The Perfect Support & ResistanceSupport & Resistance drawn based on overbought & oversold RSI . where the overbought acts as resistance and oversold acts as support.
It has 2 levels (for support and resistance - i call them level_n_high or level_n_low) for each lookback period. it checks the highest pivot and the lowest pivot based on the lookback period then we compare if rsi is higher than the highest pivot or the lowest pivot and we also check if rsi is overbought or oversold and if the statement is true, then we assign the high to the variable level_n_high or level_n_low. n being the number of levels. in total there are 5 levels with both high & low for 5 lookback periods. This is basically how the code works.
these levels can be accessed at any timeframe. the defaults are 5m and 30m.
RSI settings: (default)
-------------------
length - 14
source - close
overbought - 70
oversold - 30
lookback settings: (default)
---------------------
lookback_0 - 200
lookback_1 - 100
lookback_2 - 50
lookback_3 - 20
lookback_4 - 10
Timeframe Settings: (default)
-------------------
htf1 - 5m
htf2 - 30m
Enjoy!
Relative Strength Index (RSI)
RSI Impact Heat Map [Trendoscope]Here is a simple tool to measure and display outcome of certain RSI event over heat map.
🎲 Process
🎯Event
Event can be either Crossover or Crossunder of RSI on certain value.
🎯Measuring Impact
Impact of the event after N number of bars is measured in terms of highest and lowest displacement from the last close price. Impact can be collected as either number of times of ATR or percentage of price. Impact for each trigger is recorded separately and stored in array of custom type.
🎯Plotting Heat Map
Heat map is displayed using pine tables. Users can select heat map size - which can vary from 10 to 90. Selecting optimal size is important in order to get right interpretation of data. Having higher number of cells can give more granular data. But, chart may not fit into the window. Having lower size means, stats are combined together to get less granular data which may not give right picture of the results. Default value for size is 50 - meaning data is displayed in 51X51 cells.
Range of the heat map is adjusted automatically based on min and max value of the displacement. In order to filter out or merge extreme values, range is calculated based on certain percentile of the values. This will avoid displaying lots of empty cells which can obscure the actual impact.
🎲 Settings
Settings allow users to define their event, impact duration and reference, and few display related properties. The description of these parameters are as below:
🎲 Use Cases
In this script, we have taken RSI as an example to measure impact. But, we can do this for any event. This can be price crossing over/under upper/lower bollinger bands, moving average crossovers or even complex entry or exit conditions. Overall, we can use this to plot and evaluate our trade criteria.
🎲 Interpretation
Q1 - If more coloured dots appear on the top right corner of the table, then the event is considered to trigger high volatility and high risk environment.
Q2 - If more coloured dots appear on the top left corner, then the events are considered to trigger bearish environment.
Q3 - If more coloured dots appear on the bottom left corner of the chart, then the events are considered insignificant as they neither generate higher displacement in positive or negative side. You can further alter outlier percentage to reduce the bracket and hence have higher distribution move towards
Q4 - If more coloured dots appear on the bottom right corner, then the events are considered to trigger bullish environment.
Will also look forward to implement this as library so that any conditions or events can be plugged into it.
RSI Multi Symbol/Time Frame DetectorThis code is an implementation of the Relative Strength Index (RSI) indicator, which is a popular momentum indicator used in technical analysis. The RSI measures the strength of an asset's price action and provides information on whether the asset is overbought or oversold. The code also calculates a moving average of the RSI and allows the user to choose the type of moving average to be calculated (SMA, EMA, SMMA, WMA, or VWMA).
The user can select from different time frames (5, 15, 60, or 240), symbols (SP:SPX, OANDA:EURUSD, or OANDA:NZDUSD), RSI lengths, and moving average types and lengths.
The code starts by defining a function called "ma" for calculating different types of moving averages. This function takes as input the source data for the moving average calculation (the RSI), the length of the moving average, and the type of moving average. The function uses a switch statement to return the appropriate calculation based on the inputted moving average type.
Next, the code calculates the RSI and its moving average. The RSI is calculated using the well-known formula for the RSI, which involves calculating the average gains and losses over a specified period of time and then dividing the average gains by the average losses. The moving average is calculated using the "ma" function defined earlier.
Finally, the code allows the user to choose the symbol and time frame to be used in the RSI calculation, as well as the length of the RSI and the moving average, and the type of moving average. The user can choose from three symbols (SP:SPX, OANDA:EURUSD, OANDA:NZDUSD) and four time frames (5, 15, 60, and 240 minutes). The code then uses the "request.security" function to retrieve the RSI calculation for the selected symbol and time frame.
Note: This code is example for you to use multi timeframe/symbol in your indicator or Strategy , also prevent Repainting Calculation
change in rsiThis indicator will show how fast the rsi of a symbol is changing. you can see this as a differentiation function on rsi .
this will show the change in rsi in percentage.
Ex: suppose the rsi of a symbol at present is 60 and the previous value of rsi was 52,
as you can see the rsi has increased, which is a sign of the symbol being bullish .
this indicator will tell by what percentage the rsi of the symbol has increased or decreased.
for the above example, the change in rsi is 15.38% increase.
this is set to default chart time-frame.
JSS Table - RSI, DI+, DI-, ADXSimple table to show the values for indicators which can be used to initiate trades:
RSI: Long above 55 // Short below 45 // Choppy between 45-55
DI+: Long above 25
DI-: Short above 25
Note when to avoid trend trades:
- If DI+ and DI- are both below 25 then market is choppy
- If RSI is between 45-55 then market is choppy
Moving Average Cross and RSIThis is the updated version of the MAC cross Short/ Long indicator i had posted earlier in 2022.
This script includes a RSI and EMA of the RSI with fixed OB and OS Levels.
The purpose is to refine the amount of trades taken from the moving average cross on the 30 minute timeframe.
In the overlay, the red and green dots indicate weather the moving cross is a long or a short signal.
The theory when back tested is:
When the short signal is given, the EMA must be below 30 to enter a short.
When the long signal is given, the EMA must be above 64 to enter a long, anything in between is a false signal.
Only the first dot is meant to be a long or a short signal, not meant to be interpreted as being consecutive.
The data window is meant to be built in a way to easily set up indicators or strategies using Tradelab.ai software.
Any Oscillator Underlay [TTF]We are proud to release a new indicator that has been a while in the making - the Any Oscillator Underlay (AOU) !
Note: There is a lot to discuss regarding this indicator, including its intent and some of how it operates, so please be sure to read this entire description before using this indicator to help ensure you understand both the intent and some limitations with this tool.
Our intent for building this indicator was to accomplish the following:
Combine all of the oscillators that we like to use into a single indicator
Take up a bit less screen space for the underlay indicators for strategies that utilize multiple oscillators
Provide a tool for newer traders to be able to leverage multiple oscillators in a single indicator
Features:
Includes 8 separate, fully-functional indicators combined into one
Ability to easily enable/disable and configure each included indicator independently
Clearly named plots to support user customization of color and styling, as well as manual creation of alerts
Ability to customize sub-indicator title position and color
Ability to customize sub-indicator divider lines style and color
Indicators that are included in this initial release:
TSI
2x RSIs (dubbed the Twin RSI )
Stochastic RSI
Stochastic
Ultimate Oscillator
Awesome Oscillator
MACD
Outback RSI (Color-coding only)
Quick note on OB/OS:
Before we get into covering each included indicator, we first need to cover a core concept for how we're defining OB and OS levels. To help illustrate this, we will use the TSI as an example.
The TSI by default has a mid-point of 0 and a range of -100 to 100. As a result, a common practice is to place lines on the -30 and +30 levels to represent OS and OB zones, respectively. Most people tend to view these levels as distance from the edges/outer bounds or as absolute levels, but we feel a more way to frame the OB/OS concept is to instead define it as distance ("offset") from the mid-line. In keeping with the -30 and +30 levels in our example, the offset in this case would be "30".
Taking this a step further, let's say we decided we wanted an offset of 25. Since the mid-point is 0, we'd then calculate the OB level as 0 + 25 (+25), and the OS level as 0 - 25 (-25).
Now that we've covered the concept of how we approach defining OB and OS levels (based on offset/distance from the mid-line), and since we did apply some transformations, rescaling, and/or repositioning to all of the indicators noted above, we are going to discuss each component indicator to detail both how it was modified from the original to fit the stacked-indicator model, as well as the various major components that the indicator contains.
TSI:
This indicator contains the following major elements:
TSI and TSI Signal Line
Color-coded fill for the TSI/TSI Signal lines
Moving Average for the TSI
TSI Histogram
Mid-line and OB/OS lines
Default TSI fill color coding:
Green : TSI is above the signal line
Red : TSI is below the signal line
Note: The TSI traditionally has a range of -100 to +100 with a mid-point of 0 (range of 200). To fit into our stacking model, we first shrunk the range to 100 (-50 to +50 - cut it in half), then repositioned it to have a mid-point of 50. Since this is the "bottom" of our indicator-stack, no additional repositioning is necessary.
Twin RSI:
This indicator contains the following major elements:
Fast RSI (useful if you want to leverage 2x RSIs as it makes it easier to see the overlaps and crosses - can be disabled if desired)
Slow RSI (primary RSI)
Color-coded fill for the Fast/Slow RSI lines (if Fast RSI is enabled and configured)
Moving Average for the Slow RSI
Mid-line and OB/OS lines
Default Twin RSI fill color coding:
Dark Red : Fast RSI below Slow RSI and Slow RSI below Slow RSI MA
Light Red : Fast RSI below Slow RSI and Slow RSI above Slow RSI MA
Dark Green : Fast RSI above Slow RSI and Slow RSI below Slow RSI MA
Light Green : Fast RSI above Slow RSI and Slow RSI above Slow RSI MA
Note: The RSI naturally has a range of 0 to 100 with a mid-point of 50, so no rescaling or transformation is done on this indicator. The only manipulation done is to properly position it in the indicator-stack based on which other indicators are also enabled.
Stochastic and Stochastic RSI:
These indicators contain the following major elements:
Configurable lengths for the RSI (for the Stochastic RSI only), K, and D values
Configurable base price source
Mid-line and OB/OS lines
Note: The Stochastic and Stochastic RSI both have a normal range of 0 to 100 with a mid-point of 50, so no rescaling or transformations are done on either of these indicators. The only manipulation done is to properly position it in the indicator-stack based on which other indicators are also enabled.
Ultimate Oscillator (UO):
This indicator contains the following major elements:
Configurable lengths for the Fast, Middle, and Slow BP/TR components
Mid-line and OB/OS lines
Moving Average for the UO
Color-coded fill for the UO/UO MA lines (if UO MA is enabled and configured)
Default UO fill color coding:
Green : UO is above the moving average line
Red : UO is below the moving average line
Note: The UO naturally has a range of 0 to 100 with a mid-point of 50, so no rescaling or transformation is done on this indicator. The only manipulation done is to properly position it in the indicator-stack based on which other indicators are also enabled.
Awesome Oscillator (AO):
This indicator contains the following major elements:
Configurable lengths for the Fast and Slow moving averages used in the AO calculation
Configurable price source for the moving averages used in the AO calculation
Mid-line
Option to display the AO as a line or pseudo-histogram
Moving Average for the AO
Color-coded fill for the AO/AO MA lines (if AO MA is enabled and configured)
Default AO fill color coding (Note: Fill was disabled in the image above to improve clarity):
Green : AO is above the moving average line
Red : AO is below the moving average line
Note: The AO is technically has an infinite (unbound) range - -∞ to ∞ - and the effective range is bound to the underlying security price (e.g. BTC will have a wider range than SP500, and SP500 will have a wider range than EUR/USD). We employed some special techniques to rescale this indicator into our desired range of 100 (-50 to 50), and then repositioned it to have a midpoint of 50 (range of 0 to 100) to meet the constraints of our stacking model. We then do one final repositioning to place it in the correct position the indicator-stack based on which other indicators are also enabled. For more details on how we accomplished this, read our section "Binding Infinity" below.
MACD:
This indicator contains the following major elements:
Configurable lengths for the Fast and Slow moving averages used in the MACD calculation
Configurable price source for the moving averages used in the MACD calculation
Configurable length and calculation method for the MACD Signal Line calculation
Mid-line
Note: Like the AO, the MACD also technically has an infinite (unbound) range. We employed the same principles here as we did with the AO to rescale and reposition this indicator as well. For more details on how we accomplished this, read our section "Binding Infinity" below.
Outback RSI (ORSI):
This is a stripped-down version of the Outback RSI indicator (linked above) that only includes the color-coding background (suffice it to say that it was not technically feasible to attempt to rescale the other components in a way that could consistently be clearly seen on-chart). As this component is a bit of a niche/special-purpose sub-indicator, it is disabled by default, and we suggest it remain disabled unless you have some pre-defined strategy that leverages the color-coding element of the Outback RSI that you wish to use.
Binding Infinity - How We Incorporated the AO and MACD (Warning - Math Talk Ahead!)
Note: This applies only to the AO and MACD at time of original publication. If any other indicators are added in the future that also fall into the category of "binding an infinite-range oscillator", we will make that clear in the release notes when that new addition is published.
To help set the stage for this discussion, it's important to note that the broader challenge of "equalizing inputs" is nothing new. In fact, it's a key element in many of the most popular fields of data science, such as AI and Machine Learning. They need to take a diverse set of inputs with a wide variety of ranges and seemingly-random inputs (referred to as "features"), and build a mathematical or computational model in order to work. But, when the raw inputs can vary significantly from one another, there is an inherent need to do some pre-processing to those inputs so that one doesn't overwhelm another simply due to the difference in raw values between them. This is where feature scaling comes into play.
With this in mind, we implemented 2 of the most common methods of Feature Scaling - Min-Max Normalization (which we call "Normalization" in our settings), and Z-Score Normalization (which we call "Standardization" in our settings). Let's take a look at each of those methods as they have been implemented in this script.
Min-Max Normalization (Normalization)
This is one of the most common - and most basic - methods of feature scaling. The basic formula is: y = (x - min)/(max - min) - where x is the current data sample, min is the lowest value in the dataset, and max is the highest value in the dataset. In this transformation, the max would evaluate to 1, and the min would evaluate to 0, and any value in between the min and the max would evaluate somewhere between 0 and 1.
The key benefits of this method are:
It can be used to transform datasets of any range into a new dataset with a consistent and known range (0 to 1).
It has no dependency on the "shape" of the raw input dataset (i.e. does not assume the input dataset can be approximated to a normal distribution).
But there are a couple of "gotchas" with this technique...
First, it assumes the input dataset is complete, or an accurate representation of the population via random sampling. While in most situations this is a valid assumption, in trading indicators we don't really have that luxury as we're often limited in what sample data we can access (i.e. number of historical bars available).
Second, this method is highly sensitive to outliers. Since the crux of this transformation is based on the max-min to define the initial range, a single significant outlier can result in skewing the post-transformation dataset (i.e. major price movement as a reaction to a significant news event).
You can potentially mitigate those 2 "gotchas" by using a mechanism or technique to find and discard outliers (e.g. calculate the mean and standard deviation of the input dataset and discard any raw values more than 5 standard deviations from the mean), but if your most recent datapoint is an "outlier" as defined by that algorithm, processing it using the "scrubbed" dataset would result in that new datapoint being outside the intended range of 0 to 1 (e.g. if the new datapoint is greater than the "scrubbed" max, it's post-transformation value would be greater than 1). Even though this is a bit of an edge-case scenario, it is still sure to happen in live markets processing live data, so it's not an ideal solution in our opinion (which is why we chose not to attempt to discard outliers in this manner).
Z-Score Normalization (Standardization)
This method of rescaling is a bit more complex than the Min-Max Normalization method noted above, but it is also a widely used process. The basic formula is: y = (x – μ) / σ - where x is the current data sample, μ is the mean (average) of the input dataset, and σ is the standard deviation of the input dataset. While this transformation still results in a technically-infinite possible range, the output of this transformation has a 2 very significant properties - the mean (average) of the output dataset has a mean (μ) of 0 and a standard deviation (σ) of 1.
The key benefits of this method are:
As it's based on normalizing the mean and standard deviation of the input dataset instead of a linear range conversion, it is far less susceptible to outliers significantly affecting the result (and in fact has the effect of "squishing" outliers).
It can be used to accurately transform disparate sets of data into a similar range regardless of the original dataset's raw/actual range.
But there are a couple of "gotchas" with this technique as well...
First, it still technically does not do any form of range-binding, so it is still technically unbounded (range -∞ to ∞ with a mid-point of 0).
Second, it implicitly assumes that the raw input dataset to be transformed is normally distributed, which won't always be the case in financial markets.
The first "gotcha" is a bit of an annoyance, but isn't a huge issue as we can apply principles of normal distribution to conceptually limit the range by defining a fixed number of standard deviations from the mean. While this doesn't totally solve the "infinite range" problem (a strong enough sudden move can still break out of our "conceptual range" boundaries), the amount of movement needed to achieve that kind of impact will generally be pretty rare.
The bigger challenge is how to deal with the assumption of the input dataset being normally distributed. While most financial markets (and indicators) do tend towards a normal distribution, they are almost never going to match that distribution exactly. So let's dig a bit deeper into distributions are defined and how things like trending markets can affect them.
Skew (skewness): This is a measure of asymmetry of the bell curve, or put another way, how and in what way the bell curve is disfigured when comparing the 2 halves. The easiest way to visualize this is to draw an imaginary vertical line through the apex of the bell curve, then fold the curve in half along that line. If both halves are exactly the same, the skew is 0 (no skew/perfectly symmetrical) - which is what a normal distribution has (skew = 0). Most financial markets tend to have short, medium, and long-term trends, and these trends will cause the distribution curve to skew in one direction or another. Bullish markets tend to skew to the right (positive), and bearish markets to the left (negative).
Kurtosis: This is a measure of the "tail size" of the bell curve. Another way to state this could be how "flat" or "steep" the bell-shape is. If the bell is steep with a strong drop from the apex (like a steep cliff), it has low kurtosis. If the bell has a shallow, more sweeping drop from the apex (like a tall hill), is has high kurtosis. Translating this to financial markets, kurtosis is generally a metric of volatility as the bell shape is largely defined by the strength and frequency of outliers. This is effectively a measure of volatility - volatile markets tend to have a high level of kurtosis (>3), and stable/consolidating markets tend to have a low level of kurtosis (<3). A normal distribution (our reference), has a kurtosis value of 3.
So to try and bring all that back together, here's a quick recap of the Standardization rescaling method:
The Standardization method has an assumption of a normal distribution of input data by using the mean (average) and standard deviation to handle the transformation
Most financial markets do NOT have a normal distribution (as discussed above), and will have varying degrees of skew and kurtosis
Q: Why are we still favoring the Standardization method over the Normalization method, and how are we accounting for the innate skew and/or kurtosis inherent in most financial markets?
A: Well, since we're only trying to rescale oscillators that by-definition have a midpoint of 0, kurtosis isn't a major concern beyond the affect it has on the post-transformation scaling (specifically, the number of standard deviations from the mean we need to include in our "artificially-bound" range definition).
Q: So that answers the question about kurtosis, but what about skew?
A: So - for skew, the answer is in the formula - specifically the mean (average) element. The standard mean calculation assumes a complete dataset and therefore uses a standard (i.e. simple) average, but we're limited by the data history available to us. So we adapted the transformation formula to leverage a moving average that included a weighting element to it so that it favored recent datapoints more heavily than older ones. By making the average component more adaptive, we gained the effect of reducing the skew element by having the average itself be more responsive to recent movements, which significantly reduces the effect historical outliers have on the dataset as a whole. While this is certainly not a perfect solution, we've found that it serves the purpose of rescaling the MACD and AO to a far more well-defined range while still preserving the oscillator behavior and mid-line exceptionally well.
The most difficult parts to compensate for are periods where markets have low volatility for an extended period of time - to the point where the oscillators are hovering around the 0/midline (in the case of the AO), or when the oscillator and signal lines converge and remain close to each other (in the case of the MACD). It's during these periods where even our best attempt at ensuring accurate mirrored-behavior when compared to the original can still occasionally lead or lag by a candle.
Note: If this is a make-or-break situation for you or your strategy, then we recommend you do not use any of the included indicators that leverage this kind of bounding technique (the AO and MACD at time of publication) and instead use the Trandingview built-in versions!
We know this is a lot to read and digest, so please take your time and feel free to ask questions - we will do our best to answer! And as always, constructive feedback is always welcome!
Multi Timeframe Stochastic RSI ScreenerThis script is also a Stochastic RSI Screener, but it allows users to choose one specific symbol and three timeframes of that symbol to monitor at once.
RSI TREND FILTERRSI TREND Filter on Chart
RSI scaled to fit on chart instead of oscillator, Trend Analysis is easy and Hidden Divergence is revealed using this indicator. This indicator is an aim to reduce confusing RSI Situations. The Oversold and Overbought lines help to determine the price conditions so its easy to avoid Traps.
Oversold and Overbought conditions are marked on Chart to make it useful to confirm a Buy or Sell Signals.
RSI 50 level is plotted with reference to EMA50 and Oversold and Overbought Conditions are calculated accordingly.
Uptrend: RSI Cloud / Candles above RSI 50 Level
Down Trend: RSI Cloud / Candles below RSI 50 Level
Sideways : Candles in the Gray Area above and below RSI 50 Level
Default RSI (14) : is the Candlestick pattern itself
Disclaimer: Use Solely at your own Risk.
Stochastic RSI ScreenerStochastic RSI Screener is built as an indicator and can be applied to any chart.
It gives users the ability to choose 5 specific symbols to watch and then specify the required options to change the RSI and Stochastic settings in a way that fits their needs.
This screener shows the values of (CURRENT PRICE, RSI, K-VALUE, D-VALUE) for each one of the specified symbols. It will do the calculations based on the currently opened timeframe for all symbols.
AII - Average indicator of indicatorsThis Pine Script for TradingView is a technical analysis tool that visualizes the average of several popular indicators in the trading world. The indicators included are the RSI (Relative Strength Index), RVI (Relative Vigor Index), Stochastic RSI, Williams %R, relative MACD (ranging from 0 to 100), and Bollinger Bands price distance from 0 to 100. The script uses the "input" function to customize the length of the indicators and the "plot" function to display the results on the chart. In addition, options are included to turn off certain indicators and change the line colors if the user desires. All indicators can also be activated independently, allowing the user to see only the indicators they want. It is also mentioned that the script will be improved in the future to offer a better user experience. The calculated values are calculated with the default EMA of 14. Overall, this script is an excellent option for those looking for a combined view of several important indicators for making trading decisions.
Table rsi multiframes(by Lc_M)- Simultaneous display of RSI values on cells corresponding to each selected timeframe, organized in an intuitive table, adjustable in size and position.
- Color indicator on each cell that presents RSI values within the overbought and oversold levels. example: if the user wants to set the O.S/O.B levels to 20 - 80, the colored cells will only appear at "RSI" => 80 and "RSI" <= 20.
- Free configuration of graphic times, lengths and O.B/O.S, according to user standards
RSI Overbought/Oversold + Divergence IndicatorDESCRIPTION:
This script combines the Relative Strength Index ( RSI ), Moving Average and Divergence indicator to make a better decision when to enter or exit a trade.
- The Moving Average line (MA) has been made hidden by default but enhanced with an RSIMA cloud.
- When the RSI is above the selected MA it turns into green and when the RSI is below the select MA it turns into red.
- When the RSI is moving into the Overbought or Oversold area, some highlighted areas will appear.
- When some divergences or hidden divergences are detected an extra indication will be highlighted.
- When the divergence appear in the Overbought or Oversold area the more weight it give to make a decision.
- The same color pallet has been used as the default candlestick colors so it looks familiar.
HOW TO USE:
The prerequisite is that we have some knowledge about the Elliot Wave Theory, the Fibonacci Retracement and the Fibonacci Extension tools.
Wave 1
(1) When we receive some buy signals we wait until we receive some extra indications.
(2) On the RSI Overbought/Oversold + Divergence Indicator we can see a Bullish Divergence and our RSI is changing from red to green ( RSI is higher then the MA).
(3) If we are getting here into the trade then we need to use a stop loss. We put our stop loss 1 a 2 pips just below the lowest wick. We also invest maximum 50% of the total amount we want to invest.
Wave 2
(4) Now we wait until we see a clear reversal and here we starting to use the Fibonacci Retracement tool. We draw a line from the lowest point of wave(1) till the highest point of wave (1). When we are retraced till the 0.618 fib also called the golden ratio we check again the RSI Overbought/Oversold + Divergence Indicator. When we see a reversal we do our second buy. We set again a stop loss just below the lowest wick (this is the yellow line on the chart). We also move the stop loss we have set in step (3) to this level.
Wave 3
(5) To identify how far the uptrend can go we need to use the Fibonacci Extension tool. We draw a line from the lowest point of wave(1) till the highest point of wave (1) and draw it back to the lowest point of wave (2). Wave (3) is most of the time the longest wave and can go till it has reached the 1.618 or 2.618 fib. On the 1.618 we can take some profit. If we don't want to sell we move our stop loss to the 1 fib line (yellow line on the chart).
(6) We wait until we see a clear reversal on the Overbought/Oversold + Divergence Indicator and sell 33% to 50% of our investment.
Wave 4
(7) Now we wait again until we see a clear reversal and here we starting to use the Fibonacci Retracement tool. We draw a line from the lowest point of wave(2) till the highest point of wave (3). When we are retraced till the 0.618 fib also called the golden ratio we check again the RSI Overbought/Oversold + Divergence Indicator. When we see a reversal we buy again. We set again a stop loss just below the lowest wick (this is the yellow line on the chart).
(8) If we bought at the first reversal ours stop los was triggered (9) and we got out of the trade.
(9) If we did not bought at step (7) because our candle did not hit the 0.618 fib or we got stopped out of the trade we buy again at the reversal.
Wave 5
(10) To identify how far the uptrend can go we need to use the Fibonacci Extension tool. We draw a line from the lowest point of wave(2) till the highest point of wave (3) and draw it back to the lowest point of wave (4). Most of the time wave 5 goes up till it has reached the 1 fib. And that is the point where we got out of the trade with all of our investment. In this trade we got out of the trade a bit earlier. We received the sell signals and got a reversal on the Overbought/Oversold + Divergence Indicator.
We are hoping you learned something so you can make better decisions when to get into or out of a trade.
If you have any question just drop it into the comments below.
FEATURES:
• You can show/hide the RSI .
• You can show/hide the MA.
• You can show/hide the lRSIMA cloud.
• You can show/hide the Stoch RSI cloud.
• You can show/hide and adjust the Overbought and Oversold zones.
• You can show/hide and adjust the Overbought Extended and Oversold Extended zones.
• You can show/hide the Overbought and Oversold highlighted zones.
• Etc...
HOW TO GET ACCESS TO THE SCRIPT:
• Favorite the script and add it to your chart.
REMARKS:
• This advice is NOT financial advice.
• We do not provide personal investment advice and we are not a qualified licensed investment advisor.
• All information found here, including any ideas, opinions, views, predictions, forecasts, commentaries, suggestions, or stock picks, expressed or implied herein, are for informational, entertainment or educational purposes only and should not be construed as personal investment advice.
• We will not and cannot be held liable for any actions you take as a result of anything you read here.
• We only provide this information to help you make a better decision.
• While the information provided is believed to be accurate, it may include errors or inaccuracies.
Good Luck and have fun,
The CryptoSignalScanner Team
RSI Multi Alerts MTFThis indicator won't plot anything to the chart.
Please follow steps below to set your alarms based on RSI oversold and overbought levels:
1) Add indicator to the chart
2) Go to settings
3) Choose up to 8 different symbols to get alert notification
4) Choose up to 4 different timeframes
5) Set overbought and oversold levels
6) Once all is set go back to the chart and click on 3 dots to set alert in this indicator, rename your alert and confirm
7) You can remove indicator after alert is set and it'll keep working as expected
What is does:
This indicator will generate alerts based on symbols, timeframes and RSI levels settings.
It will consider overbought and oversold levels to alert in each symbol and each timeframe selected. Once these levels are achieved it will send an alert with the following information:
- Symbol name (BTC, ETH, LTC)
- Specific RSI level achieved (e.g: RSI 30, RSI 70 or any custom level)
- Timeframe (e.g: 5m, 1h, 1D)
- Current symbol price
This script will request RSI OB/OS information through request.security() function from all different symbols and timeframes settings. It also requests symbols' price (close).
Due to Tradingview limitation (40 requests calls) it can only request information for 8 symbols for this script (8 symbols X 4 timeframes = 32 + 8 symbols' price (close) = 40)
Standard symbols are Binance USDT-M Futures but you can choose any symbol from Tradingview.
Standard timeframes are 5m|15m|1h|4h but you can choose from a list.
Standard overbought and oversold levels are 70 and 30 but you can change it to other integer values.
Feel free to give feedbacks on comments section below.
Enjoy!
RSI Pull-BackA pull-back occurs whenever the price or the value of an indicator breaks a line and comes back to test it before continuing in the prevailing trend.
The RSI has oversold and overbought levels such as 20 and 80 and whenever the market breaks them returns to normality, we can await a pull-back to them before the reversal continues.
This indicator shows the following signals:
* A bullish signal is generated whenever the RSI surpasses the chosen oversold level then directly shapes a pull-back to it without breaking it again.
* A bearish signal is generated whenever the RSI breaks the chosen overbought level then directly shapes a pull-back to it without surpassing it again.
Rich Robin Index, The Crypto Fear & Greed Index with RSI Trend The Relative Strength Index (RSI) is a technical indicator based on price movements that is used to determine whether a particular asset is overbought or oversold. It measures the ratio of rising to falling prices over a certain period of time.
The Fear & Greed Index, on the other hand, is a composite index that tracks the sentiment of the crypto market. It is based on seven indicators, each of which measures a different aspect of market behavior. These indicators are: Safe Haven Demand, Stock Price Breadth, Market Momentum, Stock Price Strength, Put and Call Options, Junk Bond Demand, and Market Volatility.
The combination of the RSI and the Fear & Greed Index can provide valuable insights for crypto traders. The RSI can help identify overbought and oversold conditions, while the Fear & Greed Index can give an overall sense of the sentiment in the market. Together, they can provide a more complete picture of the market conditions. For example, if the RSI is indicating that an asset is overbought, but the Fear & Greed Index is showing that the market is still in a state of fear, it may be a good time to sell. On the other hand, if the RSI is indicating that an asset is oversold, but the Fear & Greed Index is showing that the market is in a state of greed, it may be a good time to buy.
Overall, the combination of the RSI and the Fear & Greed Index can provide useful information for traders to make more informed decisions, by giving a sense of the market conditions, and providing a way to identify overbought and oversold conditions.
RSI Accumulation/Distribution [M]Hello everyone,
After my long tests, I observed that the rate of change of direction of the price was high after the periods when the RSI spent a long time outside the band. As a result of my observations, I prepared this indicator.
This indicator shows you the accumulation and distribution areas that occur outside the rsi band.
There are 3 different levels available.
Level 1 = 5 Bars
Level 2 = 7 Bars
Level 3 = 9 Bars
For example, if the RSI spends more than 9 bars below the 30 level or above the 70 level, it will paint that area red. Levels can be changed from the indicator settings. The rsi is smoothed with simple moving average to reduce fake signals.
Using the RSI A/D indicator with different indicators or patterns will increase your success rate.
Examples:
Adaptive RSI/Stochastic (ARSIS)As a trader, one of the most important aspects of technical analysis is identifying the dominant cycle of the market. The dominant cycle, also known as the market's "heartbeat," can provide valuable information on the current market trend and potential future price movements. One way to measure the dominant cycle is through the use of the MESA Adaptation - MAMA Cycle function, which is a part of the Dominant Cycle Estimators library.
I have developed an "Adaptive RSI/Stochastic" indicator that incorporates the MAMA Cycle function to provide more accurate and reliable signals. The indicator uses the MAMA Cycle function to calculate the period of the data, which is then used as a parameter in the calculation of the RSI and Stochastic indicators. By adapting the calculation of these indicators to the dominant cycle of the market, the resulting signals are more in tune with the current market conditions and can provide a more accurate representation of the current trend.
The MAMA Cycle function is a powerful tool that utilizes advanced mathematical techniques to accurately calculate the dominant cycle of the market. It takes into account the dynamic nature of the market and adapts the calculation of the period to the current conditions. The result is a more accurate and reliable measurement of the market's dominant cycle, which can be used to improve the performance of other indicators and trading strategies.
In conclusion, the Adaptive RSI/Stochastic indicator that I have developed, which incorporates the MAMA Cycle function, is a valuable tool for any trader looking to improve their technical analysis. By adapting the calculation of the RSI and Stochastic indicators to the dominant cycle of the market, the resulting signals are more in tune with the current market conditions and can provide a more accurate representation of the current trend.
Huge thank you to @lastguru for making this possible!
RSI Multi Length With Divergence Alert [Skiploss]This is a modified indicator base code from RSI Multi Length and we will add some of functions by finding a classic/hidden divergence and alert.
The indicator returns information over RSI using multiple periods and calculates the percentage of overbought and oversold by overbought divided by oversold.
To find the divergence and hidden divergence we use base code from platform (Divergence Indicator) but change the input from normal to the average (RSI Multi Length).
RSI Settings
Maximum Length is maximum period.
Minimum Length is minimum period.
Overbought Level is value of the overbought level .
Oversold Level is value of the oversold level.
Source is input source of the indicator.
Divergence Settings
Pivot Right is value look back to the right side.
Pivot Left is value look back to the left side.
Max Range is maximum range value.
Min Range is minimum range value.
Alert Settings
It will be part of display of Divergence and Hidden Divergence.
Style Settings
Color of overbought/oversold/Bullish/Bearish which you can change as you wish.
Supply and Demand Zone ConfirmationHello traders and investors,
Today, I am going to share an indicator that I made by mixing RSI and CCI in different timeframe. You can use this indicator in various ways, however the best possible way I would recommend you to use it is to combine it with price action. I would suggest to play with, so you can decide if it works the best for you.
The whole purpose of making this indicator was to eliminate confusion around different indicators for overbought and oversold and many other headaches. You use price action and you are looking for confirmation to see there is a PRZ? here is your indicator. I found there are certain patterns with CCI and RSI in higher timeframe which helps to find the PRZ and I made this indicator with it.
You can choose to use this indicator in different timeframe. But you have to consider, the lower timeframe you'll go, you will get more signals but the effectiveness goes down with it. Also, if you are willing to change the time frame, You have to change some settings as well which I'll get into it in a moment.
The default settings are for 30min timeframe with these settings.
ibb.co
In case you would like to go to 15min time frame, here is the suggested changes in the setting.
ibb.co
I would suggest to play with different timeframe to find the suitable setting for the pairs you would like to trade. The main goal is you have to choose first CCI one timeframe higher ( if you are in 5min chart, first CCI should be at least 15 or 30min) and the second CCI one timeframe higher than first CCI (if you choose 15min for first CCI, go with 1hr for second CCI). And lastly, RSI can be variable but it is suggested to be at least as low as first CCI timeframe.
Lastly, you have to consider nothing in this script is a financial advice, it is only to help you improve your trading style by making other indicators as simple as possible.
Multiple Stock RSI CheckThis script will check how many stocks RSI is greater than 55 in the given list. This will give you overall idea whether stocks in sector is bullish or bearish .
Multi IND Dashboard [Skiploss]Multi IND Dashboard is dashboard combine with price change, RSI, ATR, Alligator and Supertrend. With a maximum of 10 timeframes, I think it's going to make your life easier. In looking at the momentum of each chart.
How it work??
Change :
It is the distance from the close price of previous candlestick and shows the movement value of the candlestick in that timeframe.
RSI :
Default setting are 14 and source close
Value >= 75 : Fill text color maximum overbought
Value >= 65 : Fill text color medium overbought
Value >= 55 : Fill text color minimum overbought
Value >= 45 : Fill text color minimum overbought
Value >= 35 : Fill text color medium overbought
Value >= 25 : Fill text color maximum overbought
ATR :
Default setting are 14 length and RMA smoothing, It like the average swing of the candlesticks.
Alligator :
Default setting are 13, 8 and 5
Bullish status is value lips > teeth and teeth > jaw
Bearish status is value lips < teeth and teeth < jaw
Neutral status status is value lips > teeth and teeth < jaw or lips < teeth and teeth > jaw
Supertrend :
Default setting are 8 and 3.0
Bullish status is uptrend
Bearish status is downtrend
BitCoin RSI TrendWhat is it?
This indicator will plot the RSI of BTC with a red or green background based on the top and bottom values which you can set.
How to use it?
For example, you want to trade only if the RSI of BTC is between 50 and 70, so the top value is 70 and bottom is 50. If the RSI value between those values the background will be green, else it will be red.
Why to use it?
The buy and sell strength of the BTC controls the other coins, and it is noticeable when the BTC is over sold and the RSI exceeding the 70, the price will reverse its movement to down, thus it is advisable to not open long position if the RSI of BTC is above the 70-75. Also, if the RSI is under 50 there is a big possibility to move down further to the over bought areas. The best is to buy a altcoins when the BTC RSI is between 50 and 70.
For example, I could avoid a bad long trade on MATICUSDT when the RSI of BTC is going under 50
Or, get a good long trade on MATICUSDT when the RSI of BTC is between 50 and 70
