Customizable Vertical LinesCustomizable Vertical Lines (CVL) Indicator
Version 2.0 (November 2023)
Description:
The Customizable Vertical Lines (CVL) indicator is a powerful tool for traders who want to mark specific times on their charts with vertical lines. This indicator allows users to customize the appearance of these lines, including their color, line style, and width, providing a flexible and visually intuitive way to highlight key time points.
Key Features:
User-Friendly Inputs: Easily set up to five distinct times, each associated with a unique color for the vertical lines.
Color Customization: Choose from a wide range of colors for each vertical line, allowing for clear differentiation.
Line Style Options: Tailor the appearance of the lines with three selectable styles: solid, dotted, or dashed.
Adjustable Line Width: Modify the thickness of the lines to suit your preferred visual style.
Timezone Offset: Account for different time zones by adjusting the timezone offset parameter.
How to Use:
Simply input the desired times, colors, and other parameters in the script settings. The CVL indicator will then automatically plot vertical lines at the specified times on the chart with the chosen customization.
Pine utilities
SuperTrend ToolkitThe SuperTrend Toolkit (Super Kit) introduces a versatile approach to trend analysis by extending the application of the SuperTrend indicator to a wide array of @TradingView's built-in or Community Scripts . This tool facilitates the integration of the SuperTrend algorithm with various indicators, including oscillators, moving averages, overlays, and channels.
Methodology:
The SuperTrend, at its core, calculates a trend-following indicator based on the Average-True-Range (ATR) and price action. It creates dynamic support and resistance levels, adjusting to changing market conditions, and aiding in trend identification.
pine_st(simple float factor = 3., simple int length = 10) =>
float atr = ta.atr(length)
float up = hl2 + factor * atr
up := up < nz(up ) or close > nz(up ) ? up : nz(up )
float lo = hl2 - factor * atr
lo := lo > nz(lo ) or close < nz(lo ) ? lo : nz(lo )
int dir = na
float st = na
if na(atr )
dir := 1
else if st == nz(up )
dir := close > up ? -1 : 1
else
dir := close < lo ? 1 : -1
st := dir == -1 ? lo : up
@TradingView's native SuperTrend lacks the flexibility to incorporate different price sources into its calculation.
Community scripts, addressed the limitation by implementing the option to input different price sources, for example, one of the most popular publications, @KivancOzbilgic's SuperTrend script.
In May 2023, @TradingView introduced an update allowing the passing of another indicator's plot as a source value via the input.source() function. However, the built-in ta.atr function still relied on the chart's price data, limiting the formerly mentioned scripts to the chart's price data alone.
Unique Approach -
This script addresses the aforementioned limitations by processing the data differently.
Firstly we create a User-Defined-Type (UDT) replicating a bar's open, high, low, close (OHLC) values.
type bar
float o = open
float h = high
float l = low
float c = close
We then use this type to store the external input data.
src = input.source(close, "External Source")
bar b = bar.new(
nz(src ) , open 𝘷𝘢𝘭𝘶𝘦
math.max(nz(src ), src), high 𝘷𝘢𝘭𝘶𝘦
math.min(nz(src ), src), low 𝘷𝘢𝘭𝘶𝘦
src ) close 𝘷𝘢𝘭𝘶𝘦
Finally, we pass the data into our custom built SuperTrend with ATR functions to derive the external source's version of the SuperTrend indicator.
supertrend st = b.st(mlt, len)
- Setup Guide -
Utility and Use Cases:
Universal Compatibility - Apply SuperTrend to any built-in indicator or script, expanding its use beyond traditional price data.
- A simple example on one of my own public scripts -
Trend Analysis - Gain additional trend insights into otherwise mainly mean reverting or volume indicators.
- Alerts Setup Guide -
The Super Kit empowers traders and analysts with a tool that adapts the robust SuperTrend algorithm to a myriad of indicators, allowing comprehensive trend analysis and strategy development.
Data from dataThe "Data from Data" indicator, developed by OmegaTools, is a sophisticated and versatile tool designed to offer a nuanced analysis of various market dynamics, catering to traders and investors seeking a comprehensive understanding of price movements considering a large amount of data and variables.
The uses of this indicator are nonconventional. You can use the indicator as a stand-alone tool on the chart, hiding the current symbol price data, to be able to analyze the price action with the Semaphore visualization method, you can also hide the indicator and choose from your favorite indicators and oscillator one of the data output as a source to have additional insight on the asset.
The last use of this indicator, which depends on the X Value that you set in the settings, is to have a possible scenario for the future outcomes of the markets. Remember that there is no tool that can really predict what the market will do in the future, this tool applies a large amount of formulas to use past prices as an indication that aims to be as close as possible to the future prices. The X Value not only changes the lookback of the formulas but also changes the number of future scenarios that the indicator will plot on the chart.
Key Features:
1. Rate of Change Analysis:
The indicator evaluates the rate of change variations in closing prices, providing insights into the current rate of change and expected rate of change variation.
2. Momentum Analysis:
Momentum is analyzed through calculations involving simple moving averages, offering expected values derived from momentum and momentum variation.
3. High/Low Variation:
The expected market behavior is assessed based on the average variation between high and low prices, contributing to a more holistic analysis.
4. Liquidity Targets:
Liquidity targets can be found by analyzing the highs and lows in the direction of the current fair price.
5. Regression Sequence:
Linear regression analysis is applied to closing prices, assessing momentum and providing expected values based on regression sequences.
6. Volume Presence:
The indicator evaluates the Rate of Change (ROC) by volume presence, offering insights into price movements influenced by trading volume.
7. Liquidity Grabs:
Expected market behavior is determined based on liquidity grabs, considering both current and historical price levels.
8. Fair Value Analysis:
Expected values are derived from fair value closes and fair value highs and lows, contributing to a more nuanced analysis of market conditions.
9. STT (Sequential Trend Test):
The Sequential Trend Test is employed to analyze market trends, providing expected values for a more informed decision-making process.
Visualization:
The indicator shows a "Semaphore" on the chart, visually representing all of the data extrapolated from the script. The visualization can be more minimalistic or more complex, to let the user decide that, in the settings, it's possible to decide if to show all of the data or only the average.
Additionally, the user can choose to display bars on the chart, that visualize the standard high and low of the price data, with the difference between the expected forecasted value and the actual closing price.
My suggestion is to try to change the colors of the data to fit best your eye and the data that you find more useful, and also to try to change some parameters from circle to line as a visualization method to catch with more ease some price patterns.
Error Analysis:
The indicator provides a detailed error analysis, including historical error, average error, and present error. This information is presented in a user-friendly table for quick reference. This table can be used to analyze the margin of error of the expected future price.
KNN Regression [SS]Another indicator release, I know.
But note, this isn't intended to be a stand-alone indicator, this is just a functional addition for those who program Machine Learning algorithms in Pinescript! There isn't enough content here to merit creating a library for (it's only 1 function), but it's a really useful function for those who like machine learning and Nearest Known Neighbour Algos (or KNN).
About the indicator:
This indicator creates a function to perform KNN-based regression.
In contrast to traditional linear regression, KNN-based regression has the following advantages over linear regression:
Advantages of KNN Regression vs. Linear Regression:
🎯 Non-linearity: KNN is a non-parametric method, meaning it makes no assumptions about the underlying data distribution. This allows it to capture non-linear relationships between features and the target variable.
🎯Simple Implementation: KNN is conceptually simple and easy to understand. It doesn't require the estimation of parameters, making it straightforward to implement.
🎯Robust to Outliers: KNN is less sensitive to outliers compared to linear regression. Outliers can have a significant impact on linear regression models, but KNN tends to be less affected.
Disadvantages of KNN Regression vs. Linear Regression:
🎯 Resource Intensive for Computation: Because KNN operates on identifying the nearest neighbors in a dataset, each new instance has to be searched for and identified within the dataset, vs. linear regression which can create a coefficient-based model and draw from the coefficient for each new data point.
🎯Curse of Dimensionality: KNN performance can degrade with an increasing number of features, leading to a "curse of dimensionality." This is because, in high-dimensional spaces, the concept of proximity becomes less meaningful.
🎯Sensitive to Noise: KNN can be sensitive to noisy data, as it relies on the local neighborhood for predictions. Noisy or irrelevant features may affect its performance.
Which is better?
I am very biased, coming from a statistics background. I will always love linear regression and will always prefer it over KNN. But depending on what you want to accomplish, KNN makes sense. If you are using highly skewed data or data that you cannot identify linearity in, KNN is probably preferable.
However, if you require precise estimations of ranges and outliers, such as creating co-integration models, I would advise sticking with linear regression. However, out of curiosity, I exported the function into a separate dummy indicator and pulled in data from QQQ to predict SPY close, and the results are actually very admirable:
And plotted with showing the standard error variance:
Pretty impressive, I must say I was a little shocked, it's really giving linear regression a run for its money. In school I was taught LinReg is the gold standard for modeling, nothing else compares. So as with most things in trading, this is challenging some biases of mine ;).
Functionality of the function
I have permitted 3 types of KNN regression. Traditional KNN regression, as I understand it, revolves around clustering. ( Clustering refers to identifying a cluster, normally 3, of identical cases and averaging out the Dependent variable in each of those cases) . Clustering is great, but when you are working with a finite dataset, identifying exact matches for 2 or 3 clusters can be challenging when you are only looking back at 500 candles or 1000 candles, etc.
So to accommodate this, I have added a functionality to clustering called "Tolerance". And it allows you to set a tolerance level for your Euclidean distance parameters. As a default, I have tested this with a default of 0.5 and it has worked great and no need to change even when working with large numbers such as NQ and ES1!.
However, I have added 2 additional regression types that can be done with KNN.
#1 One is a regression by the last IDENTICAL instance, which will find the most recent instance of a similar Independent variable and pull the Dependent variable from that instance. Or
#2 Average from all IDENTICAL instances.
Using the function
The code has the instructions for integrating the function into your own code, the parameters, and such, so I won't exhaust you with the boring details about that here.
But essentially, it exports 3, float variables, the Result, the Correlation, and the simplified R2.
As this is KNN regression, there are no coefficients, slopes, or intercepts and you do not need to test for linearity before applying it.
Also, the output can be a bit choppy, so I tend to like to throw in a bit of smoothing using the ta.sma function at a deault of 14.
For example, here is SPY from QQQ smoothed as a 14 SMA:
And it is unsmoothed:
It seems relatively similar but it does make a bit of an aesthetic difference. And if you are doing it over 14, there is no data loss and it is still quite reactive to changes in data.
And that's it! Hopefully you enjoy and find some interesting uses for this function in your own scripts :-).
Safe trades everyone!
Intersection Value FunctionsWinning entry for the first Pinefest contest. The challenge required providing three functions returning the intersection value between two series source1 and source2 in the event of a cross, crossunder, and crossover.
Feel free to use the code however you like.
🔶 CHALLENGE FUNCTIONS
🔹 crossValue()
//@function Finds intersection value of 2 lines/values if any cross occurs - First function of challenge -> crossValue(source1, source2)
//@param source1 (float) source value 1
//@param source2 (float) source value 2
//@returns Intersection value
example:
value = crossValue(close, close )
🔹 crossoverValue()
//@function Finds intersection value of 2 lines/values if crossover occurs - Second function of challenge -> crossoverValue(source1, source2)
//@param source1 (float) source value 1
//@param source2 (float) source value 2
//@returns Intersection value
example:
value = crossoverValue(close, close )
🔹 crossunderValue()
//@function Finds intersect of 2 lines/values if crossunder occurs - Third function of challenge -> crossunderValue(source1, source2)
//@param source1 (float) source value 1
//@param source2 (float) source value 2
//@returns Intersection value
example:
value = crossunderValue(close, close )
🔶 DETAILS
A series of values can be displayed as a series of points, where the point location highlights its value, however, it is more common to connect each point with a line to have a continuous aspect.
A line is a geometrical object connecting two points, each having y and x coordinates. A line has a slope controlling its steepness and an intercept indicating where the line crosses an axis. With these elements, we can describe a line as follows:
slope × x + intercept
A cross between two series of values occurs when one series is greater or lower than the other while its previous value isn't.
We are interested in finding the "intersection value", that is the value where two crossing lines are equal. This problem can be approached via linear interpolation.
A simple and direct approach to finding our intersection value is to find the common scaling factor of the slopes of the lines, that is the multiplicative factor that multiplies both lines slopes such that the resulting points are equal.
Given:
A = Point A1 + m1 × scaling_factor
B = Point B1 + m2 × scaling_factor
where scaling_factor is the common scaling factor, and m1 and m2 the slopes:
m1 = Point A2 - Point A1
m2 = Point B2 - Point B1
In our cases, since the horizontal distance between two points is simply 1, our lines slopes are equal to their vertical distance (rise).
Under the event of a cross, there exists a scaling_factor satisfying A = B , which allows us to directly compute our intersection value. The solution is given by:
scaling_factor = (B1 - A1)/(m1 - m2)
As such our intersection value can be given by the following equivalent calculations:
(1) A1 + m1 × (B1 - A1)/(m1 - m2)
(2) B1 + m2 × (B1 - A1)/(m1 - m2)
(3) A2 - m2 × (A2 - B2)/(m1 - m2)
(4) B2 - m2 × (A2 - B2)/(m1 - m2)
The proposed functions use the third calculation.
This approach is equivalent to expressions using the classical line equation, with:
slope1 × x + intercept1 = slope2 × x + intercept2
By solving for x , the intersection point is obtained by evaluating any of the line equations for the obtained x solution.
🔶 APPLICATIONS
The intersection point of two crossing lines might lead to interesting applications and creations, in this section various information/tools derived from the proposed calculations are presented.
This supplementary material is available within the script.
🔹 Intersections As Support/Resistances
The script allows extending the lines of the intersection value when a cross is detected, these extended lines could have applications as support/resistance lines.
🔹 Using The Scaling Factor
The core of the proposed calculation method is the common scaling factor, which can be used to return useful information, such as the position of the cross relative to the x coordinates of a line.
The above image highlights two moving averages (in green and red), the cross-interval areas are highlighted in blue, and the intersection point is highlighted as a blue line.
The pane below shows a bar plot displaying:
1 - scaling factor = 1 -
Values closer to 1 indicate that the cross location is closer to x2 (the right coordinate of the lines), while values closer to 0 indicate that the cross location is closer to x1 .
🔹 Intersection Matrix
The main proposed functions of this challenge focus on the crossings between two series of values, however, we might be interested in applying this over a collection of series.
We can see in the image above how the lines connecting two points intersect with each other, we can construct a matrix populated with the intersection value of two corresponding lines. If (X, Y) represents the intersection value between lines X and Y we have the following matrix:
| Line A | Line B | Line C | Line D |
-------|--------|--------|--------|--------|
Line A | | (A, B) | (A, C) | (A, D) |
Line B | (B, A) | | (B, C) | (B, D) |
Line C | (C, A) | (C, B) | | (C, D) |
Line D | (D, A) | (D, B) | (D, C) | |
We can see that the upper triangular part of this matrix is redundant, which is why the script does not compute it. This function is provided in the script as intersectionMatrix :
//@function Return the N * N intersection matrix from an array of values
//@param array_series (array) array of values, requires an array supporting historical referencing
//@returns (matrix) Intersection matrix showing intersection values between all array entries
In the script, we create an intersection matrix from an array containing the outputs of simple moving averages with a period in a specific user set range and can highlight if a simple moving average of a certain period crosses with another moving average with a different period, as well as the intersection value.
🔹 Magnification Glass
Crosses on a chart can be quite small and might require zooming in significantly to see a detailed picture of them. Using the obtained scaling factor allows reconstructing crossing events with an higher resolution.
A simple supplementary zoomIn function is provided to this effect:
//@function Display an higher resolution representation of intersecting lines
//@param source1 (float) source value 1
//@param source2 (float) source value 2
//@param css1 (color) color of source 1 line
//@param css2 (color) color of source 2 line
//@param intersec_css (color) color of intersection line
//@param area_css (color) color of box area
Users can obtain a higher resolution by modifying the provided "Resolution" setting.
The function returns a higher resolution representation of the most recent crosses between two input series, the intersection value is also provided.
Trend Line XrossTrend Line Xross (TLX) Uses User Input Points to draw trendlines and displays the exact intersection point of those trendlines.
This is the public indicator of the practical application for this intersection method included in my entry for Pinefest #1.
To determine the exact intersection point I am using the y-intercept method as seen below.
The code is notated for more information on the technical workings.
One difference to note between this version and the pinefest version is that I had to change the line drawings to use bar_index values so that I can use line.get_price() to grab the current value of the line to make alerts from.
Additionally, there are alerts built-in to this version for every type of cross on all of the visible lines.
Enjoy!
TUE Renko Box/Time TesterThe TUE Renko Box/Time Tester is a technical indicator designed to quantify the frequency of consecutive duplicate timestamps within Renko charts on the TradingView platform. It serves the critical purpose of assessing the prevalence of identical timestamps, a crucial factor for the accurate automation of trading strategies.
The presence of duplicate timestamps can impede the reliability of automated trading systems. This indicator systematically examines Renko bars and identifies instances where successive bars share the same timestamp. The quantified data aids traders and developers in evaluating the quality and suitability of their Renko chart data for algorithmic trading purposes.
To ensure proper speed and precision in automation, traders are advised to run Renko charts on either 1-second or 5-second timeframes. Adjusting the box sizes of Renko charts based on these timeframes is essential.
The objective is to maintain the incidence of duplicate timestamps at levels below 20%, ensuring the robustness and consistency of automated trading strategies. By providing a quantitative analysis of timestamp duplication, this indicator supports traders in optimizing their trading systems for enhanced accuracy and efficiency.
The script will automatically collate only the last two days' worth of data, in order to maintain timestamp integrity. You should be able to view individual seconds on your timestamps, and if they're all reading :00 at the end, then you have ran out of seconds-level data. This is only done with a Premium or higher subscription.
Get start of previous day on any timeframeUseful on pine scripts which need to identify the start of the previous trading day i.e. from the perspective of today's date - not the previous day on each bar calculation.
Works on any timeframe - which is the whole point as on a daily chart you can simply do time .
VWAP (Any Anchor)Hello Traders,
Introduction:
The Volume Weighted Average Price (VWAP) is a powerful trading indicator used to gauge the average price at which an asset has traded, weighted by volume, over a specific period.
One of the key factors that can significantly impact the effectiveness of VWAP is the concept of "anchoring." In this TradingView indicator script description, we'll explore the concept of anchoring and how it's integrated into a customizable VWAP indicator.
Understanding Anchoring:
Anchoring in VWAP refers to selecting a specific point in time from which the VWAP calculation begins.
This "anchor point" serves as the starting reference for VWAP, and it can substantially impact the indicator's behavior and interpretation.
Anchoring allows traders to adapt VWAP to different trading strategies and scenarios.
Here are some common anchor points used in the script and their significance:
1. Time-Based Anchors: Traders often anchor VWAP to specific times of the trading day, such as the market open (e.g., 9:30 am EST) or close (e.g., 4:00 pm EST).
You could add in the script any time-based anchor you think is relevant for your trading.
2. Event-Based Anchors: Anchoring can also be based on specific market events.
For example, some traders anchor VWAP to events like "3 Consecutive Green Candles" or "Supertrend" direction changes.
Feel free to adapt the script here and add the relevant events-based anchor for your trading.
3. Multi-Timeframe Anchoring: Traders can anchor VWAP on different timeframes, allowing them to analyze price and volume interactions across various horizons.
This flexibility is especially valuable for swing traders adapting to longer-term trends.
Anchor Selection
Traders can choose from various anchor points, including time-based, event-based, and even an "External Connector" for flexibility in adapting VWAP to specific scenarios.
The External connector is the output from another script used in this VWAP script.
Your script may have a condition being “true” whenever a signal is printed - you can use this signal as the anchor for the VWAP.
Conclusion:
Understanding anchoring in VWAP is essential for traders using this indicator effectively.
Choosing and customizing anchor points empowers traders to adapt VWAP to their specific trading styles and strategies.
Whether focused on intraday precision or analyzing longer-term trends, a customizable VWAP indicator with flexible anchoring options can be valuable to your trading toolkit.
Tailor your VWAP to your unique needs and gain deeper insights into market trends and price action.
Made with love
Dave
syminfo tableThis is nothing special, and it is not an indicator for investments.
I build this for my programming layout, so I can see all the output of the syminfo command.
Simply put...
It shows the commands on the left side,
and related outputs are on the right side.
TradingView.To Strategy Template (with Dyanmic Alerts)Hello traders,
If you're tired of manual trading and looking for a solid strategy template to pair with your indicators, look no further.
This Pine Script v5 strategy template is engineered for maximum customization and risk management.
Best part?
This Pine Script v5 template facilitates the dynamic construction of TradingView.TO alerts, sparing users the time and effort of mastering the TradingView.TO syntax and manually create alert commands.
This powerful tool gives much power to those who don't know how to code in Pinescript and want to automate their indicators' signals via TradingView.TO bot.
IMPORTANT NOTES
TradingView.TO is a trading bot software that forwards TradingView alerts to your brokers (examples: Binance, Oanda, Coinbase, Bybit, Metatrader 4/5, ...) for automating trading.
Many traders don't know how to create TradingView.TO dynamically-compatible alerts using the data from their TradingView scripts.
Traders using trading bots want their alerts to reflect the stop-loss/take-profit/trailing-stop/stop-loss to break options from your script and then create the orders accordingly.
This script showcases how to create TradingView.TO alerts dynamically.
TRADINGVIEW ALERTS
1) You'll have to create one alert per asset X timeframe = 1 chart.
Example: 1 alert for BTC/USDT on the 5 minutes chart, 1 alert for BTC/USDT on the 15-minute chart (assuming you want your bot to trade the BTC/USDT on the 5 and 15-minute timeframes)
2) Select the Order fills and alert() function calls condition
3) For each alert, the alert message is pre-configured with the text below
{{strategy.order.alert_message}}
Please leave it as it is.
It's a TradingView native variable that will fetch the alert text messages built by the script.
4) TradingView.TO uses webhook technology - setting a webhook URL from the alerts notifications tab is required.
KEY FEATURES
I) Modular Indicator Connection
* plug your existing indicator into the template.
* Only two lines of code are needed for full compatibility.
Step 1: Create your connector
Adapt your indicator with only 2 lines of code and then connect it to this strategy template.
To do so:
1) Find in your indicator where the conditions print the long/buy and short/sell signals.
2) Create an additional plot as below
I'm giving an example with a Two moving averages cross.
Please replicate the same methodology for your indicator, whether a MACD , ZigZag, Pivots , higher-highs, lower-lows or whatever indicator with clear buy and sell conditions.
//@version=5
indicator("Supertrend", overlay = true, timeframe = "", timeframe_gaps = true)
atrPeriod = input.int(10, "ATR Length", minval = 1)
factor = input.float(3.0, "Factor", minval = 0.01, step = 0.01)
= ta.supertrend(factor, atrPeriod)
supertrend := barstate.isfirst ? na : supertrend
bodyMiddle = plot(barstate.isfirst ? na : (open + close) / 2, display = display.none)
upTrend = plot(direction < 0 ? supertrend : na, "Up Trend", color = color.green, style = plot.style_linebr)
downTrend = plot(direction < 0 ? na : supertrend, "Down Trend", color = color.red, style = plot.style_linebr)
fill(bodyMiddle, upTrend, color.new(color.green, 90), fillgaps = false)
fill(bodyMiddle, downTrend, color.new(color.red, 90), fillgaps = false)
buy = ta.crossunder(direction, 0)
sell = ta.crossunder(direction, 0)
//////// CONNECTOR SECTION ////////
Signal = buy ? 1 : sell ? -1 : 0
plot(Signal, title = "Signal", display = display.data_window)
//////// CONNECTOR SECTION ////////
Important Notes
🔥 The Strategy Template expects the value to be exactly 1 for the bullish signal and -1 for the bearish signal
Now, you can connect your indicator to the Strategy Template using the method below or that one.
Step 2: Connect the connector
1) Add your updated indicator to a TradingView chart
2) Add the Strategy Template as well to the SAME chart
3) Open the Strategy Template settings, and in the Data Source field, select your 🔌Connector🔌 (which comes from your indicator)
Note it doesn’t have to be named 🔌Connector🔌 - you can name it as you want - however, I recommend an explicit name you can easily remember.
From then, you should start seeing the signals and plenty of other stuff on your chart.
🔥 Note that whenever you update your indicator values, the strategy statistics and visuals on your chart will update in real-time
II) BOT Risk Management:
- Max Drawdown:
Mode: Select whether the max drawdown is calculated in percentage (%) or USD.
Value: If the max drawdown reaches this specified value, set a value to halt the bot.
- Max Consecutive Days:
Use Max Consecutive Days BOT Halt: Enable/Disable halting the bot if the max consecutive losing days value is reached.
- Max Consecutive Days: Set the maximum number of consecutive losing days allowed before halting the bot.
- Max Losing Streak:
Use Max Losing Streak: Enable/Disable a feature to prevent the bot from taking too many losses in a row.
- Max Losing Streak Length: Set the maximum length of a losing streak allowed.
Margin Call:
- Use Margin Call: Enable/Disable a feature to exit when a specified percentage away from a margin call to prevent it.
Margin Call (%): Set the percentage value to trigger this feature.
- Close BOT Total Loss:
Use Close BOT Total Loss: Enable/Disable a feature to close all trades and halt the bot if the total loss is reached.
- Total Loss ($): Set the total loss value in USD to trigger this feature.
Intraday BOT Risk Management:
- Intraday Losses:
Use Intraday Losses BOT Halt: Enable/Disable halting the bot on reaching specified intraday losses.
Mode: Select whether the intraday loss is calculated in percentage (%) or USD.
- Max Intraday Losses (%): Set the value for maximum intraday losses.
Limit Intraday Trades:
- Use Limit Intraday Trades: Enable/Disable a feature to limit the number of intraday trades.
- Max Intraday Trades: Set the maximum number of intraday trades allowed.
Restart Intraday EA:
III) Order Types and Position Sizing
- Choose between market or limit orders.
- Set your position size directly in the template.
Please use the position size from the “Inputs” and not the “Properties” tab.
I know it's redundant. - the template needs this value from the "Inputs" tab to build the alerts, and the Backtester needs it from the "Properties" tab.
IV) Advanced Take-Profit and Stop-Loss Options
- Choose to set your SL/TP in either USD or percentages.
- Option for multiple take-profit levels and trailing stop losses.
- Move your stop loss to break even +/- offset in USD for “risk-free” trades.
V) Miscellaneous:
Retry order openings if they fail.
Order Types:
Select and specify order type and price settings.
Position Size:
Define the type and size of positions.
Leverage:
Leverage settings, including margin type and hedge mode.
Session:
Limit trades to specific sessions.
Dates:
Limit trades to a specific date range.
Trades Direction:
Direction: Specify the market direction for opening positions.
VI) Logger
The TradingView.TO commands are logged in the TradingView logger.
You'll find more information about it in this TradingView blog post .
WHY YOU MIGHT NEED THIS TEMPLATE
1) Transform your indicator into a TradingView.TO trading bot more easily than before
Connect your indicator to the template
Create your alerts
Set your EA settings
2) Save Time
Auto-generated alert messages for TradingView.TO.
I tested them all and checked with the support team what could/couldn’t be done.
3) Be in Control
Manage your trading risks with advanced features.
4) Customizable
Fits various trading styles and asset classes.
REQUIREMENTS
* Make sure you have your TradingView.TO account
* If there is any issue with the template, ask me in the comments section - I’ll answer quickly.
BACKTEST RESULTS FROM THIS POST
1) I connected this strategy template to a dummy Supertrend script.
I could have selected any other indicator or concept for this script post.
I wanted to share an example of how you can quickly upgrade your strategy, making it compatible with TradingView.TO.
2) The backtest results aren't relevant for this educational script publication.
I used realistic backtesting data but didn't look too much into optimizing the results, as this isn't the point of why I'm publishing this script.
This strategy is a template to be connected to any indicator - the sky is the limit. :)
3) This template is made to take 1 trade per direction at any given time.
Pyramiding is set to 1 on TradingView.
The strategy default settings are:
* Initial Capital: 100000 USD
* Position Size: 1%
* Commission Percent: 0.075%
* Slippage: 1 tick
* No margin/leverage used
Multiple Vertical LinesThis script allows you to have multiple vertical lines on your chart (for seeing how price action performs around certain times of interest to you.
You can adjust the code to add new lines or colours as you wish (or comment out any that are there if they don't suit you.
There is also a shaded area, so you can use that for delineating an amount of time.
The indicator is currently set to New York time, but you can adjust this to suit you.
ProfitView Strategy TemplateHello traders,
This script took me a full week of coding/testing, sweat, and tears - and I’m too nice as I’m giving it for free to the community.
If you're tired of manual trading and looking for a solid strategy template to pair with your indicators, look no further.
This Pine Script v5 strategy template is engineered for maximum customization and risk management.
Best part?
This Pine Script v5 template facilitates the dynamic construction of ProfitView alerts, sparing users the time and effort of mastering the ProfitView syntax and manually creating alert commands.
This powerful tool gives much power to those who don't know how to code in Pinescript and want to automate their indicators' signals via the ProfitView Chrome extension.
IMPORTANT NOTES
ProfitView is a trading bot software that forwards TradingView alerts to your brokers (examples: Binance, Oanda, Coinbase, Bybit, etc.) for automating trading.
Many traders don't know how to dynamically create ProfitView-compatible alerts using the data from their TradingView scripts.
Traders using trading bots want their alerts to reflect the stop-loss/take-profit/trailing-stop/stop-loss to break options from your script and then create the orders accordingly.
This script showcases how to create ProfitView alerts dynamically.
TRADINGVIEW ALERTS
1) You'll have to create one alert per asset X timeframe = 1 chart.
Example: 1 alert for EUR/USD on the 5 minutes chart, 1 alert for EUR/USD on the 15-minute chart (assuming you want your bot to trade the EUR/USD on the 5 and 15-minute timeframes)
2) Select the Order fills and alert() function calls condition
3) For each alert, the alert message is pre-configured with the text below
{{strategy.order.alert_message}}
Please leave it as it is.
It's a TradingView native variable that will fetch the alert text messages built by the script.
4) ProfitView doesn't use webhook technology, so setting a webhook URL from the alerts notifications tab is unnecessary.
KEY FEATURES
I) Modular Indicator Connection
* plug your existing indicator into the template.
* Only two lines of code are needed for full compatibility.
Step 1: Create your connector
Adapt your indicator with only 2 lines of code and then connect it to this strategy template.
To do so:
1) Find in your indicator where the conditions print the long/buy and short/sell signals.
2) Create an additional plot as below
I'm giving an example with a Two moving averages cross.
Please replicate the same methodology for your indicator, whether a MACD , ZigZag, Pivots , higher-highs, lower-lows or whatever indicator with clear buy and sell conditions.
//@version=5
indicator("Supertrend", overlay = true, timeframe = "", timeframe_gaps = true)
atrPeriod = input.int(10, "ATR Length", minval = 1)
factor = input.float(3.0, "Factor", minval = 0.01, step = 0.01)
= ta.supertrend(factor, atrPeriod)
supertrend := barstate.isfirst ? na : supertrend
bodyMiddle = plot(barstate.isfirst ? na : (open + close) / 2, display = display.none)
upTrend = plot(direction < 0 ? supertrend : na, "Up Trend", color = color.green, style = plot.style_linebr)
downTrend = plot(direction < 0 ? na : supertrend, "Down Trend", color = color.red, style = plot.style_linebr)
fill(bodyMiddle, upTrend, color.new(color.green, 90), fillgaps = false)
fill(bodyMiddle, downTrend, color.new(color.red, 90), fillgaps = false)
buy = ta.crossunder(direction, 0)
sell = ta.crossunder(direction, 0)
//////// CONNECTOR SECTION ////////
Signal = buy ? 1 : sell ? -1 : 0
plot(Signal, title = "Signal", display = display.data_window)
//////// CONNECTOR SECTION ////////
Important Notes
🔥 The Strategy Template expects the value to be exactly 1 for the bullish signal and -1 for the bearish signal
Now, you can connect your indicator to the Strategy Template using the method below or that one.
Step 2: Connect the connector
1) Add your updated indicator to a TradingView chart
2) Add the Strategy Template as well to the SAME chart
3) Open the Strategy Template settings, and in the Data Source field, select your 🔌Connector🔌 (which comes from your indicator)
Note it doesn’t have to be named 🔌Connector🔌 - you can name it as you want - however, I recommend an explicit name you can easily remember.
From then, you should start seeing the signals and plenty of other stuff on your chart.
🔥 Note that whenever you update your indicator values, the strategy statistics and visuals on your chart will update in real-time
II) BOT Risk Management:
- Max Drawdown:
Mode: Select whether the max drawdown is calculated in percentage (%) or USD.
Value: If the max drawdown reaches this specified value, set a value to halt the bot.
- Max Consecutive Days:
Use Max Consecutive Days BOT Halt: Enable/Disable halting the bot if the max consecutive losing days value is reached.
- Max Consecutive Days: Set the maximum number of consecutive losing days allowed before halting the bot.
- Max Losing Streak:
Use Max Losing Streak: Enable/Disable a feature to prevent the bot from taking too many losses in a row.
- Max Losing Streak Length: Set the maximum length of a losing streak allowed.
Margin Call:
- Use Margin Call: Enable/Disable a feature to exit when a specified percentage away from a margin call to prevent it.
Margin Call (%): Set the percentage value to trigger this feature.
- Close BOT Total Loss:
Use Close BOT Total Loss: Enable/Disable a feature to close all trades and halt the bot if the total loss is reached.
- Total Loss ($): Set the total loss value in USD to trigger this feature.
Intraday BOT Risk Management:
- Intraday Losses:
Use Intraday Losses BOT Halt: Enable/Disable halting the bot on reaching specified intraday losses.
Mode: Select whether the intraday loss is calculated in percentage (%) or USD.
- Max Intraday Losses (%): Set the value for maximum intraday losses.
Limit Intraday Trades:
- Use Limit Intraday Trades: Enable/Disable a feature to limit the number of intraday trades.
- Max Intraday Trades: Set the maximum number of intraday trades allowed.
Restart Intraday EA:
- Use Restart Intraday EA: Enable/Disable a feature to restart the bot at the first bar of the next day if it has been stopped with an intraday risk management safeguard.
III) Order Types and Position Sizing
- Choose between market, limit, or stop orders.
- Set your position size directly in the template.
Please use the position size from the “Inputs” and not the “Properties” tab.
I know it's redundant. - the template needs this value from the "Inputs" tab to build the alerts, and the Backtester needs it from the "Properties" tab.
IV) Advanced Take-Profit and Stop-Loss Options
- Choose to set your SL/TP in either pips or percentages.
- Option for multiple take-profit levels and trailing stop losses.
- Move your stop loss to break even +/- offset in pips for “risk-free” trades.
V) Miscellaneous
Retry order openings if they fail.
Order Types:
Select and specify order type and price settings.
Position Size:
Define the type and size of positions.
Leverage:
Leverage settings, including margin type and hedge mode.
Session:
Limit trades to specific sessions.
Dates:
Limit trades to a specific date range.
Trades Direction:
Direction: Specify the market direction for opening positions.
VI) Notifications (Telegram/Discord/Email/IFTTT/Twilio/SMS)
Customize notifications sent to Telegram, Discord, Email, IFTTT, Twilio, and ProfitView Logger.
VII) Logger
The ProfitView commands are logged in the TradingView logger.
You'll find more information about it in this TradingView blog post .
WHY YOU MIGHT NEED THIS TEMPLATE
1) Transform your indicator into a ProfitView trading bot more easily than before
Connect your indicator to the template
Create your alerts
Set your EA settings
2) Save Time
Auto-generated alert messages for ProfitView.
I tested them all and checked with the support team what could/couldn’t be done.
3) Be in Control
Manage your trading risks with advanced features.
4) Customizable
Fits various trading styles and asset classes.
REQUIREMENTS
* Make sure you have your ProfitView account and do the settings correctly in your Chrome extension. If you don't know how to do it, read the documentation + ask for help in the ProfitView Discord support channel.
* If there is any issue with the template, ask me in the comments section - I’ll answer quickly.
BACKTEST RESULTS FROM THIS POST
1) I connected this strategy template to a dummy Supertrend script.
I could have selected any other indicator or concept for this script post.
I wanted to share an example of how you can quickly upgrade your strategy, making it compatible with ProfitView.
2) The backtest results aren't relevant for this educational script publication.
I used realistic backtesting data but didn't look too much into optimizing the results, as this isn't the point of why I'm publishing this script.
This strategy is a template to be connected to any indicator - the sky is the limit. :)
3) This template is made to take 1 trade per direction at any given time.
Pyramiding is set to 1 on TradingView.
The strategy default settings are:
* Initial Capital: 100000 USD
* Position Size: 1%
* Commission Percent: 0.075%
* Slippage: 1 tick
* No margin/leverage used
Best regards,
Dave
[AIO] Multi Collection Moving Averages 140 MA TypesAll In One Multi Collection Moving Averages.
Since signing up 2 years ago, I have been collecting various Сollections.
I decided to get it into a decent shape and make it one of the biggest collections on TV, and maybe the entire internet.
And now I'm sharing my collection with you.
140 Different Types of Moving Averages are waiting for you.
Specifically :
"
AARMA | Adaptive Autonomous Recursive Moving Average
ADMA | Adjusted Moving Average
ADXMA | Average Directional Moving Average
ADXVMA | Average Directional Volatility Moving Average
AHMA | Ahrens Moving Average
ALF | Ehler Adaptive Laguerre Filter
ALMA | Arnaud Legoux Moving Average
ALSMA | Adaptive Least Squares
ALXMA | Alexander Moving Average
AMA | Adaptive Moving Average
ARI | Unknown
ARSI | Adaptive RSI Moving Average
AUF | Auto Filter
AUTL | Auto-Line
BAMA | Bryant Adaptive Moving Average
BFMA | Blackman Filter Moving Average
CMA | Corrected Moving Average
CORMA | Correlation Moving Average
COVEMA | Coefficient of Variation Weighted Exponential Moving Average
COVNA | Coefficient of Variation Weighted Moving Average
CTI | Coral Trend Indicator
DEC | Ehlers Simple Decycler
DEMA | Double EMA Moving Average
DEVS | Ehlers - Deviation Scaled Moving Average
DONEMA | Donchian Extremum Moving Average
DONMA | Donchian Moving Average
DSEMA | Double Smoothed Exponential Moving Average
DSWF | Damped Sine Wave Weighted Filter
DWMA | Double Weighted Moving Average
E2PBF | Ehlers 2-Pole Butterworth Filter
E2SSF | Ehlers 2-Pole Super Smoother Filter
E3PBF | Ehlers 3-Pole Butterworth Filter
E3SSF | Ehlers 3-Pole Super Smoother Filter
EDMA | Exponentially Deviating Moving Average (MZ EDMA)
EDSMA | Ehlers Dynamic Smoothed Moving Average
EEO | Ehlers Modified Elliptic Filter Optimum
EFRAMA | Ehlers Modified Fractal Adaptive Moving Average
EHMA | Exponential Hull Moving Average
EIT | Ehlers Instantaneous Trendline
ELF | Ehler Laguerre filter
EMA | Exponential Moving Average
EMARSI | EMARSI
EPF | Edge Preserving Filter
EPMA | End Point Moving Average
EREA | Ehlers Reverse Exponential Moving Average
ESSF | Ehlers Super Smoother Filter 2-pole
ETMA | Exponential Triangular Moving Average
EVMA | Elastic Volume Weighted Moving Average
FAMA | Following Adaptive Moving Average
FEMA | Fast Exponential Moving Average
FIBWMA | Fibonacci Weighted Moving Average
FLSMA | Fisher Least Squares Moving Average
FRAMA | Ehlers - Fractal Adaptive Moving Average
FX | Fibonacci X Level
GAUS | Ehlers - Gaussian Filter
GHL | Gann High Low
GMA | Gaussian Moving Average
GMMA | Geometric Mean Moving Average
HCF | Hybrid Convolution Filter
HEMA | Holt Exponential Moving Average
HKAMA | Hilbert based Kaufman Adaptive Moving Average
HMA | Harmonic Moving Average
HSMA | Hirashima Sugita Moving Average
HULL | Hull Moving Average
HULLT | Hull Triple Moving Average
HWMA | Henderson Weighted Moving Average
IE2 | Early T3 by Tim Tilson
IIRF | Infinite Impulse Response Filter
ILRS | Integral of Linear Regression Slope
JMA | Jurik Moving Average
KA | Unknown
KAMA | Kaufman Adaptive Moving Average & Apirine Adaptive MA
KIJUN | KIJUN
KIJUN2 | Kijun v2
LAG | Ehlers - Laguerre Filter
LCLSMA | 1LC-LSMA (1 line code lsma with 3 functions)
LEMA | Leader Exponential Moving Average
LLMA | Low-Lag Moving Average
LMA | Leo Moving Average
LP | Unknown
LRL | Linear Regression Line
LSMA | Least Squares Moving Average / Linear Regression Curve
LTB | Unknown
LWMA | Linear Weighted Moving Average
MAMA | MAMA - MESA Adaptive Moving Average
MAVW | Mavilim Weighted Moving Average
MCGD | McGinley Dynamic Moving Average
MF | Modular Filter
MID | Median Moving Average / Percentile Nearest Rank
MNMA | McNicholl Moving Average
MTMA | Unknown
MVSMA | Minimum Variance SMA
NLMA | Non-lag Moving Average
NWMA | Dürschner 3rd Generation Moving Average (New WMA)
PKF | Parametric Kalman Filter
PWMA | Parabolic Weighted Moving Average
QEMA | Quadruple Exponential Moving Average
QMA | Quick Moving Average
REMA | Regularized Exponential Moving Average
REPMA | Repulsion Moving Average
RGEMA | Range Exponential Moving Average
RMA | Welles Wilders Smoothing Moving Average
RMF | Recursive Median Filter
RMTA | Recursive Moving Trend Average
RSMA | Relative Strength Moving Average - based on RSI
RSRMA | Right Sided Ricker MA
RWMA | Regressively Weighted Moving Average
SAMA | Slope Adaptive Moving Average
SFMA | Smoother Filter Moving Average
SMA | Simple Moving Average
SSB | Senkou Span B
SSF | Ehlers - Super Smoother Filter P2
SSMA | Super Smooth Moving Average
STMA | Unknown
SWMA | Self-Weighted Moving Average
SW_MA | Sine-Weighted Moving Average
TEMA | Triple Exponential Moving Average
THMA | Triple Exponential Hull Moving Average
TL | Unknown
TMA | Triangular Moving Average
TPBF | Three-pole Ehlers Butterworth
TRAMA | Trend Regularity Adaptive Moving Average
TSF | True Strength Force
TT3 | Tilson (3rd Degree) Moving Average
VAMA | Volatility Adjusted Moving Average
VAMAF | Volume Adjusted Moving Average Function
VAR | Vector Autoregression Moving Average
VBMA | Variable Moving Average
VHMA | Vertical Horizontal Moving Average
VIDYA | Variable Index Dynamic Average
VMA | Volume Moving Average
VSO | Unknown
VWMA | Volume Weighted Moving Average
WCD | Unknown
WMA | Weighted Moving Average
XEMA | Optimized Exponential Moving Average
ZEMA | Zero Lag Moving Average
ZLDEMA | Zero-Lag Double Exponential Moving Average
ZLEMA | Ehlers - Zero Lag Exponential Moving Average
ZLTEMA | Zero-Lag Triple Exponential Moving Average
ZSMA | Zero-Lag Simple Moving Average
"
Don't forget that you can use any Moving Average not only for the chart but also for any of your indicators without affecting the code as in my example.
But remember that some MAs are not designed to work with anything other than a chart.
All MA and Code lists are sorted strictly alphabetically by short name (A-Z).
Each MA has its own number (ID) by which you can display the Moving Average you need.
Next to the ID selection there are tooltips with short names and their numbers. Use them.
The panel below will help you to read the Name of the selected MA.
Because of the size of the collection I think this is the optimal and most convenient use. Correct me if this is not the case.
Unknown - Some MAs I collected so long ago that I lost the full real name and couldn't find the authors. If you recognize them, please let me know.
I have deliberately simplified all MAs to input just Source and Length.
Because the collection is so large, it would be quite inconvenient and difficult to customize all MA functions (multipliers, offset, etc.).
If you need or like any MA you will still have to take it from my collection for your code.
I tried to leave the basic MA settings inside function in first strings.
I have tried to list most of the authors, but since the bulk of the collection was created a long time ago and was not intended for public publication I could not find all of them.
Some of the features were created from scratch or may have been slightly modified, so please be careful.
If you would like to improve this collection, please write to me in PM.
Also Credits, Likes, Awards, Loves and Thanks to :
@alexgrover
@allanster
@andre_007
@auroagwei
@blackcat1402
@bsharpe
@cheatcountry
@CrackingCryptocurrency
@Duyck
@ErwinBeckers
@everget
@glaz
@gotbeatz26107
@HPotter
@io72signals
@JacobAmos
@JoshuaMcGowan
@KivancOzbilgic
@LazyBear
@loxx
@LuxAlgo
@MightyZinger
@nemozny
@NGBaltic
@peacefulLizard50262
@RicardoSantos
@StalexBot
@ThiagoSchmitz
@TradingView
— 𝐀𝐧𝐝 𝐎𝐭𝐡𝐞𝐫𝐬 !
So just a Big Thank You to everyone who has ever and anywhere shared their codes.
Pineconnector Strategy Template (Connect Any Indicator)Hello traders,
If you're tired of manual trading and looking for a solid strategy template to pair with your indicators, look no further.
This Pine Script v5 strategy template is engineered for maximum customization and risk management.
Best part?
It’s optimized for Pineconnector, allowing seamless integration with MetaTrader 4 and 5.
This powerful tool gives a lot of power to those who don't know how to code in Pinescript and are looking to automate their indicators' signals on Metatrader 4/5.
IMPORTANT NOTES
Pineconnector is a trading bot software that forwards TradingView alerts to your Metatrader 4/5 for automating trading.
Many traders don't know how to dynamically create Pineconnector-compatible alerts using the data from their TradingView scripts.
Traders using trading bots want their alerts to reflect the stop-loss/take-profit/trailing-stop/stop-loss to break options from your script and then create the orders accordingly.
This script showcases how to create Pineconnector alerts dynamically.
Pineconnector doesn't support alerts with multiple Take Profits.
As a workaround, for 2 TPs, I had to open two trades.
It's not optimal, as we end up paying more spreads for that extra trade - however, depending on your trading strategy, it may not be a big deal.
TRADINGVIEW ALERTS
1) You'll have to create one alert per asset X timeframe = 1 chart.
Example: 1 alert for EUR/USD on the 5 minutes chart, 1 alert for EUR/USD on the 15-minute chart (assuming you want your bot to trade the EUR/USD on the 5 and 15-minute timeframes)
2) Select the Order fills and alert() function calls condition
3) For each alert, the alert message is pre-configured with the text below
{{strategy.order.alert_message}}
Please leave it as it is.
It's a TradingView native variable that will fetch the alert text messages built by the script.
4) Don't forget to set the Pineconnector webhook URL in the Notifications tab of the TradingView alerts UI.
You’ll find the URL on the Pineconnector documentation website.
EA CONFIGURATION
1) The Pyramiding in the EA on Metatrader must be set to 2 if you want to trade with 2 TPs => as it's opening 2 trades.
If you only want 1 TP, set the EA Pyramiding to 1.
Regarding the other EA settings, please refer to the Pineconnector documentation on their website.
2) In the EA, you can set a risk (= position size type) in %/lots/USD, as in the TradingView backtest settings.
KEY FEATURES
I) Modular Indicator Connection
* plug in your existing indicator into the template.
* Only two lines of code are needed for full compatibility.
Step 1: Create your connector
Adapt your indicator with only 2 lines of code and then connect it to this strategy template.
To do so:
1) Find in your indicator where the conditions print the long/buy and short/sell signals.
2) Create an additional plot as below
I'm giving an example with a Two moving averages cross.
Please replicate the same methodology for your indicator, whether it's a MACD , ZigZag , Pivots , higher-highs, lower-lows, or whatever indicator with clear buy and sell conditions.
//@version=5
indicator("Supertrend", overlay = true, timeframe = "", timeframe_gaps = true)
atrPeriod = input.int(10, "ATR Length", minval = 1)
factor = input.float(3.0, "Factor", minval = 0.01, step = 0.01)
= ta.supertrend(factor, atrPeriod)
supertrend := barstate.isfirst ? na : supertrend
bodyMiddle = plot(barstate.isfirst ? na : (open + close) / 2, display = display.none)
upTrend = plot(direction < 0 ? supertrend : na, "Up Trend", color = color.green, style = plot.style_linebr)
downTrend = plot(direction < 0 ? na : supertrend, "Down Trend", color = color.red, style = plot.style_linebr)
fill(bodyMiddle, upTrend, color.new(color.green, 90), fillgaps = false)
fill(bodyMiddle, downTrend, color.new(color.red, 90), fillgaps = false)
buy = ta.crossunder(direction, 0)
sell = ta.crossunder(direction, 0)
//////// CONNECTOR SECTION ////////
Signal = buy ? 1 : sell ? -1 : 0
plot(Signal, title = "Signal", display = display.data_window)
//////// CONNECTOR SECTION ////////
Important Notes
🔥 The Strategy Template expects the value to be exactly 1 for the bullish signal and -1 for the bearish signal
Now, you can connect your indicator to the Strategy Template using the method below or that one.
Step 2: Connect the connector
1) Add your updated indicator to a TradingView chart
2) Add the Strategy Template as well to the SAME chart
3) Open the Strategy Template settings, and in the Data Source field, select your 🔌Connector🔌 (which comes from your indicator)
Note it doesn’t have to be named 🔌Connector🔌 - you can name it as you want - however, I recommend an explicit name you can easily remember.
From then, you should start seeing the signals and plenty of other stuff on your chart.
🔥 Note that whenever you update your indicator values, the strategy statistics and visuals on your chart will update in real-time
II) Customizable Risk Management
- Choose between percentage or USD modes for maximum drawdown.
- Set max consecutive losing days and max losing streak length.
- I used the code from my friend @JosKodify for the maximum losing streak. :)
Will halt the EA and backtest orders fill whenever either of the safeguards above are “broken”
III) Intraday Risk Management
- Limit the maximum intraday losses both in percentage or USD.
- Option to set a maximum number of intraday trades.
- If your EA gets halted on an intraday chart, auto-restart it the next day.
IV) Spread and Account Filters
- Trade only if the spread is below a certain pip value.
- Set requirements based on account balance or equity.
V) Order Types and Position Sizing
- Choose between market, limit, or stop orders.
- Set your position size directly in the template.
Please use the position size from the “Inputs” and not the “Properties” tab.
Reason : The template sends the order on the same candle as the entry signals - at those entry signals candles, the position size isn’t computed yet, and the template can’t then send it to Pineconnector.
However, you can use the position size type (USD, contracts, %) from the “Properties” tab for backtesting.
In the EA, you can define the position size type for your orders in USD or lots or %.
VI) Advanced Take-Profit and Stop-Loss Options
- Choose to set your SL/TP in either pips or percentages.
- Option for multiple take-profit levels and trailing stop losses.
- Move your stop loss to break even +/- offset in pips for “risk-free” trades.
VII) Logger
The Pineconnector commands are logged in the TradingView logger.
You'll find more information about it in this TradingView blog post .
WHY YOU MIGHT NEED THIS TEMPLATE
1) Transform your indicator into a Pineconnector trading bot more easily than before
Connect your indicator to the template
Create your alerts
Set your EA settings
2) Save Time
Auto-generated alert messages for Pineconnector.
I tested them all, and I checked with the support team what could/can’t be done
3) Be in Control
Manage your trading risks with advanced features.
4) Customizable
Fits various trading styles and asset classes.
REQUIREMENTS
* Make sure you have your Pineconnector license ID.
* Create your alerts with the Pineconnector webhook URL
* If there is any issue with the template, ask me in the comments section - I’ll answer quickly.
BACKTEST RESULTS FROM THIS POST
1) I connected this strategy template to a dummy Supertrend script.
I could have selected any other indicator or concept for this script post.
I wanted to share an example of how you can quickly upgrade your strategy, making it compatible with Pineconnector.
2) The backtest results aren't relevant for this educational script publication.
I used realistic backtesting data but didn't look too much into optimizing the results, as this isn't the point of why I'm publishing this script.
This strategy is a template to be connected to any indicator - the sky is the limit. :)
3) This template is made to take 1 trade per direction at any given time.
Pyramiding is set to 1 on TradingView.
The strategy default settings are:
* Initial Capital: 100000 USD
* Position Size: 1 contract
* Commission Percent: 0.075%
* Slippage: 1 tick
* No margin/leverage used
WHAT’S COMING NEXT FOR YOU GUYS?
I’ll make the same template for ProfitView, then for AutoView, and then for Alertatron.
All of those are free and open-source.
I have no affiliations with any of those companies - I'm publishing those templates as they will be useful to many of you.
Dave
Risk Reward Optimiser [ChartPrime]█ CONCEPTS
In modern day strategy optimization there are few options when it comes to optimizing a risk reward ratio. Users frequently need to experiment and go through countless permutations in order to tweak, adjust and find optimal in their data.
Therefore we have created the Risk Reward Optimizer.
The Risk Reward Optimizer is a technical tool designed to provide traders with comprehensive insights into their trading strategies.
It offers a range of features and functionalities aimed at enhancing traders' decision-making process.
With a focus on comprehensive data, it is there to help traders quickly and efficiently locate Risk Reward optimums for inbuilt of custom strategies.
█ Internal and external Signals:
The script can optimize risk to reward ratio for any type of signals
You can utilize the following :
🔸Internal signals ➞ We have included a number of common indicators into the optimizer such as:
▫️ Aroon
▫️ AO (Awesome Oscillator)
▫️ RSI (Relative Strength Index)
▫️ MACD (Moving Average Convergence Divergence)
▫️ SuperTrend
▫️ Stochastic RSI
▫️ Stochastic
▫️ Moving averages
All these indicators have 3 conditions to generate signals :
Crossover
High Than
Less Than
🔸External signal
▫️ by incorporating your own indicators into the analysis. This flexibility enables you to tailor your strategy to your preferences.
◽️ How to link your signal with the optimizer:
In order to be able to analysis your signal we need to read it and to do so we would need to PLOT your signal with a defined value
plot( YOUR LONG Condition ? 100 : 0 , display = display.data_window)
█ Customizable Risk to Reward Ratios:
This tool allows you to test seven different customizable risk to reward ratios , helping you determine the most suitable risk-reward balance for your trading strategy. This data-driven approach takes the guesswork out of setting stop-loss and take-profit levels.
█ Comprehensive Data Analysis:
The tool provides a table displaying key metrics, including:
Total trades
Wins
Losses
Profit factor
Win rate
Profit and loss (PNL)
This data is essential for refining your trading strategy.
🔸 It includes a tooltip for each risk to reward ratio which gives data for the:
Most Profitable Trade USD value
Most Profitable Trade % value
Most Profitable Trade Bar Index
Most Profitable Trade Time (When it occurred)
Position and size is adjustable
█ Visual insights with histograms:
Visualize your trading performance with histograms displaying each risk to reward ratio trade space, showing total trades, wins, losses, and the ratio of profitable trades.
This visual representation helps you understand the strengths and weaknesses of your strategy.
It offers tooltips for each RR ratio with the average win and loss percentages for further analysis.
█ Dynamic Highlighting:
A drop-down menu allows you to highlight the maximum values of critical metrics such as:
Profit factor
Win rate
PNL
for quick identification of successful setups.
█ Stop Loss Flexibility:
You can adjust stop-loss levels using three different calculation methods:
ATR
Pivot
VWAP
This allows you to align risk-reward ratios with your preferred risk tolerance.
█ Chart Integration:
Visualize your trades directly on your price chart, with each trade displayed in a distinct color for easy tracking.
When your take-profit (TP) level is reached , the tool labels the corresponding risk-reward ratio for that specific TP, simplifying trade management.
█ Detailed Tooltips:
Tooltips provide deeper insights into your trading performance. They include information about the most profitable trade, such as the time it occurred, the bar index, and the percentage gain. Histogram tooltips also offer average win and loss percentages for further analysis.
█ Settings:
█ Code:
In summary, the Risk Reward Optimizer is a data-driven tool that offers traders the ability to optimize their risk-reward ratios, refine their strategies, and gain a deeper understanding of their trading performance. Whether you're a day trader, swing trader, or investor, this tool can help you make informed decisions and improve your trading outcomes.
Heatmap MACD Strategy - Pineconnector (Dynamic Alerts)Hello traders
This script is an upgrade of this template script.
Heatmap MACD Strategy
Pineconnector
Pineconnector is a trading bot software that forwards TradingView alerts to your Metatrader 4/5 for automating trading.
Many traders don't know how to dynamically create Pineconnector-compatible alerts using the data from their TradingView scripts.
Traders using trading bots want their alerts to reflect the stop-loss/take-profit/trailing-stop/stop-loss to breakeven options from your script and then create the orders accordingly.
This script showcases how to create Pineconnector alerts dynamically.
Pineconnector doesn't support alerts with multiple Take Profits.
As a workaround, for 2 TPs, I had to open two trades.
It's not optimal, as we end up paying more spreads for that extra trade - however, depending on your trading strategy, it may not be a big deal.
TradingView Alerts
1) You'll have to create one alert per asset X timeframe = 1 chart.
Example : 1 alert for EUR/USD on the 5 minutes chart, 1 alert for EUR/USD on the 15-minute chart (assuming you want your bot to trade the EUR/USD on the 5 and 15-minute timeframes)
2) For each alert, the alert message is pre-configured with the text below
{{strategy.order.alert_message}}
Please leave it as it is.
It's a TradingView native variable that will fetch the alert text messages built by the script.
3) Don't forget to set the webhook URL in the Notifications tab of the TradingView alerts UI.
EA configuration
The Pyramiding in the EA on Metatrader must be set to 2 if you want to trade with 2 TPs => as it's opening 2 trades.
If you only want 1 TP, set the EA Pyramiding to 1.
Regarding the other EA settings, please refer to the Pineconnector documentation on their website.
Logger
The Pineconnector commands are logged in the TradingView logger.
You'll find more information about it from this TradingView blog post
Important Notes
1) This multiple MACDs strategy doesn't matter much.
I could have selected any other indicator or concept for this script post.
I wanted to share an example of how you can quickly upgrade your strategy, making it compatible with Pineconnector.
2) The backtest results aren't relevant for this educational script publication.
I used realistic backtesting data but didn't look too much into optimizing the results, as this isn't the point of why I'm publishing this script.
3) This template is made to take 1 trade per direction at any given time.
Pyramiding is set to 1 on TradingView.
The strategy default settings are:
Initial Capital: 100000 USD
Position Size: 1 contract
Commission Percent: 0.075%
Slippage: 1 tick
No margin/leverage used
For example, those are realistic settings for trading CFD indices with low timeframes but not the best possible settings for all assets/timeframes.
Concept
The Heatmap MACD Strategy allows selecting one MACD in five different timeframes.
You'll get an exit signal whenever one of the 5 MACDs changes direction.
Then, the strategy re-enters whenever all the MACDs are in the same direction again.
It takes:
long trades when all the 5 MACD histograms are bullish
short trades when all the 5 MACD histograms are bearish
You can select the same timeframe multiple times if you don't need five timeframes.
For example, if you only need the 30min, the 1H, and 2H, you can set your timeframes as follow:
30m
30m
30m
1H
2H
Risk Management Features
All the features below are pips-based.
Stop-Loss
Trailing Stop-Loss
Stop-Loss to Breakeven after a certain amount of pips has been reached
Take Profit 1st level and closing X% of the trade
Take Profit 2nd level and close the remaining of the trade
Custom Exit
I added the option ON/OFF to close the opened trade whenever one of the MACD diverges with the others.
Help me help the community
If you see any issue when adding your strategy logic to that template regarding the orders fills on your Metatrader, please let me know in the comments.
I'll use your feedback to make this template more robust. :)
What's next?
I'll publish a more generic template built as a connector so you can connect any indicator to that Pineconnector template.
Then, I'll publish a template for Capitalise AI, ProfitView, AutoView, and Alertatron.
Thank you
Dave
Heatmap MACD StrategyHello traders
A customer gave me the idea indirectly after I made an update to that script:
Supertrend MTF Heatmap
Important Notes
The backtest results aren't relevant for this educational script publication.
I used realistic backtesting data but didn't look too much into optimizing the results, as this isn't the point of why I'm publishing this script.
I wanted to showcase that any Heatmap script can be converted into a strategy.
The strategy default settings are:
Initial Capital: 100000 USD
Position Size: 1 contract
Commission Percent: 0.075%
Slippage: 1 tick
No margin/leverage used
For example, those are realistic settings for trading CFD indices with low timeframes, but not the best possible settings for all assets/timeframes.
Concept
The Heatmap MACD Strategy allows selecting one MACD in five different timeframes.
You'll get an exit signal whenever one of the 5 MACDs changes direction.
Then, the strategy re-enters whenever all the MACDs are in the same direction again.
It takes:
long trades when all the 5 MACD histograms are bullish
short trades when all the 5 MACD histograms are bearish
You can select the same timeframe multiple times if you don't need five timeframes.
For example, if you only need the 30min, the 1H, and 2H, you can set your timeframes as follow:
30m
30m
30m
1H
2H
Risk Management Features
Nothing too fancy
All the features below are pips-based
Stop-Loss
Trailing Stop-Loss
Stop-Loss to Breakeven after a certain amount of pips has been reached
Take Profit 1st level and closing X% of the trade
Take Profit 2nd level and close the remaining of the trade
What's next?
I'll publish this script's open-source Pineconnector, ProfitView, and AutoView versions for educational purposes.
Thank you
Dave
EQ LEVELS / EquilibriumWhat is it, How to use it, How to adjust the settings? What Calculates EQ Level?
What is it?
EQ, Equilibrium, In the money market, the term "equilibrium" or "equilibrium" refers to the point at which supply and demand are equalised. At this point, money supply and money demand meet each other and interest rates stabilise at a certain level. Equilibrium in the money market reflects the overall financial balance in the economy
According to What Calculates the EQ Level?
Normally, there may be many different alternatives to this, but I have printed the result on the screen by adding the highest and lowest levels of the prices and averaging them to think of a simple solution.
How to use it?
I have added 4 timeframes for both long-term investors and traders to use. If you want to use which timeframe, you can select the timeframe you want from the settings and see it on the chart. For those who want to trade, my suggestion is to follow the daily eq levels and of course look at the weekly eq levels. The weekly eq level can give you an idea of what kind of price range the next day may be in.
How to Make Settings?
When you first add the indicator to the chart, it draws a line. You change it to a circle or plus in the settings, it will look like the picture I shared. I also share open source code and can make changes in the code.
Nedir?, Nasıl Kullanılır?, Ayarları Nasıl Yapılır? EQ Seviyesini Neye Göre Hesaplar?
Nedir?:
EQ yani Equilibrium, Para piyasasında "denge" veya "equilibrium" terimi, arz ve talebin eşitlendiği noktayı ifade eder. Bu noktada, para arzı ile para talebi birbirini karşılar ve faiz oranları belirli bir seviyede dengelenir. Para piyasasındaki denge, ekonomideki genel finansal dengeyi yansıtır
EQ Seviyesini Neye Göre Hesaplar?
Normalde bunun farlı bir çok alternatifi olabilir ama ben biraz basit bir çözüm düşünmek için fiyatların en yüksek ve en düşük seviyelerini toplayarak ve ortalamasını alarak çıka sonucu ekrana yazdırdım.
Nasıl Kullanılır?
Hem uzun vadeli yatırım yapanlar hem de trade yapanların kullanabilmesi için 4 zaman dilimi ekledim. Hangi zaman dilimini kullanmak istiyorsanız ayarlardan istediniz zaman dilimini seçip onu grafikte görebilirsiniz. Trade yapmak isteyenler için önerim günlük eq seviyelerini takip etmeleri ve tabiki haftalık eq seviyelerine bakın. Haftalık eq seviyesi size bir sonra ki günün nasıl bir fiyat aralığı içerisinde olabileceği konusunda fikir verebilir.
Ayarları Nasıl Yapılır?
Grafiğe indikatörü ilk eklediğiniz de çizgi çizdirir. Siz ayarlardan onu daire veya artı olarak değiştirin benim paylaştığım resimde ki gibi görünecektir. Ayrıca açık kaynak kodlu paylaşıyorum isteyen kod içerisinde değişiklikler yapabilir.
AMT: Gamma Levels PlotterAMT: Custom Levels Plotter Indicator
Purpose:
This indicator is designed to allow users to directly visualize custom price levels and their associated labels on a trading chart by copying and pasting data from the Gamma spreadsheet.
Features and Functionalities:
Direct Input from Gamma Spreadsheet:
Users can effortlessly copy rows of data from the Gamma spreadsheet and paste them into the indicator's input field. Each row should represent a price level followed by a tab (\t) and its associated label. There's no need for any adjustments or formatting changes; the indicator handles it all.
Label Size Selection:
A dropdown menu lets users select the desired size for the labels. Options include "Tiny", "Small", "Normal", and "Large".
Merge Levels Option:
A checkbox determines if labels for identical price levels should be merged. When activated, labels for the same price will consolidate; otherwise, they'll display individually.
Dynamic Visualization:
A horizontal line represents the specified price level on the chart.
An adjacent label displays the associated text.
If the "Merge Levels" option is active and there are multiple labels for the same price, they merge into one.
Automatic Cleanup:
The script automatically removes all previously plotted lines and labels before drawing the new set. This ensures the chart only displays the most recent set of levels and remains uncluttered.
Efficient Data Handling:
The indicator uses the levels and counts arrays to track unique price levels and their counts. This aids in accurately positioning labels, especially when merging is enabled.
Debugging Feature:
For diagnostic purposes, the indicator plots the size of the levels array. This helps monitor the array's growth and ensures it remains within expected limits.
Earnings LevelsI am proud to announce that the formerly secret "Key Earnings Levels" graphing tool will be freely available to TradingView users whereas before it was only available by monthly or annual subscription since its invention here at TradingView many years ago by Tim West. TradingView code writers wrote the original code for using this powerful tool and then Johannes Falkenburg re-wrote the code several years ago.
The most important FOUR days a year in a stock chart are the days that the company gives its quarterly update. Since the GRAND majority of companies have earnings, the indicator is called the "Key Earnings Level", or KEL for short. The unique part of the release of the quarterly update is that it can be "before the open" or "after the close" and the price action leading up to the earnings and immediately after the earnings are useful for future reference, as you'll see shortly.
The Key Earnings indicator plots a triangle for the range around the day before and the day after earnings and draws a mid-point line to capture the over/under level for that report. That mid-point line is then extended into the future for a minimum of one quarter until the next earnings report and as long as a year with the current code.
This triangle plot allows you to see how a stock is trading RELATIVE TO where it was trading when earnings were announced and when a glimpse into the current quarter along with projections for the upcoming year.
Simply put: Key Earnings Levels are the easiest way to see how a stock is doing relative to the most important four days a year.
You can devise your own trading strategies around these levels, but I want you to have this information so you can see it and know it too. I've kept this little secret of Key Hidden Levels to myself and my followers in the Key Hidden Levels Chat Room here at TradingView for far too long. I have occasionally published charts with the Key Earnings Levels but have not made the code freely available to TradingView subscribers.
If anyone has paid me for access to these indicators and wants a refund, I will be glad to do that. This is too important to keep from everyone any longer. I think it is essential to make this available to everyone to make sure we all have the most advantage we can get when investing and trading in the markets.
I hope you can all find the powerful benefit from using Key Earnings Levels and please thank Johannes Falkenburg aka @Vollchaot here at TradingView for writing the latest version of this code.
The idea itself came from using TradingView and the powerful graphing and layout features here to track our observations and to do research. Thank you TradingView for such a great product.
I look forward to answering any questions.
Sincerely,
Tim West
Paytience DistributionPaytience Distribution Indicator User Guide
Overview:
The Paytience Distribution indicator is designed to visualize the distribution of any chosen data source. By default, it visualizes the distribution of a built-in Relative Strength Index (RSI). This guide provides details on its functionality and settings.
Distribution Explanation:
A distribution in statistics and data analysis represents the way values or a set of data are spread out or distributed over a range. The distribution can show where values are concentrated, values are absent or infrequent, or any other patterns. Visualizing distributions helps users understand underlying patterns and tendencies in the data.
Settings and Parameters:
Main Settings:
Window Size
- Description: This dictates the amount of data used to calculate the distribution.
- Options: A whole number (integer).
- Tooltip: A window size of 0 means it uses all the available data.
Scale
- Description: Adjusts the height of the distribution visualization.
- Options: Any integer between 20 and 499.
Round Source
- Description: Rounds the chosen data source to a specified number of decimal places.
- Options: Any whole number (integer).
Minimum Value
- Description: Specifies the minimum value you wish to account for in the distribution.
- Options: Any integer from 0 to 100.
- Tooltip: 0 being the lowest and 100 being the highest.
Smoothing
- Description: Applies a smoothing function to the distribution visualization to simplify its appearance.
- Options: Any integer between 1 and 20.
Include 0
- Description: Dictates whether zero should be included in the distribution visualization.
- Options: True (include) or False (exclude).
Standard Deviation
- Description: Enables the visualization of standard deviation, which measures the amount of variation or dispersion in the chosen data set.
- Tooltip: This is best suited for a source that has a vaguely Gaussian (bell-curved) distribution.
- Options: True (enable) or False (disable).
Color Options
- High Color and Low Color: Specifies colors for high and low data points.
- Standard Deviation Color: Designates a color for the standard deviation lines.
Example Settings:
Example Usage RSI
- Description: Enables the use of RSI as the data source.
- Options: True (enable) or False (disable).
RSI Length
- Description: Determines the period over which the RSI is calculated.
- Options: Any integer greater than 1.
Using an External Source:
To visualize the distribution of an external source:
Select the "Move to" option in the dropdown menu for the Paytience Distribution indicator on your chart.
Set it to the existing panel where your external data source is placed.
Navigate to "Pin to Scale" and pin the indicator to the same scale as your external source.
Indicator Logic and Functions:
Sinc Function: Used in signal processing, the sinc function ensures the elimination of aliasing effects.
Sinc Filter: A filtering mechanism which uses sinc function to provide estimates on the data.
Weighted Mean & Standard Deviation: These are statistical measures used to capture the central tendency and variability in the data, respectively.
Output and Visualization:
The indicator visualizes the distribution as a series of colored boxes, with the intensity of the color indicating the frequency of the data points in that range. Additionally, lines representing the standard deviation from the mean can be displayed if the "Standard Deviation" setting is enabled.
The example RSI, if enabled, is plotted along with its common threshold lines at 70 (upper) and 30 (lower).
Understanding the Paytience Distribution Indicator
1. What is a Distribution?
A distribution represents the spread of data points across different values, showing how frequently each value occurs. For instance, if you're looking at a stock's closing prices over a month, you may find that the stock closed most frequently around $100, occasionally around $105, and rarely around $110. Graphically visualizing this distribution can help you see the central tendencies, variability, and shape of your data distribution. This visualization can be essential in determining key trading points, understanding volatility, and getting an overview of the market sentiment.
2. The Rounding Mechanism
Every asset and dataset is unique. Some assets, especially cryptocurrencies or forex pairs, might have values that go up to many decimal places. Rounding these values is essential to generate a more readable and manageable distribution.
Why is Rounding Needed? If every unique value from a high-precision dataset was treated distinctly, the resulting distribution would be sparse and less informative. By rounding off, the values are grouped, making the distribution more consolidated and understandable.
Adjusting Rounding: The `Round Source` input allows users to determine the number of decimal places they'd like to consider. If you're working with an asset with many decimal places, adjust this setting to get a meaningful distribution. If the rounding is set too low for high precision assets, the distribution could lose its utility.
3. Standard Deviation and Oscillators
Standard deviation is a measure of the amount of variation or dispersion of a set of values. In the context of this indicator:
Use with Oscillators: When using oscillators like RSI, the standard deviation can provide insights into the oscillator's range. This means you can determine how much the oscillator typically deviates from its average value.
Setting Bounds: By understanding this deviation, traders can better set reasonable upper and lower bounds, identifying overbought or oversold conditions in relation to the oscillator's historical behavior.
4. Resampling
Resampling is the process of adjusting the time frame or value buckets of your data. In the context of this indicator, resampling ensures that the distribution is manageable and visually informative.
Resample Size vs. Window Size: The `Resample Resolution` dictates the number of bins or buckets the distribution will be divided into. On the other hand, the `Window Size` determines how much of the recent data will be considered. It's crucial to ensure that the resample size is smaller than the window size, or else the distribution will not accurately reflect the data's behavior.
Why Use Resampling? Especially for price-based sources, setting the window size around 500 (instead of 0) ensures that the distribution doesn't become too overloaded with data. When set to 0, the window size uses all available data, which may not always provide an actionable insight.
5. Uneven Sample Bins and Gaps
You might notice that the width of sample bins in the distribution is not uniform, and there can be gaps.
Reason for Uneven Widths: This happens because the indicator uses a 'resampled' distribution. The width represents the range of values in each bin, which might not be constant across bins. Some value ranges might have more data points, while others might have fewer.
Gaps in Distribution: Sometimes, there might be no data points in certain value ranges, leading to gaps in the distribution. These gaps are not flaws but indicate ranges where no values were observed.
In conclusion, the Paytience Distribution indicator offers a robust mechanism to visualize the distribution of data from various sources. By understanding its intricacies, users can make better-informed trading decisions based on the distribution and behavior of their chosen data source.
