SentinelsSentinels is a playful variation on combining different mean averages (MA).
A cross of 2 user-defined MA's (MA 1 & MA 2) initiates the drawing of a sentinel with tentacles, which, on its turn can provide potential support/resistance or entry/stop-loss/take profit zones.
The type of each MA (MA 1, MA 2 and tentacles) can be chosen from following options:
SMA
EMA
SMMA (RMA)
HullMA
WMA
VWMA
DEMA
TEMA
🔹 Examples
Fast & slow MA: HullMA, Tentacles: TEMA
Fast & slow MA: SMA, Tentacles: WMA
Fast & slow MA: WMA, Tentacles: WMA
Fast & slow MA: TEMA, Tentacles: TEMA
🔶 DETAILS
🔹 Head-Body
The head-body is formed by:
the slow MA when there is a crossunder.
the fast MA when there is a crossover.
The color of the head-body is a gradient which can be set. The color of the tentacles (non-gradient) can be set as well.
The head-body of the sentinel will be visible for maximum 60 bars after a cross has occured.
🔹 Tentacles
The length of the 'Tentacles' is calculated by taking the difference between the length of MA 1 and MA 2 , and dividing this by 6 -> diff .
The length of each tentacle is MA 1 + a multiple of diff .
The tentacles will only begin to show from 2 bars after a cross.
Each tentacle will be shown maximum x bars after the cross:
Tentacle 1: 15 bars
Tentacle 2: 20 bars
Tentacle 3: 25 bars
Tentacle 4: 30 bars
Tentacle 5: 35 bars
Tentacle 6: 40 bars
🔹 Switch lengths
By switching lengths the colors get switched too.
Note that the tentacles act differently though.
In that way, this can be an extra option to visualize the tentacles .
🔶 Happy Holidays
Merry Christmas and a Happy New Year!
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Logarithmic CVD [IkkeOmar]The LCVD is another Mean-Reversion Indicator. it doesn't detect trends and does not give a signal per se. However the logarithmic transformation is made to visualize the direction of the trend for the volume. This allows you to see if money is flowing in or out of an asset.
What it does is tell you if we have a flashcrash based on the difference in volume.
Think of this indicator like a form of a volatility index.
Smoothing input:
The only input is an input for the smoothing length of the logDelta.
Volume Calculation:
// @IkkeOmar
//@version=5
indicator('Logarithmic CVD', shorttitle='CVD', overlay=false)
smooth = input.int(defval = 25, title = "Smoothing Distance")
// Calculate buying and selling volume
askVolume = volume * (close > open ? 1 : 0) // Assuming higher close than open indicates buying
bidVolume = volume * (close < open ? 1 : 0) // Assuming lower close than open indicates selling
// Delta is the difference between buying and selling volume
delta = askVolume - bidVolume
// Apply logarithmic transformation to delta
// Adding a check to ensure delta is not zero as log(0) is undefined
logDelta = delta > 0 ? math.log(math.abs(delta)) * math.sign(delta) : - math.log(math.abs(delta)) * math.sign(delta)
// use the the ta lib for calculating the sma of the logDelta
smoothLogDelta = ta.sma(logDelta, smooth)
// Create candlestick plot
plot(logDelta, color= color.green, title='Logarithmic CVD')
plot(smoothLogDelta, color= color.rgb(145, 37, 1), title='Smooth CVD')
These lines calculate the buying and selling volumes. askVolume is calculated as the total volume when the closing price is higher than the opening price, assuming this indicates buying pressure. bidVolume is calculated as the total volume when the closing price is lower than the opening price, assuming selling pressure.
The Delta is simply the difference between buying and selling volumes.
Logarithmic Transformation:
logDelta = delta > 0 ? math.log(math.abs(delta)) * math.sign(delta) : - math.log(math.abs(delta)) * math.sign(delta)
Applies a logarithmic transformation to delta. The math.log function is used to calculate the natural logarithm of the absolute value of delta. The sign of delta is preserved to differentiate between positive and negative values. This transformation helps in scaling the delta values, especially useful when dealing with large numbers.
This script essentially provides a visual representation of the buying and selling pressures in a market, transformed logarithmically for better scaling and smoothed for trend analysis.
Hope it makes sense!
Stay safe everyone!
Don't hesitate to ask any questions if you have any!
EUR/USD 45 MIN Strategy - FinexBOTThis strategy uses three indicators:
RSI (Relative Strength Index) - It indicates if a stock is potentially overbought or oversold.
CCI (Commodity Channel Index) - It measures the current price level relative to an average price level over a certain period of time.
Williams %R - It is a momentum indicator that shows whether a stock is at the high or low end of its trading range.
Long (Buy) Trades Open:
When all three indicators suggest that the stock is oversold (RSI is below 25, CCI is below -130, and Williams %R is below -85), the strategy will open a buy position, assuming there is no current open trade.
Short (Sell) Trades Open:
When all three indicators suggest the stock is overbought (RSI is above 75, CCI is above 130, and Williams %R is above -15), the strategy will open a sell position, assuming there is no current open trade.
SL (Stop Loss) and TP (Take Profit):
SL (Stop Loss) is 0.45%.
TP (Take Profit) is 1.2%.
The strategy automatically sets these exit points as a percentage of the entry price for both long and short positions to manage risks and secure profits. You can easily adopt these inputs according to your strategy. However, default settings are recommended.
Ultimate Seasonality Indicator [SS]Hello everyone,
This is my seasonality indicator. I have been working on it for like 2 months, so hope you like it!
What it does?
The Ultimate Seasonality indicator is designed to provide you, the trader, an in-depth look at seasonality. The indicator gives you the ability to do the following functions:
View the most bearish and bullish months over a user defined amount of years back.
View the average daily change for each respective months over a user defined amount of years back.
See the most closely correlated month to the current month to give potential insights of likely trend.
Plot out areas of High and Low Seasonality.
Create a manual seasonal forecast model by selecting the desired month you would like to model the current month data after.
Have the indicator develop an autoregressive seasonal model based on seasonally lagged variables, using principles of machine learning.
I will go over these functions 1 by 1, its a whopper of an indicator so I will try to be as clear and concise as possible.
Viewing Bullish vs Bearish Months, Average Daily Change & Correlation to Current Month
The indicator will break down the average change, as well as the number of bullish and bearish days by month. See the image below as an example:
In the table to the right, you will see a breakdown of each month over the past 3 years.
In the first column, you will see the average daily change. A negative value, means it was a particularly bearish month, a positive value means it was a particularly bullish month.
The next column over shows the correlation to the current dataset. How this works is the indicator takes the size of the monthly data for each month, and compares it to the last X number of days up until the last trading day. It will then perform a correlation assessment to see how closely similar the past X number of trading days are to the various monthly data.
The last 2 columns break down the number of Bullish and Bearish days, so you can see how many red vs green candles happened in each respective month over your set timeframe. In the example above, it is over the pats 3 years.
Plot areas of High and Low Seasonality
In the chart above, you will see red and green highlighted zones.
Red represents areas of HIGH Seasonality .
Green represents areas of LOW Seasonality .
For this function, seasonality is measured by the autocorrelation function at various lags (12 lags). When there is an average autocorrelation of greater than 0.85 across all seasonal lags, it is considered likely the result of high seasonality/trend.
If the lag is less than or equal to 0.05, it is indicative of very low seasonality, as there is no predominate trend that can be found by the autocorrelation functions over the seasonally lagged variables.
Create Manual Seasonal Forecasts
If you find a month that has a particularly high correlation to the current month, you can have the indicator create a seasonal model from this month, and fit it onto the current dataset (past X days of trading).
If we look at the example below:
We can see that the most similar month to the current data is September. So, we can ask the indicator to create a seasonal forecast model from only September data and fit it to our current month. This is the result:
You will see, using September data, our most likely close price for this month is 450 and our model is y= 1.4305x + -171.67.
We can accept the 450 value but we can use the equation to model the data ourselves manually.
For example, say we have a target price on the month of 455 based on our own analysis. We can calculate the likely close price, should this target be reached, by substituting this target for x. So y = 1.4305x + -171.67 becomes
y = 1.4305(455) +- 171.67
y = 479.20
So the likely close price would be 479.20. No likely, and thus its not likely we are to see 455.
HOWEVER, in this current example, the model is far too statistically insignificant to be used. We can see the correlation is only 0.21 and the R squared is 0.04. Not a model you would want to use!
You want to see a correlation of at least 0.5 or higher and an R2 of 0.5 or higher.
We can improve the accuracy by reducing the number of years we look back. This is what happens when we reduce the lookback years to 1:
You can see reducing to 1 year gives December as the most similar month. However, our R2 value is still far too low to really rely on this data whole-heartedly. But it is a good reference point.
Automatic Autoregressive Model
So this is my first attempt at using some machine learning principles to guide statistical analysis.
In the main chart above, you will see the indicator making an autoregressive model of seasonally lagged variables. It does this in steps. The steps include:
1) Differencing the data over 12, seasonally lagged variables.
2) Determining stationarity using DF test.
3) Determining the highest, autocorrelated lags that fall within a significant stationary result.
4) Creating a quadratic model of the two identified lags that best represents a stationary model with a high autocorrelation.
What are seasonally lagged variables?
Seasonally lagged variables are variables that represent trading months. So a lag of 25 would be 1 month, 50, 2 months, 75, 3 months, etc.
When it displays this model, it will show us what the results of the t-statistic are for the DF test, whether the data is stationary, and the result of the autocorrelation assessment.
It will then display the model detail in the tip table, which includes the equation, the current lags being used, the R2 and the correlation value.
Concluding Remarks
That's the indicator in a nutshell!
Hope you like it!
One final thing, you MUST have your chart set to daily, otherwise you will get a runtime error. This can ONLY be used on the daily timeframe!
Feel free to leave your questions, comments and suggestions below.
Note:
My "ultimate" indicators are made to give the functionality of multiple indicators in one. If you like this one, you may like some of my others:
Ultimate P&L Indicator
Ultimate Customizable EMA/SMA
Thanks for checking out the indicator!
Double RSI 00 1.0This script creates a custom indicator, visualizes two RSI values (RSI1 and RSI2) on the chart and generates alerts based on different RSI-related conditions, which can be used for technical analysis and trading strategies. Users can customize the RSI parameters and alert levels according to their preferences.
It includes several input parameters that allow the user to customize the RSI calculations and overbought/oversold levels. These parameters include:
length_1: RSI1 Length (default: 7)
length_2: RSI2 Length (default: 12)
overbought_1: Overbought Signal level for RSI1 (default: 75)
oversold_1: Oversold Signal level for RSI1 (default: 25)
overbought_2: High Overbought Signal level for RSI1 (default: 85)
oversold_2: High Oversold Signal level for RSI1 (default: 15)
The script calculates two RSI values: rsi_1 and rsi_2, based on the high and low prices averaged (hl2) and the specified RSI lengths.
It plots these RSI values on the chart using different colors and line widths.
Several horizontal lines are drawn on the chart to represent key levels:
h0: 0 (Lower Band)
h1: 50 (Middle Band)
h2: 100 (Upper Band)
h3: The Oversold level (customizable)
h4: The Overbought level (customizable)
h5: The High Oversold level (customizable)
h6: The High Overbought level (customizable)
The script defines alert conditions for various signals, including overbought, oversold, high overbought, high oversold, long (crossover between RSI1 and RSI2), and short (crossunder between RSI1 and RSI2).
It sends alerts when these conditions are met, indicating potential trading signals.
Please note that this script is meant for educational purposes and should be used cautiously in a real trading environment. It's important to have a thorough understanding of technical analysis and risk management when using such indicators in actual trading.
Support and Resistance: Triangles [YinYangAlgorithms]Overview:
Triangles have always been known to be the strongest shape. Well, why wouldn’t that likewise apply to trading? This Indicator will create Upwards and Downwards Triangles which in turn create Support and Resistance locations. For example, we find 2 highs that meet the criteria (within deviation %, Minimum Distance and Lookback Distance). We calculate the distance between these two and create an Equilateral Triangle Downwards (You can adjust the % if you want more of an Isosceles Triangle). The midpoint (tip) of this triangle is the Support and the bottom (base) of it is the Resistance. The exact opposite applies for an Upwards Triangle.
The reason why Triangles may make for good Support and Resistance locations is the % 's used, much like the fibonacci, use ratios relevant in nature and everywhere in the world around us, so why not for trading too?
Tutorial:
If you look at the locations we’ve circled above, all of them exhibit strong rejections are predictive Support and Resistance locations plotted by the triangles created. There can only ever be 1 Upward and 1 Downward Triangle at a time, so when a new one is created, the Support and Resistance locations are moved.
If you scroll back far enough you’ll notice the Triangles disappear but their Support and Resistance locations are still plotted. This has to do with the fact you are allowed only so many Lines plotted and when a new Triangle is created, an old one will be removed. The Support and Resistance locations however will stay.
If we look at the example above, you can see the Support and Resistance locations the Triangles made here may have helped predict where the price would struggle to surpass.
By default the Look Back Distance is set to 50 and the Min Distance is 10 (settings used in all previous examples). However, you can modify these to make Triangles more ‘Rare’ and therefore the Support and Resistance locations change less. In the example above for Instance we left Look Back Distance to 50 but changed Min Distance from 10 to 25. This results in Support and Resistance locations that may hold better in the long term.
If we scroll back a bit, we can see the settings ‘Look Back Distance’ 50 and ‘Minimum Distance’ 25 had done a decent job at predicting the ATH resistance and many Support and Resistance locations around it. Keep in mind, previous results don’t mean future results, but Triangles may create ratios which apply well to trading.
We will conclude our Tutorial here. Hopefully you can see the benefit to the ratio Triangles make when predicting Support and Resistance locations.
Settings:
Show Triangles: If all you want to know is the Support and Resistance locations, there’s no need to draw the Triangles.
Triangle Zones: What types of triangles should we create our zones for? Options are Upward, Downward, Both, None.
Max Deviation Allowed: Maximum Deviation up or down from the last bars High/Low for potential to create a Triangle.
Lookback Distance: How far back we look to see for potential of a High/Low within Deviation range.
Min Distance: This is so triangles are spaced properly and not from 2 bars beside each other. Min distance allocated between 2 points to create a Triangle.
Bar Percent Increase: How much % multiplier do we apply for each bar spacing of the triangle. 0.005 creates a close to Equilateral Triangle, but other values like 0.004 and 0.006 seem to work well too.
If you have any questions, comments, ideas or concerns please don't hesitate to contact us.
HAPPY TRADING!
Williams %R with EMA'sThe provided Pine Script code presents a comprehensive technical trading strategy on the TradingView platform, incorporating the Williams %R indicator, exponential moving averages (EMAs), and upper bands for enhanced decision-making. This strategy aims to help traders identify potential buy and sell signals based on various technical indicators, thereby facilitating more informed trading decisions.
The key components of this strategy are as follows:
**Williams %R Indicator:** The Williams %R, also known as the "Willy," is a momentum oscillator that measures overbought and oversold conditions. In this code, the Williams %R is calculated with a user-defined period (default 21) and smoothed using an exponential moving average (EMA).
**Exponential Moving Averages (EMAs):** Two EMAs are computed on the Williams %R values. The "Fast" EMA (default 8) responds quickly to price changes, while the "Slow" EMA (default 21) provides a smoother trend-following signal. Crossovers and divergences between these EMAs can indicate potential buy or sell opportunities.
**Candle Color Detection:** The code also tracks the color of candlesticks, distinguishing between green (bullish) and red (bearish) candles. This information is used in conjunction with other indicators to identify specific trading conditions.
**Additional Upper Bands:** The script introduces upper bands at various levels (-5, -10, -20, -25) to create zones for potential buy and sell signals. These bands are visually represented on the chart and can help traders gauge the strength of a trend.
**Alert Conditions:** The code includes several alert conditions that trigger notifications when specific events occur, such as %R crossing certain levels, candle color changes within predefined upper bands, and EMA crossovers.
**Background Highlighting:** The upper bands and the zero line are visually highlighted with different colors, making it easier for traders to identify critical price levels.
This code is valuable for traders seeking a versatile technical strategy that combines multiple indicators to improve trading decisions. By incorporating the Williams %R, EMAs, candlestick analysis, and upper bands, it offers a holistic approach to technical analysis. Traders can customize the parameters to align with their trading preferences and risk tolerance. The use of alerts ensures that traders are promptly notified of potential trade setups, allowing for timely execution and risk management. Overall, this code serves as a valuable tool for traders looking to make more informed decisions in the dynamic world of financial markets.
Fib TSIFib TSI = Fibonacci True Strength Index
The Fib TSI indicator uses Fibonacci numbers input for the True Strength Index moving averages. Then it is converted into a stochastic 0-100 scale.
The Fibonacci sequence is the series of numbers where each number is the sum of the two preceding numbers. 1, 2, 3, 5, 8, 13, 21, 34, 55, 89, 144, 233, 377, 610...
TSI uses moving averages of the underlying momentum of a financial instrument.
Stochastic is calculated by a formula of high and low over a length of time on a scale of 0-100.
How to use Fib TSI:
100 = overbought
0 = oversold
Rising = bullish
Falling = bearish
crossover 50 = bullish
crossunder 50 = bearish
The default input settings are:
2 = Stoch D smoothing
3 = TSI signal
TSI uses 2 moving averages compared with each other.
5 = TSI fastest
TSI uses 2 moving averages compared with each other.
Default value is 3/5.
color = white
8 = TSI fast
TSI uses 2 moving averages compared with each other.
Default value is 5/8.
color = blue
13 = TSI mid
TSI uses 2 moving averages compared with each other.
Default value is 8/13.
color = orange
21 = TSI slow
TSI uses 2 moving averages compared with each other.
Default value is 13/21.
color = purple
34 = TSI slowest
TSI uses 2 moving averages compared with each other.
Default value is 21/34.
color = yellow
55 = Stoch K length
All total / 5 = All TSI
color rising above 50 = bright green
color falling above 50 = mint green
color falling below 50 = bright red
color rising below 50 = pink
Up bullish reversal = green arrow up
bullish trend = green dots
Down bearish reversal = red arrow down
bearish trend = red dots
Horizontal lines:
100
75
50
25
0
2 different visual options example snapshot:
Bullish Divergence Short-term Long Trade FinderThis script is a Bullish divergence trade finder built to find small periods where Bitcoin will likely rise from. It looks for bullish divergence followed by a higher low as long as the hour RSI value is below the 40 mark, if then it will enter an long. It marks out Buy signals on the RSI if the value dips below 'RSI Bull Condition Minimum' (Default 40) on the current time frame in view. It also marks out Sell signals found when the RSI is above the 'RSI Bearish Condition Minimum' (Default 50). The sell signals are bearish divergence that has occurred recently on the RSI. When a long is in play it will sell if it finds bearish divergence or the time frame in view reaches RSI value higher than the 'RSI Sell Value'(Default 75). You can set your stop loss value with the 'Stop loss Percentage' (default 5).
Available inputs:
RSI Period: relative strength measurement length(Typically 14)
RSI Oversold Level: the bottom bar of the RSI (Typically 30)
RSI Overbought Level: the top bar of the RSI (Typically 70)
RSI Bearish Condition Minimum: The minimum value the script will use to look for a pivot high that starts the Bearish condition to Sell (Default 50)
RSI Bearish Condition Sell Min: the minimum value the script will accept a bearish condition (Default 60)
RSI Bull Condition Minimum: the minimum value it will consider a pivot low value in the RSI to find a divergence buy (Default 40)
Look Back this many candles: the amount of candles thee script will look back to find a low value in the RSI (Default 25)
RSI Sell Value: The RSI value of the exit condition for a long when value is reached (Default 75)
Stop loss Percentage: Percentage value for amount to lose (Default 5)
The formula to enter a long is stated below:
If price finds a lower low and there is a higher low found following a lower low and price has just made another dip and price closes lower than the last divergence and Relative strength index hour value is less than 40 enter a long.
The formula to exit a long is stated below:
If the value drops below the stop loss percentage OR (the RSI value is greater than the value of the parameter 'RSI Sell Value' or bearish divergence is found greater than the parameter 'RSI Bearish Condition Minimum' )
This script was built from much strategy testing on BTC but works with alts (occasionally) also. It is most successful to my knowledge using the 15 min and 7 min time frames with default values. Hope it helps! Follow for further possible updates to this script or other entry or exit strategies.
snapshot:
I only have a Pro trading view account so I cannot share a larger data set about this script because the buy signals happen pretty rarely. The most amount that I could find within a view for me was 40 trades within a viewable time. The suggested/default parameters that I have do not occur very often so it limits the data set. Adjustments can be made to the parameters so that trades can be entered more often. The scripts success is dependent on the values of the parameters set by the user. This script was written to be used for BTC/USD or BTC/USDT trading. I am unable to share a larger dataset without putting out results that are intended to fail or having a premium account so reaching the 100 trade minimum is not possible with my account.
Indian Market Sessions for BacktestingThis indicator is designed to increase the quality of your backtesting in the Indian Market.
NSE & BSE run from 9:15 am IST to 3:30 pm IST.
Naturally different times have different kinds of volatility.
On your chart you will find premarked -
Saffron - 9:15 am to 10:30 am - Opening Session - High Volatility Observed Historically
White - 10:35 am to 2:25 pm - Middle Session - Lower Volatility Observed Historically
Green - 2:30 pm to 3:30 pm - Closing Session - Medium to High Volatility Observed Historically
You will also find the start of each session marked with an arrow.
Feel free to change the times from the input settings and the color and visibility from the style settings.
_______________
Usage:
When you backtest any strategies, say moving average crossovers, also mark the sessions in your sheet which will help you further increase accuracy.
Feel free to drop your doubts in the comments.
The Z-score The Z-score, also known as the standard score, is a statistical measurement that describes a value's relationship to the mean of a group of values. It's measured in terms of standard deviations from the mean. If a Z-score is 0, it indicates that the data point's score is identical to the mean score. Z-scores may be positive or negative, with a positive value indicating the score is above the mean and a negative score indicating it is below the mean.
The concept of Z-score was introduced by statistician Carl Friedrich Gauss as part of his "method of the least squares," which was an important step in the development of the normal distribution and Z-score tables. It's a key concept in statistics and is used in various statistical tests.
In financial analysis, Z-scores are used to determine whether a data point is usual or unusual. You can think of it as a measure of how many standard deviations an element is from the mean. For instance, a Z-score of 1.0 would denote a value that is one standard deviation from the mean. Z-scores are also used to predict probabilities, with Z-scores having a distribution that is expected to be normal.
In trading, a Z-score is used to determine how often a trading system may produce a string of winners or losers. It can help a trader to understand whether the losses or profits they see are something that the system would most likely produce, or if it's a once in a blue moon situation. This helps traders make decisions about when to start or stop a system.
I just wanted to play a bit with the Z-score I guess.
Feel free to share your findings if you discover additional applications for this strategy or identify timeframes where it appears to perform more optimally.
How it works:
This strategy is based on a statistical concept called Z-score, which measures the number of standard deviations a data point is from the mean. In other words, it helps determine how unusual or usual a data point is.
In the context of this strategy, Z-score is applied to a 10-period EMA (Exponential Moving Average) of Heikin-Ashi candlestick close prices. The Z-score is calculated over a look-back period of 25 bars.
The EMA of the Z-score is then calculated over a 20-bar period, and the upper and lower thresholds (bounds for buy and sell signals) are defined using the 90th and 10th percentiles of this EMA score.
Long positions are taken when the Z-score crosses above the lower threshold or crosses above the mid-line (50th percentile). An additional long entry is made when the Z-score crosses above the highest value the EMA has been in the past 100 periods.
Short positions are initiated when the EMA crosses below the upper threshold, lower threshold or the highest value the EMA has been in the past 100 periods.
Positions are closed when opposing entry conditions are met, for example, a long position is closed when the short entry condition is true, and vice versa.
Set your desired start date for the strategy. This can be modified in the timestamp("YYYY MM DD") function at the top of the script.
MTF SuperTrends Nexus [DarkWaveAlgo]🧾 Description:
A nexus is a connection, link, or neuronal junction where signals and information are transmitted between different elements.
The MTF SuperTrends Nexus indicator serves as a nexus between MTF SuperTrends by facilitating the visualization of up to eight multi-timeframe SuperTrends, each with its own customizable timeframe, period, factor, and coloring customization. By combining these various SuperTrends, it helps you create a comprehensive view of MTF trend dynamics and cross-timeframe confluence according to the SuperTrend indicator.
It acts as a utility/control center that brings together multiple MTF SuperTrends and allows you to visualize the interactions between them with exceptional ease-of-use and customizability, helping to provide you with valuable insights into potential trend reversals, momentum shifts, and trading opportunities.
💡 Originality and Usefulness:
While there are other multi-timeframe SuperTrend indicators available, MTF SuperTrends Nexus' semi-transparent fills create a compounding opaqueness when SuperTrends from multiple timeframes coalesce - making visual assessment of cross-timeframe confluence extremely easy. We also believe it stands above the rest with its sheer quantity and quality of settings, features, and usability.
✔️ Re-Published to Avoid Misleading Values
This script has been re-published to ensure that it does not use `request.security()` calls using lookahead_on to access future data when referencing SuperTrend calculations from other timeframes. This decreases the likelihood that the indicator will provide deceiving values. This change has been made in accordance with the PineScript documentation: "Using barmerge.lookahead_on at timeframes higher than the chart's without offsetting the `expression` argument like in `close [ ]` will introduce future leak in scripts, as the function will then return the `close` price before it is actually known in the current context" and the Publishing Rule: "Do not use `request.security()` calls using lookahead to access future data". Historical and real-time values may differ when referencing timeframes other than the chart's.
💠 Features:
8 toggleable MTF SuperTrends with customizable timeframes, periods, and factors
Compounding filled areas for easy MTF SuperTrend confluence analysis
Aesthetic and flexible coloring and color theme styling options
End-of chart labels and options for ease-of-use and legibility
⚙️ Settings:
Use a Color Theme: When this setting is enabled, all manual 'Bullish and Bearish Colors' are overridden. All plots will use the colors from your selected Color Theme - excepting those plots set to use the 'Single Color' coloring method.
Color Theme: When 'Use a Color Theme' is enabled, this setting allows you to select the color theme you wish to use.
Fill SuperTrend Areas: When enabled, the area between any MTF SuperTrend and the price bars will be filled with semi-transparent coloring.
Hide SuperTrends on Timeframes Lower Than the Chart: When this setting is enabled, any MTF SuperTrend with a timeframe smaller than that of the chart the indicator is applied to will be hidden from view.
Enable: Show/hide a specific MTF SuperTrend.
Timeframe: Set the timeframe for a specific MTF SuperTrend.
Period: Set the lookback period for a specific MTF SuperTrend.
Factor: Set the multiplier factor used for a specific MTF SuperTrend's calculation.
Bullish Color: When 'Use a Color Theme' is disabled, this will set the 'bullish color' for this specific MTF SuperTrend.
Bearish Color: When 'Use a Color Theme' is disabled, this will set the 'bearish color' for this specific MTF SuperTrend.
Enable Label: When enabled, a label will show at the end of the chart displaying the timeframe, period, factor, and current price value of this specific MTF SuperTrend.
Size: Sets the font size of this specific MTF SuperTrend's label.
Label Offset (in Bars): Sets the distance from the latest bar, in bars, at which this specific MTF SuperTrend's label is displayed.
Show Label Line: When enabled, this specific MTF SuperTrend's label will be accommodated by a dashed line connecting it to its plot.
📈 Chart:
The chart shown in this original publication displays the 5 minute chart on BTCUSDT. Displayed on the chart are 6 MTF SuperTrends: the 5m 50-period/3-factor SuperTrend, 15m 50-period/3-factor SuperTrend, 30m 50-period/3-factor SuperTrend, 1h 50-period/3-factor SuperTrend, 4h 50-period/3-factor SuperTrend, and the 1D 25-period/1.5-factor SuperTrend - offering an exemplary view of how you can easily use these MTF SuperTrends to your advantage in analyzing SuperTrend relationships across multiple timeframes.
Scalp Tool
This script is primarily intended as a scalping tool.
The theory of the tool is based on the fact that the price always returns to its mean.
Elements used:
1. VWMA as a moving average. VWMA is calculated once based on source close and once based on source open.
2. the bands are not calculated like the Bollinger Band, but only a settlement is calculated for the lower bands based on the Lows and for the upper bands based on the Highs. Thus the bands do not become thicker or thinner, but remain in the same measure to the mean value above or below the price.
3. a volume filter on simple calculation of a MA with deviation. Therefore, it can be identified if a volume breakout has occurred.
4. support and resistance zones which are calculated based on the highs and lows over a certain length.
5. RSI to determine oversold and overbought zones. It also tries to capture the momentum by using a moving average (variable selectable) to filter the signals. The theory is that in an uptrend the RSI does not go below 50 and in a downtrend it does not go above 50.
However, this can be very different depending on the financial instrument.
Explanation of the signals:
The main signal in this indicator Serves for pure short-term trading and is generated purely on the basis of the bands and the RSI.
Only the first bands are taken into account.
Buy signal is generated when the price opens below the lower band 1 and closes above the lower band 1 or the RSI crosses a value of 25 from bottom to top.
Sell signal is generated when the price opens above the Upper Band 1 and closes below the Upper Band 1 or the RSI crosses a value of 75 from top to bottom.
The position should be closed when the price hits the opposite band. Alternatively, it can also be closed at the mean.
Other side signals:
1. breakouts:
The indicator includes 2 support and resistance zones, which differ only in length. For the breakout signals, the short version of the R/S is used. A signal is generated when the price breaks through the zones with increased volume. It is then assumed that the price will continue to follow the breakout.
The values of the S/R are adjustable and marked with "BK".
The value under Threshold 2 defines the volume breakout. 4 is considered as the highest value. The smaller the value, the smaller the volume must be during a breakout.
2. bounce
If the price hits a S/R (here the long variant is used with the designation "Support" or "Resistance") and makes a wick with small volume, the script assumes a bounce and generates a Sell or Buy signal accordingly.
The volume can be defined under "Threshold".
The S/R according to the designation as well.
Combined signals:
If the value of the S/R BK and the S/R is the same and the bounce logic of the S/R BK applies and an RSI signal is also generated, a signal is also plotted.
Here the idea was to get very strong signals for possible swing entries.
4. RSI Signals
The script contains two RSI.
RSI 1:
Bullish signal is generated when the set value is crossed from the bottom to the top.
Bearish signal is generated when the set value is crossed from the top to the bottom.
RSI 2:
Bullish signal is generated when the set value is crossed from the top to the bottom.
Bearish signal is generated when the set value is crossed from bottom to top.
For RSI 2 the theory is taken into account according to the description under Used elements point 5
Optical trend filter:
Also an optical trend filter was generated which fills the bands accordingly.
For this the VWMA is used and the two average values of the band.
Color definition:
Gray = Neutral
Red = Bearish
Green = Bullish
If the mean value is above the VWMA and the mean value based on the closing price is above the mean value based on the open price, the band is colored green. It is a bullish trend
If the mean value is below the VWMA and the mean value based on the closing price is below the mean value based on the open price, the band is colored red.
The band is colored gray if the mean value is correspondingly opposite. A sideways phase is assumed.
The script was developed on the basis of the pair BTCUSD in the 15 minute chart and the settings were defined accordingly on it. The display of S/R for forex pairs does not work correctly and should be hidden. The logic works anyway.
When using the script, all options should first be set accordingly to the asset and tested before trading afterwards. It applies of course also here that there is no 100% guarantee.
Also, a strong breakout leads to false signals and overheating of the indicator.
P/E RatioPlots the P/E Ratio with highest, lowest and average, as well as two ranges, 25-20 & 20-0 considered as the regular P/E Range
Statistics TableThis script display some useful Statistics data that can be useful in making trading decision.
Here the list of information this script is display in table format.
You can change each and every single ema and rs length as per your need from setting.
1) close difference from first ema
2) close difference from second ema
3) close difference from third ema
4) close difference from fourth ema
5) difference between first and second ema
6) difference between second and third ema
7) difference between first and third ema
8) volume up down ratio
9) ATR/ADR %
10) volume pocket pivot count
11) daily closing range
12) weekly closing range
13) close difference from 52week high
14) close difference from 52week low
15) close difference from All time high
16) close difference from All time low
17) rs line above or below first rs ema
18) rs line above or below second rs ema
19) rs line above or below third rs ema
20) rs line above or below fourth rs ema
21) first rs value
22) second rs value
23) third rs value
24) fourth rs value
25) difference between previous first rs length days change % and current first rs length days change %
26) difference between previous second rs length days change % and current second rs length days change %
27) difference between previous third rs length days change % and current third rs length days change %
RSI, SRSI, MACD and DMI cross - Open source codeHello,
I'm a passionate trader who has spent years studying technical analysis and exploring different trading strategies. Through my research, I've come to realize that certain indicators are essential tools for conducting accurate market analysis and identifying profitable trading opportunities. In particular, I've found that the RSI, SRSI, MACD cross, and Di cross indicators are crucial for my trading success.
Detailed explanation:
The RSI is a momentum indicator that measures the strength of price movements. It is calculated by comparing the average of gains and losses over a certain period of time. In this indicator, the RSI is calculated based on the close price with a length of 14 periods.
The Stochastic RSI is a combination of the Stochastic Oscillator and the RSI. It is used to identify overbought and oversold conditions of the market. In this indicator, the Stochastic RSI is calculated based on the RSI with a length of 14 periods.
The MACD is a trend-following momentum indicator that shows the relationship between two moving averages of prices. It consists of two lines, the MACD line and the signal line, which are used to generate buy and sell signals. In this indicator, the MACD is calculated based on the close price with fast and slow lengths of 12 and 26 periods, respectively, and a signal length of 9 periods.
The DMI is a trend-following indicator that measures the strength of directional movement in the market. It consists of three lines, the Positive Directional Indicator (+DI), the Negative Directional Indicator (-DI), and the Average Directional Index (ADX), which are used to generate buy and sell signals. In this indicator, the DMI is calculated with a length of 14 periods and an ADX smoothing of 14 periods.
The indicator generates buy signals when certain conditions are met for each of these indicators.
1) For the RSI, a buy signal is generated when the RSI is below or equal to 35 and the Stochastic RSI %K is below or equal to 15, or when the RSI is below or equal to 28 the Stochastic RSI %K is below or equal to 15 or when the RSI is below or equal to 25 and the Stochastic RSI %K is below or equal to 10 or when the RSI is below or equal to 28.
2) For the MACD, a buy signal is generated when the MACD line is below 0, there is a change in the histogram from negative to positive, the MACD line and histogram are negative in the previous period, and the current histogram value is greater than 0.
3) For the DMI, a buy signal is generated when the Positive Directional Indicator (+DI) crosses above the Negative Directional Indicator (-DI), and the -DI is less than the +DI.
The indicator generates sell signals when certain conditions are met for each of these indicators:
1) For the RSI, a sell signal is generated when the RSI is above or equal to 75 and the Stochastic RSI %K is above or equal to 85, or when the RSI is above or equal to 80 and the Stochastic RSI %K is above or equal to 85, or when the RSI is above or equal to 85 and the Stochastic RSI %K is above or equal to 90 or when the RSI is above or equal to 82.
2)For the MACD, a sell signal is generated when the MACD line is above 0, there is a change in the histogram from positive to negative, the MACD line and histogram are positive in the previous period, and the current histogram value is less than the previous histogram value. On the other hand, a buy signal is generated when the MACD line is below 0, there is a change in the histogram from negative to positive, the MACD line and histogram are negative in the previous period, and the current histogram value is greater than the previous histogram value.
3)For the DMI a bearish signal is generated when plusDI crosses above minusDI, indicating that bulls are losing strength and bears are taking control.
The indicator uses a combination of these four indicators to generate potential buy and sell signals. The buy signals are generated when RSI and SRSI values are in oversold conditions, while sell signals are generated when RSI and SRSI values are in overbought conditions. The indicator also uses MACD crossovers and DMI crossovers to generate additional buy and sell signals.
When a signal is strong?
The use of multiple signals within a specific timeframe can increase the accuracy and reliability of the signals generated by this indicator. It is recommended to look for at least two signals within a range of 5-8 candles in order to increase the probability of a successful trade.
Why it's original?
1) There is no indicator in the library that combine all of these indicators and give you a 360 view
2)The combination of the RSI, Stochastic RSI, MACD, and DMI indicators in a single script it's unique and not available in the libray.
3)The specific parameters and conditions used to calculate the signals may be unique and not found in other scripts or libraries.
4)The use of plotshape() to plot the signals as shapes on the chart may be unique compared to other scripts that simply plot lines or bars to indicate signals.
5)The use of alertcondition() to trigger alerts based on the signals may be unique compared to other scripts that do not have custom alert functionality.
Keep attention!
It is important to note that no trading indicator or strategy is foolproof, and there is always a risk of losses in trading. While this indicator may provide useful information for making conclusions, it should not be used as the sole basis for making trading decisions. Traders should always use proper risk management techniques and consider multiple factors when making trading decisions.
Support me:)
If you find this new indicator helpful in your trading analysis, I would greatly appreciate your support! Please consider giving it a like, leaving feedback, or sharing it with your trading network. Your engagement will not only help me improve this tool but will also help other traders discover it and benefit from its features. Thank you for your support!
Liquidation Levels on OIThis indicator is used to display estimated contract liquidation prices. When there are dense liquidation areas on the chart, it indicates that there may be a lot of liquidity at that price level. The horizontal lines of different colors on the chart represent different leverage ratios. See below for details.
Let me introduce the principle behind this indicator:
1. When position trading volume increases or decreases significantly higher than usual levels in a specific candlestick chart, it indicates that a large number of contracts were opened during that period. We use the 60-day moving average change as a benchmark line. If the position trading volume changes more than 1.2x, 2x or 3x its MA60 value, it is considered small, medium or large abnormal increase or decrease.
2. This indicator takes an approximate average between high, open, low and close prices of that candlestick as opening price.
3. Since contracts involve liquidity provided by both buyers and sellers with equal amounts of long and short positions corresponding to each contract respectively; since we cannot determine actual settlement prices for contract positions; therefore this indicator estimates settlement prices instead which marks five times (5x), ten times (10x), twenty-five times (25x), fifty times (50x) and one hundred times (100x) long/short settlement prices corresponding to each candlestick chart generating liquidation lines with different colors representing different leverage levels.
4. We can view areas where dense liquidation lines appear as potential liquidation zones which will have high liquidity.
5. We can adjust orders based on predicted liquidation areas because most patterns in these areas will be quickly broken.
6. We provide a density histogram to display the liquidation density of each price range.
Special thanks to the following TradingView community members for providing open-source indicators and contributing to the development of this indicator!
Liquidation - @Mysterysauce
Open Interest Delta - By Leviathan - @LeviathanCapital
Regarding the relationship with the above-mentioned open source indicators:
1. Indicator Liquidation - @Mysterysauce can also draw a liquidation line in the chart, but:
(1) Our indicator generates a liquidation line based on abnormal changes in open interest; their indicator generates a liquidation line based on trading volume.
(2) Our indicator will generate both long and short liquidation lines at the same time; their indicator will only generate a liquidation line in a single direction.
We refer to their method of drawing liquidation lines when drawing our own.
2. Indicator Open Interest Delta - By Leviathan - @LeviathanCapital obtained OI data for Binance USDT perpetual contracts in the code. We refer to their method of obtaining OI data in our code.
============= 中文版本 =============
此指标用于显示估计合约清算价格。当图表上有密集的清算区域时，表示该价格水平可能存在大量流动性。图表上不同颜色的水平线代表不同杠杆比率。详情请参见下面的说明。
让我介绍一下这个指标背后的原理：
1. 当特定蜡烛图对应的合约仓位增加量（OI Delta）显著高于通常水平时，表示在那段时间有大量合约开仓。我们使用OI Delta的60日移动均线作为基准线。如果OI Delta超过其MA60值的1.2倍、2倍或3倍，则认为是小型、中型或大型的异常OI Delta。
2. 该指标将上述蜡烛图高、开、低和收盘价的平均值作为近似的合约开仓价。
3. 由于合约涉及买方和卖方之间相互提供流动性，每个合约对应相等数量的多头和空头头寸。由于我们无法确定合约头寸的实际清算价格，因此该指标估计了清算价格。它标记了与该蜡烛图相对应的多头和空头5倍、10倍、25倍、50倍和100倍的清算价格，生成清算线。不同杠杆水平用不同颜色表示。
4. 我们可以将出现密集清算线的区域视为潜在的清算区域。这些区域将具有高流动性。
5. 我们可以根据预测到的清算区域调整自己的订单，因为根据规律，这些清算区域大部分都会很快被击穿。
6. 我们提供了密度直方图来显示每个价格范围的清算密度
特别感谢以下TradingView社区成员提供开源指标并为该指标的开发做出贡献！
Liquidation - @Mysterysauce
Open Interest Delta - By Leviathan - @LeviathanCapital
与上述开源指标的关系：
1. 指标Liquidation - @Mysterysauce也可以在图中绘制清算线，但是：
（1）我们的指标是基于open interest的异常变化生成的清算线；他们的指标是基于成交量生成的清算线
（2）我们的指标会同时生成多头和空头清算线；他们的指标仅会在单一方向生成清算线
我们的指标在绘制清算线上参考了他们绘制清算线的方式
2. 指标Open Interest Delta - By Leviathan - @LeviathanCapital在代码中获取了Binance USDT永续合约的OI数据。我们在代码中参考他们获取OI数据的方式
Volume Channel - [With Volume Filter]The indicator calculates two volume-weighted moving averages (VWMA) using different lengths, and filters them based on a moving average of volume. The filtered VWMA values are then plotted on the chart as lines, representing the fast and slow moving averages. In addition, upper and lower bands are calculated based on the slow VWMA and plotted as lines on the chart.
The fast and slow VWMA lines can be used to identify trends in the market. When the fast VWMA is above the slow VWMA, it is an indication of an uptrend, and when the fast VWMA is below the slow VWMA, it is an indication of a downtrend. The position of the VWMA lines relative to the upper and lower bands can also be used to identify potential trade signals.
When the price is near the upper band, it indicates that the market is overbought, and when the price is near the lower band, it indicates that the market is oversold. Traders can use these signals to enter or exit trades.
The indicator also includes a volume filter, which means that the VWMA values are only calculated when the volume is above a certain moving average of volume. This helps to filter out noise in the market and provide more accurate signals.
Explanation for each parameter
vwmaLength1: This is the length of the fast volume-weighted moving average (VWMA) used in the calculation. The default value is 10, and it can be adjusted by the user.
vwmaLength2: This is the length of the slow volume-weighted moving average (VWMA) used in the calculation. The default value is 25, and it can be adjusted by the user.
bandLength: This is the length of the moving average used to calculate the upper and lower bands. The default value is 34, and it is not adjustable by the user.
volumeFilterLength: This is the length of the moving average of volume used as a filter for the VWMA calculation. The default value is 5, and it can be adjusted by the user.
src: This is the input source for the VWMA calculation. The default value is close, which means the indicator is using the closing price of each bar. However, the user can select a different input source by changing this parameter.
filteredVwma1: This is the filtered VWMA calculated based on the volume filter and the fast VWMA length. It is plotted as a line on the chart and can be used to identify short-term trends.
filteredVwma2: This is the filtered VWMA calculated based on the volume filter and the slow VWMA length. It is plotted as a line on the chart and can be used to identify long-term trends.
ma: This is the moving average of the filtered slow VWMA values, which is used to calculate the upper and lower bands. It is plotted as a line on the chart.
offs: This is the offset used to calculate the upper and lower bands. It is based on the standard deviation of the filtered slow VWMA values and is multiplied by 1.6185 * 3. It is plotted as a line on the chart.
up: This is the upper band calculated as the moving average plus the offset. It is plotted as a line on the chart and can be used to identify overbought conditions.
dn: This is the lower band calculated as the moving average minus the offset. It is plotted as a line on the chart and can be used to identify oversold conditions.
KDJ-RSI Buy/Sell Signal ver. 1It is an indicator combining the RSI indicator and KDJ indicator.
Buy signal will triggers when:
RSI signal positioning below 25
J value crosses below 0
Sell signal will triggers when:
RSI signal positioning above 85
J value crosses above 100
***********
Please take note that this indicator may be not accurate for every chart in the crypto market, but it is most appropriate to use it in BTC/USDT charts, mainly for 1h, 4h, and 1d candles. Not recommended to use it for 1m or 15m leverage trades, this indicator might be altered by FOMO sentiment.
Stochastic RSI Strategy (with SMA and VWAP Filters)The strategy is designed to trade on the Stochastic RSI indicator crossover signals.
Below are all of the trading conditions:
-When the Stochastic RSI crosses above 30, a long position is entered.
-When the Stochastic RSI crosses below 70, a short position is entered.
-The strategy also includes two additional conditions for entry:
-Long entries must have a positive spread value between the 9 period simple moving average and the 21 period simple moving average.
-Short entries must have a negative spread value between the 9 period simple moving average and the 21 period simple moving average.
-Long entries must also be below the volume-weighted average price.
-Short entries must also be above the volume-weighted average price.
-The strategy includes stop loss and take profit orders for risk management:
-A stop loss of 20 ticks is placed for both long and short trades.
-A take profit of 25 ticks is placed for both long and short trades.
Rounded Forex Levels: Big-Figure, Mid-Figure, 80-20 levels, BFRNSimple indicator to show Rounded levels in typical Forex pairs: Big figure, Mid-figure, 80-20 Insitutional Levels, 10pip levels, 5pip levels
Wrote this indicator because other ones out there seem to clutter the chart. This is simple, low-clutter and can be set by user to have arbitrary start and end points for the lines.
I wanted the ability for lines to plot discreetly to the right hand side of price as in the chart above, since in my opinion, these are only of secondary consideration to a trader, an extra confirmation/confluence to an existing idea.
//Purpose & Usage:
-Big-figure levels (100pips) & Mid-figure levels (50pips) will have a senstitivity to price, that can be an additional tool when looking for confluence for a target or an entry.
-As well as BF levels and MF levels; Institutional levels (20pips below and 20 pips above a Big Figure level) and standard 10pip or 5pip levels, can be useful in the right context (i.e added confirmation that of a minor sweep target; added conviction in an idea if the level aligns with another seperately derived level).
//User inputs:
-Toggle on/off each of the types of level.
-Line spacing: choose pip spacing of lines .
-Number of lines above/below (i.e. setting of 5 will be 11 lines. One central, 5 above, 5 below).
-Formatting: for each class of lines, code by color, style and width (as per the example chart below).
-Line start offset and line end offset: bars forward/back for each of start point and end point. So lines could be spread right across chart; or neatly pushed to the far right or left of the chart.
//Notes:
-Designed for typical Forex pairs with units close to 1.0 (like Eur/Usd, Usd/Cad, Aud/Usd, Gbp/Usd, Eur/Gbp, Nzd/Usd).
-Lines are based from the rounded close of the previous bar, Updating (if applicable) on each new bar.
Demo Plotting levels in the past; Dialog box example display:
Ignition Cha Cha ChaIgnition Cha Cha Cha (ICCC) is a 3 color coded moving average indicator which numerically quantify the angle of their trends. I have labeled them as fast, medium and slow. The trend colors are Green for bullish, Red for bearish and Grey for sideways. The sideways movement can be user defined for all 3 in the settings under Threshold. If you regard for example anything under 10º as sideways then place 10 in the corresponding threshold and any angle under 10º will give a grey moving average and a grey labeled text. I use this chart in several ways. If you don't want moving averages all over your Chartistic Masterpiece you can turn off the plots and leave the numeric angles which will give you an overview of the trend. Conversely if you want to make the ultimate trend chart you can setup a 4 chart layout, Weekly, Daily, 12 hour and 4 hour and add the indicator with 200/50/25 moving averages and look for confluence. I find the best way for this is turn off the candles and use the moving averages with the numeric labels. You also have the ability to turn off and on different aspects of the indicator so that there is good control over its look. Also I have given the indicator lots of Alert presets for all 3 of the moving averages so you can avoid demented screen-stairing. Please forgive the name, my mother made me do Ballroom dancing lessons as a kid.
Fetch Buy And Hold StrategyThis script was created as an experiment using ChatGPT. I actually woudn't recommend using the ai program to help you with your Pinescripts, as it makes a fair amount of mistakes. It was a fun experiment however.
The script is a simple buy and hold tool. Here's what it does:
- Everytime the rsi enters below the set treshold, a counter increases.
- The second increase of the counter happens when the price goes above the treshold, and then dips below the treshold again.
- The program would fire off a buy signal when the counter hits the number 3.
- After the buy. the counter will reset.
Lets take a look at the following example where the rsi treshold is 30:
- So the rsi dips below 30 and the initial counter is set from 0 to 1.
- The price rises which brings the rsi back to 40.
- Then another dip happens and the rsi is now 25, increasing the counter from 1 two.
- Rsi now dips to 23 and nothing happens.
- Rsi goes back up to 31, and dips back to 28 which puts the counter at 3. A buy singal is now fired and the counter is set to 0.
