ATR Oscillator - Index (Average True range Oscillator)The purpose of converting the ATR value indicator to an oscillator;
It is known that the ATR value is not between the two specified values. So it is not compressed between 0 and 100 like RSI and %B etc. Therefore, conditions such as "A condition if ATR value is X, B condition if ATR value is Y" cannot be created. In order to create these conditions, the max and min value range of the ATR value must be determined. This indicator converts the ATR values into a percentage number according to the maximum and minimum ATR values in the period you will choose. Max value is 100, min value is 0. The considered ATR value, on the other hand, corresponds to the % of the difference between the max and min value in the selected period.
In this way, conditions such as "If the ATR Oscillator value is greater than 10 or 20 or 30" can now be created, or the value of another indicator can be calculated based on the ATR Oscillator value. For example; Let's say we want the standard deviation of BBand to change according to the value of the ATR Oscillator. If BBand Standard Deviation is 3 if ATRO value is 100, BBand Standard Deviation is 2 if ATRO value is 0, and BBand Standard Deviation is 2.5 when ATRO value is 50;
We can encode it as BBand_Std_Dev=((ATRO*0.01)+2 )
If the ATRO value is between .... and ...., you can make improvements such as plot color X.
M-oscillator
Fibonacci Moving Average (FMA)The Fibonacci Moving Average (FMA) is a technical analysis tool that uses a weighting system based on the Fibonacci sequence to smooth out fluctuations in data and help identify trends. It is calculated by first finding the metallic mean of the source data and then applying a weight to each data point based on its position in the Fibonacci sequence. The weighted data points are then averaged to create the FMA line. This script allows the user to specify the source data and the length of the moving average, and plots the resulting FMA line on a chart.
Volume Spread AnalyzerThis indicator is unseen on Tradingview and wants to be the number 1 indicator for the volume spread analysis. Its formula, as simple as useful, compares the effort (volume) of the candle with the results, or the price movement.
This way it's possible to apply the famous Volume Spread Analysis with a simple and complete indicator that's 100% objective.
This indicator can be used on almost any market, but it gives the best results on markets which has constant and high volume, like forex markets, for example.
There are 4 different modes that you can choose from, and all of the use different approaches and techniques to measure the same concept: the efficiency of the price compared to the effort of buyers and sellers:
1. The first one analyzes the formula for ONLY buy candles and ONLY for sell candles, and then plots the column oscillator to show the difference.
2. The second function shows the same formula but applied to any candle, and then confronts the two lines generated by the effort of the positive candle and the negative one as an area. You also have a single-step line on the chart that shows the real-time single-candle effort to result from efficiency.
3. Comparison between the single candle effort and the average efficiency, useful to filter out bad entry candles that could lead to a stop loss.
4. Absorbion analyzer: with this option, you can choose between the single candle and multi-candle mode.
4.1: Single candle mode display, as a pink circle on the oscillator, the candles that are more likely an absorption.
4.2: Multi-candle mode display the summation of the single candle value, to analyze the entire movement and identify the part of the trend that can be absorbed when compared to the other.
For almost any function o the indicator, the fast line input changes the fast line that you see on the chart (i suggest not increasing it above 3 for optimal results), and the slow line changes the moving average or the area that shows the difference between the other lines, you can set the slow line to 1 to have as a result the simple difference of the other lines, or you can set it to a higher value like 50 to show the middle or long term bias.
[LazyBear] SQZ Momentum + 1st Gray Cross Signals ━ whvntrI have modified LazyBears Squeeze Momentum Indicator with enhancements, plus added signals
LazyBear mentioned that in John F. Carter's book, Chapter 11, "Mastering the Trade", that "Mr. Carter suggests waiting till the first gray after a black cross, and taking a position in the direction of the momentum (for ex., if momentum value is above zero, go long). Exit the position when the momentum changes (increase or decrease --- signified by a color change)." I have done just that. Now at each "first gray after a black cross", there are now Bearish and Bullish signals.. The signals only appear in the direction of the momentum.
Disclaimer: This indicator does not constitute investment advice. Trade at your own
risk with this method of identifying changes in stock market momentum.
Correlation Coefficient: Visible Range Dynamic Average R -Correlation Coefficient with Dynamic Average R (shows R average for the visible chart only, changes as you zoom in or out)
-Label: Vis-Avg-R = Visable Average R
-the Correlation Coefficient function for Pearson's R is taken from "BA🐷 CC" indicator by @balipour (highly recommended; more thorough treatment of R and other stats, but without the dynamic average)
-I wrote this primarily to add a dynamic Average R, showing correlation for arbitrary start times/end times; whether it be the last month, last year, of some specific period from the past (backtest mode)
-I have been using this to get an idea of correlation regimes over time between Bonds vs Stocks (ZB1! vs ES1!).
-As you see from the above, most of 2022 has seen an unusually strong positive correlation between Bonds and Stocks
~~inputs:
-lookback length for calculation of R
-Backtest mode (true by default): displays Average R for ONLY the visible range displayed on any part of chart history (LHS to RHS of screen only)
-source for both Ticker and compared Asset (close, open, high, low, ohlc4.. etc)
~~some other assets worth comparing:
Aussie vs Gold; Aussie vs ES; Btc vs ES; Copper vs ES
DRM StrategyOne of the ways I go when I develop strategies is by reducing the number of parameters and removing fixed parameters and levels.
In this strategy, I'm trying to create an RSI indicator with a dynamic length.
Length is computed based on the correlation between Price and its momentum.
You can set min and max values for the RSI, and if the correlation is close to 1, we'll be at a min RSI value. When it's -1, we'll be at the max level.
I got this idea from Sofien Kaabar's book.
The strategy is super simple, and there might be much room for improvement.
Performance on the deep backtesting is not excellent, so I think the strategy needs some filters for regimes, etc.
Thanks to @MUQWISHI for helping me code it.
Disclaimer
Please remember that past performance may not indicate future results.
Due to various factors, including changing market conditions, the strategy may no longer perform as well as in historical backtesting.
This post and the script don’t provide any financial advice.
Volume Weighted Exponential Moving Average Suite (VWEMA)This is a volume weighted exponential moving average (EMA) script that allows users to customize various parameters to fit their specific needs.
The script includes four different EMA styles: EMA, DEMA, TEMA, and EHMA. Users can choose which style they would like to use by selecting it in the input field. The script also allows users to customize the length of the EMA, with options for both a maximum and minimum length. Users can also choose to use a manual length or to use the dominant cycle within a range as the length.
In addition to these options, the script also includes the ability to turn on or off volume weighting and a daily reset feature that resets the EMA every day. There is also an option to turn on deviation bands, which show the standard deviation of the selected EMA.
Overall, this script offers a wide range of customization options to help users find the best EMA settings for their needs. It is an advanced tool that can be very helpful for traders looking to optimize their EMA strategy.
Cumulative length instead of cycle length
Double EMA Volume Weighted
Triple EMA Volume Weighted
EHMA Volume Weighted
Higher time frame
Deviation Bands
Squeeze Momentum MTF [LPWN]//ENGLISH
Squeeze momentum of lazy bear, multiple time frames, It gives you information if the cycles with high temporality momentums are in harmony, by default two more momentums are shown, I prefer to use only one extra, in the options you can change the time frame of the momentums, in addition to the momentums you can add the RSI and ADX, if the momentum look small, you can change the value of general scale to make them bigger, the table gives us information on how the momentums and the adx are, in the options you can set the candles to color according to the harmony of the momentums
// SPANISH
Squeeze momentum de lazy bear, multiple time frames, te da informacion si los ciclos con momentums de temporalidad alta estan en armonia,por defecto se muestran dos momentums mas, yo prefiero usar solo uno extra, en las opcoines puedes cambiar la temporalidad de los momentums, ademas de los momentums puedes agregar el RSI y el ADX, si el momentum se ve pequeño, puedes cambiar el valor de general scale para hacerlos mas grandes, la tabla nos da infomracion de como estan los momentums y el adx, en las opciones puedes poner que las velas se pongan del color de acuerdo a la armonia de los momentums
AlexD Market annual seasonalityThe indicator displays the percentage of bullish days with a given date over several years.
This allows you to determine the days of the year when the price usually goes up or down.
Indicator has a built-in "simple moving average" shifted back by half a period, due to which the delay of this smoothing is removed.
Slope NormalizerBrief:
This oscillator style indicator takes another indicator as its source and measures the change over time (the slope). It then isolates the positive slope values from the negative slope values to determine a 'normal' slope value for each.
** A 'normal' value of 1.0 is determined by the average slope plus the standard deviation of that slope.
The Scale
This indicator is not perfectly linear. The values are interpolated differently from 0.0 - 1.0 than values greater than 1.0.
From values 0.0 to 1.0 (positive or negative): it means that the value of the slope is less than 'normal' **.
Any value above 1.0 means the current slope is greater than 'normal' **.
A value of 2.0 means the value is the average plus 2x the standard deviation.
A value of 3.0 means the value is the average plus 3x the standard deviation.
A value greater than 4.0 means the value is greater than the average plus 4x the standard deviation.
Because the slope value is normalized, the meaning of these values can remain generally the same for different symbols.
Potential Usage Examples/b]
Using this in conjunction with an SMA or WMA may indicate a change in trend, or a change in trend-strength.
Any values greater than 4 indicate a very strong (and unusual) trend that may not likely be sustainable.
Any values cycling between +1.0 and -1.0 may mean indecision.
A value that is decreasing below 0.5 may predict a change in trend (slope may soon invert).
Band Pass Normalized Suite (BPNS)Outlier-Free Normalization and Band Pass Filtering
We present a technique for normalizing and filtering a given time series, source, in order to improve its stationarity and enhance its features. The technique includes two stages: outlier-free normalization and band pass filtering.
Outlier-Free Normalization:
In order to normalize source and reduce the impact of outliers, we first smooth the time series using an exponential moving average with a smoothing factor of alpha. The smoothed time series is then normalized by subtracting the minimum value within a given lookback period, dev_lookback, and dividing the result by the range (maximum - minimum) within the same lookback period. Outliers are detected and excluded from the normalization process by identifying values that are more than outlier_level standard deviations away from the exponentially smoothed average.
Band Pass Filtering:
After normalization, the time series is passed through a band pass filter to remove low and high frequency components. The specifics of the band pass filter implementation are not provided.
Code snippet:
bes(float source = close, float alpha = 0.7) =>
var float smoothed = na
smoothed := na(smoothed) ? source : alpha * source + (1 - alpha) * nz(smoothed )
max(source, outlier_level, dev_lookback)=>
var float max = na
src = array.new()
stdev = math.abs((source - bes(source, 0.1))/ta.stdev(source, dev_lookback))
array.push(src, stdev < outlier_level ? source : -1.7976931348623157e+308)
max := math.max(nz(max ), array.get(src, 0))
min(source, outlier_level, dev_lookback) =>
var float min = na
src = array.new()
stdev = math.abs((source - bes(source, 0.1))/ta.stdev(source, dev_lookback))
array.push(src, stdev < outlier_level ? source : 1.7976931348623157e+308)
min := math.min(nz(min ), array.get(src, 0))
min_max(src, outlier_level, dev_lookback) =>
(src - min(src, outlier_level, dev_lookback))/(max(src, outlier_level, dev_lookback) - min(src, outlier_level, dev_lookback)) * 100
To apply the outlier-free normalization and band pass filter to a given time series, source, the min_max() function can be called with the desired values for outlier_level and dev_lookback as arguments. For example:
normalized_source = min_max(source, 2, 50)
This will apply the outlier-free normalization and band pass filter to source, using an outlier_level of 2 standard deviations and a lookback period of 50 data points for both the normalization and outlier detection steps. The resulting normalized and filtered time series will be stored in normalized_source.
It is important to note that the choice of values for outlier_level and dev_lookback will have a significant impact on the resulting normalized and filtered time series. These values should be chosen carefully based on the characteristics of the input time series and the desired properties of the normalized and filtered output.
In conclusion, the outlier-free normalization and band pass filtering technique presented here provides a useful tool for preprocessing time series data and improving its stationarity and feature content. The flexibility of the method, through the choice of outlier_level and dev_lookback values, allows it to be tailored to the specific characteristics of the input time series.
Slope Normalized (SN)Introduction:
The Normalized Slope script is a technical indicator that aims to measure the strength and direction of a trend in a financial market. It does this by calculating the slope of the source data series, which can be any type of data (such as price, volume, or an oscillator) over a specified length of time. The slope is then normalized, meaning it is transformed to a scale between -1 and 1, with 0 representing a flat trend.
Methodology:
The Normalized Slope script uses an exponential smoothing function to smooth the source data series. The smoothing factor, or alpha, can be adjusted by the user through the input parameter "Pre Smoothing".
Next, the script calculates the slope of the smoothed data series by finding the average difference between the current value and the values of the previous "Length" periods. This slope is then normalized using a function that scales the data to a range of -1 to 1, with 0 representing a flat trend. The normalization function takes the minimum and maximum values of the slope, calculates the difference between them, and then scales the data to the range of -1 to 1.
The normalized slope is then smoothed again using another exponential smoothing function with a user-adjustable smoothing factor (the "Post Smoothing" input parameter). A center line representing a flat trend can also be plotted on the chart by enabling the "Center Line" input parameter. Additionally, the user can choose to display bounds at the -1 and 1 levels by enabling the "Bounds" input parameter.
Conclusion:
The Normalized Slope script provides traders with a visual representation of the strength and direction of a trend in a financial market. It can be used as a standalone indicator or in combination with other technical analysis tools to help traders make informed trading decisions.
Line OscillatorThe input parameters include src, the source data for the indicator, presmooth, an integer value that determines the number of periods to use for pre-smoothing the source data, length, an integer value that determines the number of periods to use for calculating the relative strength index (RSI), smoothtype, a string value that determines whether to use the Hull moving average (HMA) or the Jurik moving average (JMA) for smoothing the RSI, smooth, an integer value that determines the number of periods to use for smoothing the RSI, and power, a float value that determines the power to use for the JMA calculation.
The script then performs some calculations, including pre-smoothing the source data using an exponential moving average (EMA), calculating the RSI from the pre-smoothed data, and smoothing the RSI using either the HMA or the JMA, depending on the value of smoothtype. The script also includes a function called calc_jma that calculates the JMA from a given source data and parameters.
Finally, the script plots the smoothed RSI on the chart and includes horizontal lines at various levels as well as an optional volume bar.
Regime Filter [CHE]About:
A market regime filter is a tool used by traders and investors to identify the current state or "regime" of the market and adjust their investment strategies accordingly. This can involve identifying trends in market behavior, such as bullish or bearish trends, and using that information to make decisions about which assets to buy or sell.
Market regime filters can be based on a variety of factors, including economic indicators, market sentiment, and technical analysis. They are often used in conjunction with other trading strategies and can help traders and investors manage risk and optimize their returns.
It's important to note that market regime filters are not always accurate and can change over time, so it's important for traders and investors to regularly review and update their filters to ensure that they are relevant and effective.
Understanding the use of a regime filter in trading:
The importance of a trading filter cannot be overemphasized. As a matter of fact, the chances of any trading system making consistent returns over the long term depends on it trading in the right market environment — buying when the market is bullish and selling when the market is bearish. Some traders may want to stay out of the market when the conditions are unfavorable.
The heard of this Regime Filter is the well kown Andean Oscillator. The proposed indicator aims to measure the degree of variations of individual up-trends and down-trends in the price, thus allowing to highlight the direction and amplitude of a current trend.
Settings
Length : Determines the significance of the trends degree of variations measured by the indicator.
Signal Length : Moving average period of the signal line.
The regime filter uses the color yellow and blue, yellow stands for bullish and blue for bearish.
In daily use I have found that it makes sense to use it in different timeframes to identify meaningful trends.
best regards and I hope you enjoy this new indicator
Chervolino
McGinley Dynamic Apply Oscillator What McGinley Dynamic Apply Oscillator?
By understanding how McGinley Dynamic work, and calculate its change% then comparing those value to lasted change%, McGinley Dynamic Apply Oscillator was created
McGinley Dynamic Apply Oscillator, use 2 McGinley Dynamic apply with multiple MA Choice including : ALMA EMA HMA SMA SMMA(RMA) SWMA VWMA LSMA and ZLASMA and plot those data out in to 2-line, Short Length and Long Length
The signal can be created by Short Length line crossing Long Length Line. In the background, there are 4 color bar chart which define 4 meaning :
Blue : The difference between Short and Long Length line are increasing and be in + value
Light Blue : The difference between Short and Long Length line are decreasing and be in + value
Yellow/Orange : The difference between Short and Long Length line are increasing and be in - value
Red : The difference between Short and Long Length line are decreasing and be in – value
What made McGinley Dynamic Apply Oscillator?
McGinley Dynamic
MA Concept
Supertrend Direction Concept
Used of McGinley Dynamic Apply Oscillator
can be use as the confirmation indicator if trader apply the indicator to any trading strategy which already have trend identifier Indicator
can also be use as trend changer/switcher indicator
Impulse Alerts - Riccardo Di GiacomoThis is the Impulse indicator that allows you to receive alerts in the case one of the following situation occurs:
1) Buy Setup
- Price above Exponential Moving Average 260
- Moving Average 21 above Exponential Moving Average 260
- Moving Average 9 above Moving Average 21
- RSI(14) above 50
- Stochastic equal or below 20
2) Sell Setup
- Price below Exponential Moving Average 260
- Moving Average 21 below Exponential Moving Average 260
- Moving Average 9 below Moving Average 21
- RSI(14) below 50
- Stochastic equal or above 80
The Bollinger Bands represents another useful information:
- If the price is near the upper band when the first situation occurs, it is another green light, otherwise be careful
- If the price is near the lower band when the second situation occurs, it is another green light, otherwise be careful
Gedhusek MomentumSqueezeThis oscillator measures a strength of momentum.
About the indicator:
Unlike the classic momentum indicator, which only measures the distance between two points, this one has a more sophisticated calculation system to better show the reality of the markets. This is reached by including the distance between the highest and lowest point over certain period and an absolute distance of each bar over certain time period. By combining the distance between the highest and lowest price point with an absolute distance into mathematical formula, we get a final value representing the momentum strength.
The next great thing about this oscillator is that its values are relative to the previous ones. Thanks to this, we get a better understanding about the current situation given what has happened in the market before.
General rules:
Value of this indicator ranges from 0 to 100.
If the value is below 50, it means that there is very weak momentum and if the value is above 50, there is strong momentum.
The idea is that these values should oscillate, therefore we can more precisely predict when the momentum is going to increase or decline.
If the current value is below 20, the market has very low momentum and it should increase and if the current value is above 80, there is an extremely high momentum and it should decline.
What is absolute distance and why use it:
Lets say that we have 2 last bars. The first one starts at 100 and closes at 110 and the second one starts at 110 and closes at 105. So the price change would be of 5 points (from 100 to 105). This is not an ideal way because we punish volatile markets with no clear trend.
With an absolute distance, we would deal with given scenario like this. The first bar went from 100 to 110, resulting in distance of 10 points, and the second bar went from 110 to 105, resulting in distance of 5 points. No we add up these distances and we get the absolute distance --> 10+5 = 15
With this type of calculation we get more accurate information about momentum
Inputs:
- Analysis Period - Sets how many bars are going to be used for calculations
Oscillator ExtremesThe Oscillator Extremes indicator plots the normalized positioning of the selected oscillator versus the Bollinger Bands' upper and lower boundaries. Currently, this indicator has four different oscillators to choose from; RSI, CMO, CCI, and ROC.
When the oscillator pushes towards one extreme, it will bring the value of the prevailing line closer to zero. If the bullish or bearish line crosses the zero line, the oscillator is past the extreme of the Bollinger Band.
Example: If the RSI crosses over the upper boundary of the Bollinger, the bullish(green) line will cross under the zero line.
Crossovers of the bullish and bearish lines can indicate a shift in momentum and are a signal. Where the line crossing under, towards zero, is the prevailing trend. The plotted lines will highlight green(bullish) or red(bearish) to show the prevailing trend. This is similar to a DI+- crossover that is commonly associated with the ADX.
We have included an optional normalized ADX to help validate signals. The ADX will change color based on the slope of the ADX. Purple indicates a positive slope and white for a negative slope.
Vector MagnitudeThe pine indicator is a script for technical analysis of stock market data. It calculates the direction and magnitude of a moving average, and plots the result on a chart. The length of the moving average is specified by the user as an input parameter. The script uses the simple moving average (SMA) function from the TA-Lib library to calculate the average of the data. It then determines the direction of the vector by comparing the current value to the average. If the current value is greater than the average, the direction is set to 1. If it is less than the average, the direction is set to -1. Otherwise, the direction is set to 0. The magnitude of the vector is calculated using the Pythagorean theorem. The output is the magnitude of the vector, with the sign indicating the direction.
A trader may use this pine script to help identify trends in the stock market. By plotting the direction and magnitude of the moving average on a chart, the trader can quickly see whether the market is trending up or down, and how strong the trend is. This can help the trader make informed decisions about when to buy and sell stocks. Additionally, the script allows the user to customize the length of the moving average, which can be useful for analyzing different time frames and making more accurate predictions.
Exponential Smoothed RSII wanted to create a custom RSI to get clearer signals, so I coded this. It is an RSI average (to prevent the classic RSI in and out oversold/overbought zones) that is approaching the 0 and 100 levels with an exponential math formula.
If the "RSI smoothing factor" input increases, the rsi gets easily closer to the 0 and 100 limits.
This RSI will never be lower than 0 or higher than 100, its smoothing is asymptotic to the limits levels
I also added the possibility to change timeframe if you need
Note: the image is a simple confrontation between built-in RSI and exponentially smoothed RSI
LowHighFinderThis chart display how value change of (low,high,close,open) is considered as a factor for buying or selling. Each element take same weight when consider the final price. The price change over a certain threshold would be the decision point (buy/sell)
Factors considered in this chart
1.Quotes: High,low,close,open,volume. If one of them higher than previous day, then it increase, otherwise decreases.
2. Multipler: If you think one quote is more important than other (High more important than close, you can set multipler higher)
3. EMA smoother: It is using to balance the price effect. Like if price increased dramatically, EMA would notify whether could be a good time to sell. (Because high deviation between MA and price suggest price increase too fast)
4. Length of line: set length of line for you need
5. Percentage change: how much percentage change is considered a significant change? 5%? or 10%? In which case should it count toward the final indicator? Adjust percentage change needed, smaller for minutes chart (less than 10) higher for hours chart (10-20), even higher for day chart
Buy/Sell method:
1. When green dot appears, wait after price start to get close to moving average to find the low point and buy.
2. Reverse for red dot.
Fetch TrendsThis indicator can be used as a tool to measure the strength of the current trend. It is also trying to achieve to alert traders on when a trend can shift.
In order to achieve this, it uses three simple indicators:
1: 9 Simple moving average
2: 50 Simple moving average
3: Rsi (14)
The moving averages are used to define the current trend of the market, and the rsi is used to measure the strength. We use a color gradient to reach our second goal with this indicator.
The gradient is calculated based on the rsi value, which means the trader can use this indicator to visualize the strength of the current trend. It also helps to alert the trader when the trend starts to shift.
Lets say we use green to signal a strong positive trend, and blue for a weak positive trend. The candles are green in a strong uptrend, and are getting more blue once the trend starts to weaken.
As soon as the trend shifts from bullish to bearish, the bars become a diferent color.
True Momentum OscillatorThe True Momentum Oscillator (TMO) calculates the delta of the price using the open and close. We have taken the true momentum oscillator a step further and have added the momentum of the main signal (TMO) and the smooth signal line. We believe this helps give a clearer picture of price momentum and helps verify crossovers of the TMO and the smooth signal line. The momentum lines can also help confirm a divergence of the TMO. We have also added multiple moving average options so the user can customize the TMO to suit their needs.
TMO- Green when above Smooth Signal Line, red when below Smooth Signal Line
Smooth Signal- Gray Line
Histogram- TMO-Smooth Signal
TMO Momentum- Orange line
Smooth Signal Momentum- Yellow line
Overbought/Oversold regions- Gray highlighted boundaries
The TMO has defined overbought and oversold regions where either a crossover signal or divergence in the oscillator itself can be taken as a signal. Similar to the MACD, a crossover of the zero line by the TMO can also be utilized as a signal.
