Five-Day High-Low Level Alert pink line5 day average level strategy in which the level of pink line is average of previous 5 days, if the price is above the line it is said to be the price will rise and vise versa
Average
J Lines EMA + VWAPThe EMA + VWAP indicator combines the power of Exponential Moving Averages (EMA) with the Volume Weighted Average Price (VWAP) to help traders spot trends, identify potential entries/exits, and understand market momentum with ease. This dual-purpose tool is designed to give both beginner and experienced traders a clear view of price direction and volume influence, whether for day trading or swing trading.
Key Features:
Dynamic EMA Lines:
Six customizable moving averages (EMA by default) adapt to your selected timeframe. EMAs help track trend direction and strength, with various colors and opacity settings that visually separate them for clarity.
VWAP Tracking: A standalone VWAP line (blue) shows the average trading price adjusted for volume, making it ideal for pinpointing significant price levels where institutional interest often lies.
EMA Ribbons for Trend Confirmation: Soft-colored ribbons are placed between EMA pairs to make the trend strength visually apparent, with different color fills between lines. This makes it easy to gauge bullish or bearish conditions at a glance.
Flexible MA Options: Besides EMA, you can choose from SMA, WMA, HMA, and RMA, allowing you to adapt the indicator to various trading strategies.
This tool simplifies trend-following and volume-based analysis by giving you insight into both price momentum and market participation levels. EMAs adapt to volatility and changing market conditions, while the VWAP keeps you aware of critical price zones based on trading volume. Together, these help you stay on the right side of the market, avoid false breakouts, and make informed decisions on when to enter or exit trades.
Ideal for beginners due to its visual clarity and flexible enough for seasoned traders, EMA + VWAP is your go-to indicator for a structured approach to market trends.
DSL Trend Analysis [ChartPrime]The DSL Trend Analysis indicator utilizes Discontinued Signal Lines (DSL) deployed directly on price, combined with dynamic bands, to analyze the trend strength and momentum of price movements. By tracking the high and low price values and comparing them to the DSL bands, it provides a visual representation of trend momentum, highlighting both strong and weakening phases of market direction.
⯁ KEY FEATURES AND HOW TO USE
⯌ DSL-Based Trend Detection :
This indicator uses Discontinued Signal Lines (DSL) to evaluate price action. When the high stays above the upper DSL band, the line turns lime, indicating strong upward momentum. Similarly, when the low stays below the lower DSL band, the line turns orange, indicating strong downward momentum. Traders can use these visual signals to identify strong trends in either direction.
⯌ Bands for Trend Momentum :
The indicator plots dynamic bands around the DSL lines based on ATR (Average True Range). These bands provide a range within which price can fluctuate, helping to distinguish between strong and weakening trends. If the high remains within the upper band, the lime-colored line becomes transparent, showing weakening upward momentum. The same concept applies for the lower band, where the line turns orange with transparency, indicating weakening downward momentum.
If high and low stays between bands line has no color
to make sure indicator catches only strong momentum of price
⯌ Real-Time Band Price Labels :
The indicator places two labels on the chart, one at the upper DSL band and one at the lower DSL band, displaying the real-time price values of these bands. These labels help traders track the current price relative to the key bands, which are essential in determining potential breakout or reversal zones.
⯌ Visual Confirmation of Momentum Shifts :
By monitoring the relationship between the high and low values of the price relative to the DSL bands, this indicator provides a reliable way to confirm whether the trend is gaining or losing strength. This allows traders to act accordingly, whether it's to enter or exit positions based on trend strength or weakness.
⯁ USER INPUTS
Length : Defines the period used to calculate the DSL lines, influencing the sensitivity of the trend detection.
Offset : Adjusts the offset applied to the upper and lower DSL bands, affecting how the thresholds for strong or weak momentum are set.
Width (ATR Multiplier) : Determines the width of the DSL bands based on an ATR multiplier, providing a dynamic range around the price for momentum analysis.
⯁ CONCLUSION
The DSL Trend Analysis indicator is a powerful tool for assessing price momentum and trend strength. By combining Discontinued Signal Lines with dynamically calculated bands, traders can easily spot key moments when momentum shifts from strong to weak or vice versa. The color-coded lines and real-time price labels provide valuable insights for trading decisions in both trending and ranging markets.
MENTFX AVERAGES MULTI TIMEFRAMEThe MENTFX AVERAGES MULTIME TIMEFRAME indicator is designed to provide traders with the ability to visualize multiple moving averages (MAs) from higher timeframes on their current chart, regardless of the chart's timeframe. It combines the power of exponential moving averages (EMAs) to help traders identify trends, spot potential reversal points, and make more informed trading decisions.
Key Features:
Multi-Timeframe Moving Averages: This indicator plots moving averages from daily timeframes directly on your chart, helping you keep track of higher timeframe trends while trading in any timeframe.
Customizable Moving Averages: You can adjust the length and visibility of up to three EMAs (default settings are 5, 10, and 20-period EMAs) to suit your trading style.
Overlay on Price: The indicator is designed to be overlaid on your price chart, seamlessly integrating with your existing analysis.
Simple but Effective: By offering a clear visual guide to where price is trading relative to important higher timeframe levels, this indicator helps traders avoid trading against major trends.
Why It’s Unique:
Validation Timeframe Flexibility: Unlike traditional moving average indicators that only work within the same chart's timeframe, the MENTFX AVERAGES M indicator allows you to pull moving averages from higher timeframes (default: Daily) and overlay them on any chart you're currently viewing, whether it's intraday (minutes) or even weekly. This cross-timeframe visibility is critical in determining the true market trend, adding context to your trades.
Customizability: Although the default settings focus on daily EMAs (5, 10, and 20 periods), traders can modify the parameters, including the type of moving average (Simple, Weighted, etc.), making it adaptable for any strategy. Whether you want shorter-term or longer-term averages, this indicator covers your needs.
Trend Confirmation Tool: The use of multiple EMAs helps traders confirm trend direction and potential price breakouts or reversals. For example, when the shorter-term 5 EMA crosses above the 20 EMA, it can signal a potential bullish trend, while the opposite could indicate bearish pressure.
How This Indicator Helps:
Identify Key Support and Resistance Levels: Higher timeframe moving averages often act as dynamic support and resistance. This indicator helps you stay aware of those critical levels, even when trading lower timeframes.
Trend Identification: Knowing where the market is relative to the 5, 10, and 20 EMAs from a higher timeframe gives you a clearer picture of whether you're trading with or against the prevailing trend.
Improved Decision Making: By aligning your trades with the direction of higher timeframe trends, you can increase your confidence in trade entries and exits, avoiding low-probability setups.
Multi-Market Use: This indicator works well across various asset classes—stocks, forex, crypto, and commodities—making it versatile for any trader.
How to Use:
Intraday Trading: Use the daily EMAs as a guide to see if intraday price movements align with longer-term trends.
Swing Trading: Plot daily EMAs to track the strength of a larger trend, using pullbacks to the moving averages as potential entry points.
Trend Trading: Monitor crossovers between the moving averages to signal potential changes in trend direction.
Default Settings:
5 EMA (Daily) – Blue Line
10 EMA (Daily) – Black Line
20 EMA (Daily) – Red Line
These lines will plot on your chart with a subtle opacity (33%) to ensure they don’t obstruct price action, while still providing crucial visual guidance on market trends.
This indicator is perfect for traders who want to blend technical analysis with multi-timeframe insights, helping you stay in sync with broader market movements while executing trades on any timeframe.
The Vet [TFO]In collaboration with @mickey1984 , "The Vet" was created to showcase various statistical measures of price.
The first core measurement utilizes the Defining Range (DR) concept on a weekly basis. For example, we might track the session from 09:30-10:30 on Mondays to get the DR high, DR low, IDR high, and IDR low. The DR high and low are the highest high and lowest low of the session, respectively, whereas the IDR high and low would be the highest candle body level (open or close) and lowest candle body level, respectively, during this window of time.
From this data, we use the IDR range (from IDR high to IDR low) to extrapolate several, custom projections of this range from its high and low so that we can collect data on how often these levels are hit, from the close of one DR session to the open of the next one.
This information is displayed in the Range Projection Table with a few main columns of information:
- The leftmost column indicates each level that is projected from the IDR range, where (+) indicates a projection above the range high, and (-) indicates a projection below the range low
- The "First Touch" column indicates how often price has reached these levels in the past at any point until the next weekly DR session
- The "Other Side Touch" column indicates how often price has reached a given level, then reversed to hit the opposing level of the same magnitude. For example, the above chart shows that if price hit the +1 projection, ~33% of instances also hit the -1 projection before the next weekly DR session. For this reason, the probabilities will be the same for projection levels of the same but opposite magnitude (+1 would be the same as -1, +3 would be the same as -3, etc.)
- The "Next Level Touch" column provides insight into how often price reaches the next greatest projection level. For example, in the above chart, the red box in the projection table is highlighting that once price hits the -2 projection, ~86% of instances reached the -3 projection before the next weekly DR session
- The last columns, "Within ADR" and "Within AWR" show if any of the projection levels are within the current Average Daily Range, or Average Weekly Range, respectively, which can both be enabled from the Average Range section
The next section, Distributions, primarily measures and displays the average price movements from specified intraday time windows. The option to Show Distribution Boxes will overlay a box showing each respective session's average range, while adjusting itself to encapsulate the price action of that session until the average range is met/exceeded. Users can choose to display the range average by Day of Week, or the Total average from all days. Values for average ranges can either be shown as point or percent values. We can also show a table to display this information about price's average ranges for each given session, and show labels displaying the current range vs its average.
The final section, Average Range, simply offers the ability to plot the Average Daily Range (ADR) and Average Weekly Range (AWR) of a specified length. An ADR of 10 for example would take the average of the last 10 days, from high to low, while an AWR of 10 would take the average of the last 10 weeks (if the current chart provides enough data to support this). Similarly, we can also show the Average Range Table to indicate what these ADR/AWR values are, what our current range is and how it compares to those values, as well as some simple statistics on how often these levels are hit. As an example, "Hit +/- ADR: 40%/35%" in this table would indicate that price has hit the upper ADR limit 40% of the time, and the lower limit 35% of the time, for the amount of data available on the current chart.
Average Down CalculatorAverage Down Calculator is an indicator for investors looking to manage their portfolio. It aids in calculating the average share price, providing insights into optimizing investment strategies. Averaging down is a strategy investors use when the price of a security they own goes down. Instead of selling at a loss, they buy more shares at the lower price to reduce the average cost per share.
There are situations where a stock's price moves contrary to your expectations. The market moves downward. Despite this, your faith in the stock persists. This indicator allowing you to strategically add more stocks to lower the average price. But You must remember, it’s not without risks, as it involves investing more money in a losing position.
This Indicator allowing you to quickly understand your new position and make informed decisions. It’s designed for easy use, regardless of your experience level with investing.
Steps to use it:
1.put buy fee from your securitas
2.next put the price of the emiten from your portofolio
3.and how many lot you have
4.next is the the taget of percentage you want it become.
5 the last you can choose, the price that you want to buy for average.
this calculator is designed to help you navigate your investment better, choose it wisely.Be aware of the risks of investing more in a declining asset and consider diversification to manage potential losses.
Multi Deviation Scaled Moving Average [ChartPrime]Multi Deviation Scaled Moving Average ChartPrime
⯁ OVERVIEW
The Multi Deviation Scaled Moving Average is an analysis tool that combines multiple Deviation Scaled Moving Averages (DSMAs) to provide a comprehensive view of market trends. The DSMA, originally created by John Ehlers, is a sophisticated moving average that adapts to market volatility. This indicator offers a unique approach to trend analysis by utilizing a series of DSMAs with different periods and presenting the results through a color-coded line and a visual histogram.
◆ KEY FEATURES
Multiple DSMA Calculation: Computes eight DSMAs with incrementally increasing periods for multi-faceted trend analysis.
Trend Strength Visualization: Provides a color-coded moving average line indicating trend strength and direction.
Trend Percentage Histogram: Displays a visual representation of bullish vs bearish trend percentages.
Signal Generation: Identifies potential entry and exit points based on trend strength crossovers.
Customizable Parameters: Allows users to adjust the base period and sensitivity of the indicator.
◆ USAGE
Trend Direction and Strength: The color and intensity of the main indicator line provide quick insights into the current trend.
Trend Percentage Histogram: The histogram value can give you an idea of the market trend ahead
Entry and Exit Signals: Diamond-shaped markers indicate potential trade entry and exit points based on trend strength shifts.
Trend Bias Assessment: The trend percentage histogram offers a visual representation of the overall market bias.
Multi-Timeframe Analysis: By applying the indicator to different timeframes, traders can gain insights into trends across various time horizons.
⯁ USER INPUTS
Period: Sets the initial calculation period for the DSMAs (default: 30).
Sensitivity: Adjusts the step size between DSMA periods. Lower values increase sensitivity (default: 60, range: 0-100).
Source: Uses HLC3 (High, Low, Close average) as the default price source.
The Multi Deviation Scaled Moving Average indicator offers traders a sophisticated tool for trend analysis and signal generation. By combining multiple DSMAs and providing clear visual cues, it enables traders to make more informed decisions about market direction and potential entry or exit points. The indicator's customizable parameters allow for fine-tuning to suit various trading styles and market conditions.
Biquad Low Pass FilterThis indicator utilizes a biquad low pass filter to smooth out price data, helping traders identify trends and reduce noise in their analysis.
The Length parameter acts as the length of the moving average, determining the smoothness and responsiveness of the filter. Adjusting this parameter changes how quickly the filter reacts to price changes.
The Q Factor controls the sharpness of the filter. A higher Q value results in a narrower frequency band, enhancing the precision of the filter. However, be cautious when setting the Q factor too high, as it can induce resonance, amplifying certain frequencies and potentially making the filter less effective by introducing noise.
Key Features of Biquad Filters
Biquad filters are a type of digital filter that provides a combination of low-pass, high-pass, band-pass, and notch filtering capabilities. In this implementation, the biquad filter is configured as a low pass filter, which allows low-frequency signals to pass while attenuating higher-frequency noise. This is particularly useful in trading to smooth out price data, making it easier to spot underlying trends and patterns.
Biquad filters are known for their smooth response and minimal phase distortion, making them ideal for technical analysis. The customizable length and Q factor allow for flexible adaptation to different trading strategies and market conditions. Designed for real-time charting, the biquad filter operates efficiently without significant lag, ensuring timely analysis.
By incorporating this biquad low pass filter into your trading toolkit, you can enhance your chart analysis with clearer insights into price movements, leading to more informed trading decisions.
ATR Gerchik LightAverage True Range ( ATR ) is a technical analysis indicator that measures volatility in the market. ATR is a moving average of the true range over a period of time.
ATR calculation procedure:
1. Determine the true maximum - this is the highest of the current maximum and yesterday's closing price of the day.
2. Determine the true minimum - this is the smallest of the current minimum and yesterday's closing price.
3. Determine the true range - this is the distance between the true maximum and minimum.
4. We exclude extremely large candles (> x2 ATR) and extremely small ones (< 0.5 ATR) from the obtained true ranges.
5. We calculate the average for the selected period based on the remaining range.
6. We calculate the percentage of the current True Range relative to the average ATR value for the previous period.
Description:
If you analyze it yourself, you will see that 75-80% of the time, the instrument moves only 1 ATR per day. You must understand that if an instrument has, for example, moved 80% of its daily range, it is not advisable to purchase it. This is comparable to a car's fuel tank: if the tank is almost empty, the car won't go far. Most indicators that calculate ATR include anomalous candles, which give unreliable results and lead to incorrect decisions. Because of this, many traders prefer to calculate ATR on their own.
However, the Gerchik ATR indicator accounts for anomalous candles and filters out extremely large candles (> 2x ATR) and extremely small ones (< 0.5x ATR). Additionally, this indicator immediately shows the consumed “fuel” of the instrument as a percentage, so you don't have to calculate the distance traveled yourself. This allows you to make quick, informed decisions. If we see that the tank is almost empty, it is logical not to get into that car today. When building any strategy, you must rely on the average movement.
Key Features:
Anomalous Candle Filtering: Excludes extremely large and small candles to provide more reliable ATR values.
Consumed Fuel Indicator: Shows the percentage of the ATR consumed, helping traders quickly assess the remaining potential movement.
Daily Timeframe Focus: Designed specifically for use on daily charts for accurate long-term analysis.
Practical Applications:
Entry and Exit Points: Use the ATR to determine optimal entry and exit points by assessing market volatility and potential price movement.
Stop-Loss Placement: Calculate stop-loss levels based on ATR to ensure they are placed at appropriate distances, accounting for current market volatility.
Trend Confirmation: Use the percentage of ATR consumed to confirm the strength of a trend and decide whether to enter or exit trades.
Examples of Use:
Trend Following: During strong trends, ATR helps identify periods of increased volatility, signaling potential breakouts or reversals.
Range Trading: In ranging markets, ATR can highlight periods of low volatility, indicating consolidation and potential breakout zones.
Note: The indicator is displayed and works only on the daily timeframe!
The indicator was created according to the instructions, description of the functionality, and strategy of Mr. Gerchik. Thank you so much, Chief!
________________________
Average True Range ( ATR , средний истинный диапазон) – это индикатор технического анализа, который измеряет волатильность на рынке. ATR представляет собой скользящее среднее истинного диапазона за определенный период времени.
Порядок расчета ATR:
1. Определяем истинный максимум – это наивысшее из текущего максимума и вчерашней цены закрытия дня.
2. Определяем истинный минимум – это наименьшее из текущего минимума и вчерашней цены закрытия.
3. Определяем истинный диапазон – это расстояние между истинным максимумом и минимумом.
4. Исключаем из полученных истинных диапазонов экстремально большие свечи (> x2 ATR) и экстремально маленькие (< 0.5 ATR).
5. Рассчитываем среднее за выбранный период исходя из оставшегося диапазона.
6 . Рассчитываем процент текущего истинного диапазона (True Range) относительно среднего значения ATR за предыдущий период.
Описание:
Если вы сами проанализируете, то увидите, что 75-80% времени инструмент ходит только 1 ATR. И вы должны понимать, что если инструмент внутри дня прошел, к примеру, 80% своего движения, то этот инструмент больше нельзя покупать. Это можно сравнить с баком машины: если бак почти пустой, машина далеко не уедет. Большинство индикаторов, которые рассчитывают ATR, производят расчет с паранормальными свечами. Это дает недостоверный результат и приводит к неверным решениям. Многие трейдеры из-за этого не используют готовые индикаторы и предпочитают считать ATR самостоятельно. Но индикатор ATR Gerchik учитывает паранормальные свечи и фильтрует экстремально большие свечи (> x2 ATR) и экстремально маленькие (< 0.5 ATR). Также этот индикатор сразу показывает израсходованный "бензин" инструмента в процентах. И вам не надо самостоятельно высчитывать пройденный путь. Вы можете быстро принимать правильные решения. Если мы видим, что бак почти пустой, логично не садиться в эту машину сегодня. Когда вы строите какую-то стратегию, вы должны обязательно полагаться на среднестатистическое движение.
Существует много стратегий, завязанных на ATR, которые учитывают волатильность инструмента, запас хода, точки разворота, места выставления стоп-лоссов (SL) и тейк-профитов (TP) и другие факторы. Я не буду останавливаться на них, так как каждый может найти описание этих стратегий и использовать их на свой выбор.
Индикатор отображается и работает только на дневном таймфрейме!
Индикатор создан по наставлениям, описанию функционала и стратегии господина Герчика. Огромное спасибо, Шеф!
Han Algo - Moving average strategyHan Algo Indicator Strategy Description
Overview:
The Han Algo Indicator is designed to identify trend directions and signal potential buy and sell opportunities based on moving average crossovers. It aims to provide clear signals while filtering out noise and minimizing false signals.
Indicators Used:
Moving Averages:
200 SMA (Simple Moving Average): Used as a long-term trend indicator.
100 SMA: Provides a medium-term perspective on price movements.
50 SMA: Offers insights into shorter-term trends.
20 SMA: Provides a very short-term perspective on recent price actions.
Trend Identification:
The indicator identifies the trend based on the relationship between the closing price (close) and the 200 SMA (ma_long):
Uptrend: When the closing price is above the 200 SMA.
Downtrend: When the closing price is below the 200 SMA.
Sideways: When the closing price is equal to the 200 SMA.
Buy and Sell Signals:
Buy Signal: Generated when transitioning from a downtrend to an uptrend (buy_condition):
Displayed as a green "BUY" label above the price bar.
Sell Signal: Generated when transitioning from an uptrend to a downtrend (sell_condition):
Displayed as a red "SELL" label below the price bar.
Signal Filtering:
Signals are filtered to prevent consecutive signals occurring too closely (min_distance_bars parameter):
Ensures that only significant trend reversals are captured, minimizing false signals.
Visualization:
Background Color:
Changes to green for uptrend and red for downtrend (bgcolor function):
Provides visual cues for current market sentiment.
Usage:
Traders can customize the indicator's parameters (long_term_length, medium_term_length, short_term_length, very_short_term_length, min_distance_bars) to align with their trading preferences and timeframes.
The Han Algo Indicator helps traders make informed decisions by highlighting potential trend reversals and aligning with market trends identified through moving average analysis.
Disclaimer:
This indicator is intended for educational purposes and as a visual aid to support trading decisions. It should be used in conjunction with other technical analysis tools and risk management strategies.
Average Session Range [QuantVue]The Average Session Range or ASR is a tool designed to find the average range of a user defined session over a user defined lookback period.
Not only is this indicator is useful for understanding volatility and price movement tendencies within sessions, but it also plots dynamic support and resistance levels based on the ASR.
The average session range is calculated over a specific period (default 14 sessions) by averaging the range (high - low) for each session.
Knowing what the ASR is allows the user to determine if current price action is normal or abnormal.
When a new session begins, potential support and resistance levels are calculated by breaking the ASR into quartiles which are then added and subtracted from the sessions opening price.
The indicator also shows an ASR label so traders can know what the ASR is in terms of dollars.
Session Time Configuration:
The indicator allows users to define the session time, with default timing set from 13:00 to 22:00.
ASR Calculation:
The ASR is calculated over a specified period (default 14 sessions) by averaging the range (high - low) of each session.
Various levels based on the ASR are computed: 0.25 ASR, 0.5 ASR, 0.75 ASR, 1 ASR, 1.25 ASR, 1.5 ASR, 1.75 ASR, and 2 ASR.
Visual Representation:
The indicator plots lines on the chart representing different ASR levels.
Customize the visibility, color, width, and style (Solid, Dashed, Dotted) of these lines for better visualization.
Labels for these lines can also be displayed, with customizable positions and text properties.
Give this indicator a BOOST and COMMENT your thoughts!
We hope you enjoy.
Cheers!
Fourier Adjusted Average True Range [BackQuant]Fourier Adjusted Average True Range
1. Conceptual Foundation and Innovation
The FA-ATR leverages the principles of Fourier analysis to dissect market prices into their constituent cyclical components. By applying Fourier Transform to the price data, the FA-ATR captures the dominant cycles and trends which are often obscured in noisy market data. This integration allows the FA-ATR to adapt its readings based on underlying market dynamics, offering a refined view of volatility that is sensitive to both market direction and momentum.
2. Technical Composition and Calculation
The core of the FA-ATR involves calculating the traditional ATR, which measures market volatility by decomposing the entire range of price movements. The FA-ATR extends this by incorporating a Fourier Transform of price data to assess cyclical patterns over a user-defined period 'N'. This process synthesizes both the magnitude of price changes and their rhythmic occurrences, resulting in a more comprehensive volatility indicator.
Fourier Transform Application: The Fourier series is calculated using price data to identify the fundamental frequency of market movements. This frequency helps in adjusting the ATR to reflect more accurately the current market conditions.
Dynamic Adjustment: The ATR is then adjusted by the magnitude of the dominant cycle from the Fourier analysis, enhancing or reducing the ATR value based on the intensity and phase of market cycles.
3. Features and User Inputs
Customizability: Traders can modify the Fourier period, ATR period, and the multiplication factor to suit different trading styles and market environments.
Visualization : The FA-ATR can be plotted directly on the chart, providing a visual representation of volatility. Additionally, the option to paint candles according to the trend direction enhances the usability and interpretative ease of the indicator.
Confluence with Moving Averages: Optionally, a moving average of the FA-ATR can be displayed, serving as a confluence factor for confirming trends or potential reversals.
4. Practical Applications
The FA-ATR is particularly useful in markets characterized by periodic fluctuations or those that exhibit strong cyclical trends. Traders can utilize this indicator to:
Adjust Stop-Loss Orders: More accurately set stop-loss orders based on a volatility measure that accounts for cyclical market changes.
Trend Confirmation: Use the FA-ATR to confirm trend strength and sustainability, helping to avoid false signals often encountered in volatile markets.
Strategic Entry and Exit: The indicator's responsiveness to changing market dynamics makes it an excellent tool for planning entries and exits in a trend-following or a breakout trading strategy.
5. Advantages and Strategic Value
By integrating Fourier analysis, the FA-ATR provides a volatility measure that is both adaptive and anticipatory, giving traders a forward-looking tool that adjusts to changes before they become apparent through traditional indicators. This anticipatory feature makes it an invaluable asset for traders looking to gain an edge in fast-paced and rapidly changing market conditions.
6. Summary and Usage Tips
The Fourier Adjusted Average True Range is a cutting-edge development in technical analysis, offering traders an enhanced tool for assessing market volatility with increased accuracy and responsiveness. Its ability to adapt to the market's cyclical nature makes it particularly useful for those trading in highly volatile or cyclically influenced markets.
Traders are encouraged to integrate the FA-ATR into their trading systems as a supplementary tool to improve risk management and decision-making accuracy, thereby potentially increasing the effectiveness of their trading strategies.
INDEX:BTCUSD
INDEX:ETHUSD
BINANCE:SOLUSD
FVG Positioning Average [LuxAlgo]The FVG Positioning Average indicator aims to uncover potential price levels of interest by averaging together recent Fair Value Gap (FVG) initiation levels.
This indicator is grounded in the theory that significant buying or selling activity is the primary catalyst for creating FVGs.
By averaging together the prices where each FVG initiated, we may potentially reveal where major participants are positioned.
🔶 USAGE
By analyzing the average price of bullish or bearish FVGs, users can identify potential support or resistance areas where the larger participants may re-enter or defend their positions.
These areas could be used to adjust entries and exits or assist with risk management such as take-profit or stop-loss levels.
The indicator displays 2 lines, the Bull Average and the Bear Average.
The Bull Average is only displayed when the price holds above the bull Average.
The Bear Average is only displayed when the price holds below the bear average.
When only one average is displayed alone, this level is seen as support or resistance, it is anticipated that this level would be defended for the current trend to stay valid.
When both averages are displayed simultaneously, it can be interpreted as one side attempting to take over the trend.
The movements and reactions during these attempts can be analyzed to provide helpful information about where the price might be headed.
Possible outcomes:
Trend Confirmation/Re-Entry (From Weak Attempts)
Trend Reversal (Creating Support or Resistance)
Consolidation (Oscillating between/around Bull & Bear Averages)
🔶 DETAILS
🔹 Lookback Types
This indicator includes 2 lookback types:
Bar Count: Uses Bars to determine what data to include. This type can be utilized for averages that are more locally relevant to the current chart data.
FVG Count: Uses a specific # of FVGs for calculations. This type can be utilized for a continuous & consistent view, typically relevant with longer term analysis.
Note: When using bar lookback, if no data is in range, no lines will be displayed.
Below is an example of the 'FVG Count' Display.
🔹 Initiation Levels
Initiation Levels are the specific price points where each FVG starts, these are the last points the price was traded at before creating the gap.
Bull Initiation Level: Lowest Point (Bottom) of FVG
Bear Initiation Level: Highest Point (Top) of FVG
🔹 FVG Display
Each FVG being used for the current calculation of averages is displayed on the chart for reference.
Note: If you prefer to not display the FVGs, they can be toggled off in the settings, uncheck "Show FVGs on Chart".
🔶 Settings
FVG Lookback: As mentioned above in the 'Lookback Types', this sets the number of FVGs or Bars to use for consideration.
Lookback Type: As also mentioned above in 'Lookback Types', this determines the method of lookback to be used.
ATR Multiplier: The FVGs are required to have a Greater Width than (ATR * Multiplier) in order to be used for calculations. This allows you to focus on the data being considered if needed.
Trend AngleThe "Trend Angle" indicator serves as a tool for traders to decipher market trends through a methodical lens. It quantifies the inclination of price movements within a specified timeframe, making it easy to understand current trend dynamics.
Conceptual Foundation:
Angle Measurement: The essence of the "Trend Angle" indicator is its ability to compute the angle between the price trajectory over a defined period and the horizontal axis. This is achieved through the calculation of the arctangent of the percentage price change, offering a straightforward measure of market directionality.
Smoothing Mechanisms: The indicator incorporates options for "Moving Average" and "Linear Regression" as smoothing mechanisms. This adaptability allows for refined trend analysis, catering to diverse market conditions and individual preferences.
Functional Versatility:
Source Adaptability: The indicator affords the flexibility to select the desired price source, enabling users to tailor the angle calculation to their analytical framework and other indicators.
Detrending Capability: With the detrending feature, the indicator allows for the subtraction of the smoothing line from the calculated angle, highlighting deviations from the main trend. This is particularly useful for identifying potential trend reversals or significant market shifts.
Customizable Period: The 'Length' parameter empowers traders to define the observation window for both the trend angle calculation and its smoothing, accommodating various trading horizons.
Visual Intuition: The optional colorization enhances interpretability, with the indicator's color shifting based on its relation to the smoothing line, thereby providing an immediate visual cue regarding the trend's direction.
Interpretative Results:
Market Flatness: An angle proximate to 0 suggests a flat market condition, indicating a lack of significant directional movement. This insight can be pivotal for traders in assessing market stagnation.
Trending Market: Conversely, a relatively high angle denotes a trending market, signifying strong directional momentum. This distinction is crucial for traders aiming to capitalize on trend-driven opportunities.
Analytical Nuance vs. Simplicity:
While the "Trend Angle" indicator is underpinned by mathematical principles, its utility lies in its simplicity and interpretative clarity. However, it is imperative to acknowledge that this tool should be employed as part of a comprehensive trading strategy , complemented by other analytical instruments for a holistic market analysis.
In essence, the "Trend Angle" indicator exemplifies the harmonization of simplicity and analytical rigor. Its design respects the complexity of market behaviors while offering straightforward, actionable insights, making it a valuable component in the arsenal of both seasoned and novice traders alike.
PhiSmoother Moving Average Ribbon [ChartPrime]DSP FILTRATION PRIMER:
DSP (Digital Signal Processing) filtration plays a critical role with financial indication analysis, involving the application of digital filters to extract actionable insights from data. Its primary trading purpose is to distinguish and isolate relevant signals separate from market noise, allowing traders to enhance focus on underlying trends and patterns. By smoothing out price data, DSP filters aid with trend detection, facilitating the formulation of more effective trading techniques.
Additionally, DSP filtration can play an impactful role with detecting support and resistance levels within financial movements. By filtering out noise and emphasizing significant price movements, identifying key levels for entry and exit points become more apparent. Furthermore, DSP methods are instrumental in measuring market volatility, enabling traders to assess volatility levels with improved accuracy.
In summary, DSP filtration techniques are versatile tools for traders and analysts, enhancing decision-making processes in financial markets. By mitigating noise and highlighting relevant signals, DSP filtration improves the overall quality of trading analysis, ultimately leading to better conclusions for market participants.
APPLYING FIR FILTERS:
FIR (Finite Impulse Response) filters are indispensable tools in the realm of financial analysis, particularly for trend identification and characterization within market data. These filters effectively smooth out price fluctuations and noise, enabling traders to discern underlying trends with greater fidelity. By applying FIR filters to price data, robust trading strategies can be developed with grounded trend-following principles, enhancing their ability to capitalize on market movements.
Moreover, FIR filter applications extend into wide-ranging utility within various fields, one being vital for informed decision-making in analysis. These filters help identify critical price levels where assets may tend to stall or reverse direction, providing traders with valuable insights to aid with identification of optimal entry and exit points within their indicator arsenal. FIRs are undoubtedly a cornerstone to modern trading innovation.
Additionally, FIR filters aid in volatility measurement and analysis, allowing traders to gauge market volatility accurately and adjust their risk management approaches accordingly. By incorporating FIR filters into their analytical arsenal, traders can improve the quality of their decision-making processes and achieve better trading outcomes when contending with highly dynamic market conditions.
INTRODUCTORY DEBUT:
ChartPrime's " PhiSmoother Moving Average Ribbon " indicator aims to mark a significant advancement in technical analysis methodology by removing unwanted fluctuations and disturbances while minimizing phase disturbance and lag. This indicator introduces PhiSmoother, a powerful FIR filter in it's own right comparable to Ehlers' SuperSmoother.
PhiSmoother leverages a custom tailored FIR filter to smooth out price fluctuations by mitigating aliasing noise problematic to identification of underlying trends with accuracy. With adjustable parameters such as phase control, traders can fine-tune the indicator to suit their specific analytical needs, providing a flexible and customizable solution.
Mathemagically, PhiSmoother incorporates various color coding preferences, enabling traders to visualize trends more effectively on a volatile landscape. Whether utilizing progression, chameleon, or binary color schemes, you can more fluidly interpret market dynamics and make informed visual decisions regarding entry and exit points based on color-coded plotting.
The indicator's alert system further enhances its utility by providing notifications of specifically chosen filter crossings. Traders can customize alert modes and messages while ensuring they stay informed about potential opportunities aligned with their trading style.
Overall, the "PhiSmoother Moving Average Ribbon" visually stands out as a revolutionary mechanism for technical analysis, offering traders a comprehensive solution for trend identification, visualization, and alerting within financial markets to achieve advantageous outcomes.
NOTEWORTHY SETTINGS FEATURES:
Price Source Selection - The indicator offers flexibility in choosing the price source for analysis. Traders can select from multiple options.
Phase Control Parameter - One of the notable standout features of this indicator is the phase control parameter. Traders can fine-tune the phase or lag of the indicator to adapt it to different market conditions or timeframes. This feature enables optimization of the indicator's responsiveness to price movements and align it with their specific trading tactics.
Coloring Preferences - Another magical setting is the coloring features, one being "Chameleon Color Magic". Traders can customize the color scheme of the indicator based on their visual preferences or to improve interpretation. The indicator offers options such as progression, chameleon, or binary color schemes, all having versatility to dynamically visualize market trends and patterns. Two colors may be specifically chosen to reduce overlay indicator interference while also contrasting for your visual acuity.
Alert Controls - The indicator provides diverse alert controls to manage alerts for specific market events, depending on their trading preferences.
Alertable Crossings: Receive an alert based on selectable predefined crossovers between moving average neighbors
Customizable Alert Messages: Traders can personalize alert messages with preferred information details
Alert Frequency Control: The frequency of alerts is adjustable for maximum control of timely notifications
EMA + Lower Timeframe EMA (correct display in Replay Mode)This indicator shows
one EMA for the current timeframe
one EMA for a lower timeframe
Unlike the built-in Tradingview EMA indicator, this indicator shows the correct values for the lower timeframe EMA during Replay Mode.
ADR % RangesThis indicator is designed to visually represent percentage lines from the open of the day. The % amount is determined by X amount of the last days to create an average...or Average Daily Range (ADR).
1. ADR Percentage Lines: The core function of the script is to apply lines to the chart that represent specific percentage changes from the daily open. It first calculates the average over X amount of days and then displays two lines that are 1/3rd of that average. One line goes above the other line goes below. The other two lines are the full "range" of the average. These lines can act as boundaries or targets to know how an asset has moved recently. *Past performance is not indicative of current or future results.
The calculation for ADR is:
Step 1. Calculate Today's Range = DailyHigh - DailyLow
Step 2. Store this average after the day has completed
Step 3. Sum all day's ranges
Step 4. Divide by total number of days
Step 5. Draw on chart
2. Customizable Inputs: Users have the flexibility to customize the script through various inputs. This includes the option to display lines only for the current trading day (`todayonly`), and to select which lines are displayed. The user can also opt to show a table the displays the total range of previous days and the average range of those previous days.
3. No Secondary Timeframe: The ADR is computed based on whatever timeframe the chart is and does not reference secondary periods. Therefore the script cannot be used on charts greater than daily.
This script is can be used by all traders for any market. The trader might have to adjust the "X" number of days back to compute a historical average. Maybe they only want to know the average over the past week (5 days) or maybe the past month (20 days).
[AIO] Multi Collection Moving Averages 140 MA TypesAll In One Multi Collection Moving Averages.
Since signing up 2 years ago, I have been collecting various Сollections.
I decided to get it into a decent shape and make it one of the biggest collections on TV, and maybe the entire internet.
And now I'm sharing my collection with you.
140 Different Types of Moving Averages are waiting for you.
Specifically :
"
AARMA | Adaptive Autonomous Recursive Moving Average
ADMA | Adjusted Moving Average
ADXMA | Average Directional Moving Average
ADXVMA | Average Directional Volatility Moving Average
AHMA | Ahrens Moving Average
ALF | Ehler Adaptive Laguerre Filter
ALMA | Arnaud Legoux Moving Average
ALSMA | Adaptive Least Squares
ALXMA | Alexander Moving Average
AMA | Adaptive Moving Average
ARI | Unknown
ARSI | Adaptive RSI Moving Average
AUF | Auto Filter
AUTL | Auto-Line
BAMA | Bryant Adaptive Moving Average
BFMA | Blackman Filter Moving Average
CMA | Corrected Moving Average
CORMA | Correlation Moving Average
COVEMA | Coefficient of Variation Weighted Exponential Moving Average
COVNA | Coefficient of Variation Weighted Moving Average
CTI | Coral Trend Indicator
DEC | Ehlers Simple Decycler
DEMA | Double EMA Moving Average
DEVS | Ehlers - Deviation Scaled Moving Average
DONEMA | Donchian Extremum Moving Average
DONMA | Donchian Moving Average
DSEMA | Double Smoothed Exponential Moving Average
DSWF | Damped Sine Wave Weighted Filter
DWMA | Double Weighted Moving Average
E2PBF | Ehlers 2-Pole Butterworth Filter
E2SSF | Ehlers 2-Pole Super Smoother Filter
E3PBF | Ehlers 3-Pole Butterworth Filter
E3SSF | Ehlers 3-Pole Super Smoother Filter
EDMA | Exponentially Deviating Moving Average (MZ EDMA)
EDSMA | Ehlers Dynamic Smoothed Moving Average
EEO | Ehlers Modified Elliptic Filter Optimum
EFRAMA | Ehlers Modified Fractal Adaptive Moving Average
EHMA | Exponential Hull Moving Average
EIT | Ehlers Instantaneous Trendline
ELF | Ehler Laguerre filter
EMA | Exponential Moving Average
EMARSI | EMARSI
EPF | Edge Preserving Filter
EPMA | End Point Moving Average
EREA | Ehlers Reverse Exponential Moving Average
ESSF | Ehlers Super Smoother Filter 2-pole
ETMA | Exponential Triangular Moving Average
EVMA | Elastic Volume Weighted Moving Average
FAMA | Following Adaptive Moving Average
FEMA | Fast Exponential Moving Average
FIBWMA | Fibonacci Weighted Moving Average
FLSMA | Fisher Least Squares Moving Average
FRAMA | Ehlers - Fractal Adaptive Moving Average
FX | Fibonacci X Level
GAUS | Ehlers - Gaussian Filter
GHL | Gann High Low
GMA | Gaussian Moving Average
GMMA | Geometric Mean Moving Average
HCF | Hybrid Convolution Filter
HEMA | Holt Exponential Moving Average
HKAMA | Hilbert based Kaufman Adaptive Moving Average
HMA | Harmonic Moving Average
HSMA | Hirashima Sugita Moving Average
HULL | Hull Moving Average
HULLT | Hull Triple Moving Average
HWMA | Henderson Weighted Moving Average
IE2 | Early T3 by Tim Tilson
IIRF | Infinite Impulse Response Filter
ILRS | Integral of Linear Regression Slope
JMA | Jurik Moving Average
KA | Unknown
KAMA | Kaufman Adaptive Moving Average & Apirine Adaptive MA
KIJUN | KIJUN
KIJUN2 | Kijun v2
LAG | Ehlers - Laguerre Filter
LCLSMA | 1LC-LSMA (1 line code lsma with 3 functions)
LEMA | Leader Exponential Moving Average
LLMA | Low-Lag Moving Average
LMA | Leo Moving Average
LP | Unknown
LRL | Linear Regression Line
LSMA | Least Squares Moving Average / Linear Regression Curve
LTB | Unknown
LWMA | Linear Weighted Moving Average
MAMA | MAMA - MESA Adaptive Moving Average
MAVW | Mavilim Weighted Moving Average
MCGD | McGinley Dynamic Moving Average
MF | Modular Filter
MID | Median Moving Average / Percentile Nearest Rank
MNMA | McNicholl Moving Average
MTMA | Unknown
MVSMA | Minimum Variance SMA
NLMA | Non-lag Moving Average
NWMA | Dürschner 3rd Generation Moving Average (New WMA)
PKF | Parametric Kalman Filter
PWMA | Parabolic Weighted Moving Average
QEMA | Quadruple Exponential Moving Average
QMA | Quick Moving Average
REMA | Regularized Exponential Moving Average
REPMA | Repulsion Moving Average
RGEMA | Range Exponential Moving Average
RMA | Welles Wilders Smoothing Moving Average
RMF | Recursive Median Filter
RMTA | Recursive Moving Trend Average
RSMA | Relative Strength Moving Average - based on RSI
RSRMA | Right Sided Ricker MA
RWMA | Regressively Weighted Moving Average
SAMA | Slope Adaptive Moving Average
SFMA | Smoother Filter Moving Average
SMA | Simple Moving Average
SSB | Senkou Span B
SSF | Ehlers - Super Smoother Filter P2
SSMA | Super Smooth Moving Average
STMA | Unknown
SWMA | Self-Weighted Moving Average
SW_MA | Sine-Weighted Moving Average
TEMA | Triple Exponential Moving Average
THMA | Triple Exponential Hull Moving Average
TL | Unknown
TMA | Triangular Moving Average
TPBF | Three-pole Ehlers Butterworth
TRAMA | Trend Regularity Adaptive Moving Average
TSF | True Strength Force
TT3 | Tilson (3rd Degree) Moving Average
VAMA | Volatility Adjusted Moving Average
VAMAF | Volume Adjusted Moving Average Function
VAR | Vector Autoregression Moving Average
VBMA | Variable Moving Average
VHMA | Vertical Horizontal Moving Average
VIDYA | Variable Index Dynamic Average
VMA | Volume Moving Average
VSO | Unknown
VWMA | Volume Weighted Moving Average
WCD | Unknown
WMA | Weighted Moving Average
XEMA | Optimized Exponential Moving Average
ZEMA | Zero Lag Moving Average
ZLDEMA | Zero-Lag Double Exponential Moving Average
ZLEMA | Ehlers - Zero Lag Exponential Moving Average
ZLTEMA | Zero-Lag Triple Exponential Moving Average
ZSMA | Zero-Lag Simple Moving Average
"
Don't forget that you can use any Moving Average not only for the chart but also for any of your indicators without affecting the code as in my example.
But remember that some MAs are not designed to work with anything other than a chart.
All MA and Code lists are sorted strictly alphabetically by short name (A-Z).
Each MA has its own number (ID) by which you can display the Moving Average you need.
Next to the ID selection there are tooltips with short names and their numbers. Use them.
The panel below will help you to read the Name of the selected MA.
Because of the size of the collection I think this is the optimal and most convenient use. Correct me if this is not the case.
Unknown - Some MAs I collected so long ago that I lost the full real name and couldn't find the authors. If you recognize them, please let me know.
I have deliberately simplified all MAs to input just Source and Length.
Because the collection is so large, it would be quite inconvenient and difficult to customize all MA functions (multipliers, offset, etc.).
If you need or like any MA you will still have to take it from my collection for your code.
I tried to leave the basic MA settings inside function in first strings.
I have tried to list most of the authors, but since the bulk of the collection was created a long time ago and was not intended for public publication I could not find all of them.
Some of the features were created from scratch or may have been slightly modified, so please be careful.
If you would like to improve this collection, please write to me in PM.
Also Credits, Likes, Awards, Loves and Thanks to :
@alexgrover
@allanster
@andre_007
@auroagwei
@blackcat1402
@bsharpe
@cheatcountry
@CrackingCryptocurrency
@Duyck
@ErwinBeckers
@everget
@glaz
@gotbeatz26107
@HPotter
@io72signals
@JacobAmos
@JoshuaMcGowan
@KivancOzbilgic
@LazyBear
@loxx
@LuxAlgo
@MightyZinger
@nemozny
@NGBaltic
@peacefulLizard50262
@RicardoSantos
@StalexBot
@ThiagoSchmitz
@TradingView
— 𝐀𝐧𝐝 𝐎𝐭𝐡𝐞𝐫𝐬 !
So just a Big Thank You to everyone who has ever and anywhere shared their codes.
Geometrical Mean Moving AverageThe geometric moving average is a type of moving average that calculates the geometric mean of the previous n-periods of the price time series. Unlike the simple moving average that uses the arithmetic mean to continuously calculate the moving average as new price data comes in, the geometric moving average uses the geometric mean formula to get the moving average of the price data as new ones come in.
Why use a geometric moving average?
The geometric moving average differs from the simple moving average in how it is calculated. Most importantly, the geometric mean takes into account the compounding that occurs from period to period.
How can you use a geometric mean moving average?
You can use the GMMA just as you would use any other moving average indicator. You can use it to identify the direction of the trend, and in this case, it can also serve as a support level during an uptrend or a resistance level during a downtrend.
Drawbacks with a geometric moving average
Just like other moving average indicators, the GMA has limitations. Some of them are as follows:
It lags because it uses past price data.
It is pretty useless when the price action is choppy or moving predominantly sideways. During such periods, it can give multiple false signals.
Strategy Gaussian Anomaly DerivativeConcept behind this Strategy :
Considering a normal "buy/sell" situation, an asset would be bought in average at the median price following a Gaussian like concept. A higher or lower average trend would significate that the current perceived value is respectively higher or lower than the current median price, which mean that the buyers are evaluating the price underpriced or overpriced.
This behaviour would be even more relevent depending on its derivative evolution.
Therefore, this Strategy setup is based on this Gaussian like concept anomaly of average close positionning compare to high-low average derivative, such as the derivative of the following ploted basic signal : 1-(high+low)/(2*close).
This Strategy can actually be used like a trend change and continuation strength indicator aswell.
In the Setup Signal part :
You can define the filtering of the basis signal "1-(high+low)/(2*close)" on EMA or SMA as you wish.
You can define the corresponding period and the threathold as a mutiply of the average 1/3 of all time value of the basis signal.
You can define the SMA filtering period of the Derivative signal and the corresponding threathold on the same mutiply of the average 1/3 of all time value of the derivative.
In the Setup Strategy part :
You can set up your strategy assesment based on Long and/or Short. You can also define the considered period.
The most successful tuned strategies I did were based on the derivative indicator with periods on the basis signal and the derivative under 30, can be 1 to 3 of te derivative and 7 to 21 for the basis signal. The threathold depends on the asset volatility aswell, 1 is usually the most efficient but 0 to 10 can be relevent depending on the situation I met. You can find an example of tuning for this strategy based on Kering's case hereafter.
I hoping that you will enjoy using this Strategy, don't hesitate to comment, to question, to correct or complete it ! I would be very curious about similar famous approaches that would have already been made.
Thank to you !
Average Range LinesThis Average Range Lines indicator identifies high and low price levels based on a chosen time period (day, week, month, etc.) and then uses a simple moving average over the length of the lookback period chosen to project support and resistance levels, otherwise referred to as average range. The calculation of these levels are slightly different than Average True Range and I have found this to be more accurate for intraday price bounces.
Lines are plotted and labeled on the chart based on the following methodology:
+3.0: 3x the average high over the chosen timeframe and lookback period.
+2.5: 2.5x the average high over the chosen timeframe and lookback period.
+2.0: 2x the average high over the chosen timeframe and lookback period.
+1.5: 1.5x the average high over the chosen timeframe and lookback period.
+1.0: The average high over the chosen timeframe and lookback period.
+0.5: One-half the average high over the chosen timeframe and lookback period.
Open: Opening price for the chosen time period.
-0.5: One-half the average low over the chosen timeframe and lookback period.
-1.0: The average low over the chosen timeframe and lookback period.
-1.5: 1.5x the average low over the chosen timeframe and lookback period.
-2.0: 2x the average low over the chosen timeframe and lookback period.
-2.5: 2.5x the average low over the chosen timeframe and lookback period.
-3.0: 3x the average low over the chosen timeframe and lookback period.
Look for price to find support or resistance at these levels for either entries or to take profit. When price crosses the +/- 2.0 or beyond, the likelihood of a reversal is very high, especially if set to weekly and monthly levels.
This indicator can be used/viewed on any timeframe. For intraday trading and viewing on a 15 minute or less timeframe, I recommend using the 4 hour, 1 day, and/or 1 week levels. For swing trading and viewing on a 30 minute or higher timeframe, I recommend using the 1 week, 1 month, or longer timeframes. I don’t believe this would be useful on a 1 hour or less timeframe, but let me know if the comments if you find otherwise.
Based on my testing, recommended lookback periods by timeframe include:
Timeframe: 4 hour; Lookback period: 60 (recommend viewing on a 5 minute or less timeframe)
Timeframe: 1 day; Lookback period: 10 (also check out 25 if your chart doesn’t show good support/resistance at 10 days lookback – I have found 25 to be useful on charts like SPX)
Timeframe: 1 week; Lookback period: 14
Timeframe: 1 month; Lookback period: 10
The line style and colors are all editable. You can apply a global coloring scheme in the event you want to add this indicator to your chart multiple times with different time frames like I do for the weekly and monthly.
I appreciate your comments/feedback on this indicator to improve. Also let me know if you find this useful, and what settings/ticker you find it works best with!
Also check out my profile for more indicators!
Average True Range Trailing Mean [Alifer]Upgrade of the Average True Range default indicator by TradingView. It adds and plots a trailing mean to show periods of increased volatility more clearly.
ATR TRAILING MEAN
A trailing mean, also known as a moving average, is a statistical calculation used to smooth out data over time and identify trends or patterns in a time series.
In our indicator, it clearly shows when the ATR value spikes outside of it's average range, making it easier to identify periods of increased volatility.
Here's how the ATR Trailing Mean (atr_mean) is calculated:
atr_mean = ta.cum(atr) / (bar_index + 1) * atr_mult
The ta.cum() function calculates the cumulative sum of the ATR over all bars up to the current bar.
(bar_index + 1) represents the number of bars processed up to the current bar, including the current one.
By dividing the cumulative ATR ta.cum(atr) by (bar_index + 1) and then multiplying it by atr_mult (Multiplier), we obtain the ATR Trailing Mean value.
If atr_mult is set to 1.0, the ATR Trailing Mean will be equal to the simple average of the ATR values, and it will follow the ATR's general trend.
However, if atr_mult is increased, the ATR Trailing Mean will react more strongly to the ATR's recent changes, making it more sensitive to short-term fluctuations.
On the other hand, reducing atr_mult will make the ATR Trailing Mean less responsive to recent changes in ATR, making it smoother and less prone to reacting to short-term volatility.
In summary, adjusting the atr_mult input allows traders to fine-tune the ATR Trailing Mean's responsiveness based on their preferred level of sensitivity to recent changes in market volatility.
IMPLEMENTATION IN A STRATEGY
You can easily implement this indicator in an existing strategy, to only enter positions when the ATR is above the ATR Trailing Mean (with Multiplier-adjusted sensitivity). To do so, add the following lines of codes.
Under Inputs:
length = input.int(title="Length", defval=20, minval=1)
atr_mult = input.float(defval=1.0, step = 0.1, title = "Multiplier", tooltip = "Adjust the sensitivity of the ATR Trailing Mean line.")
smoothing = input.string(title="Smoothing", defval="RMA", options= )
ma_function(source, length) =>
switch smoothing
"RMA" => ta.rma(source, length)
"SMA" => ta.sma(source, length)
"EMA" => ta.ema(source, length)
=> ta.wma(source, length)
This will allow you to define the Length of the ATR (lookback length over which the ATR is calculated), the Multiplier to adjust the Trailing Mean's sensitivity and the type of Smoothing to be used for the ATR.
Under Calculations:
atr= ma_function(ta.tr(true), length)
atr_mean = ta.cum(atr) / (bar_index+1) * atr_mult
This will calculate the ATR based on Length and Smoothing, and the resulting ATR Trailing Mean.
Under Entry Conditions, add the following to your existing conditions:
and atr > atr_mean
This will make it so that entries are only triggered when the ATR is above the ATR Trailing Mean (adjusted by the Multiplier value you defined earlier).
ATR - DEFINITION AND HISTORY
The Average True Range (ATR) is a technical indicator used to measure market volatility, regardless of the direction of the price. It was developed by J. Welles Wilder and introduced in his book "New Concepts in Technical Trading Systems" in 1978. ATR provides valuable insights into the degree of price movement or volatility experienced by a financial asset, such as a stock, currency pair, commodity, or cryptocurrency, over a specific period.
ATR - CALCULATION AND USAGE
The ATR calculation involves three components:
1 — True Range (TR): The True Range is a measure of the asset's price movement for a given period. It takes into account the following factors:
The difference between the high and low prices of the current period.
The absolute value of the difference between the high price of the current period and the closing price of the previous period.
The absolute value of the difference between the low price of the current period and the closing price of the previous period.
Mathematically, the True Range (TR) for the current period is calculated as follows:
TR = max(high - low, abs(high - previous_close), abs(low - previous_close))
2 — ATR Calculation: The ATR is calculated as a Moving Average (MA) of the True Range over a specified period.
The ATR is calculated as follows:
ATR = MA(TR, length)
3 — ATR Interpretation: The ATR value represents the average volatility of the asset over the chosen period. Higher ATR values indicate higher volatility, while lower ATR values suggest lower volatility.
Traders and investors can use ATR in various ways:
Setting Stop Loss and Take Profit Levels: ATR can help determine appropriate stop-loss and take-profit levels in trading strategies. A larger ATR value might require wider stop-loss levels to allow for the asset's natural price fluctuations, while a smaller ATR value might allow for tighter stop-loss levels.
Identifying Market Volatility: A sharp increase in ATR might indicate heightened market uncertainty or the potential for significant price movements. Conversely, a decreasing ATR might suggest a period of low volatility and possible consolidation.
Comparing Volatility Between Assets: Since ATR uses absolute values, it shouldn't be used to compare volatility between different assets, as assets with higher prices will consistently have higher ATR values, while assets with lower prices will consistently have lower ATR values. However, the addition of a trailing mean makes such a comparison possible. An asset whose ATR is consistently close to its ATR Trailing Mean will have a lower volatility than an asset whose ATR continuously moves far above and below its ATR Trailing Mean. This can help traders and investors decide which markets to trade based on their risk tolerance and trading strategies.
Determining Position Size: ATR can be used to adjust position sizes, taking into account the asset's volatility. Smaller position sizes might be appropriate for more volatile assets to manage risk effectively.
Rough AverageThe Rough Average indicator is a unique technical tool that calculates a modified average to provide insights into market conditions. It incorporates a combination of mathematical operations and existing indicators to offer traders a different perspective on price movements.
The Rough Average indicator aims to capture market dynamics through a specific calculation method. It utilizes two main components: a check for the approximate scale of the price and a profile calculation based on the Relative Strength Index (RSI) of the closing price.
Methodology:
Approximate Scale: The indicator determines the approximate scale of the price by analyzing the magnitude of the closing price. This step involves a mathematical process that identifies the power of 10 that best represents the scale. This function reduces overall lag and gives a better smoothing to the output of the calculation
Profile Calculation: The indicator calculates a profile value by summing the absolute values of the RSI of the closing price over a specified period. The RSI provides insights into the strength or weakness of price movements. The profile calculation considers a range of prices based on the determined scale.
Indicator Calculation:
The Rough Average is derived by applying the Exponential Moving Average (EMA) to the calculated profile. The EMA is a smoothing technique that emphasizes recent price data. The resulting value represents the modified average of the indicator.
Utility:
The Rough Average indicator offers traders an alternative perspective on market conditions. By utilizing a modified average calculation, it can reveal potential trends, reversals, or periods of market strength or weakness. Traders can use the Rough Average to complement their analysis and identify possible trading opportunities.
It is important to note that the effectiveness of the Rough Average indicator may vary depending on the specific market and trading strategy. It is recommended to combine its analysis with other technical indicators and conduct thorough testing before making trading decisions.
Key Features:
Customizable OB\OS Levels
Bar coloring methods: Trend, Reversions, Extremities
Example Charts:
