Multi-Scale Adaptive MAs (Hurst, CVaR, Fractal) // AlgoFyreThe Multi-Scale Adaptive MAs (Hurst, CVaR, Fractal) indicator adjusts moving averages based on market conditions, using Hurst Exponent for trend persistence, CVaR for extreme risk assessment, and Fractal Dimension for market complexity. It enhances trend detection and risk management across various timeframes.
TABLE OF CONTENTS
🔶 ORIGINALITY 🔸Adaptive Mechanisms
🔸Multi-Faceted Analysis
🔸Versatility Across Timeframes
🔸Multi-Scale Combination
🔶 FUNCTIONALITY 🔸Hurst Exponent (H)
🞘 How it works
🞘 How to calculate
🞘 Code extract
🔸Conditional Value at Risk (CVaR)
🞘 How it works
🞘 How to calculate
🞘 Code extract
🔸Fractal Dimension (FD)
🞘 How it works
🞘 How to calculate
🞘 Code extract
🔶 INSTRUCTIONS 🔸Step-by-Step Guidelines
🞘 Setting Up the Indicator
🞘 Understanding What to Look For on the Chart
🞘 Possible Entry Signals
🞘 Possible Take Profit Strategies
🞘 Possible Stop-Loss Levels
🞘 Additional Tips
🔸Customize settings
🔶 CONCLUSION
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🔶 ORIGINALITY The Multi-Scale Adaptive MAs (Hurst, CVaR, Fractal) indicator stands out due to its unique approach of dynamically adjusting moving averages based on advanced statistical measures, making it highly responsive to varying market conditions. Unlike traditional moving averages that rely on static periods, this indicator adapts in real-time using three distinct adaptive methods: Hurst Exponent, CVaR, and Fractal Dimension.
🔸Adaptive Mechanisms
Traditional MA indicators use fixed lengths, which can lead to lagging signals or over-sensitivity in volatile markets. The Multi-Scale Adaptive MAs employ adaptive methods to adjust the MA length dynamically, providing a more accurate reflection of current market conditions.
🔸Multi-Faceted Analysis
By integrating Hurst Exponent, CVaR, and Fractal Dimension, the indicator offers a comprehensive market analysis. It captures different aspects of market behavior, including trend persistence, risk of extreme movements, and complexity, which are often missed by standard MAs.
🔸Versatility Across Timeframes
The indicator’s ability to switch between different adaptive methods based on market conditions allows traders to analyze short-term, medium-term, and long-term trends with enhanced precision.
🔸Multi-Scale Combination
Utilizing multiple adaptive MAs in combination provides a more nuanced view of the market, allowing traders to see how short, medium, and long-term trends interact. This layered approach helps in identifying the strength and consistency of trends across different scales, offering more reliable signals and aiding in complex decision-making processes. When combined, these MAs can also signal key market shifts when they converge or diverge, offering deeper insights than a single MA could provide.
🔶 FUNCTIONALITY The indicator adjusts moving averages based on a variety of different choosable adaptives. The Hurst Exponent to identify trend persistence or mean reversion, adapting to market conditions for both short-term and long-term trends. Using CVaR, it evaluates the risk of extreme price movements, ensuring the moving average is more conservative during high-risk periods, protecting against potential large losses. By incorporating the Fractal Dimension, the indicator adapts to market complexity, adjusting to varying levels of price roughness and volatility, which allows it to respond more accurately to different market structures and patterns.
Let's dive into the details:
🔸Hurst Exponent (H)
Measures the degree of trend persistence or mean reversion.
By using the Hurst Exponent, the indicator adjusts to capture the strength and duration of trends, helping traders to stay in profitable trades longer and avoid false reversals in ranging markets.
It enhances the detection of trends, making it suitable for both short-term scalping and identifying long-term trends.
🞘 How it works Rescaled Range (R/S) Analysis Calculate the mean of the closing prices over a set window.
Determine the deviation of each price from the mean.
Compute the cumulative sum of these deviations over the window.
Calculate the range (R) of the cumulative deviations (maximum minus minimum).
Compute the standard deviation (S) of the price series over the window.
Obtain the R/S ratio as R/S.
Linear Regression for Hurst Exponent Calculate the logarithm of multiple window sizes and their corresponding R/S values.
Use linear regression to determine the slope of the line fitting the log(R/S) against log(window size).
The slope of this line is an estimate of the Hurst Exponent.
🞘 How to calculate Range (R)
Calculate the maximum cumulative deviation:
R=max(sum(deviation))−min(sum(deviation))
Where deviation is the difference between each price and the mean.
Standard Deviation (S)
Calculate the standard deviation of the price series:
S=sqrt((1/(n−1))∗sum((Xi−mean)2))
Rescaled Range (R/S)
Divide the range by the standard deviation:
R/S=R/S
Hurst Exponent
Perform linear regression to estimate the slope of:
log(R/S) versus log(windowsize)
The slope of this line is the Hurst Exponent.
🞘 Code extract // Hurst Exponent
calc_hurst(source_, adaptive_window_) =>
window_sizes = array.from(adaptive_window_/10, adaptive_window_/5, adaptive_window_/2, adaptive_window_)
float hurst_exp = 0.5
// Calculate Hurst Exponent proxy
rs_list = array.new_float()
log_length_list = array.new_float()
for i = 0 to array.size(window_sizes) - 1
len = array.get(window_sizes, i)
// Ensure we have enough data
if bar_index >= len * 2
mean = adaptive_sma(source_, len)
dev = source_ - mean
// Calculate cumulative deviations over the window
cum_dev = ta.cum(dev) - ta.cum(dev )
r = ta.highest(cum_dev, len) - ta.lowest(cum_dev, len)
s = ta.stdev(source_, len)
if s != 0
rs = r / s
array.push(rs_list, math.log(rs))
array.push(log_length_list, math.log(len))
// Linear regression to estimate Hurst Exponent
n = array.size(log_length_list)
if n > 1
mean_x = array.sum(log_length_list) / n
mean_y = array.sum(rs_list) / n
sum_num = 0.0
sum_den = 0.0
for i = 0 to n - 1
x = array.get(log_length_list, i)
y = array.get(rs_list, i)
sum_num += (x - mean_x) * (y - mean_y)
sum_den += (x - mean_x) * (x - mean_x)
hurst_exp := sum_den != 0 ? sum_num / sum_den : 0.5
else
hurst_exp := 0.5 // Default to 0.5 if not enough data
hurst_exp
🔸Conditional Value at Risk (CVaR)
Assesses the risk of extreme losses by focusing on tail risk.
This method adjusts the moving average to account for market conditions where extreme price movements are likely, providing a more conservative approach during periods of high risk.
Traders benefit by better managing risk and avoiding major losses during volatile market conditions.
🞘 How it works Calculate Returns Determine the returns as the percentage change between consecutive closing prices over a specified window.
Percentile Calculation Identify the percentile threshold (e.g., the 5th percentile) for the worst returns in the dataset.
Average of Extreme Losses Calculate the average of all returns that are less than or equal to this percentile, representing the CVaR.
🞘 How to calculate Return Calculation
Calculate the return as the percentage change between consecutive prices:
Return = (Pt − Pt−1) / Pt−1
Where Pt is the price at time t.
Percentile Threshold
Identify the return value at the specified percentile (e.g., 5th percentile):
PercentileValue=percentile(returns,percentile_threshold)
CVaR Calculation
Compute the average of all returns below the percentile threshold:
CVaR = (1/n)∗sum(Return) for all Return≤PercentileValue
Where n is the total number of returns.
🞘 Code extract // Percentile
calc_percentile(data, percentile, window) =>
arr = array.new_float(0)
for i = 0 to window - 1
array.push(arr, data )
array.sort(arr)
index = math.floor(percentile / 100 * (window - 1))
array.get(arr, index)
// Conditional Value at Risk
calc_cvar(percentile_value, returns, window) =>
// Collect returns worse than the threshold
cvar_sum = 0.0
cvar_count = 0
for i = 0 to window - 1
ret = returns
if ret <= percentile_value
cvar_sum += ret
cvar_count += 1
// Calculate CVaR
cvar = cvar_count > 0 ? cvar_sum / cvar_count : 0.0
cvar
🔸Fractal Dimension (FD)
Evaluates market complexity and roughness by analyzing how price movements behave across different scales.
It enables the moving average to adapt based on the level of market noise or structure, allowing for smoother MAs during complex, volatile periods and more sensitive MAs during clear trends.
This adaptability is crucial for traders dealing with varying market states, improving the indicator's responsiveness to price changes.
🞘 How it works Total Distance (L) Calculation Sum the absolute price movements between consecutive periods over a given window.
Maximum Distance (D) Calculation Calculate the maximum displacement from the first to the last price point within the window.
Calculate Fractal Dimension Use Katz's method to estimate the Fractal Dimension as the ratio of the logarithms of L and D, divided by the logarithm of the number of steps (N).
🞘 How to calculate Total Distance (L)
Sum the absolute price changes over the window:
L=sum(abs(Pt−Pt−1)) for t from 2 to n
Where Pt is the price at time t.
Maximum Distance (D)
Find the maximum absolute displacement from the first to the last price in the window:
D=max(abs(Pn-P1))
Fractal Dimension Calculation
Use Katz's method to estimate fractal dimension:
FD=log(L/D)/log(N)
Where N is the number of steps in the window.
🞘 Code extract // Fractal Dimension
calc_fractal(source_, adaptive_window_) =>
// Calculate the total distance (L) traveled by the price
L = 0.0
for i = 1 to adaptive_window_
L += math.abs(source_ - source_ )
// Calculate the maximum distance between first and last price
D = math.max(math.abs(source_ - source_ ), 1e-10) // Avoid division by zero
// Calculate the number of steps (N)
N = adaptive_window_
// Estimate the Fractal Dimension using Katz's formula
math.log(L / D) / math.log(N)
🔶 INSTRUCTIONS The Multi-Scale Adaptive MAs indicator can be set up by adding it to your TradingView chart and configuring the adaptive method (Hurst, CVaR, or Fractal) to match current market conditions. Look for price crossovers and changes in the slope for potential entry signals. Set take profit and stop-loss levels based on dynamic changes in the moving average, and consider combining it with other indicators for confirmation. Adjust settings and use adaptive strategies for enhanced trend detection and risk management.
🔸Step-by-Step Guidelines 🞘 Setting Up the Indicator Adding the Indicator to the Chart: Go to your TradingView chart.
Click on the "Indicators" button at the top.
Search for "Multi-Scale Adaptive MAs (Hurst, CVaR, Fractal)" in the indicators list.
Click on the indicator to add it to your chart.
Configuring the Indicator: Open the indicator settings by clicking on the gear icon next to its name on the chart.
Adaptive Method: Choose between "Hurst," "CVaR," and "Fractal" depending on the market condition and your trading style.
Length: Set the base length for the moving average (e.g., 20, 50, or 100). This length will be adjusted dynamically based on the selected adaptive method.
Other Parameters: Adjust any other parameters as needed, such as window sizes or scaling factors specific to each adaptive method.
Chart Setup: Ensure you have an appropriate timeframe selected (e.g., 1-hour, 4-hour, daily) based on your trading strategy.
Consider using additional indicators like volume or RSI to confirm signals.
🞘 Understanding What to Look For on the Chart Indicator Behavior: Observe how the adaptive moving average (AMA) behaves compared to standard moving averages, e.g. notice how it might change direction with strength (Hurst).
For example, the AMA may become smoother during high market volatility (CVaR) or more responsive during strong trends (Hurst).
Crossovers: Look for crossovers between the price and the adaptive moving average.
A bullish crossover occurs when the price crosses above the AMA, suggesting a potential uptrend.
A bearish crossover occurs when the price crosses below the AMA, indicating a possible downtrend.
Slope and Direction: Pay attention to the slope of the AMA. A rising slope suggests a bullish trend, while a declining slope indicates a bearish trend.
The slope’s steepness can give you clues about the trend's strength.
🞘 Possible Entry Signals Bullish Entry: Crossover Entry: Enter a long position when the price crosses above the AMA and the AMA has a positive slope.
Confirmation Entry: Combine the crossover with other indicators like RSI (above 50) or increasing volume for confirmation.
Bearish Entry: Crossover Entry: Enter a short position when the price crosses below the AMA and the AMA has a negative slope.
Confirmation Entry: Use additional indicators like RSI (below 50) or decreasing volume to confirm the bearish trend.
Adaptive Method Confirmation: Hurst: Enter when the AMA indicates a strong trend (steeper slope). Suitable for trend-following strategies.
CVaR: Be cautious during high-risk periods. Enter only if confirmed by other indicators, as the AMA may become more conservative.
Fractal: Ideal for capturing reversals in complex markets. Look for crossovers in volatile markets.
🞘 Possible Take Profit Strategies Static Take Profit Levels: Set take profit levels based on predefined ratios (e.g., 1:2 or 1:3 risk-reward ratio).
Place take profit orders at recent swing highs (for long positions) or swing lows (for short positions).
Trailing Stop Loss: Use a trailing stop based on a percentage of the AMA value to lock in profits as the trend progresses.
Adjust the trailing stop dynamically to follow the AMA, allowing profits to run while protecting gains.
Adaptive Method Based Exits: Hurst: Exit when the AMA begins to flatten or turn in the opposite direction, signaling a potential trend reversal.
CVaR: Consider taking profits earlier during high-risk periods when the AMA suggests caution.
Fractal: Use the AMA to exit in complex markets when it smooths out, indicating reduced volatility.
🞘 Possible Stop-Loss Levels Initial Stop Loss: Place an initial stop loss below the AMA (for long positions) or above the AMA (for short positions) to protect against adverse movements.
Use a buffer (e.g., ATR value) to avoid being stopped out by normal price fluctuations.
Adaptive Stop Loss: Adjust the stop loss dynamically based on the AMA. Move the stop loss along the AMA as the trend progresses to minimize risk.
This helps in adapting to changing market conditions and avoiding premature exits.
Adaptive Method-Specific Stop Loss: Hurst: Use wider stops during trending markets to allow for minor pullbacks.
CVaR: Adjust stops in high-risk periods to avoid being stopped out prematurely during price fluctuations.
Fractal: Place stops at recent support/resistance levels in highly volatile markets.
🞘 Additional Tips Combine with Other Indicators: Enhance your strategy by combining the AMA with other technical indicators like MACD, RSI, or Bollinger Bands for better signal confirmation.
Backtesting and Practice: Backtest the indicator on historical data to understand how it performs in different market conditions.
Practice using the indicator on a demo account before applying it to live trading.
Market Awareness: Always be aware of market conditions and fundamental events that might impact price movements, as the AMA reacts to price action and may not account for sudden news-driven events.
🔸Customize settings 🞘 Time Override: Enables or disables the ability to override the default time frame for the moving averages. When enabled, you can specify a custom time frame for the calculations.
🞘 Time: Specifies the custom time frame to use when the Time Override setting is enabled.
🞘 Enable MA: Enables or disables the moving average. When disabled, MA will not be displayed on the chart.
🞘 Show Smoothing Line: Enables or disables the display of a smoothing line for the moving average. The smoothing line helps to reduce noise and provide a clearer trend.
🞘 Show as Horizontal Line: Displays the moving average as a horizontal line instead of a dynamic line that follows the price.
🞘 Source: Specifies the data source for the moving average calculation (e.g., close, open, high, low).
🞘 Length: Sets the period length for the moving average. A longer length will result in a smoother moving average, while a shorter length will make it more responsive to price changes.
🞘 Time: Specifies a custom time frame for the moving average, overriding the default time frame if Time Override is enabled.
🞘 Method: Selects the calculation method for the moving average (e.g., SMA, EMA, SMMA, WMA, VWMA).
🞘 Offset: Shifts the moving average forward or backward by the specified number of bars.
🞘 Color: Sets the color for the moving average line.
🞘 Adaptive Method: Selects the adaptive method to dynamically adjust the moving average based on market conditions (e.g., Hurst, CVaR, Fractal).
🞘 Window Size: Sets the window size for the adaptive method, determining how much historical data is used for the calculation.
🞘 CVaR Scaling Factor: Adjusts the influence of CVaR on the moving average length, controlling how much the length changes based on calculated risk.
🞘 CVaR Risk: Specifies the percentile cutoff for the worst-case returns used in the CVaR calculation to assess extreme losses.
🞘 Smoothing Method: Selects the method for smoothing the moving average (e.g., SMA, EMA, SMMA, WMA, VWMA).
🞘 Smoothing Length: Sets the period length for smoothing the moving average.
🞘 Fill Color to Smoothing Moving Average: Enables or disables the color fill between the moving average and its smoothing line.
🞘 Transparency: Sets the transparency level for the color fill between the moving average and its smoothing line.
🞘 Show Label: Enables or disables the display of a label for the moving average on the chart.
🞘 Show Label for Smoothing: Enables or disables the display of a label for the smoothing line of the moving average on the chart.
🔶 CONCLUSION The Multi-Scale Adaptive MAs indicator offers a sophisticated approach to trend analysis and risk management by dynamically adjusting moving averages based on Hurst Exponent, CVaR, and Fractal Dimension. This adaptability allows traders to respond more effectively to varying market conditions, capturing trends and managing risks with greater precision. By incorporating advanced statistical measures, the indicator goes beyond traditional moving averages, providing a nuanced and versatile tool for both short-term and long-term trading strategies. Its unique ability to reflect market complexity and extreme risks makes it an invaluable asset for traders seeking a deeper understanding of market dynamics.
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Trailing Stop ProTrailing Stop Pro is a sophisticated TradingView indicator designed to enhance your trading strategy by dynamically managing trailing stops based on market volatility. This tool leverages the Average True Range (ATR) to adjust stop levels, providing traders with a robust mechanism to protect profits and minimize losses.
Key Features:
Dynamic Trailing Stops: Automatically adjusts stop levels using ATR, allowing for responsive and adaptive risk management.
Customizable Inputs: Tailor the indicator to your trading style with adjustable parameters such as ATR Length, ATR Multiplier, and Source Vector.
Visual Clarity: Distinct color settings for long and short stops, with adjustable line thickness and transparency, ensuring clear visualization on your charts.
Professional Grade: The "Pro" designation signifies advanced features suitable for both novice and experienced traders seeking reliable and efficient stop management.
How It Works:
To set up the indicator, begin by defining the Chrono Point, which specifies the exact time you want the trailing stop mechanism to activate. This allows for precise control over when your stops begin to trail. Next, set the Credit Unit as the initial entry price for your trade, serving as the baseline from which the trailing stops will adjust.
The indicator uses ATR-based adjustments to determine stop levels. Customize the sensitivity of the trailing stop by adjusting the ATR Length (default is 14) and ATR Multiplier (default is 0.5). A longer ATR length smooths out volatility, while a higher multiplier increases the distance of the stop from the price.
Select your Source Vector from "High/Low," "Close," or "Open" prices as the basis for stop calculation. This flexibility allows you to align the indicator with your preferred trading strategy. The indicator plots trailing stops directly on the chart, with color-coded lines indicating long (teal) and short (red) positions. You can adjust the line thickness and transparency for optimal visibility.
The Mission Status feature automatically detects whether the trade is long or short and adjusts the trailing stop accordingly. If the price hits the trailing stop, the trade is considered exited, and the indicator calculates the profit or loss percentage.
Benefits:
Risk Management: Protect your trades from adverse market movements while locking in profits as prices move favorably.
Automation: Reduce manual intervention with automatic stop adjustments, allowing you to focus on strategic decision-making.
User-Friendly Interface: Intuitive settings and clear visual cues make it easy to integrate into your existing trading workflow.
Conclusion:
Trailing Stop Pro is an essential tool for traders looking to enhance their risk management strategies with precision and ease. By automating the trailing stop process and providing clear visual feedback, this indicator empowers you to navigate the markets with confidence. Whether you're a seasoned trader or just starting, Trailing Stop Pro offers the functionality and flexibility needed to optimize your trading performance.
The Trailing Stop Pro indicator is a tool designed to assist traders in managing risk and optimizing their trading strategies. However, it should not be considered as financial advice or a guarantee of profitability. Trading involves significant risk, and it is possible to lose more than your initial investment. Users are encouraged to thoroughly test the indicator in a demo environment and consider their own financial situation and risk tolerance before using it in live trading. Past performance is not indicative of future results, and users should seek advice from a qualified financial advisor if needed.
AB_Bnf_Selling_5minThe Mathematical Level Reversal Strategy is designed to identify potential reversal points in the market using mathematical levels combined with price action on a 5-minute chart. This strategy is particularly effective for intraday traders who seek to capitalize on precise entry and exit points based on calculated levels rather than traditional indicators like moving averages or Bollinger Bands.
Creators' Mathematical Levels Explanation
Mathematical levels are predetermined price points calculated based on various factors such as previous high/low points, Fibonacci retracements, or other arithmetic calculations. These levels are used to anticipate areas where the price might reverse or experience significant support or resistance.
higher threshold: A predefined level where the price is expected to experience resistance, leading to a potential reversal downward.
Lower Threshold: A predefined level where the price might find support, leading to a potential upward reversal.
In this strategy, we focus on price movements around the upper mathematical level, where prices are likely to reverse downwards.
Strategy Logic
Setup:
The strategy is applied on a 5-minute chart.
Mathematical levels are calculated based on your preferred method, such as Fibonacci levels, pivot points, or custom calculations. For this strategy, let's assume we are using a specific predefined upper level.
Sell Signal Criteria:
A 5-minute candle must cross above the predefined upper mathematical level or close entirely above it (open and close both above the level).
The following candle must break below the low of the candle that crossed the upper level and close below that low. This confirms a bearish reversal.
Once these conditions are met, a sell signal is triggered.
Stop Loss:
The stop loss is placed at the high of the candle that crossed above the upper mathematical level.
This level represents the point where the trade setup would be invalidated.
Take Profit:
Target 1: The first take profit is set at a level that offers a 1:5 risk-to-reward ratio.
Target 2: An alternative take profit level is set at a 1:3 risk-to-reward ratio, providing flexibility based on market conditions.
Trade Management:
Once a trade is initiated, no new trades will be taken until the current trade hits either the stop loss or the first take profit level. This prevents overlapping signals and helps in managing risk effectively.
Originality and Usefulness
This strategy offers a unique approach by using mathematical levels instead of traditional indicators. It provides traders with a clear framework for identifying and executing high-probability reversal trades, particularly in intraday markets.
Originality:
The strategy's originality lies in its reliance on mathematical levels combined with a multi-candle confirmation pattern. This approach reduces the chances of false signals and offers a robust method for identifying potential reversals.
Usefulness:
The strategy is particularly useful for traders who prefer a more quantitative approach, relying on calculated price levels rather than indicators. The clear rules for entry, stop loss, and take profit make it easier to execute consistently.
The inclusion of both 1:5 and 1:3 risk-to-reward targets allows for flexibility depending on market conditions, ensuring that traders can adapt to varying levels of volatility.
Chart Signals and Examples
To demonstrate the effectiveness of this strategy, let's look at a few hypothetical examples on a 5-minute chart:
Example 1: Clear Reversal Signal
The price steadily rises and crosses above the predefined upper mathematical level. The next candle breaks below the low of this candle and closes lower, triggering a sell signal.
A red dotted line is drawn at the stop loss level (the high of the candle that crossed the upper level).
Two green dashed lines are drawn to indicate the first and second take profit levels.
Example 2: No Signal Due to Ongoing Trade
After an initial sell signal is triggered, the price fluctuates but does not hit either the stop loss or the first take profit target. During this period, the strategy refrains from issuing any new signals, adhering to the trade management rule.
Example 3: Trade Reaches Target 1
In another scenario, the price moves sharply in favor of the trade after the signal is triggered. The first take profit level is hit, securing a profit. The trade is then considered closed, and the strategy is ready to issue a new signal when conditions are met.
BB Position CalculatorPosition Size Calculator Instructions
Overview
The Position Size Calculator is designed to help traders automatically determine the appropriate lot size based on the dollar amount they are willing to risk. It includes features for automatic lot sizing, fixed lot risk calculations, take profit calculations (both automatic and fixed), max run-up, and max drawdown. Calculated values are displayed in ticks, points, and USD.
Key Features
• Automatic Lot Sizing: Automatically calculates lot size based on the amount of money you are willing to risk.
• Fixed Lot Risk Calculations: Provides risk calculations for fixed lot sizes.
• Take Profit Calculations: Offers both automatic and fixed take profit calculations.
• Max Run-Up and Max Drawdown: Monitors and displays the maximum run-up and drawdown of your trade.
• Detailed Metrics: Displays all calculated values in ticks, points, and USD.
Setup Instructions
1. Add and Remove for Each Position: The calculator is designed to be added to your chart for each new position. Once your preferences are set the first time, save them as your default to retain your settings for future use.
2. Adding the Indicator to Favorites:
• Use the TradingView keyboard shortcut “/” then type “pos.”
• Use the arrow key to select the Position Size Calculator and press enter.
• Close the indicator selection pop-up.
3. Setting the Trigger Price:
• A blue pop-up labeled “SET TRIGGER PRICE” will appear at the bottom of the chart.
• Click on the chart at the price level where you want to enter the trade.
4. Setting the Stop Loss:
• The pop-up will change to “SET STOP LOSS.”
• Click on the chart at the price level where your stop loss will be set.
5. Setting the Take Profit:
• The pop-up will change to “SET TAKE PROFIT.”
• Click on the chart at the price level where you want to take profit. If you have selected the option to overwrite with a set risk/reward ratio (R:R), the calculation will use this price level.
6. Setting the Trade Window Start:
• The pop-up will change to “SET TRADE WINDOW START.”
• Click on the bar in time where you want the indicator to start monitoring for price to trigger the position.
7. Adjusting the Position:
• Clicking on any part of the indicator will display draggable lines, allowing you to fine-tune the position that was previously plotted by the first four chart clicks.
Additional Notes
• Compatibility: This calculator has only been tested with futures trading.
• Customization: Once your preferences are set, save them as your default to make setup quicker for future trades.
• Support: If you have any questions or feature requests, please feel free to reach out.
GG Short & Long IndicatorGG Short & Long Indicator is a powerful signal indicator with AI
How do indicator signals work?
The main purpose of the indicator is to give a signal that is most likely to bring profit based on historical data. This ORIGINAL trend algorithm gives SHORT and LONG signals when several conditions coincide: 1) Breakout of the average value of the modernized VWAP (this VWAP takes data only from certain time periods and trading sessions, as a result, its breakout most often coincides with the beginning of a strong trend); 2) The previous condition must be confirmed by volumes. I noticed that on some crypto exchanges, depending on whether the breakout is false or true, the volumes are different relative to each other. I applied this knowledge for additional filtering of signals (this point works only on crypto assets, on other assets the algorithm works without taking it into account, maybe later I will refine it); 3) When some of my original formulas to determine overbought (similar in principle to RSI, but more designed to work with the trader algorithm), should not show overbought - so that the entry into the transaction was not at too unfavorable values. To summarize, the algorithm tries to find a balance to determine a true breakout, during which the price will not go too far (for an acceptable RR).
But the most important thing is that the parameters to customize the algorithm are governed by our original AI algorithm. It can adjust the indicator in two modes: 1) Settings are selected based on the most profitable historical settings. 2) The settings are selected based not only on historical profitability, but also on winrate, frequency of trades, and a few other items that we will not disclose (so the code is closed) - we consider this approach as a priority, because according to our observations, it gives the highest performance compared to manual tuning. In addition, AI simply simplifies the work with the indicator - you do not need to adjust the settings manually for different trading pairs or timeframes, AI will do it all by itself and immediately give the ready result (backtest) on the table.
How to trade?
After the signal is issued, the indicator determines the recommended levels to close the trade (green dots). Stop loss should be placed behind the corresponding gray SL mark. Levels for closing a deal (TP) and the level of stop loss setting (SL) are also determined automatically for the selected pair and TF, based on volatility and selected indicator settings
To make a trade, you can also use the built-in “Support and Resistance Zones” tool, which displays ranges on the chart based on the modernized ATR, from which the price is more likely to rebound (here I also used my own approach, where in addition to the classic ATR formula, I also used volumes from certain crypto exchanges to determine more accurate price rebound zones)
These zones are also adjusted by AI - the algorithm compares several dozens of variations of these zones (with different settings) and chooses the one that best fits the current settings of the signal algorithm. For example, if the indicator is set up for frequent trades - the zones will be updated faster and will be less deep than if the indicator is set up for medium-term trading
If desired, you can customize the indicator manually using the corresponding section of the settings. Each paramater has a tooltip describing how and what it affects.
Statistisc panel
The panel can be divided into 2 conditional parts:
1) Statistics for each individual TP for the selected strategy. It shows the winrate and gross profit, if you fix a trade on a single target completely
2) Total trading result, if you trade clearly according to the strategy and fix the position by equal hours on 4 TPs. The total trading result is displayed for the current indicator settings, it also shows the best, worst and optimal of the possible indicator settings and the trading result of these settings on the side.
How do setup the indicator?
The indicator has preset settings for several major pairs and timeframes. These are fixed settings specifically selected for individual pairs and timeframes. You can use these presets, or you can choose one of the adaptive settings, which will AUTOMATICALLY select the best/optimal indicator settings.
I recommend choosing the “Adaptive Optimal” preset, as it uses more data to determine the optimal indicator settings and according to my observations this method works better in comparison to manual indicator settings or the “Adaptive Best” preset
Or you can use the manual settings, as mentioned earlier.
Bitcoin Macro Trend Map [Ox_kali]
## Introduction
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The “Bitcoin Macro Trend Map” script is designed to provide a comprehensive analysis of Bitcoin’s macroeconomic trends. By leveraging a unique combination of Bitcoin-specific macroeconomic indicators, this script helps traders identify potential market peaks and troughs with greater accuracy. It synthesizes data from multiple sources to offer a probabilistic view of market excesses, whether overbought or oversold conditions.
This script offers significant value for the following reasons:
1. Holistic Market Analysis : It integrates a diverse set of indicators that cover various aspects of the Bitcoin market, from investor sentiment and market liquidity to mining profitability and network health. This multi-faceted approach provides a more complete picture of the market than relying on a single indicator.
2. Customization and Flexibility : Users can customize the script to suit their specific trading strategies and preferences. The script offers configurable parameters for each indicator, allowing traders to adjust settings based on their analysis needs.
3. Visual Clarity : The script plots all indicators on a single chart with clear visual cues. This includes color-coded indicators and background changes based on market conditions, making it easy for traders to quickly interpret complex data.
4. Proven Indicators : The script utilizes well-established indicators like the EMA, NUPL, PUELL Multiple, and Hash Ribbons, which are widely recognized in the trading community for their effectiveness in predicting market movements.
5. A New Comprehensive Indicator : By integrating background color changes based on the aggregate signals of various indicators, this script essentially creates a new, comprehensive indicator tailored specifically for Bitcoin. This visual representation provides an immediate overview of market conditions, enhancing the ability to spot potential market reversals.
Optimal for use on timeframes ranging from 1 day to 1 week , the “Bitcoin Macro Trend Map” provides traders with actionable insights, enhancing their ability to make informed decisions in the highly volatile Bitcoin market. By combining these indicators, the script delivers a robust tool for identifying market extremes and potential reversal points.
## Key Indicators
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Macroeconomic Data: The script combines several relevant macroeconomic indicators for Bitcoin, such as the 10-month EMA, M2 money supply, CVDD, Pi Cycle, NUPL, PUELL, MRVR Z-Scores, and Hash Ribbons (Full description bellow).
Open Source Sources: Most of the scripts used are sourced from open-source projects that I have modified to meet the specific needs of this script.
Recommended Timeframes: For optimal performance, it is recommended to use this script on timeframes ranging from 1 day to 1 week.
Objective: The primary goal is to provide a probabilistic solution to identify market excesses, whether overbought or oversold points.
## Originality and Purpose
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This script stands out by integrating multiple macroeconomic indicators into a single comprehensive tool. Each indicator is carefully selected and customized to provide insights into different aspects of the Bitcoin market. By combining these indicators, the script offers a holistic view of market conditions, helping traders identify potential tops and bottoms with greater accuracy. This is the first version of the script, and additional macroeconomic indicators will be added in the future based on user feedback and other inputs.
## How It Works
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The script works by plotting each macroeconomic indicator on a single chart, allowing users to visualize and interpret the data easily. Here’s a detailed look at how each indicator contributes to the analysis:
EMA 10 Monthly: Uses an exponential moving average over 10 monthly periods to signal bullish and bearish trends. This indicator helps identify long-term trends in the Bitcoin market by smoothing out price fluctuations to reveal the underlying trend direction.Moving Averages w/ 18 day/week/month.
Credit to @ryanman0
M2 Money Supply: Analyzes the evolution of global money supply, indicating market liquidity conditions. This indicator tracks the changes in the total amount of money available in the economy, which can impact Bitcoin’s value as a hedge against inflation or economic instability.
Credit to @dylanleclair
CVDD (Cumulative Value Days Destroyed): An indicator based on the cumulative value of days destroyed, useful for identifying market turning points. This metric helps assess the Bitcoin market’s health by evaluating the age and value of coins that are moved, indicating potential shifts in market sentiment.
Credit to @Da_Prof
Pi Cycle: Uses simple and exponential moving averages to detect potential sell points. This indicator aims to identify cyclical peaks in Bitcoin’s price, providing signals for potential market tops.
Credit to @NoCreditsLeft
NUPL (Net Unrealized Profit/Loss): Measures investors’ unrealized profit or loss to signal extreme market levels. This indicator shows the net profit or loss of Bitcoin holders as a percentage of the market cap, helping to identify periods of significant market optimism or pessimism.
Credit to @Da_Prof
PUELL Multiple: Assesses mining profitability relative to historical averages to indicate buying or selling opportunities. This indicator compares the daily issuance value of Bitcoin to its yearly average, providing insights into when the market is overbought or oversold based on miner behavior.
Credit to @Da_Prof
MRVR Z-Scores: Compares market value to realized value to identify overbought or oversold conditions. This metric helps gauge the overall market sentiment by comparing Bitcoin’s market value to its realized value, identifying potential reversal points.
Credit to @Pinnacle_Investor
Hash Ribbons: Uses hash rate variations to signal buying opportunities based on miner capitulation and recovery. This indicator tracks the health of the Bitcoin network by analyzing hash rate trends, helping to identify periods of miner capitulation and subsequent recoveries as potential buying opportunities.
Credit to @ROBO_Trading
## Indicator Visualization and Interpretation
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For each horizontal line representing an indicator, a legend is displayed on the right side of the chart. If the conditions are positive for an indicator, it will turn green, indicating the end of a bearish trend. Conversely, if the conditions are negative, the indicator will turn red, signaling the end of a bullish trend.
The background color of the chart changes based on the average of green or red indicators. This parameter is configurable, allowing adjustment of the threshold at which the background color changes, providing a clear visual indication of overall market conditions.
## Script Parameters
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The script includes several configurable parameters to customize the display and behavior of the indicators:
Color Style:
Normal: Default colors.
Modern: Modern color style.
Monochrome: Monochrome style.
User: User-customized colors.
Custom color settings for up trends (Up Trend Color), down trends (Down Trend Color), and NaN (NaN Color)
Background Color Thresholds:
Thresholds: Settings to define the thresholds for background color change.
Low/High Red Threshold: Low and high thresholds for bearish trends.
Low/High Green Threshold: Low and high thresholds for bullish trends.
Indicator Display:
Options to show or hide specific indicators such as EMA 10 Monthly, CVDD, Pi Cycle, M2 Money, NUPL, PUELL, MRVR Z-Scores, and Hash Ribbons.
Specific Indicator Settings:
EMA 10 Monthly: Options to customize the period for the exponential moving average calculation.
M2 Money: Aggregation of global money supply data.
CVDD: Adjustments for value normalization.
Pi Cycle: Settings for simple and exponential moving averages.
NUPL: Thresholds for unrealized profit/loss values.
PUELL: Adjustments for mining profitability multiples.
MRVR Z-Scores: Settings for overbought/oversold values.
Hash Ribbons: Options for hash rate moving averages and capitulation/recovery signals.
## Conclusion
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The “Bitcoin Macro Trend Map” by Ox_kali is a tool designed to analyze the Bitcoin market. By combining several macroeconomic indicators, this script helps identify market peaks and troughs. It is recommended to use it on timeframes from 1 day to 1 week for optimal trend analysis. The scripts used are sourced from open-source projects, modified to suit the specific needs of this analysis.
## Notes
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This is the first version of the script and it is still in development. More indicators will likely be added in the future. Feedback and comments are welcome to improve this tool.
## Disclaimer:
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Please note that the Open Interest liquidation map is not a guarantee of future market performance and should be used in conjunction with proper risk management. Always ensure that you have a thorough understanding of the indicator’s methodology and its limitations before making any investment decisions. Additionally, past performance is not indicative of future results.
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.
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.
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.
