D-Shape Breakout Signals [LuxAlgo]The D-Shape Breakout Signals indicator uses a unique and novel technique to provide support/resistance curves, a trailing stop loss line, and visual breakout signals from semi-circular shapes.
🔶 USAGE
D-shape is a new concept where the distance between two Swing points is used to create a semi-circle/arc, where the width is expressed as a user-defined percentage of the radius. The resulting arc can be used as a potential support/resistance as well as a source of breakouts.
Users can adjust this percentage (width of the D-shape) in the settings ( "D-Width" ), which will influence breakouts and the Stop-Loss line.
🔹 Breakouts of D-Shape
The arc of this D-shape is used for detecting breakout signals between the price and the curve. Only one breakout per D-shape can occur.
A breakout is highlighted with a colored dot, signifying its location, with a green dot being used when the top part of the arc is exceeded, and red when the bottom part of the arc is surpassed.
When the price reaches the right side of the arc without breaking the arc top/bottom, a blue-colored dot is highlighted, signaling a "Neutral Breakout".
🔹 Trailing Stop-Loss Line
The script includes a Trailing Stop-Loss line (TSL), which is only updated when a breakout of the D-Shape occurs. The TSL will return the midline of the D-Shape subject to a breakout.
The TSL can be used as a stop-loss or entry-level but can also act as a potential support/resistance level or trend visualization.
🔶 DETAILS
A D-shape will initially be colored green when a Swing Low is followed by a Swing High, and red when a Swing Low is followed by a Swing High.
A breakout of the upper side of the D-shape will always update the color to green or to red when the breakout occurs in the lower part. A Neutral Breakout will result in a blue-colored D-shape. The transparency is lowered in the event of a breakout.
In the event of a D-shape breakout, the shape will be removed when the total number of visible D-Shapes exceeds the user set "Minimum Patterns" setting. Any D-shape whose boundaries have not been exceeded (and therefore still active) will remain visible.
🔹 Trailing Stop-Loss Line
Only when a breakout occurs will the midline of the D-shape closest to the closing price potentially become the new Trailing Stop value.
The script will only consider middle lines below the closing price on an upward breakout or middle lines above the closing price when it concerns a downward breakout.
In an uptrend, with an already available green TSL, the potential new Stop-Loss value must be higher than the previous TSL value; while in a downtrend, the new TSL value must be lower.
The Stop-Loss line won't be updated when a "Neutral Breakout" occurs.
🔶 SETTINGS
Swing Length: Period used for the swing detection, with higher values returning longer-term Swing Levels.
🔹 D-Patterns
Minimum Patterns: Minimum amount of visible D-Shape patterns.
D-Width: Width of the D-Shape as a percentage of the distance between both Swing Points.
Included Swings: Include "Swing High" (followed by a Swing Low), "Swing Low" (followed by a Swing High), or "Both"
Style Historical Patterns: Show the "Arc", "Midline" or "Both" of historical patterns.
🔹 Style
Label Size/Colors
Connecting Swing Level: Shows a line connecting the first Swing Point.
Color Fill: colorfill of Trailing Stop-Loss
밴드 및 채널
Curved Price Channels (Zeiierman)█ Overview
The Curved Price Channels (Zeiierman) is designed to plot dynamic channels around price movements, much like the traditional Donchian Channels, but with a key difference: the channels are curved instead of straight. This curvature allows the channels to adapt more fluidly to price action, providing a smoother representation of the highest high and lowest low levels.
Just like Donchian Channels, the Curved Price Channels help identify potential breakout points and areas of trend reversal. However, the curvature offers a more refined approach to visualizing price boundaries, making it potentially more effective in capturing price trends and reversals in markets that exhibit significant volatility or price swings.
The included trend strength calculation further enhances the indicator by offering insight into the strength of the current trend.
█ How It Works
The Curved Price Channels are calculated based on the asset's average true range (ATR), scaled by the chosen length and multiplier settings. This adaptive size allows the channels to expand and contract based on recent market volatility. The central trendline is calculated as the average of the upper and lower curved bands, providing a smoothed representation of the overall price trend.
Key Calculations:
Adaptive Size: The ATR is used to dynamically adjust the width of the channels, making them responsive to changes in market volatility.
Upper and Lower Bands: The upper band is calculated by taking the maximum close value and adjusting it downward by a factor proportional to the ATR and the multiplier. Similarly, the lower band is calculated by adjusting the minimum close value upward.
Trendline: The trendline is the average of the upper and lower bands, representing the central tendency of the price action.
Trend Strength
The Trend Strength feature in the Curved Price Channels is a powerful feature designed to help traders gauge the strength of the current trend. It calculates the strength of a trend by analyzing the relationship between the price's position within the curved channels and the overall range of the channels themselves.
Range Calculation:
The indicator first determines the distance between the upper and lower curved channels, known as the range. This range represents the overall volatility of the price within the given period.
Range = Upper Band - Lower Band
Relative Position:
The next step involves calculating the relative position of the closing price within this range. This value indicates where the current price sits in relation to the overall range.
RelativePosition = (Close - Trendline) / Range
Normalization:
To assess the trend strength over time, the current range is normalized against the maximum and minimum ranges observed over a specified look-back period.
NormalizedRange = (Range - Min Range) / (Max Range - Min Range)
Trend Strength Calculation:
The final Trend Strength is calculated by multiplying the relative position by the normalized range and then scaling it to a percentage.
TrendStrength = Relative Position * Normalized Range * 100
This approach ensures that the Trend Strength not only reflects the direction of the trend but also its intensity, providing a more comprehensive view of market conditions.
█ Comparison with Donchian Channels
Curved Price Channels offer several advantages over Donchian Channels, particularly in their ability to adapt to changing market conditions.
⚪ Adaptability vs. Fixed Structure
Donchian Channels: Use a fixed period to plot straight lines based on the highest high and lowest low. This can be limiting because the channels do not adjust to volatility; they remain the same width regardless of how much or how little the price is moving.
Curved Price Channels: Adapt dynamically to market conditions using the Average True Range (ATR) as a measure of volatility. The channels expand and contract based on recent price movements, providing a more accurate reflection of the market's current state. This adaptability allows traders to capture both large trends and smaller fluctuations more effectively.
⚪ Sensitivity to Market Movements
Donchian Channels: Are less sensitive to recent price action because they rely on a fixed look-back period. This can result in late signals during fast-moving markets, as the channels may not adjust quickly enough to capture new trends.
Curved Price Channels: Respond more quickly to changes in market volatility, making them more sensitive to recent price action. The multiplier setting further allows traders to adjust the channel's sensitivity, making it possible to capture smaller price movements during periods of low volatility or filter out noise during high volatility.
⚪ Enhanced Trend Strength Analysis
Donchian Channels: Do not provide direct insight into the strength of a trend. Traders must rely on additional indicators or their judgment to gauge whether a trend is strong or weak.
Curved Price Channels: Includes a built-in trend strength calculation that takes into account the distance between the upper and lower channels relative to the trendline. A broader range between the channels typically indicates a stronger trend, while a narrower range suggests a weaker trend. This feature helps traders not only identify the direction of the trend but also assess its potential longevity and strength.
⚪ Dynamic Support and Resistance
Donchian Channels: Offer static support and resistance levels that may not accurately reflect changing market dynamics. These levels can quickly become outdated in volatile markets.
Curved Price Channels: Offer dynamic support and resistance levels that adjust in real-time, providing more relevant and actionable trading signals. As the channels curve to reflect price movements, they can help identify areas where the price is likely to encounter support or resistance, making them more useful in volatile or trending markets.
█ How to Use
Traders can use the Curved Price Channels in similar ways to Donchian Channels but with the added benefits of the adaptive, curved structure:
Breakout Identification:
Just like Donchian Channels, when the price breaks above the upper curved band, it may signal the start of a bullish trend, while a break below the lower curved band could indicate a bearish trend. The curved nature of the channels helps in capturing these breakouts more precisely by adjusting to recent volatility.
Volatility:
The width of the price channels in the Curved Price Channels indicator serves as a clear indicator of current market volatility. A wider channel indicates that the market is experiencing higher volatility, as prices are fluctuating more dramatically within the period. Conversely, a narrower channel suggests that the market is in a lower volatility state, with price movements being more subdued.
Typically, higher volatility is observed during negative trends, where market uncertainty or fear drives larger price swings. In contrast, lower volatility is often associated with positive trends, where prices tend to move more steadily and predictably. The adaptive nature of the Curved Price Channels reflects these volatility conditions in real time, allowing traders to assess the market environment quickly and adjust their strategies accordingly.
Support and Resistance:
The trend line act as dynamic support and resistance levels. Due to it's adaptive nature, this level is more reflective of the current market environment than the fixed level of Donchian Channels.
Trend Direction and Strength:
The trend direction and strength are highlighted by the trendline and the directional candle within the Curved Price Channels indicator. If the price is above the trendline, it indicates a positive trend, while a price below the trendline signals a negative trend. This directional bias is visually represented by the color of the directional candle, making it easy for traders to quickly identify the current market trend.
In addition to the trendline, the indicator also displays Max and Min values. These represent the highest and lowest trend strength values within the lookback period, providing a reference point for understanding the current trend strength relative to historical levels.
Max Value: Indicates the highest recorded trend strength during the lookback period. If the Max value is greater than the Min value, it suggests that the market has generally experienced more positive (bullish) conditions during this time frame.
Min Value: Represents the lowest recorded trend strength within the same period. If the Min value is greater than the Max value, it indicates that the market has been predominantly negative (bearish) over the lookback period.
By assessing these Max and Min values, traders gain an immediate understanding of the underlying trend. If the current trend strength is close to the Max value, it indicates a strong bullish trend. Conversely, if the trend strength is near the Min value, it suggests a strong bearish trend.
█ Settings
Trend Length: Defines the number of bars used to calculate the core trendline and adaptive size. A length of 200 will create a smooth, long-term trendline that reacts slowly to price changes, while a length of 20 will create a more responsive trendline that tracks short-term movements.
Multiplier: Adjusts the width of the curved price channels. A higher value tightens the channels, making them more sensitive to price movements, while a lower value widens the channels. A multiplier of 10 will create tighter channels that are more sensitive to minor price fluctuations, which is useful in low-volatility markets. A multiplier of 2 will create wider channels that capture larger trends and are better suited for high-volatility markets.
Trend Strength Length: Defines the period over which the maximum and minimum ranges are calculated to normalize the trend strength. A length of 200 will smooth out the trend strength readings, providing a stable indication of trend health, whereas a length of 50 will make the readings more reactive to recent price changes.
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Disclaimer
The information contained in my Scripts/Indicators/Ideas/Algos/Systems does not constitute financial advice or a solicitation to buy or sell any securities of any type. I will not accept liability for any loss or damage, including without limitation any loss of profit, which may arise directly or indirectly from the use of or reliance on such information.
All investments involve risk, and the past performance of a security, industry, sector, market, financial product, trading strategy, backtest, or individual's trading does not guarantee future results or returns. Investors are fully responsible for any investment decisions they make. Such decisions should be based solely on an evaluation of their financial circumstances, investment objectives, risk tolerance, and liquidity needs.
My Scripts/Indicators/Ideas/Algos/Systems are only for educational purposes!
Magic Linear Regression Channel [MW]Introduction
The Magic Linear Regression Channel indicator provides users with a way to quickly include a linear regression channel ANYWHERE on their chart, in order to find channel breakouts and bounces within any time period. It uses a novel method that allows users to adjust the start and end period of the regression channel in order to quickly make adjustments faster, with fewer steps, and with more precision than with any other linear regression channel tool. It includes Fibonacci bands AND a horizontal mode in order for users to quickly define significant price levels based on the high, low, open, and close prices defined by the start period.
Settings
Start Time: This is initially MANUALLY SELECTED ON THE CHART when the indicator is first loaded.
End time: This is also initially MANUALLY SELECTED ON THE CHART when the indicator is first loaded.
Horizontal Line: This forces the baseline to be horizontal. The band distance is defined by the maximum price distance from the band.
Horizontal Line Type: This snaps the horizontal line to the close, high, low, or open price. Or, it can also use a regression calculation for the selected time period to define the y-position of the line.
Extend Line N Bars: How many bars to the left in which to extend the baseline and bands.
Show Baseline ONLY!!: Removes all lines except the baseline and it’s extension.
Add Half Band: Includes a band that is half the distance between the baseline and the top and bottom bands
Add Outer Fibonacci Band: Includes a band that is 1.618 (phi) times the default band distance
Add Inner Fibonacci Band - Upper: Includes a band that is 0.618 (1/phi) times the default band distance
Add Inner Fibonacci Band - Lower: Includes a band that is 0.382 (1 - 1/phi) times the default band distance
Calculations
This indicator uses the least squares approach for generating a straight regression line, which can be reviewed at Wikipedia’s “Simple Linear Regression” page. It sums all of the x-values, and y-values, as well as the sum of the product of corresponding x and y values, and the sum of the squares of the x-values. These values are used to calculate the slope and intercept using the following equations:
slope = (n * sum_xy - sum_x * sum_y) / (n * sum_xx - sum_x * sum_x)
And
intercept = (sum_y - slope * sum_x) / n
The slope and intercept are then used to generate the baseline and the corresponding bands using the user-selected offsets.
How to Use
When the Magic Linear Regression Channel indicator is first added to the chart, there will be a blue prompt behind the “Indicators, Metrics & Strategies” window. Close the window, then select a START POINT by clicking at a desired location on the chart. Next, you will be prompted to select an END POINT. The end point MUST be placed after the START POINT. At this time a channel will be generated. Once you’ve selected the START POINT and END POINT, you can adjust them by dragging them anywhere on the chart. Each adjustment will generate a new channel making it easier for you to quickly visualize and recognize any channel exits and bounces.
The Magic Linear Regression Channel indicator works great at identifying wave patterns. Place the start line at a top or bottom pivot point. Place the end line at the next respective top or bottom pivot. This will give you a complete wave form to work with. When price reaches a band and rejects, it can be a strong indication that price may move back to one of the bands in the channel. If price exits the channel with volume that supports the exit, it may be an indication of a breakout.
You can also use the horizontal mode to identify key levels, then add Fibonacci bands based on regression calculations for the given time period to provide more meaningful areas of support and resistance.
Other Usage Notes and Limitations
Occasionally, off-by-1 errors appear which makes the extended lines protrude at a slightly incorrect angle. This is a known bug and will be addressed in the next release.
It's important for traders to be aware of the limitations of any indicator and to use them as part of a broader, well-rounded trading strategy that includes risk management, fundamental analysis, and other tools that can help with reducing false signals, determining trend direction, and providing additional confirmation for a trade decision. Diversifying strategies and not relying solely on one type of indicator or analysis can help mitigate some of these risks.
Double Donchian Channels [CrossTrade]Dual Channel System
The indicator incorporates two Donchian Channels - the Inner Channel and the Outer Channel. These channels are adjustable, allowing users to define their lengths according to their trading strategy.
Inner Channel: With a default length of 100 periods, the Inner Channel provides a closer view of market trends and potential support and resistance areas. It includes an upper, lower, and middle line (average of the upper and lower), offering detailed insights into shorter-term price movements.
Outer Channel: Set with a default length of 300 periods, the Outer Channel offers a broader perspective, ideal for identifying long-term trends and stronger levels of support and resistance.
Dynamic Color Coding: The middle lines of both channels change color based on the relationship between the previous close and the channel's basis. This feature provides an immediate visual cue regarding market sentiment.
Touching Bars Highlighting: The indicator highlights bars that touch the upper or lower bands of either channel. This is particularly useful for identifying potential reversals or continuation patterns.
Pullback Identification: By differentiating between bars that touch the Inner Channel only and those that touch the Outer Channel, the indicator helps in identifying pullbacks within a broader trend.
Customizable Alert System: Users can set up alerts for specific conditions - a bar touching the bottom band of the Inner Channel (green), the bottom band of the Outer Channel (blue), the upper band of the Inner Channel (red), and the upper band of the Outer Channel (orange). These alerts assist in timely decision-making and can be tailored to individual trading styles.
The indicator is a versatile tool designed to adapt to various trading styles and timeframes. Its features make it suitable for trend analysis, identifying potential reversal points, and understanding market volatility.
KASPA Slope OscillatorKASPA Slope Oscillator for analyzing KASPA on the 1D (daily) chart.
The indicator is plotted in a separate pane below the price chart and uses a mathematical approach to calculate and visualize the momentum or "slope" of KASPA's price movements.
Input Parameters:
Slope Window (days):
Defines the period (66 days by default) over which the slope is calculated.
Normalization Window (days):
The window size (85 days) for normalizing the slope values between 0 and 100.
Smoothing Period:
The number of days (15 days) over which the slope values are smoothed to reduce noise.
Overbought and Oversold Levels:
Threshold levels set at 80 (overbought) and 20 (oversold), respectively.
Calculation of the Slope:
Logarithmic Price Calculation:
Converts the close price of KASPA into a logarithmic scale to account for exponential growth or decay.
Rolling Slope:
Computes the rate of change in logarithmic prices over the defined slope window.
Normalization:
The slope is normalized between 0 and 100, allowing easier identification of extreme values.
Smoothing and Visualization:
Smoothing the Slope:
A Simple Moving Average (SMA) is applied to the normalized slope for the specified smoothing period.
Plotting the Oscillator:
The smoothed slope is plotted on the oscillator chart. Horizontal lines indicate overbought (80), oversold (20), and the mid-level (50).
Background Color Indications:
Background colors (red or green) indicate when the slope crosses above the overbought or below the oversold levels, respectively, signaling potential buy or sell conditions.
Detection of Local Maxima and Minima:
The code identifies local peaks (maxima) above the overbought level and troughs (minima) below the oversold level.
Vertical background lines are highlighted in red or green at these points, signaling potential reversals.
Short Summary:
The oscillator line fluctuates between 0 and 100, representing the normalized momentum of the price.
Red background areas indicate periods when the oscillator is above the overbought level (80), suggesting a potential overbought condition or a sell signal.
Green background areas indicate periods when the oscillator is below the oversold level (20), suggesting a potential oversold condition or a buy signal.
The vertical lines on the background mark local maxima and minima where price reversals may occur.
(I also want to thank @ForgoWork for optimizing visuality and cleaning up the source code)
HMA Z-Score Probability Indicator by Erika BarkerThis indicator is a modified version of SteverSteves's original work, enhanced by Erika Barker. It visually represents asset price movements in terms of standard deviations from a Hull Moving Average (HMA), commonly known as a Z-Score.
Key Features:
Z-Score Calculation: Measures how many standard deviations the current price is from its HMA.
Hull Moving Average (HMA): This moving average provides a more responsive baseline for Z-Score calculations.
Flexible Display: Offers both area and candlestick visualization options for the Z-Score.
Probability Zones: Color-coded areas showing the statistical likelihood of prices based on their Z-Score.
Dynamic Price Level Labels: Displays actual price levels corresponding to Z-Score values.
Z-Table: An optional table showing the probability of occurrence for different Z-Score ranges.
Standard Deviation Lines: Horizontal lines at each standard deviation level for easy reference.
How It Works:
The indicator calculates the Z-Score by comparing the current price to its HMA and dividing by the standard deviation. This Z-Score is then plotted on a separate pane below the main chart.
Green areas/candles: Indicate prices above the HMA (positive Z-Score)
Red areas/candles: Indicate prices below the HMA (negative Z-Score)
Color-coded zones:
Green: Within 1 standard deviation (high probability)
Yellow: Between 1 and 2 standard deviations (medium probability)
Red: Beyond 2 standard deviations (low probability)
The HMA line (white) shows the trend of the Z-Score itself, offering insight into whether the asset is becoming more or less volatile over time.
Customization Options:
Adjust lookback periods for Z-Score and HMA calculations
Toggle between area and candlestick display
Show/hide probability fills, Z-Table, HMA line, and standard deviation bands
Customize text color and decimal rounding for price levels
Interpretation:
This indicator helps traders identify potential overbought or oversold conditions based on statistical probabilities. Extreme Z-Score values (beyond ±2 or ±3) often suggest a higher likelihood of mean reversion, while consistent Z-Scores in one direction may indicate a strong trend.
By combining the Z-Score with the HMA and probability zones, traders can gain a nuanced understanding of price movements relative to recent trends and their statistical significance.
Cash Cycle BandCash cycle band shows the number of days and the profit margin compared to the previous period (it does not indicate how profitable the company is, but how well it is managed).
Cash cycle band consists of 6 sections:
1. DPO is the days payables outstanding in the "red" followed by O/D which is overdraft or short-term debt (if any) .
2. DIO is the days inventory outstanding in the "green" followed by classified inventory (if any) consists of finished goods. work in process and raw materials.
3. DSO is days sales outstanding in "blue".
4. DWC is days converting working capital to revenue in "orange".
5. CCC is days converting inventory and resources to cash flow in "yellow".
6. GPM is gross profit margin and OPM is operating profit margin.
The "😱" emoji indicates a value if it increases by more than or decreases by less than 20%, e.g.
- DPO, finished goods, work in process, raw materials, GPM, OPM is decreasing.
- O/D, DIO, DSO, DWC, CCC is increasing.
The "🔥" emoji indicates a value if it increases by more than or decreases, e.g.
- DPO, finished goods, work in process, raw materials, GPM, OPM is increasing.
- O/D, DIO, DSO, DWC, CCC is decreasing.
The order of the list depends on the day of each item, the more days more high.
Ranges and Breakouts [AlgoAlpha]💥 Ranges and Breakouts by AlgoAlpha is a dynamic indicator designed for traders seeking to identify market ranges and capitalize on breakout opportunities. This tool automatically detects ranges based on price action over a specified period, visualizing these ranges with shaded boxes and midlines, making it easy to spot potential breakout scenarios. The indicator includes advanced features such as customizable pivot detection, internal range allowance, and automatic trend color changes for quick market analysis.
Key Features
💹 Dynamic Range Detection : Automatically identifies market ranges using customizable look-back and confirmation periods.
🎯 Breakout Alerts : Get alerted to bullish and bearish breakouts for potential trading opportunities.
📊 Visual Aids : Displays pivot highs/lows within ranges and plots midlines with adjustable styles for easier market trend interpretation.
🔔 Alerts : Signals potential take-profit points based on volatility and moving average crossovers.
🎨 Customizable Appearance : Choose between solid, dashed, or dotted lines for midlines and adjust the colors for bullish and bearish zones.
How to Use
⭐ Add the Indicator : Add the indicator to favorites by pressing the star icon. Adjust the settings like the look-back period, confirmation length, and pivot detection to match your trading strategy.
👀 Monitor the Chart : Watch for new ranges to form, highlighted by shaded boxes on the chart. Midlines and range bounds will appear to help you gauge potential breakout points.
⚡ React to Breakouts : Pay attention to color changes and alert signals for bullish or bearish breakouts. Use these signals to enter or exit trades.
🔔 Set Alerts : Customize alert conditions for new range formations, breakout signals, and take-profit levels to stay on top of market movements without constant monitoring.
How It Works
The indicator detects price ranges by analyzing the highest and lowest prices over a specified period. It confirms a range if these levels remain unchanged for a set number of bars, at which point it visually marks the range with shaded boxes. Pivots are identified within these ranges, and a midline is plotted to help interpret potential breakouts. When price breaks out of these defined ranges, the indicator changes the chart's background color to signal a bullish or bearish trend. Alerts can be set for range formation, breakouts, and take-profit opportunities, helping traders stay proactive in volatile markets.
Abnormal value check1. indicator settings
BB Length: Sets the period used for the Bollinger Band calculation. The default is 20 periods.
BB Multiplier: Sets the multiplier to be used in the Bollinger Band calculation. The default is 2.5 multiplier.
Equilibrium volume reset: Selects whether or not the volume should be reset if it is out of equilibrium. The default setting is reset. 2.
2. bollinger band calculation
This indicator calculates Bollinger Bands (upper and lower bands and a reference line) from price and volume data.
Bollinger Bands are indicators used to measure price and volume volatility and are identified as anomalies when prices break through the bands.
3. display of abnormal prices
Abnormal Buying Price (ABP): The background color changes when the price significantly exceeds the upper limit of the Bollinger Band. The color is green.
Abnormal Selling Price (ASP): The background color changes when the price is significantly below the lower limit of the Bollinger Band. The color is red.
Abnormal High Volume (AHV): The background color changes when the volume is significantly above the upper Bollinger Band. The color is white.
Abnormal Low Volume (ALV): The background color changes when the volume is significantly below the lower limit of the Bollinger Band. The color is yellow. 4.
4. display of signals
Abnormal Price Signal: A triangle signal is displayed when the price rises or falls compared to the previous data. The color is orange for an increase and purple for a decrease.
Volume Abnormal Signal: A triangle signal is displayed when volume is up or down compared to the previous data. Rises are colored orange and falls are colored purple. 5.
5. price and volume history display
RSAB_P: Displays price anomaly history. Rising prices are displayed in green, and falling prices in red.
RSAB_V: Displays the volume anomaly history. Green indicates an increase and red indicates a decrease. 6.
6. display of equilibrium
PPE: Displays a line indicating the state of volume balance. A positive volume balance is displayed in orange, and a negative volume balance is displayed in purple.
Summary of usage
Add indicator to chart: Add this Pine Script™ code as an indicator in TradingView.
Set parameters: Based on the settings above, adjust the values to suit your trading strategy and analysis.
See signals and color changes on the chart: Visually identify price and volume anomalies to help you make trading decisions.
This indicator uses Bollinger Bands to identify abnormal price and volume movements to help you improve your trading timing and strategies.
IMI and MFI CombinedFor a strategy using the combined IMI (Intraday Momentum Index), MFI (Money Flow Index), and Bollinger Bands on a 1-minute chart of Bank NIFTY (Bank Nifty Index), here's how you can interpret the indicators and define a sell signal strategy:
Strategy Explanation:
IMI (Intraday Momentum Index):
IMI measures the ratio of upward price changes to downward price changes over a specified period, indicating momentum.
In the script, IMI is plotted with a range from 0 to 100. Levels above 75 are considered overbought, and levels below 25 are oversold.
Strategy Condition: A sell signal can be considered when IMI is above 75, indicating a potentially overbought market condition.
MFI (Money Flow Index):
MFI measures the strength of money flowing in and out of a security, using price and volume.
In the script, MFI is plotted with levels at 80 (overbought) and 20 (oversold).
Strategy Condition: A sell signal can be considered when MFI is above 80, suggesting an overbought condition in the market.
Bollinger Bands:
Bollinger Bands consist of a middle band (SMA) and upper/lower bands representing volatility levels around the price.
In the script, Bollinger Bands are plotted with a length of 20 and a standard deviation multiplier of 2.
Strategy Condition: While not explicitly used for generating sell signals in this script, Bollinger Bands can help confirm price volatility and potential reversals when combined with other indicators.
Sell Signal Criteria:
IMI Sell Signal: Look for instances where IMI rises above 75. This indicates that the recent upward price momentum may be reaching an unsustainable level, potentially signaling a reversal or a pullback in prices.
MFI Sell Signal: Look for MFI rising above 80. This suggests that the market has experienced strong buying pressure, possibly leading to an overbought condition where a price correction or reversal might occur.
Implementation Considerations:
Confirmation: Consider waiting for both IMI and MFI to confirm the overbought condition simultaneously before entering a sell trade. This can increase the reliability of the signal.
Risk Management: Use stop-loss orders to manage risk in case the market moves against the anticipated direction after the sell signal is triggered.
Timeframe: This strategy is tailored for a 1-minute chart, meaning signals should be interpreted and acted upon quickly due to the rapid nature of price movements in intraday trading.
By combining these indicators and interpreting their signals, you can develop a systematic approach to identifying potential sell opportunities in the Bank NIFTY index on a 1-minute timeframe. Adjustments to indicator parameters and additional technical analysis may further refine the strategy based on your trading preferences and risk tolerance.
Inside Candle - Multi TimeframesIndicator looks for inside candle on 3 timeframes. Chart's default timeframe and 2 higher timeframes to spot Inside candle on any of these timeframes.
Main purpose was to look at multiple inside candle at multiple timeframes to identify consolidation within consolidation and implement intraday, hence for 15min chart timeframe.
However, code works for all timeframes from 5 min to quarterly and higher timeframes will be picked automatically.
Reference and credits
This indicator is inspired by and uses code from:
- Author Name - // © Fab_Coin_
-
Advanced Keltner Channel/Oscillator [MyTradingCoder]This indicator combines a traditional Keltner Channel overlay with an oscillator, providing a comprehensive view of price action, trend, and momentum. The core of this indicator is its advanced ATR calculation, which uses statistical methods to provide a more robust measure of volatility.
Starting with the overlay component, the center line is created using a biquad low-pass filter applied to the chosen price source. This provides a smoother representation of price than a simple moving average. The upper and lower channel lines are then calculated using the statistically derived ATR, with an additional set of mid-lines between the center and outer lines. This creates a more nuanced view of price action within the channel.
The color coding of the center line provides an immediate visual cue of the current price momentum. As the price moves up relative to the ATR, the line shifts towards the bullish color, and vice versa for downward moves. This color gradient allows for quick assessment of the current market sentiment.
The oscillator component transforms the channel into a different perspective. It takes the price's position within the channel and maps it to either a normalized -100 to +100 scale or displays it in price units, depending on your settings. This oscillator essentially shows where the current price is in relation to the channel boundaries.
The oscillator includes two key lines: the main oscillator line and a signal line. The main line represents the current position within the channel, smoothed by an exponential moving average (EMA). The signal line is a further smoothed version of the oscillator line. The interaction between these two lines can provide trading signals, similar to how MACD is often used.
When the oscillator line crosses above the signal line, it might indicate bullish momentum, especially if this occurs in the lower half of the oscillator range. Conversely, the oscillator line crossing below the signal line could signal bearish momentum, particularly if it happens in the upper half of the range.
The oscillator's position relative to its own range is also informative. Values near the top of the range (close to 100 if normalized) suggest that price is near the upper Keltner Channel band, indicating potential overbought conditions. Values near the bottom of the range (close to -100 if normalized) suggest proximity to the lower band, potentially indicating oversold conditions.
One of the strengths of this indicator is how the overlay and oscillator work together. For example, if the price is touching the upper band on the overlay, you'd see the oscillator at or near its maximum value. This confluence of signals can provide stronger evidence of overbought conditions. Similarly, the oscillator hitting extremes can draw your attention to price action at the channel boundaries on the overlay.
The mid-lines on both the overlay and oscillator provide additional nuance. On the overlay, price action between the mid-line and outer line might suggest strong but not extreme momentum. On the oscillator, this would correspond to readings in the outer quartiles of the range.
The customizable visual settings allow you to adjust the indicator to your preferences. The glow effects and color coding can make it easier to quickly interpret the current market conditions at a glance.
Overlay Component:
The overlay displays Keltner Channel bands dynamically adapting to market conditions, providing clear visual cues for potential trend reversals, breakouts, and overbought/oversold zones.
The center line is a biquad low-pass filter applied to the chosen price source.
Upper and lower channel lines are calculated using a statistically derived ATR.
Includes mid-lines between the center and outer channel lines.
Color-coded based on price movement relative to the ATR.
Oscillator Component:
The oscillator component complements the overlay, highlighting momentum and potential turning points.
Normalized values make it easy to compare across different assets and timeframes.
Signal line crossovers generate potential buy/sell signals.
Advanced ATR Calculation:
Uses a unique method to compute ATR, incorporating concepts like root mean square (RMS) and z-score clamping.
Provides both an average and mode-based ATR value.
Customizable Visual Settings:
Adjustable colors for bullish and bearish moves, oscillator lines, and channel components.
Options for line width, transparency, and glow effects.
Ability to display overlay, oscillator, or both simultaneously.
Flexible Parameters:
Customizable inputs for channel width multiplier, ATR period, smoothing factors, and oscillator settings.
Adjustable Q factor for the biquad filter.
Key Advantages:
Advanced ATR Calculation: Utilizes a statistical method to generate ATR, ensuring greater responsiveness and accuracy in volatile markets.
Overlay and Oscillator: Provides a comprehensive view of price action, combining trend and momentum analysis.
Customizable: Adjust settings to fine-tune the indicator to your specific needs and trading style.
Visually Appealing: Clear and concise design for easy interpretation.
The ATR (Average True Range) in this indicator is derived using a sophisticated statistical method that differs from the traditional ATR calculation. It begins by calculating the True Range (TR) as the difference between the high and low of each bar. Instead of a simple moving average, it computes the Root Mean Square (RMS) of the TR over the specified period, giving more weight to larger price movements. The indicator then calculates a Z-score by dividing the TR by the RMS, which standardizes the TR relative to recent volatility. This Z-score is clamped to a maximum value (10 in this case) to prevent extreme outliers from skewing the results, and then rounded to a specified number of decimal places (2 in this script).
These rounded Z-scores are collected in an array, keeping track of how many times each value occurs. From this array, two key values are derived: the mode, which is the most frequently occurring Z-score, and the average, which is the weighted average of all Z-scores. These values are then scaled back to price units by multiplying by the RMS.
Now, let's examine how these values are used in the indicator. For the Keltner Channel lines, the mid lines (top and bottom) use the mode of the ATR, representing the most common volatility state. The max lines (top and bottom) use the average of the ATR, incorporating all volatility states, including less common but larger moves. By using the mode for the mid lines and the average for the max lines, the indicator provides a nuanced view of volatility. The mid lines represent the "typical" market state, while the max lines account for less frequent but significant price movements.
For the color coding of the center line, the mode of the ATR is used to normalize the price movement. The script calculates the difference between the current price and the price 'degree' bars ago (default is 2), and then divides this difference by the mode of the ATR. The resulting value is passed through an arctangent function and scaled to a 0-1 range. This scaled value is used to create a color gradient between the bearish and bullish colors.
Using the mode of the ATR for this color coding ensures that the color changes are based on the most typical volatility state of the market. This means that the color will change more quickly in low volatility environments and more slowly in high volatility environments, providing a consistent visual representation of price momentum relative to current market conditions.
Using a good IIR (Infinite Impulse Response) low-pass filter, such as the biquad filter implemented in this indicator, offers significant advantages over simpler moving averages like the EMA (Exponential Moving Average) or other basic moving averages.
At its core, an EMA is indeed a simple, single-pole IIR filter, but it has limitations in terms of its frequency response and phase delay characteristics. The biquad filter, on the other hand, is a two-pole, two-zero filter that provides superior control over the frequency response curve. This allows for a much sharper cutoff between the passband and stopband, meaning it can more effectively separate the signal (in this case, the underlying price trend) from the noise (short-term price fluctuations).
The improved frequency response of a well-designed biquad filter means it can achieve a better balance between smoothness and responsiveness. While an EMA might need a longer period to sufficiently smooth out price noise, potentially leading to more lag, a biquad filter can achieve similar or better smoothing with less lag. This is crucial in financial markets where timely information is vital for making trading decisions.
Moreover, the biquad filter allows for independent control of the cutoff frequency and the Q factor. The Q factor, in particular, is a powerful parameter that affects the filter's resonance at the cutoff frequency. By adjusting the Q factor, users can fine-tune the filter's behavior to suit different market conditions or trading styles. This level of control is simply not available with basic moving averages.
Another advantage of the biquad filter is its superior phase response. In the context of financial data, this translates to more consistent lag across different frequency components of the price action. This can lead to more reliable signals, especially when it comes to identifying trend changes or price reversals.
The computational efficiency of biquad filters is also worth noting. Despite their more complex mathematical foundation, biquad filters can be implemented very efficiently, often requiring only a few operations per sample. This makes them suitable for real-time applications and high-frequency trading scenarios.
Furthermore, the use of a more sophisticated filter like the biquad can help in reducing false signals. The improved noise rejection capabilities mean that minor price fluctuations are less likely to cause unnecessary crossovers or indicator movements, potentially leading to fewer false breakouts or reversal signals.
In the specific context of a Keltner Channel, using a biquad filter for the center line can provide a more stable and reliable basis for the entire indicator. It can help in better defining the overall trend, which is crucial since the Keltner Channel is often used for trend-following strategies. The smoother, yet more responsive center line can lead to more accurate channel boundaries, potentially improving the reliability of overbought/oversold signals and breakout indications.
In conclusion, this advanced Keltner Channel indicator represents a significant evolution in technical analysis tools, combining the power of traditional Keltner Channels with modern statistical methods and signal processing techniques. By integrating a sophisticated ATR calculation, a biquad low-pass filter, and a complementary oscillator component, this indicator offers traders a comprehensive and nuanced view of market dynamics.
The indicator's strength lies in its ability to adapt to varying market conditions, providing clear visual cues for trend identification, momentum assessment, and potential reversal points. The use of statistically derived ATR values for channel construction and the implementation of a biquad filter for the center line result in a more responsive and accurate representation of price action compared to traditional methods.
Furthermore, the dual nature of this indicator – functioning as both an overlay and an oscillator – allows traders to simultaneously analyze price trends and momentum from different perspectives. This multifaceted approach can lead to more informed decision-making and potentially more reliable trading signals.
The high degree of customization available in the indicator's settings enables traders to fine-tune its performance to suit their specific trading styles and market preferences. From adjustable visual elements to flexible parameter inputs, users can optimize the indicator for various trading scenarios and time frames.
Ultimately, while no indicator can predict market movements with certainty, this advanced Keltner Channel provides traders with a powerful tool for market analysis. By offering a more sophisticated approach to measuring volatility, trend, and momentum, it equips traders with valuable insights to navigate the complex world of financial markets. As with any trading tool, it should be used in conjunction with other forms of analysis and within a well-defined risk management framework to maximize its potential benefits.
Future SD ProjectionFuture Standard Deviation Projector
This innovative indicator projects price volatility into the future, helping traders anticipate potential price ranges and breakouts. It calculates standard deviation bands based on recent price action and extends them forward, providing a unique perspective on future price movement possibilities.
Key Features:
- Projects standard deviation bands into the future
- Customizable lookback period for volatility calculation
- Adjustable future projection timeframe
- Flexible standard deviation multiplier
- Clear visual signals for band breaches
How it works:
1. Calculates standard deviation from recent closing prices
2. Projects upper and lower bands into the future
3. Plots these bands on the chart
4. Signals with arrows when closing price crosses projected bands
Use this indicator to:
- Gauge potential future price ranges
- Identify possible breakout levels
- Assess market volatility expectations
- Enhance your trading strategy with forward-looking volatility projections
Customize the settings to align with your trading timeframe and risk tolerance. Remember, while this tool offers valuable insights, it should be used in conjunction with other analysis methods for comprehensive trading decisions.
Note: Past performance and projections do not guarantee future results. Always manage your risk appropriately.
RSI with Bollinger Bands Scalp Startegy (1min)
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The "RSI with Bollinger Bands Scalp Strategy (1min)" is a highly effective tool designed for traders who engage in short-term scalping on the 1-minute chart. This indicator combines the strengths of the RSI (Relative Strength Index) and Bollinger Bands to generate precise buy signals, helping traders make quick and informed decisions in fast-moving markets.
How It Works:
RSI (Relative Strength Index):
The RSI is a widely-used momentum oscillator that measures the speed and change of price movements. It operates on a scale of 0 to 100 and helps identify overbought and oversold conditions in the market.
This strategy allows customization of the RSI's lower and upper bands (default settings: 30 for the lower band and 70 for the upper band) and the RSI length (default: 14).
Bollinger Bands:
Bollinger Bands consist of a central moving average (the basis) and two bands that represent standard deviations above and below the basis. These bands expand and contract based on market volatility.
In this strategy, the Bollinger Bands are used to identify potential buy and sell signals based on the price's relationship to the upper and lower bands.
Signal Generation:
Buy Signal: A buy signal is triggered when two conditions are met:
The RSI value falls below the specified lower band, indicating an oversold condition.
The price crosses below the lower Bollinger Band.
The buy signal is then issued on the first positive candle (where the closing price is greater than or equal to the opening price) after these conditions are met.
Sell Signal: In this version of the strategy, the sell signal is currently disabled to focus solely on generating and optimizing the buy signals for scalping.
Strategy Highlights:
This indicator is particularly effective for traders who focus on 1-minute charts and want to capitalize on rapid price movements.
The combination of RSI and Bollinger Bands ensures that buy signals are only generated during significant oversold conditions, helping to filter out false signals.
Customization:
Users can adjust the RSI length, Bollinger Bands length, and the standard deviation multiplier to better fit their specific trading style and the asset they are trading.
The moving average type for Bollinger Bands can be selected from various options, including SMA, EMA, SMMA, WMA, and VWMA, allowing further customization based on individual preferences.
Usage:
Use this indicator on a 1-minute chart to identify potential buy opportunities during short-term price dips.
Since the sell signals are disabled, this strategy is best used in conjunction with other indicators or strategies to manage exit points effectively.
This "RSI with Bollinger Bands Scalp Strategy (1min)" indicator is a valuable tool for traders looking to enhance their short-term trading performance by focusing on high-probability entry points in volatile market conditions.
ka66: Bar Range BandsThis tool takes a bar's range, and reflects it above the high and below the low of that bar, drawing upper and lower bands around the bar. Repeated for each bar. There's an option to then multiply that range by some multiple. Use a value greater than 1 to get wider bands, and less than one to get narrower bands.
This tool stems out of my frustration from the use of dynamic bands (like Keltner Channels, or Bollinger Bands), in particular for estimating take profit points.
Dynamic bands work great for entries and stop loss, but their dynamism is less useful for a future event like taking profit, in my experience. We can use a smaller multiple, but then we can often lose out on a bigger chunk of gains unnecessarily.
The inspiration for this came from a friend explaining an ICT/SMC concept around estimating the magnitude of a trend, by calculating the Asian Session Range, and reflecting it above or below on to the New York and London sessions. He described this as standard deviation of the Asian Range, where the range can thus be multiplied by some multiple for a wider or narrower deviation.
This, in turn, also reminded me of the Measured Move concept in Technical Analysis. We then consider that the market is fractal in nature, and this is why patterns persist in most timeframes. Traders exist across the spectrum of timeframes. Thus, a single bar on a timeframe, is made up of multiple bars on a lower timeframe . In other words, when we reflect a bar's range above or below itself, in the event that in a lower timeframe, that bar fit a pattern whose take profit target could be estimated via a Measured Move , then the band's value becomes a more valid estimate of a take profit point .
Yet another way to think about it, by way of the fractal nature above, is that it is essentially a simplified dynamic support and resistance mechanism , even simpler than say the various Pivot calculations (e.g. Classical, Camarilla, etc.).
This tool in general, can also be used by those who manually backtest setups (and certainly can be used in an automated setting too!). It is a research tool in that regard, applicable to various setups.
One of the pitfalls of manual backtesting is that it requires more discipline to really determine an exit point, because it's easy to say "oh, I'll know more or less where to exit when I go live, I just want to see that the entry tends to work". From experience, this is a bad idea, because our mind subconsciously knows that we haven't got a trained reflex on where to exit. The setup may be decent, but without an exit point, we will never have truly embraced and internalised trading it. Again, I speak from experience!
Thus, to use this to research take profit/exit points:
Have a setup in mind, with all the entry rules.
Plot your setup's indicators, mark your signals.
Use this indicator to get an idea of where to exit after taking an entry based on your signal.
Credits:
@ICT_ID for providing the idea of using ranges to estimate how far a trend move might go, in particular he used the Asian Range projected on to the London and New York market sessions.
All the technicians who came up with the idea of the Measured Move.
Tether Ratio ChannelTether Ratio Channel is an on-chain metric that tracks the ebb & flow of the ratio of BTC market cap / stablecoin market cap.
This ratio is relevant to traders, as it tends to lead total crypto market cap's short to medium term trend, and has for many years.
The ratio's most straightforwards visualization may be Stablecoin Supply Oscillator , a legacy on-chain metric that captures the ratio but isn't useful on its own as a trading tool.
Tether Ratio Channel builds on top of Stablecoin Supply Oscillator, to create a new metric that's:
Signal-generating , with clear entry & exit signals
Unambiguous , so use is mechanical
Optimized , with the intent to generate signals as close as possible to BTC local tops & bottoms
Normalized across its history , so each signal has a rich uniform history & context
METRIC CONSTRUCTION
Tether Ratio Channel is a higher timeframe RSI of Stablecoin Supply Oscillator, bound inside a bollinger band channel, normalized and smoothed for optimal signal clarity.
Instead of chart price as the source, the metric uses a proxy for stablecoin market cap:
(USDT + USDC + DAI) divided by BTC mkt cap
But it's named for Tether specifically, because USDT just completely dominates the asset class.
Default settings are very close to the on-chain metric original, but not identical. Settings are adjustable in the metric inputs.
VERTICAL LOCATION IN THE CHANNEL
The lower the yellow print is on the metric's Y-axis, the more upside potential total crypto market cap typically has.
The higher the yellow print is on the metric's Y-axis, the more downside risk most crypto assets typically have.
SWING TRADE SIGNALS
Tether Ratio Channel is signal-generating, a simple cross of the metric (the yellow line) and its weighted moving average (the white line) is the signal.
A bullish cross below the green horizontal target is a high conviction buy signal
A bullish cross above the green target is a lower conviction buy signal, but historically still tends to make for a good entry
Any bearish cross is typically a good time to take profits
Any bearish cross above 55 (on the metric's Y axis) tends to coincide with BTC local tops
Buy signals are visualized with a green vertical, and a background fill that persists until the next sell signal
High conviction buy signals (below the green line) also print an arrow, if enabled.
Background fills and arrow prints will only appear if the chart timeframe is equal to or lower than the 8H chart. (Or whatever the metric's timeframe input is set to, if the user changes default settings).
Adjustable Percentage Range Moving AverageAdjustable Percentage Range Moving Average (APRMA)
The Adjustable Percentage Range Moving Average (APRMA) is a technical analysis tool designed for traders and market analysts who seek a dynamic approach to understanding market volatility and trend identification. Unlike traditional moving averages, the APRMA incorporates user-adjustable percentage bands around a central moving average line, offering a customizable view of price action relative to its recent history.
Key Features:
Central Moving Average: At its core, APRMA calculates a moving average (type of your choice) of the price over a specified number of periods, serving as the baseline for the indicator.
Percentage Bands: Surrounding the moving average are four bands, two above and two below, set at user-defined percentages away from the central line. These bands expand and contract based on the percentage input, not on standard deviation like Bollinger Bands, which allows for a consistent visual interpretation of how far the price has moved from its average.
Customizability: Users can adjust:
The length of the moving average period to suit short-term, medium-term, or long-term analysis.
The percentage offset for the bands, enabling traders to set the sensitivity of the indicator according to the asset's volatility or their trading strategy.
Visual Interpretation:
When the price moves towards or beyond the upper band, it might indicate that the asset is potentially overbought or that a strong upward trend is in place.
Conversely, price action near or below the lower band could suggest an oversold condition or a strong downward trend.
The space between the bands can be used to gauge volatility; narrower bands suggest lower current volatility relative to the average, while wider bands indicate higher volatility.
Usage in Trading:
Trend Confirmation: A price staying above the moving average and pushing the upper band might confirm an uptrend, while staying below and testing the lower band could confirm a downtrend.
Reversion Strategies: Traders might look for price to revert to the mean (moving average) when it touches or crosses the bands, setting up potential entry or exit points.
Breakout Signals: A price moving decisively through a band after a period of consolidation within the bands might signal a breakout.
The APRMA provides a clear, adaptable framework for traders to visualize where the price stands in relation to its recent average, offering insights into potential overbought/oversold conditions, trend strength, and volatility, all tailored by the trader's strategic preferences.
Machine Learning Support and Resistance [AlgoAlpha]🚀 Elevate Your Trading with Machine Learning Dynamic Support and Resistance!
The Machine Learning Dynamic Support and Resistance by AlgoAlpha leverages advanced machine learning techniques to identify dynamic support and resistance levels on your chart. This tool is designed to help traders spot key price levels where the market might reverse or stall, enhancing your trading strategy with precise, data-driven insights.
Key Features:
🎯 Dynamic Levels: Continuously adjusts support and resistance levels based on real-time price data using a K-means clustering algorithm.
🧠 Machine Learning: Utilizes clustering methods to optimize the identification of significant price zones.
⏳ Configurable Lookback Periods: Customize the training length and confirmation length for better adaptability to different market conditions.
🎨 Visual Clarity: Clearly distinguish bullish and bearish zones with customizable color schemes.
📉 Trailing and Fixed Levels: Option to display both trailing and fixed support/resistance levels for comprehensive analysis.
🚮 Auto-Cleaning: Automatically removes outdated levels after a specified number of bars to keep your chart clean and relevant.
Quick Guide to Using the Machine Learning Dynamic Support and Resistance Indicator
Maximize your trading with this powerful indicator by following these streamlined steps! 🚀✨
🛠 Add the Indicator: Add the indicator to favorites by pressing the star icon. Customize settings like clustering training length, confirmation length, and whether to show trailing or fixed levels to fit your trading style.
📊 Market Analysis: Monitor the dynamic levels to identify potential reversal points. Use these levels to inform entry and exit points, or to set stop losses.
How It Works
This indicator employs a K-means clustering algorithm to dynamically identify key price levels based on the historical price data within a specified lookback window. It starts by initializing three centroids based on the highest, lowest, and an average between the highest and lowest price over the lookback period. The algorithm then iterates through the price data to cluster the prices around these centroids, dynamically adjusting them until they stabilize, representing potential support and resistance levels. These levels are further confirmed based on a separate confirmation length parameter to identify "fixed" levels, which are then drawn as horizontal lines on the chart. The script continuously updates these levels as new data comes in, while also removing older levels to keep the chart clean and relevant, offering traders a clear and adaptive view of market structure.
Uptrick: Momentum Channel Indicator
### 🌟 **Uptrick: Momentum Channel Indicator (MC_Ind)** 🌟
The **"Uptrick: Momentum Channel Indicator"** is a powerful tool designed to help traders gauge market momentum and identify potential overbought or oversold conditions. Whether you're a day trader, swing trader, or long-term investor, this indicator can be your compass 🧭 in the complex world of trading.
### 🎯 **Purpose of the Indicator**
The primary goal of the **Momentum Channel Indicator** is to measure the deviation of price from its moving average (the mid-point) and to smooth this deviation to identify momentum shifts. By plotting overbought and oversold levels, the indicator helps traders spot potential reversal points where the market might change direction, offering valuable entry or exit signals.
### 🔧 **Inputs & Parameters**
Let's break down the input parameters that you can adjust to tailor the indicator to your trading style:
1. **`length1` (Channel Length) 📏**: This is the period over which the moving average (mid-point) and price deviation are calculated. The default value is 14, meaning the last 14 bars are considered for calculations.
2. **`length2` (Smoothing Length) 🧘**: This parameter controls the smoothing of the channel index, with a default value of 28. The higher the value, the smoother the momentum line, reducing noise and making trends more visible.
3. **`overbought1` & `overbought2` (Overbought Levels) 🔴**: These levels, set at 70 and 65 by default, represent the threshold above which the market is considered overbought, potentially signaling a selling opportunity.
4. **`oversold1` & `oversold2` (Oversold Levels) 🟢**: Similarly, these levels, set at -70 and -65, mark the threshold below which the market is considered oversold, indicating a potential buying opportunity.
### 🛠️ **How the Indicator Works**
Now, let's dive into the mechanics of the Momentum Channel Indicator:
1. **Mid-Point Calculation 🏁**: The mid-point is calculated using a simple moving average (SMA) of the closing prices over the `length1` period. This mid-point acts as a reference line from which deviations are measured.
2. **Price Deviation 📊**: The price deviation is the absolute difference between the closing price and the mid-point, smoothed over the same period (`length1`). This represents the typical price movement away from the mid-point.
3. **Channel Index 📉**: The channel index is calculated by dividing the price deviation by a fraction (0.01) of the mid-point, providing a normalized measure of how far the price has deviated from the average.
4. **Smoothing of the Channel Index 🌊**: The smoothed index (`mci1`) is calculated by applying a smoothing filter (SMA) over the channel index using the `length2` parameter. This helps reduce noise and highlight the true momentum of the market.
5. **Momentum Lines 📈**:
- **`mci1`**: The main momentum line, representing the smoothed channel index.
- **`mci2`**: A secondary momentum line, which is a further smoothed version of `mci1` using a 6-period SMA.
6. **Signal Lines 🚦**:
- **Overbought & Oversold Levels**: Horizontal lines plotted at `overbought1`, `overbought2`, `oversold1`, and `oversold2` levels serve as visual cues for overbought and oversold conditions.
- **Zero Line**: A central reference line at 0, indicating neutral momentum.
### 📈 **How to Use the Indicator**
#### 1. **Day Traders ⚡**
For day traders, the Momentum Channel Indicator can be a quick signal generator for short-term trades. Here's how you can use it:
- **Identify Entry Points 🎯**: Look for a **bullish crossover** when `mci1` crosses above `mci2` from below the `oversold1` level. This signals a potential upward reversal.
- **Spot Exit Points 🏁**: Watch for a **bearish crossunder** when `mci1` crosses below `mci2` from above the `overbought1` level. This could indicate a downward reversal.
- **Scalping 🔄**: In a fast-moving market, use the indicator to scalp by entering and exiting trades at these crossover points, with a tight stop-loss strategy.
#### 2. **Swing Traders 🎢**
Swing traders benefit from using the Momentum Channel Indicator to identify potential reversal points over a longer period:
- **Trend Confirmation 📊**: Use the smoothing effect of `mci2` to confirm trends. If `mci2` remains consistently above 0, it indicates a strong bullish trend, and vice versa.
- **Overbought/Oversold Reversals 🚀**: Enter trades when the price approaches the overbought or oversold levels (`overbought1`, `oversold1`). Combine this with other indicators, such as RSI, for more reliable signals.
- **Hold Positions 🧗**: Let the momentum lines guide your hold strategy. If the momentum lines stay aligned (both `mci1` and `mci2` are moving in the same direction), consider holding the position until a crossover or reversal signal appears.
#### 3. **Long-Term Investors 🏦**
For long-term investors, the Momentum Channel Indicator helps in fine-tuning entry and exit points based on broader market momentum:
- **Divergence Analysis 📐**: Look for divergence between the price and the momentum lines. If the price makes new highs but the momentum lines do not, it could signal a weakening trend and a potential reversal.
- **Strategic Entry/Exit 🏹**: Use the `overbought2` and `oversold2` levels to strategically enter or exit positions. These secondary levels provide an early warning before the market reaches extreme conditions.
- **Risk Management 🛡️**: The indicator can also be used as part of a risk management strategy by identifying when to reduce exposure in overbought markets or increase exposure in oversold markets.
### 🖼️ **Visualization & Interpretation**
The Momentum Channel Indicator is visually intuitive, with each component providing key insights:
1. **Momentum Lines (MCI1 & MCI2) 📈**:
- **Blue Line (`mci1`)**: Represents the main momentum line, providing immediate insights into market direction.
- **Orange Line (`mci2`)**: A secondary momentum line, further smoothed to confirm trends.
2. **Overbought/Oversold Levels 🔴🟢**:
- **Solid & Dashed Lines**: These lines highlight overbought and oversold regions, guiding traders on when to consider entering or exiting trades.
3. **MCI Difference (Purple Area) 🌌**:
- **Shaded Area**: The difference between `mci1` and `mci2`, shaded in purple, helps visualize the strength of the momentum. The larger the shaded area, the stronger the momentum.
### 🚀 **Advanced Tips & Tricks**
For those looking to maximize the potential of the Momentum Channel Indicator, here are some advanced strategies:
1. **Combine with Volume Indicators 📊**: Use volume indicators like OBV (On-Balance Volume) or Volume Oscillator to confirm momentum signals. For instance, a bullish crossover combined with increasing volume can reinforce a buy signal.
2. **Multiple Timeframe Analysis 🕒**: Apply the Momentum Channel Indicator across multiple timeframes (e.g., daily and weekly) to get a more comprehensive view of the market. This can help in aligning short-term trades with long-term trends.
3. **Adjusting Parameters 🔄**: Depending on market conditions, tweak the `length1` and `length2` parameters. In a highly volatile market, shorter lengths might provide quicker signals, whereas in a stable market, longer lengths could smooth out noise.
4. **Divergence & Convergence 📐**: Watch for divergence between price and momentum lines as a leading indicator of potential reversals. Convergence (when the price and momentum move in sync) can confirm the strength of the trend.
### **Conclusion**
The **Uptrick: Momentum Channel Indicator** is a versatile tool that can be customized for various trading styles and market conditions. Whether you're trading in fast-paced environments or analyzing long-term trends, this indicator offers a clear and intuitive way to gauge market momentum, identify potential reversals, and make informed trading decisions.
By understanding and applying the principles outlined above, you can harness the full power of this indicator, transforming your trading strategy from good to great! 🌟
Gaussian Kernel Smoothing EMAGaussian Kernel Smoothing EMA
The Gaussian Kernel Smoothing EMA integrates the exponential moving average with kernel smoothing techniques to refine the trend tool. Kernel smoothing is a non-parametric technique used to estimate a smooth curve from a set of data points. It is particularly useful in reducing noise and capturing the underlying structure of data. The smoothed value at each point is calculated as a weighted average of neighboring points, with the weights determined by a kernel function.
The Gaussian kernel is a popular choice in kernel smoothing due to its properties of being smooth, symmetric, and having infinite support. This function gives higher weights to data points closer to the target point and lower weights to those further away, resulting in a smooth and continuous estimate. Since price isn't normally distributed a logarithmic transformation is performed to remove most of its skewness to be able to fit the Gaussian kernel.
This indicator also has a bandwidth, which in kernel smoothing controls the width of the window over which the smoothing is performed. It determines how much influence nearby data points have on the smoothed value. In this indicator, the bandwidth is dynamically adjusted based on the standard deviation of the log-transformed prices so that the smoothing adapts to the underlying variability and potential volatility.
Bandwidth Factor: The bandwidth factor in this indicator is used to adjust the degree of the smoothing applied to the MA. In kernel smoothing, Bandwidth controls the width of the window over which the smoothing is applied. It determines how many data points around a central point are considered when calculating a smooth value. A smaller bandwidth results in less smoothing, while a larger bandwidth smooths out more noise, leading to a broader, more general trend.
Big Candle Touches Bollinger BandWhat It Does:
This indicator helps you spot important trading signals by combining Bollinger Bands with big candles.
Key Features:
Bollinger Bands: These bands show the average price (middle band) and the range of price movement (upper and lower bands) over a set period. The bands widen when prices are more volatile and narrow when they are less volatile.
Big Candle Detection: A "big candle" is a candle that has a larger body compared to the average price movement over a period. This is determined using the Average True Range (ATR), which measures market volatility.
How It Works:
Detects Big Candles: It checks if a candle’s body (the difference between its open and close prices) is bigger than usual, based on a multiplier of the ATR.
Touching Bollinger Bands: It looks for candles that touch or cross the upper or lower Bollinger Bands.
Highlights Important Signals:
Sell Signal: When a big candle touches the upper Bollinger Band, it marks it as a "Sell" signal with a red label.
Buy Signal: When a big candle touches the lower Bollinger Band, it marks it as a "Buy" signal with a green label.
Alerts:
You'll get alerts when a big candle touches the upper or lower Bollinger Bands, so you don’t miss these potential trading opportunities.
Visuals:
Bollinger Bands: Shown as three lines on the chart — the upper band (red), the lower band (green), and the middle band (blue).
Labels: Red labels for sell signals and green labels for buy signals when a big candle touches the bands.
This indicator helps you identify potential trading opportunities by focusing on significant price movements and how they interact with the Bollinger Bands.
Artaking 2Components of the Indicator:
Moving Averages:
Short-Term Moving Average (MA): This is a 50-period Simple Moving Average (SMA) applied to the closing price. It is used to track the short-term trend of the market.
Long-Term Moving Average (MA): This is a 200-period SMA used to track the long-term trend.
Day Trading Moving Average: A 20-period SMA is used specifically for day trading signals, focusing on shorter-term price movements.
Purpose:
The crossing of these moving averages (short-term crossing above or below long-term) provides basic buy and sell signals, indicative of potential trend reversals or continuations.
ADX (Average Directional Index) for Trend Strength:
ADX Calculation: The ADX is calculated using a 14-period length with 14-period smoothing. The ADX value indicates the strength of a trend, regardless of direction.
Strong Trend Condition: The indicator considers a trend to be strong if the ADX value is above 25. This threshold helps filter out trades during weak or sideways markets.
Purpose:
To ensure that the strategy only generates signals when there is a strong trend, thus avoiding whipsaws in low volatility or range-bound conditions.
Support Levels:
Support Level Calculation: The indicator calculates the lowest close over the last 100 periods. This level is used to identify significant support zones where the price might find a floor.
Purpose:
Support levels are critical in identifying potential areas where the price might bounce, making them ideal for setting stop losses or identifying buy opportunities.
Volatility Spike (Proxy for News Trading):
ATR (Average True Range) Calculation: The indicator uses a 14-period ATR to measure market volatility. A volatility spike is identified when the ATR is greater than 1.5 times the 14-period SMA of the ATR.
Purpose:
This serves as a proxy for news events or other sudden market movements that could make the market unpredictable. The indicator avoids generating signals during these periods to reduce the risk of being caught in a volatile, potentially news-driven move.
Fibonacci Retracement Levels:
61.8% Fibonacci Level: Calculated from the highest high and lowest low over the long MA period, this retracement level is widely regarded as a significant support or resistance level.
Purpose:
Position traders often use Fibonacci levels to identify potential reversal points. The indicator incorporates the 61.8% level to fine-tune entries and exits.
Candlestick Patterns for Price Action Trading:
Bullish Engulfing Pattern: A bullish reversal pattern where a green candle fully engulfs the previous red candle.
Bearish Engulfing Pattern: A bearish reversal pattern where a red candle fully engulfs the previous green candle.
Purpose:
These patterns are classic signals used in price action trading to identify potential reversals at key levels, especially when they align with other conditions like support/resistance or Fibonacci levels.
Signal Generation:
The indicator generates buy and sell signals by combining the above elements:
Buy Signal:
A buy signal is triggered when:
The short-term MA crosses above the long-term MA (indicating a potential uptrend).
The trend is strong (ADX > 25).
The current price is near or below the 61.8% Fibonacci retracement level, suggesting a potential reversal.
No significant volatility spike is detected, ensuring the market isn’t reacting unpredictably to news.
Sell Signal:
A sell signal is triggered when:
The short-term MA crosses below the long-term MA (indicating a potential downtrend).
The trend is strong (ADX > 25).
The current price is near or above the 61.8% Fibonacci retracement level, suggesting potential resistance.
No significant volatility spike is detected.
Day Trading Signals:
Independent of the main trend signals, the indicator also generates intraday buy and sell signals when the price crosses above or below the 20-period day trading MA.
Price Action Signals:
The indicator can trigger buy or sell signals based purely on price action, such as the occurrence of bullish or bearish engulfing patterns. This is optional and can be enabled or disabled.
Alerts:
The indicator includes built-in alert conditions that notify the trader when a buy or sell signal is generated. This allows traders to act immediately without having to constantly monitor the charts.
Practical Application:
This indicator is versatile and can be used across various trading styles:
Position Trading: The long-term MA, Fibonacci retracement, and ADX provide a solid foundation for identifying long-term trends and potential entry/exit points.
Day Trading: The short-term MA and day trading MA offer quick signals for intraday trading.
Price Action: Candlestick pattern recognition allows for precise entry points based on market sentiment and behavior.
News Trading: The volatility spike filter helps avoid trading during periods of market instability, often driven by news events.
Conclusion:
The Comprehensive Trading Strategy Indicator is a robust tool designed to help traders navigate various market conditions by integrating multiple strategies into a single, coherent framework. It provides clear, actionable signals while filtering out potentially dangerous trades during volatile or weak market conditions. Whether you're a long-term trader, a day trader, or someone who relies on price action, this indicator can be a valuable addition to your trading toolkit.
Prometheus TTM SqueezeThe TTM indicator is an indicator used to better understand an underlying’s direction and volatility. Positive values indicate a rising price, negative falling. There is also an element of the underlying's volatility, explained below.
When, in this particular indicator, the zero line is the aqua color, that means that the volatility has picked up. In literal terms, it means that the upper Keltner Channel is above the upper Bollinger Band and the lower Keltner Channel is below the lower Bollinger Band. The range of the Keltner Channels is greater than the range of the Bollinger bands. What this is supposed to correlate to with price action is a more volatile choppier area. See below.
This is an example of volatility picking up being shown as the speed of the underlying. When the line turns aqua the move following tends to be sharp in the respective direction. Not a smooth delivery of price.
Regarding why this script is different from the others, with this script you do not need to input a bar's back value if you do not want to. Bars back being the amount of bars used in the indicator calculation. This is because of the use of Sum of Squared Errors, or SSE. How we do it is we calculate a Simple Moving Average or SMA and the indicator using a lot of different bars back values. Then if there is an event, characterized by the oscillator crossing over or under the 0 line, we subtract the close by the SMA and square it. If there is no event we return a big value, we want the error to be as small as possible. Because we loop over every value for bars back, we get the value with the smallest error. Or the SMA closest to the price ensuring we are following it as close as we can. This also becomes the value used as the multiplier for the Keltner Channels and Bollinger Bands, we simply divide them by 10 to normalize it. This leads to ease of use. A user does not need to worry about finding the best bars back for each ticker and time frame. We have you covered! SSE is not to be regarded to be the best given values for a pocket of the market, simply an estimation.
Of course we have the option for users to enter their own bars back or multipliers. Here is a comparison of the SSE at work and a 20 period bar’s back with 2 as the multiplier on a 4 hour $QQQ.
The top one is the SSE, the bottom is 20. I turned off showing the SMA, and alerts for better visibility. We see the SSE version does not cross above 0 again until the trend totally reverses. I would much rather overestimate risk than underestimate it.
The BULL and BEAR plotted on the chart is a result of the following conditions. A BULL if the price is above our auto optimized SMA and the oscillator crosses over 0. BEAR is the opposite, price below the SMA and an oscillator cross below 0. Here is the Daily NYSE:PLTR chart to show some.
Users have the options to toggle on and off the BULL and BEAR plots, SMA, as well as input their own lookback and multipliers.
We encourage traders to not follow indicators blindly, none are 100% accurate. SSE does not guarantee that the values generated will be the best for a given moment in time. Please comment on any desired updates, all criticism is welcome!
