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.
Average
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!
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.
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.
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:
TimeLy Moving Average - TMAHello traders, I'm Only Fibonacci.
With this indicator, you will see the averages according to the hourly, weekly and monthly price movements in many periods on the chart.
This will show you the moving average values of the price over different periods in a progressive manner on the chart that is open to you.
Options and Usage
To see the hourly average, your chart's time range must be less than or equal to 60 minutes, otherwise it will produce a NaN value.
In order to see the daily average, your chart must be open for any minute period or (even if the second is open, it must be greater than 6 seconds). Otherwise, it does not produce any value.
Your chart must be larger than the second chart to see the weekly average. In other words, you can see the weekly average with at least 1 minute chart open.
In order to see the monthly average, your chart time interval must be above 10 minutes, otherwise you will not be able to see data again.
Settings
You choose the moving average type and the time interval value you want to see from the indicator settings.
You can also select a source for moving averages.
Enjoy it, you can make improvements on it.
Please do not forget to comment for various bug reports.
Anchored VWAP+This indicator is an enhanced version of the Anchored VWAP indicator with additional functions:
1. Anchored AP (average price). It removes the volume weighting step in Anchored VWAP, and can display the average price over a period of time. For example, if the price of the stock in the last 3 days is 100, 200, 300, then AP is their average value of 200
2. Anchored AC (average cost). The average cost over time can be displayed. For example, if the price of the stock in the last 2 days is 100,300, then AC is (1+1)/(1/100+1/300)=150
When using the indicator, you need to choose a starting point, then the indicator will start to calculate the subsequent VWAP, AP and AC from this starting point, and draw 3 lines in the graph
These three lines can be regarded as the average cost line of the market, with potential support and resistance effects
We have filled the shadow between VWAP and AP, which can be regarded as a potential support resistance band
===========================中文版本===========================
该指标为增强版本的Anchored VWAP指标。在Anchored VWAP基础上增加了额外功能：
1. Anchored AP。其去掉了Anchored VWAP中成交量加权的步骤，可以显示一段时间的平均价格。举个例子，假如股票最近3天的价格为100，200，300，那么AP为他们的平均值200
2. Anchored AC。可以显示一段时间的平均成本。举个例子，假如股票最近2天的价格为100，300，那么AC为(1+1)/(1/100+1/300)=150
使用指标时你需要先选择一个起点，随后指标将会以该起点开始计算后续的VWAP、AP和AC，并且在图中绘制3根线
这3根线均可以视作是市场的平均成本线，具有潜在的支撑和阻力效果
我们让VWAP和AP之间填充了阴影，该阴影可以视作潜在的支撑阻力带
Ratio To Average - The Quant ScienceRatio To Average - The Quant Science is a quantitative indicator that calculates the percentage ratio of the market price in relation to a reference average. The indicator allows the calculation of the ratio using four different types of averages: SMA, EMA, WMA, and HMA. The ratio is represented by a series of histograms that highlight periods when the ratio is positive (in green) and periods when the ratio is negative (in red).
What is the Ratio to Average?
The Ratio to Average is a measure that tracks the price movements with one of its averages, calculating how much the price is above or below its own average, in percentage terms.
USER INTERFACE
Lenght: it adjusts the number of bars to include in the calculation of the average.
Moving Average: it allows you to choose the type of average to use.
Color Up/Color Down : it allows you to choose the color of the indicator for positive and negative ratios.
MADI(Moving average deviation rate index)This script is "Moving average deviation rate" to Indexing.
index = average deviation rate / (Sigma * (input:SIgma)) * 100
It's for people who like simplicity.
Average Trend with Deviation Bands v2TL;DR: An average based trend incl. micro trend spotting and multiple display options.
This script is basically an update of my "Average Trend with Deviation Bands" script. I made the following changes:
Not an overlay anymore - The amount of drawn lines makes the chart pretty messy. That's why I moved it to a pane. If you preferred the overlay you can use my "Average Trend with Deviation Bands" script. *This is also the reason why I publish this script instead of updating the existing one.
I added an EMA to represent the price movement instead of candles
I added a signal (SMA) to spot micro trends and early entry/exit signals
I added the option to switch between a "line view" which shows the average trend and deviation bands and an "oscillator view" which shows an oscillator and histogram (MACD style)
General usage:
1. The white line is the average trend (which is an average of the last N bars open, close, high, low price).
2. Bands around the average trend are standard deviations which can be adjusted in the options menu and are only visible in "lines view". Basically they are like the clouds in the Ichimoku Cloud indicator - In big deviation bands the price movement needs more "power" to break through the average trend and vice versa.
3. Indicator line (blue line) - This is the EMA which represents the price. Crossing the average trend from below indicates an uptrend and vice versa (crossing from above indicates a down trend).
4. Signal line (red line) - This is a smoothed version of the indicator line which can be used to predict the movement of the price when crossed by the indicator line (like at MACD and many other indicators).
Oscillator usage:
When switched to "oscillator view" the indicator line oscillates around a zero line which can be seen as the average trend. The usage is basically the same as described above. However there is also the histogram which shows the difference between the indicator and signal. Of course the histogram can be deactivated. Additionally a color filling can be added to easily spot entry/exit signals.
As always: Code is free do whatever you like. If you have any questions/comments/etc. just drop it in the comment section.
Manual PnL (Profit and Loss) % Tracker - spot long only
This is a manual profit and loss tracker. It takes the user's manual input of total cost and quantity, and then outputs a table on the bottom right of the chart showing the profit or loss %, average purchase price, gross profit or loss, and market value.
Instructions:
1. Double click the indicator title at the top left of the chart
2. Select the "Inputs" tab and click the empty field next to "Symbol" to enter the traded symbol+exchange. This entry MUST be the same as the chart you are on, for example BTCUSDT/BINANCE (indicator will not display otherwise)
3. Enter the Total Cost and Qty of shares/coins owned
4. Optional - change positive or negative colors
5. Optional - under the "Style" tab, change the color of the average price (AVG) line
Note that for the average price (AVG) line to be shown/hidden you must enable/disable "Indicator and financials labels" in the scales settings.
For crypto or other tickers that have prices in many decimal places I would suggest, for the sake of accuracy, adjusting the decimal places in the code so that for prices under $1 you will display more info.
For example let's say you purchase x number of crypto at a price of 0.031558 you should change the code displaying "0.00" on line 44 to "0.000000"
This will ensure that the output table and plotted line will calculate an average price with the same number of decimals.
Ignition Cha Cha ChaIgnition Cha Cha Cha (ICCC) is a 3 color coded moving average indicator which numerically quantify the angle of their trends. I have labeled them as fast, medium and slow. The trend colors are Green for bullish, Red for bearish and Grey for sideways. The sideways movement can be user defined for all 3 in the settings under Threshold. If you regard for example anything under 10º as sideways then place 10 in the corresponding threshold and any angle under 10º will give a grey moving average and a grey labeled text. I use this chart in several ways. If you don't want moving averages all over your Chartistic Masterpiece you can turn off the plots and leave the numeric angles which will give you an overview of the trend. Conversely if you want to make the ultimate trend chart you can setup a 4 chart layout, Weekly, Daily, 12 hour and 4 hour and add the indicator with 200/50/25 moving averages and look for confluence. I find the best way for this is turn off the candles and use the moving averages with the numeric labels. You also have the ability to turn off and on different aspects of the indicator so that there is good control over its look. Also I have given the indicator lots of Alert presets for all 3 of the moving averages so you can avoid demented screen-stairing. Please forgive the name, my mother made me do Ballroom dancing lessons as a kid.
Average Cost (Costo Promedio)ENGLISH
This 'Average Cost' script allows the user to input and visualize profit or loss for different stocks (up to 50) with average cost and quantity data on a single chart. This is useful for tracking the profit or loss of each stock in real-time.
To use this script, the user should follow these steps:
1. Add the 'Average Cost' script to your TradingView chart.
2. In the script's configuration window, input the tickers, average costs, and quantity of shares for each ticker you want to monitor.
3. Click 'Accept' to apply the changes.
This script is primarily designed for stock markets, but can also be useful in other financial markets where the user is interested in tracking the performance of multiple assets.
ESPAÑOL
Este script de "Costo Promedio" permite al usuario ingresar y visualizar si hay ganancia o perdida para diferentes acciones (hasta 50) con los datos de costos promedio y cantidad de acciones en un solo gráfico. Esto es útil para realizar un seguimiento de la ganancia o pérdida de cada acción en tiempo real.
Para utilizar este script, el usuario debe seguir estos pasos:
1. Agregue el script "Costo Promedio" a su gráfico en TradingView.
2. En la ventana de configuración del script, ingrese los tickers, costos promedio y cantidad de acciones para cada ticker que desee monitorear.
3. Haga clic en "Aceptar" para aplicar los cambios.
Este script está diseñado principalmente para los mercados de acciones, pero también puede ser útil en otros mercados financieros donde el usuario esté interesado en rastrear el rendimiento de múltiples activos.
