot has been used to test the different parameters and determine which ones maximize return while limiting drawdown. This strategy is the most optimal on BITSTAMP:BTCUSD in 8h timeframe with the following parameters :
BB Length = 120
Standard Deviation Multipler = 2
SMA Exit Signal Length = 110
Max Risk per trade (in %) = 6%
ENTER RULES :
The entry rules are simple:
If close > Upper_band it's a LONG signal
If close < Lower_band it's a SHORT signal
EXIT RULES :
If we are LONG and close < SMA_EXIT, position is closed
If we are SHORT and close > SMA_EXIT, the position is closed
Positions close automatically if they lose more than 6% to limit risk
RISK MANAGEMENT :
This strategy is subject to losses. We manage our risk using the exit SMA or using a SL sets to 6%. This SMA gives us exit signals when the price closes below or above, thus limiting losses. If the signal arrives too late, the position is closed after a loss of 6%.
MONEY MANAGEMENT :
The fixed ratio method was used to manage our gains and losses. For each gain of an amount equal to the fixed ratio value, we increase the order size by a value defined by the user in the "Increasing order amount" parameter. Similarly, each time we lose an amount equal to the value of the fixed ratio, we decrease the order size by the same user-defined value. This strategy increases both performance and drawdown.
NOTE :
Please note that the strategy is backtested from 2017-01-01. As the timeframe is 8h, this strategy is a medium/long-term strategy. That's why only 51 trades were closed. Be careful, as the test sample is small and performance may not necessarily reflect what may happen in the future.
Enjoy the strategy and don't forget to take the trade :)
Price Based Z-Trend - Strategy [presentTrading]█ Introduction and How it is Different
Z-score: a statistical measurement of a score's relationship to the mean in a group of scores.
Simple but effective approach.
The "Price Based Z-Trend - Strategy " leverages the Z-score, a statistical measure that gauges the deviation of a price from its moving average, normalized against its standard deviation. This strategy stands out due to its simplicity and effectiveness, particularly in markets where price movements often revert to a mean. Unlike more complex systems that might rely on a multitude of indicators, the Z-Trend strategy focuses on clear, statistically significant price movements, making it ideal for traders who prefer a streamlined, data-driven approach.
BTCUSD 6h LS Performance
█ Strategy, How It Works: Detailed Explanation
🔶 Calculation of the Z-score
"Z-score is a statistical measurement that describes a value's relationship to the mean of a group of values. Z-score is measured in terms of standard deviations from the mean. If a Z-score is 0, it indicates that the data point's score is identical to the mean score. A Z-score of 1.0 would indicate a value that is one standard deviation from the mean. Z-scores may be positive or negative, with a positive value indicating the score is above the mean and a negative score indicating it is below the mean."
The Z-score is central to this strategy. It is calculated by taking the difference between the current price and the Exponential Moving Average (EMA) of the price over a user-defined length, then dividing this by the standard deviation of the price over the same length:
z = (x - μ) /σ
Local
🔶 Trading Signals
Trading signals are generated based on the Z-score crossing predefined thresholds:
- Long Entry: When the Z-score crosses above the positive threshold.
- Long Exit: When the Z-score falls below the negative threshold.
- Short Entry: When the Z-score falls below the negative threshold.
- Short Exit: When the Z-score rises above the positive threshold.
█ Trade Direction
The strategy allows users to select their preferred trading direction through an input option.
█ Usage
To use this strategy effectively, traders should first configure the Z-score thresholds according to their risk tolerance and market volatility. It's also crucial to adjust the length for the EMA and standard deviation calculations based on historical performance and the expected "noise" in price data.
The strategy is designed to be flexible, allowing traders to refine settings to better capture profitable opportunities in specific market conditions.
█ Default Settings
- Trade Direction: Both
- Standard Deviation Length: 100
- Average Length: 100
- Threshold for Z-score: 1.0
- Bar Color Indicator: Enabled
These settings offer a balanced starting point but can be customized to suit various trading styles and market environments. The strategy's parameters are designed to be adjusted as traders gain experience and refine their approach based on ongoing market analysis.
Z-score is a must-learn approach for every algorithmic trader.
Buy Sell Strategy With Z-Score [TradeDots]The "Buy Sell Strategy With Z-Score" is a trading strategy that harnesses Z-Score statistical metrics to identify potential pricing reversals, for opportunistic buying and selling opportunities.
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.
This approach provides an estimation of the price's departure from its traditional trajectory, thereby identifying market conditions conducive to an asset being overpriced or underpriced.
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 EURUSD 1h timeframe
Rolling Window: 80
Z-Score Threshold: 2.8
Signal Cool Down Period: 5
Commission: 0.03%
Initial Capital: $10,000
Equity per Trade: 30%
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.
[Sharpe projection SGM]Dynamic Support and Resistance: Traces adjustable support and resistance lines based on historical prices, signaling new market barriers.
Price Projections and Volatility: Calculates future price projections using moving averages and plots annualized standard deviation-based volatility bands to anticipate price dispersion.
Intuitive Coloring: Colors between support and resistance lines show up or down trends, making it easy to analyze quickly.
Analytics Dashboard: Displays key metrics such as the Sharpe Ratio, which measures average ROI adjusted for asset volatility
Volatility Management for Options Trading: The script helps evaluate strike prices and strategies for options, based on support and resistance levels and projected volatility.
Importance of Diversification: It is necessary to diversify investments to reduce risks and stabilize returns.
Disclaimer on Past Performance: Past performance does not guarantee future results, projections should be supplemented with other analyses.
The script settings can be adjusted according to the specific needs of each user.
The mean and standard deviation are two fundamental statistical concepts often represented in a Gaussian curve, or normal distribution. Here's a quick little lesson on these concepts:
Average
The mean (or arithmetic mean) is the result of the sum of all values in a data set divided by the total number of values. In a data distribution, it represents the center of gravity of the data points.
Standard Deviation
The standard deviation measures the dispersion of the data relative to its mean. A low standard deviation indicates that the data is clustered near the mean, while a high standard deviation shows that it is more spread out.
Gaussian curve
The Gaussian curve or normal distribution is a graphical representation showing the probability of distribution of data. It has the shape of a symmetrical bell centered on the middle. The width of the curve is determined by the standard deviation.
68-95-99.7 rule (rule of thumb): Approximately 68% of the data is within one standard deviation of the mean, 95% is within two standard deviations, and 99.7% is within three standard deviations.
In statistics, understanding the mean and standard deviation allows you to infer a lot about the nature of the data and its trends, and the Gaussian curve provides an intuitive visualization of this information.
In finance, it is crucial to remember that data dispersion can be more random and unpredictable than traditional statistical models like the normal distribution suggest. Financial markets are often affected by unforeseen events or changes in investor behavior, which can result in return distributions with wider standard deviations or non-symmetrical distributions.
Trend Analysis with Standard Deviation by zdmre This script analyzes trends in financial markets using standard deviation.
The script works by first calculating the standard deviation of a security's price over a specified period of time. The script then uses this standard deviation to identify potential trend reversals.
For example, if the standard deviation of a security's price is high, this could indicate that the security is overvalued and due for a correction. Conversely, if the standard deviation of a security's price is low, this could indicate that the security is undervalued and due for a rally.
The script can be used to analyze any security, including stocks, bonds, and currencies. It can also be used to analyze different time frames, such as daily, weekly, and monthly.
How to Use the Script
To use the script, you will need to specify the following parameters:
Time frame: The time frame you want to analyze.
Standard deviation: The standard deviation you want to use.
Once you have specified these parameters, the script will calculate the standard deviation of the security's price over the specified time frame. The script will then use this standard deviation to identify potential trend reversals.
#DYOR
OI Bubbles aggrThis indicator visually represents the positioning of market participants using open interest (OI) data of Bitcoin futures obtained from multiple exchanges.
The main features and functions of the indicator are as follows:
1. Aggregation of OI data from multiple exchanges
- Retrieves and sums OI data from 5 symbols: Binance (BTCUSDTPERP, BTCPERP), Kraken (BTCUSDTPERP), and BitMEX (XBTUSD, XBTUSDT)
2. Calculation of Z-score for OI
- Calculates the Z-score for the total OI
- Uses a moving average (default period is 21) specified for the Z-score calculation
- The Z-score expresses how much the OI value deviates from the average in units of standard deviation
3. Display of signals based on Z-score
- Displays signals when the Z-score exceeds/falls below multiple predefined thresholds (default is 5 levels: 2, 2.5, 3, 4, 5)
- Signals are displayed as colored circles in the middle of the corresponding candle
- The size of the circle increases as the threshold is significantly exceeded, visually emphasizing the magnitude of the position bias
4. Customizable parameters
- Selection of exchanges and symbols to use
- Setting of the type and period of moving average used for Z-score calculation
- Setting of Z-score thresholds
- Setting of signal colors
Extreme position biases may lead to subsequent price movements, making them a key signal for trading.
However, this indicator is based solely on OI data and does not consider other market data such as price action or trading volume.
Therefore, it is crucial to combine the signals obtained from this indicator with other analytical methods for a comprehensive assessment.
Furthermore, the results can be greatly influenced by the parameter settings of the indicator, such as the Z-score thresholds and calculation periods. As a result, it is necessary to conduct thorough backtesting on historical data to find the optimal settings.
VWAP SpiderThe VWAP Spider indicator enhances the conventional Volume Weighted Average Price (VWAP) analysis by anchoring it to the first candle and incorporating an extensive series of standard deviation (SD) lines, extending up to +8 SDs with additional half-step increments. This configuration provides a more suitable set of lines for identifying support and resistance, distinguishing it from existing VWAP and SD indicators. Its design, featuring color gradients for fills and distinct labels for each line, aims to improve the utility and user experience.
Optimal Timeframes:
It is recommended for use on weekly or monthly resolutions to ensure all price and volume history is included.
Distinctive Features:
The indicator includes a more extensive array of SD lines than typically found in VWAP indicators, enhancing the depth of market analysis.
The visual presentation is optimized with color gradients and clear labeling, facilitating ease of use and integration into trading strategies.
Practical Use of the VWAP Spider:
SD Lines as Support and Resistance : Observe the interactions between the price and the SD lines closely. These can serve as dynamic support and resistance indicators, influencing trading decisions.
Analyzing Historical Price Action : Investigate how the price has historically interacted with the SD lines. Identify which lines have frequently acted as support and resistance in the past, as they will often continue to be revisited.
Strategic Application : Leverage insights from the interactions between price and SD lines to fine-tune entry and exit points. For example, a rebound from an SD line may suggest a strong entry point, while breaching an SD line could indicate a potential exit.
This indicator is freely available and open-source on TradingView for all. It is designed to help traders enhance their market analysis and strategic decision-making.
GKD-V Stiffness [Loxx]The Giga Kaleidoscope GKD-V Stiffness is a Volume/Volatility module included in Loxx's "Giga Kaleidoscope Modularized Trading System."
█ GKD-V Stiffness
The stiffness indicator quantifies the market's momentum by analyzing the relationship between price movements and volatility over a specific time frame. It employs a moving average to smooth out price data, providing a baseline for trend assessment. The key element in this calculation is the incorporation of a volatility factor, typically standard deviation, which adjusts the moving average to account for market volatility. This adjusted moving average creates a benchmark that the current price must surpass to signal significant momentum.
By comparing the current price to this volatility-adjusted moving average, the stiffness indicator determines the strength of the market's trend. A higher stiffness value, surpassing a predefined threshold, indicates a strong and potentially profitable trend, either upward or downward, suggesting opportunities for strategic trading positions. Conversely, a stiffness value below the threshold signifies insufficient momentum, advising traders to refrain from entering the market due to the high risk of unpredictability. This method provides a systematic approach to evaluate market trends, enabling traders to make decisions based on the robustness of price movements relative to historical volatility.
█ Giga Kaleidoscope Modularized Trading System
Core components of an NNFX algorithmic trading strategy
The NNFX algorithm is built on the principles of trend, momentum, and volatility. There are six core components in the NNFX trading algorithm:
1. Volatility - price volatility; e.g., Average True Range, True Range Double, Close-to-Close, etc.
2. Baseline - a moving average to identify price trend
3. Confirmation 1 - a technical indicator used to identify trends
4. Confirmation 2 - a technical indicator used to identify trends
5. Continuation - a technical indicator used to identify trends
6. Volatility/Volume - a technical indicator used to identify volatility/volume breakouts/breakdown
7. Exit - a technical indicator used to determine when a trend is exhausted
8. Metamorphosis - a technical indicator that produces a compound signal from the combination of other GKD indicators*
*(not part of the NNFX algorithm)
What is Volatility in the NNFX trading system?
In the NNFX (No Nonsense Forex) trading system, ATR (Average True Range) is typically used to measure the volatility of an asset. It is used as a part of the system to help determine the appropriate stop loss and take profit levels for a trade. ATR is calculated by taking the average of the true range values over a specified period.
True range is calculated as the maximum of the following values:
-Current high minus the current low
-Absolute value of the current high minus the previous close
-Absolute value of the current low minus the previous close
ATR is a dynamic indicator that changes with changes in volatility. As volatility increases, the value of ATR increases, and as volatility decreases, the value of ATR decreases. By using ATR in NNFX system, traders can adjust their stop loss and take profit levels according to the volatility of the asset being traded. This helps to ensure that the trade is given enough room to move, while also minimizing potential losses.
Other types of volatility include True Range Double (TRD), Close-to-Close, and Garman-Klass
What is a Baseline indicator?
The baseline is essentially a moving average, and is used to determine the overall direction of the market.
The baseline in the NNFX system is used to filter out trades that are not in line with the long-term trend of the market. The baseline is plotted on the chart along with other indicators, such as the Moving Average (MA), the Relative Strength Index (RSI), and the Average True Range (ATR).
Trades are only taken when the price is in the same direction as the baseline. For example, if the baseline is sloping upwards, only long trades are taken, and if the baseline is sloping downwards, only short trades are taken. This approach helps to ensure that trades are in line with the overall trend of the market, and reduces the risk of entering trades that are likely to fail.
By using a baseline in the NNFX system, traders can have a clear reference point for determining the overall trend of the market, and can make more informed trading decisions. The baseline helps to filter out noise and false signals, and ensures that trades are taken in the direction of the long-term trend.
What is a Confirmation indicator?
Confirmation indicators are technical indicators that are used to confirm the signals generated by primary indicators. Primary indicators are the core indicators used in the NNFX system, such as the Average True Range (ATR), the Moving Average (MA), and the Relative Strength Index (RSI).
The purpose of the confirmation indicators is to reduce false signals and improve the accuracy of the trading system. They are designed to confirm the signals generated by the primary indicators by providing additional information about the strength and direction of the trend.
Some examples of confirmation indicators that may be used in the NNFX system include the Bollinger Bands, the MACD (Moving Average Convergence Divergence), and the MACD Oscillator. These indicators can provide information about the volatility, momentum, and trend strength of the market, and can be used to confirm the signals generated by the primary indicators.
In the NNFX system, confirmation indicators are used in combination with primary indicators and other filters to create a trading system that is robust and reliable. By using multiple indicators to confirm trading signals, the system aims to reduce the risk of false signals and improve the overall profitability of the trades.
What is a Continuation indicator?
In the NNFX (No Nonsense Forex) trading system, a continuation indicator is a technical indicator that is used to confirm a current trend and predict that the trend is likely to continue in the same direction. A continuation indicator is typically used in conjunction with other indicators in the system, such as a baseline indicator, to provide a comprehensive trading strategy.
What is a Volatility/Volume indicator?
Volume indicators, such as the On Balance Volume (OBV), the Chaikin Money Flow (CMF), or the Volume Price Trend (VPT), are used to measure the amount of buying and selling activity in a market. They are based on the trading volume of the market, and can provide information about the strength of the trend. In the NNFX system, volume indicators are used to confirm trading signals generated by the Moving Average and the Relative Strength Index. Volatility indicators include Average Direction Index, Waddah Attar, and Volatility Ratio. In the NNFX trading system, volatility is a proxy for volume and vice versa.
By using volume indicators as confirmation tools, the NNFX trading system aims to reduce the risk of false signals and improve the overall profitability of trades. These indicators can provide additional information about the market that is not captured by the primary indicators, and can help traders to make more informed trading decisions. In addition, volume indicators can be used to identify potential changes in market trends and to confirm the strength of price movements.
What is an Exit indicator?
The exit indicator is used in conjunction with other indicators in the system, such as the Moving Average (MA), the Relative Strength Index (RSI), and the Average True Range (ATR), to provide a comprehensive trading strategy.
The exit indicator in the NNFX system can be any technical indicator that is deemed effective at identifying optimal exit points. Examples of exit indicators that are commonly used include the Parabolic SAR, and the Average Directional Index (ADX).
The purpose of the exit indicator is to identify when a trend is likely to reverse or when the market conditions have changed, signaling the need to exit a trade. By using an exit indicator, traders can manage their risk and prevent significant losses.
In the NNFX system, the exit indicator is used in conjunction with a stop loss and a take profit order to maximize profits and minimize losses. The stop loss order is used to limit the amount of loss that can be incurred if the trade goes against the trader, while the take profit order is used to lock in profits when the trade is moving in the trader's favor.
Overall, the use of an exit indicator in the NNFX trading system is an important component of a comprehensive trading strategy. It allows traders to manage their risk effectively and improve the profitability of their trades by exiting at the right time.
What is an Metamorphosis indicator?
The concept of a metamorphosis indicator involves the integration of two or more GKD indicators to generate a compound signal. This is achieved by evaluating the accuracy of each indicator and selecting the signal from the indicator with the highest accuracy. As an illustration, let's consider a scenario where we calculate the accuracy of 10 indicators and choose the signal from the indicator that demonstrates the highest accuracy.
The resulting output from the metamorphosis indicator can then be utilized in a GKD-BT backtest by occupying a slot that aligns with the purpose of the metamorphosis indicator. The slot can be a GKD-B, GKD-C, or GKD-E slot, depending on the specific requirements and objectives of the indicator. This allows for seamless integration and utilization of the compound signal within the GKD-BT framework.
How does Loxx's GKD (Giga Kaleidoscope Modularized Trading System) implement the NNFX algorithm outlined above?
Loxx's GKD v2.0 system has five types of modules (indicators/strategies). These modules are:
1. GKD-BT - Backtesting module (Volatility, Number 1 in the NNFX algorithm)
2. GKD-B - Baseline module (Baseline and Volatility/Volume, Numbers 1 and 2 in the NNFX algorithm)
3. GKD-C - Confirmation 1/2 and Continuation module (Confirmation 1/2 and Continuation, Numbers 3, 4, and 5 in the NNFX algorithm)
4. GKD-V - Volatility/Volume module (Confirmation 1/2, Number 6 in the NNFX algorithm)
5. GKD-E - Exit module (Exit, Number 7 in the NNFX algorithm)
6. GKD-M - Metamorphosis module (Metamorphosis, Number 8 in the NNFX algorithm, but not part of the NNFX algorithm)
(additional module types will added in future releases)
Each module interacts with every module by passing data to A backtest module wherein the various components of the GKD system are combined to create a trading signal.
That is, the Baseline indicator passes its data to Volatility/Volume. The Volatility/Volume indicator passes its values to the Confirmation 1 indicator. The Confirmation 1 indicator passes its values to the Confirmation 2 indicator. The Confirmation 2 indicator passes its values to the Continuation indicator. The Continuation indicator passes its values to the Exit indicator, and finally, the Exit indicator passes its values to the Backtest strategy.
This chaining of indicators requires that each module conform to Loxx's GKD protocol, therefore allowing for the testing of every possible combination of technical indicators that make up the six components of the NNFX algorithm.
What does the application of the GKD trading system look like?
Example trading system:
Backtest: Multi-Ticker CC Backtest
Baseline: Hull Moving Average
Volatility/Volume: Hurst Exponent
Confirmation 1: Advance Trend Pressure as shown on the chart above
Confirmation 2: uf2018
Continuation: Coppock Curve
Exit: Rex Oscillator
Metamorphosis: Baseline Optimizer
Each GKD indicator is denoted with a module identifier of either: GKD-BT, GKD-B, GKD-C, GKD-V, GKD-M, or GKD-E. This allows traders to understand to which module each indicator belongs and where each indicator fits into the GKD system.
█ Giga Kaleidoscope Modularized Trading System Signals
Standard Entry
1. GKD-C Confirmation gives signal
2. Baseline agrees
3. Price inside Goldie Locks Zone Minimum
4. Price inside Goldie Locks Zone Maximum
5. Confirmation 2 agrees
6. Volatility/Volume agrees
1-Candle Standard Entry
1a. GKD-C Confirmation gives signal
2a. Baseline agrees
3a. Price inside Goldie Locks Zone Minimum
4a. Price inside Goldie Locks Zone Maximum
Next Candle
1b. Price retraced
2b. Baseline agrees
3b. Confirmation 1 agrees
4b. Confirmation 2 agrees
5b. Volatility/Volume agrees
Baseline Entry
1. GKD-B Baseline gives signal
2. Confirmation 1 agrees
3. Price inside Goldie Locks Zone Minimum
4. Price inside Goldie Locks Zone Maximum
5. Confirmation 2 agrees
6. Volatility/Volume agrees
7. Confirmation 1 signal was less than 'Maximum Allowable PSBC Bars Back' prior
1-Candle Baseline Entry
1a. GKD-B Baseline gives signal
2a. Confirmation 1 agrees
3a. Price inside Goldie Locks Zone Minimum
4a. Price inside Goldie Locks Zone Maximum
5a. Confirmation 1 signal was less than 'Maximum Allowable PSBC Bars Back' prior
Next Candle
1b. Price retraced
2b. Baseline agrees
3b. Confirmation 1 agrees
4b. Confirmation 2 agrees
5b. Volatility/Volume agrees
Volatility/Volume Entry
1. GKD-V Volatility/Volume gives signal
2. Confirmation 1 agrees
3. Price inside Goldie Locks Zone Minimum
4. Price inside Goldie Locks Zone Maximum
5. Confirmation 2 agrees
6. Baseline agrees
7. Confirmation 1 signal was less than 7 candles prior
1-Candle Volatility/Volume Entry
1a. GKD-V Volatility/Volume gives signal
2a. Confirmation 1 agrees
3a. Price inside Goldie Locks Zone Minimum
4a. Price inside Goldie Locks Zone Maximum
5a. Confirmation 1 signal was less than 'Maximum Allowable PSVVC Bars Back' prior
Next Candle
1b. Price retraced
2b. Volatility/Volume agrees
3b. Confirmation 1 agrees
4b. Confirmation 2 agrees
5b. Baseline agrees
Confirmation 2 Entry
1. GKD-C Confirmation 2 gives signal
2. Confirmation 1 agrees
3. Price inside Goldie Locks Zone Minimum
4. Price inside Goldie Locks Zone Maximum
5. Volatility/Volume agrees
6. Baseline agrees
7. Confirmation 1 signal was less than 7 candles prior
1-Candle Confirmation 2 Entry
1a. GKD-C Confirmation 2 gives signal
2a. Confirmation 1 agrees
3a. Price inside Goldie Locks Zone Minimum
4a. Price inside Goldie Locks Zone Maximum
5a. Confirmation 1 signal was less than 'Maximum Allowable PSC2C Bars Back' prior
Next Candle
1b. Price retraced
2b. Confirmation 2 agrees
3b. Confirmation 1 agrees
4b. Volatility/Volume agrees
5b. Baseline agrees
PullBack Entry
1a. GKD-B Baseline gives signal
2a. Confirmation 1 agrees
3a. Price is beyond 1.0x Volatility of Baseline
Next Candle
1b. Price inside Goldie Locks Zone Minimum
2b. Price inside Goldie Locks Zone Maximum
3b. Confirmation 1 agrees
4b. Confirmation 2 agrees
5b. Volatility/Volume agrees
Continuation Entry
1. Standard Entry, 1-Candle Standard Entry, Baseline Entry, 1-Candle Baseline Entry, Volatility/Volume Entry, 1-Candle Volatility/Volume Entry, Confirmation 2 Entry, 1-Candle Confirmation 2 Entry, or Pullback entry triggered previously
2. Baseline hasn't crossed since entry signal trigger
4. Confirmation 1 agrees
5. Baseline agrees
6. Confirmation 2 agrees
BTC Spread Indicator"Hot potato, Bitcoin style!
In the dynamic world of cryptocurrency, keeping an eye on price movements across different exchanges can be as exhilarating as a game of hot potato. By calculating the average Bitcoin price across major exchanges, we can then dive deeper to identify the spreads between this global average and the prices on individual exchanges. This analysis reveals who's currently 'holding the potato'—or dealing with higher prices—and predicts who might be next. It's a fun, yet insightful way to visualize market volatility and trading opportunities. Let's see where the potato lands next!"
Bitcoin Leverage Sentiment - Strategy [presentTrading]█ Introduction and How it is Different
The "Bitcoin Leverage Sentiment - Strategy " represents a novel approach in the realm of cryptocurrency trading by focusing on sentiment analysis through leveraged positions in Bitcoin. Unlike traditional strategies that primarily rely on price action or technical indicators, this strategy leverages the power of Z-Score analysis to gauge market sentiment by examining the ratio of leveraged long to short positions. By assessing how far the current sentiment deviates from the historical norm, it provides a unique lens to spot potential reversals or continuation in market trends, making it an innovative tool for traders who wish to incorporate market psychology into their trading arsenal.
BTC 4h L/S Performance
local
█ Strategy, How It Works: Detailed Explanation
🔶 Data Collection and Ratio Calculation
Firstly, the strategy acquires data on leveraged long (**`priceLongs`**) and short positions (**`priceShorts`**) for Bitcoin. The primary metric of interest is the ratio of long positions relative to the total of both long and short positions:
BTC Ratio=priceLongs / (priceLongs+priceShorts)
This ratio reflects the prevailing market sentiment, where values closer to 1 indicate a bullish sentiment (dominance of long positions), and values closer to 0 suggest bearish sentiment (prevalence of short positions).
🔶 Z-Score Calculation
The Z-Score is then calculated to standardize the BTC Ratio, allowing for comparison across different time periods. The Z-Score formula is:
Z = (X - μ) / σ
Where:
- X is the current BTC Ratio.
- μ is the mean of the BTC Ratio over a specified period (**`zScoreCalculationPeriod`**).
- σ is the standard deviation of the BTC Ratio over the same period.
The Z-Score helps quantify how far the current sentiment deviates from the historical norm, with high positive values indicating extreme bullish sentiment and high negative values signaling extreme bearish sentiment.
🔶 Signal Generation: Trading signals are derived from the Z-Score as follows:
Long Entry Signal: Occurs when the BTC Ratio Z-Score crosses above the thresholdLongEntry, suggesting bullish sentiment.
- Condition for Long Entry = BTC Ratio Z-Score > thresholdLongEntry
Long Exit/Short Entry Signal: Triggered when the BTC Ratio Z-Score drops below thresholdLongExit for exiting longs or below thresholdShortEntry for entering shorts, indicating a shift to bearish sentiment.
- Condition for Long Exit/Short Entry = BTC Ratio Z-Score < thresholdLongExit or BTC Ratio Z-Score < thresholdShortEntry
Short Exit Signal: Happens when the BTC Ratio Z-Score exceeds the thresholdShortExit, hinting at reducing bearish sentiment and a potential switch to bullish conditions.
- Condition for Short Exit = BTC Ratio Z-Score > thresholdShortExit
🔶Implementation and Visualization: The strategy applies these conditions for trade management, aligning with the selected trade direction. It visualizes the BTC Ratio Z-Score with horizontal lines at entry and exit thresholds, illustrating the current sentiment against historical norms.
█ Trade Direction
The strategy offers flexibility in trade direction, allowing users to choose between long, short, or both, depending on their market outlook and risk tolerance. This adaptability ensures that traders can align the strategy with their individual trading style and market conditions.
█ Usage
To employ this strategy effectively:
1. Customization: Begin by setting the trade direction and adjusting the Z-Score calculation period and entry/exit thresholds to match your trading preferences.
2. Observation: Monitor the Z-Score and its moving average for potential trading signals. Look for crossover events relative to the predefined thresholds to identify entry and exit points.
3. Confirmation: Consider using additional analysis or indicators for signal confirmation, ensuring a comprehensive approach to decision-making.
█ Default Settings
- Trade Direction: Determines if the strategy engages in long, short, or both types of trades, impacting its adaptability to market conditions.
- Timeframe Input: Influences signal frequency and sensitivity, affecting the strategy's responsiveness to market dynamics.
- Z-Score Calculation Period: Affects the strategy’s sensitivity to market changes, with longer periods smoothing data and shorter periods increasing responsiveness.
- Entry and Exit Thresholds: Set the Z-Score levels for initiating or exiting trades, balancing between capturing opportunities and minimizing false signals.
- Impact of Default Settings: Provides a balanced approach to leverage sentiment trading, with adjustments needed to optimize performance across various market conditions.
Likelihood of Winning - Probability Density FunctionIn developing the "Likelihood of Winning - Probability Density Function (PDF)" indicator, my aim was to offer traders a statistical tool to quantify the probability of reaching target prices. This indicator, grounded in risk assessment principles, enables users to analyze potential outcomes based on the normal distribution, providing insights into market dynamics.
The tool's flexibility allows for customization of the data series, lookback periods, and target settings for both long and short scenarios. It features a color-coded visualization to easily distinguish between probabilities of hitting specified targets, enhancing decision-making in trading strategies.
I'm excited to share this indicator with the trading community, hoping it will enhance data-driven decision-making and offer a deeper understanding of market risks and opportunities. My goal is to continuously improve this tool based on user feedback and market evolution, contributing to more informed trading practices.
This indicator leverages the "NormalDistributionFunctions" library, enabling easy integration into other indicators or strategies. Users can readily embed advanced statistical analysis into their trading tools, fostering innovation within the Pine Script community.
VWAP Bands @shrilssVWAP Bands Integrates VWAP with standard deviation bands to provide traders with insights into potential support and resistance levels based on volume dynamics. VWAP is a key metric used by institutional traders to gauge the average price a security has traded at throughout the trading day, taking into account both price and volume.
This script calculates the VWAP for each trading session and overlays it on the price chart as a solid line. Additionally, it plots multiple standard deviation bands around the VWAP to indicate potential areas of price extension or contraction. These bands are derived from multiplying the standard deviation of price by predetermined factors, offering traders a visual representation of potential price ranges.
Dynamic Price Targets @shrilssDynamic Price Targets is a designed to provide traders with a comprehensive view of dynamic price levels based on Volume Weighted Moving Average (VWMA) and standard deviation. This script allows users to identify potential support and resistance zones, aiding in strategic decision-making during market analysis.
The script calculates the VWMA of a chosen price source over a specified length, establishing a dynamic baseline for market trends. The standard deviation is then used to derive multiple upper and lower targets, each representing a certain deviation from the VWMA. These levels are color-coded for clarity, with upper targets displayed in shades of red and lower targets in shades of green.
Modern Portfolio TheoryModern Portfolio Theory
The indicator is designed to apply the principles of Modern Portfolio Theory, a financial theory developed by Harry Markowitz. MPT aims to maximize portfolio returns for a given level of risk by diversifying investments.
User Inputs:
Users can customize various parameters, including the bar scale, risk-free rate, and the start year for the portfolio. Additionally, users can assign weights to different assets (symbols) in the portfolio.
Asset Selection:
Users can choose up to 10 different symbols (assets) for the portfolio. The script supports a variety of symbols, including cryptocurrencies such as BTCUSD and ETHUSD.
Weights and Allocation:
Users can assign weights to each selected asset, determining its percentage allocation in the portfolio. The script calculates the total portfolio weight to ensure it equals 100%. If total portfolio weight is lower then 100% you will see orange color with additional cash % bellow
If total portfolio weight is bigger then 100% you will see red big % warning.
Warning: (Total Weight must be 100%)
Cash Mode:
Risk and Return Calculation:
The script calculates the daily returns and standard deviation for each selected asset. These metrics are essential for assessing the risk and return of each asset, as well as the overall portfolio.
Scatter Plot Visualization:
The indicator includes a scatter plot that visualizes the risk-return profile of each asset. Each point on the plot represents an asset, and its position is determined by its risk (X-axis) and return (Y-axis).
Portfolio Optimization:
The script calculates the risk and return of the overall portfolio based on the selected assets and their weights. Based on the selected assets and their weights user can create optimal portfolio with preferable risk and return.
It then plots the portfolio point on the scatter plot, indicating its risk-return profile.
Additional Information:
The indicator provides a table displaying information about each selected asset, including its symbol, weight, and total portfolio weight. The table also shows the total portfolio weight and, if applicable, the percentage allocated to cash.
Visualization and Legend:
The script includes visual elements such as a legend, capital allocation line (CAL), and labels for risk-free rate and key information. This enhances the overall understanding of the portfolio's risk and return characteristics.
User Guidance:
The script provides informative labels and comments to guide users through the interpretation of the scatter plot, risk-return axes, and other key elements.
Interactivity:
Users can interact with the indicator on the TradingView platform, exploring different asset combinations and weightings to observe the resulting changes in the portfolio's risk and return.
In summary, this Pine Script serves as a comprehensive tool for traders and investors interested in applying Modern Portfolio Theory principles to optimize their portfolio allocations based on individual asset characteristics, risk preferences, and return
Z-score changeAs a wise man once said that:
1. beginners think in $ change
2. intermediates think in % change
3. pros think in Z change
Here is the "Z-score change" indicator that calculates up/down moves normalized by standard deviation (volatility) displayed as bar chart with 1,2 and 3 stdev levels.
CARNAC Elasticity IndicatorThe CARNAC Elasticity Indicator (EI) is a technical analysis tool designed for traders and investors using TradingView. It calculates the percentage deviation of the current price from an Exponential Moving Average (EMA) and helps traders identify potential overbought and oversold conditions in a financial instrument.
Key Features:
EMA Length: Users can customize the length of the Exponential Moving Average (EMA) used in the calculations by adjusting the "EMA Length" parameter in the indicator settings.
Percentage Deviation: The indicator calculates the percentage deviation of the current price from the EMA. Positive values indicate prices above the EMA, while negative values indicate prices below the EMA.
Maximum Deviations: The indicator tracks the maximum positive (above EMA) and negative (below EMA) percentage deviations over time, allowing traders to monitor extreme price movements.
Bands: Upper and lower bands are displayed on the indicator chart at 100 and -100, respectively. Additionally, dashed middle bands at 50 and -50 provide reference points for moderate deviations.
Dynamic Color Coding: The indicator uses dynamic color coding to highlight the current percentage deviation. It turns red for values above 50 (indicating potential overbought conditions), green for values below -50 (indicating potential oversold conditions), and purple for values in between.
How to Use:
Overbought Conditions: Watch for the percentage deviation to cross above 50, indicating potential overbought conditions. This might be a signal to consider selling or taking profits.
Oversold Conditions: Look for the percentage deviation to cross below -50, signaling potential oversold conditions. This could be an opportunity to consider buying or entering a long position.
Historical Extremes: Keep an eye on the upper and lower bands (100 and -100) to identify historical extremes in percentage deviation.
The CARNAC Elasticity Indicator can be a valuable tool for traders seeking to identify potential trend reversals and assess the strength of price movements. However, it should be used in conjunction with other technical analysis tools and risk management strategies for comprehensive trading decisions.
Rolling VWAP [QuantraSystems]Rolling VWAP
Introduction
The Rolling VWAP (R͜͡oll-VWAP) indicator modernizes the traditional VWAP by recalculating continuously on a rolling window, making it adept at pinpointing market trends and breakout points.
Its dual functionality includes both the dynamic rolling VWAP and a customizable anchored VWAP, enhanced by color-coded visual cues, thereby offering traders valuable flexibility and insight for their market analysis.
Legend
In the Image you can see the BTCUSD 1D Chart with the R͜͡oll-VWAP overlay.
You can see the individually activatable Standard Deviation (SD) Bands and the main VWAP Line.
It also features a Trend Signal which is deactivated by default and can be enabled if required.
Furthermore you can find the coloring of the VWAP line to represent the Trend.
In this case the trend itself is defined as:
Close being greater than the VWAP line -> Uptrend
Close below the VWAP line -> Downtrend
Notes
The R͜͡oll-VWAP can be used in a variety of ways.
Volatility adjusted expected range
This aims to identify in which range the asset is likely to move - according to the historical values the SD Bands are calculated and thus their according probabilities displayed.
Trend analysis
Trending above or below the VWAP shows up or down trends accordingly.
S/R Levels
Based on the probability distribution the 2. SD often works as a Resistance level and either mid line or 1. SD lines can act as S/R levels
Unsustainable levels
Based on the probability distributions a SD level of beyond 2.5, especially 3 and higher is hit very seldom and highly unsustainable.
This can either mean a mean reversion state or a momentum slowdown is necessary to get back to a sustainable level.
Please note that we always advise to find more confluence by additional indicators.
Traders are encouraged to test and determine the most suitable settings for their specific trading strategies and timeframes.
Methodology
The R͜͡oll-VWAP is based on the inbuilt TV VWAP.
It expands upon the limitations of having an anchored timeframe and thus a limited data set that is being reset constantly.
Instead we have integrated a rolling nature that continuously calculates the VWAP over a customizable lookback.
To also keep the base utility it is possible to use the anchored timeframes as well.
Furthermore the visualization has been improved and we added the coloring of the main VWAP line according to the Trend as stated above.
The applicable Trend signals are also part of that.
The parameter settings and also the visualizations allow for ample customizations by the trader.
For questions or recommendations, please feel free to seek contact in the comments.
Volatility ZigZagIt calculates and plots zigzag lines based on volatility and price movements. It has various inputs for customization, allowing you to adjust parameters like source data, length, deviation, line styling, and labeling options.
The indicator identifies pivot points in the price movement, drawing lines between these pivots based on the deviation from certain price levels or volatility measures.
The script labels various data points at the ZigZag pivot points on the chart. These labels provide information about different aspects of the price movement and volume around these pivot points. Here's a breakdown of what gets labeled:
Price Change: Indicates the absolute and average percentage change between the two pivot points. It displays the absolute or relative change in price as a percentage. Additionally, the average absolute price increase or the average rate of increase can also be labeled.
Volume: Shows the total volume and average volume between the two pivot points.
Number of Bars: Indicates the number of bars between the current and the last pivot point.
Reversal Price: Displays the price of the reversal point (the previous pivot).
Machine Learning: STDEV Oscillator [YinYangAlgorithms]This Indicator aims to fill a gap within traditional Standard Deviation Analysis. Rather than its usual applications, this Indicator focuses on applying Standard Deviation within an Oscillator and likewise applying a Machine Learning approach to it. By doing so, we may hope to achieve an Adaptive Oscillator which can help display when the price is deviating from its standard movement. This Indicator may help display both when the price is Overbought or Underbought, and likewise, where the price may face Support and Resistance. The reason for this is that rather than simply plotting a Machine Learning Standard Deviation (STDEV), we instead create a High and a Low variant of STDEV, and then use its Highest and Lowest values calculated within another Deviation to create Deviation Zones. These zones may help to display these Support and Resistance locations; and likewise may help to show if the price is Overbought or Oversold based on its placement within these zones. This Oscillator may also help display Momentum when the High and/or Low STDEV crosses the midline (0). Lastly, this Oscillator may also be useful for seeing the spacing between the High and Low of the STDEV; large spacing may represent volatility within the STDEV which may be helpful for seeing when there is Momentum in the form of volatility.
Tutorial:
Above is an example of how this Indicator looks on BTC/USDT 1 Day. As you may see, when the price has parabolic movement, so does the STDEV. This is due to this price movement deviating from the mean of the data. Therefore when these parabolic movements occur, we create the Deviation Zones accordingly, in hopes that it may help to project future Support and Resistance locations as well as helping to display when the price is Overbought and Oversold.
If we zoom in a little bit, you may notice that the Support Zone (Blue) is smaller than the Resistance Zone (Orange). This is simply because during the last Bull Market there was more parabolic price deviation than there was during the Bear Market. You may see this if you refer to their values; the Resistance Zone goes to ~18k whereas the Support Zone is ~10.5k. This is completely normal and the way it is supposed to work. Due to the nature of how STDEV works, this Oscillator doesn’t use a 1:1 ratio and instead can develop and expand as exponential price action occurs.
The Neutral (0) line may also act as a Support and Resistance location. In the example above we can see how when the STDEV is below it, it acts as Resistance; and when it’s above it, it acts as Support.
This Neutral line may also provide us with insight as towards the momentum within the market and when it has shifted. When the STDEV is below the Neutral line, the market may be considered Bearish. When the STDEV is above the Neutral line, the market may be considered Bullish.
The Red Line represents the STDEV’s High and the Green Line represents the STDEV’s Low. When the STDEV’s High and Low get tight and close together, this may represent there is currently Low Volatility in the market. Low Volatility may cause consolidation to occur, however it also leaves room for expansion.
However, when the STDEV’s High and Low are quite spaced apart, this may represent High levels of Volatility in the market. This may mean the market is more prone to parabolic movements and expansion.
We will conclude our Tutorial here. Hopefully this has given you some insight into how applying Machine Learning to a High and Low STDEV then creating Deviation Zones based on it may help project when the Momentum of the Market is Bullish or Bearish; likewise when the price is Overbought or Oversold; and lastly where the price may face Support and Resistance in the form of STDEV.
If you have any questions, comments, ideas or concerns please don't hesitate to contact us.
HAPPY TRADING!
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.
