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.
Movingavarage
Fear/Greed Zone Reversals [UAlgo]The "Fear/Greed Zone Reversals " indicator is a custom technical analysis tool designed for TradingView, aimed at identifying potential reversal points in the market based on sentiment zones characterized by fear and greed. This indicator utilizes a combination of moving averages, standard deviations, and price action to detect when the market transitions from extreme fear to greed or vice versa. By identifying these critical turning points, traders can gain insights into potential buy or sell opportunities.
🔶 Key Features
Customizable Moving Averages: The indicator allows users to select from various types of moving averages (SMA, EMA, WMA, VWMA, HMA) for both fear and greed zone calculations, enabling flexible adaptation to different trading strategies.
Fear Zone Settings:
Fear Source: Select the price data point (e.g., close, high, low) used for Fear Zone calculations.
Fear Period: This defines the lookback window for calculating the Fear Zone deviation.
Fear Stdev Period: This sets the period used to calculate the standard deviation of the Fear Zone deviation.
Greed Zone Settings:
Greed Source: Select the price data point (e.g., close, high, low) used for Greed Zone calculations.
Greed Period: This defines the lookback window for calculating the Greed Zone deviation.
Greed Stdev Period: This sets the period used to calculate the standard deviation of the Greed Zone deviation.
Alert Conditions: Integrated alert conditions notify traders in real-time when a reversal in the fear or greed zone is detected, allowing for timely decision-making.
🔶 Interpreting Indicator
Greed Zone: A Greed Zone is highlighted when the price deviates significantly above the chosen moving average. This suggests market sentiment might be leaning towards greed, potentially indicating a selling opportunity.
Fear Zone Reversal: A Fear Zone is highlighted when the price deviates significantly below the chosen moving average of the selected price source. This suggests market sentiment might be leaning towards fear, potentially indicating a buying opportunity. When the indicator identifies a reversal from a fear zone, it suggests that the market is transitioning from a period of intense selling pressure to a more neutral or potentially bullish state. This is typically indicated by an upward arrow (▲) on the chart, signaling a potential buy opportunity. The fear zone is characterized by high price volatility and overselling, making it a crucial point for traders to consider entering the market.
Greed Zone Reversal: Conversely, a Greed Zone is highlighted when the price deviates significantly above the chosen moving average. This suggests market sentiment might be leaning towards greed, potentially indicating a selling opportunity. When the indicator detects a reversal from a greed zone, it indicates that the market may be moving from an overbought condition back to a more neutral or bearish state. This is marked by a downward arrow (▼) on the chart, suggesting a potential sell opportunity. The greed zone is often associated with overconfidence and high buying activity, which can precede a market correction.
🔶 Why offer multiple moving average types?
By providing various moving average types (SMA, EMA, WMA, VWMA, HMA) , the indicator offers greater flexibility for traders to tailor the indicator to their specific trading strategies and market preferences. Different moving averages react differently to price data and can produce varying signals.
SMA (Simple Moving Average): Provides an equal weighting to all data points within the specified period.
EMA (Exponential Moving Average): Gives more weight to recent data points, making it more responsive to price changes.
WMA (Weighted Moving Average): Allows for custom weighting of data points, providing more flexibility in the calculation.
VWMA (Volume Weighted Moving Average): Considers both price and volume data, giving more weight to periods with higher trading volume.
HMA (Hull Moving Average): A combination of weighted moving averages designed to reduce lag and provide a smoother curve.
Offering multiple options allows traders to:
Experiment: Traders can try different moving averages to see which one produces the most accurate signals for their specific market.
Adapt to different market conditions: Different market conditions may require different moving average types. For example, a fast-moving market might benefit from a faster moving average like an EMA, while a slower-moving market might be better suited to a slower moving average like an SMA.
Personalize: Traders can choose the moving average that best aligns with their personal trading style and risk tolerance.
In essence, providing a variety of moving average types empowers traders to create a more personalized and effective trading experience.
🔶 Disclaimer
Use with Caution: This indicator is provided for educational and informational purposes only and should not be considered as financial advice. Users should exercise caution and perform their own analysis before making trading decisions based on the indicator's signals.
Not Financial Advice: The information provided by this indicator does not constitute financial advice, and the creator (UAlgo) shall not be held responsible for any trading losses incurred as a result of using this indicator.
Backtesting Recommended: Traders are encouraged to backtest the indicator thoroughly on historical data before using it in live trading to assess its performance and suitability for their trading strategies.
Risk Management: Trading involves inherent risks, and users should implement proper risk management strategies, including but not limited to stop-loss orders and position sizing, to mitigate potential losses.
No Guarantees: The accuracy and reliability of the indicator's signals cannot be guaranteed, as they are based on historical price data and past performance may not be indicative of future results.
Swing Trend AnalysisIntroducing the Swing Trend Analyzer: A Powerful Tool for Swing and Positional Trading
The Swing Trend Analyzer is a cutting-edge indicator designed to enhance your swing and positional trading by providing precise entry points based on volatility contraction patterns and other key technical signals. This versatile tool is packed with features that cater to traders of all timeframes, offering flexibility, clarity, and actionable insights.
Key Features:
1. Adaptive Moving Averages:
The Swing Trend Analyzer offers multiple moving averages tailored to the timeframe you are trading on. On the daily chart, you can select up to four different moving average lengths, while all other timeframes provide three moving averages. This flexibility allows you to fine-tune your analysis according to your trading strategy. Disabling a moving average is as simple as setting its value to zero, making it easy to customize the indicator to your needs.
2. Dynamic Moving Average Colors Based on Relative Strength:
This feature allows you to compare the performance of the current ticker against a major index or any symbol of your choice. The moving average will change color based on whether the ticker is outperforming or underperforming the selected index over the chosen period. For example, on a daily chart, if the 21-day moving average turns blue, it indicates that the ticker has outperformed the selected index over the last 21 days. This visual cue helps you quickly identify relative strength, a key factor in successful swing trading.
3. Visual Identification of Price Contractions:
The Swing Trend Analyzer changes the color of price bars to white (on a dark theme) or black (on a light theme) when a contraction in price is detected. Price contractions are highlighted when either of the following conditions is met: a) the current bar is an inside bar, or b) the price range of the current bar is less than the 14-period Average Daily Range (ADR). This feature makes it easier to spot price contractions across all timeframes, which is crucial for timing entries in swing trading.
4. Overhead Supply Detection with Automated Resistance Lines:
The indicator intelligently detects the presence of overhead supply and draws a single resistance line to avoid clutter on the chart. As price breaches the resistance line, the old line is automatically deleted, and a new resistance line is drawn at the appropriate level. This helps you focus on the most relevant resistance levels, reducing noise and improving decision-making.
5. Buyable Gap Up Marker: The indicator highlights bars in blue when a candle opens with a gap that remains unfilled. These bars are potential Buyable Gap Up (BGU) candidates, signaling opportunities for long-side entries.
6. Comprehensive Swing Trading Information Table:
The indicator includes a detailed table that provides essential data for swing trading:
a. Sector and Industry Information: Understand the sector and industry of the ticker to identify stocks within strong sectors.
b. Key Moving Averages Distances (10MA, 21MA, 50MA, 200MA): Quickly assess how far the current price is from key moving averages. The color coding indicates whether the price is near or far from these averages, offering vital visual cues.
c. Price Range Analysis: Compare the current bar's price range with the previous bar's range to spot contraction patterns.
d. ADR (20, 10, 5): Displays the Average Daily Range over the last 20, 10, and 5 periods, crucial for identifying contraction patterns. On the weekly chart, the ADR continues to provide daily chart information.
e. 52-Week High/Low Data: Shows how close the stock is to its 52-week high or low, with color coding to highlight proximity, aiding in the identification of potential breakout or breakdown candidates.
f. 3-Month Price Gain: See the price gain over the last three months, which helps identify stocks with recent momentum.
7. Pocket Pivot Detection with Visual Markers:
Pocket pivots are a powerful bullish signal, especially relevant for swing trading. Pocket pivots are crucial for swing trading and are effective across all timeframes. The indicator marks pocket pivots with circular markers below the price bar:
a. 10-Day Pocket Pivot: Identified when the volume exceeds the maximum selling volume of the last 10 days. These are marked with a blue circle.
b. 5-Day Pocket Pivot: Identified when the volume exceeds the maximum selling volume of the last 5 days. These are marked with a green circle.
The Swing Trend Analyzer is designed to provide traders with the tools they need to succeed in swing and positional trading. Whether you're looking for precise entry points, analyzing relative strength, or identifying key price contractions, this indicator has you covered. Experience the power of advanced technical analysis with the Swing Trend Analyzer and take your trading to the next level.
VWAP Bands [TradingFinder] 26 Brokers Data (Forex + Crypto)🔵 Introduction
Indicators are tools that help analysts predict the price trend of a stock through mathematical calculations on price or trading volume. It is evident that trading volume significantly impacts the price trend of a stock symbol.
The Volume-Weighted Average Price (VWAP) indicator combines the influence of trading volume and price, providing technical analysts with a practical tool.
This technical indicator determines the volume-weighted average price of a symbol over a specified time period. Consequently, this indicator can be used to identify trends and entry or exit points.
🟣 Calculating the VWAP Indicator
Adding the VWAP indicator to a chart will automatically perform all calculations for you. However, if you wish to understand how this indicator is calculated, the following explains the steps involved.
Consider a 5-minute chart. In the first candle of this chart (which represents price information in the first 5 minutes), sum the high, low, and close prices, and divide by 3. Multiply the resulting number by the volume for the period and call it a variable (e.g., X).
Then, divide the resulting output by the total volume for that period to calculate your VWAP. To maintain the VWAP sequence throughout the trading day, it is necessary to add the X values obtained from each period to the previous period and divide by the total volume up to that time. It is worth noting that the calculation method is the same for intervals shorter than a day.
The mathematical formula for this VWAP indicator : VWAP = ∑ (Pi×Vi) / ∑ Vi
🔵 How to Use
Traders might consider the VWAP indicator as a tool for predicting trends. For example, they might buy a stock when the price is above the VWAP level and sell it when the price is below the VWAP.
In other words, when the price is above the VWAP, the price is rising, and when it is below the VWAP, the price is falling. Major traders and investment funds also use the VWAP ratio to help enter or exit stocks with the least possible market impact.
It is important to note that one should not rely solely on the VWAP indicator when analyzing symbols. This is because if prices rise quickly, the VWAP indicator may not adequately describe the conditions. This indicator is generally used for daily or shorter time frames because using longer intervals can distort the average.
Since this indicator uses past data in its calculations, it can be considered a lagging indicator. As a result, the more data there is, the greater the delay.
🟣 Difference Between VWAP and Simple Moving Average
On a chart, the VWAP and the simple moving average may look similar, but these two indicators have different calculations. The VWAP calculates the total price considering volume, while the simple moving average does not consider volume.
In simpler terms, the VWAP indicator measures each day's price change relative to the trading volume that occurred that day. In contrast, the simple moving average implicitly assumes that all trading days have the same volume.
🟣 Reasons Why Traders Like the VWAP Indicator
The VWAP Considers Volume: Since VWAP takes volume into account, it can be more reliable than a simple arithmetic average of prices. Theoretically, one person can buy 200,000 shares of a symbol in one transaction at a single price.
However, during the same time frame, 100 other people might place 200 different orders at various prices that do not total 100,000 shares. In this case, if you only consider the average price, you might be mistaken because trading volume is ignored.
The Indicator Can Help Day Traders: While reviewing your trades, you might notice that the shares you bought at market price are trading below the VWAP indicator.
In this case, there's no need to worry because with the help of VWAP, you always get a price below the average. By knowing the volume-weighted average price of a stock, you can easily make an informed decision about paying more or less than other traders for the stock.
VWAP Can Signal Market Trend Changes: Buying low and selling high can be an excellent strategy for individuals. However, you are looking to buy when prices start to rise and sell your shares when prices start to fall.
Since the VWAP indicator simulates a balanced price in the market, when the price crosses above the VWAP line, one can assume that traders are willing to pay more to acquire shares, and as a result, the market will grow. Conversely, when the price crosses below the line, this can be considered a sign of a downward movement.
🔵 Setting
Period : Indicator calculation time frame.
Source : The Price used for calculations.
Market Ultra Data : If you turn on this feature, 26 large brokers will be included in the calculation of the trading volume.
The advantage of this capability is to have more reliable volume data. You should be careful to specify the market you are in, FOREX brokers and Crypto brokers are different.
Multiplier : Coefficient of band lines.
Stochastic Biquad Band Pass FilterThis indicator combines the power of a biquad band pass filter with the popular stochastic oscillator to provide a unique tool for analyzing price movements.
The Filter Length parameter determines the center frequency of the biquad band pass filter, affecting which frequency band is isolated. Adjusting this parameter allows you to focus on different parts of the price movement spectrum.
The Bandwidth (BW) controls the width of the frequency band in octaves. It represents the bandwidth between -3 dB frequencies for the band pass filter. A narrower bandwidth results in a more focused filtering effect, isolating a tighter range of frequencies.
The %K Length parameter sets the period for the stochastic calculation, determining the range over which the stochastic values are calculated.
The %K Smoothing parameter applies a simple moving average to the %K values to smooth out the oscillator line.
The %D Length parameter sets the period for the %D line, which is a simple moving average of the %K line, providing a signal line for the oscillator.
Key Features of the Stochastic Biquad Band Pass Filter
Biquad filters are known for their smooth response and minimal phase distortion, making them ideal for technical analysis. In this implementation, the biquad filter is configured as a band pass filter, which allows frequencies within a specified band to pass while attenuating frequencies outside this band. This is particularly useful in trading to isolate specific price movements, making it easier to detect patterns and trends within a targeted frequency range.
The stochastic oscillator is a popular momentum indicator that shows the location of the close relative to the high-low range over a set number of periods. Combining it with a biquad band pass filter enhances its effectiveness by focusing on specific frequency bands of price movements.
By incorporating this stochastic biquad band pass filter into your trading toolkit, you can enhance your chart analysis with clearer insights into specific frequency bands of price movements, leading to more informed trading decisions.
Internal Bar Strength IBS [Anan]This indicator calculates and displays the Internal Bar Strength (IBS) along with its moving average. The IBS is a measure that represents where the closing price is relative to the high-low range of a given period.
█ Main Formula
The core of this indicator is the Internal Bar Strength (IBS) calculation. The basic IBS formula is:
ibs = (close - low) / (high - low)
I enhanced the original formula by incorporating a user-defined length parameter. This modification allows for greater flexibility in analysis and interpretation. The extended version enables users to adjust the indicator's length according to their specific needs or market conditions. Notably, setting the length parameter to 1 reproduces the behavior of the original formula, maintaining backward compatibility while offering expanded functionality:
ibs = (close - ta.lowest(low, ibs_length)) / (ta.highest(high, ibs_length) - ta.lowest(low, ibs_length))
Where:
- `close` is the closing price of the current bar
- `lowest low` is the lowest low price over the specified IBS length
- `highest high` is the highest high price over the specified IBS length
█ Key Features
- Calculates IBS using a user-defined length
- Applies a moving average to the IBS values
- Offers multiple moving average types
- Includes optional Bollinger Bands or Donchian Channel overlays
- Visualizes bull and bear areas
█ Inputs
- IBS Length: The period used for IBS calculation
- MA Type: The type of moving average applied to IBS (options: SMA, EMA, SMMA, WMA, VWMA, Bollinger Bands, Donchian)
- MA Length: The period used for the moving average calculation
- BB StdDev: Standard deviation multiplier for Bollinger Bands
█ How to Use and Interpret
1. IBS Line Interpretation:
- IBS values range from 0 to 1
- Values close to 1 indicate the close was near the high, suggesting a bullish sentiment
- Values close to 0 indicate the close was near the low, suggesting a bearish sentiment
- Values around 0.5 suggest the close was near the middle of the range
2. Overbought/Oversold Conditions:
- IBS values above 0.8 (teal zone) may indicate overbought conditions
- IBS values below 0.2 (red zone) may indicate oversold conditions
- These zones can be used to identify potential reversal points
3. Trend Identification:
- Consistent IBS values above 0.5 may indicate an uptrend
- Consistent IBS values below 0.5 may indicate a downtrend
4. Using Moving Averages:
- The yellow MA line can help smooth out IBS fluctuations
- Crossovers between the IBS and its MA can signal potential trend changes
5. Bollinger Bands/Donchian Channel:
- When enabled, these can provide additional context for overbought/oversold conditions
- IBS touching or exceeding the upper band may indicate overbought conditions
- IBS touching or falling below the lower band may indicate oversold conditions
Remember that no single indicator should be used in isolation. Always combine IBS analysis with other technical indicators, price action analysis, and broader market context for more reliable trading decisions.
Nasan Moving AverageNasan Moving Average belong to the group of moving average which provides a high degree of smoothness with very low lag.
The calculation process involves several steps to analyze the typical price of a financial asset over specific periods. It starts by computing a simple moving average and standard deviation of the typical price. Then, it standardizes (differencing TP - Average Typical price over previous n periods) the price and applies an inverse hyperbolic sine transformation to the standardized value. The transformed values are summed cumulatively, and various weighted moving averages are calculated to adjust and smooth the data. The final output is a smoothed signal with reduced lag.
Input Parameters:
len: Differencing length (default 21, Use a minimum of 5 and for lower time frames less than 15 min use values between 300 -3000)
len1: Correction Factor Length 1 (default 21, this determines the length of the MA you want , eg. 10 MA, 50 MA, 100 MA, )
len2: Correction Factor Length 2 (default 9, this works best if it is ~ </=1/2 of len1 )
len3: Smoothing Length (default 5, I would not change this and only use if I want to introduce lag where you want to use it for cross over strategies).
Differencing and Standardization:
The code calculates the standardized price a by differencing the typical price and normalizing it using the mean and standard deviation. This step standardizes the price changes.
Transformation:
The transformation using logarithms and square roots (b) aim to stabilize the variance and make the distribution more normal-like, improving the robustness of the cumulative sum c.
Cumulative Sum:
The cumulative sum c of the transformed series helps in integrating the series over time, capturing the overall trend and movement.
Correction Factors:
Correction factors c1 and c4 adjust the cumulative sum based on weighted averages, to correct any biases or to align it with the typical price.
Smoothing:
The final result c6 is smoothed using a weighted moving average, reducing noise and making it easier to interpret trends.
Moving average to price cloudHi all!
This indicator shows when the price crosses the defined moving average. It plots a green or red cloud (depending on trend) and the moving average. It also plots an arrow when the trend changes (this can be disabled in 'style'->'labels' in the settings).
The moving average itself can be used as dynamic support/resistance. The trend will change based on your settings (described below). By default the trend will change when the whole bar is above/below the moving average for 2 bars (that's closed). This can be changed by "Source" and "Bars".
Settings
• Length (choose the length of the moving average. Defaults to 21)
• Type (choose what type of moving average).
- "SMA" (Simple Moving Average)
- "EMA" (Exponential Moving Average)
- "HMA" (Hull Moving Average)
- "WMA" (Weighted Moving Average)
- "VWMA" (Volume Weighted Moving Average)
- "DEMA" (Double Exponential Moving Average)
Defaults to"EMA".
• Source (Define the price source that must be above/below the moving average for the trend to change. Defaults to 'High/low (passive)')
- 'Open' The open of the bar has to cross the moving average
- 'Close' The close of the bar has to cross the moving average
- 'High/low (passive)' In a down trend: the low of the bar has to cross the moving average
- 'High/low (aggressive)' In a down trend: the high of the bar has to cross the moving average
• Source bar must be close. Defaults to 'true'.
• Bars (Define the number bars whose value (defined in 'Source') must be above/below the moving average. All the bars (defined by this number) must be above/below the moving average for the trend to change. Defaults to 2.)
Let me know if you have any questions.
Best of trading luck!
Moving Average Bands with Signals [UAlgo]The "Moving Average Bands with Signals combines various moving average types with ATR-based bands to help traders identify potential support and resistance levels.
It plots moving average bands with upper and lower support/resistance levels based on the Average True Range (ATR) and user-defined settings.Additionally, the script generates buy/sell signals based on price crossing above or below the bands.
🔶 Key Features
Multiple Moving Average Types:
Supports various moving average calculations including Arnaud Legoux Moving Average (ALMA), Exponential Moving Average (EMA), Double Exponential Moving Average (DEMA), Triple Exponential Moving Average (TEMA), Kaufman Adaptive Moving Average (KAMA), Hull Moving Average (HMA), Least Squares Moving Average (LSMA), Simple Moving Average (SMA), Triangular Moving Average (TMA), Volume-Weighted Moving Average (VWMA), Weighted Moving Average (WMA), and Zero-Lag Moving Average (ZLMA).
Customizable ATR Bands:
Integrates the Average True Range (ATR) to calculate dynamic support and resistance bands around the moving average. The multiplier for the bands is user-adjustable, allowing for finer control over the sensitivity and width of the bands.
Signal Generation:
Provides visual signals on the chart when the price interacts with the support or resistance bands. Users can choose between using the wick or the close price to generate these signals, adding an extra layer of customization based on their trading style.
Flexible Input Parameters:
Allows users to input parameters for moving average length, ATR length, band multiplier, and signal type. Additional settings are available for specific moving average types, such as ALMA's offset and sigma, KAMA's fast and slow periods, and LSMA's offset.
🔶 Disclaimer
This script is provided for educational purposes only and should not be considered financial advice.
Trading financial instruments involves substantial risk and can result in significant financial losses.
The script’s performance in the past is not indicative of future results, and no guarantees are made regarding its accuracy, reliability, or performance.
3 MA Strategy [Projeadam] OVERVIEW:
3 MA Strategy indicator displays and analyzes three types of moving averages (MAs) on a price chart. The primary function of this indicator is to identify buy and sell signals based on the crossover and crossunder events of the specified moving averages. It provides extensive customization options for the types and settings of the moving averages, and it can visualize these signals on the chart through labels and background colors.
Algorithm:
1. Initialization and Function Definition
• Define the ma_function to calculate different types of moving averages (EMA, SMA, RMA, WMA) based on user inputs.
2. Inputs and Moving Average Calculation
• Gather user inputs for three moving averages, including length, source, line width, color, and type.
• Calculate the values for the three moving averages using the ma_function.
3. Plotting Moving Averages
• Plot the calculated moving averages on the chart with the specified settings.
4. Buy and Sell Conditions
• Establish initial buy and sell conditions based on the crossover and crossunder of the first two moving averages.
• Adjust these conditions if the third moving average is enabled, considering its relationship with the close price.
5. Signal Control Logic
• Use variables (last_buy, last_sell, sinyal_control) to manage the signal generation process, ensuring a buy signal is followed by a sell signal and vice versa.
6. Signal Label and Background
• Add labels and background colors to the chart based on the generated signals if the respective settings are enabled.
7. Plotting Additional Information
• If the third moving average is enabled and the label_show_price setting is active, plot additional lines and labels to indicate the position of the moving average.
8. Alerts
• Set up alert conditions to notify the user when buy or sell conditions are met.
How Does the Indicator Work?
Moving Average Calculation
• The script calculates three different moving averages using the user-defined settings. Each moving average can be an EMA, SMA, RMA, or WMA and is calculated using the specified length and source.
Signal Generation
• Buy signals are generated when the first moving average crosses above the second moving average. If the third moving average is enabled, the close price must also be above the third moving average for a buy signal.
• Sell signals are generated when the first moving average crosses below the second moving average. If the third moving average is enabled, the close price must also be below the third moving average for a sell signal.
Visualization
• The moving averages are plotted on the chart with the colors and line widths specified by the user.
• Buy and sell signals are indicated by labels ('BUY' for buy signals, 'SELL' for sell signals) and optionally by changing the background color of the chart.
Alerts
• Alerts are set up to notify the user of buy or sell signals, as well as when either condition is met.
Settings Panel
MOVING AVERAGE SETTINGS 1 (BUY - SELL)
• Length: Length of the first moving average.
• Source: Source of the first moving average (e.g., close, open).
• Line Width: Line width of the first moving average.
• Color: Color of the first moving average.
• Moving Average Type: Type of the first moving average (EMA, SMA, RMA, WMA).
MOVING AVERAGE SETTINGS 2 (BUY - SELL)
• Length: Length of the second moving average.
• Source: Source of the second moving average.
• Line Width: Line width of the second moving average.
• Color: Color of the second moving average.
• Moving Average Type: Type of the second moving average (EMA, SMA, RMA, WMA).
FINAL MOVING AVERAGE SETTINGS
• Enable 3rd Average?: Toggle to activate the third moving average.
• Length: Length of the third moving average.
• Source: Source of the third moving average.
• Line Width: Line width of the third moving average.
• Color: Color of the third moving average.
• Moving Average Type: Type of the third moving average (EMA, SMA, RMA, WMA).
BUY - SELL SETTINGS
• Enable Background?: Toggle to activate background color changes based on signals.
• Enable Signal Labels?: Toggle to activate signal labels.
• Enable Price Labels?: Toggle to activate price labels.
• Sell Background: Background color for sell signals.
• Buy Background: Background color for buy signals.
Benefits of the 3 MA Indicator
1. Versatility and Customization
• The indicator supports multiple types of moving averages (EMA, SMA, RMA, WMA), allowing users to choose the one that best fits their trading strategy.
• Users can customize the length, source, line width, and color of each moving average, providing flexibility to tailor the indicator to their preferences.
2. Comprehensive Signal Generation
• The indicator generates clear buy and sell signals based on the crossover and crossunder events of the moving averages. This helps traders make informed decisions about entry and exit points.
• It includes an optional third moving average to filter signals, potentially reducing false signals and improving accuracy.
3. Visual Aids for Better Decision Making
• The indicator plots the moving averages on the chart, making it easy for traders to visualize trends and market conditions.
• Signal labels ('BUY' and 'SELL') are displayed on the chart, providing immediate visual cues for trading actions.
• The background color changes based on the signals, adding another layer of visual confirmation for traders.
4. Alert Notifications
• The indicator includes alert conditions for buy and sell signals, as well as a combined alert for either condition. This ensures that traders are notified in real-time when a signal is generated, allowing for timely action.
5. Historical Analysis
• By plotting moving averages and signals on the chart, traders can conduct historical analysis to see how the indicator would have performed in the past. This can help in evaluating the effectiveness of the trading strategy.
6. Enhanced Trading Confidence
• The use of multiple moving averages and customizable settings can enhance a trader's confidence in their trading decisions. By relying on objective criteria for signals, traders can reduce emotional trading and adhere to a disciplined approach.
7. Improved Market Understanding
• The indicator helps traders understand market trends and momentum by analyzing the relationships between different moving averages. This can lead to a deeper insight into market behavior and better trading strategies.
8. Ease of Use
• The indicator is straightforward to implement and use within TradingView, making it accessible to traders of all experience levels. The customizable settings panel ensures that even novice traders can set it up according to their needs.
Johnny's Adjusted BB Buy/Sell Signal"Johnny's Adjusted BB Buy/Sell Signal" leverages Bollinger Bands and moving averages to provide dynamic buy and sell signals based on market conditions. This indicator is particularly useful for traders looking to identify strategic entry and exit points based on volatility and trend analysis.
How It Works
Bollinger Bands Setup: The indicator calculates Bollinger Bands using a specified length and multiplier. These bands serve to identify potential overbought (upper band) or oversold (lower band) conditions.
Moving Averages: Two moving averages are calculated — a trend moving average (trendMA) and a long-term moving average (longTermMA) — to gauge the market's direction over different time frames.
Market Phase Determination: The script classifies the market into bullish or bearish phases based on the relationship of the closing price to the long-term moving average.
Strong Buy and Sell Signals: Enhanced signals are generated based on how significantly the price deviates from the Bollinger Bands, coupled with the average candle size over a specified lookback period. The signals are adjusted based on whether the market is bullish or bearish:
In bullish markets, a strong buy signal is triggered if the price significantly drops below the lower Bollinger Band. Conversely, a strong sell signal is activated when the price rises well above the upper band.
In bearish markets, these signals are modified to be more conservative, adjusting the thresholds for triggering strong buy and sell signals.
Features:
Flexibility: Users can adjust the length of the Bollinger Bands and moving averages, as well as the multipliers and factors that determine the strength of buy and sell signals, making it highly customizable to different trading styles and market conditions.
Visual Aids: The script vividly plots the Bollinger Bands and moving averages, and signals are visually represented on the chart, allowing traders to quickly assess trading opportunities:
Regular buy and sell signals are indicated by simple shapes below or above price bars.
Strong buy and sell signals are highlighted with distinctive colors and placed prominently to catch the trader's attention.
Background Coloring: The background color changes based on the market phase, providing an immediate visual cue of the market's overall sentiment.
Usage:
This indicator is ideal for traders who rely on technical analysis to guide their trading decisions. By integrating both Bollinger Bands and moving averages, it provides a multi-faceted view of market trends and volatility, making it suitable for identifying potential reversals and continuation patterns. Traders can use this tool to enhance their understanding of market dynamics and refine their trading strategies accordingly.
AllTheUpsTheresAlwaysDowns "AllTheUpsTheresAlwaysDowns" ☆ATUTAD☆ // w%r + ma indicator designed for forex trading.
This indicator combines the Williams %R, moving averages, and session tracking.
Key Inputs:
Williams%Range Period: Adjusts the sensitivity of the Williams %R calculation.
Moving Average Period: Defines the period for the moving average used in the indicator.
Overbought and Oversold Thresholds: Sets the thresholds for identifying overbought and oversold conditions.
Features:
Williams %R Calculation: Calculates the Williams %R, a momentum oscillator that measures overbought and oversold levels.
Moving Averages: Plots two moving averages to capitalize on and visualize trend direction.
Session Tracking: Identifies the start and end of trading sessions (Tokyo, London, New York) for better session-based analysis.
Signal Generation: Generates buy/sell signals based on Williams %R levels and moving average crossovers.
Color Coding: Visualizes color-coded bars and shapes to highlight different market conditions and signal types.
Alerts: For buy/sell signals and overbought/oversold conditions to prompt timely actions.
Usage Tips:
Interpret Signals: Trend direction through buy/sell signals and overbought/oversold trend,- reversal / breakout line conditions for potential trading opportunities.
Session Awareness: Take into account the trading sessions (Tokyo, London, New York) to move along with the market dynamics during different times of the day.
Confirmation: Use additional technical analysis tools to confirm signals before executing trades. For example the Williams Percetange Range indicator.
Risk Management: Trade with proper risk management strategies to avoid potential losses.
HappyTrading
First In, First Out Moving AverageThis script is a tool designed to calculate a First In, First Out (FIFO) Moving Average (MA) using traded prices and volumes. Additionally, it computes the Point of Control (PoC) from, which identifies the price levels (developing POC) with the maximum volume. The script is built to provide traders with a comprehensive analysis of price movements and volume dynamics, enhancing their understanding of market trends and potential entry/exit points.
Understanding the Mechanics:
The script maintains arrays for prices and volumes, where hypothetical trades are added.
For long trades (identified by red candles/bars), traded prices and volumes are appended to the respective arrays.
Short trades (identified by green candles/bars) trigger the removal of volumes from the arrays following the FIFO principle.
This process ensures the adjustment of partial or complete removal of oldest entries based on traded volume.
Analyzing Profit and Loss (PnL):
The script also tracks a hypothetical Profit and Loss (PnL) to understand whether the outcome is in red (negative) or green (positive) - color of the FIFO MA.
Interpreting the Results:
Once the script is applied to the chart, traders can observe the FIFO Moving Average (MA) and Point of Control (PoC) lines plotted.
By analyzing these lines and the associated colors (indicating positive or negative PnL), traders can make informed decisions regarding market trends, support/resistance levels and potential trading opportunities.
Range Finder [UAlgo]🔶 Description:
The "Range Finder " indicator aims at identifying and visualizing price ranges within a specified number of candles. By utilizing the Average True Range (ATR) indicator and Simple Moving Average (SMA), it detects potential breakout conditions and tracks consecutive candles that remain within the breakout range. This indicator offers flexibility by allowing users to customize settings such as range length, method for determining range breaks (based on either candle close or wick), and visualization options for displaying range breaks on the chart.
🔶 Key Features
Identifying Ranges: The Range Finder automatically adapts to the market by continuously evaluating the Average True Range (ATR) and its Simple Moving Average (SMA). This helps in dynamically adjusting the range based on market volatility.
Range Length: Users can specify the number of candles to be used for constructing the range via the "Range Length" input setting. This allows for customization based on trading strategies and preferences.
Range Break Method: The indicator offers the flexibility to choose between two methods for identifying range breaks. Users can select between "Close" or "Wick" based on their preference for using the closing price or the highs and lows (including wicks) of candles for defining the breakout.
Show Range Breaks: This option enables visual representation of range breaks on the chart. When activated, labels with the letter "B" will appear at the breakout point, colored according to the breakout direction (upward breakouts in the chosen up range color and downward breakouts in the chosen down range color).
Range Color Customization: The indicator provides the ability to personalize the visual appearance of the range by selecting preferred colors for ranges indicating potential upward and downward breakouts.
🔶 Disclaimer
It's important to understand that the Range Finder indicator is intended for informational purposes only and should not be solely relied upon for making trading decisions. Trading financial instruments involves inherent risks, and past performance is not necessarily indicative of future results.
The OG Outback [TTF]The Outback indicator
After a major overhaul of our Outback strategy, we decided that we would make our original version available for anyone to use.
The fundamental element of this indicator is based on price action relative to a slow moving average. That said, given that price will always tend towards a moving average, we have also implemented a method for helping filter out false signals leveraging a "consolidation cloud" and fast moving average. This, coupled with references to a customized version of the Relative Strength Index (RSI), has enabled us to provide significantly higher quality signals relating to price crossing a moving average.
Note: For this version, we have only prepared a single set of conditions and alerts (as noted by the 🦘 symbols). However it's worth noting there are several variations that can be done with some fundamental technical analysis and referencing additional indicators that can take this foundation and build upon it for a substantial increase in risk/reward and profit targets.
Moving Average PropertiesThis indicator calculates and visualizes the Relative Smoothness (RS) and Relative Lag (RL) or call it accuracy of a selected moving average (MA) in comparison to the SMA of length 2 (the lowest possible length for a moving average and also the one closest to the price).
Median RS (Relative Smoothness):
Interpretation: The median RS represents the median value of the Relative Smoothness calculated for the selected moving average across a specified look-back period (max bar lookback is set at 3000).
Significance: A more negative (larger) median RS suggests that the chosen moving average has exhibited smoother price behavior compared to a simple moving average over the analyzed period. A less negative value indicates a relatively choppier price movement.
Median RL (Relative Lag):
Interpretation: The median RL represents the median value of the Relative Lag calculated for the selected moving average compared to a simple moving average of length 2.
Significance: A higher median RL indicates that the chosen moving average tends to lag more compared to a simple moving average. Conversely, lower values suggest less lag in the selected moving average.
Ratio of Median RS to Median RL:
Interpretation: This ratio is calculated by dividing the median RS by the median RL.
Significance: Traders might use this ratio to assess the balance between smoothness and lag in the chosen moving average. This a measure of for every % of lag what is the smoothness achieved. This can be used a benchmark to decide what length to choose for a MA to get an equivalent value between two stocks. For example a TESLA stock on a 15 minute time frame with a length of 12 has a value (ratio of RS/RL) of -150 , where as APPLE stock of length 35 on a 15 minute chart also has a value (ratio of RS/RL) of -150.
I imply that a MA of length 12 working on TESLA stock is equivalent to MA of length 35 on a APPLE stock. (THIS IS A EXAMPLE).
My assumption is that finding the right moving average length for a stock isn't a one-size-fits-all situation. It's not just about using a fixed length; it's about adapting to the unique characteristics of each stock. I believe that what works for one stock might not work for another because they have different levels of smoothness or lag in their price movements. So, instead of applying the same length to all stocks, I suggest adjusting the length of the moving average to match the values that we know work best for achieving the desired smoothness or lag or its ratio (RS/RL). This way, we're customizing the indicator for each stock, tailoring it to their individual behaviors rather than sticking to a one-size-fits-all approach.
Users can choose from various types of moving averages (EMA, SMA, WMA, VWMA, HMA) and customize the length of the moving average. RS measures the smoothness of the MA, while RL measures its lag compared to a simple moving average. The script plots the median RS and RL values, the selected MA, and the ratio of median RS to median RL on the price chart. Traders can use this information to assess the performance of different moving averages and potentially inform their trading decisions.
MTF VWAPThis indicator is an enhanced version of the traditional VWAP, providing traders with multiple timeframe views, automatic session anchoring, and customization options for optimized technical analysis.
Key Features:
1. Multiple Timeframes, One View : Visualize Daily, Weekly, Monthly, and Yearly VWAP calculations simultaneously on a single chart.
2. Automatic Anchoring : The indicator intelligently auto-anchors each VWAP calculation to the start of its respective session. This ensures accurate readings and streamlines your analysis by eliminating the need for manual adjustments.
3. Customizability : Tailor the appearance of the indicator with fully customizable colors and the ability to select your preferred price source (e.g., high, low, close, hlc3, hlcc4, or a custom one).
Volume Candle DistributionThe Volume Candle Distribution (VCD) indicator examines the volume distribution across candle type, distinguishes between neutral, bullish and bearish volume pressures.
The VCD indicator calculates and displays the cumulative volume of bullish and bearish candles over a user-defined period, aggregates the volumes of bullish and bearish candles separately and plots them.
Bullish Volume : This is accumulated when the closing price of a candle is higher than the opening price, the VCD adds up the volume of bullish candle within the user-defined period, and consequently subtracts the volume when bearish candle.
Bearish Volume : Conversely, when the closing price is lower than the opening price, the volume of that candle is considered bearish, the VCD sums the volume of bearish candles over the same period, and consequently subtracts the volume when bullish candle.
Neutral Volume : In cases where the opening and closing prices are equal, the volume of that candle is treated as neutral, and the VCD subtracts the volume from both candles.
The 3 Simple Moving Average (SMAs) included is based volume calculated separately for both bullish and bearish volume data, and the sum of them.
Qu_Trend+
composition
- Consists of a thick trend line and a thin yellow line.
- The largest (green/red) lines indicate rising and falling markets.
- This line represents the 13-candle moving average of Tilson T3.
- The reason for 13 candles is because it best matches the recent market price based on Bitcoin.
- This value cannot be changed, so if you need it, please modify the public code and use it.
- The yellow line is the MA20 line, the ‘Bollinger Band center line’
(UI will show whether this line has been breakout)
- The same algorithm as 20 of the basic moving average (close standard) is applied.
- The algorithm for breakthrough is calculated based on real-time prices, not based on closing prices.
An additional short-term SMA is created, and whether it crosses the SMA is classified as a breakout/resistance.
How to use it
- If the trend line becomes gentle, it may indicate a change in trend when + MA20 is broken.
- While the slope of the trend line is steep, it indicates that the trend is difficult to change.
(If the trend changes at this time, it is likely to move sideways)
- If the trend changes continuously, it is a sideways market.
At this time, watch out for the movement of the end point where the sideways trend ends.
MA+ ProjectionThe "MA+ Projection" indicator is designed to visualize the potential future direction of a moving average, taking into account the impact of historical data loss. It is primarily aimed at providing a practical perspective on how moving averages could evolve as older data points are no longer considered.
Key Features:
Supported Moving Averages: SMA, EMA, WMA, VWMA, and VAWMA (Volume Adjusted WMA).
Flexible Time Span Settings: Customize the moving average length in bars, minutes, or days.
Adjustable Projection Scope: Set a percentage of the measurement to project forward.
Projection 'Cone': Show/hide the deviation and control the multiple.
Use Last Source Value: An option to add the latest known value to the moving window instead of only letting the window shrink. (Enabled by default.)
How It Works:
Given the specified parameters, it takes the selected moving average type (a known formula like SMA, EMA, or WMA), and projects the future data points by continuing to move the data 'window' forward without adding any more data. By default, it extends the average by assuming the price hasn't changed after the last bar. Alternatively, the projection can be the result of shrinking the window as it moves forward without adding any new data points.
Note:
This tool is for visual projection, not prediction. Its purpose is to aid in the analysis of potential future trends based on historical data, not to provide definitive market forecasts.
SMA Cross with a Price FilterA moving average strategy generates an entry (buy) signal when the price goes above the moving average, and an exit (sell) signal when the price goes below the moving average. But it gives lots of whipsaws and noise depends on the moving average we use. A fast moving average gives more whipsaws and a slow moving average gives less whipsaws. To reduce the noise/whipsaws, we can add a filter on a fast/slow moving average. It will improve entry/exit performance significantly specially for those who don't want to watch the market actively.
I created this indicator with a price filter. This means the price of an underlying asset must be at least a specific percentage above its moving average to generate a buy signal and a specific percentage below its moving average to generate a sell signal. This price filter can also be a confirmation after the price crosses above/below its SMA. I couldn't find any indicator yet based on this idea. So I wrote this indicator and publishing it so it helps those who are interested.
I use 200 SMA and 3% price filter as default and using SPY as an example. So,
ENTRY signal when the closing price of SPY is 3% above its 200 SMA.
EXIT signal when the closing price of SPY is 3% below its 200 SMA.
Enjoy and let me know if it works.
** This chart only generates entry (buy) and exit (sell) signals. Please, do your own diligence to make any investment or trading decisions.
Alpha Momentum Trade - AMT (QUAD Financial)The "Alpha Momentum Trend" indicator was conceived by Tiago Friedrich and programmed by Conrado Villaça.
The indicator description applies to the daily chart. When used on other timeframes, the indicator also changes its signals based on the timeframe used.
It has five fields, from top to bottom:
1. "ATR Multiple MA" greater than multiple: shows how many candles the asset stayed 7 times the ATR (average true range) above the 50-period simple moving average (SMA) in the last 126 candles. The purpose is to identify the strength of the asset because the more times it stayed at this distance from the SMA 50, the greater the acceleration of its prices tends to be, indicating a high momentum asset. You can change the period of the SMA in the indicator settings.
2. ATR% Multiple from MA: shows the multiple of ATR that the asset is from the same SMA as in the upper field. The default is the SMA 50, and the indicator helps identify interesting regions to take profits from long positions. When the asset is more than 7 ATRs above the SMA 50, the asset is considered "stretched," and a correction or price consolidation becomes likely. For high beta assets with a very strong trend, you can use a multiple of 10 ATRs for this purpose.
3. ATR% Multiple from 52w Low: shows the multiple of ATR that the asset is in relation to the 52-week low price. The higher the number, the more the asset has risen relative to its volatility standards, indicating a stronger trend. For momentum traders, it's ideal for the asset to be at least 15 ATRs above the minimum for this period to ensure that it's in a strong uptrend and far from the lows.
4. Longest streak above SMA: within the last 126 candles, it shows the longest streak of days when the asset didn't close below a specific simple moving average. The default definition is with the 10-day SMA, but you can change it in the indicator settings. The more consecutive days the asset can stay above the SMA10, the sign that its trend is consistent and not very volatile, which is desirable. Ideally, an asset should have previously formed an uptrend by staying at least 20 consecutive days above the SMA10.
5. Longest streak above EMA: within the last 126 candles, it shows the longest streak of days when the asset didn't close below a specific exponential moving average. The default definition is with the 21-day EMA, but you can change it in the indicator settings. The more consecutive days the asset can stay above the EMA21, the sign that its trend is consistent and not very volatile, which is desirable. Ideally, an asset should have previously formed an uptrend by staying at least 35 consecutive days above the EMA21.
It's also possible to visualize on the chart the moving averages used for the calculation of the "ATR Multiple MA," "Longest streak above SMA," and "Longest streak above EMA". In the default configuration, this results in a simple 50-day moving average, a simple 10-day moving average, and an exponential 21-day moving average being displayed on the chart, respectively.
Z-ScoreThe "Z-Score" indicator is a unique and powerful tool designed to help traders identify overbought and oversold conditions in the market. Below is an explanation of its features, usefulness, and what makes it special:
Features:
Z-Score Calculation: The indicator calculates the Z-Score, a statistical measure that represents how far the current price is from the moving average (MA) in terms of standard deviations. It helps identify extreme price movements.
Customizable Parameters: Traders can adjust key parameters such as the Z-Score threshold, the type of MA (e.g., SMA, EMA), and the length of the moving average to suit their trading preferences.
Signal Options: The indicator offers flexibility in terms of signaling. Traders can choose whether to trigger signals when the Z-Score crosses the specified threshold or when it moves away from the threshold.
Visual Signals : Z-Score conditions are represented visually on the chart with color-coded background highlights. Overbought conditions are marked with a red background, while oversold conditions are indicated with a green background.
Information Table: A dynamic information table displays essential details, including the MA type, MA length, MA value, standard deviation, current price, and Z-Score. This information table helps traders make informed decisions.
Usefulness:
Overbought and Oversold Signals: Z-Score is particularly valuable for identifying overbought and oversold market conditions. Traders can use this information to potentially enter or exit positions.
Statistical Analysis: The Z-Score provides a statistical measure of price deviation, offering a data-driven approach to market analysis.
Customization: Traders can customize the indicator to match their trading strategies and preferences, enhancing its adaptability to different trading styles.
Visual Clarity: The visual signals make it easy for traders to quickly spot potential trade opportunities on the price chart.
In summary, the Z-Score indicator is a valuable tool for traders looking to incorporate statistical analysis into their trading strategies. Its customizability, visual signals, and unique statistical approach make it an exceptional choice for identifying overbought and oversold market conditions and potential trading opportunities.
