DiscordWebhooksLibrary🚀 Introduction
Welcome to the TradingView PineScript Library for Discord Webhook Integration! This library is designed for traders and developers who use TradingView for technical analysis and want to integrate their trading strategies with Discord notifications.
Key Features:
* Embed Creation: Easily create rich and informative embeds for your Discord messages, allowing you to send detailed trading alerts and summaries.
* Flexible Webhook Formatting: Customize your Discord messages with options for usernames, avatars, and text content, providing a personalized touch to your notifications.
* Simple Integration: Designed with simplicity in mind, this library can be integrated into your existing Pine Script trading strategies without extensive coding knowledge.
* Real-time Alerts: Utilize TradingView's alert system to send real-time trade signals and market updates to your Discord server.
Compatibility:
This library is compatible with TradingView's Pine Script version 5.
🍃 Code Snippets and Usage Examples
The following examples demonstrate how to use the Discord Webhook Integration Library in your TradingView Pine Scripts. These snippets cover various scenarios, showcasing the flexibility and utility of the library.
Example 1: Simple Alert with Markdown in Embed Description
embedDesc = "This is a **bold** and _italic_ alert message with a (replace_with_your_link)"
embedJson = createEmbedJSON("Simple Alert", embedDesc, 12345)
content = discordWebhookJSON("Alert from Captain Hook", "Captain Hook", na, embedJson)
Example 2: Multiple Embeds with Different Markdown Styles
embedDesc1 = "First alert with **bold** text"
embedDesc2 = "Second alert with _italic_ text"
embedDesc3 = "Third alert with ~~strikethrough~~"
embedJson1 = createEmbedJSON("Alert 1", embedDesc1, 654321)
embedJson2 = createEmbedJSON("Alert 2", embedDesc2, 123456)
embedJson3 = createEmbedJSON("Alert 3", embedDesc3, 111111)
embeds = embedJson1 + "," + embedJson2 + "," + embedJson3
content = discordWebhookJSON("Multiple Alerts", "Captain Hook", na, embeds)
Example 3: Complex Alert with Full Markdown Usage in Embed
embedDesc = "Alert: **Price Breakout!**\\n\\n" +
"*Symbol*: " + syminfo.ticker + "\\n" +
"*Price*: $" + str.tostring(close) + "\\n\\n" +
" (replace_with_your_link)"
embedJson = createEmbedJSON("Complex Alert", embedDesc, 16711680) // Red color
content = discordWebhookJSON("Complex Alert", "Captain Hook", na, embedJson)
Example 4: Advanced Technical Analysis Alert
rsiValue = ta.rsi(close, 14)
= ta.macd(close, 12, 26, 9)
taMessage = "RSI: " + str.tostring(rsiValue) + "\\nMACD: " + str.tostring(macdLine)
embedJson = createEmbedJSON("Technical Analysis Update", taMessage, 255) // Blue color
content = discordWebhookJSON("TA Alert", "Captain Hook", na, embedJson)
Example 5: Market Summary with Multiple Fields
counterTrend = "Your counter trend criterias"
counterTrendEmbed = createEmbedJSON(title = "Counter Trend", description = counterTrend, color = 15258703)
redFlags = "Your red flag criterias"
redFlagsEmbed = createEmbedJSON(title = "Red Flags", description = redFlags, color = 15229263)
embeds = counterTrendEmbed + "," + redFlagsEmbed
content = discordWebhookJSON(contentText = "Example of how a market analysis could look like", username = "Captain Hook", embeds = embeds)
🚨 Error Handling
Use Escape Characters Correctly: In message strings, remember to use \\n for new lines instead of \n. This ensures that the newline character is correctly interpreted in the JSON format.
It can be helpful to plot the json on the last candle
if barstate.islast
label.new(bar_index, high, text=debugMessage, color=color.red, textcolor=color.white, yloc=yloc.abovebar)
🔥 FAQs
Q1: Can I send alerts for multiple conditions?
A: Yes, you can configure multiple conditions in your script. Use separate if statements for each condition and call the discordWebhookJSON function with the relevant message for each alert.
Q2: Why is my alert not triggering?
A: Ensure your alert conditions are correct and that you've properly set up the webhook in both your script and TradingView's alert configuration. Also, check for any syntax errors in your script.
Q3: How many alerts can I send to Discord?
A: While TradingView doesn't limit the number of alerts, Discord has rate limits for webhooks. Be mindful of these limits to avoid your webhook being temporarily blocked.
Q4: Can I customize the appearance of my Discord messages?
A: Yes, the createEmbedJSON function allows you to customize your messages with titles, descriptions, colors, and more. Experiment with different parameters to achieve the desired appearance.
Q5: Is it possible to include real-time data in alerts?
A: Yes, your script can include real-time price data, indicator values, or any other real-time data available in Pine Script.
Q6: How can I contribute to the library or suggest improvements?
A: You can provide feedback, suggest improvements, or contribute to the library's development through the community channels or contact points provided in the "Support and Community" section.
formatTimeframe()
discordWebhookJSON(contentText, username, avatar_url, embeds)
Constructs a JSON string for a Discord webhook message. This string includes optional fields for content, username, avatar URL, and embeds.
Parameters:
contentText (string) : (string, optional): The main text content of the webhook message. Default is 'na'.
username (string) : (string, optional): Overrides the default username of the webhook. Default is 'na'.
avatar_url (string) : (string, optional): Overrides the default avatar URL of the webhook. Default is 'na'.
embeds (string) : (string, optional): A string containing one or more embed JSON objects. This should be formatted correctly as a JSON array. Default is 'na'.
createEmbedJSON(title, description, color, authorName, authorUrl, authorIconUrl, fields)
Creates a JSON string for a single embed object for a Discord webhook.
Parameters:
title (string) : (string, optional): The title of the embed. Default is 'na' (not applicable).
description (string) : (string, optional): The description text of the embed. Supports basic formatting. Default is 'na'.
color (int) : (int, optional): The color code of the embed, typically in decimal format. Default is 'na'.
authorName (string) : (string, optional): The name of the author to display in the embed. Default is 'na'.
authorUrl (string) : (string, optional): The URL linked to the author's name. Default is 'na'.
authorIconUrl (string) : (string, optional): The URL of the icon to display next to the author's name. Default is 'na'.
fields (string) : (string, optional): A string containing one or more field JSON objects. This should be formatted correctly as a JSON array. Default is 'na'. Note: Use the 'createEmbedFieldJSON' function to generate these JSON field strings before adding them to the array.
createEmbedFieldJSON(name, value, inline)
Creates a JSON string representing a single field object within an embed for a Discord webhook message.
Parameters:
name (string) : (string): The name of the field, acting as a title for the field content.
value (string) : (string): The value of the field, containing the actual text or information you want to display within the field.
inline (bool) : (bool, optional): A boolean flag indicating whether the field should be displayed inline with other fields. If set to true, the field will be displayed on the same line as the next field
❤️ Please, support the work with like & comment! ❤️
Cerca negli script per "北京地铁3号线和12号线线路图"
Temporary imbalances 2.0 This indicator attempts to calculate potential points of imbalance and equilibrium based on VWAPs and modified moving averages. The idea is to determine if there has been a change in volume and perform the calculation from that point It uses the standard deviation to determine the significant imbalance threshold. Candles with bullish imbalances are highlighted in green, while candles with bearish imbalances are highlighted in red.
"It also features a set of VWAPs and modified moving averages that you can enable or disable."
When you activate the 'Show Anchor VWAP' option, it will add five modified VWAPs.
Practical Significance:
The Anchored VWAP is a volume-weighted average price that serves as a dynamic reference to assess the average price during specific moments of market imbalance.
During a bullish imbalance, the anchor_vwap reflects the VWAP at that moment, emphasizing price behavior during that specific period.
Similarly, in a bearish imbalance, the anchor_vwap provides the associated VWAP for that condition, highlighting price movements during the imbalance phase.
How to Use:
The anchor_vwap can be employed to contextualize the volume-weighted average price during critical moments associated with significant changes in market imbalance.
By analyzing price behavior during and after periods of imbalance, the Anchored VWAP can help better understand market dynamics and identify potential areas of support or resistance.
Show VWAP Percent Imbalance"
Definition: Represents the Volume Weighted Average Price (VWAP) adjusted by the volume-weighted average of the price multiplied by volume, with a focus on conditions where the percentage volume variation surpasses a predefined threshold.
Calculation: Utilizes the simple moving average weighted of the product of the volume-weighted average price and volume only when the percentage volume variation exceeds a specific threshold.
Interpretation: Provides insight into the volume-weighted price trend during conditions where the percentage volume variation exceeds a predefined limit.
The "showDeltaVWAP" is a toggleable setting that you can turn on or off. When activated, it displays special lines on the chart. Let's understand what these lines represent:
Delta Anchor VWAP:
A green line (Delta Anchor VWAP) represents a measure of market volume imbalance.
Delta2 Anchor VWAP:
A red line (Delta2 Anchor VWAP) shows another perspective of volume imbalance.
VWAP Delta Volume:
A light blue line (VWAP Delta Volume) displays a volume-weighted average of price.
VWAP Delta Volume2:
An orange line (VWAP Delta Volume2) shows another view of the volume-weighted average of price.
Delta3 Anchor VWAP:
A light blue line (Delta3 Anchor VWAP) represents a combination of the previous measures.
Delta4 Anchor VWAP:
A purple line (Delta4 Anchor VWAP) is another combination, providing an overall view.
These lines are based on different conditions and calculations related to trading volume. When you activate "showDeltaVWAP," these lines appear on the chart, aiding in better understanding market behavior.
"Show Faster Volatility" is an option that you can enable or disable. When activated (set to true), it displays special lines on the chart called "Faster Volatility VWAP," "Faster Volatility VWAP2," and "Faster Volatility VWAP3." Let's understand what these lines represent:
Faster Volatility VWAP:
A purple line (Faster Volatility VWAP) is a Volume Weighted Average Price (VWAP) that is calculated more quickly based on short-term price reversal patterns.
Faster Volatility VWAP2:
A light gray line (Faster Volatility VWAP2) is another Volume Weighted Average Price (VWAP) that is calculated even more quickly based on even shorter-term price reversal patterns.
Faster Volatility VWAP3:
A purple line (Faster Volatility VWAP3) is another Volume Weighted Average Price (VWAP) calculated rapidly based on even shorter-term price reversal patterns.
These lines are designed to indicate moments of possible exhaustion of volatility in the market, suggesting that there may be a subsequent increase in volatility. When you activate "Show Faster Volatility," these lines are displayed on the chart.
"Show Average VWAPs Imbalance" displays weighted averages of different Volume Weighted Average Prices (VWAPs) in relation to specific market conditions. Here's an explanation of each component:
Standard VWAP:
The blue line represents the standard VWAP, a volume-weighted average of asset prices over a specific period.
VWAP with Added Imbalance (avg_vwap2):
The pink line is a weighted average that adds an imbalance value to the standard VWAP. This component highlights periods of market imbalance.
VWAP with Balance (avg_vwap3):
The lilac line is a weighted average that adds balance based on the imbalance between uptrend and downtrend, reflecting changes in volume. This provides insights into supply and demand dynamics.
Overall Average of VWAPs (avg_vwaptl):
The violet line is a weighted average that incorporates both standard and adjusted VWAPs, offering an overview of market behavior under different considered conditions.
Visual Customization (Show Average VWAPs Imbalance):
Users have the option to show or hide these average lines on the chart, allowing for a clear visualization of market trends.
"Show Min Variation VWAP" is associated with the calculation and display of a smoothed version of the Volume Weighted Average Price (VWAP), taking into account the minimum price variation over a specific period.
"How Imbalance Anchor VWAP Calculated as the smoothed relationship between liquidity difference and maximum VWAP equilibrium" is associated with the calculation and display of a smoothed version of the Imbalance Anchor VWAP. Here is a detailed explanation:
Calculations and Smoothing:
The variable "smoothed_difference" represents the exponential moving average (EMA) of the difference between two variables related to liquidity.
"smoothed_difference2" is the division of "smoothed_difference" by the maximum variation of the VWAP Equilibrium.
"smoothed_difference3" involves additional manipulation of "smoothed_difference" and "vwap_delta3."
"smoothed_difference4" incorporates the previous results, adjusted by the value of the VWAP.
Visual Customization:
The user has the option to enable or disable the display on the chart.
The line is colored in a shade of green.
It provides a smoothed representation of the Imbalance Anchor VWAP.
The line is colored in a shade of blue, and the calculation involves the summation of moving averages (20, 50, 200). Afterward, there is division by 3. Additionally, there is the summation of moving averages (766, 866, 966), divided by 3. The final step is to add these results together and divide by 2. media name is Imbalance Value2
Show VWAP Equilibrium (Max Variation) Calculated as the difference between two VWAPs derived from the highest and lowest price changes
Show Equilibrium VWAP Calculated as the sum of VWAP and (sma200 - sma20)
calculate the difference between the media of 200 to 20
Show Equilibrium VWAP Calculated as the sum of VWAP and (766+866+966)/3 - (sma200 - sma20)
Show Equilibrium VWAP Standard Deviation Calculated as the Exponential Moving Average (EMA) of the Standard Deviation of SMA (sma200 + sma20 + sma8)/3
Show Equilibrium VWAP Delta Calculated as the ratio of the smoothed VWAP Delta Result componentes
Show Standard Deviation Equilibrium VWAP Delta: Calculated as the Standard Deviation between the Average of VWAP Delta Result Components and Their Smoothed Versions
This average attempts to calculate the equilibrium."
vwap_equilibrium:
Definition: Represents the Volume Weighted Average Price (VWAP) adjusted by the volume-weighted average of the price (hl2) multiplied by volume, focusing on periods of volume equilibrium.
Calculation: Utilizes the simple moving average weighted (sma) of the product of the volume-weighted average price and volume only when there is no volume imbalance.
Interpretation: This indicator provides a view of the volume-weighted price trend during moments when the market is in equilibrium, meaning there is no noticeable imbalance in volume conditions. The calculation of VWAP is adjusted to reflect market characteristics during periods of stability.
vwap_percent_condition:
Definition: Represents the Volume Weighted Average Price (VWAP) adjusted by the volume-weighted average of the price multiplied by volume, with a focus on conditions where the percentage volume variation surpasses a predefined threshold.
Calculation: Utilizes the simple moving average weighted of the product of the volume-weighted average price and volume only when the percentage volume variation exceeds a specific threshold.
Interpretation: Provides insight into the volume-weighted price trend during conditions where the percentage volume variation exceeds a predefined limit.
The objective of these two VWAPs is to calculate possible equilibrium points between buyers and sellers.
The indicator works for all timeframes This indicator can be adjusted according to the preferences and characteristics of the specific asset or market. It provides clear visual information and can be used as a complementary tool for technical analysis in trading strategies.
Interesting
Interesting
lookback period 7 , 12, 20,70,200, 500,766,866,966
imbalance threshold 2.4, 3.3 ,4.2
The objective of this indicator is to identify and highlight various points of imbalance and equilibrium.
Candle size in pipsDescription
Enhance your trading strategy with precision using this script, designed to measure the range of a candle from wick to wick in pips. Whether you're implementing a specific pip requirement within a candle for your strategy, or simply seeking to better understand market dynamics, this tool provides valuable insights. The script is calculating the amount of pips between the high and the low then compares it to the minimal size you declared. If the amount of pips is more or equal to minimal size it will show the label.
Features
Alert Functionality: Opt to receive alerts by checking the checkbox (default: false).
Customizable Pip Threshold: Tailor the script to your needs by setting the minimum required pips to display on the screen (default: 12).
Different shape: circle, triangle up, triangle down, none
How to Use
Personalize your trading approach by integrating this script with your preferred strategy. For instance, in my strategy involving a 3M continuation, I leverage this tool to determine the pip count of the M15 candle before making entry decisions.
Note: Ensure you understand your strategy's requirements and adjust the script settings accordingly for optimal result s.
Feel free to reach out if you have any questions or require further assistance in maximizing the utility of this script.
Multi-Timeframe EMA Tracker by Ox_kaliThis script is an advanced trend analysis indicator crafted for traders who seek a detailed and customizable view of market trends across multiple timeframes. This tool utilizes exponential moving averages (EMAs) to offer insights into market direction and momentum.
Key Features:
Multi-Timeframe Analysis: MTEMA-Tracker covers a wide range of timeframes, including 1, 2, 3, 5, 10, 15, 30 minutes; 1, 2, 4, 6, 12 hours; 1 day; and 1 week. This allows traders to analyze market trends from various perspectives, from short-term fluctuations to longer-term movements.
EMA-Based Trend Determination: The indicator employs two EMAs (50 and 200 periods) for each timeframe to ascertain the market trend. A higher EMA50 compared to EMA200 indicates an uptrend, while the opposite scenario suggests a downtrend.
User-Defined Trend Colors: Traders can personalize the appearance of the trend lines with custom colors for upward and downward trends, enhancing visual clarity and quick interpretation.
Selectable Timeframe Display: MTEMA-Tracker by Ox_kali offers the flexibility to choose which timeframes to display, enabling traders to focus on the most relevant data for their trading strategy.
Average Trend Calculation: A unique feature of MTEMA-Tracker is its ability to compute the average trend across all selected timeframes, providing a holistic view of the market's general direction.
List of Parameters:
Color of the trend: Customizable color settings for both upward and downward trends.
Settings for the Lengths of the EMAs: Options to set the lengths of the short and long-term EMAs.
Display Options for Each Timeframe's EMA Trend: Ability to activate or deactivate the display of EMAs for each selected timeframe.
Indicators and Financial Name Label settings: To ensure maximum clarity and understanding of the displayed trends, users should not hesitate to use the function to display "indicators and financial name labels" in their settings. This feature will help in identifying the legends for each trend, making it easier to interpret the market direction for the selected timeframes.
Please note that the MTEMA-Tracker is not a guarantee of future market performance and should be used in conjunction with proper risk management. Always ensure that you have a thorough understanding of the indicator’s methodology and its limitations before making any investment decisions. Additionally, past performance is not indicative of future results.
Zemog Channels[Zemogtrading]Channels Strategy
User Description:
This Channels strategy is a powerful technical analysis tool that empowers traders with a comprehensive view of the market's support and resistance levels. Designed for both beginners and experienced traders, this strategy brings a systematic and adaptable approach to chart analysis.
Default Parameters:
Swing Length (SL): 45
Higher Timeframe: Daily (D)
Multiplier for Level 2: 3.5
Multiplier for Level 3: 12
How It Works:
Swing Analysis: The Swing Length (SL) parameter allows users to fine-tune the sensitivity of the strategy. A higher SL value provides a more smoothed-out analysis, ideal for a broader market perspective, while a lower value enhances responsiveness to short-term price movements.
Higher Timeframe Insights: The Channels fetches high and low prices from a user-specified higher timeframe (default: Daily). This ensures that the strategy is well-informed by significant price levels from a broader market context.
Dynamic ATR Calculation: The Average True Range (ATR) adapts dynamically to changing market conditions. This ensures that support and resistance levels adjust in real-time based on the prevailing volatility, providing traders with adaptive insights.
Smoothed Support and Resistance: Utilizing a Smoothed Moving Average (SMA), the strategy calculates support and resistance levels based on high and low prices from the higher timeframe. This smoothing effect enhances clarity in identifying key levels, facilitating more informed trading decisions.
Additional Levels: The Channels introduces Level 2 and Level 3 support and resistance zones. Users can customize multipliers for these levels, allowing for the identification of secondary zones for potential market reversals.
Visualization: The strategy vividly plots support and resistance levels on the chart. Green lines indicate support, red lines denote resistance, and yellow lines represent additional support at Level 3.
Using Channels is a versatile tool that equips traders with a deeper understanding of crucial market levels. By seamlessly integrating swing analysis, higher timeframe data, and adaptive calculations, this strategy offers a holistic and user-friendly approach to technical analysis.
Scale Ability [TrendX_]Scale Ability indicator can indicate a company’s potential for future growth and profitability.
A scalable company is one that can increase its revenue and market share without increasing its costs proportionally, which can benefit from economies of scale. Therefore, the high-scale ability can generate more value for its shareholders - which is important for investment decisions.
Scale Ability indicator consists of 3 financial components:
Cash Flow from Investing Activities to Total Assets Ratio (CFIA / TA)
Net Income to Total Debt Ratio (NI / TD)
Earnings Before Interest, Taxes, Depreciation and Amortization to Equity Ratio (EBITDA / E)
These measures can help investors assess how efficiently and effectively a company uses its resources to generate revenue and profit.
Note:
This can be customizable between Fiscal Quarter (FQ) and Fiscal Year (Fy)
This is suitable for companies in fast-growing industries.
FUNCTION
CFIA / TA Ratio
A company with a net income to total debt of 9% could indicate that it is investing in its assets to keep up with the market demand and the technological changes which can create competitive advantages.
NI/ TD Ratio
A company with a net income to total debt of 9% could show that it is profitable and has a strong financial position, which can easily cover its debt payments.
EBITDA / E Ratio
A company with a net income to total debt of 14% illustrates that it is generating a high return on its equity.
USAGE
Scale index division:
> 43 : Excellent
32 - 43 : Good
12 - 31 : Above Average
= 11 : Average
8 - 10 : Below Average
5 - 7 : Poor
< 4 : Very Poor
DISCLAIMER
This is only a rough estimate, and the actual ratio may differ significantly depending on the stage of the business cycle and the company’s strategy, and the comparison of each company and its peers.
This indicator is not financial advice, it can only help traders make better decisions. There are many factors and uncertainties that can affect the outcome of any endeavor, and no one can guarantee or predict with certainty what will occur.
Therefore, one should always exercise caution and judgment when making decisions based on past performance.
Enhanced McClellan Summation Index
The Enhanced McClellan Summation Index (MSI) is a comprehensive tool that transforms the MSI indicator with Heikin-Ashi visualization, offering improved trend analysis and momentum insights. This indicator includes MACD and it's histogram calculations to refine trend signals, minimize false positives and offer additional momentum analysis.
Methodology:
McClellan Summation Index (MSI) -
The MSI begins by calculating the ratio between advancing and declining issues in the specified index.
float decl = 𝘐𝘯𝘥𝘪𝘤𝘦 𝘥𝘦𝘤𝘭𝘪𝘯𝘪𝘯𝘨 𝘪𝘴𝘴𝘶𝘦𝘴
float adv = 𝘐𝘯𝘥𝘪𝘤𝘦 𝘢𝘥𝘷𝘢𝘯𝘤𝘪𝘯𝘨 𝘪𝘴𝘴𝘶𝘦𝘴
float ratio = (adv - decl) / (adv + decl)
It then computes a cumulative sum of the MACD (the difference between a 19-period EMA and a 39-period EMA) of this ratio. The result is a smoothed indicator reflecting market breadth and momentum.
macd(float r) =>
ta.ema(r, 19) - ta.ema(r, 39)
float msi = ta.cum(macd(ratio))
Heikin-Ashi Transformation -
Heikin-Ashi is a technique that uses a modified candlestick formula to create a smoother representation of price action. It averages the open, close, high, and low prices of the current and previous periods. This transformation reduces noise and provides a clearer view of trends.
type bar
float o = open
float h = high
float l = low
float c = close
bar b = bar.new()
float ha_close = math.avg(b.o, b.h, b.l, b.c)
MACD and Histogram -
The Enhanced MSI incorporates MACD and histogram calculations to provide additional momentum analysis and refine trend signals. The MACD represents the difference between the 12-period EMA and the 26-period EMA of the MSI. The histogram is the visual representation of the difference between the MACD and its signal line.
Options:
Index Selection - Choose from TVC:NYA , NASDAQ:NDX , or TVC:XAX to tailor the MSI-HA to the desired market index.
MACD Settings - Adjust the parameters for the MACD calculation to fine-tune the indicator's responsiveness.
Ratio Multiplier - Apply scaling to the MSI to suit different market conditions and indices.
Benefits of Heikin-Ashi -
Smoothed Trends - Heikin-Ashi reduces market noise, providing a more apparent and smoothed representation of trends.
Clearer Patterns - Candlestick patterns are more distinct, aiding in the identification of trend reversals and continuations.
Utility and Use Cases:
Trend & Momentum Analysis - Utilize the tool's Heikin-Ashi visualization for clearer trend identification in confluence with it's MACD and histogram to gain additional insights into the strength and direction of trends, while filtering out potential false positives.
Breadth Analysis - Explore market breadth through the MSI's cumulative breadth indicator, gauging the overall health and strength of the underlying market.
- Alerts Setup Guide -
The Enhanced MSI is a robust indicator that combines the breadth analysis of the McClellan Summation Index with the clarity of Heikin-Ashi visualization and additional momentum insights from MACD and histogram calculations. Its customization options make it adaptable to various indices and market conditions, offering traders a comprehensive tool for trend and momentum analysis.
TASC 2023.12 Growth and Value Switching System█ OVERVIEW
This script implements a rotation system for trading value and growth ETFs, as developed by Markos Katsanos and detailed in the article titled 'Growth Or Value?' in TASC's December 2023 edition of Traders' Tips . The purpose of this script is to demonstrate how short-term momentum can be employed to track market trends and provide clarity on when to switch between value and growth.
█ CONCEPTS
The central concept of the presented rotation strategy is based on the observation that the stock market undergoes cycles favoring either growth or value stocks. Consequently, the script introduces a momentum trading system that is designed to switch between value and growth equities based on prevailing market conditions. Specifically tailored for long-term index investors, the system focuses on trading Vanguard's value and growth ETFs ( VTV and VUG ) on a weekly timeframe.
To identify the ETF likely to outperform, the script uses a custom relative strength indicator applied to both VTV and VUG in comparison with an index ( SPY ). To minimize risk and drawdowns during bear markets, when both value and growth experience downtrends, the script employs the author's custom volume flow indicator (VFI) and blocks trades when its reading indicates money outflow . Positions are closed if the relative strength of the current open trade ETF falls below that of the other ETF for two consecutive weeks and is also below its moving average. Additionally, the script implements a stop-loss when the ETF is trading below its 40-week moving average, but only during bear markets.
The script plots the relative strengths of the value and growth equities along with the signals triggered by the aforementioned rules. Information about the current readings of the relative strength and volume flow indicators, along with the current open position, is displayed in a table.
█ CALCULATIONS
The script uses the request.security() function to gather price data for both equities and the reference index. Custom relative strength and volume flow indicators are calculated based on the formulas presented in the original article. By default, the script employs the same parameters for these indicators as proposed in the original article for VTV and VUG on a weekly timeframe.
Session Fibonacci Levels [QuantVue]The "Session Fibonacci Levels" indicator is a powerful tool designed for traders who aim to use Fibonacci retracement and extension levels in their trading strategy.
The indicator combines Fibonacci levels with customized trading sessions, allowing traders to observe and utilize Fibonacci levels that are automatically calculated for each defined session.
This approach offers a dynamic and session-relevant perspective on potential support and resistance levels, which can be crucial for intraday trading strategies.
🔹The indicator calculates Fibonacci retracement and extension levels based on the high and low prices of a specified trading session, dynamically adjusting to the location of the high and low bar.
If the low of the session occurs before the high, the fib levels are measured from low to high.
If the low of the session occurs after the high, the fib levels are measured from high to low.
🔹Users can set their time zone and define trading sessions, allowing for flexibility and applicability across global markets. This is particularly beneficial for traders who focus on specific market hours like the London or New York sessions.
Important sessions:
New York (8:00am - 5:00pm EST)
London (3:00am - 12:00pm EST)
Asia (7:00pm - 4:00am EST)
Custom session (user defined session in indicator settings)
🔹The indicator dynamically updates Fibonacci levels as new highs and lows are made within the session, keeping the analysis current. Additionally, it provides alerts when prices hit key Fibonacci levels, aiding in timely decision-making.
How to Use:
Configure the time zone and session time
Once the session begins, the indicator will begin highlighting the session range
When the session ends, Fibonacci levels based on the high and low of the session will be drawn
Use these levels to identify potential support and resistance areas
Multi-TF AI SuperTrend with ADX - Strategy [PresentTrading]
## █ Introduction and How it is Different
The trading strategy in question is an enhanced version of the SuperTrend indicator, combined with AI elements and an ADX filter. It's a multi-timeframe strategy that incorporates two SuperTrends from different timeframes and utilizes a k-nearest neighbors (KNN) algorithm for trend prediction. It's different from traditional SuperTrend indicators because of its AI-based predictive capabilities and the addition of the ADX filter for trend strength.
BTC 8hr Performance
ETH 8hr Performance
## █ Strategy, How it Works: Detailed Explanation (Revised)
### Multi-Timeframe Approach
The strategy leverages the power of multiple timeframes by incorporating two SuperTrend indicators, each calculated on a different timeframe. This multi-timeframe approach provides a holistic view of the market's trend. For example, a 8-hour timeframe might capture the medium-term trend, while a daily timeframe could capture the longer-term trend. When both SuperTrends align, the strategy confirms a more robust trend.
### K-Nearest Neighbors (KNN)
The KNN algorithm is used to classify the direction of the trend based on historical SuperTrend values. It uses weighted voting of the 'k' nearest data points. For each point, it looks at its 'k' closest neighbors and takes a weighted average of their labels to predict the current label. The KNN algorithm is applied separately to each timeframe's SuperTrend data.
### SuperTrend Indicators
Two SuperTrend indicators are used, each from a different timeframe. They are calculated using different moving averages and ATR lengths as per user settings. The SuperTrend values are then smoothed to make them suitable for KNN-based prediction.
### ADX and DMI Filters
The ADX filter is used to eliminate weak trends. Only when the ADX is above 20 and the directional movement index (DMI) confirms the trend direction, does the strategy signal a buy or sell.
### Combining Elements
A trade signal is generated only when both SuperTrends and the ADX filter confirm the trend direction. This multi-timeframe, multi-indicator approach reduces false positives and increases the robustness of the strategy.
By considering multiple timeframes and using machine learning for trend classification, the strategy aims to provide more accurate and reliable trade signals.
BTC 8hr Performance (Zoom-in)
## █ Trade Direction
The strategy allows users to specify the trade direction as 'Long', 'Short', or 'Both'. This is useful for traders who have a specific market bias. For instance, in a bullish market, one might choose to only take 'Long' trades.
## █ Usage
Parameters: Adjust the number of neighbors, data points, and moving averages according to the asset and market conditions.
Trade Direction: Choose your preferred trading direction based on your market outlook.
ADX Filter: Optionally, enable the ADX filter to avoid trading in a sideways market.
Risk Management: Use the trailing stop-loss feature to manage risks.
## █ Default Settings
Neighbors (K): 3
Data points for KNN: 12
SuperTrend Length: 10 and 5 for the two different SuperTrends
ATR Multiplier: 3.0 for both
ADX Length: 21
ADX Time Frame: 240
Default trading direction: Both
By customizing these settings, traders can tailor the strategy to fit various trading styles and assets.
Renko StrategyRENKO STRATEGY
CAUTION : This strategy must be applied to a candlestick chart (not a Renko chart).
INTRODUCTION :
The Traditional Renko chart has been reproduced and is plotted according to the evolution of the price. It will enable us to receive buy or sell signals and follow major trends. This is a medium/long term strategy and depends a lot on the box size chosen in the parameters. There's also a money management method allowing us to reinvest part of the profits or reduce the size of orders in the event of substantial losses.
RENKO CHART :
Renko chart construction methodology :
The user must first choose the box size. The minimum is 0.00001 and there is no maximum. The default is 10. The user must then choose the source that will define the data on which the calculations will be based (high, low, open, close). By default, close is selected. The first candle on the chart is used to draw the first box with its high and low.
Each time the price changes by the amount of the box size relative to the high or low of the last box, a new box is added above or below the previous one. If price variations are less than the box size, the same box is added next to the previous one. If price variations are N (integer number) times greater than box size, N boxes are added above or below the previous one. Each box added above the previous one is a green box, while each box added below the previous one is a red box.
Conditions for drawing a green box above the previous one :
(source - high_of_the_last_box) / box_size > 1
Condition for drawing a red box below the previous one :
(low_of_the_last_box - source) / box_size > 1
If neither condition is triggered, the same box is drawn next to the previous one.
Example :
The last candle has drawn a box with low 12 and high 14. The box size is therefore 2. The strategy will look at the value of the close each time a candle ends. The current candle closes with a close equal to 15.5. As the variation from the previous high is only 1.5 (which is less than the box size), the same box is added next to the previous one. The next candle closes at 16.2. The price variation is therefore 2.2 compared with the previous high. We can now add a new green box just above the previous one, with a low of 14 and a high of 16. The same process applies if the candle's close is at least one box size below the low of the last box. In this case, a new red box is placed below the previous one.
PARAMETERS :
Source : Allows you to specify which data will be taken into account by the strategy when performing calculations. The default is close.
Box size : Size of Renko graph boxes. This is a very important parameter to choose carefully, as it has a strong impact on the strategy's performance. Defaults to 10.
Fixed Ratio : This is the amount of gain or loss at which the order quantity is changed. The default is 400, meaning that for each $400 gain or loss, the order size is increased or decreased by a user-selected amount.
Increasing Order Amount : This is the amount to be added to or subtracted from orders when the fixed ratio is reached. The default is $200, which means that for every $400 gain, $200 is reinvested in the strategy. On the other hand, for every $400 loss, the order size is reduced by $200.
Initial capital : $1000
Fees : Interactive Broker fees apply to this strategy. They are set at 0.18% of the trade value.
Slippage : 3 ticks or $0.03 per trade. Corresponds to the latency time between the moment the signal is received and the moment the order is executed by the broker.
Important : A bot has been used to test all possible box sizes to find out which one generates the highest return on BITSTAMP:LTCUSD while limiting the drawdown. This strategy is the most optimal with a box size equal to 5.08 in 8h timeframe.
BUY AND SHORT SIGNALS :
As the aim of this strategy is to follow major trends based on price movements, we need to be on the right side of price fluctuation. We trade every box reversal, i.e. we are LONG when the boxes are green indicating an uptrend and SHORT when they are red indicating a downtrend.
RISK MANAGEMENT :
This strategy can incur losses. The size of the box is decisive, as it is used to plot the RENKO chart and thus trigger buy or sell signals. It's also what allows us to manage risk. For every trade, we risk a maximum amount equal to 2 times the size of the box, i.e. :(5.08*2*nb_contract)/trade_value.
MONEY MANAGEMENT :
The fixed ratio method has been used to manage our gains and losses. For each gain of an amount equal to the value of the fixed ratio, we increase the order size by a value defined by the user in the "Increasing order amount" parameter. Similarly, each time we lose an amount equal to the value of the fixed ratio, we decrease the order size by the same user-defined value. This strategy not only increases our performance, but also our drawdown.
Enjoy the strategy and don't forget to take the trade :)
WU Sahm Recession Indicator The Sahm Recession Indicator devised by Economist Claudia Sahm is a rather insightful tool that captures the onset of recessions by utilizing unemployment data, which can provide more real-time insights compared to quarterly GDP reports. If the three-month simple moving average (SMA) of the unemployment rate exceeds the minimum unemployment rate of the previous 12 months by 0.5 percentage points, it indicates a high likelihood of a recession.
This script allows you to visualize this indicator and set up alerts for when this criterion indicates that a recession could be coming.
Scoopy StacksWaffle Around Multiple
(Open, High, Low, Close) Stacks On
Pre/Post Market & (Daily, Weekly,
Monthly, Yearly) Sessions With
Meticulous Columns, Rows, Tooltips,
Colors, Custom Ideas, and Alerts.
Sessions Use Two Step Incremental Values
Default Value: (1) Shows Two Previous
(O, H, L, C); Increasing Value Swaps
Sessions With Next Two Stacks.
⬛️ KEY WORDS:
🟢 Crossover | 🔴 Crossunder
📗 High | 📕 Low
📔 Open | 📓 Close
🥇 First Idea | 🥈 Second Idea
🥉 Third Idea | 🎖️ Fourth Idea
🟥 ALERTS:
Default Option: (Per Bar)
Alerts Once Conditions Are Met
(Bar Close) Alerts When Bar Closes
Default Option: (Reg)
Alerts During Regular Market
Trading Hours, (0930-1600)
(Ext) Alerts During Extended
Market Hours, (1600-0930)
(24/7) Alerts All Day
Optional Preferences:
Regular Alerts - Stocks
Extended Alerts - Futures
24/7 Alerts - Crypto
🟧 STACKS:
Default Value: (1)
Incremental Stack Value, Increasing Value
Swaps Sessions With the Next Two Stacks
(✓) Swap Stacks?
Pre/Post Market High/Lows,
1-2 Day High/Lows, 1-2 Week High/Lows,
1-2 Month High/Lows, 1-2 Year High/Lows
( ) Swap Stacks?
Pre/Post Market Open/Close,
1-2 Day Open/Close, 1-2 Week Open/Close,
1-2 Month Open/Close, 1-2 Year Open/Close
🟨 EXAMPLES:
Default Stack:
🟢 | 📗 Pre Market High (PRE) | 4600.00
🔴 | 📕 Post Market Low (POST) | 420.00
Optional: (Open)
🟢 | 📔 Post Market Open (POST) | 4400.00
Optional: (Close)
🔴 | 📓 Pre Market Close (PRE) | 430.00
Default Stack Value: (1)
🔴 | 📗 1 Day High (1DH) | 460.00
Next Stack Value: (3)
🟢 | 📕 4 Day Low (4DL) | 420.00
Optional: (Open)
🔴 | 📔 2 Day Open (2DO) | 440.00
Optional: (Close)
🟢 | 📓 3 Day Close (3DC) | 430.00
Default Stack Value: (5)
🟢 | 📗 5 Week High (5WH) | 460.00
Next Stack Value: (7)
🔴 | 📕 8 Week Low (8WL) | 420.00
Optional: (Open)
🔴 | 📔 7 Week Open (7WO) | 4400.00
Optional: (Close)
🟢 | 📓 6 Week Close (6WC) | 430.00
Default Stack Value: (9)
🔴 | 📗 9 Month High (9MH) | 460.00
Next Stack Value: (11)
🟢 | 📕 12 Month Low (12ML) | 420.00
Optional: (Open)
🟢 | 📔 11 Month Open (11MO) | 4400.00
Optional: (Close)
🔴 | 📓 10 Month Close (10MC) | 430.00
Default Stack Value: (13)
🟢 | 📗 13 Year High (13YH) | 460.00
Next Stack Value: (15)
🟢 | 📕 16 Year Low (16YL) | 420.00
Optional: (Open)
🔴 | 📔 15 Year Open (15YO) | 4400.00
Optional: (Close)
🔴 | 📓 14 Year Close (14YC) | 430.00
🟩 TABLES:
Default Value: (1)
Moves Table Up, Down, Left, or Right
Based on Second Default Value
First Default Value: (Top Right)
Sets Table Placement, Middle Center
Allows Table To Move In All Directions
Second Default Value: (Default)
Fixed Table Position, Switching Values
Moves Direction of the Table
🟦 IDEAS:
(✓) Show Ideas?
Shows Four Ideas With Custom Texts
and Values; Ideas Are Based Around
Post-It Note Reminders with Alerts
Suggestions For Text Ideas:
Take Profit, Stop Loss, Trim, Hold,
Long, Short, Bounce Spot, Retest,
Chop, Support, Resistance, Buy, Sell
🟪 EXAMPLES:
Default Value: (5)
Shows the Custom Table Value For
Sorted Table Positions and Alerts
Default Text: (🥇)
Shown On First Table Cell and
Message Appearing On Alerts
Alert Shows: 🟢 | 🥇 | 5.00
Default Value: (10)
Shows the Custom Table Value For
Sorted Table Positions and Alerts
Default Text: (🥈)
Shown On Second Table Cell and
Message Appearing On Alerts
Alert Shows: 🔴 | 🥈 | 10.00
Default Value: (50)
Shows the Custom Table Value For
Sorted Table Positions and Alerts
Default Text: (🥉)
Shown On Third Table Cell and
Message Appearing On Alerts
Alert Shows: 🟢 | 🥉 | 50.00
Default Value: (100)
Shows the Custom Table Value For
Sorted Table Positions and Alerts
Default Text: (🎖️)
Shown On Fourth Table Cell and
Message Appearing On Alerts
Alert Shows: 🔴 | 🎖️ | 100.00
⬛️ REFERENCES:
Pre-market Highs & Lows on regular
trading hours (RTH) chart
By Twingall
Previous Day Week Highs & Lows
By Sbtnc
Screener for 40+ instruments
By QuantNomad
Daily Weekly Monthly Yearly Opens
By Meliksah55
Ribbit RangesBounce Around Multiple
(Open, High, Low, Close) Ranges
On Pre/Post Market & (Daily, Weekly,
Monthly, Yearly) Sessions With
Meticulous Lines, Labels, Tooltips,
Colors, Custom Ideas, and Alerts.
Sessions Use Two Step Incremental Values
Default Value: (1) Shows Two Previous
(O, H, L, C); Increasing Value Swaps
Sessions With Next Two Ranges.
⬛️ KEY WORDS:
🟢 Crossover | 🔴 Crossunder
📗 High | 📕 Low
📔 Open | 📓 Close
🥇 First Idea | 🥈 Second Idea
🥉 Third Idea | 🎖️ Fourth Idea
🟥 ALERTS:
Default Option: (Per Bar)
Alerts Once Conditions Are Met
(Bar Close) Alerts When Bar Closes
Default Option: (Reg)
Alerts During Regular Market
Trading Hours, (0930-1600)
(Ext) Alerts During Extended
Market Hours, (1600-0930)
(24/7) Alerts All Day
Optional Preferences:
Regular Alerts - Stocks
Extended Alerts - Futures
24/7 Alerts - Crypto
🟧 RANGES:
Default Value: (1)
Incremental Range Value, Increasing Value
Swaps Sessions With the Next Two Ranges
(✓) Swap Ranges?
Pre/Post Market High/Lows,
1-2 Day High/Lows, 1-2 Week High/Lows,
1-2 Month High/Lows, 1-2 Year High/Lows
( ) Swap Ranges?
Pre/Post Market Open/Close,
1-2 Day Open/Close, 1-2 Week Open/Close,
1-2 Month Open/Close, 1-2 Year Open/Close
🟨 EXAMPLES:
Default Range:
🟢 | 📗 Pre Market High (PRE) | 4600.00
🔴 | 📕 Post Market Low (POST) | 420.00
Optional: (Open)
🟢 | 📔 Post Market Open (POST) | 4400.00
Optional: (Close)
🔴 | 📓 Pre Market Close (PRE) | 430.00
Default Range Value: (1)
🔴 | 📗 1 Day High (1DH) | 460.00
Next Range Value: (3)
🟢 | 📕 4 Day Low (4DL) | 420.00
Optional: (Open)
🔴 | 📔 2 Day Open (2DO) | 440.00
Optional: (Close)
🟢 | 📓 3 Day Close (3DC) | 430.00
Default Range Value: (5)
🟢 | 📗 5 Week High (5WH) | 460.00
Next Range Value: (7)
🔴 | 📕 8 Week Low (8WL) | 420.00
Optional: (Open)
🔴 | 📔 7 Week Open (7WO) | 4400.00
Optional: (Close)
🟢 | 📓 6 Week Close (6WC) | 430.00
Default Range Value: (9)
🔴 | 📗 9 Month High (9MH) | 460.00
Next Range Value: (11)
🟢 | 📕 12 Month Low (12ML) | 420.00
Optional: (Open)
🟢 | 📔 11 Month Open (11MO) | 4400.00
Optional: (Close)
🔴 | 📓 10 Month Close (10MC) | 430.00
Default Range Value: (13)
🟢 | 📗 13 Year High (13YH) | 460.00
Next Range Value: (15)
🟢 | 📕 16 Year Low (16YL) | 420.00
Optional: (Open)
🔴 | 📔 15 Year Open (15YO) | 4400.00
Optional: (Close)
🔴 | 📓 14 Year Close (14YC) | 430.00
🟩 COLORS:
(✓) Swap Colors?
Text Color Is Shown Using
Background Color
( ) Swap Colors?
Background Color Is Shown
Using Text Color
🟦 IDEAS:
(✓) Show Ideas?
Plots Four Ideas With Custom Lines
and Labels; Ideas Are Based Around
Post-It Note Reminders with Alerts
Suggestions For Text Ideas:
Take Profit, Stop Loss, Trim, Hold,
Long, Short, Bounce Spot, Retest,
Chop, Support, Resistance, Buy, Sell
🟪 EXAMPLES:
Default Value: (5)
Shows the Custom Value For
Lines, Labels, and Alerts
Default Text: (🥇)
Shown On First Label and
Message Appearing On Alerts
Alert Shows: 🟢 | 🥇 | 5.00
Default Value: (10)
Shows the Custom Value For
Lines, Labels, and Alerts
Default Text: (🥈)
Shown On Second Label and
Message Appearing On Alerts
Alert Shows: 🔴 | 🥈 | 10.00
Default Value: (50)
Shows the Custom Value For
Lines, Labels, and Alerts
Default Text: (🥉)
Shown On Third Label and
Message Appearing On Alerts
Alert Shows: 🟢 | 🥉 | 50.00
Default Value: (100)
Shows the Custom Value For
Lines, Labels, and Alerts
Default Text: (🎖️)
Shown On Fourth Label and
Message Appearing On Alerts
Alert Shows: 🔴 | 🎖️ | 100.00
⬛️ REFERENCES:
Pre-market Highs & Lows on regular
trading hours (RTH) chart
By Twingall
Previous Day Week Highs & Lows
By Sbtnc
Screener for 40+ instruments
By QuantNomad
Daily Weekly Monthly Yearly Opens
By Meliksah55
Supertrend Multiasset Correlation - vanAmsen Hello traders!
I am elated to introduce the "Supertrend Multiasset Correlation" , a groundbreaking fusion of the trusted Supertrend with multi-asset correlation insights. This approach offers traders a nuanced, multi-layered perspective of the market.
The Underlying Concept:
Ever pondered over the term Multiasset Correlation?
In the intricate tapestry of financial markets, assets do not operate in silos. Their movements are frequently intertwined, sometimes palpably so, and at other times more covertly. Understanding these correlations can unlock deeper insights into overarching market narratives and directional trends.
By melding the Supertrend with multi-asset correlations, we craft a holistic narrative. This allows traders to fathom not merely the trend of a lone asset but to appreciate its dynamics within a broader market tableau.
Strategy Insights:
At the core of this indicator is its strategic approach. For every asset, a signal is generated based on the Supertrend parameters you've configured. Subsequently, the correlation of daily price changes is assessed. The ultimate signal on the selected asset emerges from the average of the squared correlations, factoring in their direction. This indicator not only accounts for the asset under scrutiny (hence a correlation of 1) but also integrates 12 additional assets. By default, these span U.S. growth ETFs, value ETFs, sector ETFs, bonds, and gold.
Indicator Highlights:
The "Supertrend Multiasset Correlation" isn't your run-of-the-mill Supertrend adaptation. It's a bespoke concoction, tailored to arm traders with an all-encompassing view of market intricacies, fortified with robust correlation metrics.
Key Features:
- Supertrend Line : A crystal-clear visual depiction of the prevailing market trajectory.
- Multiasset Correlation : Delve into the intricate interplay of various assets and their correlation with your primary instrument.
- Interactive Correlation Table : Nestled at the top right, this table offers a succinct overview of correlation metrics.
- Predictive Insights : Leveraging correlations to proffer predictive pointers, adding another layer of conviction to your trades.
Usage Nuances:
- The bullish Supertrend line radiates in a rejuvenating green hue, indicative of potential upward swings.
- On the flip side, the bearish trajectory stands out in a striking red, signaling possible downtrends.
- A rich suite of customization tools ensures that the chart resonates with your trading ethos.
Parting Words:
While the "Supertrend Multiasset Correlation" bestows traders with a rejuvenated perspective, it's paramount to embed it within a comprehensive trading blueprint. This would include blending it with other technical tools and adhering to stringent risk management practices. And remember, before plunging into live trades, always backtest to fine-tune your strategies.
IPDA Standard Deviations [DexterLab x TFO x toodegrees]> Introduction and Acknowledgements
The IPDA Standard Deviations tool encompasses the Time and price relationship as studied by @TraderDext3r .
I am not the creator of this Theory, and I do not hold the answers to all the questions you may have; I suggest you to study it from Dexter's tweets, videos, and material.
This tool was born from a collaboration between @TraderDext3r, @tradeforopp and I, with the objective of bringing a comprehensive IPDA Standard Deviations tool to Tradingview.
> Tool Description
This is purely a graphical aid for traders to be able to quickly determine Fractal IPDA Time Windows, and trace the potential Standard Deviations of the moves at their respective high and low extremes.
The disruptive value of this tool is that it allows traders to save Time by automatically adapting the Time Windows based on the current chart's Timeframe, as well as providing customizations to filter and focus on the appropriate Standard Deviations.
> IPDA Standard Deviations by TraderDext3r
The underlying idea is based on the Interbank Price Delivery Algorithm's lookback windows on the daily chart as taught by the Inner Circle Trader:
IPDA looks at the past three months of price action to determine how to deliver price in the future.
Additionally, the ICT concept of projecting specific manipulation moves prior to large displacement upwards/downwards is used to navigate and interpret the priorly mentioned displacement move. We pay attention to specific Standard Deviations based on the current environment and overall narrative.
Dexter being one of the most prominent Inner Circle Trader students, harnessed the fractal nature of price to derive fractal IPDA Lookback Time Windows for lower Timeframes, and studied the behaviour of price at specific Deviations.
For Example:
The -1 to -2 area can initiate an algorithmic retracement before continuation.
The -2 to -2.5 area can initiate an algorithmic retracement before continuation, or a Smart Money Reversal.
The -4 area should be seen as the ultimate objective, or the level at which the displacement will slow down.
Given that these ideas stem from ICT's concepts themselves, they are to be used hand in hand with all other ICT Concepts (PD Array Matrix, PO3, Institutional Price Levels, ...).
> Fractal IPDA Time Windows
The IPDA Lookbacks Types identified by Dexter are as follows:
Monthly – 1D Chart: one widow per Month, highlighting the past three Months.
Weekly – 4H to 8H Chart: one window per Week, highlighting the past three Weeks.
Daily – 15m to 1H Chart: one window per Day, highlighting the past three Days.
Intraday – 1m to 5m Chart: one window per 4 Hours highlighting the past 12 Hours.
Inside these three respective Time Windows, the extreme High and Low will be identified, as well as the prior opposing short term market structure point. These represent the anchors for the Standard Deviation Projections.
> Tool Settings
The User is able to plot any type of Standard Deviation they want by inputting them in the settings, in their own line of the text box. They will always be plotted from the Time Windows extremes.
As previously mentioned, the User is also able to define their own Timeframe intervals for the respective IPDA Lookback Types. The specific Timeframes on which the different Lookback Types are plotted are edge-inclusive. In case of an overlap, the higher Timeframe Lookback will be prioritized.
Finally the User is able to filter and remove Standard Deviations in two ways:
"Remove Once Invalidated" will automatically delete a Deviation once its outer anchor extreme is traded through.
Manual Toggles will allow to remove the Upward or Downward Deviation of each Time Window at the discretion of the User.
Major shoutout to Dexter and TFO for their Time, it was a pleasure to collaborate and create this tool with them.
GLGT!
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.
90 Minute Cycles90m cycles for 7:30-9, 9-10:30, 10:30-12
This indicator shows the 90 minute cycles for 7:30am-9am, 9am-10:30am and 10:30am-12pm New York time.
EphemerisLibrary "Ephemeris"
TODO: add library description here
mercuryElements()
mercuryRates()
venusElements()
venusRates()
earthElements()
earthRates()
marsElements()
marsRates()
jupiterElements()
jupiterRates()
saturnElements()
saturnRates()
uranusElements()
uranusRates()
neptuneElements()
neptuneRates()
rev360(x)
Normalize degrees to within [0, 360)
Parameters:
x (float) : degrees to be normalized
Returns: Normalized degrees
scaleAngle(longitude, magnitude, harmonic)
Scale angle in degrees
Parameters:
longitude (float)
magnitude (float)
harmonic (int)
Returns: Scaled angle in degrees
julianCenturyInJulianDays()
Constant Julian days per century
Returns: 36525
julianEpochJ2000()
Julian date on J2000 epoch start (2000-01-01)
Returns: 2451545.0
meanObliquityForJ2000()
Mean obliquity of the ecliptic on J2000 epoch start (2000-01-01)
Returns: 23.43928
getJulianDate(Year, Month, Day, Hour, Minute)
Convert calendar date to Julian date
Parameters:
Year (int) : calendar year as integer (e.g. 2018)
Month (int) : calendar month (January = 1, December = 12)
Day (int) : calendar day of month (e.g. January valid days are 1-31)
Hour (int) : valid values 0-23
Minute (int) : valid values 0-60
julianCenturies(date, epoch_start)
Centuries since Julian Epoch 2000-01-01
Parameters:
date (float) : Julian date to conver to Julian centuries
epoch_start (float) : Julian date of epoch start (e.g. J2000 epoch = 2451545)
Returns: Julian date converted to Julian centuries
julianCenturiesSinceEpochJ2000(julianDate)
Calculate Julian centuries since epoch J2000 (2000-01-01)
Parameters:
julianDate (float) : Julian Date in days
Returns: Julian centuries since epoch J2000 (2000-01-01)
atan2(y, x)
Specialized arctan function
Parameters:
y (float) : radians
x (float) : radians
Returns: special arctan of y/x
eccAnom(ec, m_param, dp)
Compute eccentricity of the anomaly
Parameters:
ec (float) : Eccentricity of Orbit
m_param (float) : Mean Anomaly ?
dp (int) : Decimal places to round to
Returns: Eccentricity of the Anomaly
planetEphemerisCalc(TGen, planetElementId, planetRatesId)
Compute planetary ephemeris (longtude relative to Earth or Sun) on a Julian date
Parameters:
TGen (float) : Julian Date
planetElementId (float ) : All planet orbital elements in an array. This index references a specific planet's elements.
planetRatesId (float ) : All planet orbital rates in an array. This index references a specific planet's rates.
Returns: X,Y,Z ecliptic rectangular coordinates and R radius from reference body.
calculateRightAscensionAndDeclination(earthX, earthY, earthZ, planetX, planetY, planetZ)
Calculate right ascension and declination for a planet relative to Earth
Parameters:
earthX (float) : Earth X ecliptic rectangular coordinate relative to Sun
earthY (float) : Earth Y ecliptic rectangular coordinate relative to Sun
earthZ (float) : Earth Z ecliptic rectangular coordinate relative to Sun
planetX (float) : Planet X ecliptic rectangular coordinate relative to Sun
planetY (float) : Planet Y ecliptic rectangular coordinate relative to Sun
planetZ (float) : Planet Z ecliptic rectangular coordinate relative to Sun
Returns: Planet geocentric orbital radius, geocentric right ascension, and geocentric declination
mercuryHelio(T)
Compute Mercury heliocentric longitude on date
Parameters:
T (float)
Returns: Mercury heliocentric longitude on date
venusHelio(T)
Compute Venus heliocentric longitude on date
Parameters:
T (float)
Returns: Venus heliocentric longitude on date
earthHelio(T)
Compute Earth heliocentric longitude on date
Parameters:
T (float)
Returns: Earth heliocentric longitude on date
marsHelio(T)
Compute Mars heliocentric longitude on date
Parameters:
T (float)
Returns: Mars heliocentric longitude on date
jupiterHelio(T)
Compute Jupiter heliocentric longitude on date
Parameters:
T (float)
Returns: Jupiter heliocentric longitude on date
saturnHelio(T)
Compute Saturn heliocentric longitude on date
Parameters:
T (float)
Returns: Saturn heliocentric longitude on date
neptuneHelio(T)
Compute Neptune heliocentric longitude on date
Parameters:
T (float)
Returns: Neptune heliocentric longitude on date
uranusHelio(T)
Compute Uranus heliocentric longitude on date
Parameters:
T (float)
Returns: Uranus heliocentric longitude on date
sunGeo(T)
Parameters:
T (float)
mercuryGeo(T)
Parameters:
T (float)
venusGeo(T)
Parameters:
T (float)
marsGeo(T)
Parameters:
T (float)
jupiterGeo(T)
Parameters:
T (float)
saturnGeo(T)
Parameters:
T (float)
neptuneGeo(T)
Parameters:
T (float)
uranusGeo(T)
Parameters:
T (float)
moonGeo(T_JD)
Parameters:
T_JD (float)
mercuryOrbitalPeriod()
Mercury orbital period in Earth days
Returns: 87.9691
venusOrbitalPeriod()
Venus orbital period in Earth days
Returns: 224.701
earthOrbitalPeriod()
Earth orbital period in Earth days
Returns: 365.256363004
marsOrbitalPeriod()
Mars orbital period in Earth days
Returns: 686.980
jupiterOrbitalPeriod()
Jupiter orbital period in Earth days
Returns: 4332.59
saturnOrbitalPeriod()
Saturn orbital period in Earth days
Returns: 10759.22
uranusOrbitalPeriod()
Uranus orbital period in Earth days
Returns: 30688.5
neptuneOrbitalPeriod()
Neptune orbital period in Earth days
Returns: 60195.0
jupiterSaturnCompositePeriod()
jupiterNeptuneCompositePeriod()
jupiterUranusCompositePeriod()
saturnNeptuneCompositePeriod()
saturnUranusCompositePeriod()
planetSineWave(julianDateInCenturies, planetOrbitalPeriod, planetHelio)
Convert heliocentric longitude of planet into a sine wave
Parameters:
julianDateInCenturies (float)
planetOrbitalPeriod (float) : Orbital period of planet in Earth days
planetHelio (float) : Heliocentric longitude of planet in degrees
Returns: Sine of heliocentric longitude on a Julian date
Ehlers SuperSmootherJohn F. Ehlers has provided the SuperSmoother filter in several of his works, including his book "Cyclical Analytics for Traders", Chapter 3.
The SuperSmoother filter is utilized whenever one might typically apply a moving average of any kind. The outcome is that the output signal from the SuperSmoother filter displays significantly less lag compared to an equivalent amount of smoothing from a moving average. The lag difference between a moving average and the SuperSmoother filter becomes even more pronounced when critical periods are extended.
Market data contains noise, and the purpose of smoothing filters is to mitigate this noise. In fact, there are various types of noise inherent in market data. One type of noise is systemic, originating from random trading activities. Another type is aliasing noise, which arises due to the use of discrete data. Aliasing noise dominates the data when considering shorter cycle durations.
It's tempting to perceive market data as a continuous wave, but that's a misconception. Taking the closing price as representative of a bar provides just a single data point. Whether you opt for the midpoint between the high and low instead of the closing price, you're still limited to one sample per bar. Given the discrete nature of this data, certain spectral implications must be considered. For instance, the shortest feasible analysis period (without aliasing) is a two-bar cycle. This is referred to as the Nyquist frequency, at 0.5 cycles per sample.
An ideally sampled two-beat sinusoidal cycle becomes rectified when discretized. However, peak sampling for the cycle isn't always guaranteed, and interference between the sampling rate and the data frequency results in aliasing noise. This noise decreases as the data period lengthens. For example, a four-beat cycle implies four samples per cycle. With more samples, the sampled data provides a better representation of the sinusoidal component. The replica becomes even more accurate for an eight-bar data component. The increased precision of discrete data signifies that aliasing noise decreases as cycle durations expand.
A smoothing filter should possess the selectivity to reduce the aliasing noise below systemic noise levels. Given that aliasing noise increases by 6 dB per octave above the filter's selected cutoff frequency and the SuperSmoother's attenuation rate is 12 dB per octave, the SuperSmoother filter emerges as an effective tool to virtually eliminate aliasing noise in its output signal.
There are already several SuperSmoother indicators on Tradingview, but I like to structure the code and highlight the main components as functions rather than hiding them in the code. I hope this is useful for those who are starting to learn Pine Script.
Weighted Oscillator Convergence DivergenceThe Weighted Oscillator Convergence Divergence (WOCD) aims to help traders identify potential trend reversals or momentum shifts in financial markets by calculating and visualizing the difference between a smoothed oscillator (WMA) value and its exponential moving average (EMA) and simple moving average (SMA) counterparts. This indicator is particularly useful for traders who want an alternative perspective on price momentum and divergence.
Key Features:
Inputs:
Length: The user can specify the number of bars to consider for calculations (default is 9).
Smoothing 1: Defines the smoothing factor for the first smoothed value (default is 5).
Smoothing 2: Specifies the smoothing factor for the second smoothed value (default is 7).
Ma Type: There are three types of moving averages you can choose (Wilder, non-lag, Weighted is by default).
Color Settings: Users can customize the indicator's colors for various elements, such as length, smoothing values, and different sections of the histogram.
Calculation:
WOCD calculates the raw oscillator value by subtracting the close price from a 3-period High, Low, Close (HLC3) moving average.
It then applies smoothing to this raw oscillator value using two different methods: exponential moving average (EMA) and simple moving average (SMA) with user-defined smoothing periods.
Histogram Plot:
The indicator plots a histogram based on the difference between the smoothed oscillator and the first smoothed value.
When the histogram is above zero and rising, it is colored according to the "Above Grow" color setting. When it's above zero and falling, it uses the "Fall" color for visualization.
Similarly, when the histogram is below zero and rising, it is colored according to the "Below Grow" color setting, and when it's below zero and falling, it uses the "Fall" color.
Oscillator and Smoothed Values:
The indicator also plots the smoothed oscillator, smoothed value 1 (EMA-based), and smoothed value 2 (SMA-based) on the chart.
Zero Line:
A horizontal line at zero is drawn on the chart for reference.
How to Use the WOCD Indicator:
Trend Identification: Observe the histogram's direction and color. A rising histogram above zero may indicate bullish momentum, while a falling histogram below zero could signal bearish momentum.
Divergence: Look for divergences between price action and the histogram. When the histogram and price move in opposite directions, it can be a potential reversal signal.
Crossovers: Pay attention to crossovers between the smoothed oscillator and its smoothed counterparts (EMA and SMA). These crossovers can indicate changes in trend strength or direction.
Zero Line: The zero line can act as a reference point. Positive histogram values suggest bullish sentiment, while negative values indicate bearish sentiment.
Comparison to MACD Indicator:
The WOCD indicator shares some similarities with the Moving Average Convergence Divergence (MACD) indicator but also has distinct differences:
Similarities:
Both WOCD and MACD are momentum oscillators designed to identify potential trend reversals and divergences.
They use moving averages (EMA in the case of MACD) to smooth the raw oscillator values.
Both indicators provide histogram representations of the difference between the oscillator and its smoothed counterpart.
Differences:
WOCD uses a 3-period High, Low, Close (HLC3) moving average to calculate the raw oscillator value, whereas MACD uses the difference between two exponential moving averages (usually 12-period and 26-period EMAs).
The smoothing in WOCD employs both EMA and SMA, while MACD exclusively uses EMA.
WOCD allows users to customize colors for various elements, enhancing visual clarity.
7 consecutive closes above/below the 5-periodThis script looks for 7 consecutive closes above/below the 5-period SMA. The indicator is inspired by legendary trader Linda Raschke's work.
First are the two models for which the indicator was created, both inspired by Raschke:
1) Persistency of trend / Extended run setup.
Around 10-12 times per year we get a persistency of trend in instruments in general.
After 7 consecutive closes above/below the 5-period as price pulls back we can look to enter in the direction of the main trend as it moves up/down above/below 5 ma again. You should use price action trading to pinpoint the entries. Now try to hold this as long as possible. Way longer than you can percieve or think is possible. Up to 24-28 periods is what we are looking for in these cases.
2) Normal usage.
When the trend is not persistent, it is possible to use this as an oscillating signal, for a shorter term trade, where we can look for a short or long term reversal setup in price action.
3) I also use it at as a learning to see the swing trades clearer. You can also use it as a visual aid for developing new variances of the classic swing trading setup.
Read and listen to Linda Raschkes work to learn more.
Alxuse Supertrend 4EMA Buy and Sell for tutorialAll abilities of Supertrend, moreover :
Drawing 4 EMA band & the ability to change values, change colors, turn on/off show.
Sends Signal Sell and Buy in multi timeframe.
The ability used in the alert section and create customized alerts.
To receive valid alerts the replay section , the timeframe of the chart must be the same as the timeframe of the indicator.
Supertrend with a simple EMA Filter can improve the performance of the signals during a strong trend.
For detecting the continuation of the downward and upward trend we can use 4 EMA colors.
In the upward trend , the EMA lines are in order of green, blue, red, yellow from bottom to top.
In the downward trend, the EMA lines are in order of yellow, red, blue, green from bottom to top.
How it works:
x1 = MA1 < MA2 and MA2 < MA3 and MA3 < MA4 and ta.crossunder(MA3, MA4)
x2 = MA1 < MA2 and MA2 < MA3 and MA3 < MA4 and ta.crossunder(MA2, MA3)
x3 = MA1 < MA2 and MA2 < MA3 and MA3 < MA4 and ta.crossunder(MA1, MA2)
y1 = MA4 < MA3 and MA3 < MA2 and MA2 < MA1 and ta.crossover(MA3, MA4)
y2 = MA4 < MA3 and MA3 < MA2 and MA2 < MA1 and ta.crossover(MA2, MA3)
y3 = MA4 < MA3 and MA3 < MA2 and MA2 < MA1 and ta.crossover(MA1, MA2)
Red triangle = x1 or x2 or x3
Green triangle = y1 or y2 or y3
Long = BUY signal and followed by a Green triangle
Exit Long = SELL signal
Short = SELL signal and followed by a Red triangle
Exit Short = BUY signal
It is also possible to get help from the Stochastic RSI and MACD indicators for confirmation.
For receiving a signal with these two conditions or more conditions, i am making a video tutorial that I will release soon.
Supertrend
Definition
Supertrend is a trend-following indicator based on Average True Range (ATR). The calculation of its single line combines trend detection and volatility. It can be used to detect changes in trend direction and to position stops.
The basics
The Supertrend is a trend-following indicator. It is overlaid on the main chart and their plots indicate the current trend. A Supertrend can be used with varying periods (daily, weekly, intraday etc.) and on varying instruments.
The Supertrend has several inputs that you can adjust to match your trading strategy. Adjusting these settings allows you to make the indicator more or less sensitive to price changes.
For the Supertrend inputs, you can adjust atrLength and multiplier:
the atrLength setting is the lookback length for the ATR calculation;
multiplier is what the ATR is multiplied by to offset the bands from price.
When the price falls below the indicator curve, it turns red and indicates a downtrend. Conversely, when the price rises above the curve, the indicator turns green and indicates an uptrend. After each close above or below Supertrend, a new trend appears.
Summary
The Supertrend helps you make the right trading decisions. However, there are times when it generates false signals. Therefore, it is best to use the right combination of several indicators. Like any other indicator, Supertrend works best when used with other indicators such as MACD, Parabolic SAR, or RSI.
Exponential Moving Average
Definition
The Exponential Moving Average (EMA) is a specific type of moving average that points towards the importance of the most recent data and information from the market. The Exponential Moving Average is just like it’s name says - it’s exponential, weighting the most recent prices more than the less recent prices. The EMA can be compared and contrasted with the simple moving average.
Similar to other moving averages, the EMA is a technical indicator that produces buy and sell signals based on data that shows evidence of divergence and crossovers from general and historical averages. Additionally, the EMA tries to amplify the importance that the most recent data points play in a calculation.
It is common to use more than one EMA length at once, to provide more in-depth and focused data. For example, by choosing 10-day and 200-day moving averages, a trader is able to determine more from the results in a long-term trade, than a trader who is only analyzing one EMA length.
It’s best to use the EMA when for trending markets, as it shows uptrends and downtrends when a market is strong and weak, respectively. An experienced trader will know to look both at the line the EMA projects, as well as the rate of change that comes from each bar as it moves to the next data point. Analyzing these points and data streams correctly will help the trader determine when they should buy, sell, or switch investments from bearish to bullish or vice versa.
Short-term averages, on the other hand, is a different story when analyzing Exponential Moving Average data. It is most common for traders to quote and utilize 12- and 26-day EMAs in the short-term. This is because they are used to create specific indicators. Look into Moving Average Convergence Divergence (MACD) for more information. Similarly, the 50- and 200-day moving averages are most common for analyzing long-term trends.
Moving averages can be very useful for traders using technical analysis for profit. It is important to identify and realize, however, their shortcomings, as all moving averages tend to suffer from recurring lag. It is difficult to modify the moving average to work in your favor at times, often having the preferred time to enter or exit the market pass before the moving average even shows changes in the trend or price movement for that matter.
All of this is true, however, the EMA strives to make this easier for traders. The EMA is unique because it places more emphasis on the most recent data. Therefore, price movement and trend reversals or changes are closely monitored, allowing for the EMA to react quicker than other moving averages.
Limitations
Although using the Exponential Moving Average has a lot of advantages when analyzing market trends, it is also uncertain whether or not the use of most recent data points truly affects technical and market analysis. In addition, the EMA relies on historical data as its basis for operating and because news, events, and other information can change rapidly the indicator can misinterpret this information by weighting the current prices higher than when the event actually occurred.
Summary
The Exponential Moving Average (EMA) is a moving average and technical indicator that reflects and projects the most recent data and information from the market to a trader and relies on a base of historical data. It is one of many different types of moving averages and has an easily calculable formula.
The added features to the indicator are made for training, it is advisable to use it with caution in tradings.
