ROE BandROE Band shows the return on net profit from shareholders' equity and the formula for decomposition
ROE = ROA x CSL x CEL
ROE Band consists of 5 parts:
1. ROE (TTM) is the 12-month ROE calculation in "green"
2. Return on Equity (ROE) is the current quarterly net profit / the average of the beginning and ending periods of shareholders' equity in "yellow"
3. Return on Assets (ROA) is the current quarterly NOPAT (net profit before tax) / the average of the beginning and ending periods of total assets in "blue"
4. Capital structure leverage (CSL) is a financial measure that compares a company's debt to its total capital. It is calculated by taking the average of the beginning and ending periods of total assets / the average of the beginning and ending periods of shareholders' equity. The higher the CSL, the more deb, in. "red"
5. Common earnings leverage (CEL) is the proportion of net profit and NOPAT (net profit before tax), where a lower CEL means more tax, in "orange"
The "😱" emoji represents the value if it increases by more than or decreases by less than 20%, e.g.
- ROE(TTM), ROE, ROA, CEL is decreasing
- CSL is increasing
The "🔥" emoji represents the value if it increases by more than or decreases, e.g.
- ROE(TTM), ROE, ROA, CEL is increasing
- CSL is decreasing
Buscar en scripts para "band"
TMA Bands TMA (Triangular Moving Average):
Üçgen hareketli ortalamalar, fiyat verilerini yumuşatarak trendi daha net göstermek için kullanılır.
"Centered Asymmetric Bands" terimi, bu indikatörün merkezlenmiş bir yapıda çalıştığını ve farklı genişliklerde bantlar içerdiğini gösteriyor.
Polygonal Pivot Bands [FXSMARTLAB]The Polygonal Pivot Bands highlights key price pivots, dynamic support and resistance levels, and recent price action on a trading chart. This indicator connects pivot highs and lows with a zigzag line, extends a real-time dashed line to the latest price point, and plots diagonal support/resistance levels that adapt to price movement. These elements together provide traders with a view of significant price zones and potential trend shifts.
Key Components of the Indicator
Pivots are calculated based on user-defined lengths, specifying how many bars on either side of a high or low are required to validate it as a pivot.
Adjustable left and right pivot lengths allow traders to control the sensitivity of pivot detection, with higher values resulting in fewer, more prominent pivots, and lower values increasing sensitivity to price changes.
Zigzag Line
The zigzag line connects consecutive pivot points, filtering out smaller fluctuations and emphasizing the broader direction of price movement.
Users can customize the line's color and thickness to match their preferences, helping them focus on larger trends and potential reversal points.
By linking pivot highs and lows, the zigzag pattern highlights the overall trend and potential points of reversal.
Real-Time Connector Line
A dashed line extends from the last confirmed pivot to the latest price point, providing a real-time, bar-by-bar update of the current price relative to the previous pivot.
This line does not project future price direction but maintains an up-to-date connection with the current price, showing the distance from the last pivot.
Its color and thickness are customizable for improved visibility on the chart.
Dynamic Support and Resistance Levels
The indicator plots dynamic support and resistanc e levels by connecting recent pivot highs and lows, resulting in lines that may appear diagonal rather than strictly horizontal.
These levels move in line with price action, adapting to the natural direction of trends, and offer visual cues where price may encounter support or resistance.
Colors and thickness of these lines can be set individually, allowing traders to adjust visibility according to their preferences.
Enabling these lines gives traders an ongoing reference for critical price boundaries that align more closely with the overall trend.
Cash Cycle BandCash cycle band shows the number of days and the profit margin compared to the previous period (it does not indicate how profitable the company is, but how well it is managed).
Cash cycle band consists of 6 sections:
1. DPO is the days payables outstanding in the "red" followed by O/D which is overdraft or short-term debt (if any) .
2. DIO is the days inventory outstanding in the "green" followed by classified inventory (if any) consists of finished goods. work in process and raw materials.
3. DSO is days sales outstanding in "blue".
4. DWC is days converting working capital to revenue in "orange".
5. CCC is days converting inventory and resources to cash flow in "yellow".
6. GPM is gross profit margin and OPM is operating profit margin.
The "😱" emoji indicates a value if it increases by more than or decreases by less than 20%, e.g.
- DPO, finished goods, work in process, raw materials, GPM, OPM is decreasing.
- O/D, DIO, DSO, DWC, CCC is increasing.
The "🔥" emoji indicates a value if it increases by more than or decreases, e.g.
- DPO, finished goods, work in process, raw materials, GPM, OPM is increasing.
- O/D, DIO, DSO, DWC, CCC is decreasing.
The order of the list depends on the day of each item, the more days more high.
PEV Price BandThe PEV Price Band shows prices calculated using the high and low P/FQ EV of the previous period. (price to enterprise value per share for the last quarter) multiplied by FQ's current EVPS (similar to comparing marketcap to enterprise value but edit equations that are close to the theory of P/E)
If the current price is lower than the minimum P/EVPS, it is considered cheap. In other words, a current price is above the maximum is considered expensive.
PEV Price Band consists of 2 parts.
- First of all, the current P/EVPS value is "green" (if the markecap is less than the enterprise value) or "red" (if the marketcap is more than the enterprise value) or "gold" (if the market value is less than the enterprise value and less than equity)
- Second, the blue line is the closing price.
PE BandThe PE Band shows the highest and lowest P/E in the previous period with TTM EPS. If the current P/E is lower than the minimum P/E, it is considered cheap. In other words, higher than the maximum P/E is considered expensive.
PE Band consists of 2 lines.
- Firstly, the historical P/E value in "green" (if TTM EPS is positive) or "red" (if TTM EPS is negative) states will change according to the latest high or low price of TTM EPS, such as: :
After the second quarter of 2023 (end of June), how do prices from 1 July – 30 September reflect net profits? The program will get the highest and lowest prices during that time.
After the 3rd quarter of 2023 (end of September), how do prices from 1 Oct. - 31 Dec. reflect net profits? The program will get the highest and lowest prices during that time.
- Second, the blue line is the closing price divided by TTM EPS, which shows the current P/E.
Dynamic GANN Square Of 9 BandsDynamic GANN Square Of 9 Bands
Created on 3 Sept 2023
Adjust Increment Value:
Customize increment to match symbol and price characteristics for accuracy.
Green Line:
200 EMA. Identifies trend direction; moves with the prevailing trend.
Red Lines:
Mark prominent reversal levels closer to the red range; ideal for mean reversion strategies.
Crossing red levels may indicate trend continuation to the next red level.
Grey Lines:
Show immediate target reversal levels; watch for potential reversals.
Key Features:
Levels are different from Standard Deviation Lines.
Levels remain fixed and parallel, unaffected by volatility.
Despite its dynamism, it can serve as a leading indicator, revealing potential trend changes.
Primarily designed for trend-following strategies.
Additional Tips:
Use additional confirmations
Manage predefined risk and quantity
Additional Resources:
GANN Square Of 9 Pivots:
Multi Bollinger Bands with Over ZoneThis indicator is called "Multi Bollinger Bands with Over Zone". The indicator uses linear regression to calculate the regression line and standard deviation to calculate the upper and lower deviation lines. It also plots filled areas between the deviation lines to highlight overbought and oversold zones.
The indicator has several customizable inputs, including the length of the regression period, depth, and deviations used to calculate the deviation lines.
The regression line is plotted in green color with circle markers. The upper and lower deviation lines are plotted in blue and red colors, respectively. The area between the deviation lines is filled with light blue color for the overbought zone and light pink color for the oversold zone.
This indicator helps traders in identifying trends and potential price reversals. When the price is above the upper deviation line, it indicates a potential overbought zone, while when the price is below the lower deviation line, it indicates a potential oversold zone.
Please note that this indicator is only a tool for analysis and does not provide direct trading signals. It is important to combine this indicator with additional analysis and appropriate trading strategies.
Bollinger Bands %B (ValueRay)One of the key features of this BB%B is its ability to highlight overbought and oversold conditions. This allows you to make informed decisions on when to enter and exit a trade, helping you maximize your profits and minimize your losses.
- Bollinger Bands %B with the ability to change to a different Time Frame.(Defaults to current Chart Time Frame).
- Ability To Turn On/Off Background Highlighting if BB %B is Above/Below 0 / 1 thresholds.
- Ability To Turn On/Off Background Highlighting when BB %B Crosses back above/unser 0/1 thresholds.
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My personal recommandation use: combine with CM_Ultimate RSI Multi Time Frame (ChrisMoody) and have solid oversold/overbought levels, when hes RSI and my BB %B are bot red/green
Rekt Edge Reversion BandRekt Edge Reversion band is a technical indicator that utilizes a combination of moving averages and standard deviations to determine optimal entry and exit points in the market. By comparing the current price to its moving average, the indicator identifies potential trends and determines how you can position around them by plotting buy/sell signals and two channels based on user input parameters. The user can choose between Simple Moving Average ( SMA ) or Exponential Moving Average ( EMA ) and select the moving average period, the unit of separation, the multiples of the unit, and other important parameters. The indicator's inputs can be adjusted to suit different trading styles, and it can be used on any time frame. The indicator can be used to identify potential trend reversals or breakouts (or breakdowns) when the price moves outside of the channels. The indicators potential use cases include identifying overbought or oversold conditions. With its ability to provide a clear signal on when to enter and exit a trade, this indicator is a popular tool among traders looking to make more informed and profitable trading decisions. This indicator can also be used in conjunction with other technical analysis tools to confirm or invalidate trading signals.
MA Band Distance Monitor'MA Band Distance Monitor' indicator is a simple tool for traders who rely on moving averages to make trading decisions. This indicator plots two moving averages of your choice (you can select the type of the moving average), and fills the space between them, creating a "band".
The indicator also generates a table that displays the current price distance from both the fast and slow moving averages, as well as the average of the two. This allows you to quickly assess the strength of the trend and potential entry or exit points.
In addition, the table also shows the average price distance from one to another MA and also the current distance between them, allowing you to compare the current price action to the historical average. This information can help you identify potential trend reversals and assess the overall health of the market.
*** Slow length input must be greater than fast length input, otherwise indicator will produce faulty results
Momentum Deviation Bands [Loxx]Momentum Deviation Bands uses a variation of standard deviation. Instead of using price to calculate standard deviation, this uses momentum. This is another type of volatility that will be used in future indicators. This indicator serves more as an educational tool, but can also be used in trading.
You can read about the included moving averages here:
Included
Bar coloring
HMA w/ SSE-Dynamic EWMA Volatility Bands [Loxx]This indicator is for educational purposes to lay the groundwork for future closed/open source indicators. Some of thee future indicators will employ parameter estimation methods described below, others will require complex solvers such as the Nelder-Mead algorithm on log likelihood estimations to derive optimal parameter values for omega, gamma, alpha, and beta for GARCH(1,1) MLE and other volatility metrics. For our purposes here, we estimate the rolling lambda (λ) value used to calculate EWMA by minimizing of the sum of the squared errors minus the long-run variance--a rolling window of the one year mean of squared log-returns. In practice, practitioners will use a λ equal to a standardized value put out by institutions such as JP Morgan. Even simpler than this, others use a ratio of (per - 1) / (per + 1) to derive λ where per is the lookback period for EWMA. Due to computation limits in Pine, we'll likely not see a true GARCH(1,1) MLE on Pine for quite some time, but future closed source indicators will contain some very interesting industry hacks to get close by employing modifications to EWMA. Enjoy!
Exponentially weighted volatility and its relationship to GARCH(1,1)
Exponentially weighted volatility--also called exponentially weighted moving average volatility (EWMA)--puts more weight on more recent observations. EWMA is calculated as follows:
σ*2 = λσ(n - 1)^2 + (1 − λ)u(n - 1)^2
The estimate, σn, of the volatility for day n (made at the end of day n − 1) is calculated from σn −1 (the estimate that was made at the end of day n − 2 of the volatility for day n − 1) and u^n−1 (the most recent daily percentage change).
The EWMA approach has the attractive feature that the data storage requirements are modest. At any given time, we need to remember only the current estimate of the variance rate and the most recent observation on the value of the market variable. When we get a new observation on the value of the market variable, we calculate a new daily percentage change to update our estimate of the variance rate. The old estimate of the variance rate and the old value of the market variable can then be discarded.
The EWMA approach is designed to track changes in the volatility. Suppose there is a big move in the market variable on day n − 1 so that u2n−1 is large. This causes our estimate of the current volatility to move upward. The value of λ governs how responsive the estimate of the daily volatility is to the most recent daily percentage change. A low value of λ leads to a great deal of weight being given to the u(n−1)^2 when σn is calculated. In this case, the estimates produced for the volatility on successive days are themselves highly volatile. A high value of λ (i.e., a value close to 1.0) produces estimates of the daily volatility that respond relatively slowly to new information provided by the daily percentage change.
The RiskMetrics database, which was originally created by JPMorgan and made publicly available in 1994, used the EWMA model with λ = 0.94 for updating daily volatility estimates. The company found that, across a range of different market variables, this value of λ gives forecasts of the variance rate that come closest to the realized variance rate. In 2006, RiskMetrics switched to using a long memory model. This is a model where the weights assigned to the u(n -i)^2 as i increases decline less fast than in EWMA.
GARCH(1,1) Model
The EWMA model is a particular case of GARCH(1,1) where γ = 0, α = 1 − λ, and β = λ. The “(1,1)” in GARCH(1,1) indicates that σ^2 is based on the most recent observation of u^2 and the most recent estimate of the variance rate. The more general GARCH(p, q) model calculates σ^2 from the most recent p observations on u2 and the most recent q estimates of the variance rate.7 GARCH(1,1) is by far the most popular of the GARCH models. Setting ω = γVL, the GARCH(1,1) model can also be written:
σ(n)^2 = ω + αu(n-1)^2 + βσ(n-1)^2
What this indicator does
Calculate log returns log(close/close(1))
Calculates Lambda (λ) dynamically by minimizing the sum of squared errors. I've restricted this to the daily timeframe so as to not bloat the code with additional logic required to derive an annualized EWMA historical volatility metric.
After the Lambda is derived, EWMA is calculated one last time and the result is the daily volatility
This daily volatility is multiplied by the source and the multiplier +/- the HMA to create the volatility bands
Finally, daily volatility is multiplied by the square-root of days per year to derive annualized volatility. Years are trading days for the asset, for most everything but crypto, its 252, for crypto is 365.
MA20 Hi-Lo-Close Magic BandThis is an improvement over my previous MA20 High Low Magic Band, as it keeps a central 20 MA reference point. So it can help find the up from MA20 lows and down from MA20 highs resisted or supported by MA20 average before final entry. Usable in any time frame of choice - 15m, 30m, Hourly or Daily. In the Hourly / Daily time frame, the signal used with the volume data may work in 6/10 events or more ... Happy trading!
Polynomial Regression Bands w/ Extrapolation of Price [Loxx]Polynomial Regression Bands w/ Extrapolation of Price is a moving average built on Polynomial Regression. This indicator paints both a non-repainting moving average and also a projection forecast based on the Polynomial Regression. I've included 33 source types and 38 moving average types to smooth the price input before it's run through the Polynomial Regression algorithm. This indicator only paints X many bars back so as to increase on screen calculation speed. Make sure to read the tooltips to answer any questions you have.
What is Polynomial Regression?
In statistics, polynomial regression is a form of regression analysis in which the relationship between the independent variable x and the dependent variable y is modeled as an nth degree polynomial in x. Polynomial regression fits a nonlinear relationship between the value of x and the corresponding conditional mean of y, denoted E(y |x). Although polynomial regression fits a nonlinear model to the data, as a statistical estimation problem it is linear, in the sense that the regression function E(y | x) is linear in the unknown parameters that are estimated from the data. For this reason, polynomial regression is considered to be a special case of multiple linear regression .
Related indicators
Polynomial-Regression-Fitted Oscillator
Polynomial-Regression-Fitted RSI
PA-Adaptive Polynomial Regression Fitted Moving Average
Poly Cycle
Fourier Extrapolator of Price w/ Projection Forecast
Bitcoin Support BandsSMA and EMA support/resistance bands for Bitcoin. Based on 4 week multiples; 1 month, 3 month, 6 month, 1 year, 2 year, 4 year.
Bollinger Bands SqueezeBollinger Bands set to only display when a squeeze is taking place. Squeeze will be highlighted.
SMA EMA Bands [CraftyChaos]This indicator creates bands for SMA and EMA averages and adds an average of the two with the idea that price often touches one of them at support and resistance levels. Saves indicator space by combining all into one indicator
ALMA stdev band with fibsArnaud Legoux Moving Average with standard deviation band and standard deviation Fibonacci levels.
Standard deviation band is alma + stdev and alma - stdev.
Fibonacci levels are alma + stdev * fib ratio and alma - stdev * fib ratio (0.382 / 0.5 / 0.618 / 1.618 / 2.618).
Used like a moving average, but also shows probable price range based on past volatility, and helps to recognize support/resistance levels, trends and trend momentum based on the Fibonacci levels.
Bollinger Band Width Percentile - Multi Time FrameMy plan with this indicator was when trading at short timeframes, to modify my expectations on the potential impact of short term volatility based on volatility in longer timeframes, and when trading on longer timeframes to attempt to find an optimal entry point based on shorter term volatility.
The BBWP is calculated for a short, medium and long timeframe, alerts are triggered at extremities with the ability to filter by moving averages and chart movement. The alerts also trigger a plot to the "Backtest Signal" which can be used to trigger trades in a backtester.
Please see the discussions of how I'm using this indicator in the comments below.
Thanks to The_Caretaker for "Bollinger Band Width Percentile" upon which this multi time frame version is based.
Greedy MA & Greedy Bollinger Bands This moving average takes all of the moving averages between 1 and 700 and takes the average of them all. It also takes the min/max average (donchian) of every one of those averages. Also included is Bollinger Bands calculated in the same way. One nice feature I have added is the option to use geometric calculations for. I also added regular bb calculations because this can be a major hog. Use this default setting on 1d or 1w. Enjoy!
ps, I call it greedy because the default settings wont work on lower time frames
Bollinger Band with Moving Average & Pin BarsThis indicator was specifically built to be used for trading the Scalpius Trading System promoted by @scottphillipstrading. Additionally I've added Daily and Weekly Highs, Lows and Central Pivot lines
The central indicators used in the Scalpius trading system which are included here are: The Bollinger Band, chart plotting of Pin Bars (Hammers & Shooting Stars) and an Exponential Moving Average.
In the settings the user has the option select EMA, SMA or WMA along with desired length, the default settings are 8EMA as per the Scalpius system rules. Also the Bollinger Band settings can be amended by the user and the Pin Bar chart plots and daily + weekly high and low plots can be removed by the user.
Smarter MACD BandThe Smarter MACD displayed as a band instead of an oscillator. A classic MACD with average peak and dip lines. The lighter green and red horizontal lines are the average peak and dip of the entire span, respectively. The second, bolder of the two lines are the averages of the peaks and dips above and below the overall peak and dip averages. The filled in color is to help visualize these averages and possible trade setups.
