E9 Bollinger RangeThe E9 Bollinger Range is a technical trading tool that leverages Bollinger Bands to track volatility and price deviations, along with additional trend filtering via EMAs.
The script visually enhances price action with a combination of trend-filtering EMAs, bar colouring for trend direction, signals to indicate potential buy and sell points based on price extension and engulfing patterns.
Here’s a breakdown of its key components:
Bollinger Bands: The strategy plots multiple Bollinger Band deviations to create different price levels. The furthest deviation bands act as warning signs for traders when price extends significantly, signaling potential overbought or oversold conditions.
Bar Colouring: Visual bar colouring is applied to clearly indicate trend direction: green bars for an uptrend and red bars for a downtrend.
EMA Filtering: Two EMAs (50 and 200) are used to help filter out false signals, giving traders a better sense of the underlying trend.
This combination of signals, visual elements, and trend filtering provides traders with a systematic approach to identifying price deviations and taking advantage of market corrections.
Brief History of Bollinger Bands
Bollinger Bands were developed by John Bollinger in the early 1980s as a tool to measure price volatility in financial markets. The bands consist of a moving average (typically 20 periods) with upper and lower bands placed two standard deviations away. These bands expand and contract based on market volatility, offering traders a visual representation of price extremes and potential reversal zones.
John Bollinger’s work revolutionized technical analysis by incorporating volatility into trend detection. His bands remain widely used across markets, including stocks, commodities, and cryptocurrencies. With the ability to highlight overbought and oversold conditions, Bollinger Bands have become a staple in many trading strategies.
Deviation
Multi-Step FlexiSuperTrend - Indicator [presentTrading]This version of the indicator is built upon the foundation of a strategy version published earlier. However, this indicator version focuses on providing visual insights and alerts for traders, rather than executing trades. This one is mostly for @thorcmt.
█ Introduction and How it is Different
The **Multi-Step FlexiSuperTrend Indicator** is a versatile tool designed to provide traders with a highly customizable and flexible approach to trend analysis. Unlike traditional supertrend indicators, which focus on a single factor or threshold, the **FlexiSuperTrend** allows users to define multiple levels of take-profit targets and incorporate different trend normalization methods.
It comes with several advanced customization features, including multi-step take profits, deviation plotting, and trend normalization, making it suitable for both novice and expert traders.
BTCUSD 6hr Performance
█ Strategy, How It Works: Detailed Explanation
The **Multi-Step FlexiSuperTrend** works by calculating a supertrend based on multiple factors and incorporating oscillations from trend deviations. Here’s a breakdown of how it functions:
🔶 SuperTrend Calculation
At the heart of the indicator is the SuperTrend formula, which dynamically adjusts based on price movements.
🔶 Normalization of Deviations
To enhance accuracy, the **FlexiSuperTrend** calculates multiple deviations from the trend and normalizes them.
🔶 Multi-Step Take Profit Levels
The indicator allows setting up to three take profit levels, which are displayed via price level alerts. lows traders to exit part of their position at various profit intervals.
For more detail, please check the strategy version - Multi-Step-FlexiSuperTrend-Strategy:
and 'FlexiSuperTrend-Strategy'
█ Trade Direction
The **Multi-Step FlexiSuperTrend Indicator** supports both long and short trade directions.
This flexibility allows traders to adapt to trending, volatile, or sideways markets.
█ Usage
To use the **FlexiSuperTrend Indicator**, traders can set up their preferences for the following key features:
- **Trading Direction**: Choose whether to focus on long, short, or both signals.
- **Indicator Source**: The price source to calculate the trend (e.g., close, hl2).
- **Indicator Length**: The number of periods to calculate the ATR and trend (the larger the value, the smoother the trend).
- **Starting and Increment Factor**: These adjust how reactive the trend is to price movements. The starting factor dictates how far the initial trend band is from the price, and the increment factor adjusts subsequent trend deviations.
The indicator then displays buy and sell signals on the chart, along with alerts for each take-profit level.
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█ Default Settings
The default settings of the **Multi-Step FlexiSuperTrend** are carefully designed to provide an optimal balance between sensitivity and accuracy. Let’s examine these default parameters and their effect on performance:
🔶 Indicator Length (Default: 10)
The **Indicator Length** determines the lookback period for the ATR calculation. A smaller value makes the indicator more reactive to price changes, but may generate more false signals. A longer length smooths the trend and reduces noise but may delay signals.
Effect on performance: Shorter lengths perform better in volatile markets, while longer lengths excel in trending markets.
🔶 Starting Factor (Default: 0.618)
This factor adjusts the starting distance of the SuperTrend from the current price. The smaller the starting factor, the closer the trend is to the price, making it more sensitive. Conversely, a larger factor allows more distance, reducing sensitivity but filtering out false signals.
Effect on performance: A smaller factor provides quicker signals but can lead to frequent false positives. A larger factor generates fewer but more reliable signals.
🔶 Increment Factor (Default: 0.382)
The **Increment Factor** controls how the trend bands adjust as the price moves. It increases the distance of the bands from the price with each iteration.
Effect on performance: A higher increment factor can result in wider stop-loss or trend reversal bands, allowing for longer trends to develop without frequent exits. A lower factor keeps the bands closer to the price and is more suited for shorter-term trades.
🔶 Take Profit Levels (Default: 2%, 8%, 18%)
The default take-profit levels are set at 2%, 8%, and 18%. These values represent the thresholds at which the trader can partially exit their positions. These multi-step levels are highly customizable depending on the trader’s risk tolerance and strategy.
Effect on performance: Lower take-profit levels (e.g., 2%) capture small, quick profits in volatile markets, while higher levels (8%-18%) allow for a more gradual exit in strong trends.
🔶 Normalization Method (Default: None)
The default normalization method is **None**, meaning the deviations are not normalized. However, enabling normalization (e.g., **Max-Min**) can improve the clarity of the indicator’s signals in volatile or choppy markets by smoothing out the noise.
Effect on performance: Using a normalization method can reduce the effect of extreme deviations, making signals more stable and less prone to false positives.
VWAP Bands [TradingFinder] 26 Brokers Data (Forex + Crypto)🔵 Introduction
Indicators are tools that help analysts predict the price trend of a stock through mathematical calculations on price or trading volume. It is evident that trading volume significantly impacts the price trend of a stock symbol.
The Volume-Weighted Average Price (VWAP) indicator combines the influence of trading volume and price, providing technical analysts with a practical tool.
This technical indicator determines the volume-weighted average price of a symbol over a specified time period. Consequently, this indicator can be used to identify trends and entry or exit points.
🟣 Calculating the VWAP Indicator
Adding the VWAP indicator to a chart will automatically perform all calculations for you. However, if you wish to understand how this indicator is calculated, the following explains the steps involved.
Consider a 5-minute chart. In the first candle of this chart (which represents price information in the first 5 minutes), sum the high, low, and close prices, and divide by 3. Multiply the resulting number by the volume for the period and call it a variable (e.g., X).
Then, divide the resulting output by the total volume for that period to calculate your VWAP. To maintain the VWAP sequence throughout the trading day, it is necessary to add the X values obtained from each period to the previous period and divide by the total volume up to that time. It is worth noting that the calculation method is the same for intervals shorter than a day.
The mathematical formula for this VWAP indicator : VWAP = ∑ (Pi×Vi) / ∑ Vi
🔵 How to Use
Traders might consider the VWAP indicator as a tool for predicting trends. For example, they might buy a stock when the price is above the VWAP level and sell it when the price is below the VWAP.
In other words, when the price is above the VWAP, the price is rising, and when it is below the VWAP, the price is falling. Major traders and investment funds also use the VWAP ratio to help enter or exit stocks with the least possible market impact.
It is important to note that one should not rely solely on the VWAP indicator when analyzing symbols. This is because if prices rise quickly, the VWAP indicator may not adequately describe the conditions. This indicator is generally used for daily or shorter time frames because using longer intervals can distort the average.
Since this indicator uses past data in its calculations, it can be considered a lagging indicator. As a result, the more data there is, the greater the delay.
🟣 Difference Between VWAP and Simple Moving Average
On a chart, the VWAP and the simple moving average may look similar, but these two indicators have different calculations. The VWAP calculates the total price considering volume, while the simple moving average does not consider volume.
In simpler terms, the VWAP indicator measures each day's price change relative to the trading volume that occurred that day. In contrast, the simple moving average implicitly assumes that all trading days have the same volume.
🟣 Reasons Why Traders Like the VWAP Indicator
The VWAP Considers Volume: Since VWAP takes volume into account, it can be more reliable than a simple arithmetic average of prices. Theoretically, one person can buy 200,000 shares of a symbol in one transaction at a single price.
However, during the same time frame, 100 other people might place 200 different orders at various prices that do not total 100,000 shares. In this case, if you only consider the average price, you might be mistaken because trading volume is ignored.
The Indicator Can Help Day Traders: While reviewing your trades, you might notice that the shares you bought at market price are trading below the VWAP indicator.
In this case, there's no need to worry because with the help of VWAP, you always get a price below the average. By knowing the volume-weighted average price of a stock, you can easily make an informed decision about paying more or less than other traders for the stock.
VWAP Can Signal Market Trend Changes: Buying low and selling high can be an excellent strategy for individuals. However, you are looking to buy when prices start to rise and sell your shares when prices start to fall.
Since the VWAP indicator simulates a balanced price in the market, when the price crosses above the VWAP line, one can assume that traders are willing to pay more to acquire shares, and as a result, the market will grow. Conversely, when the price crosses below the line, this can be considered a sign of a downward movement.
🔵 Setting
Period : Indicator calculation time frame.
Source : The Price used for calculations.
Market Ultra Data : If you turn on this feature, 26 large brokers will be included in the calculation of the trading volume.
The advantage of this capability is to have more reliable volume data. You should be careful to specify the market you are in, FOREX brokers and Crypto brokers are different.
Multiplier : Coefficient of band lines.
RSI DeviationAn oscillator which de-trends the Relative Strength Index. Rather, it takes a moving average of RSI and plots it's standard deviation from the MA, similar to a Bollinger %B oscillator. This seams to highlight short term peaks and troughs, Indicating oversold and overbought conditions respectively. It is intended to be used with a Dollar Cost Averaging strategy, but may also be useful for Swing Trading, or Scalping on lower timeframes.
When the line on the oscillator line crosses back into the channel, it signals a trade opportunity.
~ Crossing into the band from the bottom, indicates the end of an oversold condition, signaling a potential reversal. This would be a BUY signal.
~ Crossing into the band from the top, indicates the end of an overbought condition, signaling a potential reversal. This would be a SELL signal.
For ease of use, I've made the oscillator highlight the main chart when Overbought/Oversold conditions are occurring, and place fractals upon reversion to the Band. These repaint as they are calculated at close. The earliest trade would occur upon open of the following day.
I have set the default St. Deviation to be 2, but in my testing I have found 1.5 to be quite reliable. By decreasing the St. Deviation you will increase trade frequency, to a point, at the expense of efficiency.
Cheers
DJSnoWMan06
London Killzone + Deviations[MK]For traders that use the London Killzone session high/low to project possible take profit targets.
The indicator will determine the current day London killzone high and low range and draw a range box to the right of the last candle on the chart. Drawing to the right of the chart keeps the workspace cleaner.
The high/low range is then used to project Standard Deviation levels above and below the London range.
Levels projected are +/- 1, 2, 2.5, 3, 4.
Users of the script should conduct proper backtesting using a large data range before applying to live accounts.
FlexiMA x FlexiST - Strategy [presentTrading]█ Introduction and How it is Different
The FlexiMA x FlexiST Strategy blends two analytical methods - FlexiMA and FlexiST, which are opened in my early post.
- FlexiMA calculates deviations between an indicator source and a dynamic moving average, controlled by a starting factor and increment factor.
- FlexiST, on the other hand, leverages the SuperTrend model, adjusting the Average True Range (ATR) length for a comprehensive trend-following oscillator.
This synergy offers traders a more nuanced and multifaceted tool for market analysis.
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█ Strategy, How It Works: Detailed Explanation
The strategy combines two components: FlexiMA and FlexiST, each utilizing unique methodologies to analyze market trends.
🔶FlexiMA Component:
- Calculates deviations between an indicator source and moving averages of variable lengths.
- Moving average lengths are dynamically adjusted using a starting factor and increment factor.
- Deviations are normalized and analyzed to produce median and standard deviation values, forming the FlexiMA oscillator.
Length indicator (50)
🔶FlexiST Component:
- Uses SuperTrend indicators with varying ATR (Average True Range) lengths.
- Trends are identified based on the position of the indicator source relative to the SuperTrend bands.
- Deviations between the indicator source and SuperTrend values are calculated and normalized.
Starting Factor (5)
🔶Combined Strategy Logic:
- Entry Signals:
- Long Entry: Triggered when median values of both FlexiMA and FlexiST are positive.
- Short Entry: Triggered when median values of both FlexiMA and FlexiST are negative.
- Exit Signals:
- Long Exit: Triggered when median values of FlexiMA or FlexiST turn negative.
- Short Exit: Triggered when median values of FlexiMA or FlexiST turn positive.
This strategic blend of FlexiMA and FlexiST allows for a nuanced analysis of market trends, providing traders with signals based on a comprehensive view of market momentum and trend strength.
█ Trade Direction
The strategy is designed to cater to various trading preferences, offering "Long", "Short", and "Both" options. This flexibility allows traders to align the strategy with their specific market outlook, be it bullish, bearish, or a combination of both.
█ Usage
Traders can effectively utilize the FlexiMA x FlexiST Strategy by first selecting their desired trade direction. The strategy then generates entry signals when the conditions for either the FlexiMA or FlexiST are met, indicating potential entry points in the market. Conversely, exit signals are generated when the conditions for these indicators diverge, thus signaling a potential shift in market trends and suggesting a strategic exit point.
█ Default Settings
1. Indicator Source (HLC3): Provides a balanced and stable price source, reducing the impact of extreme market fluctuations.
2. Indicator Lengths (20 for FlexiMA, 10 for FlexiST): Longer FlexiMA length smooths out short-term fluctuations, while shorter FlexiST length allows for quicker response to market changes.
3. Starting Factors (1.0 for FlexiMA, 0.618 for FlexiST): Balanced start for FlexiMA and a harmonized approach for FlexiST, resonating with natural market cycles.
4. Increment Factors (1.0 for FlexiMA, 0.382 for FlexiST): FlexiMA captures a wide range of market behaviors, while FlexiST provides a gradual transition to capture finer trend shifts.
5. Normalization Methods ('None'): Uses raw deviations, suitable for markets where absolute price movements are more significant.
6. Trade Direction ('Both'): Allows strategy to consider both long and short opportunities, ideal for versatile market engagement.
*More details:
1. FlexiMA
2. FlexiST
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.
FlexiSuperTrend - Strategy [presentTrading]█ Introduction and How it is Different
The "FlexiSuperTrend - Strategy" by PresentTrading is a cutting-edge trading strategy that redefines market analysis through the integration of the SuperTrend indicator and advanced variance tracking.
BTC 6H L/S
This strategy stands apart from conventional methods by its dynamic adaptability, capturing market trends and momentum shifts with increased sensitivity. It's designed for traders seeking a more responsive tool to navigate complex market movements.
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█ Strategy, How It Works: Detailed Explanation
The "FlexiSuperTrend - Strategy" employs a multifaceted approach, combining the adaptability of the SuperTrend indicator with variance tracking. The strategy's core lies in its unique formulation and application of these components:
🔶 SuperTrend Polyfactor Oscillator:
- Basic Concept: The oscillator is a series of SuperTrend calculations with varying ATR lengths and multipliers. This approach provides a broader and more nuanced perspective of market trends.
- Calculation:
- For each iteration, `i`, the SuperTrend is calculated using:
- `ATR Length = indicatorLength * (startingFactor + i * incrementFactor)`.
- `Multiplier = dynamically adjusted based on market conditions`.
- The SuperTrend output for each iteration is compared with the indicator source (like hlc3), and the deviation is recorded.
SuperTrend Calculation:
- `Upper Band (UB) = hl2 + (ATR Length * Multiplier)`
- `Lower Band (LB) = hl2 - (ATR Length * Multiplier)`
- Where `hl2` is the average of high and low prices.
Deviation Calculation:
- `Deviation = indicatorSource - SuperTrend Value`
- This value is calculated for each SuperTrend setting in the oscillator series.
🔶 Indicator Source (`hlc3`):
- **Usage:** The strategy uses the average of high, low, and close prices, providing a balanced representation of market activity.
🔶 Adaptive ATR Lengths and Factors:
- Dynamic Adjustment: The strategy adjusts the ATR length and multiplier based on the `startingFactor` and `incrementFactor`. This adaptability is key in responding to changing market volatilities.
- Equation: ATR Length at each iteration `i` is given by `len = indicatorLength * (startingFactor + i * incrementFactor)`.
incrementFactor - 1
incrementFactor - 2
🔶 Normalization Methods:
Purpose: To standardize the deviations for comparability.
- Methods:
- 'Max-Min': Scales the deviation based on the range of values.
- 'Absolute Sum': Uses the sum of absolute deviations for normalization.
Normalization 'Absolute Sum'
- For 'Max-Min': `Normalized Deviation = (Deviation - Min(Deviations)) / (Max(Deviations) - Min(Deviations))`
- For 'Absolute Sum': `Normalized Deviation = Deviation / Sum(Absolute(Deviations))`
🔶 Trading Logic:
The strategy integrates the SuperTrend indicator, renowned for its effectiveness in identifying trend direction and reversals. The SuperTrend's incorporation enhances the strategy's ability to filter out false signals and confirm genuine market trends. * The SuperTrend Toolkit is made by @QuantiLuxe
- Long Entry Conditions: A buy signal is generated when the current trend, as indicated by the SuperTrend Polyfactor Oscillator, turns positive.
- Short Entry Conditions: A sell signal is triggered when the current trend turns negative.
- Entry and Exit Strategy: The strategy opens or closes positions based on these signals, aligning with the selected trade direction (long, short, or both).
█ Trade Direction
The strategy is versatile, allowing traders to choose their preferred trading direction: long, short, or both. This flexibility enables traders to tailor their strategies to their market outlook and risk appetite.
█ Usage
The FlexiSuperTrend strategy is suitable for various market conditions and can be adapted to different asset classes and time frames. Traders should set the strategy parameters according to their risk tolerance and trading goals. It's particularly useful for capturing long-term movements, ideal for swing traders, yet adaptable for short-term trading strategies.
█ Default Settings
1. Trading Direction: Choose from "Long", "Short", or "Both" to define the trade type.
2. Indicator Source (HLC3): Utilizes the HLC3 as the primary price reference.
3. Indicator Length (Default: 10): Influences the moving average calculation and trend sensitivity.
4. Starting Factor (0.618): Initiates the ATR length, influenced by Fibonacci ratios.
5. Increment Factor (0.382): Adjusts the ATR length incrementally for dynamic trend tracking.
6. Normalization Method: Options include "None", "Max-Min", and "Absolute Sum" for scaling deviations.
7. SuperTrend Settings: Varied ATR lengths and multipliers tailor the indicator's responsiveness.
8. Additional Settings: Features mesh style plotting and customizable colors for visual distinction.
The default settings provide a balanced approach, but users are encouraged to adjust them based on their individual trading style and market analysis.
SizeblockPrice change indicator in the form of diagonal rows.
The calculation is based on the percentage or tick deviation of the price movement (indicated in the "Deviation" parameter), which is displayed on the chart in the form of rows.
The row consists of the base middle line, upper and lower limits:
The middle line is the basis for the upper and lower limits of the current row.
The upper and lower limits are deviations from the base middle line of the current row.
The base middle line is equal to the upper or lower limits of the previous row (if the price changes rapidly in one time interval, then the base middle line of the current row is greater than the upper limit of the previous row or less than the lower limit of the previous row by an equal number of deviations depending on the direction of price movement). At the beginning of the calculation, the base middle line is equal to the initial value of the first row.
The "Quantity" parameter determines the deviation for the upper or lower limits depending on the direction of the price movement, and the "U-turn" parameter determines the deviation for changing the direction of the price movement.
The rule for constructing a new row:
The "Source" parameter accepts, depending on the choice, the price of high, low values or the closing price from the time interval of the chart.
When the price reaches the upper or lower limits of the row and goes beyond them, a new row is formed with the same parameters for deviation of the upper and lower limits from the base middle line, depending on the direction of price movement.
By adjusting certain deviations, you can clearly see the local trend and reversal points on the chart.
A useful tool for tracking price direction.
Thanks for your attention!
EMA-Deviation-Corrected T3 [Loxx]EMA-Deviation-Corrected T3 is a T3 moving average that uses EMA deviation correcting to produce signals. This comes via the beloved genius Mladen.
The origin of the correcting algorithm can be attributed to Dr. Alexander Uhl, who developed a method to filter the moving average and identify signals. Originally, this method utilized standard deviation as a measure to correct the average values.
However, the current indicator in question employs a modified version of the correcting method. Instead of using standard deviation for calculation, it uses EMA deviation, which stands for Exponential Moving Average deviation. The idea behind using EMA deviation is two-fold:
Efficiency: EMA deviation can be calculated faster than standard deviation, resulting in more efficient code execution.
Signal Reduction: Surprisingly, this modified "correcting" approach generates fewer signals compared to using standard deviation. This is because EMA deviation is more responsive to price changes, making the correcting process less sensitive to whipsaws or false signals.
What is T3?
The T3 moving average, short for "Tim Tillson's Triple Exponential Moving Average," is a technical indicator used in financial markets and technical analysis to smooth out price data over a specific period. It was developed by Tim Tillson, a software project manager at Hewlett-Packard, with expertise in Mathematics and Computer Science.
The T3 moving average is an enhancement of the traditional Exponential Moving Average (EMA) and aims to overcome some of its limitations. The primary goal of the T3 moving average is to provide a smoother representation of price trends while minimizing lag compared to other moving averages like Simple Moving Average (SMA), Weighted Moving Average (WMA), or EMA.
To compute the T3 moving average, it involves a triple smoothing process using exponential moving averages. Here's how it works:
Calculate the first exponential moving average (EMA1) of the price data over a specific period 'n.'
Calculate the second exponential moving average (EMA2) of EMA1 using the same period 'n.'
Calculate the third exponential moving average (EMA3) of EMA2 using the same period 'n.'
The formula for the T3 moving average is as follows:
T3 = 3 * (EMA1) - 3 * (EMA2) + (EMA3)
By applying this triple smoothing process, the T3 moving average is intended to offer reduced noise and improved responsiveness to price trends. It achieves this by incorporating multiple time frames of the exponential moving averages, resulting in a more accurate representation of the underlying price action.
Included
Bar coloring
Signals
Alerts
Loxx's Expanded Source Types
Monday_Weekly_Range/ErkOzi/Deviation Level/V1"Hello, first of all, I believe that the most important levels to look at are the weekly Fibonacci levels. I have planned an indicator that automatically calculates this. It models a range based on the weekly opening, high, and low prices, which is well-detailed and clear in my scans. I hope it will be beneficial for everyone.
***The logic of the Monday_Weekly_Range indicator is to analyze the weekly price movement based on the trading range formed on Mondays. Here are the detailed logic, calculation, strategy, and components of the indicator:
***Calculation of Monday Range:
The indicator calculates the highest (mondayHigh) and lowest (mondayLow) price levels formed on Mondays.
If the current bar corresponds to Monday, the values of the Monday range are updated. Otherwise, the values are assigned as "na" (undefined).
***Calculation of Monday Range Midpoint:
The midpoint of the Monday range (mondayMidRange) is calculated using the highest and lowest price levels of the Monday range.
***Fibonacci Levels:
// Calculate Fibonacci levels
fib272 = nextMondayHigh + 0.272 * (nextMondayHigh - nextMondayLow)
fib414 = nextMondayHigh + 0.414 * (nextMondayHigh - nextMondayLow)
fib500 = nextMondayHigh + 0.5 * (nextMondayHigh - nextMondayLow)
fib618 = nextMondayHigh + 0.618 * (nextMondayHigh - nextMondayLow)
fibNegative272 = nextMondayLow - 0.272 * (nextMondayHigh - nextMondayLow)
fibNegative414 = nextMondayLow - 0.414 * (nextMondayHigh - nextMondayLow)
fibNegative500 = nextMondayLow - 0.5 * (nextMondayHigh - nextMondayLow)
fibNegative618 = nextMondayLow - 0.618 * (nextMondayHigh - nextMondayLow)
fibNegative1 = nextMondayLow - 1 * (nextMondayHigh - nextMondayLow)
fib2 = nextMondayHigh + 1 * (nextMondayHigh - nextMondayLow)
***Fibonacci levels are calculated using the highest and lowest price levels of the Monday range.
Common Fibonacci ratios such as 0.272, 0.414, 0.50, and 0.618 represent deviation levels of the Monday range.
Additionally, the levels are completed with -1 and +1 to determine at which level the price is within the weekly swing.
***Visualization on the Chart:
The Monday range, midpoint, Fibonacci levels, and other components are displayed on the chart using appropriate shapes and colors.
The indicator provides a visual representation of the Monday range and Fibonacci levels using lines, circles, and other graphical elements.
***Strategy and Usage:
The Monday range represents the starting point of the weekly price movement. This range plays an important role in determining weekly support and resistance levels.
Fibonacci levels are used to identify potential reaction zones and trend reversals. These levels indicate where the price may encounter support or resistance.
You can use the indicator in conjunction with other technical analysis tools and indicators to conduct a more comprehensive analysis. For example, combining it with trendlines, moving averages, or oscillators can enhance the accuracy.
When making investment decisions, it is important to combine the information provided by the indicator with other analysis methods and use risk management strategies.
Thank you in advance for your likes, follows, and comments. If you have any questions, feel free to ask."
Average Variation Bands OscillatorSimilar to how a donchian% of channel helps to visualize trend and volatility, this tool helps identify those same characteristics, if the oscillator is generally above the 50 mark, it is considered to be trending upwards, and the reverse if it is generally bellow 50.
Strongest TrendlineUnleashing the Power of Trendlines with the "Strongest Trendline" Indicator.
Trendlines are an invaluable tool in technical analysis, providing traders with insights into price movements and market trends. The "Strongest Trendline" indicator offers a powerful approach to identifying robust trendlines based on various parameters and technical analysis metrics.
When using the "Strongest Trendline" indicator, it is recommended to utilize a logarithmic scale . This scale accurately represents percentage changes in price, allowing for a more comprehensive visualization of trends. Logarithmic scales highlight the proportional relationship between prices, ensuring that both large and small price movements are given due consideration.
One of the notable advantages of logarithmic scales is their ability to balance price movements on a chart. This prevents larger price changes from dominating the visual representation, providing a more balanced perspective on the overall trend. Logarithmic scales are particularly useful when analyzing assets with significant price fluctuations.
In some cases, traders may need to scroll back on the chart to view the trendlines generated by the "Strongest Trendline" indicator. By scrolling back, traders ensure they have a sufficient historical context to accurately assess the strength and reliability of the trendline. This comprehensive analysis allows for the identification of trendline patterns and correlations between historical price movements and current market conditions.
The "Strongest Trendline" indicator calculates trendlines based on historical data, requiring an adequate number of data points to identify the strongest trend. By scrolling back and considering historical patterns, traders can make more informed trading decisions and identify potential entry or exit points.
When using the "Strongest Trendline" indicator, a higher Pearson's R value signifies a stronger trendline. The closer the Pearson's R value is to 1, the more reliable and robust the trendline is considered to be.
In conclusion, the "Strongest Trendline" indicator offers traders a robust method for identifying trendlines with significant predictive power. By utilizing a logarithmic scale and considering historical data, traders can unleash the full potential of this indicator and gain valuable insights into price trends. Trendlines, when used in conjunction with other technical analysis tools, can help traders make more informed decisions in the dynamic world of financial markets.
Volume+This volume indicator uses a long WMA to establish an average volume and calculates the standard deviation based on that average. Each deviation level from 1 to 3 is also plotted with the bar color gradually increasing in intensity when more than one standard deviation is exceeded.
MTF VWAP & StDev BandsMulti Timeframe Volume Weighted Average Price with Standard Deviation Bands
I used the script "Koalafied VWAP D/W/M/Q/Y" by Koalafied_3 and made some changes, such as adding more standard deviation bands.
The script can display the daily, weekly, monthly, quarterly and yearly VWAP.
Standard deviation bands values can be changed (default values are 0.618, 1, 1.618, 2, 2.618, 3).
Also the previous standard deviation bands can be displayed.
[Sidders]Std. Deviation from Mean/MA (Z-score)This indicator visualizes in a straight forward way the distance price is away from the mean in absolute standard deviations (Z-score) over a certain lookback period (can be configured). Additionally I've included a moving average of the distance, the MA type can be configured in the settings.
Personally using this indicator for some of my algo mean reversion strategies. Price reaching the extreme treshold (can be configured in settings, standard is 3) could be seen as a point where price will revert to the mean.
I've included alerts for when price crosses into extreme areas, as well as alerts for when crosses back into 'normal' territory again. Both are also plotted on the indicator through background coloring/shapes.
Since I've learned so much from other developers I've decided to open source the code. Let me know if you have any ideas on how to improve, I'll see if I can implement them.
Enjoy!
Sequence Distribution Reporta basic tool to retrieve statistics of the distribution of price range sequences.
Loft Strategy V4This strategy is an advanced version of the Loft Strategy V1, I shared earlier. (Loft Strategy V1 consists of a kalman filter (by alexgrover ) and a "stop and reverse" line which is following and the kalman filter. If the price goes in the same direction as the position side, the "stop and reverse" line approaches the kalman filter as set on the "Approach Decrease Step" parameter.)
In addition to the previous version, it includes a martingale like deviation and multiple take-profit.
Here it is some parameters definitions of the strategy:
Kalman Filter: The higher this parameter, the faster and more aggressive the filter. Otherwise the filter goes very smoothly
Beginning Approach: First approximation as a percentage of stop-n-reverse line
Final Approach: Minimum approximation of stop-n-reverse line
Approach Decrease Step: If the price moves in the same direction as the strategy, the approach percentage is reduced by this parameter. Otherwise nothing do
Base Order Quantity: Initial capital of position
Max Safe Order Attempt: This parameter determines the maximum number of times the strategy will raise the bet after losing in a row.
Safe Order Deviation: if the last trade is loss, multiply the bet by this parameter (aka. martingale factor)
Profit Deviation: if last trade in loss, multiply the take-profit points
Max Order Quantity: Maximum capital allowed for a position
TP1, TP2, TP3 : Take profit spots in percentage
QT1, QT2, QT3: Amount of take-profit spots
Stop Loss: Maximum stop loss allowed for a trade
Long Entry, Short Entry: Only long side, only short side or both side
Safe Stop After TP2: If the price reaches the TP2 point, move the stop-loss point to the entry price.
Safe Stop After TP1: If the price reaches TP1, move the stop-loss point to the stop-n-reverse line.
Weighted Standard Deviation BandsLinearly weighted standard deviations over linearly weighted mean.
The rationale of the study can be deduced from my latest publications where I go deeper into explaining the benefits of linear weighting, but in short, I can remind that by using linear weighting we are able to increase the information gain by communicating the sequential nature of time series to the calculations via linear weighting.
Note, that multiplier parameters can take both negative and positive values resulting in ability to have, for example, 1st and 6th weighted standard deviations higher than the weighted mean.
Despite the modification of the classic standard deviation formula, I assume that mathematical qualities of standard deviation will hold due to the fact we can alternately weight the window itself, and then apply the classic standard deviation over the weighted window. In both cases, the results will be the same.
Aight that was too formal, but your short strangles should be happy
Here is it, for you
Anchored TWAP with StDev Bands [MrShadow]TWAP with:
- Anchoring: Custom, Day, Week, Month, Quarter, Year (custom anchoring can be selected by dragging a vertical line through the chart)
- Standard Devation Bands
- Auto-coloring depending on the trend
Ergodic Mean Deviation Indicator [CC]The Ergodic Mean Deviation Indicator was created by William Blau and this is a hidden gem that takes the difference between the current price and it's exponential moving average and then double smooths the result to create this indicator. This double smoothing of course creates a lag that allows it to give off a sustained buy signal during a bullish trend and vice versa. This is a very fun indicator to experiment with and surprised that no one on here gives William Blau much attention so I will go ahead and publish the rest of his scripts eventually. I have included strong buy and sell signals in addition to normal ones so strong signals are darker in color and normal signals are lighter in color. Buy when the line turns green and sell when it turns red.
Let me know if there are any other indicators or scripts you would like to see me publish!
Time-of-Day DeviationCreates a 'Time-of-Day' Deviation cone starting from the first bar of the session based upon data from previous days.
DailyDeviationLibrary "DailyDeviation"
Helps in determining the relative deviation from the open of the day compared to the high or low values.
hlcDeltaArrays(daysPrior, maxDeviation, spec, res) Retuns a set of arrays representing the daily deviation of price for a given number of days.
Parameters:
daysPrior : Number of days back to get the close from.
maxDeviation : Maximum deviation before a value is considered an outlier. A value of 0 will not filter results.
spec : session.regular (default), session.extended or other time spec.
res : The resolution (default = '1440').
Returns: Where OH = Open vs High, OL = Open vs Low, and OC = Open vs Close
fromOpen(daysPrior, maxDeviation, comparison, spec, res) Retuns a value representing the deviation from the open (to the high or low) of the current day given number of days to measure from.
Parameters:
daysPrior : Number of days back to get the close from.
maxDeviation : Maximum deviation before a value is considered an outlier. A value of 0 will not filter results.
comparison : The value use in comparison to the current open for the day.
spec : session.regular (default), session.extended or other time spec.
res : The resolution (default = '1440').
