Position Size Calculator for ContractDescription:
Position Size Calculator is a versatile Pine Script tool designed to help traders manage their risk and position sizing effectively. This script calculates essential trading metrics and visualizes them directly on your chart, helping you make informed trading decisions.
Features:
- Account Size & Risk Management:
- Account Size: Input your total account balance to calculate position sizes.
- Maximum Risk: Define how much of your account you are willing to risk per trade in dollars.
- Pip Value: Set the value of a single pip for one contract, which is crucial for calculating risk
and position size.
Trade Setup Visualization:
- Entry Price: Specify the price at which you plan to enter the trade.
- Stop Loss: Define your stop loss level to manage your risk.
- Take Profit: Set your target profit level for the trade.
- Visualize the Entry, Stop Loss, and Take Profit levels on your chart with customizable line
colors and text sizes.
- View the distance in pips between the Entry, Stop Loss, and Take Profit levels.
Position Size Calculation:
- Calculates the number of contracts to open based on your risk tolerance and the pip value.
- Displays the maximum number of contracts you can open given your risk parameters.
Customizable Table Display:
- Table Position: Choose the position of the summary table on the chart (Top-Left, Top-Right,
Bottom-Left, Bottom-Right, etc.).
- Table Text Size: Adjust the text size for the summary table.
- Table Background Color: Set the background color for the summary table.
- Table Border Color: Customize the border color of the summary table.
How to Use:
1- Input your Account Size: Enter your current account balance.
2- Set Maximum Risk and Pip Value: Define how much you're willing to risk per trade and the
pip value for your contract.
3- Define Trade Levels: Input your desired Entry Price, Stop Loss, and Take Profit levels.
4- Customize Visuals: Adjust the line styles and table settings to fit your preferences.
5- View Calculations: The script will display the distance in pips and the calculated position
size directly on your chart.
Example Usage:
Example to calculate the value of 1 pips with 1 contract:
Inputs:
Account Size: Your total trading account balance.
Maximum Risk: Risk amount per trade in dollars.
Pip Value: Value of one pip for a single contract.
Entry Price: The price at which you plan to enter the trade.
Stop Loss: The level at which you will exit the trade to cut losses.
Take Profit: The target price to lock in profits.
Line Text Size: Size of the text for the Entry, Stop Loss, and Take Profit lines.
Line Extend: Option to extend the lines for visual clarity.
Table Position: Position of the summary table on the chart.
Table Text Size: Size of the text in the summary table.
Table Background Color: Background color of the summary table.
Table Border Color: Border color of the summary table.
Visuals:
Entry Price, Stop Loss, and Take Profit levels are clearly marked on the chart.
Summary Table with important trade metrics displayed.
Cerca negli script per "profit"
Uptrick: Supply and Demand Zones with RSI, MACD and TP signalsUptrick: Supply and Demand Zones with RSI, MACD Signals and TP Signals
This script is a comprehensive technical analysis indicator for the TradingView platform, combining multiple strategies and indicators to assist traders in making informed decisions. The script incorporates supply and demand zones, Relative Strength Index (RSI), Moving Average Convergence Divergence (MACD) signals, and trend and take profit signals. Below is a detailed explanation of each feature, its purpose, how to use it, and how it differs from other indicators.
Key Features
Supply and Demand Zones:
Purpose: Identify key price levels where buying (demand) or selling (supply) pressure has historically been strong.
Inputs:
supplySwingLength (Default: 20): Determines the number of bars to consider for identifying swing highs for supply zones.
demandSwingLength (Default: 20): Determines the number of bars to consider for identifying swing lows for demand zones.
zoneExtensionBars (Default: 50): Specifies how many bars to extend the zones to the right for visibility.
Usage: The indicator highlights these zones on the chart, making it easier for traders to spot potential reversal points.
Relative Strength Index (RSI) and Moving Average of RSI:
Purpose: RSI measures the speed and change of price movements, helping to identify overbought or oversold conditions. The moving average of RSI smoothens the RSI values to reduce noise.
Inputs:
lengthrsi (Default: 14): The period for calculating RSI.
lengthrsima (Default: 8): The period for calculating the moving average of RSI.
Usage: Buy and sell signals are generated when the RSI crosses above or below the 50 level, respectively, indicating potential entry or exit points.
MACD (Moving Average Convergence Divergence):
Purpose: MACD is a trend-following momentum indicator that shows the relationship between two moving averages of a security’s price.
Inputs:
macdFastLength (Default: 12): The short period for the fast EMA.
macdSlowLength (Default: 26): The long period for the slow EMA.
macdSignalSmoothing (Default: 9): The period for the signal line.
Usage: Buy and sell signals are generated when the MACD line crosses above or below the signal line, respectively. This is an optional feature that can be enabled or disabled.
Signal Type Selection:
Purpose: Allows the trader to choose between RSI signals or supply/demand zone signals.
Inputs:
signalType (Default: "RSI"): Options are "RSI" or "Supply/Demand".
Usage: The chosen signal type determines the logic for plotting buy and sell signals on the chart.
Take Profit Signals:
Purpose: Provide take profit signals based on statistical volatility.
Inputs:
TheLength (Default: 20): The period for calculating the basis SMA and standard deviation.
tpmult (Default: 2.5): The multiplier for the standard deviation to set the take profit levels.
Usage: Generates buy and sell take profit signals when the price crosses over or under the calculated levels.
Detailed Explanation
Supply and Demand Zones Logic:
Swing High and Swing Low:
Functions isSwingHigh and isSwingLow determine whether the current high or low is the highest or lowest within a specified length, indicating potential supply or demand zones.
Zone Visualization:
When a new swing high or low is detected, a box is drawn from the identified bar and extended to the right for visibility. This helps traders visually identify these critical zones.
The boxes are updated dynamically as new swings are detected, ensuring the most relevant zones are always displayed.
RSI and MACD Signals:
RSI Calculation:
The script calculates the RSI using the specified period and then smooths it using an exponential moving average.
Buy and sell signals are generated based on the RSI's crossover with the 50 level.
MACD Calculation:
The MACD line and signal line are calculated using the specified periods.
Buy and sell signals are generated based on crossovers between the MACD line and the signal line.
These signals can be enabled or disabled based on user preference.
Trend Detection and Take Profit Signals:
Trend Detection:
The script calculates the basis (SMA) and upper and lower bands based on the standard deviation.
It determines the trend strength and direction by comparing the current price to these bands.
Take Profit Levels:
Take profit levels are set by multiplying the standard deviation by a user-defined multiplier.
Signals are plotted when the price crosses these take profit levels, indicating potential exit points.
Differences from Other Indicators
Combination of Multiple Indicators:
This script integrates supply and demand zones with RSI and MACD signals, offering a comprehensive tool for technical analysis.
Most other indicators focus on a single strategy, whereas this script provides a holistic view by combining multiple strategies.
Customizable Inputs:
The script offers a high degree of customization, allowing traders to adjust various parameters to suit their trading style and preferences.
Many indicators have fixed settings, limiting their adaptability to different market conditions.
Dynamic Zone Visualization:
The supply and demand zones are dynamically updated, providing real-time insights into key price levels.
This feature is not commonly found in other indicators, which may rely on static levels or less visually intuitive methods.
Usage Guide
Setup:
Add the script to your TradingView chart.
Adjust the input parameters as needed to match your trading strategy.
Interpreting Signals:
Supply and Demand Zones: Look for potential reversal points at these zones.
RSI and MACD Signals: Use these signals to identify potential entry and exit points.
Take Profit Signals: Set take profit levels based on the calculated signals to manage risk and lock in profits.
Combining Signals:
Combine signals from different features to increase the reliability of your trading decisions.
For example, a buy signal from RSI combined with a price approaching a demand zone may indicate a stronger buy opportunity.
Inputs Explained
Supply and Demand Zones:
supplySwingLength: The length of bars to consider for identifying swing highs.
demandSwingLength: The length of bars to consider for identifying swing lows.
zoneExtensionBars: The number of bars to extend the zones to the right.
RSI:
lengthrsi: The period for calculating the RSI.
lengthrsima: The period for calculating the EMA of the RSI.
MACD:
macdFastLength: The short period for the fast EMA.
macdSlowLength: The long period for the slow EMA.
macdSignalSmoothing: The period for the signal line.
Signal Type:
signalType: Choose between "RSI" and "Supply/Demand" signals.
Take Profit:
TheLength: The period for calculating the basis SMA and standard deviation.
tpmult: The multiplier for the standard deviation to set the take profit levels.
Conclusion
The "Uptrick: Supply and Demand Zones with RSI, MACD Signals and TP signals" script is a powerful and versatile indicator that combines multiple strategies to provide traders with a comprehensive analysis tool. Its detailed visualization of supply and demand zones, coupled with RSI and MACD signals, and trend-based take profit signals, makes it an invaluable tool for both novice and experienced traders. By understanding and utilizing its features effectively, traders can make more informed and confident trading decisions.
TrendFireOverview
They say "Trend is your Friend". In my short trading timeline, I've realized the difficult part is making this friendship to happen. Although, not impossible.
Trend Fire is one of the trend following strategy amongst many strategies out there. But the unique part of Trend Fire lies in the implementation and its accuracy to identify healthy Trends. Trend Fire is a purely Mathematical Indicator and aims for generating more successful trade signals. It has a unique strategy to avoid sideways market, false signals, and calculation to find entry for Trends, hence, more quality of trades.
I started my trading journey by observing the market movement for a long time as a beginner trader. Over time, I've realized that profit maximization can happen only if I can properly identify long trend. The reason why I was fascinated with trend following strategies and keen to solve the problems that trend following has.
Approach
In most typical trend following strategy setup, Trend identification starts by using fast and long period moving average crossovers. The fact that, moving averages are lagging in nature, it fails to identify good trends and produce many false signals. Although, it generates signals for trend also along with the false signals.
My aim was to reduce the false signals that occurs during consolidation and gain more accuracy on detecting healthy trends. The reason why I've obtained several approaches -
1. Moving Average Gap - during a consolidation period where lots of false signal generates in a crossover system, we can see that the distance/gap between the moving averages is very small, and in long trend the distance is large. So, a simple implementation was to limit the distance/gap by using a threshold to generate signals for trend outside the false signal threshold. This way, signals for long trend generates a few candles away but reduces false signal generation. For this Gap to work, a gap threshold of 20 works great to identify large trends and it is also a good entry point.
3. Volatility Adaptive moving average - As, this system is based on calculating distance/gap between MA's, the distance also doesn't always indicate proper momentum during a trend. The reason behind is that, 200 Moving average is also moving along the price during a trend and the distance/gap between moving averages vary according to the price. This also leads to generate false signals. So, it is more appropriate to replace 200 moving average with volatility adaptive moving average with a period of 1000, because adaptive moving average always reacts to the price and creates a larger distance/gap with price when there’s a trend in the market. Otherwise, it moves close with price in a sideways market. This nature of adaptability helps to reduce more false signals and gain more chances to take profitable trends.
This is also should be considered that no indicator system alone in trading is purely accurate. So, Trend Fire also is not an exception. There will be false signals, but the probability of getting false signal is less than the overall profits compared to any other moving average crossover system. The idea here is, maximizing your equity gradually over time rather than in a day and trade only when market is tradeable. Exactly how trading should be.
Usage
The usage of the indicator is simple. Once the indicator is applied in the mentioned currency pairs, it will show Buy/Sell signals along with Exit points in the chart.
The yellow line is the volatility adaptive moving average line which create distance during a trend and moves close to price when there is no trend. It is also used for trade exit indication, where the line meets with the price at the end of the trend and shows total pips gains/loss in a popup.
As, the indicator have built in adaptive and ATR base stop loss system, a good approach is to enable this in settings. So that, the loss will be minimum. The reason behind, by default the trades closed when a certain trend is over (When yellow line reaches close to the price after a gap) and this closing point not necessarily closes above/below signal. This is why Adaptive and ATR stop loss together make sure when trend reverses during a trend to take profit. Although, settings for Stop loss have been configured in the indicator, but if needed, settings can be changed for optimized results. It is also advisable to not to trade during a news alert as there are chances to generate false signal for high movement of the market.
Down-Sides
The indicator is dependent on the 1-minute time frame, larger time frames resulting in a signal overfitting condition. The indicator is set for only some selective currencies and commodities. So, its behavior might also change if the currency pair is out of scope. Below is the list of currencies which will work for now.
• EURUSD – FXCM
• GBPUSD – FXCM
• AUDUSD – OANDA
• USDCAD – OANDA
• GBPCAD – FXCM
• USDJPY – FXCM
• GBPJPY – OANDA
• EURJPY – OANDA
• CADJPY – FXCM
• AUDJPY – OANDA
• CHFJPY – OANDA
• EURAUD – FXCM
• GBPAUD – FXCM
• AUDCAD – OANDA
• EURGBP – FXCM
• EURCAD – OANDA
• XAUUSD – OANDA
• XAGUSD – OANDA
• USOIL – TVC
• BTCUSDT.P – BYBIT
More currency pair will be added in the future.
Settings
• Fast MA : Fast Moving Average
• Trend MA : Trend line Ema for determining Exit point
• Trend Threshold : Gap threshold between VAMA and Fast EMA
• VAMA : Volatility Adaptive Moving Average Length for calculation
• Enable Trend Coloring : Enable trend coloring on adaptive moving average line
• Enable Trailing Stop : Enable Adaptive and ATR trailing stop to exit trades
• Show Dashboard : Enable Trend and Signal value dashboard
• Position : Position of Dashboard in Chart
Alerts
Alert conditions are set for trade Entry and Exit scopes only and it does not mention Buy/Sell trade specifically in alerts for now. For that, you need to follow the chart after an alert as indicator shows Buy/Sell/Exit on chart. To create an alert based on the indicator follow these steps:
Go to the alert section (the alarm clock) -> create new alert -> select TrendFire in condition -> Below select TRADE ALERT and select date duration. In option select “once per bar close”, By default the message is set with ticker ID. Change the message if you want a personalized message.
Conclusion
As a programmer and problem solver, I have invested over a year to understand the market and tried to solve the problem that I faced as a trader. I wanted to develop an indicator that make sense and works logically in market. Also, the aim is to trade smartly with a strategy rather than biting in the bush randomly. Trade Fire is a result of countless failures and losses. I hope future contributions will grow this indicator to be more efficient down the line.
Thanks for reading…Happy Trading!
MAC Investor V3.0 [VK]This indicator combines multiple functionalities to assist traders in making informed decisions. It primarily uses Heikin Ashi candles, Moving Averages, and a Price Action Channel (PAC) to provide signals for entering and exiting trades. Here's a detailed breakdown:
Inputs
MAC Length: Sets the length for the PAC calculation.
Use Heikin Ashi Candles: Option to use Heikin Ashi candles for calculations.
Show Coloured Bars around MAC: Option to color bars based on their relation to the PAC.
Show Long/Short Signals: Options to display long and short signals.
Show MAs? : Option to show moving averages on the chart.
Show MAs Trend at the Bottom?: Option to show trend signals at the bottom of the chart.
MA Lengths: Length settings for three different moving averages.
Change MA Color Based on Direction?: Option to change the color of moving averages based on trend direction.
MA Higher TimeFrame: Allows setting a higher timeframe for moving averages.
Show SL-TP Lines: Option to display Stop Loss and Take Profit lines.
SL/TP Percentages: Set the percentages for Stop Loss and three levels of Take Profit.
Calculations and Features
Heikin Ashi Candles: Calculations are based on Heikin Ashi candle data if selected.
Price Action Channel (PAC): Uses Exponential Moving Averages (EMA) of the high, low, and close to create a channel.
Bar Coloring: Colors the bars based on their position relative to the PAC.
Long and Short Signals: Uses crossovers of the close price and PAC upper/lower bands to generate signals.
Moving Averages (MA): Plots three moving averages and colors them based on their trend direction.
Overall Trend Indicators: Uses triangles at the bottom of the chart to show the overall trend of the MAs.
Stop Loss and Take Profit Levels: Calculates and plots these levels based on user-defined percentages from the entry price.
Alerts: Provides alerts for long and short signals.
Use Cases and How to Use
Identifying Trends: The PAC helps to identify the trend direction. If the closing price is above the PAC upper band, it suggests an uptrend; if below the lower band, it suggests a downtrend.
Entering Trades: Use the long and short signals to enter trades. A long signal is generated when the closing price crosses above the PAC upper band, and a short signal is generated when it crosses below the PAC lower band.
Exit Strategies: Utilize the Stop Loss (SL) and Take Profit (TP) levels to manage risk and lock in profits. These levels are automatically calculated based on the entry price and user-defined percentages.
Trend Confirmation with MAs: The moving averages provide additional confirmation of the trend. When all three MAs are trending in the same direction (e.g., all green for an uptrend), it adds confidence to the trade signal.
Overall Trend Indicators: The triangles at the bottom of the chart show the overall trend direction of the MAs:
Green Triangle: All three MAs are trending upwards, indicating a strong uptrend.
Red Triangle: All three MAs are trending downwards, indicating a strong downtrend.
Yellow Triangle: Mixed signals from the MAs, indicating no clear trend.
Bar Coloring for Quick Analysis: The colored bars give a quick visual cue about the market condition, aiding in faster decision-making.
Alerts: Set up alerts to get notified when a long or short signal is generated, allowing you to act promptly without constantly monitoring the chart.
Maximizing Profit
To maximize profit with this indicator:
Follow the Signals: Use the long and short signals to time your entries. Ensure you follow the trend indicated by the PAC and MAs.
Risk Management: Always set your Stop Loss and Take Profit levels to manage risk. This will help you cut losses early and secure profits.
Confirm with MAs: Look for confirmation from the moving averages. When all MAs align with the signal, it indicates a stronger trend.
Overall Trend Indicators: Pay attention to the triangles at the bottom for overall trend confirmation. Only enter trades when the overall trend is in your favor.
Heikin Ashi for Smoothing: Use Heikin Ashi candles for smoother trends and fewer false signals.
Backtesting: Test the indicator on historical data to understand its performance and adjust settings as necessary.
Adapt to Market Conditions: Adjust the lengths of PAC and MAs based on the market's volatility and timeframe you are trading on.
How to Use the Indicator
Add to Chart: Add the indicator to your TradingView chart.
Configure Settings: Customize the input settings to fit your trading strategy and timeframe.
Monitor Signals: Watch for long and short signals and observe the trend direction with the PAC and MAs.
Check Overall Trend: Look at the triangles at the bottom of the chart to see the overall trend direction of the MAs.
Set Alerts: Configure alerts to get notified of new signals.
Manage Trades: Use the SL and TP levels to manage your trades effectively.
Grid TraderGrid Trader Indicator ( GTx ):
Overview
The Grid Trader Indicator is a tool that helps traders visualize key levels within a specified trading range. The indicator plots accumulation and distribution levels, an entry level, an exit level, and a midpoint. This guide will help you understand how to use the indicator and its features for effective grid trading.
Basics of Trading Range, Grid Buy, and Grid Sell
Trading Range
A trading range is the horizontal price movement between a defined upper ( resistance ) and lower ( support ) level over a period of time. When a security trades within a range, it repeatedly moves between these two levels without trending upwards or downwards significantly. Traders often use the trading range to identify potential buy and sell points:
Upper Level (Resistance): This is the price level at which selling pressure overcomes buying pressure, preventing the price from rising further.
Lower Level (Support): This is the price level at which buying pressure overcomes selling pressure, preventing the price from falling further.
Grid Trading Strategy
Grid trading is a type of trading strategy that involves placing buy and sell orders at predefined intervals around a set price. It aims to profit from the natural market volatility by buying low and selling high in a range-bound market. The strategy divides the trading range into several grid levels where orders are placed.
Grid Buy
Grid buy orders are placed at intervals below the current price . When the price drops to these levels, buy orders are triggered . This strategy ensures that the trader buys more as the price falls, potentially lowering the average purchase price .
Grid Sell
Grid sell orders are placed at intervals above the current price . When the price rises to these levels, sell orders are triggered . This ensures that the trader sells portions of their holdings as the price increases, potentially securing profits at higher levels .
Key Points of Grid Trading
Grid Size : The interval between each buy and sell order. This can be constant (e.g., $2 intervals) or variable based on certain conditions.
Accumulation Range : The lower part of the trading range where buy orders are placed.
Distribution Range : The upper part of the trading range where sell orders are placed.
Midpoint : The average price of the entry and exit levels, often used as a reference point for balance.
As the price moves up and down within this range, your buy orders will be triggered as the price drops and your sell orders will be triggered as the price rises. This allows you to accumulate more of the asset at lower prices and sell portions at higher prices, profiting from the price oscillations within the defined range. Grid trading can be particularly effective in a sideways market where there is no clear long-term trend. However, it requires careful monitoring and adjustment of grid levels based on market conditions to minimize risks and maximize returns .
Configuring the Indicator :
Once the indicator is added, you will see a settings icon next to it. Click on it to open the settings menu.
Adjust the Upper Level , Lower Level , Entry Level , and Exit Level to match your trading strategy and market conditions.
Set the Levels Visibility to control how many bars back the levels will be plotted.
Interpreting the Levels :
Accumulation Levels : These are plotted below the entry level and are potential buy zones. They are labeled as Accumulation Level 1, 2, and 3.
Distribution Levels : These are plotted above the exit level and are potential sell zones. They are labeled as Distribution Level 1, 2, and 3.
Upper Level : Marked in fuchsia, indicating the top boundary of the trading range.
Exit Level : Marked in yellow, indicating the level at which you plan to exit trades.
Midpoint : Marked in white, indicating the average of the entry and exit levels.
Entry Level : Marked in yellow, indicating the level at which you plan to enter trades.
Lower Level : Marked in aqua, indicating the bottom boundary of the trading range.
By visualizing key levels, you can make informed decisions on where to place buy and sell orders, potentially maximizing your trading profits through systematic grid trading.
Wolf DCA CalculatorThe Wolf DCA Calculator is a powerful and flexible indicator tailored for traders employing the Dollar Cost Averaging (DCA) strategy. This tool is invaluable for planning and visualizing multiple entry points for both long and short positions. It also provides a comprehensive analysis of potential profit and loss based on user-defined parameters, including leverage.
Features
Entry Price: Define the initial entry price for your trade.
Total Lot Size: Specify the total number of lots you intend to trade.
Percentage Difference: Set the fixed percentage difference between each DCA point.
Long Position: Toggle to switch between long and short positions.
Stop Loss Price: Set the price level at which you plan to exit the trade to minimize losses.
Take Profit Price: Set the price level at which you plan to exit the trade to secure profits.
Leverage: Apply leverage to your trade, which multiplies the potential profit and loss.
Number of DCA Points: Specify the number of DCA points to strategically plan your entries.
How to Use
1. Add the Indicator to Your Chart:
Search for "Wolf DCA Calculator" in the TradingView public library and add it to your chart.
2. Configure Inputs:
Entry Price: Set your initial trade entry price.
Total Lot Size: Enter the total number of lots you plan to trade.
Percentage Difference: Adjust this to set the interval between each DCA point.
Long Position: Use this toggle to choose between a long or short position.
Stop Loss Price: Input the price level at which you plan to exit the trade to minimize losses.
Take Profit Price: Input the price level at which you plan to exit the trade to secure profits.
Leverage: Set the leverage you are using for the trade.
Number of DCA Points: Specify the number of DCA points to plan your entries.
3. Analyze the Chart:
The indicator plots the DCA points on the chart using a stepline style for clear visualization.
It calculates the average entry point and displays the potential profit and loss based on the specified leverage.
Labels are added for each DCA point, showing the entry price and the lots allocated.
Horizontal lines mark the Stop Loss and Take Profit levels, with corresponding labels showing potential loss and profit.
Benefits
Visual Planning: Easily visualize multiple entry points and understand how they affect your average entry price.
Risk Management: Clearly see your Stop Loss and Take Profit levels and their impact on your trade.
Customizable: Adapt the indicator to your specific strategy with a wide range of customizable parameters.
Buffett Quality Score [Communication Services]Buffett Quality Score "Communication Services": Analyzing Communication Companies with Precision
The communication services sector encompasses a diverse range of companies involved in telecommunications, media, and entertainment. To assess the financial strength and performance of companies within this sector, the Buffett Quality Score employs a tailored set of financial metrics. This scoring system, inspired by the Piotroski F-Score methodology, assigns points based on specific financial criteria to provide a comprehensive quality assessment.
Scoring Methodology
The Buffett Quality Score is designed to evaluate the overall financial health and quality of companies operating within the communication services sector. Each selected financial metric is chosen for its relevance and importance in evaluating a company's performance and potential for sustainable growth. The score is computed by assigning points based on the achievement of specific thresholds for each indicator, with the total points determining the final score. This methodology ensures a nuanced analysis that captures the unique dynamics of the communication services industry.
Selected Financial Metrics and Criteria
1. Return on Invested Capital (ROIC) > 10.0%
Relevance: ROIC measures a company's efficiency in allocating capital to profitable investments. For communication companies, a ROIC above 10.0% indicates effective capital utilization, crucial for sustaining growth and innovation.
2. Return on Equity (ROE) > 15.0%
Relevance: ROE evaluates the return generated on shareholders' equity. A ROE exceeding 15.0% signifies robust profitability and effective management of shareholder funds, essential for investor confidence in communication companies.
3. Revenue One-Year Growth > 10.0%
Relevance: High revenue growth indicates strong market demand and successful business strategies. For communication services, where innovation and content delivery are paramount, growth exceeding 10.0% reflects market leadership and competitive positioning.
4. Gross Margin > 40.0%
Relevance: Gross margin measures profitability after accounting for production costs. In the communication services sector, a gross margin above 40.0% demonstrates efficient operations and high-value content offerings, critical for maintaining competitive advantage.
5. Net Margin > 10.0%
Relevance: Net margin assesses overall profitability after all expenses. A net margin exceeding 10.0% indicates effective cost management and operational efficiency, fundamental for sustained profitability in communication companies.
6. EPS One-Year Growth > 10.0%
Relevance: EPS growth reflects the company's ability to increase earnings per share. For communication firms, where content monetization and subscription models are prevalent, EPS growth above 10.0% signals successful business expansion and value creation.
7. Piotroski F-Score > 6.0
Relevance: The Piotroski F-Score evaluates fundamental strength across various financial metrics. A score above 6.0 suggests strong financial health and operational efficiency, crucial for navigating competitive pressures in the communication services industry.
8. Price/Earnings Ratio (Forward) < 25.0
Relevance: The forward P/E ratio compares current share price to expected future earnings. A ratio below 25.0 indicates reasonable valuation relative to growth prospects, important for investors seeking value opportunities in communication stocks.
9. Current Ratio > 1.5
Relevance: The current ratio assesses short-term liquidity by comparing current assets to current liabilities. In communication companies, a ratio above 1.5 ensures financial flexibility and the ability to meet short-term obligations, vital for operational stability.
10. Debt to Equity Ratio < 1.0
Relevance: A lower debt to equity ratio indicates prudent financial management and reduced reliance on debt financing. For communication firms, maintaining a ratio below 1.0 signifies a healthy balance sheet and lower financial risk.
Interpreting the Buffett Quality Score
0-4 Points: Indicates potential weaknesses across multiple financial areas, suggesting higher risk.
5 Points: Represents average performance, warranting further analysis to understand underlying factors.
6-10 Points: Reflects strong financial health and quality, positioning the company favorably within the competitive communication services industry.
Conclusion
The Buffett Quality Score provides a robust framework for evaluating communication companies, emphasizing critical financial indicators tailored to industry dynamics. By leveraging these insights, investors and analysts can make informed decisions, identifying companies poised for sustainable growth and performance in the ever-evolving communication services landscape.
Disclaimer: The Buffett Quality Score serves as a tool for financial analysis and should not replace professional advice or comprehensive due diligence. Investors should conduct thorough research and consult with financial experts based on individual investment objectives.
Buffett Quality Score [Information Technology]Buffett Quality Score 'Information Technology': Assessing Tech Companies with Precision
The information technology sector is characterized by rapid innovation, high growth potential, and significant competition. To evaluate the financial health and performance of companies within this dynamic industry, the Buffett Quality Score employs a tailored set of financial metrics. This scoring system, inspired by the Piotroski F-Score methodology, assigns points based on specific financial criteria to provide a comprehensive quality assessment.
Scoring Methodology
The Buffett Quality Score is designed to assess the overall financial strength and quality of companies within the tech sector. Each selected financial metric is chosen for its relevance and importance in evaluating a company's performance and potential for sustainable growth. The score is computed by assigning points based on the achievement of specific thresholds for each indicator, with the total points determining the final score. This methodology ensures a nuanced analysis that captures the unique dynamics of the information technology industry.
Selected Financial Metrics and Criteria
1. Return on Invested Capital (ROIC) > 10.0%
Relevance: ROIC measures a company's efficiency in allocating capital to profitable investments. For tech companies, a ROIC above 10.0% indicates effective use of investment capital to generate strong returns, crucial for sustaining innovation and growth.
2. Return on Assets (ROA) > 5.0%
Relevance: ROA assesses how efficiently a company utilizes its assets to generate earnings. A ROA above 5.0% signifies that the company is effectively leveraging its assets, which is vital in the capital-intensive tech sector.
3. Revenue One-Year Growth > 10.0%
Relevance: High revenue growth indicates robust market demand and successful product or service offerings. For tech companies, where rapid scalability is common, growth exceeding 10.0% demonstrates significant market traction and expansion potential.
4. Gross Margin > 40.0%
Relevance: Gross margin reflects the proportion of revenue remaining after accounting for the cost of goods sold. In the tech sector, a gross margin above 40.0% indicates efficient production and high-value offerings, essential for maintaining competitive advantage.
5. Net Margin > 15.0%
Relevance: Net margin measures overall profitability after all expenses. A net margin above 15.0% demonstrates strong financial health and the ability to convert revenue into profit, highlighting the company's operational efficiency.
6. EPS One-Year Growth > 10.0%
Relevance: Earnings per share (EPS) growth indicates the company's ability to increase profitability per share. For tech firms, EPS growth above 10.0% signals positive earnings momentum, reflecting successful business strategies and market adoption.
7. Piotroski F-Score > 6.0
Relevance: The Piotroski F-Score assesses fundamental strength, including profitability, leverage, liquidity, and operational efficiency. A score above 6.0 suggests solid financial fundamentals and resilience in the competitive tech landscape.
8. Price/Earnings Ratio (Forward) < 25.0
Relevance: The forward P/E ratio compares current share price to expected future earnings. A ratio below 25.0 indicates reasonable valuation relative to growth expectations, important for identifying undervalued opportunities in the fast-paced tech sector.
9. Current Ratio > 1.5
Relevance: The current ratio evaluates short-term liquidity by comparing current assets to current liabilities. In the tech industry, a ratio above 1.5 ensures the company can meet its short-term obligations, essential for operational stability.
10. Debt to Equity Ratio < 1.0
Relevance: A lower debt to equity ratio signifies prudent financial management and reduced reliance on debt. For tech companies, which often require significant investment in R&D, a ratio below 1.0 highlights a strong financial structure.
Interpreting the Buffett Quality Score
0-4 Points: Indicates potential weaknesses across multiple financial areas, suggesting higher risk.
5 Points: Represents average performance, warranting further analysis to understand underlying factors.
6-10 Points: Reflects strong financial health and quality, positioning the company favorably within the competitive tech industry.
Conclusion
The Buffett Quality Score provides a strategic framework for evaluating tech companies, emphasizing critical financial indicators tailored to industry dynamics. By leveraging these insights, investors and analysts can make informed decisions, identifying companies poised for sustainable growth and performance in the ever-evolving tech landscape.
Disclaimer: The Buffett Quality Score serves as a tool for financial analysis and should not replace professional advice or comprehensive due diligence. Investors should conduct thorough research and consult with financial experts based on individual investment objectives.
Buffett Quality Score [Health Care]Evaluating Health Care Companies with the Buffett Quality Score "Health Care"
The health care sector presents unique challenges and opportunities, demanding a specialized approach to financial evaluation. The Buffett Quality Score is meticulously designed to assess the financial robustness and quality of companies within this dynamic industry. By focusing on industry-specific financial metrics, this scoring system provides valuable insights for investors and analysts navigating the complexities of the health care sector.
Scoring Methodology
Each selected financial metric contributes a point to the overall score if the specified condition is met. The combined score is a summation of points across all criteria, providing a comprehensive assessment of financial health and quality.
Selected Financial Metrics and Criteria
1. Altman Z-Score > 2.0
Relevance: The Altman Z-Score evaluates bankruptcy risk based on profitability, leverage, liquidity, solvency, and activity. In the health care sector, where regulatory changes and technological advancements can impact financial stability, a score above 2.0 signifies a lower risk of financial distress.
2. Piotroski F-Score > 6.0
Relevance: The Piotroski F-Score assesses fundamental strength, emphasizing profitability, leverage, liquidity, and operating efficiency. For health care companies, which often face regulatory challenges and R&D expenses, a score above 6.0 indicates strong financial health and operational efficiency.
3. Current Ratio > 1.5
Relevance: The Current Ratio evaluates short-term liquidity by comparing current assets to current liabilities. In the health care sector, where cash flow stability is essential for ongoing operations, a ratio above 1.5 ensures the company's ability to meet near-term obligations.
4. Debt to Equity Ratio < 1.0
Relevance: A lower Debt to Equity Ratio signifies prudent financial management and reduced reliance on debt financing. This is critical for health care companies, which require significant investments in research and development without overleveraging.
5. EBITDA Margin > 15.0%
Relevance: The EBITDA Margin measures operating profitability, excluding non-operating expenses. A margin above 15.0% indicates efficient operations and the ability to generate substantial earnings from core activities.
6. EPS One-Year Growth > 5.0%
Relevance: EPS growth reflects the company's ability to increase earnings per share over the past year. For health care companies, which often face pricing pressures and regulatory changes, growth exceeding 5.0% signals positive earnings momentum and potential market strength.
7. Net Margin > 10.0%
Relevance: Net Margin measures overall profitability after all expenses. A margin above 10.0% demonstrates strong financial performance and the ability to convert revenue into profit effectively.
8. Return on Equity (ROE) > 15.0%
Relevance: ROE indicates the company's ability to generate profits from shareholder equity. An ROE above 15.0% suggests efficient use of capital and strong returns for investors.
9. Revenue One-Year Growth > 5.0%
Relevance: Revenue growth reflects market demand and company expansion. In the health care sector, where innovation drives growth, revenue exceeding 5.0% indicates successful market penetration and product adoption.
10. Price/Earnings Ratio (Forward) < 20.0
Relevance: The Forward P/E Ratio reflects investor sentiment and earnings expectations. A ratio below 20.0 suggests reasonable valuation relative to earnings projections, which is important for investors seeking value and growth opportunities in the health care sector.
Interpreting the Buffett Quality Score
0-4 Points: Indicates potential weaknesses across multiple financial areas, warranting careful consideration and risk assessment.
5 Points: Suggests average performance based on sector-specific criteria, requiring further analysis to determine investment viability.
6-10 Points: Signifies strong financial health and quality, positioning the company favorably within the competitive health care industry.
Conclusion
The Buffett Quality Score offers a strategic framework for evaluating health care companies, emphasizing critical financial indicators tailored to industry dynamics. By leveraging these insights, stakeholders can make informed decisions and identify companies poised for sustainable growth and performance in the evolving health care landscape.
Disclaimer: The Buffett Quality Score serves as a tool for financial analysis and should not replace professional advice or comprehensive due diligence. Investors should conduct thorough research and consult with financial experts based on individual investment objectives.
Buffett Quality Score [Consumer Staples]Evaluating Consumer Staples Companies with the Buffett Quality Score
In the world of consumer staples, where stability and consistent performance are paramount, the Buffett Quality Score provides a comprehensive framework for assessing financial health and quality. This specialized scoring system is tailored to capture key aspects that are particularly relevant in the consumer staples sector, influencing investment decisions and strategic evaluations.
Selected Financial Metrics and Criteria
1. Gross Margin > 25.0%
Relevance: Consumer staples companies often operate in competitive markets. A Gross Margin exceeding 25.0% signifies efficient cost management and pricing strategies, critical for sustainable profitability amidst market pressures.
2. Net Margin > 5.0%
Relevance: Net Margin > 5.0% reflects the ability of consumer staples companies to generate bottom-line profits after accounting for all expenses, indicating operational efficiency and profitability.
3. Return on Assets (ROA) > 5.0%
Relevance: ROA > 5.0% measures how effectively consumer staples companies utilize their assets to generate earnings, reflecting operational efficiency and resource utilization.
4. Return on Equity (ROE) > 10.0%
Relevance: ROE > 10.0% indicates efficient capital deployment and shareholder value creation, fundamental for sustaining growth and competitiveness in the consumer staples industry.
5. Current Ratio > 1.5
Relevance: Consumer staples companies require strong liquidity to manage inventory and operational expenses. A Current Ratio > 1.5 ensures sufficient short-term liquidity to support ongoing operations.
6. Debt to Equity Ratio < 1.0
Relevance: With the need for stable finances, a Debt to Equity Ratio < 1.0 reflects prudent financial management and reduced reliance on debt financing, essential for long-term sustainability.
7. Interest Coverage Ratio > 3.0
Relevance: Consumer staples companies with an Interest Coverage Ratio > 3.0 demonstrate their ability to comfortably meet interest obligations, safeguarding against financial risks.
8. EPS One-Year Growth > 5.0%
Relevance: EPS growth > 5.0% indicates positive momentum and adaptability to changing market dynamics, crucial for consumer staples companies navigating evolving consumer preferences.
9. Revenue One-Year Growth > 5.0%
Relevance: Consistent revenue growth > 5.0% reflects market adaptability and consumer demand, highlighting operational resilience and strategic positioning.
10. EV/EBITDA Ratio < 15.0
Relevance: The EV/EBITDA Ratio < 15.0 reflects favorable valuation and earnings potential relative to enterprise value, offering insights into investment attractiveness and market competitiveness.
Interpreting the Buffett Quality Score
0-4 Points: Signals potential weaknesses across critical financial areas, warranting deeper analysis and risk assessment.
5 Points: Indicates average performance based on sector-specific criteria.
6-10 Points: Highlights strong financial health and quality, aligning with the stability and performance expectations of the consumer staples industry.
Conclusion
The Buffett Quality Score for consumer staples provides investors and analysts with a structured approach to evaluate and compare companies within this sector. By focusing on these essential financial metrics, stakeholders can make informed decisions and identify opportunities aligned with the stability and growth potential of consumer staples businesses.
Disclaimer: The Buffett Quality Score serves as a tool for financial evaluation and analysis. It is not a substitute for professional financial advice or investment recommendations. Investors should conduct thorough research and seek personalized guidance based on individual circumstances.
Buffett Quality Score [Materials]The Buffett Quality Score tailored for the Materials sector aims to assess the financial strength and quality of companies within this industry. Each selected financial ratio is strategically chosen to align with the unique characteristics and challenges prevalent in the Materials sector.
Selected Financial Ratios and Criteria:
1. Asset Turnover > 0.8
Relevance: In the Materials sector, efficient asset utilization is crucial for productivity and profitability. A high Asset Turnover (>0.8) indicates effective management of resources and operational efficiency.
2. Current Ratio > 1.5
Relevance: Materials companies often require adequate liquidity to manage inventory and operational expenses. A Current Ratio > 1.5 ensures sufficient short-term liquidity to support ongoing operations and investments.
3. Debt to Equity Ratio < 1.0
Relevance: Given the capital-intensive nature of Materials projects, maintaining a low Debt to Equity Ratio (<1.0) signifies prudent financial management with reduced reliance on debt financing, essential for stability amid industry fluctuations.
4. Gross Margin > 25.0%
Relevance: Materials companies deal with varying production costs and market pricing. A Gross Margin exceeding 25.0% reflects effective cost management and pricing strategies, critical for profitability in a competitive market.
5. EBITDA Margin > 15.0%
Relevance: Strong EBITDA margins (>15.0%) indicate robust operational performance and profitability, essential for sustaining growth and weathering industry-specific challenges.
6. Interest Coverage Ratio > 3.0
Relevance: The Materials sector is subject to market cyclicality and commodity price fluctuations. An Interest Coverage Ratio > 3.0 ensures the company's ability to service debt obligations, safeguarding against financial risks.
7. EPS One-Year Growth > 5.0%
Relevance: EPS growth > 5.0% demonstrates the company's ability to generate sustainable earnings amidst industry dynamics, reflecting positive investor sentiment and potential future prospects.
8. Revenue One-Year Growth > 5.0%
Relevance: Materials companies require consistent revenue growth (>5.0%) to support expansion initiatives and capitalize on market opportunities, indicative of operational resilience and adaptability.
9. Return on Assets (ROA) > 5.0%
Relevance: ROA > 5.0% showcases efficient asset utilization and profitability, essential metrics for evaluating performance and competitive positioning within the Materials industry.
10. Return on Equity (ROE) > 10.0%
Relevance: ROE > 10.0% reflects effective capital deployment and shareholder value creation, crucial for sustaining long-term growth and investor confidence in Materials sector investments.
Score Interpretation:
0-4 Points: Signals potential weaknesses across critical financial aspects, requiring in-depth analysis and risk assessment.
5 Points: Represents average performance based on sector-specific criteria.
6-10 Points: Indicates strong financial health and quality, demonstrating robustness and resilience within the demanding Materials industry landscape.
Development and Context:
The selection and weighting of these specific financial metrics underwent meticulous research and consideration to ensure relevance and applicability within the Materials sector. This scoring framework aims to provide actionable insights for stakeholders navigating investment decisions and evaluating company performance in the Materials industry.
Disclaimer: This information serves as an educational resource on financial evaluation methodology tailored for the Materials sector. It does not constitute financial advice or a guarantee of future performance. Consult qualified professionals for personalized financial guidance based on your specific circumstances and investment objectives.
Dividend-to-ROE RatioDividend-to-ROE Ratio Indicator
The Dividend-to-ROE Ratio indicator offers valuable insights into a company's dividend distribution relative to its profitability, specifically comparing the Dividend Payout Ratio (proportion of earnings as dividends) to the Return on Equity (ROE), a measure of profitability from shareholder equity.
Interpretation:
1. Higher Ratio: A higher Dividend-to-ROE Ratio suggests a stable dividend policy, where a significant portion of earnings is returned to shareholders. This can indicate consistent dividend payments, often appealing to income-seeking investors.
2. Lower Ratio: Conversely, a lower ratio implies that the company retains more earnings for growth, potentially signaling a focus on reinvestment for future expansion rather than immediate dividend payouts.
3. Excessively High Ratio: An exceptionally high ratio may raise concerns. While it could reflect a generous dividend policy, excessively high ratios might indicate that a company is distributing more earnings than it can sustainably afford. This could potentially hinder the company's ability to reinvest in its operations, research, or navigate economic downturns effectively.
Utility and Applications:
The Dividend-to-ROE Ratio can be particularly useful in the following scenarios:
1. Income-Oriented Investors: For investors seeking consistent dividend income, a higher ratio signifies a company's commitment to distributing profits to shareholders, potentially aligning with income-oriented investment strategies.
2. Financial Health Assessment: Analysts and stakeholders can use this ratio to gauge a company's financial health and dividend sustainability. It provides insights into management's capital allocation decisions and strategic focus.
3. Comparative Analysis: When comparing companies within the same industry, this ratio helps in benchmarking dividend policies and identifying outliers with unusually high or low ratios.
Considerations:
1. Contextual Analysis: Interpretation should be contextualized within industry standards and the company's financial history. Comparing the ratio with peers in the same sector can provide meaningful insights.
2. Financial Health: It's crucial to evaluate this indicator alongside other financial metrics (like cash flow, debt levels, and profit margins) to grasp the company's overall financial health and sustainability of its dividend policy.
Disclaimer: This indicator is for informational purposes only and does not constitute financial advice. Investors should conduct thorough research and consult with financial professionals before making investment decisions based on this ratio.
Market Structure (Range) & Internal Liquidity
This indicator will simplify the price-action reading of any trader/investor by decluttering his/her charts from un-important & confusing candles to highlight the true momentum candles which are usually formed by institutional buying/selling .
The indicator will be a good tool in the arsenal of the following styles of Trading/Investing
Smart Money / Liquidity Concepts
Price Action Concepts
Demand & Supply Concepts
Support & Resistance Concepts
UNIQUE FEATURES:
1. Market Structure - Range & Internal Liquidity:
Unlike other liquidity indicators, this indicator only highlights liquidity levels of significant importance. Not every intermediate high & low in a chart are worthy of noticing, hence by enabling the 'Swings' & 'Range (BoS)' feature in the indicator settings, the structure highs and lows (external liquidity) in a chart can be identified.
Any other liquidity levels within a market range (Range between structural High & Low) is known as internal liquidity which price targets to collect enough orders before heading towards the external liquidity levels.
2. Gaps (Fair Value Gaps / Imbalance):
Not every imbalance / gap between candles are important & trade-worthy. This feature of the indicator is different from the other widely available imbalance indicators & only highlights gaps formed by true momentum candles. Gaps between unimportant inside bars are not highlighted, as these bars occur in the absence of momentum.
3. True Price Action:
Looking at the two charts below, we can clearly observe the difference between price action of a confusing normal chart & the simplified price action highlighted by the indicator. This feature declutters the charts by only highlighting the candles a trader / investor should notice in a chart.
This feature when used in confluence with the liquidity levels feature & gap feature of the indicator, helps identify the true demand & supply zones (order blocks) in a chart.
Before
After
4. Zig Zag Lines:
This unique feature which is useful to Identify & Backtest different entry types taught by Smart Money Traders . This feature helps the trader understand the True Fractal Nature of price. This can also be seen as an alternate to the default line chart feature.
Examples of Entry Types taken by Smart Money Traders
ADDITIONAL FEATURES:
(These features are essential addons to trade liquidity. However, these are derived from publicly available indicators from the Tradingview library, but with a different interpretation for a better visualization of charts & or to time better trade entries without cluttering the charts)
a. Inside Bar & Outside Bars:
Identify not just a single Inside Bar as highlighted by other indicators, but to highlight a series of candles which are within a master candle range and are exhibiting unimportant sideways price action.
Outside Bars only relevant to momentum candles are highlighted, ignoring candles that occur within a master candle range. Highs & Lows of such Outside Bars are used by aggressive traders to identify liquidity levels in the charts.
b. Highs & Lows of previous Monthly / Weekly / Daily & Hourly Candles:
This feature draws Highs & Lows of previous Monthly / Weekly / Daily & Hourly Candles on the extreme right hand side of the chart to keep the charts clean.
Additionally for Hourly time frame, the indicator includes a setting to select the hourly candle time frame (60 min / 75 min / 240 min), which are personal and different for each trader.
UNDERLYING CONCEPT:
In the image below we see how a large majority of Traders / Investors incorrectly mark Structure markings, mistaking a raid of internal liquidity as a Break of Structure, thereby taking trades opposite to the broader trend of the markets
However, this indicator has a higher accuracy of identifying the correct price structure by only marking a structure high or low, when a subsequently opposite side liquidity is taken/raided. Further the broader trend of the markets can be easily identified by looking as to which side the Break of Structure has happened. (This is visible in the indicator in the form of 'Range' feature, so if a Range High is broken then it is understood to be in an uptrend & vice versa)
The underlying core functionality of the indicator is best displayed by the image below
USECASE OF THE INDICATOR:
Before taking any Buying/Selling position in the markets, a Trader / Investor must analyze the price action on the following parameters
HTF & LTF Trend Identification (To judge if trade is Pro-Trend or Counter-Trend)
Is Price at a High Probability Area of Interest?
Is Price satisfying the trade entry conditions?
Let us see how this indicator can be used as a complete trading system in itself and addresses each of the above parameters
Disclaimer: Illustrations shown below are just for understanding the features of the indicator & does not guarantee profitability. Every trader must back test their setups to arrive at a setup with an edge (positive expectancy) before they start actively trading the setup.
1. HTF & LTF Trend Identification (Pro-Trend / Counter-Trend) using 'Range (BoS)' feature of the indicator
Let's assume a Day Trader, uses hourly chart (75 min) to frame his Higher Time Frame (HTF) ideas & 15min charts (LTF) for trade entries
Looking at the chart below the Trader concludes that the HTF has most recently broken the structure to the downside and is considered Bearish till price action is below the range high of 48600 levels. It can also be concluded that the price is currently in a Bullish retracement.
The Trader can choose to take both Pro-Trend or Counter-Trend Trades, timing the trade entries using the LTF charts.
Looking at the LTF chart below, it is evident that price on LTF has also broken structure to the downside and is now aligned with the HTF Bearish Trend. The Trader will now look to get into short trades, to take trades both in line with HTF & LTF trend.
2. Let's identify if Price is at a High Probability Area of Interest, using either single or combination of the 'Swings' / 'Gaps' / 'Outside Bars' / 'HL of previous M,W,D, H candles' features of the indicator
Definition of High Probability Level / Area differs from each Traders perspective depending upon which of the Trading Styles (mentioned in the beginning) does one use.
Smart Money Traders
SMC Traders are known to get into trades early and their high R:R trades are taken mostly at a High Probability Area of Interest which are identified by them on HTF, by looking for candles with imbalance (gaps) & or candles which have taken out a previous liquidity and then having creating imbalance (gaps).
Also Turtle Soups is one of the favorite setups for SMC traders, where a trader enters a trade on LTF (typically 1 min/3min & 5min) after grabbing HTF liquidity lying at H/L of outside bar / previous monthly, weekly, daily or hourly candles.
Demand & Supply Traders
Some of the Best Demand & Supply Traders have the patience to wait for trades and take trades at the extreme Demand & Supply Zones within a market Range.
As illustrated below, the extreme hourly supply zone just below the structure high, which has the confluence of imbalance and Bearish HTF confirmation resulted in a good R:R trade.
Price Action Traders & Support & Resistance Traders
From the illustration below we can see how the 15 min Range breakdown confirms the breakdown of the Inverted Cup Pattern for Price Action Traders & Support & Resistance Traders using the same area of breakdown as the new Resistance to enter Short trades
3. Let's identify if Price is satisfying the Trade Entry Conditions using the 'Zig-Zag Lines' feature
Statistics say that majority (> 80%) of Traders blow up their accounts multiple times or completely give up and never achieve profitability.
One of the primary reasons for this is Traders punching trades randomly and without having proper Setup or rules for entering Trades.
Also in order to arrive at rules or execute the different entry models (couple of examples highlighted earlier) taught by different Trainers, a Trader needs to learn to visualize charts in a similar format to what the trainers are teaching.
The Zig-Zag lines feature is a form of line chart that joins the swing high points to the swing low points on the chart to represent the True Price action & a proper fractal nature of the markets, unlike the line chart which is formed by only by joining the closing value of each candle.
From the image below we can see that the Zig-Zag lines feature eliminates the randomness visible in the line chart and is a more smoother chart. Using this feature one can back test the various entry models widely available on the internet or arrive at a user specific model which he/she is comfortable with.
CONCLUSION:
Trading with a deeper understanding of Price Action allows a Trader/Investor to enter or exit trades with ease. Price Action trading allows individuals to keep their charts clean and stay away from the other lagging technical indicators and enter trades much earlier than other technical indicators.
This indicator attempts in simplifying the understanding of price action for every one and identify potential high probability areas / levels where one should enter / exit trades.
This indicator will be an important tool in the arsenal of any Trader / Investor to take better informed trades, however it does not guarantee profitability of a Trader, due to the randomness of the markets & external factors that influence each trader.
GET ACCESS:
Refer Author's instructions below to get access to the indicator
PUELL - PUELL Top and Bottom Indicator for BTC [Logue]Puell Multiple Indicator (PUELL) - The Puell multiple is the ratio between the daily coin issuance in USD and its 365-day moving average. This multiple helps to measure miner profitability. The PUELL indicator smooths the Puell multiple using a 14-day simple moving average. When the PUELL goes to high values relative to historical values, it indicates the profitability of the miners is high and a top may be near. When the PUELL is low relative to historical values, it indicates the profitability of the minors is low and a bottom may be near. The default trigger values are PUELL values above 3.0 for a "top" and below 0.5 for a "bottom".
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.
BearMetricsLooking at the financial health of a company is a critical aspect of stock analysis because it provides essential insights into the company's ability to generate profits, meet its financial obligations, and sustain its operations over the long term. Here are several reasons why assessing a company's financial health is important when evaluating a stock:
1. **Profitability and Earnings Growth**: A company's financial statements, particularly the income statement, provide information about its profitability. Analyzing earnings and revenue trends over time can help you assess whether the company is growing or declining. Investors generally prefer companies that show consistent earnings growth.
2. **Risk Assessment**: Financial statements, including the balance sheet and income statement, offer a comprehensive view of a company's assets, liabilities, and equity. By evaluating these components, you can gauge the level of financial risk associated with the stock. A healthy balance sheet typically includes a manageable debt load and strong equity.
3. **Cash Flow Analysis**: Cash flow statements reveal how effectively a company manages its cash, which is crucial for day-to-day operations, debt servicing, and future investments. Positive cash flow is essential for a company's stability and growth prospects.
4. **Debt Levels**: Examining a company's debt levels and debt-to-equity ratio can help you determine its leverage. High debt levels can be a cause for concern, as they may indicate that the company is at risk of financial distress, especially if it struggles to meet interest payments.
5. **Liquidity**: Liquidity is vital for a company's short-term survival. By assessing a company's current assets and current liabilities, you can gauge its ability to meet its short-term obligations. Companies with low liquidity may face difficulties during economic downturns or unexpected financial challenges.
6. **Dividend Sustainability**: If you're an income-oriented investor interested in dividend-paying stocks, you'll want to ensure that the company can sustain its dividend payments. A healthy balance sheet and consistent cash flow can provide confidence in dividend sustainability.
7. **Investment Confidence**: A company with a strong financial position is more likely to attract investor confidence and positive sentiment. This can lead to higher stock prices and a lower cost of capital for the company, which can be beneficial for its growth initiatives.
8. **Risk Mitigation**: By assessing a company's financial health, you can mitigate investment risk. Understanding a company's financial position allows you to make more informed decisions about the level of risk you are comfortable with and whether a particular stock aligns with your risk tolerance.
9. **Long-Term Viability**: Ultimately, investors are interested in companies that have the potential for long-term success. A company with a healthy financial foundation is more likely to weather economic downturns, adapt to industry changes, and thrive over the years.
In summary, examining a company's financial health is a fundamental aspect of stock analysis because it provides a comprehensive picture of the company's current state and its ability to navigate future challenges and capitalize on opportunities. It helps investors make informed decisions and assess the long-term prospects of a stock in their portfolio.
Trade Manager & Position Size Tool & PnL Tracker [AlgoScopes] V1Position size tool, leverage calculator, trade tracker, money management, trade presentation, risk reward management, margin position, live profit and loss, that's all in this one Trade Manager indicator.
The idea for this indicator comes from two years ago when I was helping a friend who, at the request of 15-20 members from our telegram group, wanted to create a paid group and share our ideas for trade with them (it started as an experiment for just a month or two and ended with 15 months with over 500 trading ideas and signals, with a complete TA chart). If I had time to create this indicator back then for members, it would have been much easier for them to be able to understand and follow the trade idea that was presented through a classic chart, with all the things that a TA must have:
Entry (as well as the reason for entry),
Stop (where the idea for the trade is no longer valid),
Target (with the reason why it is the target for that trade),
Take profits (taking part of the profit on the way to the target).
The majority of members still did not understand how much position to trade, what is the possible profit or loss, if the margin trade is how much leverage to use, in one word “money management”. The most important rule that every trader must follow is "Plan your trade and trade your plan". Learn money management and you are halfway there to becoming a successful trader. It is only after all that, you learn to use some of the "holy grail" indicators. When you have mastered those first two rules, find and master your favorite indicator or trading style (the most important thing is to stick to those two rules). The margin | leverage is also included in the script, for which there are so many dilemmas, arguments and discussions. (that many who still do not understand margin, would trade that it is not passionate if it is controlled). Too much for an introduction, especially since this indicator has so much to explain.
Most importantly, this is an invite-only indicator, and there are so many free indicators on tradingview that can also serve you very well. As far as I know, all exchanges have a calculator tool to calculate the possible profit and loss for each trade you plan to take.
*This indicator is not recommended for scalping on a 1min chart because the script, as you will see, is very complex, so the loading time is longer than with simpler indicators.
💠 ABOUT THE SCRIPT
This script is made to help manage trade. In this one indicator you have the possibility to do technical analysis, calculation for trade (four types: account size risk, trade investment, maximum to lose or position size), monitor 'PnL' (profit and loss in real time) do the calculation in the second, maybe local currency, and set an alert (from entry to any other change in trade). As the script is made for general use, some slight differences are possible for real time 'PnL' or 'ROI'. Always do a test before you start trading with larger amounts. The script is recommended for intra day trading and above. The script is not recommended for scalping on the 1min chart
💎 PROCESS TO ADD SCRIPT TO CHART
Possible trade on break example trade
As this script is invite-only, to add it to the chart you need to click on Indicators and find it under the 'Invite-Only' section. When you add the script to the chart (as it is interactive), you will be asked to do 4 steps.
🔸 'SET TRADE TIME'
Click on the chart where the last vertical bar is.
If you are already in the trade, then find the bar|time where the trade started
(you want to follow trade or trade presentation)
🔸 1) 'SET ENTRY'
Click on the horizontal level where you want to place the Entry
🔸 2) 'SET STOP'
Click on the horizontal level where you want to set the Stop
🔸 3) 'SET TARGET
Click on the horizontal level where you want to place the Target
💎 CONFIRM INPUTS
After you have done those 4 steps, a popup will appear with the relevant inputs for the trade.
You will see that some inputs are already filled (done in those 4 steps before, Entry, Stop and Target). You can correct them if you want (you will sometimes notice a longer 'space decimal' for the trade ticker, but this will not affect the calculator or other parts of the script). You can do the rest of the inputs for trade or finish it later when the script is loaded on the chart (it is recommended to fill in 'Trade Type' and 'Amount'. Don't forget to click on the "Apply" button to load the script on the chart.
💎 INDICATOR LOADED ON CHART
• When the indicator is loaded on the chart (regardless of whether it is a new trade or a trade that has already started), the following items are displayed by default:
🔸 ' Trade Table ' shows all relevant information for the trade
🔸 ' Trade Box ' with lines for Entry, Stop and Target (Take Profits if enabled)
🔸 ' Trade Box Labels ' with relevant data
• The Entry label is also the trade status label, and if the trade is not active, by default it is the Entry color
If the trade is active or when a new trade reached Entry, several new things are noticeable:
• Entry|Status label as well as status row in table will change color as well as 'Entry Reached' text
• Several extra columns relative to trade will be added to the Entry|Status label
• 3 new columns will also appear on the Trade Table (Live PnL, Live min PnL and Live ROI)
• If Trail Stop is enabled, the label will change the text to T.Stop and change color depending on whether it is in loss or profit.
• If Trail Stop is enabled, inside Trade Box trail line it will follow price action inside the box, while the label will always be fixed at the initial level
• A vertical colored line will appear on the right side of the Trade Box (depending on whether the trade is in profit or loss) which shows as in the Trade Table like Live PnL
⚪ SETTINGS
💎 Trade Account Setup
🔸 ‘Trade Type’
• 'Account Capital' or portfolio (with combination '% Capital Risk')
• 'Investment' (how much you want to invest in the trade)
• 'Risk To Lose' (how much you want to risk losing)
• 'Position Size' (exact position size, units|share for trade)
🔸 ‘Account Type’
• If the account is in another currency or you want to see possible profit | loss in local currency
• Around 150 world and local currencies supported by ICE exchange
🔸 ‘Amount’
• Amount for ‘Trade Type’
🔸 ‘% Capital Risk’
• Only for ‘Account Capital’ trade type
(i.e. 10.000 account capital with ‘% Capital Risk’ 4 is 10.000 x 4% = maximum loss 400)
🔸 ‘Leverage’
• Enable|Disable for margin trade i size of leverage (maximum 125x)
(be sure to study how and when to use margin trade through the tutorial, because margin trade can be very dangerous. If you have not perfected margin trade, there is a great possibility of losing most or even all of your account capital).
💎 TRADE ENTRY & TARGET & STOP & T.STOP & DATE | TIME
🔸 ‘Trade Date & Time’
🔸 ‘Entry’
🔸 ‘Stop’
🔸 ‘Target’
• (all was set in the previous step but can be correct/adjusted if needed)
🔸 ‘Market Entry’
• Enabled will move Entry on that bar close
🔸 ‘Liquidation’ (enabled by default)
• Show ‘Warning’ if trade Stop is close or invalid (trade will hit liquidation before reached Stop level)
🔸 ‘Trailing Type’ (4 trailing stop type)
• ‘Disabled’ (Stop will stay the entire time at the initial stop level)
• ‘Continuous’ (I.Stop follow price by distance or percent when price reached Trail start level)
• ‘Stepped’ (I.Stop moves to previous level when price reached Trail start level)
• ‘Breakeven’ (I.Stop moves to Entry when price reached Trail start level)*
* (least one Take Profit enabled)
🔸 ‘Trailing Active’ (Entry, TP1, TP2 and TP3)
• Trailing stop starts level if ‘Trailing Type’ is enabled
🔸 ‘Trailing by’ (distance or percent)
• ‘Distance’ (T.Stop will follow price action by distance)
• ‘Percent’ (T.Stop will follow price action by percent)
(this is a good example to see the difference between trailing by initial distance and initial percentage)
🔸 ‘T.Stop Distance & Percent’ (initial distance and percent for table trade only)
• Useful for bot or exchange
🔸 ‘Stop, T.Stop, Target and TP’s in PIP’s’
• Distance in PIP’s
💎 TAKE PROFIT
🔸 ‘Split Target’ (enabled by default to three take profits (TP) with auto split)
🔸 ‘Number of Take Profits’ (up to three take profits)
🔸 ‘Type’ (auto or manual)
• For manual type fill all prices to preferred level. TP percent (TP1%, TP2% and TP3% ) and Target% is how much profit you want to take on a specific level.
• PLEASE NOTE sum of all enabled ‘TP’ and targets = 100 (e.g. two TP and sets TP1% to 25 and TP2% to 35, then Target% should be 40% i.e. 25 + 35 + 40 = 100)
💎 TRADE BOX & LINES
🔸 ‘Target Line’ (color for target line and trade table ‘direction’)
🔸 ‘Stop Line’ (color for initial line and trail line)
🔸 ‘Entry Line’ (color for entry line and label & table status)
🔸 ‘To Trade Time’ (‘trade box’ left vertical line)
• By default is set to trade date and time
• Unchecked will be moved to the last bar (live time)
🔸 ‘Extended Left’ (extend Entry, Stop, Target and TP’s lines to left)
• To check for possible support|resistance
🔸 ‘Size’ (Entry, Stop, Target and TP’s lines size)
🔸 ‘PnL Box Size’ (line size for vertical box lines)
🔸 ‘Offset’ (right vertical line offset from last bar)
🔸 ‘PnL Box Color’ (right vertical line and trail fill color)
• Color changes for profit & loss
🔸 ‘Box Line Color’ (box base color)
💎 LABELS
🔸 ‘Stop & Target Labels’ (enable|disable stop and target labels)
• By default is set to small (tiny, small, normal, large, huge and auto option)
• Disabled will move all information on Entry|Status label
🔸 ‘Offset’ (label offset from trade box)
🔸 ‘Target Label’ (label color for target and all enabled tp’s)
🔸 ‘Stop Label’ (label color for initial stop and enabled trailing stop)
🔸 ‘Label Text’ (color for label text)
🔸 ‘Status Label Color’ (label table entry|status color when trade is not active)
🔸 ‘PnL’ (entry|status color for profit and loss)
🔸 ‘Size’ (by default set to normal, option tiny, small, normal, large, huge and auto)
🔸 ‘Risk to Reward’ (show risk to reward on labels)
🔸 ‘Extra Info’ (by default disabled, show extra related info for trade on labels)
• Useful if Trade Table disabled
🔸 ‘Close Trade Stats’ (by default disabled, show all info when trade is closed)
• By default is white text color for close trade stats label
💎 ALERTS
🔸 ‘Failed Trade’ (alert if price reached Stop before is active, reached Entry)
• Useful if trade need adjustment but it can also be left as it is
and alert is just warning
🔸 ‘New & Update Alert’ (alert when price reached Entry or change status to enabled Take Profits)
🔸 ‘Trade Closure Alert’ (alert when trade closed, reached Stop, Target or enabled Trail Stop)
• Alert can be in modified or default preset jSon format as well as in plain text format
• Place holders for creating alerts are :
{type}, {symbol}, {exchange}, {ticker}, {base}, {quote}, {timeframe}, {price}, {direction}, {entry}, {stop}, {tstop}, {tp1}, {tp2}, {tp3}, {target}, {tstopstatus}, {status}, {result}
* {type} placeholder is set to ‘Trade Active’, ‘Trade Update’ and ‘Trade Closed’
💎 TABLE DISPLAY
🔸 ‘Trade Table’ (enable|disable trade table)
🔸 ‘Position’ (by default set to bottom right with option bottom, middle and top with left, center and right)
🔸 ‘Size’ (by default set to normal, option tiny, small, normal, large, huge and auto)
🔸 ‘Full Table’ (by default enabled, disabled show small table without some info*)
* check picture for reference
🔸 ‘Presentation’ (by default disabled, hide all info related to PnL in trade currency)
• Useful if trade shared for presentation, hidden trade fiat|currency info)
🔸 ‘Header’ (color for trade table first row)
🔸 ‘Stats’ (color for trade table statistics row)
🔸 ‘Text’ (color for trade table text)
🔸 ‘Error’ (color for all errors if is made when trade is setup)
• Color for errors is for trade table and trade labels
🔸 ‘Fiat Price’ (by default enabled, show info for second fiat*
* if trade is in crypto and ‘quoted’ currency is not stable coin, like ETHBTC, or ‘Account Type’ is set to different currency
🔸 ‘Live Fiat Price’ (if ‘quoted’ currency enabled will show live exchange conversion)
🔸 ‘All Errors’ (enabled by default, show all error if trade setup is wrong)
• When error shows on trade, disabled this to see what|where is error
• Check below for more details
🔸 ‘Tool Tip (chart)’ (enabled show all tooltip on chart)
• Check below for more details
• When you are familiar with indicator, disable popup tooltip
💎 TOOLTIP
All possible tooltips have been added for easier understanding, especially for traders who are just learning how to place a trade. (when you perfect this indicator, you can turn off the tooltip in settings, and you can also normally use the lite version of this indicator, which does not contain all these futures)
🔸 ' Settings Tooltips’
🔸 ‘Chart Tooltips’
🔸 ‘Table Tooltips’
🔴 ERRORS
When you setup trade, not only a novice in trading, but also experienced traders can make a mistake and for this reason all possible errors are included in the indicator which will be shown on the chart by changing the color of the labels as well as on the trade table and in most of the cases and error text.
If the tooltip is enabled in the settings, you can see the reason for the error as well as the solution.
Here are some examples of possible errors.
Stay safe
PLAN YOUR TRADE AND TRADE YOUR PLAN
TradeMaster ProTrading effectively requires a range of techniques, experience, and expertise. From technical analysis to market fundamentals, traders must navigate multiple factors, including market sentiment and economic conditions. However, traders often find themselves overwhelmed by market noise, making it challenging to filter out distractions and make informed decisions. To address this, we present a powerful indicator package designed to assist traders on their journey to success.
The TradeMaster indicator package encompasses a variety of trading strategies, including the SMC (Supply, Demand, and Price Action) approach, along with many other techniques. By leveraging concepts such as price action trading, support and resistance analysis, supply and demand dynamics, these indicators can empower traders to analyze entry and exit positions with precision. Unlike other forms of technical analysis that produce values or plots based on historical price data, Price Action brings you the facts straight from the source - the current price movements.
The indicator package consists of three powerful indicators that can be used individually or together to maximize trading effectiveness.
⭐ About the Pro Indicator
The Pro indicator is the cornerstone of the package, offering a comprehensive range of functions. It's strength lies in our unique structure calculation, which is based on real price action data, capturing every ticks from small intraday fluctuations to the significant high timeframe movements. The Pro Indicator reflects our personal use and deep comprehension of Smart Money Concepts. It provides streamlined tools for tracking algorithmic trends with modern visualizations, without unnecessary clutter.
In the ever-evolving trading landscape, mainstream methods and strategies can quickly become outdated as they are widely adopted. Liquidity is constantly sought after, and the best source for this is exploring and exploiting trading strategies that are widely accepted and applied. Currently, one of these strategies is the SMC (Supply, Demand, and Price Action).
It's no coincidence that our educational materials incorporate concepts such as liquidity grabs (LG) and Smart Money Traps (SMT). As the application of SMC gains popularity among retail traders, trading with this approach becomes more challenging. Therefore, the recent focus has been on reforming the SMC methodology, as it is the only method that relies on real price movements and will always work when applied correctly.
▸ What does proper application of SMC entail?
Many SMC traders associate their key areas of interest with the market structure, which is generally considered acceptable. However, depending solely on a single foundation can lead to significant deviations, which may cause notable impacts on trading results. Moreover, if the basis for the market structure calculation is inaccurate, the consequences can be even more severe. It's akin to risking money on a lottery ticket, believing it will be a winner.
Our methodology is different, and it may ensure longevity in the financial markets. The structure remains crucial, but it is not the sole foundation of everything; instead, it serves as a validation tool. Each calculation, such as order blocks (OB), Fair Value Gaps (FVG), liquidity grabs (LG), range analysis, and more, is independent and unique, separate from the structure. However, validation must ultimately come from the structure itself.
We employ individual and high-quality filters: before a function calculation is validated by the structure, it must undergo rigorous testing based on its own set of validation conditions. This approach aims to enhance robustness and accuracy, providing traders with a reliable framework for making informed trading decisions.
▸ An example for structure validation: Order Block with "Swing Sensitivity"
These order blocks will only be displayed and utilized by the script if there is a swing structure validation with a valid break. In other words, the presence of a confirmed swing Change of Character (ChoCh) or Break of Structure (BoS) is essential for the Order Block to be considered valid and relevant.
This approach ensures that the order blocks are aligned with the overall market structure and are not based on isolated or unreliable price movements. Whether it's Fair Value Gaps (FVG), Liquidity Grabs (LG), Range calculations, or other functionalities, the same underlying principle holds true. The background structure calculation serves as a validation mechanism for the data and insights generated by these functions, ensuring they adhere to the specific criteria and rules established within our methodology. By incorporating this robust validation process, traders can have confidence in the reliability and accuracy of the information provided by the indicator, allowing them to make informed trading decisions based on validated data and analysis.
👉 Usage - the general approach:
Determine your trading style using the Pro Indicator and build your basic strategy. This indicator helps you understand your trading style, whether it's swing trading, scalping or another approach. By analyzing the Pro Indicator, you gain valuable information about potential market trends, entry and exit points, and overall market sentiment.
👉 Example of usage:
In the following chart, you'll notice how we've utilized the indicator to formulate a strategic trading approach. We've employed Order Blocks equipped with volume parameters to identify crucial market zones. Simultaneously, we've leveraged swing/internal market structures to gain insights into potential long and short-term market turnarounds. Lastly, we've examined trend line liquidity zones to pinpoint probable impulses and breakouts within ongoing trends.
Now we can see how the price descended to the order block with the highest volume, which we had previously marked as our point of interest for an entry. As the price closed below the median Order Block, we noted its mitigation. After an internal CHoCH, it's directing us towards the main Order Block as a target.
👉 Smart Money Concepts Functions
Market Structure: identifies and marks key structural changes in the market, in order to visually highlight shifts in market trends and patterns. This feature is designed to alert you of significant changes in the market's behavior, signaling a potential shift from accumulation to distribution phase, or vice versa. It helps traders adapt their strategies based on evolving market dynamics.
Order Blocks: pinpoints crucial zones where large institutional investors ("smart money") have shown strong buying or selling interest recently. Order blocks can serve as a tool for identifying key levels for potential trade entries or exits.
FVGs (Fair Value Gaps): detects discrepancies between the perceived market value and actual market price, revealing potential areas for price correction. With its mitigation settings, you can fine-tune the FVG detection according to the magnitude of value misalignment you consider significant.
Liquidity Grabs: helps track "smart money" footprints by identifying levels where large institutional traders may have induced liquidity traps. Understanding these traps can aid in avoiding false market moves and optimizing trade entries.
Automatic Fibonacci Tool: Simplifying the task of identifying key Fibonacci retracement and extension levels, this tool ties Fibonacci levels to the structure for you. It aids in recognizing significant support and resistance levels, providing a clearer understanding of potential price movements.
The Smart Money Concepts trading strategy - combined with these dynamic features - becomes a powerful analytical asset for any trader, providing in-depth insights into market dynamics, trends, and potential opportunities.
👉 Algorithmic trend and dynamic support and resistance
Trend Rainbow: This proprietary feature uses our unique TRMA** method to define short-term, medium-term, and long-term market trends. It incorporates state-of-the-art visualization techniques to render the trend information in an intuitive, easily interpretable manner. It's a 21st-century tool designed for the modern trader who values both precision and simplicity.
Multi-Timeframe Moving Averages: This feature allows traders to simultaneously monitor moving averages across multiple timeframes, providing a comprehensive perspective on market trends. It helps identify dynamic support and resistance zones, key levels where price movements are likely to slow down or reverse. This function not only aids in planning potential trade entries and exits, but also calculates the precise percentage distance to these levels. Can be as well crucial for risk management, enabling traders to set stop losses and profit targets based on solid, data-driven analysis. The Multi-Timeframe Moving Averages function is a versatile tool that combines strategic planning and risk control into a single, easy-to-use feature.
👉 Unlock the Hidden Market Dynamics
Market Sessions: This feature - by default - provides a clear representation of the four major global trading sessions. Each session is distinctly marked on your trading chart, helping you visualize the specific time periods when these markets are most active. Recognizing these sessions is critical for understanding market dynamics, as the opening and closing of major markets can lead to significant price movements. Whether you're a day trader looking to exploit intra-day volatility or a long-term investor wanting to understand broader market trends, the Market Sessions feature can be a useful tool in your trading toolkit.
Divergence Functions: allow the use of unique indicators along with our proprietary ones to detect potential price reversals. As each asset has a different market maker, divergences can vary greatly across different charts and timeframes. With our Divergence Ranking Table, you can quickly determine which divergences have the highest success rates and which are the least successful on a given chart. This feature allows you to adapt your strategies to the most effective signals, enhancing your trading decisions and boosting your potential profits.
Volume Profile with delta: This feature may give traders an edge by providing an in-depth view of market activity. It illustrates the amount of trading volume at different price levels, combined with the 'delta', which is the difference between buying and selling volume. This information allows you to see areas of high trading activity and understand whether the volume is pushing the price up or down. This real-time insight into the market's supply and demand can be instrumental in identifying key support and resistance levels, predicting potential reversals, and recognizing where the market is likely to move. Similarly to Fibonacci tool, Volume Profile can be tied to the current market structure.
👉 Improve Trading Decisions
Range: This innovative feature assists traders in determining discount, premium, and equilibrium zones. It provides a unique way of visualizing price areas where a security could be overbought or oversold (premium or discount zones), and where the price is expected to be fair and balanced (equilibrium zone). Distance from current price is displayed in percentage terms, which can assist traders with crucial data for risk management and strategic planning. The Range function helps you identify the most favorable price zones for entries and set your stop-loss and take-profit levels more accurately.
Previous OHLC: This functionality offers the capability to display the previous Open, High, Low, Close values. It is primarily set on the daily timeframe and serves as an important reference for traders. Having an overview of these key levels from the previous day gives you a solid foundation on which to base today's trading decisions. Recognizing these levels can help you predict potential turning points in the market, providing an advantage in your trading strategy.
Smart Money Zones: our secret weapon for swing traders. Similarly to order blocks, these zones can accurately identify crucial areas of strong buying or selling interest by large institutional investors. However while Order Blocks focus on recent price action, Smart Money Zones take the whole chart into consideration, resulting in more established support and demand zones.
The summary graph combines six unique indicators (Momentum, Trend Strength, Volume, Volatility, Asset Strength, and Sentiment) along with Structure and Sessions. These indicators use our TRMA** method to provide a comprehensive overview of market dynamics. By consolidating these indicators into a single graph, traders can gain valuable insights into the overall market landscape.
** TRMA (Trend Rainbow Moving Averages) is a complex but customizable moving average matrix calculation that is designed to measure market trend direction, strength and shifting.
⭐ Conclusion
We hold the view that the true path to success is the synergy between the trader and the tool, contrary to the common belief that the tool itself is the sole determinant of profitability. The actual scenario is more nuanced than such an oversimplification. Our aim is to offer useful features that meet the needs of the 21st century and that we actually use.
🛑 Risk Notice:
Everything provided by trademasterindicator – from scripts, tools, and articles to educational materials – is intended solely for educational and informational purposes. Past performance does not assure future returns.
Stocashi + CaffeineCrush Momentum Indicator by CoffeeShopCryptoThis is just a fun script to give a different representation to the ever popular Stochastic RSI
Even for me over the years the stochastic has been a difficult one to use in trading merely because of its choppy look.
Since Heikin-Ashi Candles do such a powerful job in smoothing out the look of choppy markets,
I decided to test it out on the look of the Stochastic RSI.
From an initial visual standpoint it worked out WAY better than I thought but it seemed to need something more.
I decided to use the PineScript "Color.From_Gradient" feature to give the Stochastic a more 3 dimensional look, which really brought the "old-school" indicator to life.
Description:
The CaffeineCrush Momentum Indicator is your ultimate trading companion, blending the invigorating world of coffee with the excitement of market momentum. Just like a finely brewed cup of joe,
This indicator provides you with a powerful insight into market dynamics, helping you stay in the trading groove.
As you sip on this caffeinated delight, CaffeineCrush monitors the velocity and strength of price movements,
measuring the momentum of the market. But here's where it gets even more enticing – it goes a step further by incorporating a pressure indication, adding a stimulating twist to your trading experience.
Imagine yourself in a bustling coffee shop, surrounded by the aroma of freshly roasted beans and the energetic buzz of conversations.
CaffeineCrush mimics that atmosphere, keeping you on your toes, always aware of market forces at play.
With CaffeineCrush, you'll never miss a beat. It identifies and highlights moments of heightened momentum and increased pressure,
giving you an edge in capturing profitable opportunities. Just like a perfectly extracted espresso shot, this indicator helps you maintain your trading momentum and navigate the market with confidence.
So, grab your favorite cup of joe, fire up your trading charts, and let CaffeineCrush awaken your trading prowess.
Stay in the groove, embrace the buzz, and master the momentum with this flavorful indicator by your side.
Divergence -
Regular Divergence shows when there is a conflict between the strength of the trend and the swing of the price movement.
Hidden Divergence -
Are to be traded using the same methods as hidden divergences of the MACD or the RSI. A hidden divergence is commonly a trend CONTINUATION move.
Pink Pause -
This shows a ranging area where price is taking a pause. It can be a single candle or a string of candles. But histogram with continue with its RED / GREEN colors once the pause is over.
Stocashi + CaffeineCrush is not an entry / exit indicator. It's designed to help you understand:
1. Weather your trend is continuing
2. When it pauses
3. Has your pullback started / ended
Its best used near area of conflict. For example:
1. If you have a breakout to the low side of support zone, and you get a BULLISH divergence, this can be viewed as a false breakout.
2. If you trading towards the opposite area of a range or key level and you get conflicting movement in the Stocashi + CaffeineCrush, then you should take ur profits and wait for the next move.
3. If you are following through with example 2 above, but get NO conflicts, you can immediately look for a secondary take profit area and split / hedge your take profits.
Moving Average With Risk:Reward**Title: A Detailed Guide to Using the Moving Average With Risk:Reward Indicator**
The dynamic world of financial markets offers a myriad of opportunities for market participants to make profitable trades. However, to unlock these opportunities, traders require reliable tools to guide their decisions, tools such as technical indicators. One such indicator is the 'Moving Average With Risk:Reward' Indicator, a versatile tool that combines the simple moving average (SMA), exponential moving average (EMA), Average True Range (ATR) indicator, and automated entry, stop-loss, and take-profit markers to provide a comprehensive analysis of market trends. This article aims to detail the use and interpretation of this indicator.
**Understanding the Building Blocks**
1. **Moving Averages (SMA & EMA):**
Moving averages are arguably some of the most common tools used by traders worldwide. They help smooth out price data to form a trend following indicator. Our custom indicator utilizes both a 21-period SMA, which averages the closing prices of the past 21 periods, and a 9-period EMA, which gives more weight to recent prices. The difference in sensitivity between these two moving averages forms the basis of our trade signals.
2. **Average True Range (ATR):**
The ATR is an essential component of our indicator. It measures market volatility by decomposing the entire range of an asset price for that period. It plays a critical role in determining the stop loss and take profit levels in our indicator, as detailed later.
**How the Indicator Works**
Our custom indicator works by generating buy or sell signals based on crossover and crossunder events between the SMA and EMA. A crossover occurs when the EMA (more sensitive to recent prices) crosses above the SMA, indicating upward momentum and hence triggering a buy signal. Conversely, a crossunder, where the EMA moves below the SMA, indicates increasing downward momentum and generates a sell signal.
Upon the generation of a signal, the indicator draws lines on the chart to represent the entry point, stop loss, and take profit levels. The user has the freedom to adjust the color of these lines for visual clarity. The script will also delete previous lines whenever a new signal is generated to avoid clutter and confusion.
**Determining the Stop Loss and Take Profit Levels**
Our custom indicator uses the ATR and a predetermined multiplier to calculate stop loss and take profit levels, thus incorporating market volatility into these critical decisions. The user can input their preferred multiplier for both stop loss and take profit.
Stop Loss (SL): SL is set at a level that is the ATR value multiplied by the stop-loss multiplier subtracted from (for a long position) or added to (for a short position) the closing price.
Take Profit (TP): Conversely, TP is set at a level that is the ATR value multiplied by the take-profit multiplier added to (for a long position) or subtracted from (for a short position) the closing price.
These SL and TP levels get plotted as horizontal lines on the chart, extending to the right. Labels are also placed to easily identify these levels.
**Making the Most of the Indicator**
A significant advantage of this indicator lies in its simplicity and clarity. Traders can clearly see the entry point, stop loss, and take profit levels on the chart. They can modify these levels based on their risk tolerance or trading strategy.
The combination of SMA and EMA offers the best of both worlds, with SMA providing a lagging, stable trend indication and EMA offering a more responsive indication to recent price changes. The indicator's use of ATR for SL and TP settings also ensures that these levels adapt to changing market volatility.
It is essential to remember that while this indicator can be an invaluable tool in a trader's arsenal, it is not infallible. Markets can often behave unpredictably, and even the most robust and reliable indicators can occasionally generate false signals. Therefore, traders should always employ sound money management strategies and use this indicator in conjunction with other technical analysis tools and fundamental analysis to confirm signals and make informed trading decisions.
In conclusion, the Moving Average With Risk:Reward indicator provides a comprehensive and versatile tool that can significantly enhance trading strategies. Its integration of trend-following moving averages, volatility-adjusted stop loss and take profit levels, and clear chart visualizations make it a potent tool in the financial markets. By fully understanding how to interpret and utilize this indicator, traders can navigate the markets with increased confidence and precision.
ProfitAlgoOverview
ProfitAlgo is a powerful and intuitive trading tool specifically developed to cater to the requirements of both beginners and experienced traders. It is designed to function in every timeframe and on all cryptocurrencies, stocks, indices, forex, futures, currencies, ETF's, energy and commodities. This innovative tool provides real-time signals, comprehensive trend analysis, and advanced risk management features, making it an indispensable asset for traders of all levels. This cutting-edge tool generates 'BUY' and 'SELL' signals, complemented by an array of robust analytical tools. Empower your trading analysis with this all-in-one solution and add to your arsenal of indicators to make well-informed decisions.
This algorithm incorporates a sophisticated Fourier smoothing technique to effectively filter price data, reduce noise and reveal underlying patterns and trends. By utilizing multiple price series data and incorporating Price Volume Trend, it leverages volume analysis and price movement patterns. Furthermore, the algorithm employs relative and simple moving average calculations to enhance signal clarity and filter out outliers, resulting in a more refined and robust indicator.
Features
Buy/Sell signals: Visually illustrated by 'BUY' and 'SELL' labels, these signals provide indications to traders about optimal times to enter or exit positions in the market based on the particular asset they are trading. Traders may want to enter long positions when buy signals appear, and enter short positions when 'SELL' signals appear.
Stop Loss/Take Profit Levels: Stop loss and take profit levels are predefined price thresholds that allow traders to automatically exit trades to limit losses or secure profits, respectively. Stop loss and take profit levels are visually depicted through three dotted lines on the trading chart, including the entry price, take profit (TP), and stop loss (SL). Additionally, a table displays the corresponding price entries for all three levels, providing a comprehensive overview of the trade. Traders can effectively manage their risk and optimize their trading by implementing predefined threshold settings and establishing take profit levels, thus safeguarding their profits using a strategic approach.
Support and Resistance Levels: Support and resistance levels are key price levels in the market that act as barriers or turning points for the price movement of an asset. Traders utilize these levels to identify potential areas of buying and selling opportunities. These can be depicted as red (resistance) and green (support) horizontal lines. These levels can serve as valuable complements to stop/loss and take profit levels, providing confirmation for profit-taking opportunities and facilitating effective risk management. Moreover, they can synergistically work alongside the price lines to identify potential reversal zones by visualizing market highs/lows in conjunction with areas of supply & demand.
Moving Average Bands: Moving average bands, plotted alongside the price data, dynamically change color based on the prevailing trend, with red indicating a downtrend and green representing an uptrend. This visual tool provides valuable insights to users, allowing them to quickly identify and interpret market trends. Integrating Moving Average bands with our buy/sell signals offers added confidence in identifying market trends, enabling traders to seek validation and enhance their decision-making process.
Trend Table: The trend table provides real-time information on the current trend of an asset, displaying three distinct outputs: "Uptrend," "Downtrend," and "Ranging Trend." This valuable tool enables users to assess the live trend of an asset, which may differ from the buy/sell signals. The primary objective of this feature is to analyze real-time trends in both ranging and trending market conditions. While the current signal may indicate a 'BUY' signal, the table can present an alternative output, providing valuable insights for traders and investors.
Price Lines: Price lines are depicted as two parallel grey lines running alongside the price data, representing the highs and lows of the market. This visual tool is utilized to identify patterns of higher highs and lower lows, enabling traders to gain insights into the overall trend and potential reversals in the market. When used in conjunction with our signals, MA bands and trend table, it may reinforce your interpretation of the underlying trend as well as provide insights into the trend strength.
*Note: These features are customizable via the settings menu in TradingView.
Calculations
How are buy/sell signals calculated?
The buy and sell signals are generated through a comprehensive calculation process that encompasses various types of analysis techniques. With permission from the author, wbburgin's Fourier transform is utilized to filter and extract relevant information from the price data, removing noise from the signals (filter is only applied in this feature). The buy and sell conditions are calculated based on a combination of volume-based analysis, and price movement patterns, employed to assess the direction and strength of market trends. The combination aims to produce a comprehensive view of both volume-based and price-based market dynamics. By integrating these analysis techniques, traders can gain insights into the relationship between volume, price, and market trends. This combined approach, as well as Fourier smoothing, can help identify potential market reversals, confirm trend strength, produce less noisy data and provide additional confirmation signals for trading decisions. By considering the insights provided by this analysis, the algorithm determines the appropriate actions, signaling the opportunities to enter or exit positions in the market. In summary, these calculations aim to identify favorable trading opportunities by considering factors such as trend strength, volume dynamics, and price patterns, ultimately assisting traders in making well-informed decisions in the market.
How are stop/loss and take/profit levels calculated?
The stop loss and take profit levels are calculated using a combination of technical factors, including the Average True Range (ATR) and Exponential Moving Average (EMA). The rationale for this combination is to enable dynamic risk management and align profit targets with the prevailing market conditions; ATR provides a measure of volatility and risk, while EMA helps identify the underlying trend, allowing for effective stop-loss and take-profit placement. These indicators are utilized to gauge market volatility and determine suitable levels for managing risk and securing potential profits. By incorporating ATR and EMA calculations, the algorithm generates dynamic stop loss and take profit levels that adapt to market conditions.
Calculating support and resistance levels
These levels help identify areas where the price tends to find support (support levels) or encounter resistance (resistance levels). This script utilizes pivot point calculations to determine these significant price levels, which can assist traders in trading decisions regarding potential price reversals, trend continuations, and entry/exit points in their strategies.
What are the moving average bands based on?
The moving average bands, based on VWMA (Volume Weighted Moving Average) calculations using OHLC4 price data, are visualized as unique bands on the chart. VWMA bands are chosen to find trends because they effectively combine volume-weighted calculations with moving averages, providing valuable insights into the strength and direction of price movements. These bands dynamically change color to reflect the prevailing trend. In an uptrend, the bands are represented by a green color, while in a downtrend, they appear in red. The VWMA bands utilize a unique counting method to capture trend movements and potential reversals.
How is the Trend Table calculated?
The underlying trends in the trend table are calculated based on counting methods applied to the VWMA bands. It utilizes specific thresholds to determine different trends, such as "Up Trend," "Down Trend," and "Ranging Trend." These thresholds are used to assess the current trend of the asset and provide valuable insights for traders.
Price Lines Calculation
The price lines are calculated based on the price data. They represent the range of prices, with one line plotted above the closing price and another line plotted below it. The space between these lines is filled to visualize the price volatility. Traders can utilize these lines to identify significant price levels and observe the overall price movement.
Disclaimer:
The information provided in my indicators/strategies/systems is not intended as financial advice. I assume no responsibility for any losses or damages, including loss of profits, resulting from the use of or reliance on such information.
All investments carry risks, and past performance of a security, industry, sector, market, financial product, trading strategy, backtest, or individual's trading does not guarantee future results or returns. Investors bear full responsibility for their investment decisions, which should be based on their own evaluation of financial circumstances, investment objectives, risk tolerance, and liquidity requirements.
Please note that my indicators/strategies/systems are solely for educational purposes! DO NOT request access in the comment's section.
Rainbow IndicatorName of the indicator: Rainbow indicator
A brief description of the indicator:
Using this indicator, you can see the "margin of safety" for opening a position in shares of fundamentally strong companies with an acceptable P/E level, as well as the price range for closing a position.
The background to the creation of the indicator:
I got the idea to create this indicator thanks to the concept of the "margin of safety", which was invented by the father of value investing - Benjamin Graham. According to his idea, it is reasonable to buy shares of a company only when the price offered by the market is lower than the "intrinsic value" calculated on the basis of financial statements. The value of this difference is the "margin of safety”. At the same time, the indicator does not copy Graham's idea but develops it relying on my own methodology.
So, according to Graham, the "margin of safety" is a good discount to the intrinsic value of the company. That is, if a company's stock is trading at prices that are well below the company's intrinsic value (on a per-share basis), it's a good opportunity to consider buying it. In this case, you will have a certain margin of safety in case the company is in financial distress and its stock price goes down. Accordingly, the greater the discount, the better.
When it comes to the intrinsic value of a company, there are many approaches to determining it - from calculating the Price-to-book value financial ratio to the discounted cash flow method. As for my approach, I am not trying to find the cherished intrinsic value, but I am trying to understand how fundamentally strong the company is in front of me, and in how many years the investment in it will pay off. To determine fundamental strength, I use the appropriate Fundamental Strength Indicator . To estimate the payback period, I use the P/E ratio (*). If I am satisfied with both of these indicators, I move on to the Rainbow Indicator.
(*) If you want to learn more about the P/E ratio, I suggest reading my two articles on TradingView:
Price / Earnings: Interpretation #1
Price/Earnings: amazing interpretation #2
Indicator calculation methodology:
The Rainbow indicator starts with a simple moving average of one year (this is the thick red line in the center). Hereinafter a year will mean the last 252 trading days.
Applying a moving average of this length - is a good way to smooth out sharp price fluctuations which can happen during a year as much as possible, keeping the trend direction as much as possible. Thus, the moving average becomes for me the center of fluctuations of the imaginary pendulum of the market price.
Then the deviations are calculated from the center of fluctuations. To do this, a certain amount of earnings per share is subtracted from and added to the moving average. This is the diluted EPS of the last year.
Deviations with a "-" sign form the Lower Rainbow of four colors:
- The blue spectrum of the lower rainbow begins with a deflection of -4 EPS and ends with a deflection of -8 EPS.
- Green spectrum of the lower rainbow begins with a deflection of -8 EPS and ends with a deflection of -16 EPS.
- The orange spectrum of the lower rainbow begins with a deflection of -16 EPS and ends with a deflection of -32 EPS.
- Red spectrum of the lower rainbow begins with a deflection of -32 EPS and goes to infinity.
The Lower Rainbow is used to determine the price ranges that can be considered for buying stocks. It is in the spectra of the Lower Rainbow that the very "margin of safety" according to my methodology is located. The Lower Rainbow has the boundaries between the spectra as a solid line . And only the red spectrum of the Lower Rainbow has only one boundary.
Deviations with a "+" sign form the Upper Rainbow of four similar colors:
- The red spectrum of the upper rainbow begins with a deflection of 0 EPS and ends with a deflection of +4 EPS.
- The orange spectrum of the upper rainbow begins with a deflection of +4 EPS and ends with a deflection of +8 EPS.
- Green spectrum top rainbow begins with a deflection of +8 EPS and ends with a deflection of +16 EPS.
- The blue spectrum of the upper rainbow begins with a deflection of +16 EPS and goes to infinity.
The Upper Rainbow is used to determine the price ranges that can be considered for selling stocks already purchased. The top rainbow has boundaries between the spectra in the form of crosses . And only the blue spectrum of the upper rainbow has only one boundary.
The presence of the Empty Area (the size of 4 EPS) above the Lower Rainbow creates some asymmetry between the two rainbows - the Lower Rainbow looks wider than the Upper Rainbow. This asymmetry is deliberate because the market tends to fall much faster and deeper than it grows . Therefore, a wider Lower Rainbow is conducive to buying stocks at a good discount during a period of massive "sell-offs.
The situation, when the Lower Rainbow is below the center of fluctuations (the thick red line) and the Upper Rainbow, is above the center of fluctuations is called an Obverse . It is only possible to buy a stock in an Obverse situation .
The situation when the Lower Rainbow is above the center of fluctuations and the Upper Rainbow is below the center of fluctuations is called Reverse . In this situation, the stock cannot be considered for purchase , according to my approach.
Selling a previously purchased stock is possible in both situations: Reverse and Obverse. After loading the indicator, you can see a hint next to the closing price - Reverse or Obverse now.
Due to the fact that the size of the deviation from the center of fluctuation depends on the size of the diluted EPS, several important conclusions can be made:
- The Obverse situation is characteristic of companies that show a profit over the last year.
- The Reverse situation is typical for companies that show a loss over the last year.
- An increase in the width of both rainbows in the Obverse situation tells us about an increase in profits for the company.
- A decrease in the width of both rainbows in the Obverse situation tells us about a decrease in the company's profits.
- An increase in the width of both rainbows in the Reverse situation tells us about an increase in the company's losses.
- A decrease in the width of both rainbows in the Reverse situation tells us about a decrease in the company's losses.
- The higher the profit level of the company, the greater your "margin of safety" should be. This will provide the necessary margin of safety in case you go into a cycle of declining financial results. The appropriate width of the Lower Rainbow will just create this "margin".
- Increased profits in the company (after buying its stock) will allow you to stay in position longer by widening the Upper Rainbow.
- A decrease in profits in the company (after buying its stock) will allow you to close your position more quickly by narrowing the Upper Rainbow.
Conditions for opening and closing positions:
So, the Lower Rainbow has four differently colored spectra: blue, green, orange, and red. Each one highlights the desired range of prices acceptable for buying in an Obverse situation. The blue spectrum is upper with respect to the green spectrum, and the green spectrum is lower with respect to the blue spectrum, etc.
- If the current price is in the Blue Spectrum of the Lower Rainbow, that is a reason to consider that company for buying the first portion (*) of the stock.
- If the current price has fallen below (into the Green Spectrum of the Lower Rainbow), that is a reason to consider this company to buy a second portion of the stock.
- If the current price has fallen below (into the Orange Spectrum of the Lower Rainbow), it is a reason to consider this company to buy a third portion of the stock.
- If the current price has fallen below (into the Red Spectrum of the Lower Rainbow), that is a reason to consider that company to buy a fourth portion of the stock.
(*) The logic of the Rainbow Indicator implies that no more than 4 portions of one company's stock can be purchased. One portion refers to the number of shares you can consider buying at the current price (depending on your account size and personal diversification ratio - see information below).
The Upper Rainbow also has four differently colored spectra: blue, green, orange, and red. Each of them highlights the appropriate range of prices acceptable for closing an open position.
- If the current price is in the red spectrum of the Upper Rainbow, I close one portion of an open position bought in the red spectrum of the Lower Rainbow.
- If the current price is in the orange spectrum of the Upper Rainbow, I close one portion of an open position bought in the orange spectrum of the Lower Rainbow.
- If the current price is in the green spectrum of the Upper Rainbow, I close one portion of an open position bought in the green spectrum of the Lower Rainbow.
- If the current price is in the blue spectrum of the Upper Rainbow, I close one portion of an open position bought in the blue spectrum of the Lower Rainbow.
This position-closing logic applies to both the Obverse and Reverse situations. In both cases, the position is closed in portions in four steps. However, there are 3 exceptions to this rule when it is possible to close an entire position in whole rather than in parts:
- If there is a Reverse situation and the current price is above the thick red line.
- If I decide to invest in another company and I do not have enough available cash to purchase the necessary number of portions.
- If I find out about events that pose a real threat to the further existence of the company (for example, a bankruptcy filing), I can close the position earlier, without waiting for the price to hit the corresponding Upper Rainbow spectrum.
So, the basic scenario of opening and closing a position assumes the gradual purchase of shares in 4 stages and their gradual sale in 4 stages. However, there is a situation where one of the stages is skipped in the case of buying shares and in the case of selling them. For example, because the Fundamental Strength Indicator and the P/E ratio became acceptable for me only at a certain stage (spectrum) or the moment was missed for a transaction due to technical reasons. In such cases, I buy or sell more than one portion of a stock in the spectrum I am in. The number of additional portions will depend on the number of missed spectra. For example, if I have no position in the stock of the company in question, all conditions for buying the stock have been met, and the current price is in the orange spectrum of the Lower Rainbow, I can buy three portions of the stock at once (for the blue, green, and orange spectrum). I will sell these three portions in the corresponding Upper Rainbow spectra (orange, green, and blue). However, if for some reason the orange spectrum of the Upper Rainbow was missed, and the current price is in the green spectrum - I will sell two portions of the three (in the green spectrum). I will sell the last, third portion only when the price reaches the blue spectrum of the Upper Rainbow.
The Rainbow Indicator also helps calculate the number of shares that can be considered for purchase at the current price position in the Lower Rainbow spectra. To do this, you need to go to the indicator settings.
+ Cash in - Cash out +/- Closed profit/loss + Dividends - Fees - Taxes
Here I indicate the amount of funds deposited to my account, withdrawn from it, profit/loss on closed positions, dividends credited to the account, and taxes deducted from the account.
Diversification coefficient
The diversification coefficient determines how diversified I want my portfolio to be. For example, a diversification coefficient of 20 means that I plan to buy 20 share portions of different companies, but no more than 4 portions per company (based on the number of Lower Rainbow spectra).
The cost of purchased shares of this company (fees excluded)
Here I specify the amount of already purchased shares of the company in question in the currency of my portfolio. For example, if at this point in time, I have purchased 1000 shares at $300 per share, and my portfolio is expressed in $, I enter - $300,000.
The cost of all purchased shares in the portfolio (fees excluded)
Here I enter the amount of all purchased shares for all companies in the currency of my portfolio (without commissions spent on the purchase). This is necessary to determine the amount of available funds available to purchase shares.
After entering all the necessary data, I go to the checkbox, by checking it I confirm that the company in question has been studied with the Fundamental Strength Indicator and the P/E ratio, and their values are satisfactory to me. No calculation is performed without the checkbox checked. This is done intentionally because the application of the Rainbow Indicator for stock acquisition purposes is possible only after studying the Fundamental Strength of the company and an acceptable P/E value.
Next, I click "Ok" and get the calculation in the form of a table on the left.
Free cash in the portfolio
This is the amount of free cash available to purchase stocks. Please note that the price of the stock and the funds in your portfolio must be denominated in the same currency. On TradingView, you can choose which currency to display the stock price in.
Cash amount for one portion
The amount of cash needed to buy one portion of a stock. Depends on the diversification ratio entered.
Potential portions amount
Number of portions, available for purchase at the current price. Can be a fractional number.
Cash amount to buy
The amount of cash needed to buy portions available for purchase at the current price.
Shares amount to buy
Number of shares in portions available for purchase at the current price.
The table also contains additional information in the form of the current value of the company's market capitalization and P/E ratio.
Mandatory requirements for using the indicator:
- works only on a daily timeframe;
- the indicator is only applicable to shares of public companies;
- quarterly income statements for the last year are required;
- an acceptable for you P/E ratio is required to consider the company's stock for purchase;
- the Rainbow Indicator only applies in tandem with the Fundamental Strength Indicator. To consider a company's stock for purchase, you need confirmation that the company is fundamentally strong.
What is the value of the Rainbow Indicator?
- clearly demonstrates a company's profit and loss dynamics;
- shows the price ranges that can be used to open and close a position;
- takes into account the principle of gradual increase and decrease of a position;
- allows calculating the number of shares to be purchased;
- shows the current value of the P/E ratio;
- shows the current capitalization of the company.
Example:
As an example, consider the situation with NVIDIA Corporation stock (ticker - NVDA).
September 02, 2022:
Fundamental Strength Indicator - 11.46 (fundamentally strong company).
P/E - 39.58 (acceptable to me).
Current Price - $136.47 (is in the Orange Spectrum of the Lower Rainbow).
Situation - Obverse.
The basic conditions for buying this company's stock are met. The Rainbow Indicator settings are filled out as follows:
The table to the left of the Rainbow Indicator shows how many shares are possible to buy in the Orange Spectrum of Lower Rainbow at the current price = 10 shares. This corresponds to 2.73 portions.
To give you an example, I buy 10 shares of NVDA at $136.47 per share.
October 14, 2022:
NVDA's stock price has moved into the red spectrum of the Lower Rainbow.
The Fundamental Strength Indicator is 10.81 (fundamentally strong company).
P/E is 35.80 (an acceptable level for me).
Current Price - $112.27 (is in the Red Spectrum of the Lower Rainbow).
Situation - Obverse.
The basic conditions for buying this company's stock are still met. The Rainbow Indicator settings are populated as follows:
The table to the left of the Rainbow Indicator shows how many shares are possible to buy in the Lower Rainbow Red Spectrum at the current price (5 shares). This corresponds to 1.12 portions.
To give you an example, I buy 5 shares of NVDA at $112.27 per share. A total of 3.85 portions were purchased, which is the maximum possible number of portions at the current price level. The remainder in the form of 0.15 portions can be purchased only at a price level below $75 per share.
January 23, 2023:
The price of NVDA stock passes through the red spectrum of the Upper Rainbow and stops in the orange spectrum. As an example, I sell 5 shares bought in the red spectrum of the Lower Rainbow, for example at $180 per share (+60%). And also a third of the shares bought in the orange spectrum, 3 shares out of 10, for example at $190 a share (+39%). That leaves me with 7 shares.
January 27, 2023:
NVDA's stock price has continued to rise and has moved into the green spectrum of the Upper Rainbow. This is a reason to close some of the remaining 7 shares. I divide the 7 shares by 2 and round up to a whole number - that's 4 shares. For my example, I sell 4 shares at $199 a share (+46%). Now I am left with 3 shares of stock.
February 02, 2023:
The price of NVDA stock moves into the blue spectrum of the Upper Rainbow, and I close the remaining 3 shares, for example, at $216 per share (+58%). The entire position in NVDA stock is closed.
As you can see, the Fundamental Strength Indicator and the P/E ratio were not used in the process of closing the position. Decisions were made only on the basis of the Rainbow Indicator.
As another example, let's look at the situation with the shares of Papa Johns International, Inc. (ticker PZZA).
November 01, 2017:
Fundamental Strength Indicator - 13.22 points (fundamentally strong company).
P/E - 21.64 (acceptable to me).
Current Price - $62.26 (is in the blue spectrum of the Lower Rainbow).
Situation - Obverse.
The basic conditions for buying shares of this company are met. The settings of the Rainbow Indicator are filled as follows:
The table to the left of the Rainbow Indicator shows how many shares are possible to buy in the Lower Rainbow Blue Spectrum at the current price - 8 shares. This corresponds to 1 portion.
To give you an example, I buy 8 shares of PZZA at a price of $62.26.
August 8, 2018:
PZZA's share price has moved into the green spectrum of the Lower Rainbow.
The Fundamental Strength Indicator is a 9.83 (fundamentally strong company).
P/E is 16.07 (an acceptable level for me).
Current Price - $38.94 (is in the green spectrum of the Lower Rainbow).
Situation - Obverse.
The basic conditions for buying shares of this company are still met. The Rainbow Indicator settings are populated as follows:
The table to the left of the Rainbow Indicator shows how many shares are possible to buy in the Lower Rainbow Green Spectrum at the current price - 12 shares. This corresponds to 0.93 portions.
To give you an example, I buy 12 shares of PZZA at a price of $38.94. A total of 1.93 portions were purchased.
October 31, 2018:
PZZA's stock price moves into the Upper Rainbow red spectrum and is $54.54 per share. Since I did not have any portions purchased in the Lower Rainbow red spectrum, there is no closing part of the position.
February 01, 2019:
After a significant decline, PZZA's stock price moves into the orange spectrum of the Lower Rainbow at $38.51 per share. However, I am not taking any action because the company's Fundamental Strength on this day is 5.02 (a fundamentally mediocre company).
March 27, 2019:
PZZA's stock price passes the green and blue spectrum of the Upper Rainbow. This allowed to close the previously purchased 12 shares, for example, at $50 a share (+28%) and 8 shares at $50.38 a share (-19%).
Closing the entire position at once was facilitated by a significant narrowing in both rainbows. As we now know, this indicates a decline in earnings at the company.
Risk disclaimer:
When working with the Rainbow Indicator, keep in mind that the release of the Income statement (from which diluted EPS is derived) occurs some time after the end of the fiscal quarter. This means that the new relevant data for the calculation will only appear after the publication of the new statement. In this regard, there may be a significant change in the Rainbow Indicator after the publication of the new statement. The magnitude of this change will depend on both the content of the new statement and the number of days between the end of the financial quarter and the publication date of the statement. Prior to the publication date of the new statement, the latest actual data will be used for the calculations. Also, once again, please note that the Rainbow Indicator can only be used in tandem with the Fundamental Strength Indicator and the P/E ratio. Without these additional filters, the Rainbow Indicator loses its intended meaning.
The Rainbow Indicator allows you to determine the price ranges for opening and closing a position gradually, based on available data and the methodology I created. You can also use it to calculate the number of shares you can consider buying taking into account the position you already have. However, this Indicator and/or its description and examples cannot be used as the sole reason for buying or selling stocks or for any other action or inaction related to stocks.
Goertzel Browser [Loxx]As the financial markets become increasingly complex and data-driven, traders and analysts must leverage powerful tools to gain insights and make informed decisions. One such tool is the Goertzel Browser indicator, a sophisticated technical analysis indicator that helps identify cyclical patterns in financial data. This powerful tool is capable of detecting cyclical patterns in financial data, helping traders to make better predictions and optimize their trading strategies. With its unique combination of mathematical algorithms and advanced charting capabilities, this indicator has the potential to revolutionize the way we approach financial modeling and trading.
█ Brief Overview of the Goertzel Browser
The Goertzel Browser is a sophisticated technical analysis tool that utilizes the Goertzel algorithm to analyze and visualize cyclical components within a financial time series. By identifying these cycles and their characteristics, the indicator aims to provide valuable insights into the market's underlying price movements, which could potentially be used for making informed trading decisions.
The primary purpose of this indicator is to:
1. Detect and analyze the dominant cycles present in the price data.
2. Reconstruct and visualize the composite wave based on the detected cycles.
3. Project the composite wave into the future, providing a potential roadmap for upcoming price movements.
To achieve this, the indicator performs several tasks:
1. Detrending the price data: The indicator preprocesses the price data using various detrending techniques, such as Hodrick-Prescott filters, zero-lag moving averages, and linear regression, to remove the underlying trend and focus on the cyclical components.
2. Applying the Goertzel algorithm: The indicator applies the Goertzel algorithm to the detrended price data, identifying the dominant cycles and their characteristics, such as amplitude, phase, and cycle strength.
3. Constructing the composite wave: The indicator reconstructs the composite wave by combining the detected cycles, either by using a user-defined list of cycles or by selecting the top N cycles based on their amplitude or cycle strength.
4. Visualizing the composite wave: The indicator plots the composite wave, using solid lines for the past and dotted lines for the future projections. The color of the lines indicates whether the wave is increasing or decreasing.
5. Displaying cycle information: The indicator provides a table that displays detailed information about the detected cycles, including their rank, period, Bartel's test results, amplitude, and phase.
This indicator is a powerful tool that employs the Goertzel algorithm to analyze and visualize the cyclical components within a financial time series. By providing insights into the underlying price movements and their potential future trajectory, the indicator aims to assist traders in making more informed decisions.
█ What is the Goertzel Algorithm?
The Goertzel algorithm, named after Gerald Goertzel, is a digital signal processing technique that is used to efficiently compute individual terms of the Discrete Fourier Transform (DFT). It was first introduced in 1958, and since then, it has found various applications in the fields of engineering, mathematics, and physics.
The Goertzel algorithm is primarily used to detect specific frequency components within a digital signal, making it particularly useful in applications where only a few frequency components are of interest. The algorithm is computationally efficient, as it requires fewer calculations than the Fast Fourier Transform (FFT) when detecting a small number of frequency components. This efficiency makes the Goertzel algorithm a popular choice in applications such as:
1. Telecommunications: The Goertzel algorithm is used for decoding Dual-Tone Multi-Frequency (DTMF) signals, which are the tones generated when pressing buttons on a telephone keypad. By identifying specific frequency components, the algorithm can accurately determine which button has been pressed.
2. Audio processing: The algorithm can be used to detect specific pitches or harmonics in an audio signal, making it useful in applications like pitch detection and tuning musical instruments.
3. Vibration analysis: In the field of mechanical engineering, the Goertzel algorithm can be applied to analyze vibrations in rotating machinery, helping to identify faulty components or signs of wear.
4. Power system analysis: The algorithm can be used to measure harmonic content in power systems, allowing engineers to assess power quality and detect potential issues.
The Goertzel algorithm is used in these applications because it offers several advantages over other methods, such as the FFT:
1. Computational efficiency: The Goertzel algorithm requires fewer calculations when detecting a small number of frequency components, making it more computationally efficient than the FFT in these cases.
2. Real-time analysis: The algorithm can be implemented in a streaming fashion, allowing for real-time analysis of signals, which is crucial in applications like telecommunications and audio processing.
3. Memory efficiency: The Goertzel algorithm requires less memory than the FFT, as it only computes the frequency components of interest.
4. Precision: The algorithm is less susceptible to numerical errors compared to the FFT, ensuring more accurate results in applications where precision is essential.
The Goertzel algorithm is an efficient digital signal processing technique that is primarily used to detect specific frequency components within a signal. Its computational efficiency, real-time capabilities, and precision make it an attractive choice for various applications, including telecommunications, audio processing, vibration analysis, and power system analysis. The algorithm has been widely adopted since its introduction in 1958 and continues to be an essential tool in the fields of engineering, mathematics, and physics.
█ Goertzel Algorithm in Quantitative Finance: In-Depth Analysis and Applications
The Goertzel algorithm, initially designed for signal processing in telecommunications, has gained significant traction in the financial industry due to its efficient frequency detection capabilities. In quantitative finance, the Goertzel algorithm has been utilized for uncovering hidden market cycles, developing data-driven trading strategies, and optimizing risk management. This section delves deeper into the applications of the Goertzel algorithm in finance, particularly within the context of quantitative trading and analysis.
Unveiling Hidden Market Cycles:
Market cycles are prevalent in financial markets and arise from various factors, such as economic conditions, investor psychology, and market participant behavior. The Goertzel algorithm's ability to detect and isolate specific frequencies in price data helps trader analysts identify hidden market cycles that may otherwise go unnoticed. By examining the amplitude, phase, and periodicity of each cycle, traders can better understand the underlying market structure and dynamics, enabling them to develop more informed and effective trading strategies.
Developing Quantitative Trading Strategies:
The Goertzel algorithm's versatility allows traders to incorporate its insights into a wide range of trading strategies. By identifying the dominant market cycles in a financial instrument's price data, traders can create data-driven strategies that capitalize on the cyclical nature of markets.
For instance, a trader may develop a mean-reversion strategy that takes advantage of the identified cycles. By establishing positions when the price deviates from the predicted cycle, the trader can profit from the subsequent reversion to the cycle's mean. Similarly, a momentum-based strategy could be designed to exploit the persistence of a dominant cycle by entering positions that align with the cycle's direction.
Enhancing Risk Management:
The Goertzel algorithm plays a vital role in risk management for quantitative strategies. By analyzing the cyclical components of a financial instrument's price data, traders can gain insights into the potential risks associated with their trading strategies.
By monitoring the amplitude and phase of dominant cycles, a trader can detect changes in market dynamics that may pose risks to their positions. For example, a sudden increase in amplitude may indicate heightened volatility, prompting the trader to adjust position sizing or employ hedging techniques to protect their portfolio. Additionally, changes in phase alignment could signal a potential shift in market sentiment, necessitating adjustments to the trading strategy.
Expanding Quantitative Toolkits:
Traders can augment the Goertzel algorithm's insights by combining it with other quantitative techniques, creating a more comprehensive and sophisticated analysis framework. For example, machine learning algorithms, such as neural networks or support vector machines, could be trained on features extracted from the Goertzel algorithm to predict future price movements more accurately.
Furthermore, the Goertzel algorithm can be integrated with other technical analysis tools, such as moving averages or oscillators, to enhance their effectiveness. By applying these tools to the identified cycles, traders can generate more robust and reliable trading signals.
The Goertzel algorithm offers invaluable benefits to quantitative finance practitioners by uncovering hidden market cycles, aiding in the development of data-driven trading strategies, and improving risk management. By leveraging the insights provided by the Goertzel algorithm and integrating it with other quantitative techniques, traders can gain a deeper understanding of market dynamics and devise more effective trading strategies.
█ Indicator Inputs
src: This is the source data for the analysis, typically the closing price of the financial instrument.
detrendornot: This input determines the method used for detrending the source data. Detrending is the process of removing the underlying trend from the data to focus on the cyclical components.
The available options are:
hpsmthdt: Detrend using Hodrick-Prescott filter centered moving average.
zlagsmthdt: Detrend using zero-lag moving average centered moving average.
logZlagRegression: Detrend using logarithmic zero-lag linear regression.
hpsmth: Detrend using Hodrick-Prescott filter.
zlagsmth: Detrend using zero-lag moving average.
DT_HPper1 and DT_HPper2: These inputs define the period range for the Hodrick-Prescott filter centered moving average when detrendornot is set to hpsmthdt.
DT_ZLper1 and DT_ZLper2: These inputs define the period range for the zero-lag moving average centered moving average when detrendornot is set to zlagsmthdt.
DT_RegZLsmoothPer: This input defines the period for the zero-lag moving average used in logarithmic zero-lag linear regression when detrendornot is set to logZlagRegression.
HPsmoothPer: This input defines the period for the Hodrick-Prescott filter when detrendornot is set to hpsmth.
ZLMAsmoothPer: This input defines the period for the zero-lag moving average when detrendornot is set to zlagsmth.
MaxPer: This input sets the maximum period for the Goertzel algorithm to search for cycles.
squaredAmp: This boolean input determines whether the amplitude should be squared in the Goertzel algorithm.
useAddition: This boolean input determines whether the Goertzel algorithm should use addition for combining the cycles.
useCosine: This boolean input determines whether the Goertzel algorithm should use cosine waves instead of sine waves.
UseCycleStrength: This boolean input determines whether the Goertzel algorithm should compute the cycle strength, which is a normalized measure of the cycle's amplitude.
WindowSizePast and WindowSizeFuture: These inputs define the window size for past and future projections of the composite wave.
FilterBartels: This boolean input determines whether Bartel's test should be applied to filter out non-significant cycles.
BartNoCycles: This input sets the number of cycles to be used in Bartel's test.
BartSmoothPer: This input sets the period for the moving average used in Bartel's test.
BartSigLimit: This input sets the significance limit for Bartel's test, below which cycles are considered insignificant.
SortBartels: This boolean input determines whether the cycles should be sorted by their Bartel's test results.
UseCycleList: This boolean input determines whether a user-defined list of cycles should be used for constructing the composite wave. If set to false, the top N cycles will be used.
Cycle1, Cycle2, Cycle3, Cycle4, and Cycle5: These inputs define the user-defined list of cycles when 'UseCycleList' is set to true. If using a user-defined list, each of these inputs represents the period of a specific cycle to include in the composite wave.
StartAtCycle: This input determines the starting index for selecting the top N cycles when UseCycleList is set to false. This allows you to skip a certain number of cycles from the top before selecting the desired number of cycles.
UseTopCycles: This input sets the number of top cycles to use for constructing the composite wave when UseCycleList is set to false. The cycles are ranked based on their amplitudes or cycle strengths, depending on the UseCycleStrength input.
SubtractNoise: This boolean input determines whether to subtract the noise (remaining cycles) from the composite wave. If set to true, the composite wave will only include the top N cycles specified by UseTopCycles.
█ Exploring Auxiliary Functions
The following functions demonstrate advanced techniques for analyzing financial markets, including zero-lag moving averages, Bartels probability, detrending, and Hodrick-Prescott filtering. This section examines each function in detail, explaining their purpose, methodology, and applications in finance. We will examine how each function contributes to the overall performance and effectiveness of the indicator and how they work together to create a powerful analytical tool.
Zero-Lag Moving Average:
The zero-lag moving average function is designed to minimize the lag typically associated with moving averages. This is achieved through a two-step weighted linear regression process that emphasizes more recent data points. The function calculates a linearly weighted moving average (LWMA) on the input data and then applies another LWMA on the result. By doing this, the function creates a moving average that closely follows the price action, reducing the lag and improving the responsiveness of the indicator.
The zero-lag moving average function is used in the indicator to provide a responsive, low-lag smoothing of the input data. This function helps reduce the noise and fluctuations in the data, making it easier to identify and analyze underlying trends and patterns. By minimizing the lag associated with traditional moving averages, this function allows the indicator to react more quickly to changes in market conditions, providing timely signals and improving the overall effectiveness of the indicator.
Bartels Probability:
The Bartels probability function calculates the probability of a given cycle being significant in a time series. It uses a mathematical test called the Bartels test to assess the significance of cycles detected in the data. The function calculates coefficients for each detected cycle and computes an average amplitude and an expected amplitude. By comparing these values, the Bartels probability is derived, indicating the likelihood of a cycle's significance. This information can help in identifying and analyzing dominant cycles in financial markets.
The Bartels probability function is incorporated into the indicator to assess the significance of detected cycles in the input data. By calculating the Bartels probability for each cycle, the indicator can prioritize the most significant cycles and focus on the market dynamics that are most relevant to the current trading environment. This function enhances the indicator's ability to identify dominant market cycles, improving its predictive power and aiding in the development of effective trading strategies.
Detrend Logarithmic Zero-Lag Regression:
The detrend logarithmic zero-lag regression function is used for detrending data while minimizing lag. It combines a zero-lag moving average with a linear regression detrending method. The function first calculates the zero-lag moving average of the logarithm of input data and then applies a linear regression to remove the trend. By detrending the data, the function isolates the cyclical components, making it easier to analyze and interpret the underlying market dynamics.
The detrend logarithmic zero-lag regression function is used in the indicator to isolate the cyclical components of the input data. By detrending the data, the function enables the indicator to focus on the cyclical movements in the market, making it easier to analyze and interpret market dynamics. This function is essential for identifying cyclical patterns and understanding the interactions between different market cycles, which can inform trading decisions and enhance overall market understanding.
Bartels Cycle Significance Test:
The Bartels cycle significance test is a function that combines the Bartels probability function and the detrend logarithmic zero-lag regression function to assess the significance of detected cycles. The function calculates the Bartels probability for each cycle and stores the results in an array. By analyzing the probability values, traders and analysts can identify the most significant cycles in the data, which can be used to develop trading strategies and improve market understanding.
The Bartels cycle significance test function is integrated into the indicator to provide a comprehensive analysis of the significance of detected cycles. By combining the Bartels probability function and the detrend logarithmic zero-lag regression function, this test evaluates the significance of each cycle and stores the results in an array. The indicator can then use this information to prioritize the most significant cycles and focus on the most relevant market dynamics. This function enhances the indicator's ability to identify and analyze dominant market cycles, providing valuable insights for trading and market analysis.
Hodrick-Prescott Filter:
The Hodrick-Prescott filter is a popular technique used to separate the trend and cyclical components of a time series. The function applies a smoothing parameter to the input data and calculates a smoothed series using a two-sided filter. This smoothed series represents the trend component, which can be subtracted from the original data to obtain the cyclical component. The Hodrick-Prescott filter is commonly used in economics and finance to analyze economic data and financial market trends.
The Hodrick-Prescott filter is incorporated into the indicator to separate the trend and cyclical components of the input data. By applying the filter to the data, the indicator can isolate the trend component, which can be used to analyze long-term market trends and inform trading decisions. Additionally, the cyclical component can be used to identify shorter-term market dynamics and provide insights into potential trading opportunities. The inclusion of the Hodrick-Prescott filter adds another layer of analysis to the indicator, making it more versatile and comprehensive.
Detrending Options: Detrend Centered Moving Average:
The detrend centered moving average function provides different detrending methods, including the Hodrick-Prescott filter and the zero-lag moving average, based on the selected detrending method. The function calculates two sets of smoothed values using the chosen method and subtracts one set from the other to obtain a detrended series. By offering multiple detrending options, this function allows traders and analysts to select the most appropriate method for their specific needs and preferences.
The detrend centered moving average function is integrated into the indicator to provide users with multiple detrending options, including the Hodrick-Prescott filter and the zero-lag moving average. By offering multiple detrending methods, the indicator allows users to customize the analysis to their specific needs and preferences, enhancing the indicator's overall utility and adaptability. This function ensures that the indicator can cater to a wide range of trading styles and objectives, making it a valuable tool for a diverse group of market participants.
The auxiliary functions functions discussed in this section demonstrate the power and versatility of mathematical techniques in analyzing financial markets. By understanding and implementing these functions, traders and analysts can gain valuable insights into market dynamics, improve their trading strategies, and make more informed decisions. The combination of zero-lag moving averages, Bartels probability, detrending methods, and the Hodrick-Prescott filter provides a comprehensive toolkit for analyzing and interpreting financial data. The integration of advanced functions in a financial indicator creates a powerful and versatile analytical tool that can provide valuable insights into financial markets. By combining the zero-lag moving average,
█ In-Depth Analysis of the Goertzel Browser Code
The Goertzel Browser code is an implementation of the Goertzel Algorithm, an efficient technique to perform spectral analysis on a signal. The code is designed to detect and analyze dominant cycles within a given financial market data set. This section will provide an extremely detailed explanation of the code, its structure, functions, and intended purpose.
Function signature and input parameters:
The Goertzel Browser function accepts numerous input parameters for customization, including source data (src), the current bar (forBar), sample size (samplesize), period (per), squared amplitude flag (squaredAmp), addition flag (useAddition), cosine flag (useCosine), cycle strength flag (UseCycleStrength), past and future window sizes (WindowSizePast, WindowSizeFuture), Bartels filter flag (FilterBartels), Bartels-related parameters (BartNoCycles, BartSmoothPer, BartSigLimit), sorting flag (SortBartels), and output buffers (goeWorkPast, goeWorkFuture, cyclebuffer, amplitudebuffer, phasebuffer, cycleBartelsBuffer).
Initializing variables and arrays:
The code initializes several float arrays (goeWork1, goeWork2, goeWork3, goeWork4) with the same length as twice the period (2 * per). These arrays store intermediate results during the execution of the algorithm.
Preprocessing input data:
The input data (src) undergoes preprocessing to remove linear trends. This step enhances the algorithm's ability to focus on cyclical components in the data. The linear trend is calculated by finding the slope between the first and last values of the input data within the sample.
Iterative calculation of Goertzel coefficients:
The core of the Goertzel Browser algorithm lies in the iterative calculation of Goertzel coefficients for each frequency bin. These coefficients represent the spectral content of the input data at different frequencies. The code iterates through the range of frequencies, calculating the Goertzel coefficients using a nested loop structure.
Cycle strength computation:
The code calculates the cycle strength based on the Goertzel coefficients. This is an optional step, controlled by the UseCycleStrength flag. The cycle strength provides information on the relative influence of each cycle on the data per bar, considering both amplitude and cycle length. The algorithm computes the cycle strength either by squaring the amplitude (controlled by squaredAmp flag) or using the actual amplitude values.
Phase calculation:
The Goertzel Browser code computes the phase of each cycle, which represents the position of the cycle within the input data. The phase is calculated using the arctangent function (math.atan) based on the ratio of the imaginary and real components of the Goertzel coefficients.
Peak detection and cycle extraction:
The algorithm performs peak detection on the computed amplitudes or cycle strengths to identify dominant cycles. It stores the detected cycles in the cyclebuffer array, along with their corresponding amplitudes and phases in the amplitudebuffer and phasebuffer arrays, respectively.
Sorting cycles by amplitude or cycle strength:
The code sorts the detected cycles based on their amplitude or cycle strength in descending order. This allows the algorithm to prioritize cycles with the most significant impact on the input data.
Bartels cycle significance test:
If the FilterBartels flag is set, the code performs a Bartels cycle significance test on the detected cycles. This test determines the statistical significance of each cycle and filters out the insignificant cycles. The significant cycles are stored in the cycleBartelsBuffer array. If the SortBartels flag is set, the code sorts the significant cycles based on their Bartels significance values.
Waveform calculation:
The Goertzel Browser code calculates the waveform of the significant cycles for both past and future time windows. The past and future windows are defined by the WindowSizePast and WindowSizeFuture parameters, respectively. The algorithm uses either cosine or sine functions (controlled by the useCosine flag) to calculate the waveforms for each cycle. The useAddition flag determines whether the waveforms should be added or subtracted.
Storing waveforms in matrices:
The calculated waveforms for each cycle are stored in two matrices - goeWorkPast and goeWorkFuture. These matrices hold the waveforms for the past and future time windows, respectively. Each row in the matrices represents a time window position, and each column corresponds to a cycle.
Returning the number of cycles:
The Goertzel Browser function returns the total number of detected cycles (number_of_cycles) after processing the input data. This information can be used to further analyze the results or to visualize the detected cycles.
The Goertzel Browser code is a comprehensive implementation of the Goertzel Algorithm, specifically designed for detecting and analyzing dominant cycles within financial market data. The code offers a high level of customization, allowing users to fine-tune the algorithm based on their specific needs. The Goertzel Browser's combination of preprocessing, iterative calculations, cycle extraction, sorting, significance testing, and waveform calculation makes it a powerful tool for understanding cyclical components in financial data.
█ Generating and Visualizing Composite Waveform
The indicator calculates and visualizes the composite waveform for both past and future time windows based on the detected cycles. Here's a detailed explanation of this process:
Updating WindowSizePast and WindowSizeFuture:
The WindowSizePast and WindowSizeFuture are updated to ensure they are at least twice the MaxPer (maximum period).
Initializing matrices and arrays:
Two matrices, goeWorkPast and goeWorkFuture, are initialized to store the Goertzel results for past and future time windows. Multiple arrays are also initialized to store cycle, amplitude, phase, and Bartels information.
Preparing the source data (srcVal) array:
The source data is copied into an array, srcVal, and detrended using one of the selected methods (hpsmthdt, zlagsmthdt, logZlagRegression, hpsmth, or zlagsmth).
Goertzel function call:
The Goertzel function is called to analyze the detrended source data and extract cycle information. The output, number_of_cycles, contains the number of detected cycles.
Initializing arrays for past and future waveforms:
Three arrays, epgoertzel, goertzel, and goertzelFuture, are initialized to store the endpoint Goertzel, non-endpoint Goertzel, and future Goertzel projections, respectively.
Calculating composite waveform for past bars (goertzel array):
The past composite waveform is calculated by summing the selected cycles (either from the user-defined cycle list or the top cycles) and optionally subtracting the noise component.
Calculating composite waveform for future bars (goertzelFuture array):
The future composite waveform is calculated in a similar way as the past composite waveform.
Drawing past composite waveform (pvlines):
The past composite waveform is drawn on the chart using solid lines. The color of the lines is determined by the direction of the waveform (green for upward, red for downward).
Drawing future composite waveform (fvlines):
The future composite waveform is drawn on the chart using dotted lines. The color of the lines is determined by the direction of the waveform (fuchsia for upward, yellow for downward).
Displaying cycle information in a table (table3):
A table is created to display the cycle information, including the rank, period, Bartel value, amplitude (or cycle strength), and phase of each detected cycle.
Filling the table with cycle information:
The indicator iterates through the detected cycles and retrieves the relevant information (period, amplitude, phase, and Bartel value) from the corresponding arrays. It then fills the table with this information, displaying the values up to six decimal places.
To summarize, this indicator generates a composite waveform based on the detected cycles in the financial data. It calculates the composite waveforms for both past and future time windows and visualizes them on the chart using colored lines. Additionally, it displays detailed cycle information in a table, including the rank, period, Bartel value, amplitude (or cycle strength), and phase of each detected cycle.
█ Enhancing the Goertzel Algorithm-Based Script for Financial Modeling and Trading
The Goertzel algorithm-based script for detecting dominant cycles in financial data is a powerful tool for financial modeling and trading. It provides valuable insights into the past behavior of these cycles and potential future impact. However, as with any algorithm, there is always room for improvement. This section discusses potential enhancements to the existing script to make it even more robust and versatile for financial modeling, general trading, advanced trading, and high-frequency finance trading.
Enhancements for Financial Modeling
Data preprocessing: One way to improve the script's performance for financial modeling is to introduce more advanced data preprocessing techniques. This could include removing outliers, handling missing data, and normalizing the data to ensure consistent and accurate results.
Additional detrending and smoothing methods: Incorporating more sophisticated detrending and smoothing techniques, such as wavelet transform or empirical mode decomposition, can help improve the script's ability to accurately identify cycles and trends in the data.
Machine learning integration: Integrating machine learning techniques, such as artificial neural networks or support vector machines, can help enhance the script's predictive capabilities, leading to more accurate financial models.
Enhancements for General and Advanced Trading
Customizable indicator integration: Allowing users to integrate their own technical indicators can help improve the script's effectiveness for both general and advanced trading. By enabling the combination of the dominant cycle information with other technical analysis tools, traders can develop more comprehensive trading strategies.
Risk management and position sizing: Incorporating risk management and position sizing functionality into the script can help traders better manage their trades and control potential losses. This can be achieved by calculating the optimal position size based on the user's risk tolerance and account size.
Multi-timeframe analysis: Enhancing the script to perform multi-timeframe analysis can provide traders with a more holistic view of market trends and cycles. By identifying dominant cycles on different timeframes, traders can gain insights into the potential confluence of cycles and make better-informed trading decisions.
Enhancements for High-Frequency Finance Trading
Algorithm optimization: To ensure the script's suitability for high-frequency finance trading, optimizing the algorithm for faster execution is crucial. This can be achieved by employing efficient data structures and refining the calculation methods to minimize computational complexity.
Real-time data streaming: Integrating real-time data streaming capabilities into the script can help high-frequency traders react to market changes more quickly. By continuously updating the cycle information based on real-time market data, traders can adapt their strategies accordingly and capitalize on short-term market fluctuations.
Order execution and trade management: To fully leverage the script's capabilities for high-frequency trading, implementing functionality for automated order execution and trade management is essential. This can include features such as stop-loss and take-profit orders, trailing stops, and automated trade exit strategies.
While the existing Goertzel algorithm-based script is a valuable tool for detecting dominant cycles in financial data, there are several potential enhancements that can make it even more powerful for financial modeling, general trading, advanced trading, and high-frequency finance trading. By incorporating these improvements, the script can become a more versatile and effective tool for traders and financial analysts alike.
█ Understanding the Limitations of the Goertzel Algorithm
While the Goertzel algorithm-based script for detecting dominant cycles in financial data provides valuable insights, it is important to be aware of its limitations and drawbacks. Some of the key drawbacks of this indicator are:
Lagging nature:
As with many other technical indicators, the Goertzel algorithm-based script can suffer from lagging effects, meaning that it may not immediately react to real-time market changes. This lag can lead to late entries and exits, potentially resulting in reduced profitability or increased losses.
Parameter sensitivity:
The performance of the script can be sensitive to the chosen parameters, such as the detrending methods, smoothing techniques, and cycle detection settings. Improper parameter selection may lead to inaccurate cycle detection or increased false signals, which can negatively impact trading performance.
Complexity:
The Goertzel algorithm itself is relatively complex, making it difficult for novice traders or those unfamiliar with the concept of cycle analysis to fully understand and effectively utilize the script. This complexity can also make it challenging to optimize the script for specific trading styles or market conditions.
Overfitting risk:
As with any data-driven approach, there is a risk of overfitting when using the Goertzel algorithm-based script. Overfitting occurs when a model becomes too specific to the historical data it was trained on, leading to poor performance on new, unseen data. This can result in misleading signals and reduced trading performance.
No guarantee of future performance: While the script can provide insights into past cycles and potential future trends, it is important to remember that past performance does not guarantee future results. Market conditions can change, and relying solely on the script's predictions without considering other factors may lead to poor trading decisions.
Limited applicability: The Goertzel algorithm-based script may not be suitable for all markets, trading styles, or timeframes. Its effectiveness in detecting cycles may be limited in certain market conditions, such as during periods of extreme volatility or low liquidity.
While the Goertzel algorithm-based script offers valuable insights into dominant cycles in financial data, it is essential to consider its drawbacks and limitations when incorporating it into a trading strategy. Traders should always use the script in conjunction with other technical and fundamental analysis tools, as well as proper risk management, to make well-informed trading decisions.
█ Interpreting Results
The Goertzel Browser indicator can be interpreted by analyzing the plotted lines and the table presented alongside them. The indicator plots two lines: past and future composite waves. The past composite wave represents the composite wave of the past price data, and the future composite wave represents the projected composite wave for the next period.
The past composite wave line displays a solid line, with green indicating a bullish trend and red indicating a bearish trend. On the other hand, the future composite wave line is a dotted line with fuchsia indicating a bullish trend and yellow indicating a bearish trend.
The table presented alongside the indicator shows the top cycles with their corresponding rank, period, Bartels, amplitude or cycle strength, and phase. The amplitude is a measure of the strength of the cycle, while the phase is the position of the cycle within the data series.
Interpreting the Goertzel Browser indicator involves identifying the trend of the past and future composite wave lines and matching them with the corresponding bullish or bearish color. Additionally, traders can identify the top cycles with the highest amplitude or cycle strength and utilize them in conjunction with other technical indicators and fundamental analysis for trading decisions.
This indicator is considered a repainting indicator because the value of the indicator is calculated based on the past price data. As new price data becomes available, the indicator's value is recalculated, potentially causing the indicator's past values to change. This can create a false impression of the indicator's performance, as it may appear to have provided a profitable trading signal in the past when, in fact, that signal did not exist at the time.
The Goertzel indicator is also non-endpointed, meaning that it is not calculated up to the current bar or candle. Instead, it uses a fixed amount of historical data to calculate its values, which can make it difficult to use for real-time trading decisions. For example, if the indicator uses 100 bars of historical data to make its calculations, it cannot provide a signal until the current bar has closed and become part of the historical data. This can result in missed trading opportunities or delayed signals.
█ Conclusion
The Goertzel Browser indicator is a powerful tool for identifying and analyzing cyclical patterns in financial markets. Its ability to detect multiple cycles of varying frequencies and strengths make it a valuable addition to any trader's technical analysis toolkit. However, it is important to keep in mind that the Goertzel Browser indicator should be used in conjunction with other technical analysis tools and fundamental analysis to achieve the best results. With continued refinement and development, the Goertzel Browser indicator has the potential to become a highly effective tool for financial modeling, general trading, advanced trading, and high-frequency finance trading. Its accuracy and versatility make it a promising candidate for further research and development.
█ Footnotes
What is the Bartels Test for Cycle Significance?
The Bartels Cycle Significance Test is a statistical method that determines whether the peaks and troughs of a time series are statistically significant. The test is named after its inventor, George Bartels, who developed it in the mid-20th century.
The Bartels test is designed to analyze the cyclical components of a time series, which can help traders and analysts identify trends and cycles in financial markets. The test calculates a Bartels statistic, which measures the degree of non-randomness or autocorrelation in the time series.
The Bartels statistic is calculated by first splitting the time series into two halves and calculating the range of the peaks and troughs in each half. The test then compares these ranges using a t-test, which measures the significance of the difference between the two ranges.
If the Bartels statistic is greater than a critical value, it indicates that the peaks and troughs in the time series are non-random and that there is a significant cyclical component to the data. Conversely, if the Bartels statistic is less than the critical value, it suggests that the peaks and troughs are random and that there is no significant cyclical component.
The Bartels Cycle Significance Test is particularly useful in financial analysis because it can help traders and analysts identify significant cycles in asset prices, which can in turn inform investment decisions. However, it is important to note that the test is not perfect and can produce false signals in certain situations, particularly in noisy or volatile markets. Therefore, it is always recommended to use the test in conjunction with other technical and fundamental indicators to confirm trends and cycles.
Deep-dive into the Hodrick-Prescott Fitler
The Hodrick-Prescott (HP) filter is a statistical tool used in economics and finance to separate a time series into two components: a trend component and a cyclical component. It is a powerful tool for identifying long-term trends in economic and financial data and is widely used by economists, central banks, and financial institutions around the world.
The HP filter was first introduced in the 1990s by economists Robert Hodrick and Edward Prescott. It is a simple, two-parameter filter that separates a time series into a trend component and a cyclical component. The trend component represents the long-term behavior of the data, while the cyclical component captures the shorter-term fluctuations around the trend.
The HP filter works by minimizing the following objective function:
Minimize: (Sum of Squared Deviations) + λ (Sum of Squared Second Differences)
Where:
The first term represents the deviation of the data from the trend.
The second term represents the smoothness of the trend.
λ is a smoothing parameter that determines the degree of smoothness of the trend.
The smoothing parameter λ is typically set to a value between 100 and 1600, depending on the frequency of the data. Higher values of λ lead to a smoother trend, while lower values lead to a more volatile trend.
The HP filter has several advantages over other smoothing techniques. It is a non-parametric method, meaning that it does not make any assumptions about the underlying distribution of the data. It also allows for easy comparison of trends across different time series and can be used with data of any frequency.
However, the HP filter also has some limitations. It assumes that the trend is a smooth function, which may not be the case in some situations. It can also be sensitive to changes in the smoothing parameter λ, which may result in different trends for the same data. Additionally, the filter may produce unrealistic trends for very short time series.
Despite these limitations, the HP filter remains a valuable tool for analyzing economic and financial data. It is widely used by central banks and financial institutions to monitor long-term trends in the economy, and it can be used to identify turning points in the business cycle. The filter can also be used to analyze asset prices, exchange rates, and other financial variables.
The Hodrick-Prescott filter is a powerful tool for analyzing economic and financial data. It separates a time series into a trend component and a cyclical component, allowing for easy identification of long-term trends and turning points in the business cycle. While it has some limitations, it remains a valuable tool for economists, central banks, and financial institutions around the world.
