[F][IND] - Draw Vertial Line at Last N BarDescription:
Enhance your trading analysis with the "Vertical Line at N Last Bars" script! This powerful tool provides traders with a visual reference to key points in the historical price action, aiding in the identification of crucial patterns, trends, and potential trading opportunities.
Key Features:
1. Customizable Parameters:
Tailor the script to your specific needs by adjusting the number of last bars (N) to plot vertical lines. This flexibility allows you to focus on short-term or long-term trends based on your trading strategy.
2. Visualize Critical Events:
Instantly mark important events, such as the release of economic data, key market sessions, or specific price levels. The vertical lines serve as a quick reference, making it easier for traders to identify correlations between events and price movements.
3. Enhance Technical Analysis:
Complement your technical analysis by visually highlighting points of interest on the chart. Whether you're tracking reversals, breakouts, or support/resistance levels, the script aids in better understanding price dynamics.
4. Easy to Use:
The script is designed with simplicity in mind. Just apply it to your chart, customize the parameters, and let it do the work for you. No complex coding or manual drawing required.
Alerts:
You can enable alerts on this indicator to receive timely notifications.
Disclaimer:
This indicator is provided for educational purposes only. Trading involves risk, and users should consult with a financial professional before making any trading decisions.
Your Feedback Matters!
Please feel free to comment or reach out if you have any improvement suggestions or if you would like to request the development of a specific indicator. Your feedback is invaluable!
Educational
[F][IND] - Big Candle IdentifierDescription:
The size of a candle in trading offers a fundamental insight into market direction. Larger candles often indicate robust price movements, suggesting strength in either buying or selling activity. In an uptrend, substantial green (bullish) candles signify strong buying momentum, while in a downtrend, sizable red (bearish) candles indicate significant selling pressure. Traders frequently interpret these larger candles as potential signals for a shift in sentiment or the continuation of an existing trend.
This indicator specifically identifies whether the candle body (the difference between Open and Close) is larger than the previous 5 candles. It serves as a simple yet effective tool for traders seeking recent notable candle movements as potential entry signals. It's crucial to emphasize that the indicator labels/alerts are initiated once the technical conditions are satisfied. However, it's imperative to wait for the candle to close to confirm that all technical conditions are met at the close of the candle.
It's important to note that while the candle body size provides valuable information, it's usually more effective when used in conjunction with other technical indicators and analysis methods. Traders often combine multiple tools to gain a comprehensive understanding of the market and make well-informed trading decisions.
Alerts:
You can enable alerts on this indicator to receive timely notifications.
Disclaimer:
This indicator is provided for educational purposes only. Trading involves risk, and users should consult with a financial professional before making any trading decisions.
Your Feedback Matters!
Please feel free to comment or reach out if you have any improvement suggestions or if you would like to request the development of a specific indicator. Your feedback is invaluable!
Limited Growth Stock-to-Flow (LGS2F) [AlgoAlpha]Description:
The "∂ Limited Growth Stock-to-Flow (LG-S2F)" indicator, developed by AlgoAlpha, is a technical analysis tool designed to analyze the price of Bitcoin (BTC) based on the Stock-to-Flow model. The indicator calculates the expected price range of BTC by incorporating variables such as BTC supply, block height, and model parameters. It also includes error bands to indicate potential overbought and oversold conditions.
How it Works:
The LG-S2F indicator utilizes the Stock-to-Flow model, which measures the scarcity of an asset by comparing its circulating supply (stock) to its newly produced supply (flow). In this script, the BTC supply and block height data are obtained to calculate the price using the model formula. The formula includes coefficients (a, b, c) and exponentiation functions to derive the expected price.
The script incorporates error bands based on uncertainty values derived from the standard errors of the model parameters. These error bands indicate the potential range of variation in the expected price, accounting for uncertainties in the model's parameters. The upper and lower error bands visualize potential overbought and oversold conditions, respectively.
Usage:
Traders can utilize the LG-S2F indicator to gain insights into the potential price movements of Bitcoin. The indicator's main line represents the expected price, while the error bands highlight the potential range of variation. Traders may consider taking long positions when the price is near or below the lower error band and short positions when the price is close to or above the upper error band.
It's important to note that the LG-S2F indicator is specifically designed for Bitcoin and relies on the Stock-to-Flow model. Users should exercise caution and consider additional analysis and factors before making trading decisions solely based on this indicator.
Originality:
The LG-S2F indicator, developed by QuantMario and AlgoAlpha, is an original implementation that combines the Stock-to-Flow model with error bands to provide a comprehensive view of BTC's potential price range. While the concept of Stock-to-Flow analysis exists, the specific calculations, incorporation of error bands, and customization options in this script are unique to QuantMario's methodology. The script is released under Mozilla Public License 2.0, allowing users to utilize and modify it while adhering to the license terms.
ICT Premium/DiscountGuided by ICT mentorship and help from TraderTim and its community, I created this versatile indicator to mark a "Premium/Discount" price range.
This indicator shows the Premium and Discount Zones in an alternative way, manually setting the start of the band and automatically shows the HTF and LTF FVG present only in the set band, having a cleaning of the graph from possible other distractions, so as to be able to have a clear vision clear of the set trading range
The user has the possibility to:
- Choose the start of the interval from the graph by moving the start line
- Choose to show levels 50% - 75% - 25% of the range
- Choose the color, style and size of the lines
- Choose to display FVG LTF or HTF in range
- Choose the FVG mitigation mode
The indicator must be used as shown by the ICT in its concepts, the Premium and Discount zones are nothing more than zones where the price risks retracing, and consequently we can evaluate making entries in the Premium Zone, Sell is evaluated, in the Discoutn Zone they are evaluated as Buy, taking the opposite area as Take Profit
As in the example below:
If anything is unclear, comment below and I will get back to you as soon as possible.
How to change range:
Mandelbrot SetThe Mandelbrot set represents a set of complex numbers with distinctive and very well known intricate geometric properties. Here I have attempted to implement it in Pinescript leveraging tables.
The defining formula for the set is:
Zn+1 = Zn2 + C
If, after a certain number of iterations, the magnitude of the complex number remains bounded (does not diverge to infinity), the point is considered part of the Mandelbrot set.
The Mandelbrot set exhibits intricate and infinitely detailed fractal patterns, characterized by self-similarity at different scales. Due to limitations in Pinescript and the number of possible table cells (Pinescript is not designed for this at all and this is merely a showcase of how flexible & great Pinescript can be it is) the resolution over this set is low.
Users can zoom in and out of the set via the provided inputs.
The values in each cell represent the number of iterations required for the corresponding point in the Mandelbrot set to escape a certain threshold.
Time & Sales (Tape) [By MUQWISHI]▋ INTRODUCTION :
The “Time and Sales” (Tape) indicator generates trade data, including time, direction, price, and volume for each executed trade on an exchange. This information is typically delivered in real-time on a tick-by-tick basis or lower timeframe, providing insights into the traded size for a specific security.
_______________________
▋ OVERVIEW:
_______________________
▋ Volume Dynamic Scale Bar:
It's a way for determining dominance on the time and sales table, depending on the selected length (number of rows), indicating whether buyers or sellers are in control in selected length.
_______________________
▋ INDICATOR SETTINGS:
#Section One: Table Settings
#Section Two: Technical Settings
(1) Implement By: Retrieve data by
(1A) Lower Timeframe: Fetch data from the selected lower timeframe.
(1B) Live Tick: Fetch data in real-time on a tick-by-tick basis, capturing data as soon as it's observed by the system.
(2) Length (Number of Rows): User able to select number of rows.
(3) Size Type: Volume OR Price Volume.
_____________________
▋ COMMENT:
The values in a table should not be taken as a major concept to build a trading decision.
Please let me know if you have any questions.
Thank you.
NCI - Lot size (Forex)Description:
The "NCI - Lot Size (Forex)" is a comprehensive tool designed for Forex traders to optimise their risk management strategies. This indicator dynamically calculates and displays the ideal lot size for your trades based on real-time currency conversion rates and your predefined risk parameters.
Key Features:
1. Real-Time Data Integration: Leverages current Forex market data from OANDA for major currency pairs, including USDJPY, USDCHF, AUDUSD, GBPUSD, NZDUSD, USDCAD, and EURUSD, ensuring accurate lot size calculations.
2. Customizable Account Balances: Set up to five different account balances to simulate various trading scenarios.
3. Adjustable Risk Management: Define your risk tolerance with a customizable risk percentage, allowing you to align the lot size calculations with your individual trading strategy.
4. Stoploss Adjustment: Input your desired stop loss in pips, which directly influences the calculated lot size, ensuring that your trades stay within your risk parameters.
5. Currency-Specific Adjustments: The script automatically adjusts the lot size based on the currency pair being traded, accounting for differences in currency values and volatility.
6. Intuitive Display: A clear and concise table is displayed on your chart, presenting the calculated lot sizes for each account balance and risk setting, alongside your specified stop loss.
7. User-Friendly Interface: Easy-to-use inputs make setting up the indicator a breeze, allowing both novice and experienced traders to make the most of this tool.
How to Use:
- Set your account balances (up to five different accounts).
- Define your risk percentage.
- Input your stop loss in pips.
- The table will dynamically show the ideal lot size for each account based on the current Forex market data and your settings.
---
Please Note: Trading in Forex involves significant risk and may not be suitable for all investors. The use of this indicator does not guarantee profits and should be used as part of a comprehensive trading strategy.
Choose Symbol, Mode with HullThis Pine Script code is designed to create a customizable indicator on the TradingView platform. Below is an introduction to its features and purpose:
Introduction:
This script serves as a versatile indicator on TradingView, allowing users to choose between different modes (Heikin-Ashi, Linear, and Normal) and apply a Hull Moving Average (Hull) for trend analysis. The primary features include mode selection, the choice of using different calculation methods, and the option to incorporate the Hull Moving Average for enhanced trend visibility.
Key Features:
Mode Selection:
Users can choose between "Heikin-Ashi," "Linear," or "Normal" modes, influencing how the open, high, low, and close prices are calculated.
Hull Moving Average:
The script incorporates the Hull Moving Average (Hull) to provide a smoothed trend line for better trend identification.
Calculation Methods:
Users can select different calculation methods for the open, high, low, and close prices, including Simple Moving Average (SMA), Exponential Moving Average (EMA), Smoothed Moving Average (SMMA or RMA), Weighted Moving Average (WMA), and Volume Weighted Moving Average (VWMA).
Customizable Lengths:
Length parameters are customizable, allowing users to adjust the period lengths for the Hull Moving Average and other calculation methods.
Buy and Sell Signals:
Buy and sell signals are generated based on crossovers and crossunders between the Hull Moving Average and the price. These signals are visually displayed on the chart with corresponding labels.
Color-Coding:
The script utilizes color-coding to distinguish between bullish (lime) and bearish (red) trends, making it easier for users to identify potential changes in market direction.
Customizable Symbol and Resolution:
Users have the option to choose a specific trading symbol and resolution for analysis.
Important Note:
This script is provided for educational purposes and does not constitute financial advice. Traders and investors should conduct thorough research and analysis before making any trading decisions. Additionally, customization options should be explored to align the script with individual trading preferences.
Trading Strategy - Follow The Plan"Trading Strategy - Follow The Plan" is a TradingView indicator specifically crafted for traders dedicated to adhering to a structured approach. It emphasizes the elimination of emotional decision-making by providing clear, actionable steps. This tool allows you to articulate and visually embed your trading strategy directly onto your charts, encompassing your entry plan, exit plan, and any additional notes crucial for maintaining focus and discipline. It's designed to aid in sustaining consistency in your trading executions, ensuring that you remain steadfastly aligned with your predetermined trading methodology.
Features
1. Entry Plan: Allows traders to outline specific criteria for market entry. This could include conditions like divergences on multiple timeframes, specific pattern recognitions, or other entry triggers. The flexibility of this section caters to various trading styles and strategies.
2. Exit Plan: Dedicated to defining exit strategies, this section can include details on profit targets, stop-loss levels, or conditions for position reversal. It serves as a constant reminder of exit strategies during active trades.
3. Notes: A customizable space for traders to jot down essential rules, observations, or reminders. This section is particularly useful for reinforcing risk management practices and maintaining focus on broader trading goals.
4. Visibility Controls: Each section of the trading plan (Entry Plan, Exit Plan, Notes) can be toggled on or off, allowing traders to manage on-screen information and reduce chart clutter.
5. Layout Customization: Users can choose the placement of the trading plan on their chart, with options including Top Right, Top Left, Bottom Right, and Bottom Left. This caters to individual preferences and screen setups.
6. Appearance Customization: The indicator allows for adjustments in text and background colors, and text sizes for titles and content, enhancing readability and personal preference alignment.
AMDX-XAMDGuided by ICT tutoring and also inspired by the teaching of
Daye', I create this versatile "AMDX" indicator.
A = Accumulation
M = Manipulation
D = Distribution
X = Continuation Or Reversal
This indicator shows a different way of viewing all the Timeframes by dividing them into Quarters, in this context the Trading sessions are divided into a 90m cycle, dividing each time range into Q1-Q2-Q3-Q4, in this way you have a clear vision of what the price is likely to do
True Open Times =
Opening Week - Monday at 6pm
Opening Day - 00:00
Asia -7.30pm
London -01.30
New York -07:30
PM -1.30pm
Session Times =
Q1 Asia 18:00-00:00
Q2 London 00:00-06:00
Q3 New York 06:00-12:00
Q4 PM 12:00-18:00
The user has the possibility to:
- Choose whether to display AMDX W
- Choose whether to display AMDX D
- Choose whether to display AMDX Session
- Choose to show the text in the Box
- Choose to show open levels
The indicator should be used as ICT and 'Daye' show in their concepts.
The indicator divides everything into Quarter ranges and classifies them into Q1-Q2-Q3-Q4 (as in the example above), and each Quarter has its own specific function, and can be used in this way:
If Q1 does an expansion it is likely that Q2 will do a consolidation, Q3 will do a Manipulation and Q4 will do a reversal returning to Q1
-If we are Bullish we buy under Open Session
-If we are Bearish we buy above open session
As in the example below:
If something is not clear, comment below and I will reply as soon as possible.
Capital Accumulation Plan (CAP) Simulator 2.0Description:
This indicator serves as a simulation tool for the Capital Accumulation Plan (CAP). The CAP is an investment strategy involving regular contributions of a fixed amount at consistent intervals, regardless of market fluctuations. This simulator allows you to visualize how your invested capital might grow over time, considering a fixed monthly investment in a given financial instrument.
How to Use:
Customize the monthly investment amount, the day of the month for the investment, and the simulation period. Also, input the percentage of taxation on potential dividends and the Total Expense Ratio (TER) of the financial instrument. The indicator calculates the portfolio value over time, the invested capital, and the average cost. If applicable, it also calculates the dividend amounts over time and the corresponding taxes to be paid.
The indicator displays how these metrics would change over time following the PAC strategy.
Important Notes:
Apply exclusively to the daily chart; a fix for the chosen day absence will be implemented shortly.
OKX Signal BOT - Strategy Scanner & Orderer
Hello traders,
With the OKX Signal BOT - Strategy Scanner & Orderer, you can now design your own strategy, scan over 20 cryptocurrencies, and send orders for futures trades on the OKX exchange.
How to Use:
🌐 First, log into your account on the OKX exchange and create a signal bot.
📝 While creating the signal bot, note down the webhook URL and signal token variables given to you; they'll be needed later.
🔍 Select the trading pairs that the bot will work on.
📈 Add this indicator to your chart.
⚙️ Adjust the values of the indicators you will use in your strategy.
📊 Set your entry conditions and indicator setups according to your preference.
🚀 Decide which condition will generate a LONG signal and which will generate a SHORT signal.
🔗 Then, link these conditions with either an AND or OR connector.
🛠️ This also serves as a strategy designer.
🆔 Paste the signal token value you got from OKX into the OKX Signal ID section in the indicator.
➕ Add the cryptocurrency pairs you added to the bot on OKX to this design tool as well.
💾 Save and exit.
🚨 Set an alarm and paste the webhook URL link you got from OKX.
Congratulations, you can now send signals from Tradingview to the OKX exchange without needing any other platform.
Warnings:
⚠️ Works only for futures trades.
📈 Make your leverage settings through the exchange.
🛑 It is recommended to set take profit and stop loss through the exchange.
🚫 If too many alarms are triggered, Tradingview may stop your alarms.
💡 Ensure that the coins you add in the symbol section are from the OKX exchange.
🔍 For futures trades, make sure the symbols end with ".P".
🎉 Enjoy using it!
Supertrend Advance Pullback StrategyHandbook for the Supertrend Advance Strategy
1. Introduction
Purpose of the Handbook:
The main purpose of this handbook is to serve as a comprehensive guide for traders and investors who are looking to explore and harness the potential of the Supertrend Advance Strategy. In the rapidly changing financial market, having the right tools and strategies at one's disposal is crucial. Whether you're a beginner hoping to dive into the world of trading or a seasoned investor aiming to optimize and diversify your portfolio, this handbook offers the insights and methodologies you need. By the end of this guide, readers should have a clear understanding of how the Supertrend Advance Strategy works, its benefits, potential pitfalls, and practical application in various trading scenarios.
Overview of the Supertrend Advance Pullback Strategy:
At its core, the Supertrend Advance Strategy is an evolution of the popular Supertrend Indicator. Designed to generate buy and sell signals in trending markets, the Supertrend Indicator has been a favorite tool for many traders around the world. The Advance Strategy, however, builds upon this foundation by introducing enhanced mechanisms, filters, and methodologies to increase precision and reduce false signals.
1. Basic Concept:
The Supertrend Advance Strategy relies on a combination of price action and volatility to determine the potential trend direction. By assessing the average true range (ATR) in conjunction with specific price points, this strategy aims to highlight the potential starting and ending points of market trends.
2. Methodology:
Unlike the traditional Supertrend Indicator, which primarily focuses on closing prices and ATR, the Advance Strategy integrates other critical market variables, such as volume, momentum oscillators, and perhaps even fundamental data, to validate its signals. This multidimensional approach ensures that the generated signals are more reliable and are less prone to market noise.
3. Benefits:
One of the main benefits of the Supertrend Advance Strategy is its ability to filter out false breakouts and minor price fluctuations, which can often lead to premature exits or entries in the market. By waiting for a confluence of factors to align, traders using this advanced strategy can increase their chances of entering or exiting trades at optimal points.
4. Practical Applications:
The Supertrend Advance Strategy can be applied across various timeframes, from intraday trading to swing trading and even long-term investment scenarios. Furthermore, its flexible nature allows it to be tailored to different asset classes, be it stocks, commodities, forex, or cryptocurrencies.
In the subsequent sections of this handbook, we will delve deeper into the intricacies of this strategy, offering step-by-step guidelines on its application, case studies, and tips for maximizing its efficacy in the volatile world of trading.
As you journey through this handbook, we encourage you to approach the Supertrend Advance Strategy with an open mind, testing and tweaking it as per your personal trading style and risk appetite. The ultimate goal is not just to provide you with a new tool but to empower you with a holistic strategy that can enhance your trading endeavors.
2. Getting Started
Navigating the financial markets can be a daunting task without the right tools. This section is dedicated to helping you set up the Supertrend Advance Strategy on one of the most popular charting platforms, TradingView. By following the steps below, you'll be able to integrate this strategy into your charts and start leveraging its insights in no time.
Setting up on TradingView:
TradingView is a web-based platform that offers a wide range of charting tools, social networking, and market data. Before you can apply the Supertrend Advance Strategy, you'll first need a TradingView account. If you haven't set one up yet, here's how:
1. Account Creation:
• Visit TradingView's official website.
• Click on the "Join for free" or "Sign up" button.
• Follow the registration process, providing the necessary details and setting up your login credentials.
2. Navigating the Dashboard:
• Once logged in, you'll be taken to your dashboard. Here, you'll see a variety of tools, including watchlists, alerts, and the main charting window.
• To begin charting, type in the name or ticker of the asset you're interested in the search bar at the top.
3. Configuring Chart Settings:
• Before integrating the Supertrend Advance Strategy, familiarize yourself with the chart settings. This can be accessed by clicking the 'gear' icon on the top right of the chart window.
• Adjust the chart type, time intervals, and other display settings to your preference.
Integrating the Strategy into a Chart:
Now that you're set up on TradingView, it's time to integrate the Supertrend Advance Strategy.
1. Accessing the Pine Script Editor:
• Located at the top-center of your screen, you'll find the "Pine Editor" tab. Click on it.
• This is where custom strategies and indicators are scripted or imported.
2. Loading the Supertrend Advance Strategy Script:
• Depending on whether you have the script or need to find it, there are two paths:
• If you have the script: Copy the Supertrend Advance Strategy script, and then paste it into the Pine Editor.
• If searching for the script: Click on the “Indicators” icon (looks like a flame) at the top of your screen, and then type “Supertrend Advance Strategy” in the search bar. If available, it will show up in the list. Simply click to add it to your chart.
3. Applying the Strategy:
• After pasting or selecting the Supertrend Advance Strategy in the Pine Editor, click on the “Add to Chart” button located at the top of the editor. This will overlay the strategy onto your main chart window.
4. Configuring Strategy Settings:
• Once the strategy is on your chart, you'll notice a small settings ('gear') icon next to its name in the top-left of the chart window. Click on this to access settings.
• Here, you can adjust various parameters of the Supertrend Advance Strategy to better fit your trading style or the specific asset you're analyzing.
5. Interpreting Signals:
• With the strategy applied, you'll now see buy/sell signals represented on your chart. Take time to familiarize yourself with how these look and behave over various timeframes and market conditions.
3. Strategy Overview
What is the Supertrend Advance Strategy?
The Supertrend Advance Strategy is a refined version of the classic Supertrend Indicator, which was developed to aid traders in spotting market trends. The strategy utilizes a combination of data points, including average true range (ATR) and price momentum, to generate buy and sell signals.
In essence, the Supertrend Advance Strategy can be visualized as a line that moves with the price. When the price is above the Supertrend line, it indicates an uptrend and suggests a potential buy position. Conversely, when the price is below the Supertrend line, it hints at a downtrend, suggesting a potential selling point.
Strategy Goals and Objectives:
1. Trend Identification: At the core of the Supertrend Advance Strategy is the goal to efficiently and consistently identify prevailing market trends. By recognizing these trends, traders can position themselves to capitalize on price movements in their favor.
2. Reducing Noise: Financial markets are often inundated with 'noise' - short-term price fluctuations that can mislead traders. The Supertrend Advance Strategy aims to filter out this noise, allowing for clearer decision-making.
3. Enhancing Risk Management: With clear buy and sell signals, traders can set more precise stop-loss and take-profit points. This leads to better risk management and potentially improved profitability.
4. Versatility: While primarily used for trend identification, the strategy can be integrated with other technical tools and indicators to create a comprehensive trading system.
Type of Assets/Markets to Apply the Strategy:
1. Equities: The Supertrend Advance Strategy is highly popular among stock traders. Its ability to capture long-term trends makes it particularly useful for those trading individual stocks or equity indices.
2. Forex: Given the 24-hour nature of the Forex market and its propensity for trends, the Supertrend Advance Strategy is a valuable tool for currency traders.
3. Commodities: Whether it's gold, oil, or agricultural products, commodities often move in extended trends. The strategy can help in identifying and capitalizing on these movements.
4. Cryptocurrencies: The volatile nature of cryptocurrencies means they can have pronounced trends. The Supertrend Advance Strategy can aid crypto traders in navigating these often tumultuous waters.
5. Futures & Options: Traders and investors in derivative markets can utilize the strategy to make more informed decisions about contract entries and exits.
It's important to note that while the Supertrend Advance Strategy can be applied across various assets and markets, its effectiveness might vary based on market conditions, timeframe, and the specific characteristics of the asset in question. As always, it's recommended to use the strategy in conjunction with other analytical tools and to backtest its effectiveness in specific scenarios before committing to trades.
4. Input Settings
Understanding and correctly configuring input settings is crucial for optimizing the Supertrend Advance Strategy for any specific market or asset. These settings, when tweaked correctly, can drastically impact the strategy's performance.
Grouping Inputs:
Before diving into individual input settings, it's important to group similar inputs. Grouping can simplify the user interface, making it easier to adjust settings related to a specific function or indicator.
Strategy Choice:
This input allows traders to select from various strategies that incorporate the Supertrend indicator. Options might include "Supertrend with RSI," "Supertrend with MACD," etc. By choosing a strategy, the associated input settings for that strategy become available.
Supertrend Settings:
1. Multiplier: Typically, a default value of 3 is used. This multiplier is used in the ATR calculation. Increasing it makes the Supertrend line further from prices, while decreasing it brings the line closer.
2. Period: The number of bars used in the ATR calculation. A common default is 7.
EMA Settings (Exponential Moving Average):
1. Period: Defines the number of previous bars used to calculate the EMA. Common periods are 9, 21, 50, and 200.
2. Source: Allows traders to choose which price (Open, Close, High, Low) to use in the EMA calculation.
RSI Settings (Relative Strength Index):
1. Length: Determines how many periods are used for RSI calculation. The standard setting is 14.
2. Overbought Level: The threshold at which the asset is considered overbought, typically set at 70.
3. Oversold Level: The threshold at which the asset is considered oversold, often at 30.
MACD Settings (Moving Average Convergence Divergence):
1. Short Period: The shorter EMA, usually set to 12.
2. Long Period: The longer EMA, commonly set to 26.
3. Signal Period: Defines the EMA of the MACD line, typically set at 9.
CCI Settings (Commodity Channel Index):
1. Period: The number of bars used in the CCI calculation, often set to 20.
2. Overbought Level: Typically set at +100, denoting overbought conditions.
3. Oversold Level: Usually set at -100, indicating oversold conditions.
SL/TP Settings (Stop Loss/Take Profit):
1. SL Multiplier: Defines the multiplier for the average true range (ATR) to set the stop loss.
2. TP Multiplier: Defines the multiplier for the average true range (ATR) to set the take profit.
Filtering Conditions:
This section allows traders to set conditions to filter out certain signals. For example, one might only want to take buy signals when the RSI is below 30, ensuring they buy during oversold conditions.
Trade Direction and Backtest Period:
1. Trade Direction: Allows traders to specify whether they want to take long trades, short trades, or both.
2. Backtest Period: Specifies the time range for backtesting the strategy. Traders can choose from options like 'Last 6 months,' 'Last 1 year,' etc.
It's essential to remember that while default settings are provided for many of these tools, optimal settings can vary based on the market, timeframe, and trading style. Always backtest new settings on historical data to gauge their potential efficacy.
5. Understanding Strategy Conditions
Developing an understanding of the conditions set within a trading strategy is essential for traders to maximize its potential. Here, we delve deep into the logic behind these conditions, using the Supertrend Advance Strategy as our focal point.
Basic Logic Behind Conditions:
Every strategy is built around a set of conditions that provide buy or sell signals. The conditions are based on mathematical or statistical methods and are rooted in the study of historical price data. The fundamental idea is to recognize patterns or behaviors that have been profitable in the past and might be profitable in the future.
Buy and Sell Conditions:
1. Buy Conditions: Usually formulated around bullish signals or indicators suggesting upward price momentum.
2. Sell Conditions: Centered on bearish signals or indicators indicating downward price momentum.
Simple Strategy:
The simple strategy could involve using just the Supertrend indicator. Here:
• Buy: When price closes above the Supertrend line.
• Sell: When price closes below the Supertrend line.
Pullback Strategy:
This strategy capitalizes on price retracements:
• Buy: When the price retraces to the Supertrend line after a bullish signal and is supported by another bullish indicator.
• Sell: When the price retraces to the Supertrend line after a bearish signal and is confirmed by another bearish indicator.
Indicators Used:
EMA (Exponential Moving Average):
• Logic: EMA gives more weight to recent prices, making it more responsive to current price movements. A shorter-period EMA crossing above a longer-period EMA can be a bullish sign, while the opposite is bearish.
RSI (Relative Strength Index):
• Logic: RSI measures the magnitude of recent price changes to analyze overbought or oversold conditions. Values above 70 are typically considered overbought, and values below 30 are considered oversold.
MACD (Moving Average Convergence Divergence):
• Logic: MACD assesses the relationship between two EMAs of a security’s price. The MACD line crossing above the signal line can be a bullish signal, while crossing below can be bearish.
CCI (Commodity Channel Index):
• Logic: CCI compares a security's average price change with its average price variation. A CCI value above +100 may mean the price is overbought, while below -100 might signify an oversold condition.
And others...
As the strategy expands or contracts, more indicators might be added or removed. The crucial point is to understand the core logic behind each, ensuring they align with the strategy's objectives.
Logic Behind Each Indicator:
1. EMA: Emphasizes recent price movements; provides dynamic support and resistance levels.
2. RSI: Indicates overbought and oversold conditions based on recent price changes.
3. MACD: Showcases momentum and direction of a trend by comparing two EMAs.
4. CCI: Measures the difference between a security's price change and its average price change.
Understanding strategy conditions is not just about knowing when to buy or sell but also about comprehending the underlying market dynamics that those conditions represent. As you familiarize yourself with each condition and indicator, you'll be better prepared to adapt and evolve with the ever-changing financial markets.
6. Trade Execution and Management
Trade execution and management are crucial aspects of any trading strategy. Efficient execution can significantly impact profitability, while effective management can preserve capital during adverse market conditions. In this section, we'll explore the nuances of position entry, exit strategies, and various Stop Loss (SL) and Take Profit (TP) methodologies within the Supertrend Advance Strategy.
Position Entry:
Effective trade entry revolves around:
1. Timing: Enter at a point where the risk-reward ratio is favorable. This often corresponds to confirmatory signals from multiple indicators.
2. Volume Analysis: Ensure there's adequate volume to support the movement. Volume can validate the strength of a signal.
3. Confirmation: Use multiple indicators or chart patterns to confirm the entry point. For instance, a buy signal from the Supertrend indicator can be confirmed with a bullish MACD crossover.
Position Exit Strategies:
A successful exit strategy will lock in profits and minimize losses. Here are some strategies:
1. Fixed Time Exit: Exiting after a predetermined period.
2. Percentage-based Profit Target: Exiting after a certain percentage gain.
3. Indicator-based Exit: Exiting when an indicator gives an opposing signal.
Percentage-based SL/TP:
• Stop Loss (SL): Set a fixed percentage below the entry price to limit potential losses.
• Example: A 2% SL on an entry at $100 would trigger a sell at $98.
• Take Profit (TP): Set a fixed percentage above the entry price to lock in gains.
• Example: A 5% TP on an entry at $100 would trigger a sell at $105.
Supertrend-based SL/TP:
• Stop Loss (SL): Position the SL at the Supertrend line. If the price breaches this line, it could indicate a trend reversal.
• Take Profit (TP): One could set the TP at a point where the Supertrend line flattens or turns, indicating a possible slowdown in momentum.
Swing high/low-based SL/TP:
• Stop Loss (SL): For a long position, set the SL just below the recent swing low. For a short position, set it just above the recent swing high.
• Take Profit (TP): For a long position, set the TP near a recent swing high or resistance. For a short position, near a swing low or support.
And other methods...
1. Trailing Stop Loss: This dynamic SL adjusts with the price movement, locking in profits as the trade moves in your favor.
2. Multiple Take Profits: Divide the position into segments and set multiple TP levels, securing profits in stages.
3. Opposite Signal Exit: Exit when another reliable indicator gives an opposite signal.
Trade execution and management are as much an art as they are a science. They require a blend of analytical skill, discipline, and intuition. Regularly reviewing and refining your strategies, especially in light of changing market conditions, is crucial to maintaining consistent trading performance.
7. Visual Representations
Visual tools are essential for traders, as they simplify complex data into an easily interpretable format. Properly analyzing and understanding the plots on a chart can provide actionable insights and a more intuitive grasp of market conditions. In this section, we’ll delve into various visual representations used in the Supertrend Advance Strategy and their significance.
Understanding Plots on the Chart:
Charts are the primary visual aids for traders. The arrangement of data points, lines, and colors on them tell a story about the market's past, present, and potential future moves.
1. Data Points: These represent individual price actions over a specific timeframe. For instance, a daily chart will have data points showing the opening, closing, high, and low prices for each day.
2. Colors: Used to indicate the nature of price movement. Commonly, green is used for bullish (upward) moves and red for bearish (downward) moves.
Trend Lines:
Trend lines are straight lines drawn on a chart that connect a series of price points. Their significance:
1. Uptrend Line: Drawn along the lows, representing support. A break below might indicate a trend reversal.
2. Downtrend Line: Drawn along the highs, indicating resistance. A break above might suggest the start of a bullish trend.
Filled Areas:
These represent a range between two values on a chart, usually shaded or colored. For instance:
1. Bollinger Bands: The area between the upper and lower band is filled, giving a visual representation of volatility.
2. Volume Profile: Can show a filled area representing the amount of trading activity at different price levels.
Stop Loss and Take Profit Lines:
These are horizontal lines representing pre-determined exit points for trades.
1. Stop Loss Line: Indicates the level at which a trade will be automatically closed to limit losses. Positioned according to the trader's risk tolerance.
2. Take Profit Line: Denotes the target level to lock in profits. Set according to potential resistance (for long trades) or support (for short trades) or other technical factors.
Trailing Stop Lines:
A trailing stop is a dynamic form of stop loss that moves with the price. On a chart:
1. For Long Trades: Starts below the entry price and moves up with the price but remains static if the price falls, ensuring profits are locked in.
2. For Short Trades: Starts above the entry price and moves down with the price but remains static if the price rises.
Visual representations offer traders a clear, organized view of market dynamics. Familiarity with these tools ensures that traders can quickly and accurately interpret chart data, leading to more informed decision-making. Always ensure that the visual aids used resonate with your trading style and strategy for the best results.
8. Backtesting
Backtesting is a fundamental process in strategy development, enabling traders to evaluate the efficacy of their strategy using historical data. It provides a snapshot of how the strategy would have performed in past market conditions, offering insights into its potential strengths and vulnerabilities. In this section, we'll explore the intricacies of setting up and analyzing backtest results and the caveats one must be aware of.
Setting Up Backtest Period:
1. Duration: Determine the timeframe for the backtest. It should be long enough to capture various market conditions (bullish, bearish, sideways). For instance, if you're testing a daily strategy, consider a period of several years.
2. Data Quality: Ensure the data source is reliable, offering high-resolution and clean data. This is vital to get accurate backtest results.
3. Segmentation: Instead of a continuous period, sometimes it's helpful to backtest over distinct market phases, like a particular bear or bull market, to see how the strategy holds up in different environments.
Analyzing Backtest Results:
1. Performance Metrics: Examine metrics like the total return, annualized return, maximum drawdown, Sharpe ratio, and others to gauge the strategy's efficiency.
2. Win Rate: It's the ratio of winning trades to total trades. A high win rate doesn't always signify a good strategy; it should be evaluated in conjunction with other metrics.
3. Risk/Reward: Understand the average profit versus the average loss per trade. A strategy might have a low win rate but still be profitable if the average gain far exceeds the average loss.
4. Drawdown Analysis: Review the periods of losses the strategy could incur and how long it takes, on average, to recover.
9. Tips and Best Practices
Successful trading requires more than just knowing how a strategy works. It necessitates an understanding of when to apply it, how to adjust it to varying market conditions, and the wisdom to recognize and avoid common pitfalls. This section offers insightful tips and best practices to enhance the application of the Supertrend Advance Strategy.
When to Use the Strategy:
1. Market Conditions: Ideally, employ the Supertrend Advance Strategy during trending market conditions. This strategy thrives when there are clear upward or downward trends. It might be less effective during consolidative or sideways markets.
2. News Events: Be cautious around significant news events, as they can cause extreme volatility. It might be wise to avoid trading immediately before and after high-impact news.
3. Liquidity: Ensure you are trading in assets/markets with sufficient liquidity. High liquidity ensures that the price movements are more reflective of genuine market sentiment and not due to thin volume.
Adjusting Settings for Different Markets/Timeframes:
1. Markets: Each market (stocks, forex, commodities) has its own characteristics. It's essential to adjust the strategy's parameters to align with the market's volatility and liquidity.
2. Timeframes: Shorter timeframes (like 1-minute or 5-minute charts) tend to have more noise. You might need to adjust the settings to filter out false signals. Conversely, for longer timeframes (like daily or weekly charts), you might need to be more responsive to genuine trend changes.
3. Customization: Regularly review and tweak the strategy's settings. Periodic adjustments can ensure the strategy remains optimized for the current market conditions.
10. Frequently Asked Questions (FAQs)
Given the complexities and nuances of the Supertrend Advance Strategy, it's only natural for traders, both new and seasoned, to have questions. This section addresses some of the most commonly asked questions regarding the strategy.
1. What exactly is the Supertrend Advance Strategy?
The Supertrend Advance Strategy is an evolved version of the traditional Supertrend indicator. It's designed to provide clearer buy and sell signals by incorporating additional indicators like EMA, RSI, MACD, CCI, etc. The strategy aims to capitalize on market trends while minimizing false signals.
2. Can I use the Supertrend Advance Strategy for all asset types?
Yes, the strategy can be applied to various asset types like stocks, forex, commodities, and cryptocurrencies. However, it's crucial to adjust the settings accordingly to suit the specific characteristics and volatility of each asset type.
3. Is this strategy suitable for day trading?
Absolutely! The Supertrend Advance Strategy can be adjusted to suit various timeframes, making it versatile for both day trading and long-term trading. Remember to fine-tune the settings to align with the timeframe you're trading on.
4. How do I deal with false signals?
No strategy is immune to false signals. However, by combining the Supertrend with other indicators and adhering to strict risk management protocols, you can minimize the impact of false signals. Always use stop-loss orders and consider filtering trades with additional confirmation signals.
5. Do I need any prior trading experience to use this strategy?
While the Supertrend Advance Strategy is designed to be user-friendly, having a foundational understanding of trading and market analysis can greatly enhance your ability to employ the strategy effectively. If you're a beginner, consider pairing the strategy with further education and practice on demo accounts.
6. How often should I review and adjust the strategy settings?
There's no one-size-fits-all answer. Some traders adjust settings weekly, while others might do it monthly. The key is to remain responsive to changing market conditions. Regular backtesting can give insights into potential required adjustments.
7. Can the Supertrend Advance Strategy be automated?
Yes, many traders use algorithmic trading platforms to automate their strategies, including the Supertrend Advance Strategy. However, always monitor automated systems regularly to ensure they're operating as intended.
8. Are there any markets or conditions where the strategy shouldn't be used?
The strategy might generate more false signals in markets that are consolidative or range-bound. During significant news events or times of unexpected high volatility, it's advisable to tread with caution or stay out of the market.
9. How important is backtesting with this strategy?
Backtesting is crucial as it allows traders to understand how the strategy would have performed in the past, offering insights into potential profitability and areas of improvement. Always backtest any new setting or tweak before applying it to live trades.
10. What if the strategy isn't working for me?
No strategy guarantees consistent profits. If it's not working for you, consider reviewing your settings, seeking expert advice, or complementing the Supertrend Advance Strategy with other analysis methods. Remember, continuous learning and adaptation are the keys to trading success.
Other comments
Value of combining several indicators in this script and how they work together
Diversification of Signals: Just as diversifying an investment portfolio can reduce risk, using multiple indicators can offer varied perspectives on potential price movements. Each indicator can capture a different facet of the market, ensuring that traders are not overly reliant on a single data point.
Confirmation & Reduced False Signals: A common challenge with many indicators is the potential for false signals. By requiring confirmation from multiple indicators before acting, the chances of acting on a false signal can be significantly reduced.
Flexibility Across Market Conditions: Different indicators might perform better under different market conditions. For example, while moving averages might excel in trending markets, oscillators like RSI might be more useful during sideways or range-bound conditions. A mashup strategy can potentially adapt better to varying market scenarios.
Comprehensive Analysis: With multiple indicators, traders can gauge trend strength, momentum, volatility, and potential market reversals all at once, providing a holistic view of the market.
How do the different indicators in the Supertrend Advance Strategy work together?
Supertrend: This is primarily a trend-following indicator. It provides traders with buy and sell signals based on the volatility of the price. When combined with other indicators, it can filter out noise and give more weight to strong, confirmed trends.
EMA (Exponential Moving Average): EMA gives more weight to recent price data. It can be used to identify the direction and strength of a trend. When the price is above the EMA, it's generally considered bullish, and vice versa.
RSI (Relative Strength Index): An oscillator that measures the magnitude of recent price changes to evaluate overbought or oversold conditions. By cross-referencing with other indicators like EMA or MACD, traders can spot potential reversals or confirmations of a trend.
MACD (Moving Average Convergence Divergence): This indicator identifies changes in the strength, direction, momentum, and duration of a trend in a stock's price. When the MACD line crosses above the signal line, it can be a bullish sign, and when it crosses below, it can be bearish. Pairing MACD with Supertrend can provide dual confirmation of a trend.
CCI (Commodity Channel Index): Initially developed for commodities, CCI can indicate overbought or oversold conditions. It can be used in conjunction with other indicators to determine entry and exit points.
In essence, the synergy of these indicators provides a balanced, comprehensive approach to trading. Each indicator offers its unique lens into market conditions, and when they align, it can be a powerful indication of a trading opportunity. This combination not only reduces the potential drawbacks of each individual indicator but leverages their strengths, aiming for more consistent and informed trading decisions.
Backtesting and Default Settings
• This indicator has been optimized to be applied for 1 hour-charts. However, the underlying principles of this strategy are supply and demand in the financial markets and the strategy can be applied to all timeframes. Daytraders can use the 1min- or 5min charts, swing-traders can use the daily charts.
• This strategy has been designed to identify the most promising, highest probability entries and trades for each stock or other financial security.
• The combination of the qualifiers results in a highly selective strategy which only considers the most promising swing-trading entries. As a result, you will normally only find a low number of trades for each stock or other financial security per year in case you apply this strategy for the daily charts. Shorter timeframes will result in a higher number of trades / year.
• Consequently, traders need to apply this strategy for a full watchlist rather than just one financial security.
• Default properties: RSI on (length 14, RSI buy level 50, sell level 50), EMA, RSI, MACD on, type of strategy pullback, SL/TP type: ATR (length 10, factor 3), trade direction both, quantity 5, take profit swing hl 5.1, highest / lowest lookback 2, enable ATR trail (ATR length 10, SL ATR multiplier 1.4, TP multiplier 2.1, lookback = 4, trade direction = both).
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!
OHLC BreakThis indicator shows the Support and Resistance zones in a different way with Boxes that extend to the right and show the candle that has broken a minimum number of High or Low
The user has the possibility to:
- Choose to show High or Low levels not yet broken
- Shows candles that have broken a total of high or Low that you pre-set
- Choose to show a Box on candles that have broken the minimum of the preset levels
- Choose to show the total of broken levels with a Label on the candle
The indicator should be used as OHLC shows in its concepts, it can also be implemented to your Support and Resistance strategies, it can be implemented to Sessions strategies as in the Example
Below I show various examples on how to set the indicator for show High or Low levels not yet broken
If something is not clear, comment below and I will reply as soon as possible.
[KVA]K Stochastic IndicatorOriginal Stochastic Oscillator Formula:
%K=(C−Lowest Low)/(Highest High−Lowest Low)×100
Lowest Low refers to the lowest low of the past n periods.
Highest High refers to the highest high of the past n periods.
K Stochastic Indicator Formula:
%K=(Source−Lowest Source)/(Highest Source−Lowest Source)×100
Lowest Source refers to the lowest value of the chosen source over the past length periods.
Highest Source refers to the highest value of the chosen source over the past length periods.
Key Difference :
The original formula calculates %K using the absolute highest high and lowest low of the price over the past n periods.
The K Stochastic formula calculates %K using the highest and lowest values of a chosen source (which could be the close, open, high, or low) over the specified length periods.
So, if _src is set to something other than the high for the Highest Source or something other than the low for the Lowest Source, the K Stochastic will yield different results compared to the original formula which strictly uses the highest high and the lowest low of the price.
Impact on Traders :
Flexibility in Price Source :
By allowing the source (_src) to be customizable, traders can apply the Stochastic calculation to different price points (e.g., open, high, low, close, or even an average of these). This could provide a different perspective on market momentum and potentially offer signals that are more aligned with a trader's specific strategy.
Sensitivity to Price Action :
Changing the source from high/low to potentially less extreme values (like close or open) could result in a less volatile oscillator, smoothing out some of the extreme peaks and troughs and possibly offering a more filtered view of market conditions.
Customization of Periods :
The ability to adjust the length period offers traders the opportunity to fine-tune the sensitivity of the indicator to match their trading horizon. Shorter periods may provide earlier signals, while longer periods could filter out market noise.
Possibility of Applying the Indicator on Other Indicators :
Layered Technical Analysis :
The K Stochastic can be applied to other indicators, not just price. For example, it could be applied to a moving average to analyze its momentum or to indicators like RSI or MACD, offering a meta-analysis that studies the oscillator's behavior of other technical tools.
Creation of Composite Indicator s:
By applying the K Stochastic logic to other indicators, traders could create composite indicators that blend the characteristics of multiple indicators, potentially leading to unique signals that could offer an edge in certain market conditions.
Enhanced Signal Interpretation :
When applied to other indicators, the K Stochastic can help in identifying overbought or oversold conditions within those indicators, offering a different dimension to the interpretation of their output.
Overall Implications :
The KStochastic Indicator's modifications could lead to a more tailored application, giving traders the ability to adapt the tool to their specific trading style and analysis preferences.
By being applicable to other indicators, it broadens the scope of stochastic analysis beyond price action, potentially offering innovative ways to interpret data and make trading decisions.
The changes might also influence the trading signals, either by smoothing the oscillator's output to reduce noise or by altering the sensitivity to generate more or fewer signal
Including the additional %F line, which is unique to the K Stochastic Indicator, further expands the potential impacts and applications for traders:
Impact on Traders with the %F Line:
Triple Smoothing :
The %F line introduces a third level of smoothing, which could help in identifying longer-term trends and filtering out short-term fluctuations. This could be particularly useful for traders looking to avoid whipsaws and focus on more sustained movements.
Potential for Enhanced Confirmation :
The %F line might be used as a confirmation signal. For instance, if all three lines (%K, %D, and %F) are in agreement, a trader might consider this as a stronger signal to buy or sell, as opposed to when only the traditional two lines (%K and %D) are used.
Risk Management:
The additional line could be utilized for more sophisticated risk management strategies, where a trader might decide to scale in or out of positions based on the convergence or divergence of these lines.
Possibility of Applying the Indicator on Other Indicators with the %F Line:
Depth of Analysis :
When applied to other indicators, the %F line can provide an even deeper layer of analysis, perhaps identifying macro trends within the indicator it is applied to, which could go unnoticed with just the traditional two-line approach.
Refined Signal Strength Assessment :
The strength of signals from other indicators could be assessed by the position and direction of the %F line, providing an additional filter to evaluate the robustness of buy or sell signals.
Overall Implications with the %F Line :
The inclusion of the %F line in the K Stochastic Indicator enhances its utility as a tool for trend analysis and signal confirmation. It allows traders to potentially identify and act on more reliable trading opportunities.
This feature can enrich the trader's toolkit by providing a nuanced view of momentum and trend strength, which can be particularly valuable in volatile or choppy markets.
For those applying the K Stochastic to other indicators, the %F line could be integral in creating a multi-tiered analysis strategy, potentially leading to more sophisticated interpretations and decisions.
The presence of the %F line adds a dimension of depth to the analysis possible with the K Stochastic Indicator, making it a versatile tool that could be tailored to a variety of trading styles and objectives. However, as with any indicator, the additional complexity requires careful study and back-testing to ensure its signals are understood and actionable within the context of a comprehensive trading plan.
Oscillator overlayHi all!
This script is useful in the way that it let's you see an oscillator value on the chart, as an overlay. As of now you can choose from displaying Money Flow Index (MFI) (www.tradingview.com), Relative Strength Index (RSI) (www.tradingview.com) or Stochastic (www.tradingview.com). The size of the area, where the oscillator value is shown, is determined by a factor of the Average True Range (ATR), that defaults to 2 (the 'ATR factor' setting). Oscillator pivots (of user defined length in the 'Length' setting) and oscillator pivot values)ä can be shown and the background can change when the oscillator value crosses oversold/overbought. The value from the hidden plot "Value (for alerts)" can be used for setting alerts on oscillator values, e.g. crossings. The length and overbought/oversold values can be set by the user as a setting.
Best of trading luck!
Yield Spread HistogramMeasures the difference between 10Y treasury yield and 2Y treasury yield.
Highlights via histogram in green or red if difference is positive or negative.
j trader ModelAn indicator designed to trade indices using the jtrader model and ICT concepts.
jtrader Model:
Below are the key points to trade this model:
Power of 3 is the key element of this model.
Accumulation during pre NY open.NY Open represents 9:30am opening of NY Stock Exchange.
Manipulation(JUDA) immediately after NY open. Juda is a manipulated move by the indices after the session open.
Distribution as a reversal with BOS ,Heatmap preferably during Macros. Distribution is market phase where it moves towards its original expansion during macros. Macros are 20 minute time windows where indices give moves with strong force. Heatmap represent kis point of interests for the trade.
Indicator Features:
Creates a complete window of trading with key elements needed to trade The jtrader Model.
Identify and marks key points of interests (POIs).
Identify and highlights key swing points of Sessions, Days, Weeks, True open etc.
Highlights the NY Open.
Highlights the Macros.
Indicator Settings:
Enable/Disable any POI marking.
Adjust session time ranges.
Adjust enabling of model poi marking time window.
Choose color of choice for highlighting the POI.
Enable/Disable Macros.
This indicator will gradually updated with new features to trade the jtrader model. Your feedback will help us improve and enhance this indicator.
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.
Trend Shift ProThe indicator is designed to identify shifts or changes in trends as blocks, the indicator's focus on analyzing the Median of Means, Interquartile Range, and Practical Significance for potential trend changes in the market using non parametric Cohen's D. The script is designed to operate on blocks of 21 bars. The key parts of the script related to this are the conditions inside the "if" statements: The bar_index % 21 == 0 condition checks if the current bar index is divisible by 21, meaning it's the beginning of a new block of 21 bars. This condition is used to reset and calculate new values at the start of each block.
Therefore, signals or calculations related to the median of means (MoM), interquartile range (IQR), and Cohen's D are updated and calculated once every 21 bars. What this means is the frequency of signals is shown once every 21 bars.
Price Movements of Blocks:
Block-Based Analysis: This approach divides the price data into blocks or segments, often a fixed number of bars or candles. Each block represents a specific interval of time or price action. It involves No Smoothing: Unlike moving averages, block-based analysis does not apply any smoothing to the price data within each block. It directly examines the raw prices within each block.
Let's break down the key concepts and how they are used for trading:
Median of Means (MoM):
The script calculates the median of the means of seven subgroups, each consisting of three bars in shuffled order.
Each subgroup's mean is calculated based on the typical price (hlc3) of the bars within that subgroup.
The median is then computed from these seven means, representing a central tendency measure.
Note: The Median of Means provides a robust measure of central tendency, especially in situations where the dataset may have outliers or exhibit non-normal distribution characteristics. By calculating means within smaller subgroups, the method is less sensitive to extreme values that might unduly influence the overall average. This can make the Median of Means more robust than a simple mean or median when dealing with datasets that have heterogeneity or skewed distributions.
Interquartile Range (IQR):
The script calculates the IQR for each block of 21 bars.
The IQR is a measure of statistical dispersion, representing the range between the first quartile (Q1) and the third quartile (Q3) of the data.
Q1 and Q3 are calculated from the sorted array of closing prices of the 21 bars.
Non-Parametric Cohen's D Calculation:
Cohen's D is a measure of effect size, indicating the standardized difference between two means.
In this script, a non-parametric version of Cohen's D is calculated, comparing the MoM values of the current block with the MoM values of the previous block.
The calculation involves the MoM difference divided by the square root of the average squared IQR values.
Practical Significance Threshold:
The user can set a threshold for practical significance using the Threshold input.
The script determines practical significance by comparing the calculated Cohen's D with this threshold.
Plotting:
The script plots the MoM values using both straight lines and circles, with the color of the circles indicating the direction of the MoM change (green for upward, red for downward, and blue for no change).
Triangular shapes are plotted when the absolute value of Cohen's D is less than the practical significance threshold.
Overall Purpose for Trading:
The indicator is designed to help traders identify potential turning points or shifts in market sentiment. and use it as levels which needs to be crossed to have a new trend.
Changes in MoM, especially when accompanied by practical significance as determined by Cohen's D, may signal the start of a new trend or a significant move in the market.
Traders using this indicator would typically look for instances where the MoM values and associated practical significance suggest a high probability of a trend change, providing them with potential entry or exit signals. It's important for users to backtest and validate the indicator's effectiveness in different market conditions before relying on it for trading decisions.
Oops!Oops! is based on an overemotional response, then a quick reversal of the concomitant overreaction of price. The overreaction we are looking for to give us a buy signal is an opening that is below the previous day's low. The entry comes when, following the lower open, price then rallies back to the previous day's low (selling pressures have been abated and a market rally should follow). A sell signal is just the opposite. We will be looking for an open greater than the prior day's high. Our entry then comes from price falling back to the prior high, giving us a strong short-term suggestion of lower prices to come.
Stx Monthly Trades ProfitMonthly profit displays profits in a grid and allows you to know the gain related to the investment during each month.
The profit could be computed in terms of gain/trade_cost or as percentage of equity update.
Settings:
- Profit: Monthly profit percentage or percentage of equity
- Table position
This strategy is intended only as a container for the code and for testing the script of the profit table.
Setting of strategy allows to select the test case for this snippet (percentage grid).
Money management: not relevant as strategy is a test case.
This script stand out as take in account the gain of each trade in relation to the capital invested in each trade. For example consider the following scenario:
Capital of 1000$ and we invest a fixed amount of 1000$ (I know is too risky but is a good example), we gain 10% every month.
After 10 months our capital is of 2000$ and our strategy is perfect as we have the same performance every month.
Instead, evaluating the percentage of equity we have 10% the first month, 9.9% the second (1200$/1100$ - 1) and 5.26% the tenth month. So seems that strategy degrade with times but this is not true.
For this reason, to evaluate my strategy I prefer to see the montly return of investment.
WARNING: The strategy provided with this script is only a test case and allows to see the behavior with different "trades" management, for these reason commision are set to zero.
At the moment only the provided test cases are handled:
test 1 - single entry and single exit;
test 2 - single entry and multiple exits;
test 3 - single entry and switch position;
