Volume BaseVolume Base Indicator
Description:
The Volume Base indicator is designed to help traders identify significant price levels based on volume and price action. This tool utilizes pivot points to highlight swing highs and lows, providing visual cues for potential support and resistance areas.
Key Features:
Pivot Lookback: Customize the lookback period for identifying swing highs and lows, allowing for flexibility based on your trading strategy.
Swing Area Options: Choose between "Wick Extremity" and "Full Range" to define the area of interest for swing points, catering to different trading styles.
Intrabar Precision: Enable intrabar precision to analyze volume data on a lower timeframe, enhancing the accuracy of your signals.
Volume Filtering: Filter areas based on either the count of occurrences or the total volume, helping you focus on the most relevant price levels.
Visual Customization: Adjust colors and styles for swing highs, swing lows, and their respective areas to suit your personal preferences and improve chart readability.
Dynamic Labels and Zones: Automatically generated labels and zones for swing highs and lows provide clear visual indicators of potential market reversals or continuations.
How to Use:
Set the Lookback Period: Adjust the pivot lookback period to match your trading timeframe.
Select Swing Area Type: Choose whether to focus on the wick extremity or the full range of the swing.
Enable Intrabar Precision: If desired, turn on intrabar precision for more detailed volume analysis.
Filter Settings: Decide whether to filter by count or volume and set your threshold value accordingly.
Analyze the Chart: Observe the plotted swing highs and lows, along with their respective zones, to make informed trading decisions.
Disclaimer: This indicator is for educational purposes only and should not be considered financial advice. Always conduct your own research and analysis before making trading decisions.
Forecasting
Stockguru Intraday IndicatorAdvanced Buy & Sell Indicator with Pivot Lines & Labels Uses RSI, Volume MACD and pivot lines ✅ Buy (Green) & Sell (Red) Labels based on trend conditions
✅ Pivot Lines connecting highs and lows dynamically
✅ RSI & MACD for confirmation to filter noise
✅ Volume Spike Detection to avoid false signals
How This Works
Buy Signal (Green Label)
RSI crosses above 40 (momentum shifting bullish)
MACD crosses above signal line (trend reversal confirmation)
Price is above short & long moving averages (strong trend)
Volume spike filters weak signals
Sell Signal (Red Label)
RSI crosses below 60 (momentum shifting bearish)
MACD crosses below signal line (downtrend confirmation)
Price is below moving averages (trend weakness)
Volume spike confirms selling pressure
Pivot Lines
Blue Dashed Lines connect previous highs.
Orange Dashed Lines connect previous lows.
Helps identify support & resistance levels.
Trend Background Color
Green when a buy signal appears.
Red when a sell signal appears.
6-Hour Forecast (15m Steps) with Arrowed Lines & 95% CI -BesharaExplanation
Timeframe Conversion:
The helper function converts the chart’s timeframe (e.g., "15", "1H", etc.) into minutes so that the script can determine how many bars correspond to a 15‑minute interval.
Regression & Forecasting:
The script calculates a linear regression over the specified number of bars, approximates the slope, and computes the standard deviation of the residuals for error estimation. Then, for each forecast step (every 15 minutes for 6 hours), it extrapolates the forecast, calculates the 95% confidence interval, and draws red line segments connecting forecast points.
Visualization:
Arrows: At each forecast point, an arrow (▲ for upward, ▼ for downward, or → for unchanged) is drawn to indicate direction.
Confidence Intervals: Dotted orange lines display the 95% confidence interval at each forecast point.
Final Label: A label at the final forecast point shows the predicted price and its confidence interval.
Historical Regression: The blue line represents the historical regression line.
This script is provided for educational purposes only and does not guarantee predictive accuracy. Always use multiple tools and proper risk management in trading.
Supertrend with DEMA Strategy (Reversal Enabled)Just simple Supertrend with DEMA filter strategy.
Just for daylytrading with optional disabling long and short positions
Dynamic Pivot PointsDynamic Pivot Point Indicator
The Dynamic Pivot Point is an indicator used on the TradingView platform that dynamically calculates pivot points and displays them on the chart. This indicator provides automatically adjustable support and resistance levels for different timeframes. By visualizing dynamic levels that match current market conditions, traders can plan their strategies more effectively.
Features
Adapts to Timeframes
The indicator automatically selects the appropriate pivot calculation method based on the user's current timeframe. For example:
For short timeframes such as 1, 3, or 5 minutes, it uses daily (1D) data.
For medium timeframes like 15, 30, or 60 minutes, it uses weekly (1W) data.
For longer timeframes such as 120, 180, or 240 minutes, it uses monthly (1M) data.
For very long timeframes like 360, 480 minutes, daily (D), or weekly (1W), it uses 12-month (12M) data.
Dynamic Pivot Levels
The indicator automatically calculates pivot levels based on the specified high and low values.
Flexible Line Style Options
Users can choose different line styles (Dashed, Dotted, Solid) to improve visual clarity on the chart.
Clean and Clear Visualization
The indicator automatically removes previous lines and displays the latest levels clearly on the chart, preventing clutter and allowing traders to focus more efficiently.
How It Works
Identifying High and Low Levels
The indicator retrieves previous and current high and low levels based on the selected timeframe.
New high and low levels are updated by comparing them with previous levels.
Calculating Pivot Levels
Pivot points are calculated using Fibonacci ratios between high and low levels.
These levels represent dynamic support and resistance zones.
Drawing Lines
The calculated levels are displayed as lines on the chart, each represented with different colors and styles.
Use Cases
Support and Resistance Levels
The indicator dynamically calculates and displays support and resistance levels, serving as reference points for buy and sell decisions.
Trend Analysis
Fibonacci levels help identify trend strength and potential reversal points.
Risk Management
Pivot points assist in setting stop-loss and take-profit levels.
Multi-Timeframe Analysis
Since the indicator adapts to different timeframes, it can be used for both short-term and long-term analysis.
Advantages
✅ Automatic Calculation: No manual calculations are required, as it updates dynamically.
✅ Flexible Timeframe Support: Adapts to different timeframes.
✅ Visual Clarity: Line styles and colors make it easy to distinguish levels on the chart.
✅ Fibonacci Integration: Adds depth to technical analysis.
Conclusion
The Dynamic Pivot Point indicator is a useful tool for both beginners and experienced traders. By dynamically calculating pivot points and Fibonacci levels, it simplifies market analysis and aids in strategy development. With its flexible structure and clear visualization, it can be effectively used across all timeframes.
6 dakika önce
Sürüm Notları
This indicator is written for Support Resistance Traders
Bitcoin Power Law: Complete with Oscillator + Future Projection
Firstly, we would like to give credit to @apsk32 and @x_X_77_X_x as part of the code originates from their work. Additionally, @apsk32 is widely credited with applying the Power Law concept to Bitcoin and popularizing this model within the crypto community. Additionally, the visual layout is fully inspired by @apsk32's designs, and we think it looks amazing. So much so that we had to turn it into a TradingView script. Thank you!
Understanding the Bitcoin Power Law Model
Also called the Long-Term Bitcoin Power Law Model. The Bitcoin Power Law model tries to capture and predict Bitcoin's price growth over time. It assumes that Bitcoin's price follows an exponential growth pattern, where the price increases over time according to a mathematical relationship.
By fitting a power law to historical data, the model creates a trend line that represents this growth. It then generates additional parallel lines (support and resistance lines) to show potential price boundaries, helping to visualize where Bitcoin’s price could move within certain ranges.
In simple terms, the model helps us understand Bitcoin's general growth trajectory and provides a framework to visualize how its price could behave over the long term.
The Bitcoin Power Law has the following function:
Power Law = 10^(a + b * log10(d))
Consisting of the following parameters:
a: Power Law Intercept (default: -17.668).
b: Power Law Slope (default: 5.926).
d: Number of days since a reference point(calculated by counting bars from the reference point with an offset).
Explanation of the a and b parameters:
Roughly explained, the optimal values for the a and b parameters are determined through a process of linear regression on a log-log scale (after applying a logarithmic transformation to both the x and y axes). On this log-log scale, the power law relationship becomes linear, making it possible to apply linear regression. The best fit for the regression is then evaluated using metrics like the R-squared value, residual error analysis, and visual inspection. This process can be quite complex and is beyond the scope of this post.
Applying vertical shifts to generate the other lines:
Once the initial power-law is created, additional lines are generated by applying a vertical shift . This shift is achieved by adding a specific number of days (or years in case of this script) to the d-parameter. This creates new lines perfectly parallel to the initial power law with an added vertical shift, maintaining the same slope and intercept.
In the case of this script, shifts are made by adding +365 days, +2 * 365 days, +3 * 365 days, +4 * 365 days, and +5 * 365 days, effectively introducing one to five years of shifts. This results in a total of six Power Law lines, as outlined below (From lowest to highest):
Base Power Law Line (no shift)
1-year shifted line
2-year shifted line
3-year shifted line
4-year shifted line
5-year shifted line
The six power law lines:
Bitcoin Power Law Oscillator
This publication also includes the oscillator version of the Bitcoin Power Law. This version applies a logarithmic transformation to the price, Base Power Law Line, and 5-year shifted line using the formula log10(x) .
The log-transformed price is then normalized using min-max normalization relative to the log-transformed Base Power Law Line and 5-year shifted line with the formula:
normalized price = log(close) - log(Base Power Law Line) / log(5-year shifted line) - log(Base Power Law Line)
Finally, the normalized price was multiplied by 5 to map its value between 0 and 5, aligning with the shifted lines. The Oscillator version can be found here .
Interpretation of the Bitcoin Power Law Model:
The shifted Power Law lines provide a framework for predicting Bitcoin's future price movements based on historical trends. These lines are created by applying a vertical shift to the initial Power Law line, with each shifted line representing a future time frame (e.g., 1 year, 2 years, 3 years, etc.).
By analyzing these shifted lines, users can make predictions about minimum price levels at specific future dates. For example, the 5-year shifted line will act as the main support level for Bitcoin’s price in 5 years, meaning that Bitcoin’s price should not fall below this line, ensuring that Bitcoin will be valued at least at this level by that time. Similarly, the 2-year shifted line will serve as the support line for Bitcoin's price in 2 years, establishing that the price should not drop below this line within that time frame.
On the other hand, the 5-year shifted line also functions as an absolute resistance , meaning Bitcoin's price will not exceed this line prior to the 5-year mark. This provides a prediction that Bitcoin cannot reach certain price levels before a specific date. For example, the price of Bitcoin is unlikely to reach $100,000 before 2021, and it will not exceed this price before the 5-year shifted line becomes relevant. After 2028, however, the price is predicted to never fall below $100,000, thanks to the support established by the shifted lines.
In essence, the shifted Power Law lines offer a way to predict both the minimum price levels that Bitcoin will hit by certain dates and the earliest dates by which certain price points will be reached. These lines help frame Bitcoin's potential future price range, offering insight into long-term price behavior and providing a guide for investors and analysts. Lets examine some examples:
Example 1:
In Example 1 it can be seen that point A on the 5-year shifted line acts as major resistance . Also it can be seen that 5 years later this price level now corresponds to the Base Power Law Line and acts as a major support (Note: Vertical yearly grid lines have been added for this purpose👍).
Example 2:
In Example 2, the price level at point C on the 3-year shifted line becomes a major support three years later at point C, now aligning with the Base Power Law Line.
Finally, let's explore some future price predictions, as this script provides projections on the weekly timeframe :
Example 3:
In Example 3, the Bitcoin Power Law indicates that Bitcoin's price cannot surpass approximately $808K before 2030 as can be seen at point E, while also ensuring it will be at least $224K by then (point F).
Long Setup IdentifierDescription:
This indicator helps long-only traders identify potential entry points by detecting three key setups: Breakouts, Pullbacks, and Consolidations . It's designed for daily charts but can be adapted to other timeframes.
Key Features:
Breakout (B): Identifies when price breaks above a recent high with increased volume, signaling potential trend continuation or reversal.
Pullback (P): Detects retracements to the 50 EMA in an uptrend, offering potential entry points at support.
Consolidation (C): Highlights periods of low volatility, which often precede breakouts.
The indicator uses small, unobtrusive labels (B, P, C) to mark these setups on the chart, minimizing clutter while providing clear signals.
Customizable Parameters:
Lookback Period: Adjusts the historical data range for calculations.
Breakout Volume Multiplier: Sets the volume threshold for confirming breakouts.
Consolidation Threshold: Determines how tight the price range should be to qualify as consolidation.
This tool is ideal for traders focusing on momentum and trend-following strategies in bullish markets. It helps in identifying optimal entry points for long positions, whether you're looking to enter on breakouts, buy dips, or anticipate moves after consolidation periods.
Note: This indicator is for educational and informational purposes only. Always combine with other forms of analysis and risk management for best results.
RFX - Predator [Yoshio & Borges]Resposta que a IA deu:
Eu estou desenvolvendo um sistema que monitora cada moeda individualmente para identificar quando ela está em uma tendência clara e no ponto ideal de entrada.
Esse sistema analisa diferentes timeframes, levando em conta fatores como tendência macro, sobrecompra/sobrevenda e confirmações de movimento.
Com isso, eu consigo encontrar pares de moedas onde uma está em um forte momento de compra e a outra em um forte momento de venda, gerando setups de altíssima probabilidade.
Por exemplo, se meu sistema identificar que o dólar está enfraquecendo e o euro está ganhando força, ele pode sugerir uma compra em EUR/USD no momento exato em que o preço começar a confirmar a alta.
WEN_GPT - CDC Action Zone V.2**WEN_GPT - CDC Action Zone V.2 Strategy**
The **WEN_GPT - CDC Action Zone V.2 Strategy** is a trend-following strategy based on the **CDC Action Zone** indicator, which utilizes two exponential moving averages (EMAs) to identify bullish and bearish trends. This strategy is designed for medium-volatility markets and executes trades based on trend reversals.
**Key Features:**
- **EMA-Based Trend Detection:**
- A short EMA (Fast) and a long EMA (Slow) are calculated using an additional smoothing EMA (AP).
- A bullish trend is identified when the Fast EMA crosses above the Slow EMA.
- A bearish trend is identified when the Fast EMA crosses below the Slow EMA.
- **Trade Execution Logic:**
- **Long Entry:** Opens a long position when the trend shifts from bearish to bullish.
- **Exit Position:** Closes the long position when the trend shifts from bullish to bearish.
- **No Short Trades:** This strategy only takes long positions and exits instead of opening short trades.
- **Visual Elements for Market Analysis:**
- Plots the Fast and Slow EMAs on the chart.
- Uses dynamic bar coloring to represent different market conditions:
- **Green:** Strong bullish momentum.
- **Red:** Strong bearish momentum.
- **Yellow:** Weak bullish signal (caution).
- **Blue:** Weak bearish signal (caution).
- **Risk Management & Execution Settings:**
- Uses 100% of the account equity for each trade.
- Includes a **0.1% commission** and **3-point slippage** to simulate real trading conditions.
- Trades are only executed within the user-defined time range (default: **January 1, 2018 – December 31, 2030**).
This strategy is ideal for traders looking for **trend-following** setups with clear entry and exit signals. It provides a structured approach to capitalizing on trend shifts while maintaining an intuitive visual representation of market conditions.
EMA POD Indicator #gangesThis script is a technical analysis indicator that uses multiple Exponential Moving Averages (EMAs) to identify trends and track price changes in the market. Here's a breakdown:
EMA Calculation: It calculates six different EMAs (for periods 5, 10, 20, 50, 100, and 150) to track short- and long-term trends.
Trend Identification:
Uptrend: The script identifies an uptrend when the EMAs are in ascending order (EMA5 > EMA10 > EMA20 > EMA50 > EMA100 > EMA150).
Downtrend: A downtrend is identified when the EMAs are not in ascending order.
Trend Change Tracking: It tracks when an uptrend starts and ends, displaying the duration of the trend and the percentage price change during the trend.
Visuals:
It plots the EMAs on the chart with different colors.
It adds green and red lines to represent the ongoing uptrend and downtrend.
Labels are displayed showing when the uptrend starts and ends, along with the trend's duration and price change percentage.
In short, this indicator helps visualize trends, track their changes, and measure the impact of those trends on price.
WEN - SMA with RSI Strategy SMA with RSI Trading Strategy Description
The "SMA with RSI Strategy" is a technical analysis-based trading bot designed to identify potential entry and exit points in financial markets using a combination of Simple Moving Averages (SMA) and the Relative Strength Index (RSI). This strategy blends trend-following and momentum-filtering techniques to create a balanced approach suitable for various market conditions.
Key Features:
1. **Dual SMA Crossover System**:
- Utilizes two Simple Moving Averages with customizable periods:
- Short MA (default: 9 periods) – Faster-moving average to capture short-term price trends.
- Long MA (default: 21 periods) – Slower-moving average to identify longer-term trends.
- Generates buy signals when the Short MA crosses above the Long MA (bullish crossover).
- Generates sell signals when the Short MA crosses below the Long MA (bearish crossover).
2. **RSI Confirmation**:
- Incorporates the Relative Strength Index (default length: 14 periods) to filter trades and avoid overextended market conditions.
- Configurable overbought (default: 70) and oversold (default: 30) thresholds.
- Long entries are only executed if RSI is below the overbought level, preventing buys in potentially overextended upward moves.
- Short entries are only executed if RSI is above the oversold level, avoiding shorts in potentially overextended downward moves.
3. **Risk Management**:
- Built-in stop loss (default: 1%) and take profit (default: 2%) levels, calculated as percentages of the entry price.
- Automatically exits positions when either the stop loss or take profit is hit, helping to manage risk and lock in gains.
Trading Logic:
- **Long Entry**: Triggers when the Short MA crosses above the Long MA and RSI is below the overbought threshold, indicating a potential upward trend with room to grow.
- **Short Entry**: Triggers when the Short MA crosses below the Long MA and RSI is above the oversold threshold, signaling a potential downward trend with room to fall.
- **Exit**: Closes positions based on predefined stop loss or take profit levels, or when a short signal closes an existing long position.
Visual Indicators:
- Plots the Short MA (blue) and Long MA (red) on the price chart for easy trend visualization.
- RSI is typically displayed in a separate panel (platform-dependent) to monitor momentum.
Customization:
- All key parameters (MA lengths, RSI period, overbought/oversold levels, stop loss, and take profit) are adjustable, allowing traders to optimize the strategy for different markets, timeframes, and risk preferences.
Ideal Use Cases:
- Best suited for trending markets where SMA crossovers can capture sustained price movements.
- The RSI filter helps reduce false signals in choppy or ranging markets.
- Applicable to various asset classes (stocks, forex, cryptocurrencies, etc.) with proper parameter tuning.
This strategy offers a straightforward yet effective approach to automated trading, combining trend-following with momentum confirmation while maintaining robust risk management controls.
Wickless Candle Indicator with Extended Lines (final)This Pine Script indicator identifies “wickless” candles—those with no upper wick (when the close equals the high) or no lower wick (when the open equals the low)—and marks these events on the chart. When such a candle is detected, it:
Records the Level and Bar Index:
Saves the price level (high for wickless tops, low for wickless bottoms) and the bar index where the condition occurred.
Draws an Extended Horizontal Line:
Creates a green horizontal line for a wickless top or a red line for a wickless bottom, starting at the detection bar and extending across subsequent bars as long as the price remains below (for tops) or above (for bottoms) the recorded level.
Resets When the Price Breaks the Level:
If a future bar’s price moves beyond the saved level (i.e., a high above a wickless top or a low below a wickless bottom), the indicator resets that level, ending the extension of the line.
Visual Markers:
Additionally, it plots a small triangle above a wickless top and below a wickless bottom for easy identification on the chart.
Overall, this script helps traders visualize potential support or resistance levels created by candles that close at their highs or open at their lows, with lines that dynamically adjust as price evolves.
24-Hour Volume and Fibonacci Levels StrategyExplanation:
24-Hour High and Low: The script tracks the highest and lowest prices within the past 24 hours.
Fibonacci Levels: It calculates the Fibonacci retracement levels (23.6%, 38.2%, 61.8%, and 78.6%) based on the high and low of the past 24 hours.
Volume: The script plots a 20-period simple moving average (SMA) of the volume to give an indication of the market's activity.
Plotting Fibonacci Levels: The Fibonacci retracement levels are plotted on the chart with distinct colors.
Wick Size in USD with 10-Bar AverageWick Size in USD with 10-Bar Average
Version: 1.0
Author: QCodeTrader
🔍 Overview
This indicator converts the price wicks of your candlestick chart into USD values based on ticks, providing both raw and smoothed data via a 10-bar simple moving average. It helps traders visualize the monetary impact of price extremes, making it easier to assess volatility, potential risk, and plan appropriate stop loss levels.
⚙️ Key Features
Tick-Based Calculation:
Converts wick sizes into ticks (using a fixed tick size of 0.01, typical for stocks) and then into USD using a customizable tick value.
10-Bar Moving Average:
Smooths out the wick values over the last 10 bars, giving you a clearer view of average wick behavior.
Bullish/Bearish Visual Cues:
The chart background automatically highlights bullish candles in green and bearish candles in red for quick visual assessment.
Stop Loss Optimization:
The indicator highlights long wick sizes, which can help you set more accurate stop loss levels. Even when the price moves in your favor, long wicks may indicate potential reversals—allowing you to account for this risk when planning your stop losses.
User-Friendly Customization:
Easily adjust the USD value per tick through the settings to tailor the indicator to your specific instrument.
📊 How It Works
Wick Calculation:
The indicator calculates the upper and lower wicks by measuring the distance between the candle’s high/low and its body (open/close).
Conversion to Ticks & USD:
These wick sizes are first converted from price points to ticks (dividing by a fixed tick size of 0.01) and then multiplied by the user-defined tick value to convert the measurement into USD.
Smoothing Data:
A 10-bar simple moving average is computed for both the upper and lower wick values, providing smoothed data that helps identify trends and deviations.
Visual Representation:
Columns display the raw wick sizes in USD.
Lines indicate the 10-bar moving averages.
Background Color shifts between green (bullish) and red (bearish) based on candle type.
⚡ How to Use
Add the Indicator:
Apply it to your chart to begin visualizing wick sizes in monetary terms.
Customize Settings:
Adjust the Tick Value in USD in the settings to match your instrument’s tick value.
(Note: The tick size is fixed at 0.01, which is standard for many stocks.)
Optimize Your Stop Loss:
Analyze the raw and averaged wick values to understand volatility. Long wicks—even when the price moves in your favor—may indicate potential reversals. This insight can help you set more accurate stop loss levels to protect your gains.
Analyze:
Use the indicator’s data to gauge market volatility and assess the significance of price movements, aiding in more informed trading decisions.
This indicator is perfect for traders looking to understand the impact of extreme price movements in monetary terms, optimize stop loss levels, and effectively manage risk across stocks and other instruments with similar tick structures.
Window Seasonality IndicatorThis is a time window seasonal returns indicator. That is, it will provide the mean returns for a given time window based on a given number of lookbacks set by the user. The script finds matching time windows, e.g., 1st week of March going back 5 years or 9:00-10:00 window of every day going 50 days, and then calculates an average return for that window close price with respect to the close price in the immediately preceding time window, e.g. last week of February or 8:00-9:00 close price, respectively.
There are 4 input options:
1) Historical Periods to Average: Set the number of matching historical windows with which to calculate an average price. The max is 730 lookback windows. Note: for monthly or weekly windows, setting too large a number will cause the script to error out.
2) Use Open Price: calculates the seasonal returns using the open price rather than close price.
3) Show Bands: select from 1 Gaussian standard deviation or a nonparamateric ranked confidence interval. As a rough heuristic, the Gaussian band requires at least 30 lookback periods, and the ranked confidence interval requires 50 or more.
4) Upper Percentile: set the upper cutoff for ranked confidence interval.
5) Lower Percentile: set the lower cutoff for ranked confidence interval.
Please be aware, this indicator does not use rigorous statistical methodology and does not imply predictive power. You'll notice the range bands are very wide. Do not trade solely based on this indicator! Certain time windows, such as weekly and monthly, will make more sense applied to commodities, where annual cycles play a role in its supply and demand dynamics. Hourly windows are more useful in looking at equities markets. I like to look at equities with 1-hr windows to see if there is some pattern to overnight behavior or for market open and close.
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SSL Channel-JUANCHOSEGUIR LA TENDENCIA Y ENTRAR CUANDO LA SEGUNDA VELA CONFIRME LA TENDENCIA.
//@version=5
indicator("SSL Channel", shorttitle="SSL Channel", overlay=true, timeframe="", timeframe_gaps=false)
wicks = input(false, "Take Wicks into Account ?")
highlightState = input(true, "Highlight State ?")
ma(source, length, type) =>
type == "SMA" ? ta.sma(source, length) :
type == "EMA" ? ta.ema(source, length) :
type == "SMMA (RMA)" ? ta.rma(source, length) :
type == "WMA" ? ta.wma(source, length) :
type == "VWMA" ? ta.vwma(source, length) :
na
show_ma1 = input(true , "MA High", inline="MA #1", group="Channel №1")
ma1_type = input.string("SMA" , "" , inline="MA #1", options= , group="Channel №1")
ma1_source = input(high , "" , inline="MA #1", group="Channel №1")
ma1_length = input.int(200 , "" , inline="MA #1", minval=1, group="Channel №1")
ma1_color = input(color.green, "" , inline="MA #1", group="Channel №1")
ma1 = ma(ma1_source, ma1_length, ma1_type)
show_ma2 = input(true , "MA Low", inline="MA #2", group="Channel №1")
ma2_type = input.string("SMA" , "" , inline="MA #2", options= , group="Channel №1")
ma2_source = input(low , "" , inline="MA #2", group="Channel №1")
ma2_length = input.int(200 , "" , inline="MA #2", minval=1, group="Channel №1")
ma2_color = input(color.red, "" , inline="MA #2", group="Channel №1")
ma2 = ma(ma2_source, ma2_length, ma2_type)
showLabels1 = input(true, "Show Buy/Sell Labels ?", group="Channel №1")
show_ma3 = input(false , "MA High", inline="MA #3", group="Channel №2")
ma3_type = input.string("SMA" , "" , inline="MA #3", options= , group="Channel №2")
ma3_source = input(high , "" , inline="MA #3", group="Channel №2")
ma3_length = input.int(20 , "" , inline="MA #3", minval=1, group="Channel №2")
ma3_color = input(color.orange, "" , inline="MA #3", group="Channel №2")
ma3 = ma(ma3_source, ma3_length, ma3_type)
show_ma4 = input(false , "MA Low", inline="MA #4", group="Channel №2")
ma4_type = input.string("SMA" , "" , inline="MA #4", options= , group="Channel №2")
ma4_source = input(low , "" , inline="MA #4", group="Channel №2")
ma4_length = input.int(20 , "" , inline="MA #4", minval=1, group="Channel №2")
ma4_color = input(color.blue, "" , inline="MA #4", group="Channel №2")
ma4 = ma(ma4_source, ma4_length, ma4_type)
showLabels2 = input(true, "Show Buy/Sell Labels ?", group="Channel №2")
Hlv1 = float(na)
Hlv1 := (wicks ? high : close) > ma1 ? 1 : (wicks ? low : close) < ma2 ? -1 : Hlv1
sslUp1 = Hlv1 < 0 ? ma2 : ma1
sslDown1 = Hlv1 < 0 ? ma1 : ma2
Color1 = Hlv1 == 1 ? ma1_color : ma2_color
fillColor1 = highlightState ? (color.new(Color1, 90)) : na
highLine1 = plot(show_ma1 ? sslUp1 : na, title="UP", linewidth=2, color = Color1)
lowLine1 = plot(show_ma2 ? sslDown1 : na, title="DOWN", linewidth=2, color = Color1)
plotshape(show_ma1 and showLabels1 and Hlv1 == 1 and Hlv1 == -1, title="Buy Label", text="Buy", location=location.belowbar, style=shape.labelup, size=size.tiny, color=Color1, textcolor=color.white)
plotshape(show_ma2 and showLabels1 and Hlv1 == -1 and Hlv1 == 1, title="Sell Label", text="Sell", location=location.abovebar, style=shape.labeldown, size=size.tiny, color=Color1, textcolor=color.white)
fill(highLine1, lowLine1, color = fillColor1)
Hlv2 = float(na)
Hlv2 := (wicks ? high : close) > ma3 ? 1 : (wicks ? low : close) < ma4 ? -1 : Hlv2
sslUp2 = Hlv2 < 0 ? ma4 : ma3
sslDown2 = Hlv2 < 0 ? ma3 : ma4
Color2 = Hlv2 == 1 ? ma3_color : ma4_color
fillColor2 = highlightState ? (color.new(Color2, 90)) : na
highLine2 = plot(show_ma3 ? sslUp2 : na, title="UP", linewidth=2, color = Color2)
lowLine2 = plot(show_ma4 ? sslDown2 : na, title="DOWN", linewidth=2, color = Color2)
plotshape(show_ma3 and showLabels2 and Hlv2 == 1 and Hlv2 == -1, title="Buy Label", text="Buy", location=location.belowbar, style=shape.labelup, size=size.tiny, color=Color2, textcolor=color.white)
plotshape(show_ma4 and showLabels2 and Hlv2 == -1 and Hlv2 == 1, title="Sell Label", text="Sell", location=location.abovebar, style=shape.labeldown, size=size.tiny, color=Color2, textcolor=color.white)
fill(highLine2, lowLine2, color = fillColor2)
// Alerts
alertcondition(Hlv1 == 1 and Hlv1 == -1, title="SSL Channel (1) Buy Alert", message = "SSL Channel (1): BUY")
alertcondition(Hlv1 == -1 and Hlv1 == 1, title="SSL Channel (1) Sell Alert", message = "SSL Channel (1): SELL")
alertcondition(Hlv2 == 1 and Hlv2 == -1, title="SSL Channel (2) Buy Alert", message = "SSL Channel (2): BUY")
alertcondition(Hlv2 == -1 and Hlv2 == 1, title="SSL Channel (2) Sell Alert", message = "SSL Channel (2): SELL")
My Madam Dior....The Madam Dior indicator focuses on detecting RBR and DBD patterns, which signify periods of increased momentum and potential continuation or reversal of the prevailing trend.
The RBR pattern consists of a rally (upward movement), followed by a base (consolidation or retracement), and then another rally. It suggests that the upward momentum may persist and provide trading opportunities.
On the other hand, the DBD pattern comprises a drop (downward movement), followed by a base, and then another drop. It indicates that the downward momentum might continue, offering potential shorting opportunities.
Bullish(RBR)
Bearish(DBD)
1. The bullish (RBR) and bearish (DBD) patterns share the same underlying logic, only differing in their directionality.
2. For both RBR and DBD patterns, the first rise/drop can consist of one or multiple candles. However, in the case of multiple candles, all candles must exhibit a bullish nature for RBR and a bearish nature for DBD.
3. It is a prerequisite for the first rise/drop to include at least one candle with a defined percentage of health, as determined by the user.
4. The base, following the first rise/drop, may comprise one or multiple candles.
5. To maintain consistency, the base is not allowed to retrace beyond 80%, although this value can be adjusted by the user.
6. Similar to the first rise/drop, the second rise/drop in both RBR and DBD patterns can consist of one or multiple candles. However, all candles within this phase must demonstrate a bullish nature for RBR and a bearish nature for DBD.
7. Confirmation of the bullish (RBR) pattern occurs when a candle closes above the high of the first rise. Conversely, the bearish (DBD) pattern is confirmed when a candle closes below the low of the first drop.
Alerts can be set for all bullish and bearish pattern or for the first pattern in the range of similar pattern.
Opposite Delta Candle Highlighter with EMAs & Delta Boxes**Description:**
This indicator is designed to enhance market analysis by highlighting **candles with opposite-colored delta**, plotting **Exponential Moving Averages (EMAs)**, and displaying **delta volume as small boxes below the chart**.
🔹 **Key Features:**
✅ **Opposite Delta Candle Highlighting** – Candles where delta volume contradicts the price direction are highlighted with a **yellow background** and a **blue triangle** above the bar.
✅ **Three Exponential Moving Averages (EMAs)** – Includes **EMA (9, 21, 50)** to help identify trends and dynamic support/resistance levels.
✅ **Delta Volume Display** – Instead of large volume columns, delta is plotted as **small square boxes below the chart**, ensuring clear visibility without overlapping price candles.
✅ **Optimized for Lower Timeframes** – The indicator **automatically selects an appropriate lower timeframe** for more precise delta calculations.
🔹 **How It Works:**
- **Green Candle + Red Delta** → Opposite delta signal (Bearish Sign).
- **Red Candle + Green Delta** → Opposite delta signal (Bullish Sign).
- **Delta bars below the chart** indicate the strength of buying/selling pressure.
- **EMAs help identify the market trend** and potential trade entry zones.
🔹 **Use Cases:**
✔ **Scalping & Day Trading** – Identify potential reversals and trend continuation setups.
✔ **Volume Analysis** – Understand market participation and possible absorption.
✔ **Trend Confirmation** – Use EMAs to confirm trend direction alongside delta volume.
📌 *Best used with lower timeframes (1m, 5m, 15m) for detailed volume analysis.*
🚀 **Enhance your trading with real-time delta insights and price action analysis!**
Filtered Buy/Sell Signals After Stochastic Extreme Crossover//@version=5
indicator("Filtered Buy/Sell Signals After Stochastic Extreme Crossover", overlay=true)
// Define parameters
lr_period = 6
tma_period = 5
stoch_k = 8
stoch_d = 4
stoch_smooth = 4
// Compute Linear Regression Forecast (6, close)
linRegForecast = ta.linreg(close, lr_period, 0)
// Compute Triangular Moving Average (5)
tma = ta.sma(ta.sma(close, math.ceil(tma_period / 2)), tma_period)
// Compute the Average Line
averageLine = (linRegForecast + tma) / 2
// Compute Stochastic (8,4,4)
k = ta.sma(ta.stoch(close, high, low, stoch_k), stoch_smooth)
d = ta.sma(k, stoch_d)
// Track last confirmed Stochastic crossovers
var float lastBuyCrossover = na
var float lastSellCrossover = na
if ta.crossover(k, d) and k < 30
lastBuyCrossover := bar_index // Store the bar index of last Buy crossover below 30
if ta.crossunder(k, d) and k > 70
lastSellCrossover := bar_index // Store the bar index of last Sell crossover above 70
// Define Buy & Sell Signal Conditions with Confirmation
buySignal = ta.crossover(linRegForecast, tma) and lastBuyCrossover > lastSellCrossover
sellSignal = ta.crossunder(linRegForecast, tma) and lastSellCrossover > lastBuyCrossover
// Plot the indicators
plot(linRegForecast, color=color.blue, title="Linear Regression Forecast")
plot(tma, color=color.green, title="Triangular Moving Average (TMA)")
plot(averageLine, color=color.white, title="Average Line", linewidth=2) // White Average Line
// Plot Buy and Sell Signals
plotshape(series=buySignal, location=location.belowbar, color=color.green, style=shape.labelup, size=size.small, title="BUY")
plotshape(series=sellSignal, location=location.abovebar, color=color.red, style=shape.labeldown, size=size.small, title="SELL")
Filtered Buy/Sell Signals After Stochastic Extreme Crossover//@version=5
indicator("Filtered Buy/Sell Signals After Stochastic Extreme Crossover", overlay=true)
// Define parameters
lr_period = 6
tma_period = 5
stoch_k = 8
stoch_d = 4
stoch_smooth = 4
// Compute Linear Regression Forecast (6, close)
linRegForecast = ta.linreg(close, lr_period, 0)
// Compute Triangular Moving Average (5)
tma = ta.sma(ta.sma(close, math.ceil(tma_period / 2)), tma_period)
// Compute the Average Line
averageLine = (linRegForecast + tma) / 2
// Compute Stochastic (8,4,4)
k = ta.sma(ta.stoch(close, high, low, stoch_k), stoch_smooth)
d = ta.sma(k, stoch_d)
// Track last confirmed Stochastic crossovers
var float lastBuyCrossover = na
var float lastSellCrossover = na
if ta.crossover(k, d) and k < 30
lastBuyCrossover := bar_index // Store the bar index of last Buy crossover below 30
if ta.crossunder(k, d) and k > 70
lastSellCrossover := bar_index // Store the bar index of last Sell crossover above 70
// Define Buy & Sell Signal Conditions with Confirmation
buySignal = ta.crossover(linRegForecast, tma) and lastBuyCrossover > lastSellCrossover
sellSignal = ta.crossunder(linRegForecast, tma) and lastSellCrossover > lastBuyCrossover
// Plot the indicators
plot(linRegForecast, color=color.blue, title="Linear Regression Forecast")
plot(tma, color=color.green, title="Triangular Moving Average (TMA)")
plot(averageLine, color=color.white, title="Average Line", linewidth=2) // White Average Line
// Plot Buy and Sell Signals
plotshape(series=buySignal, location=location.belowbar, color=color.green, style=shape.labelup, size=size.small, title="BUY")
plotshape(series=sellSignal, location=location.abovebar, color=color.red, style=shape.labeldown, size=size.small, title="SELL")
GMMA Long-Short SignalIntroduction
This indicator is based on multiple EMA (Exponential Moving Average) constructions, aiming to identify buy and sell signals in the market. It calculates different periods of EMA lines and generates trading signals based on the relationship between prices and these EMA lines. This indicator is suitable for the TradingView platform and supports real-time alerts and chart drawing.
Indicator Composition
EMA Lines
This indicator calculates the following periods of EMA lines:
Short-term EMA lines: 3, 5, 8, 10, 12, 15
Medium-term EMA lines: 30, 35, 40, 45, 50, 60
Long-term EMA lines: 120, 140, 160, 180, 200, 240
These EMA lines are drawn on the chart with different colors and line widths, making it convenient for users to observe.
Trading Signals
The indicator generates four types of trading signals:
Buy Signal 1 (Buy 1): Triggered when the price meets the conditions of the short-term EMA line and the K-line is a bullish line.
Buy Signal 2 (Buy 2): Triggered when the price meets the conditions of the medium-term EMA line and the K-line is a bullish line.
Buy Signal 2 (Buy 3): Triggered when the price meets the conditions of the long-term EMA line and the K-line is a bullish line.
Sell Signal 1 (Sell 1): Triggered when the price meets the conditions of the short-term EMA line and the K-line is a bearish line.
Sell Signal 2 (Sell 2): Triggered when the price meets the conditions of the medium-term EMA line and the K-line is a bearish line.
Sell Signal 2 (Sell 2): Triggered when the price meets the conditions of the long-term EMA line and the K-line is a bearish line.
My usage method
I tend to rely on buy and sell signals 1 and 2.
Signal 3 is slightly lagging when it appears under normal circumstances, and entering at this time requires taking on greater risk, but it can be used as a reference for partial profit-taking.
I speculate that signal 3 may be credible when trading in highly volatile crazy stocks(WSB, meme...etc), as their prices fluctuate greatly (this speculation has not been verified by me, please judge for yourself).
The short, medium, and long-term EMMA indicators can mutually serve as support or resistance levels, and I personally prefer to use the long-term (red) EMMA as the final resistance or support.
If you find that signals appear frequently and buy and sell signals intersect, it usually means that the market is in a consolidation phase (box adjustment). At this time, you can either wait patiently for a candlestick that can break through the box to make a decision, or you can switch to a higher time-level candlestick chart, such as when multiple signals appear continuously on the 5-minute chart, switch to the 15-minute chart.
The above is my insight into using this indicator, and if you have a better strategy, you are welcome to leave a message. I will update the indicator according to the situation.
Wish we can all harvest rich profits!!!!!
