Swiss Knife [MERT]Introduction
The Swiss Knife indicator is a comprehensive trading tool designed to provide a multi-dimensional analysis of the market. By integrating a wide array of technical indicators across multiple timeframes, it offers traders a holistic view of market sentiment, momentum, and potential reversal points. This indicator is particularly useful for traders looking to combine trend analysis, momentum indicators, volume data, and price action into a single, easy-to-read format.
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Key Features
Multi-Timeframe Analysis : Evaluates indicators on Daily , 4-Hour , 1-Hour , and 15-Minute timeframes.
Comprehensive Indicator Suite : Incorporates MACD , Awesome Oscillator (AO) , Parabolic SAR , SuperTrend , DPO , RSI , Stochastic Oscillator , Bollinger Bands , Ichimoku Cloud , Chande Momentum Oscillator (CMO) , Donchian Channels , ADX , volume-based momentum indicators, Fractals , and divergence detection.
Market Sentiment Scoring : Aggregates signals from multiple indicators to provide an overall sentiment score.
Visual Aids : Displays EMA lines, trendlines, divergence signals, and a sentiment table directly on the chart.
Super Trend Reversal Signals : Identifies potential market reversal points by assessing the momentum of automated trading bots.
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Explanation of Each Indicator
Moving Average Convergence Divergence (MACD)
- Purpose : Measures the relationship between two moving averages of price.
- Interpretation : A positive histogram suggests bullish momentum; a negative histogram indicates bearish momentum.
Awesome Oscillator (AO)
- Purpose : Gauges market momentum by comparing recent market movements to historic ones.
- Interpretation : Above zero indicates bullish momentum; below zero indicates bearish momentum.
Parabolic SAR (SAR)
- Purpose : Identifies potential reversal points in price direction.
- Interpretation : Dots below price suggest an uptrend; dots above price suggest a downtrend.
SuperTrend
- Purpose : Determines the prevailing market trend.
- Interpretation : Provides buy or sell signals based on price movements relative to the SuperTrend line.
Detrended Price Oscillator (DPO)
- Purpose : Removes trend from price to identify cycles.
- Interpretation : Values above zero suggest price is above the moving average; values below zero indicate it is below.
Relative Strength Index (RSI)
- Purpose : Measures the speed and change of price movements.
- Interpretation : Values above 50 indicate bullish momentum; values below 50 indicate bearish momentum.
Stochastic Oscillator
- Purpose : Compares a particular closing price to a range of its prices over a certain period.
- Interpretation : Values above 50 indicate bullish conditions; values below 50 indicate bearish conditions.
Bollinger Bands (BB)
- Purpose : Measures market volatility and provides relative price levels.
- Interpretation : Price above the middle band suggests bullishness; below the middle band suggests bearishness.
Ichimoku Cloud
- Purpose : Provides support and resistance levels, trend direction, and momentum.
- Interpretation : Bullish signals when price is above the cloud; bearish signals when price is below the cloud.
Chande Momentum Oscillator (CMO)
- Purpose : Measures momentum on both up and down days.
- Interpretation : Values above 50 indicate strong upward momentum; values below -50 indicate strong downward momentum.
Donchian Channels
- Purpose : Identifies volatility and potential breakouts.
- Interpretation : Price above the upper band suggests bullish breakout; below the lower band suggests bearish breakout.
Average Directional Index (ADX)
- Purpose : Measures the strength of a trend.
- Interpretation : DI+ above DI- indicates bullish trend; DI- above DI+ indicates bearish trend.
Volume Momentum Indicators (VolMom, CumVolMom, POCMom)
- Purpose : Analyze volume to assess buying and selling pressure.
- Interpretation : Positive values suggest bullish volume momentum; negative values indicate bearish volume momentum.
Fractals
- Purpose : Identify potential reversal points in the market.
- Interpretation : Up fractals may indicate a future downtrend; down fractals may indicate a future uptrend.
Divergence Detection
- Purpose : Identifies divergences between price and various indicators (RSI, MACD, Stochastic, OBV, MFI, A/D Line).
- Interpretation : Bullish divergences suggest potential upward reversal; bearish divergences suggest potential downward reversal.
- Note : This functionality utilizes the library from Divergence Indicator .
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Coloring Scheme
Background Color
- Purpose : Reflects the overall market sentiment by combining sentiment scores from all indicators across different timeframes.
- Interpretation :
- Green Shades : Indicate bullish market sentiment.
- Red Shades : Indicate bearish market sentiment.
- Intensity : The strength of the color corresponds to the strength of the sentiment score.
Sentiment Table
- Purpose : Displays the status of each indicator across different timeframes.
- Interpretation :
- Green Cell : The indicator suggests a bullish signal.
- Red Cell : The indicator suggests a bearish signal.
- Percentage Score : Indicates the overall bullish or bearish sentiment on that timeframe.
Exponential Moving Averages (EMAs)
- Purpose : Provide dynamic support and resistance levels.
- Colors :
- EMA 10 : Lime
- EMA 20 : Yellow
- EMA 50 : Orange
- EMA 100 : Red
- EMA 200 : Purple
Trendlines
- Purpose : Visual representation of support and resistance levels based on pivot points.
- Interpretation :
- Upward Trendlines : Colored green , indicating support levels.
- Downward Trendlines : Colored red , indicating resistance levels.
- Note : Trendlines are drawn using the library from Simple Trendlines .
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Utility of Market Sentiment
The indicator aggregates signals from multiple technical indicators across various timeframes to compute an overall market sentiment score . This comprehensive approach helps traders understand the prevailing market conditions by:
Confirming Trends : Multiple indicators pointing in the same direction can confirm the strength of a trend.
Identifying Reversals : Divergences and fractals can signal potential turning points.
Timeframe Alignment : Aligning signals across different timeframes can enhance the probability of successful trades.
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Divergences
Divergence occurs when the price of an asset moves in the opposite direction of a technical indicator, suggesting a potential reversal.
- Bullish Divergence : Price makes a lower low, but the indicator makes a higher low.
- Bearish Divergence : Price makes a higher high, but the indicator makes a lower high.
The indicator detects divergences for:
RSI
MACD
Stochastic Oscillator
On-Balance Volume (OBV)
Money Flow Index (MFI)
Accumulation/Distribution Line (A/D Line)
By identifying these divergences, traders can spot early signs of trend reversals and adjust their strategies accordingly.
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Trendlines
Trendlines are essential tools for identifying support and resistance levels. The indicator automatically draws trendlines based on pivot points:
- Upward Trendlines (Support) : Connect higher lows, indicating an uptrend.
- Downward Trendlines (Resistance) : Connect lower highs, indicating a downtrend.
These trendlines help traders visualize the trend direction and potential breakout or reversal points.
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Super Trend Reversals (ST Reversal)
The core idea behind the Super Trend Reversals indicator is to assess the momentum of automated trading bots (often referred to as 'Supertrend bots') that enter the market during critical turning points. Specifically, the indicator is tuned to identify when the market is nearing bottoms or peaks, just before it shifts direction based on the triggered Supertrend signals. This approach helps traders:
Engage Early : Enter the market as reversal momentum builds up.
Optimize Entries and Exits : Enter under favorable conditions and exit before momentum wanes.
By capturing these reversal points, traders can enhance their trading performance.
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Conclusion
The Swiss Knife indicator serves as a versatile tool that combines multiple technical analysis methods into a single, comprehensive indicator. By assessing various aspects of the market—including trend direction, momentum, volume, and price action—it provides traders with valuable insights to make informed trading decisions.
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Citations
- Divergence Detection Library : Divergence Indicator by DevLucem
- Trendline Drawing Library : Simple Trendlines by HoanGhetti
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Note : This indicator is intended for informational purposes and should be used in conjunction with other analysis techniques. Always perform due diligence before making trading decisions.
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Komut dosyalarını "momentum" için ara
Uptrick: RSI Histogram
1. **Introduction to the RSI and Moving Averages**
2. **Detailed Breakdown of the Uptrick: RSI Histogram**
3. **Calculation and Formula**
4. **Visual Representation**
5. **Customization and User Settings**
6. **Trading Strategies and Applications**
7. **Risk Management**
8. **Case Studies and Examples**
9. **Comparison with Other Indicators**
10. **Advanced Usage and Tips**
---
## 1. Introduction to the RSI and Moving Averages
### **1.1 Relative Strength Index (RSI)**
The Relative Strength Index (RSI) is a momentum oscillator developed by J. Welles Wilder and introduced in his 1978 book "New Concepts in Technical Trading Systems." It is widely used in technical analysis to measure the speed and change of price movements.
**Purpose of RSI:**
- **Identify Overbought/Oversold Conditions:** RSI values range from 0 to 100. Traditionally, values above 70 are considered overbought, while values below 30 are considered oversold. These thresholds help traders identify potential reversal points in the market.
- **Trend Strength Measurement:** RSI also indicates the strength of a trend. High RSI values suggest strong bullish momentum, while low values indicate bearish momentum.
**Calculation of RSI:**
1. **Calculate the Average Gain and Loss:** Over a specified period (e.g., 14 days), calculate the average gain and loss.
2. **Compute the Relative Strength (RS):** RS is the ratio of average gain to average loss.
3. **RSI Formula:** RSI = 100 - (100 / (1 + RS))
### **1.2 Moving Averages (MA)**
Moving Averages are used to smooth out price data and identify trends by filtering out short-term fluctuations. Two common types are:
**Simple Moving Average (SMA):** The average of prices over a specified number of periods.
**Exponential Moving Average (EMA):** A type of moving average that gives more weight to recent prices, making it more responsive to recent price changes.
**Smoothed Moving Average (SMA):** Used to reduce the impact of volatility and provide a clearer view of the underlying trend. The RMA, or Running Moving Average, used in the USH script is similar to an EMA but based on the average of RSI values.
## 2. Detailed Breakdown of the Uptrick: RSI Histogram
### **2.1 Indicator Overview**
The Uptrick: RSI Histogram (USH) is a technical analysis tool that combines the RSI with a moving average to create a histogram that reflects momentum and trend strength.
**Key Components:**
- **RSI Calculation:** Determines the relative strength of price movements.
- **Moving Average Application:** Smooths the RSI values to provide a clearer trend indication.
- **Histogram Plotting:** Visualizes the deviation of the smoothed RSI from a neutral level.
### **2.2 Indicator Purpose**
The primary purpose of the USH is to provide a clear visual representation of the market's momentum and trend strength. It helps traders identify:
- **Bullish and Bearish Trends:** By showing how far the smoothed RSI is from the neutral 50 level.
- **Potential Reversal Points:** By highlighting changes in momentum.
### **2.3 Indicator Design**
**RSI Moving Average (RSI MA):** The RSI MA is a smoothed version of the RSI, calculated using a running moving average. This smooths out short-term fluctuations and provides a clearer indication of the underlying trend.
**Histogram Calculation:**
- **Neutral Level:** The histogram is plotted relative to the neutral level of 50. This level represents a balanced market where neither bulls nor bears have dominance.
- **Histogram Values:** The histogram bars show the difference between the RSI MA and the neutral level. Positive values indicate bullish momentum, while negative values indicate bearish momentum.
## 3. Calculation and Formula
### **3.1 RSI Calculation**
The RSI calculation involves:
1. **Average Gain and Loss:** Calculated over the specified length (e.g., 14 periods).
2. **Relative Strength (RS):** RS = Average Gain / Average Loss.
3. **RSI Formula:** RSI = 100 - (100 / (1 + RS)).
### **3.2 Moving Average Calculation**
For the USH indicator, the RSI is smoothed using a running moving average (RMA). The RMA formula is similar to that of the EMA but is based on averaging RSI values over the specified length.
### **3.3 Histogram Calculation**
The histogram value is calculated as:
- **Histogram Value = RSI MA - 50**
**Plotting the Histogram:**
- **Positive Histogram Values:** Indicate that the RSI MA is above the neutral level, suggesting bullish momentum.
- **Negative Histogram Values:** Indicate that the RSI MA is below the neutral level, suggesting bearish momentum.
## 4. Visual Representation
### **4.1 Histogram Bars**
The histogram is plotted as bars on the chart:
- **Bullish Bars:** Colored green when the RSI MA is above 50.
- **Bearish Bars:** Colored red when the RSI MA is below 50.
### **4.2 Customization Options**
Traders can customize:
- **RSI Length:** Adjust the length of the RSI calculation to match their trading style.
- **Bull and Bear Colors:** Choose colors for histogram bars to enhance visual clarity.
### **4.3 Interpretation**
**Bullish Signal:** A histogram bar that moves from red to green indicates a potential shift to a bullish trend.
**Bearish Signal:** A histogram bar that moves from green to red indicates a potential shift to a bearish trend.
## 5. Customization and User Settings
### **5.1 Adjusting RSI Length**
The length parameter determines the number of periods over which the RSI is calculated and smoothed. Shorter lengths make the RSI more sensitive to price changes, while longer lengths provide a smoother view of trends.
### **5.2 Color Settings**
Traders can adjust:
- **Bull Color:** Color of histogram bars indicating bullish momentum.
- **Bear Color:** Color of histogram bars indicating bearish momentum.
**Customization Benefits:**
- **Visual Clarity:** Traders can choose colors that stand out against their chart’s background.
- **Personal Preference:** Adjust settings to match individual trading styles and preferences.
## 6. Trading Strategies and Applications
### **6.1 Trend Following**
**Identifying Entry Points:**
- **Bullish Entry:** When the histogram changes from red to green, it signals a potential entry point for long positions.
- **Bearish Entry:** When the histogram changes from green to red, it signals a potential entry point for short positions.
**Trend Confirmation:** The histogram helps confirm the strength of a trend. Strong, consistent green bars indicate robust bullish momentum, while strong, consistent red bars indicate robust bearish momentum.
### **6.2 Swing Trading**
**Momentum Analysis:**
- **Entry Signals:** Look for significant shifts in the histogram to time entries. A shift from bearish to bullish (red to green) indicates potential for upward movement.
- **Exit Signals:** A shift from bullish to bearish (green to red) suggests a potential weakening of the trend, signaling an exit or reversal point.
### **6.3 Range Trading**
**Market Conditions:**
- **Consolidation:** The histogram close to zero suggests a range-bound market. Traders can use this information to identify support and resistance levels.
- **Breakout Potential:** A significant move away from the neutral level may indicate a potential breakout from the range.
### **6.4 Risk Management**
**Stop-Loss Placement:**
- **Bullish Positions:** Place stop-loss orders below recent support levels when the histogram is green.
- **Bearish Positions:** Place stop-loss orders above recent resistance levels when the histogram is red.
**Position Sizing:** Adjust position sizes based on the strength of the histogram signals. Strong trends (indicated by larger histogram bars) may warrant larger positions, while weaker signals suggest smaller positions.
## 7. Risk Management
### **7.1 Importance of Risk Management**
Effective risk management is crucial for long-term trading success. It involves protecting capital, managing losses, and optimizing trade setups.
### **7.2 Using USH for Risk Management**
**Stop-Loss and Take-Profit Levels:**
- **Stop-Loss Orders:** Use the histogram to set stop-loss levels based on trend strength. For instance, place stops below support levels in bullish trends and above resistance levels in bearish trends.
- **Take-Profit Targets:** Adjust take-profit levels based on histogram changes. For example, lock in profits as the histogram starts to shift from green to red.
**Position Sizing:**
- **Trend Strength:** Scale position sizes based on the strength of histogram signals. Larger histogram bars indicate stronger trends, which may justify larger positions.
- **Volatility:** Consider market volatility and adjust position sizes to mitigate risk.
## 8. Case Studies and Examples
### **8.1 Example 1: Bullish Trend**
**Scenario:** A trader notices a transition from red to green histogram bars.
**Analysis:**
- **Entry Point:** The transition indicates a potential bullish trend. The trader decides to enter a long position.
- **Stop-Loss:** Set stop-loss below recent support levels.
- **Take-Profit:** Consider taking profits as the histogram moves back towards zero or turns red.
**Outcome:** The bullish trend continues, and the histogram remains green, providing a profitable trade setup.
### **8.2 Example 2: Bearish Trend**
**Scenario:** A trader observes a transition from green to red histogram bars.
**Analysis:**
- **Entry Point:** The transition suggests a potential
bearish trend. The trader decides to enter a short position.
- **Stop-Loss:** Set stop-loss above recent resistance levels.
- **Take-Profit:** Consider taking profits as the histogram approaches zero or shifts to green.
**Outcome:** The bearish trend continues, and the histogram remains red, resulting in a successful trade.
## 9. Comparison with Other Indicators
### **9.1 RSI vs. USH**
**RSI:** Measures momentum and identifies overbought/oversold conditions.
**USH:** Builds on RSI by incorporating a moving average and histogram to provide a clearer view of trend strength and momentum.
### **9.2 RSI vs. MACD**
**MACD (Moving Average Convergence Divergence):** A trend-following momentum indicator that uses moving averages to identify changes in trend direction.
**Comparison:**
- **USH:** Provides a smoothed RSI perspective and visual histogram for trend strength.
- **MACD:** Offers signals based on the convergence and divergence of moving averages.
### **9.3 RSI vs. Stochastic Oscillator**
**Stochastic Oscillator:** Measures the level of the closing price relative to the high-low range over a specified period.
**Comparison:**
- **USH:** Focuses on smoothed RSI values and histogram representation.
- **Stochastic Oscillator:** Provides overbought/oversold signals and potential reversals based on price levels.
## 10. Advanced Usage and Tips
### **10.1 Combining Indicators**
**Multi-Indicator Strategies:** Combine the USH with other technical indicators (e.g., Moving Averages, Bollinger Bands) for a comprehensive trading strategy.
**Confirmation Signals:** Use the USH to confirm signals from other indicators. For instance, a bullish histogram combined with a moving average crossover may provide a stronger buy signal.
### **10.2 Customization Tips**
**Adjust RSI Length:** Experiment with different RSI lengths to match various market conditions and trading styles.
**Color Preferences:** Choose histogram colors that enhance visibility and align with personal preferences.
### **10.3 Continuous Learning**
**Backtesting:** Regularly backtest the USH with historical data to refine strategies and improve accuracy.
**Education:** Stay updated with trading education and adapt strategies based on market changes and personal experiences.
MLMomentumIndexLibrary "MLMomentumIndex"
Enables market momentum analysis with k-NN predictions on pivot points, offering customizable parameters for dynamic trading strategies.
momentumIndexPivots(source, pivotBars, momentumWindow, maxData, numNeighbors, predictionSmoothing)
Parameters:
source (float)
pivotBars (int)
momentumWindow (int)
maxData (int)
numNeighbors (int)
predictionSmoothing (int)
ULTRA RSI 2025//@version=6
indicator(title="ULTRA RSI 2025", shorttitle="ULTRA RSI 2025", format=format.price, precision=2)
// ==================== CONFIGURAÇÃO VISUAL FUTURISTA ====================
cyberTheme = input.string("IC", title="🎨 Tema Visual", options= , group="🎨 Visual Settings")
showGradients = input.bool(true, title="🎨 Exibir Preenchimentos em Gradiente", group="🎨 Visual Settings")
glowIntensity = input.float(0.3, title="🎨 Intensidade do Brilho", minval=0.0, maxval=1.0, step=0.1, group="🎨 Visual Settings")
// Cores para hline (usando input.color)
overboughtColor = input.color(color.new(#ff0000, 20), title="📈 Cor Sobrevendido", group="🎨 Visual Settings")
oversoldColor = input.color(color.new(#31fc09, 20), title="📉 Cor Sobrecomprado", group="🎨 Visual Settings")
midlineColor = input.color(color.new(#ffffff, 81), title="⚡ Cor da Linha Média", group="🎨 Visual Settings")
// ==================== CORES FUTURISTAS ====================
getThemeColors() =>
switch cyberTheme
"IC" =>
"Matrix Green" =>
"Tron Orange" =>
"Blade Runner Pink" =>
=>
= getThemeColors()
// Colores adicionales cyber
cyberGreen = color.new(#39FF14, 0)
cyberRed = color.new(#FF073A, 0)
darkCyber = color.new(#0D1117, 0)
neonWhite = color.new(#FFFFFF, 0)
// ==================== CÓDIGO RSI ORIGINAL (SIN MODIFICAR) ====================
rsiLengthInput = input.int(14, minval=1, title=" RSI Length", group=" RSI Settings")
rsiSourceInput = input.source(close, " Source", group=" RSI Settings")
calculateDivergence = input.bool(false, title=" Calculate Divergence", group=" RSI Settings", display = display.data_window, tooltip = "Calculating divergences is needed in order for divergence alerts to fire.")
change = ta.change(rsiSourceInput)
up = ta.rma(math.max(change, 0), rsiLengthInput)
down = ta.rma(-math.min(change, 0), rsiLengthInput)
rsi = down == 0 ? 100 : up == 0 ? 0 : 100 - (100 / (1 + up / down))
// ==================== VISUAL FUTURISTA ====================
// Color dinámico para el RSI
getRsiColor(rsiValue) =>
if rsiValue >= 80
neonPrimary // Azul neón para sobrecomprado
else if rsiValue >= 70
color.new(neonPrimary, 30)
else if rsiValue <= 20
cyberRed // Rojo cyber para sobrevendido
else if rsiValue <= 30
color.new(cyberRed, 30)
else if rsiValue > 50
color.new(cyberGreen, 40)
else
color.new(neonSecondary, 50)
rsiColor = getRsiColor(rsi)
glowColor = color.new(rsiColor, math.round(100 - glowIntensity * 100))
// Plot RSI con efecto glow futurista
rsiPlot = plot(rsi, "🔮 Cyber RSI", color=rsiColor, linewidth=3)
plot(rsi, "✨ RSI Glow 1", color=glowColor, linewidth=5)
plot(rsi, "✨ RSI Glow 2", color=color.new(rsiColor, 90), linewidth=7)
// Líneas de banda con estilo cyber
rsiUpperBand = hline(70, "🔥 Cyber Overbought", color=overboughtColor, linestyle=hline.style_dashed, linewidth=2)
midline = hline(50, " Cyber Midline", color=midlineColor, linestyle=hline.style_dotted)
rsiLowerBand = hline(30, "❄️ Cyber Oversold", color=oversoldColor, linestyle=hline.style_dashed, linewidth=2)
// Background fills futuristas
midLinePlot = plot(50, color = na, editable = false, display = display.none)
// Fill condicional usando operador ternario
backgroundFillColor = showGradients ? color.new(darkCyber, 90) : na
overboughtFillColor = showGradients ? color.new(neonPrimary, 0) : na
overboughtFillColorBottom = showGradients ? color.new(neonPrimary, 100) : na
oversoldFillColorTop = showGradients ? color.new(neonSecondary, 100) : na
oversoldFillColorBottom = showGradients ? color.new(neonSecondary, 0) : na
fill(rsiUpperBand, rsiLowerBand, color=backgroundFillColor, title="🌃 Cyber Background")
fill(rsiPlot, midLinePlot, 100, 70, top_color = overboughtFillColor, bottom_color = overboughtFillColorBottom, title = "🌌 Cyber Overbought Zone")
fill(rsiPlot, midLinePlot, 30, 0, top_color = oversoldFillColorTop, bottom_color = oversoldFillColorBottom, title = "🌌 Cyber Oversold Zone")
// ==================== SMOOTHING MA (CÓDIGO ORIGINAL) ====================
GRP = "🌊 Smoothing"
TT_BB = "Only applies when 'SMA + Bollinger Bands' is selected. Determines the distance between the SMA and the bands."
maTypeInput = input.string("SMA", "Type", options = , group = GRP, display = display.data_window)
maLengthInput = input.int(14, "Length", group = GRP, display = display.data_window)
bbMultInput = input.float(2.0, "BB StdDev", minval = 0.001, maxval = 50, step = 0.5, tooltip = TT_BB, group = GRP, display = display.data_window)
var enableMA = maTypeInput != "None"
var isBB = maTypeInput == "SMA + Bollinger Bands"
// Smoothing MA Calculation (CÓDIGO ORIGINAL)
ma(source, length, MAtype) =>
switch MAtype
"SMA" => ta.sma(source, length)
"SMA + Bollinger Bands" => ta.sma(source, length)
"EMA" => ta.ema(source, length)
"SMMA (RMA)" => ta.rma(source, length)
"WMA" => ta.wma(source, length)
"VWMA" => ta.vwma(source, length)
// Smoothing MA plots con colores cyber
smoothingMA = enableMA ? ma(rsi, maLengthInput, maTypeInput) : na
smoothingStDev = isBB ? ta.stdev(rsi, maLengthInput) * bbMultInput : na
plot(smoothingMA, "🌊 Cyber MA", color=color.new(color.yellow, 0), linewidth=2, display = enableMA ? display.all : display.none, editable = enableMA)
bbUpperBand = plot(smoothingMA + smoothingStDev, title = "🔺 Upper Cyber Band", color=neonPrimary, linewidth=2, display = isBB ? display.all : display.none, editable = isBB)
bbLowerBand = plot(smoothingMA - smoothingStDev, title = "🔻 Lower Cyber Band", color=neonSecondary, linewidth=2, display = isBB ? display.all : display.none, editable = isBB)
// Fill para Bollinger Bands
bbFillColor = isBB ? color.new(neonPrimary, 90) : na
fill(bbUpperBand, bbLowerBand, color=bbFillColor, title="🌌 Cyber Bollinger Fill", display = isBB ? display.all : display.none, editable = isBB)
// ==================== DIVERGENCE (CÓDIGO ORIGINAL CORREGIDO) ====================
lookbackRight = 5
lookbackLeft = 5
rangeUpper = 60
rangeLower = 5
bearColor = cyberRed
bullColor = cyberGreen
textColor = neonWhite
noneColor = color.new(color.white, 100)
// Función _inRange calculada en cada barra
_inRange(bool cond) =>
bars = ta.barssince(cond)
rangeLower <= bars and bars <= rangeUpper
plFound = false
phFound = false
bullCond = false
bearCond = false
rsiLBR = rsi
// Calcular _inRange en cada barra para evitar inconsistencias
plFoundPrev = not na(ta.pivotlow(rsi, lookbackLeft, lookbackRight) )
phFoundPrev = not na(ta.pivothigh(rsi, lookbackLeft, lookbackRight) )
inRangeBull = _inRange(plFoundPrev)
inRangeBear = _inRange(phFoundPrev)
if calculateDivergence
//------------------------------------------------------------------------------
// Regular Bullish
// rsi: Higher Low
plFound := not na(ta.pivotlow(rsi, lookbackLeft, lookbackRight))
rsiHL = rsiLBR > ta.valuewhen(plFound, rsiLBR, 1) and inRangeBull
// Price: Lower Low
lowLBR = low
priceLL = lowLBR < ta.valuewhen(plFound, lowLBR, 1)
bullCond := priceLL and rsiHL and plFound
//------------------------------------------------------------------------------
// Regular Bearish
// rsi: Lower High
phFound := not na(ta.pivothigh(rsi, lookbackLeft, lookbackRight))
rsiLH = rsiLBR < ta.valuewhen(phFound, rsiLBR, 1) and inRangeBear
// Price: Higher High
highLBR = high
priceHH = highLBR > ta.valuewhen(phFound, highLBR, 1)
bearCond := priceHH and rsiLH and phFound
// Divergence plots con estilo cyber
plot(
plFound ? rsiLBR : na,
offset = -lookbackRight,
title = "🚀 Cyber Bull Divergence",
linewidth = 3,
color = (bullCond ? bullColor : noneColor),
display = display.pane,
editable = calculateDivergence)
plotshape(
bullCond ? rsiLBR : na,
offset = -lookbackRight,
title = "🚀 Cyber Bull Signal",
text = "🚀 BULL",
style = shape.labelup,
location = location.absolute,
color = bullColor,
textcolor = textColor,
size = size.normal,
display = display.pane,
editable = calculateDivergence)
plot(
phFound ? rsiLBR : na,
offset = -lookbackRight,
title = "🔻 Cyber Bear Divergence",
linewidth = 3,
color = (bearCond ? bearColor : noneColor),
display = display.pane,
editable = calculateDivergence)
plotshape(
bearCond ? rsiLBR : na,
offset = -lookbackRight,
title = "🔻 Cyber Bear Signal",
text = "🔻 BEAR",
style = shape.labeldown,
location = location.absolute,
color = bearColor,
textcolor = textColor,
size = size.normal,
display = display.pane,
editable = calculateDivergence)
// ==================== TABLA DE INFORMACIÓN CYBER ====================
// Calcular ta.change en cada barra para consistencia
rsiChange3 = ta.change(rsi, 3)
if barstate.islast
var table infoTable = table.new(position.top_right, 2, 5,
bgcolor=color.new(darkCyber, 10),
border_width=2,
border_color=neonPrimary,
frame_width=3,
frame_color=neonSecondary)
table.clear(infoTable, 0, 0, 1, 4)
table.cell(infoTable, 0, 0, " ULTRA RSI", bgcolor=neonPrimary, text_color=neonWhite, text_size=size.small)
table.cell(infoTable, 1, 0, " INFO", bgcolor=neonSecondary, text_color=neonWhite, text_size=size.small)
table.cell(infoTable, 0, 1, " VALOR RSI", bgcolor=color.new(darkCyber, 30), text_color=neonPrimary, text_size=size.small)
table.cell(infoTable, 1, 1, str.tostring(math.round(rsi, 2)), bgcolor=color.new(darkCyber, 30), text_color=neonWhite, text_size=size.small)
rsiStatus = rsi >= 70 ? " SOBRENDIDO" : rsi <= 30 ? " SOBRECOMPRADO" : " NEUTRO"
statusColor = rsi >= 70 ? cyberRed : rsi <= 30 ? cyberGreen : neonWhite
table.cell(infoTable, 0, 2, " MOMENTO", bgcolor=color.new(darkCyber, 30), text_color=neonSecondary, text_size=size.small)
table.cell(infoTable, 1, 2, rsiStatus, bgcolor=color.new(darkCyber, 30), text_color=statusColor, text_size=size.small)
if enableMA
table.cell(infoTable, 0, 3, " EMA RSI", bgcolor=color.new(darkCyber, 30), text_color=neonPrimary, text_size=size.small)
table.cell(infoTable, 1, 3, str.tostring(math.round(smoothingMA, 2)), bgcolor=color.new(darkCyber, 30), text_color=neonWhite, text_size=size.small)
momentum = rsiChange3 > 0 ? " SUBINDO" : " CAINDO"
momentumColor = rsiChange3 > 0 ? cyberGreen : cyberRed
table.cell(infoTable, 0, 4, " TENDÊNCIA", bgcolor=color.new(darkCyber, 30), text_color=neonPrimary, text_size=size.small)
table.cell(infoTable, 1, 4, momentum, bgcolor=color.new(darkCyber, 30), text_color=momentumColor, text_size=size.small)
// ==================== ALERTS (CÓDIGO ORIGINAL) ====================
alertcondition(bullCond, title='🚀 Cyber Bullish Divergence', message="🎯 Found a new Cyber Bullish Divergence!")
alertcondition(bearCond, title='🔻 Cyber Bearish Divergence', message='🎯 Found a new Cyber Bearish Divergence!')
Awesome_Accelerator_Zone OscillatorExplanation and Usage Guide for AO_AC_ZONE Oscillator
Indicator Overview
The **AO_AC_ZONE** oscillator is based on the concepts introduced by **Bill Williams** in his book *New Trading Dimensions*. This indicator combines the **Awesome Oscillator (AO)**, **Accelerator Oscillator (AC)**, and a custom **Zone Oscillator**, visualizing them together in a clear, color-coded format.
The Zone Oscillator is derived from the relationship between AO and AC, indicating the market's dominant momentum state (bullish, bearish, or neutral). It also integrates real-time candle coloring to visually align price bars with the Zone's momentum.
---
**Components**
1. **Awesome Oscillator (AO)**:
- AO measures the difference between a 5-period and 34-period Simple Moving Average (SMA) applied to the midpoints of candles.
- It reflects market momentum, where:
- Green bars = increasing momentum
- Red bars = decreasing momentum
2. **Accelerator Oscillator (AC)**:
- AC is calculated as the difference between AO and its 5-period SMA.
- It indicates the acceleration or deceleration of market momentum.
- Fuchsia bars = increasing momentum
- Purple bars = decreasing momentum
3. **Zone Oscillator**:
- The Zone combines AO and AC states:
- **Green Zone**: Both AO and AC are positive (bullish momentum).
- **Red Zone**: Both AO and AC are negative (bearish momentum).
- **Gray Zone**: AO and AC have differing signs (neutral/uncertain momentum).
- Candle colors dynamically match the Zone’s state for enhanced visual clarity.
---
**How to Use the Indicator**
**1. Interpreting the Oscillators**
- **AO**: Use it to detect momentum direction and changes. Pay attention to shifts in bar color:
- **Increasing AO (Aqua)**: Bullish momentum gaining strength.
- **Decreasing AO (Navy)**: Bullish momentum weakening or bearish momentum strengthening.
- **AC**: Provides early signals of momentum shifts.
- If AC changes color ahead of AO, it signals potential trend reversals or accelerations.
**2. Using the Zone Oscillator**
- **Green Zone**:
- Both AO and AC are positive.
- Indicates a strong bullish trend. Look for buying opportunities in line with the trend.
- **Red Zone**:
- Both AO and AC are negative.
- Signals strong bearish momentum. Look for shorting opportunities.
- **Gray Zone**:
- AO and AC are in conflict.
- Represents uncertainty; avoid trading or wait for a clear signal.
---
**Real-Time Application**
**Candle Coloring**
- The indicator modifies candle colors to match the Zone Oscillator's state:
- **Green Candles**: Strong bullish momentum.
- **Red Candles**: Strong bearish momentum.
- **Gray Candles**: Neutral momentum.
**Recommended Strategy (Based on New Trading Dimensions)**:
1. **Identify the Zone**:
- Focus on Green Zones for long entries and Red Zones for short entries.
2. **Look for AO/AC Confirmation**:
- Enter trades in the direction of both AO and AC when they align with the Zone.
- For exits, monitor when AO and AC conflict (Gray Zone).
3. **Use in Combination**:
- Combine this oscillator with fractals or trend indicators to confirm signals.
---
**Benefits**
- Visualizes momentum strength, acceleration, and alignment in one chart.
- Simplifies decision-making by integrating price action with oscillator dynamics.
- Supports faster trade identification and execution by highlighting bullish, bearish, and neutral zones.
---
**Disclaimer**
This indicator is a tool to assist in market analysis. Always incorporate proper risk management and avoid trading during uncertain conditions (Gray Zones). For optimal results, use this oscillator in conjunction with other analysis methods like support/resistance, volume analysis, and trend-following systems.
The Flash-Strategy with Minervini Stage Analysis QualifierThe Flash-Strategy (Momentum-RSI, EMA-crossover, ATR) with Minervini Stage Analysis Qualifier
Introduction
Welcome to a comprehensive guide on a cutting-edge trading strategy I've developed, designed for the modern trader seeking an edge in today's dynamic markets. This strategy, which I've honed through my years of experience in the trading arena, stands out for its unique blend of technical analysis and market intuition, tailored specifically for use on the TradingView platform.
As a trader with a deep passion for the financial markets, my journey began several years ago, driven by a relentless pursuit of a trading methodology that is both effective and adaptable. My background in trading spans various market conditions and asset classes, providing me with a rich tapestry of experiences from which to draw. This strategy is the culmination of that journey, embodying the lessons learned and insights gained along the way.
The cornerstone of this strategy lies in its ability to generate precise long signals in a Stage 2 uptrend and equally accurate short signals in a Stage 4 downtrend. This approach is rooted in the principles of trend following and momentum trading, harnessing the power of key indicators such as the Momentum-RSI, EMA Crossover, and Average True Range (ATR). What sets this strategy apart is its meticulous design, which allows it to adapt to the ever-changing market conditions, providing traders with a robust tool for navigating both bullish and bearish scenarios.
This strategy was born out of a desire to create a trading system that is not only highly effective in identifying potential trade setups but also straightforward enough to be implemented by traders of varying skill levels. It's a reflection of my belief that successful trading hinges on clarity, precision, and disciplined execution. Whether you are a seasoned trader or just beginning your journey, this guide aims to provide you with a comprehensive understanding of how to harness the full potential of this strategy in your trading endeavors.
In the following sections, we will delve deeper into the mechanics of the strategy, its implementation, and how to make the most out of its features. Join me as we explore the nuances of a strategy that is designed to elevate your trading to the next level.
Stage-Specific Signal Generation
A distinctive feature of this trading strategy is its focus on generating long signals exclusively during Stage 2 uptrends and short signals during Stage 4 downtrends. This approach is based on the widely recognized market cycle theory, which divides the market into four stages: Stage 1 (accumulation), Stage 2 (uptrend), Stage 3 (distribution), and Stage 4 (downtrend). By aligning the signal generation with these specific stages, the strategy aims to capitalize on the most dynamic and clear-cut market movements, thereby enhancing the potential for profitable trades.
1. Long Signals in Stage 2 Uptrends
• Characteristics of Stage 2: Stage 2 is characterized by a strong uptrend, where prices are consistently rising. This stage typically follows a period of accumulation (Stage 1) and is marked by increased investor interest and bullish sentiment in the market.
• Criteria for Long Signal Generation: Long signals are generated during this stage when the technical indicators align with the characteristics of a Stage 2 uptrend.
• Rationale for Stage-Specific Signals: By focusing on Stage 2 for long trades, the strategy seeks to enter positions during the phase of strong upward momentum, thus riding the wave of rising prices and investor optimism. This stage-specific approach minimizes exposure to less predictable market phases, like the consolidation in Stage 1 or the indecision in Stage 3.
2. Short Signals in Stage 4 Downtrends
• Characteristics of Stage 4: Stage 4 is identified by a pronounced downtrend, with declining prices indicating prevailing bearish sentiment. This stage typically follows the distribution phase (Stage 3) and is characterized by increasing selling pressure.
• Criteria for Short Signal Generation: Short signals are generated in this stage when the indicators reflect a strong bearish trend.
• Rationale for Stage-Specific Signals: Targeting Stage 4 for shorting capitalizes on the market's downward momentum. This tactic aligns with the natural market cycle, allowing traders to exploit the downward price movements effectively. By doing so, the strategy avoids the potential pitfalls of shorting during the early or late stages of the market cycle, where trends are less defined and more susceptible to reversals.
In conclusion, the strategy’s emphasis on stage-specific signal generation is a testament to its sophisticated understanding of market dynamics. By tailoring the long and short signals to Stages 2 and 4, respectively, it leverages the most compelling phases of the market cycle, offering traders a clear and structured approach to aligning their trades with dominant market trends.
Strategy Overview
At the heart of this trading strategy is a philosophy centered around capturing market momentum and trend efficiency. The core objective is to identify and capitalize on clear uptrends and downtrends, thereby allowing traders to position themselves in sync with the market's prevailing direction. This approach is grounded in the belief that aligning trades with these dominant market forces can lead to more consistent and profitable outcomes.
The strategy is built on three foundational components, each playing a critical role in the decision-making process:
1. Momentum-RSI (Relative Strength Index): The Momentum-RSI is a pivotal element of this strategy. It's an enhanced version of the traditional RSI, fine-tuned to better capture the strength and velocity of market trends. By measuring the speed and change of price movements, the Momentum-RSI provides invaluable insights into whether a market is potentially overbought or oversold, suggesting possible entry and exit points. This indicator is especially effective in filtering out noise and focusing on substantial market moves.
2. EMA (Exponential Moving Average) Crossover: The EMA Crossover is a crucial component for trend identification. This strategy employs two EMAs with different timeframes to determine the market trend. When the shorter-term EMA crosses above the longer-term EMA, it signals an emerging uptrend, suggesting a potential long entry. Conversely, a crossover below indicates a possible downtrend, hinting at a short entry opportunity. This simple yet powerful tool is key in confirming trend directions and timing market entries.
3. ATR (Average True Range): The ATR is instrumental in assessing market volatility. This indicator helps in understanding the average range of price movements over a given period, thus providing a sense of how much a market might move on a typical day. In this strategy, the ATR is used to adjust stop-loss levels and to gauge the potential risk and reward of trades. It allows for more informed decisions by aligning trade management techniques with the current volatility conditions.
The synergy of these three components – the Momentum-RSI, EMA Crossover, and ATR – creates a robust framework for this trading strategy. By combining momentum analysis, trend identification, and volatility assessment, the strategy offers a comprehensive approach to navigating the markets. Whether it's capturing a strong trend in its early stages or identifying a potential reversal, this strategy aims to provide traders with the tools and insights needed to make well-informed, strategically sound trading decisions.
Detailed Component Analysis
The efficacy of this trading strategy hinges on the synergistic functioning of its three key components: the Momentum-RSI, EMA Crossover, and Average True Range (ATR). Each component brings a unique perspective to the strategy, contributing to a well-rounded approach to market analysis.
1. Momentum-RSI (Relative Strength Index)
• Definition and Function: The Momentum-RSI is a modified version of the classic Relative Strength Index. While the traditional RSI measures the velocity and magnitude of directional price movements, the Momentum-RSI amplifies aspects that reflect trend strength and momentum.
• Significance in Identifying Trend Strength: This indicator excels in identifying the strength behind a market's move. A high Momentum-RSI value typically indicates strong bullish momentum, suggesting the potential continuation of an uptrend. Conversely, a low Momentum-RSI value signals strong bearish momentum, possibly indicative of an ongoing downtrend.
• Application in Strategy: In this strategy, the Momentum-RSI is used to gauge the underlying strength of market trends. It helps in filtering out minor fluctuations and focusing on significant movements, providing a clearer picture of the market's true momentum.
2. EMA (Exponential Moving Average) Crossover
• Definition and Function: The EMA Crossover component utilizes two exponential moving averages of different timeframes. Unlike simple moving averages, EMAs give more weight to recent prices, making them more responsive to new information.
• Contribution to Market Direction: The interaction between the short-term and long-term EMAs is key to determining market direction. A crossover of the shorter EMA above the longer EMA is an indicator of an emerging uptrend, while a crossover below signals a developing downtrend.
• Application in Strategy: The EMA Crossover serves as a trend confirmation tool. It provides a clear, visual representation of the market's direction, aiding in the decision-making process for entering long or short positions. This component ensures that trades are aligned with the prevailing market trend, a crucial factor for the success of the strategy.
3. ATR (Average True Range)
• Definition and Function: The ATR is an indicator that measures market volatility by calculating the average range between the high and low prices over a specified period.
• Role in Assessing Market Volatility: The ATR provides insights into the typical market movement within a given timeframe, offering a measure of the market's volatility. Higher ATR values indicate increased volatility, while lower values suggest a calmer market environment.
• Application in Strategy: Within this strategy, the ATR is instrumental in tailoring risk management techniques, particularly in setting stop-loss levels. By accounting for the market's volatility, the ATR ensures that stop-loss orders are placed at levels that are neither too tight (risking premature exits) nor too loose (exposing to excessive risk).
In summary, the combination of Momentum-RSI, EMA Crossover, and ATR in this trading strategy provides a comprehensive toolkit for market analysis. The Momentum-RSI identifies the strength of market trends, the EMA Crossover confirms the market direction, and the ATR guides in risk management by assessing volatility. Together, these components form the backbone of a strategy designed to navigate the complexities of the financial markets effectively.
1. Signal Generation Process
• Combining Indicators: The strategy operates by synthesizing signals from the Momentum-RSI, EMA Crossover, and ATR indicators. Each indicator serves a specific purpose: the Momentum-RSI gauges trend momentum, the EMA Crossover identifies the trend direction, and the ATR assesses the market’s volatility.
• Criteria for Signal Validation: For a signal to be considered valid, it must meet specific criteria set by each of the three indicators. This multi-layered approach ensures that signals are not only based on one aspect of market behavior but are a result of a comprehensive analysis.
2. Conditions for Long Positions
• Uptrend Confirmation: A long position signal is generated when the shorter-term EMA crosses above the longer-term EMA, indicating an uptrend.
• Momentum-RSI Alignment: Alongside the EMA crossover, the Momentum-RSI should indicate strong bullish momentum. This is typically represented by the Momentum-RSI being at a high level, confirming the strength of the uptrend.
• ATR Consideration: The ATR is used to fine-tune the entry point and set an appropriate stop-loss level. In a low volatility scenario, as indicated by the ATR, the stop-loss can be set tighter, closer to the entry point.
3. Conditions for Short Positions
• Downtrend Confirmation: Conversely, a short position signal is indicated when the shorter-term EMA crosses below the longer-term EMA, signaling a downtrend.
• Momentum-RSI Confirmation: The Momentum-RSI should reflect strong bearish momentum, usually seen when the Momentum-RSI is at a low level. This confirms the bearish strength of the market.
• ATR Application: The ATR again plays a role in determining the stop-loss level for the short position. Higher volatility, as indicated by a higher ATR, would warrant a wider stop-loss to accommodate larger market swings.
By adhering to these mechanics, the strategy aims to ensure that each trade is entered with a high probability of success, aligning with the market’s current momentum and trend. The integration of these indicators allows for a holistic market analysis, providing traders with clear and actionable signals for both entering and exiting trades.
Customizable Parameters in the Strategy
Flexibility and adaptability are key features of this trading strategy, achieved through a range of customizable parameters. These parameters allow traders to tailor the strategy to their individual trading style, risk tolerance, and specific market conditions. By adjusting these parameters, users can fine-tune the strategy to optimize its performance and align it with their unique trading objectives. Below are the primary parameters that can be customized within the strategy:
1. Momentum-RSI Settings
• Period: The lookback period for the Momentum-RSI can be adjusted. A shorter period makes the indicator more sensitive to recent price changes, while a longer period smoothens the RSI line, offering a broader view of the momentum.
• Overbought/Oversold Thresholds: Users can set their own overbought and oversold levels, which can help in identifying extreme market conditions more precisely according to their trading approach.
2. EMA Crossover Settings
• Timeframes for EMAs: The strategy uses two EMAs with different timeframes. Traders can modify these timeframes, choosing shorter periods for a more responsive approach or longer periods for a more conservative one.
• Source Data: The choice of price data (close, open, high, low) used in calculating the EMAs can be varied depending on the trader’s preference.
3. ATR Settings
• Lookback Period: Adjusting the lookback period for the ATR impacts how the indicator measures volatility. A longer period may provide a more stable but less responsive measure, while a shorter period offers quicker but potentially more erratic readings.
• Multiplier for Stop-Loss Calculation: This parameter allows traders to set how aggressively or conservatively they want their stop-loss to be in relation to the ATR value.
Here are the standard settings:
VXD SupercycleVXD is a brand new indicator and still developing. to minimize stop losses and overcome sideways market conditions, Higher Timeframe are recommended
Trend lines
-using Rolling VWAP as trend line to determined if Volume related to a certain price.
-you can switch RVWAP to EMA in the setting
ATR
-trailing 12*ATR and 2.4 Mutiplier
Pivot point and Rejected Block
Pivot show last High and low of a price in past bars
Rejected Block show when that High or Low price are important level to determined if it's Hidden Divergence or Divergence
Symbols on chart show Premium and Discount Prices
X-Cross - show potential reversal trend with weak volume .
O-circle - show potential reversal trend with strong volume .
Setting
Momentum: RSI = 25 , RSI MA = 14
Trend: Rolling VWAP and ATR and Subhag
Trailing STOP: ATR 12 x 2.4
Highlight Bars color when volume is above SMA 6
SMA200 act as TP Line
Risk:Reward Calculation
if Buy your Stoploss will be previous Pivot low
if Sell your Stoploss will be previous Pivot high and will be calculated form there, then show TP in Orange color line
VXD เป็นระบบเทรดที่ผมทดลองเอาหลาย ๆ ไอเดีย ทั้งจาก Youtube facebook และกลุ่มคนต่าง ๆ มารวบรวมไว้ แล้วตกผลึกขึ้นมาเป็นระบบนี้ ใน Timeframe ใหญ่ ๆ สามารถลากได้ทั้ง Cycle กันเลย
Trend lines
-ใช้ Rolling VWAP ของแอพ Tradingview (สามารถตั้งแค่าเป็น EMA ได้)
ATR
-ใช้ค่า ATR 12 Mutiplier 2.4
Pivot point and Rejected Block
Pivot โชว์เส้น High low และมีผลกับออเดอร์ หากแท่งเทียนปิดทะลุเส้นนี้
Rejected Block วาดแนวรับ-ต้าน อัตโนมัติ ใช้ประกอบ RSI ว่ามี Divergence หรือไม่
สัญลักษณ์ต่าง ๆ
X-Cross - แท่งกลืนกิน วอลุ่มน้อย
O-circle - แท่งกลืนกิน มีวอลุ่ม
Setting
Momentum: RSI = 25 , RSI MA = 14
Trend: Rolling VWAP and ATR and Subhag
Trailing STOP: ATR 12 x 2.4
Highlight Bars color when volume is above SMA 6
SMA200 act as TP Line
Risk:Reward Calculation
หาก Buy จุด SL จะอยู่ที่ Pivot low
หาก Sell จุด SL จะอยู่ที่ Pivot high และระบบจะคำนวณจากตรงนั้น จากนั้นแสดงเป็นเส้น TP สีส้ม
This Strategy Combined the following indicators and conditioning by me
ATR , RSI , EMA , SMA
Rolling VWAP - /script/ZU2UUu9T-Rolling-VWAP/
Regression Lines - Subhag form Subhag Ghosh /script/LHHBVpQu-Subhag-Ghosh-Algo-Version-for-banknifty/
Rejection Block , Pivots , High Volume Bars and PPDD form Super OrderBlock / FVG / BoS Tools by makuchaku & eFe /script/aZACDmTC-Super-OrderBlock-FVG-BoS-Tools-by-makuchaku-eFe/
ขอให้รวยครับ.
Canuck Trading Projection IndicatorCanuck Trading Projection Indicator
Overview
The Canuck Trading Projection Indicator is a powerful PineScript v6 tool designed for TradingView to project potential bullish and bearish price trajectories based on historical price and volume movements. It provides traders with actionable insights by estimating future price targets and assigning confidence levels to each outlook, helping to identify probable market directions across any timeframe. Ideal for both short-term and long-term traders, this indicator combines momentum analysis, RSI filtering, support/resistance detection, and time-weighted trend analysis to deliver robust projections.
Features
Bullish and Bearish Projections: Forecasts price targets for upward (bullish) and downward (bearish) movements over a user-defined projection period (default 20 bars).
Confidence Levels: Assigns percentage confidence scores to each outlook, reflecting the likelihood of the projected price based on historical trends, volatility, and volume.
RSI Filter: Incorporates a 14-period Relative Strength Index (RSI) to validate trends, requiring RSI > 50 for bullish and RSI < 50 for bearish signals.
Support/Resistance Detection: Adjusts confidence levels when projections are near key swing highs/lows (within 2% of average price), boosting confidence by 5% for alignments.
Time-Based Weighting: Prioritizes recent price movements in trend analysis, giving more weight to newer bars for improved relevance.
Customizable Inputs: Allows users to tailor lookback period, projection bars, RSI period, confidence threshold, colors, and label positioning.
Forced Label Spacing: Prevents overlap of bullish and bearish text labels, even for tight projections, using fixed vertical slots when price differences are small (<2% of average price).
Timeframe Flexibility: Works seamlessly across all TradingView timeframes (e.g., 30-minute, hourly, daily, weekly, monthly), adapting projections to the chart’s resolution.
Clean Visualization: Displays projections as green (bullish) and red (bearish) dashed lines, with non-overlapping text labels at the projection endpoints showing price targets and confidence levels.
How It Works
The indicator analyzes historical price and volume data over a user-defined lookback period (default 50 bars) to calculate:
Momentum: Combines price changes and volume to assess trend strength, using a weighted moving average (WMA) for directional bias.
Trend Analysis: Counts bullish (price up, volume above average, RSI > 50) and bearish (price down, volume above average, RSI < 50) trends, weighting recent bars more heavily.
Projections:
Bullish Slope: Positive or flat when momentum is upward, scaled by price change and momentum intensity.
Bearish Slope: Negative or flat when momentum is downward, amplified by bearish confidence for stronger projections.
Projects prices forward by 20 bars (default) using current close plus slope times projection bars.
Confidence Levels:
Base confidence derived from the proportion of bullish/bearish trends, with a 5% minimum to avoid zero confidence.
Adjusted by volatility (lower volatility increases confidence), volume trends, and proximity to support/resistance levels.
Visualization:
Draws projection lines from the current close to the 20-bar future target.
Places text labels at line endpoints, showing price targets and confidence percentages, with forced spacing for readability.
Input Parameters
Lookback Period (default: 50): Number of bars for historical analysis (minimum 10).
Projection Bars (default: 20): Number of bars to project forward (minimum 5).
Confidence Threshold (default: 0.6): Minimum confidence for strong trend indication (0.1 to 1.0).
Bullish Projection Line Color (default: Green): Color for bullish projection line and label.
Bearish Projection Line Color (default: Red): Color for bearish projection line and label.
RSI Period (default: 14): Period for RSI momentum filter (minimum 5).
Label Vertical Offset (%) (default: 1.0): Base offset for labels as a percentage of price range (0.1% to 5.0%).
Minimum Label Spacing (%) (default: 2.0): Minimum vertical spacing between labels for tight projections (0.5% to 10.0%).
Usage Instructions
Add to Chart: Copy the script into TradingView’s Pine Editor, save, and add the indicator to your chart.
Select Timeframe: Apply to any timeframe (e.g., 30-minute, hourly, daily, weekly, monthly) to match your trading strategy.
Interpret Outputs:
Green Line/Label: Bullish price target and confidence (e.g., "Bullish: 414.37, Confidence: 35%").
Red Line/Label: Bearish price target and confidence (e.g., "Bearish: 279.08, Confidence: 41.3%").
Higher confidence indicates a stronger likelihood of the projected outcome.
Adjust Inputs:
Modify Lookback Period to focus on shorter/longer historical trends (e.g., 20 for short-term, 100 for long-term).
Change Projection Bars to adjust forecast horizon (e.g., 10 for shorter, 50 for longer).
Tweak RSI Period or Confidence Threshold for sensitivity to momentum or trend strength.
Customize Colors for visual preference.
Increase Minimum Label Spacing if labels overlap in volatile markets.
Combine with Analysis: Use alongside other indicators (e.g., moving averages, Bollinger Bands) or fundamental analysis to confirm signals, as projections are probabilistic.
Example: TSLA Across Timeframes
Using live TSLA data (close ~346.46 USD, May 31, 2025), the indicator produces:
30-Minute: Bullish 341.93 (13.3%), Bearish 327.96 (86.7%) – Strong bearish sentiment due to intraday volatility.
1-Hour: Bullish 342.00 (33.9%), Bearish 327.50 (62.3%) – Bearish but less intense, reflecting hourly swings.
4-Hour: Bullish 345.52 (73.4%), Bearish 344.44 (19.0%) – Flat outlook, indicating consolidation.
Daily: Bullish 391.26 (68.8%), Bearish 302.22 (31.2%) – Bullish bias from recent uptrend, bearish tempered by longer lookback.
Weekly: Bullish 414.37 (35.0%), Bearish 279.08 (41.3%) – Wide range, reflecting annual volatility.
Monthly: Bullish 396.70 (54.9%), Bearish 296.93 (10.2%) – Long-term bullish optimism.
These results align with market dynamics: short-term intervals capture volatility, while longer intervals smooth trends, providing balanced outlooks.
Notes
Accuracy: Projections are estimates based on historical data and should be used with other analysis tools. Confidence levels indicate likelihood, not certainty.
Timeframe Sensitivity: Short-term intervals (e.g., 30-minute) show larger price swings and higher confidence due to volatility, while longer intervals (e.g., monthly) are more stable.
Customization: Adjust inputs to match your trading style (e.g., shorter lookback for day trading, longer for swing trading).
Performance: Tested on volatile stocks like TSLA, NVIDIA, and others, ensuring robust performance across markets.
Limitations: May produce conservative bearish projections in strong uptrends due to momentum weighting. Adjust lookback or projection_bars for sensitivity.
Feedback
If you encounter issues (e.g., label overlap, projection mismatches), please share your timeframe, settings, or a screenshot. Suggestions for enhancements (e.g., additional filters, visual tweaks) are welcome!
Disclaimer
The Canuck Trading Projection Indicator is provided for educational and informational purposes only. It is not financial advice. Trading involves significant risks, and past performance is not indicative of future results. Always perform your own due diligence and consult a qualified financial advisor before making trading decisions.
Cointegration Buy and Sell Signals [EdgeTerminal]The Cointegration Buy And Sell Signals is a sophisticated technical analysis tool to spot high-probability market turning points — before they fully develop on price charts.
Most reversal indicators rely on raw price action, visual patterns, or basic and common indicator logic — which often suffer in noisy or trending markets. In most cases, they lag behind the actual change in trend and provide useless and late signals.
This indicator is rooted in advanced concepts from statistical arbitrage, mean reversion theory, and quantitative finance, and it packages these ideas in a user-friendly visual format that works on any timeframe and asset class.
It does this by analyzing how the short-term and long-term EMAs behave relative to each other — and uses statistical filters like Z-score, correlation, volatility normalization, and stationarity tests to issue highly selective Buy and Sell signals.
This tool provides statistical confirmation of trend exhaustion, allowing you to trade mean-reverting setups. It fades overextended moves and uses signal stacking to reduce false entries. The entire indicator is based on a very interesting mathematically grounded model which I will get into down below.
Here’s how the indicator works at a high level:
EMAs as Anchors: It starts with two Exponential Moving Averages (EMAs) — one short-term and one long-term — to track market direction.
Statistical Spread (Regression Residuals): It performs a rolling linear regression between the short and long EMA. Instead of using the raw difference (short - long), it calculates the regression residual, which better models their natural relationship.
Normalize the Spread: The spread is divided by historical price volatility (ATR) to make it scale-invariant. This ensures the indicator works on low-priced stocks, high-priced indices, and crypto alike.
Z-Score: It computes a Z-score of the normalized spread to measure how “extreme” the current deviation is from its historical average.
Dynamic Thresholds: Unlike most tools that use fixed thresholds (like Z = ±2), this one calculates dynamic thresholds using historical percentiles (e.g., top 10% and bottom 10%) so that it adapts to the asset's current behavior to reduce false signals based on market’s extreme volatility at a certain time.
Z-Score Momentum: It tracks the direction of the Z-score — if Z is extreme but still moving away from zero, it's too early. It waits for reversion to start (Z momentum flips).
Correlation Check: Uses a rolling Pearson correlation to confirm the two EMAs are still statistically related. If they diverge (low correlation), no signal is shown.
Stationarity Filter (ADF-like): Uses the volatility of the regression residual to determine if the spread is stationary (mean-reverting) — a key concept in cointegration and statistical arbitrage. It’s not possible to build an exact ADF filter in Pine Script so we used the next best thing.
Signal Control: Prevents noisy charts and overtrading by ensuring no back-to-back buy or sell signals. Each signal must alternate and respect a cooldown period so you won’t be overwhelmed and won’t get a messy chart.
Important Notes to Remember:
The whole idea behind this indicator is to try to use some stat arb models to detect shifting patterns faster than they appear on common indicators, so in some cases, some assumptions are made based on historic values.
This means that in some cases, the indicator can “jump” into the conclusion too quickly. Although we try to eliminate this by using stationary filters, correlation checks, and Z-score momentum detection, there is still a chance some signals that are generated can be too early, in the stock market, that's the same as being incorrect. So make sure to use this with other indicators to confirm the movement.
How To Use The Indicator:
You can use the indicator as a standalone reversal system, as a filter for overbought and oversold setups, in combination with other trend indicators and as a part of a signal stack with other common indicators for divergence spotting and fade trades.
The indicator produces simple buy and sell signals when all criteria is met. Based on our own testing, we recommend treating these signals as standalone and independent from each other . Meaning that if you take position after a buy signal, don’t wait for a sell signal to appear to exit the trade and vice versa.
This is why we recommend using this indicator with other advanced or even simple indicators as an early confirmation tool.
The Display Table:
The floating diagnostic table in the top-right corner of the chart is a key part of this indicator. It's a live statistical dashboard that helps you understand why a signal is (or isn’t) being triggered, and whether the market conditions are lining up for a potential reversal.
1. Z-Score
What it shows: The current Z-score value of the volatility-normalized spread between the short EMA and the regression line of the long EMA.
Why it matters: Z-score tells you how statistically extreme the current relationship is. A Z-score of:
0 = perfectly average
> +2 = very overbought
< -2 = very oversold
How to use it: Look for Z-score reaching extreme highs or lows (beyond dynamic thresholds). Watch for it to start reversing direction, especially when paired with green table rows (see below)
2. Z-Score Momentum
What it shows: The rate of change (ROC) of the Z-score:
Zmomentum=Zt − Zt − 1
Why it matters: This tells you if the Z-score is still stretching out (e.g., getting more overbought/oversold), or reverting back toward the mean.
How to use it: A positive Z-momentum after a very low Z-score = potential bullish reversal A negative Z-momentum after a very high Z-score = potential bearish reversal. Avoid signals when momentum is still pushing deeper into extremes
3. Correlation
What it shows: The rolling Pearson correlation coefficient between the short EMA and long EMA.
Why it matters: High correlation (closer to +1) means the EMAs are still statistically connected — a key requirement for cointegration or mean reversion to be valid.
How to use it: Look for correlation > 0.7 for reliable signals. If correlation drops below 0.5, ignore the Z-score — the EMAs aren’t moving together anymore
4. Stationary
What it shows: A simplified "Yes" or "No" answer to the question:
“Is the spread statistically stable (stationary) and mean-reverting right now?”
Why it matters: Mean reversion strategies only work when the spread is stationary — that is, when the distance between EMAs behaves like a rubber band, not a drifting cloud.
How to use it: A "Yes" means the indicator sees a consistent, stable spread — good for trading. "No" means the market is too volatile, disjointed, or chaotic for reliable mean reversion. Wait for this to flip to "Yes" before trusting signals
5. Last Signal
What it shows: The last signal issued by the system — either "Buy", "Sell", or "None"
Why it matters: Helps avoid confusion and repeated entries. Signals only alternate — you won’t get another Buy until a Sell happens, and vice versa.
How to use it: If the last signal was a "Buy", and you’re watching for a Sell, don’t act on more bullish signals. Great for systems where you only want one position open at a time
6. Bars Since Signal
What it shows: How many bars (candles) have passed since the last Buy or Sell signal.
Why it matters: Gives you context for how long the current condition has persisted
How to use it: If it says 1 or 2, a signal just happened — avoid jumping in late. If it’s been 10+ bars, a new opportunity might be brewing soon. You can use this to time exits if you want to fade a recent signal manually
Indicator Settings:
Short EMA: Sets the short-term EMA period. The smaller the number, the more reactive and more signals you get.
Long EMA: Sets the slow EMA period. The larger this number is, the smoother baseline, and more reliable trend bases are generated.
Z-Score Lookback: The period or bars used for mean & std deviation of spread between short and long EMAs. Larger values result in smoother signals with fewer false positives.
Volatility Window: This value normalizes the spread by historical volatility. This allows you to prevent scale distortion, showing you a cleaner and better chart.
Correlation Lookback: How many periods or how far back to test correlation between slow and long EMAs. This filters out false positives when EMAs lose alignment.
Hurst Lookback: The multiplier to approximate stationarity. Lower leads to more sensitivity to regime change, higher produces a more stricter filtering.
Z Threshold Percentile: This value sets how extreme Z-score must be to trigger a signal. For example, 90 equals only top/bottom 10% of extremes, 80 = more frequent.
Min Bars Between Signals: This hard stop prevents back-to-back signals. The idea is to avoid over-trading or whipsaws in volatile markets even when Hurst lookback and volatility window values are not enough to filter signals.
Some More Recommendations:
We recommend trying different EMA pairs (10/50, 21/100, 5/20) for different asset behaviors. You can set percentile to 85 or 80 if you want more frequent but looser signals. You can also use the Z-score reversion monitor for powerful confirmation.
Uptrick: Dynamic Z-Score DeviationOverview
Uptrick: Dynamic Z‑Score Deviation is a trading indicator built in Pine Script that combines statistical filters and adaptive smoothing to highlight potential reversal points in price action. It combines a hybrid moving average, dual Z‑Score analysis on both price and RSI, and visual enhancements like slope‑based coloring, ATR‑based shadow bands, and dynamically scaled reversal signals.
Introduction
Statistical indicators like Z‑Scores measure how far a value deviates from its average relative to the typical variation (standard deviation). Standard deviation quantifies how dispersed a set of values is around its mean. A Z‑Score of +2 indicates a value two standard deviations above the mean, while -2 is two below. Traders use Z‑Scores to spot unusually high or low readings that may signal overbought or oversold conditions.
Moving averages smooth out price data to reveal trends. The Arnaud Legoux Moving Average (ALMA) reduces lag and noise through weighted averaging. A Zero‑Lag EMA (approximated here using a time‑shifted EMA) seeks to further minimize delay in following price. The RSI (Relative Strength Index) is a momentum oscillator that measures recent gains against losses over a set period.
ATR (Average True Range) gauges market volatility by averaging the range between high and low over a lookback period. Shadow bands built using ATR give a visual mood of volatility around a central trend line. Together, these tools inform a dynamic but statistically grounded view of market extremes.
Purpose
The main goal of this indicator is to help traders spot short‑term reversal opportunities on lower timeframes. By requiring both price and momentum (RSI) to exhibit statistically significant deviations from their norms, it filters out weak setups and focuses on higher‑probability mean‑reversion zones. Reversal signals appear when price deviates far enough from its hybrid moving average and RSI deviates similarly in the same direction. This makes it suitable for discretionary traders seeking clean entry cues in volatile environments.
Originality and Uniqueness
Uptrick: Dynamic Z‑Score Deviation distinguishes itself from standard reversal or mean‑reversion tools by combining several elements into a single framework:
A composite moving average (ALMA + Zero‑Lag EMA) for a smooth yet responsive baseline
Dual Z‑Score filters on price and RSI rather than relying on a single measure
Adaptive visual elements, including slope‑aware coloring, multi‑layer ATR shadows, and signal sizing based on combined Z‑Score magnitude
Most indicators focus on one aspect—price envelopes or RSI thresholds—whereas Uptrick: Dynamic Z‑Score Deviation requires both layers to align before signaling. Its visual design aids quick interpretation without overwhelming the chart.
Why these indicators were merged
Every component in Uptrick: Dynamic Z‑Score Deviation has a purpose:
• ALMA: provides a smooth moving average with reduced lag and fewer false crossovers than a simple SMA or EMA.
• Zero‑Lag EMA (ZLMA approximation): further reduces the delay relative to price by applying a time shift to EMA inputs. This keeps the composite MA closer to current price action.
• RSI and its EMA filter: RSI measures momentum. Applying an EMA filter on RSI smooths out false spikes and confirms genuine overbought or oversold momentum.
• Dual Z‑Scores: computing Z‑Scores on both the distance between price and the composite MA, and on smoothed RSI, ensures that signals only fire when both price and momentum are unusually stretched.
• ATR bands: using ATR‑based shadow layers visualizes volatility around the MA, guiding traders on potential support and resistance zones.
At the end, these pieces merge into a single indicator that detects statistically significant mean reversions while staying adaptive to real‑time volatility and momentum.
Calculations
1. Compute ALMA over the chosen MA length, offset, and sigma.
2. Approximate ZLMA by applying EMA to twice the price minus the price shifted by the MA length.
3. Calculate the composite moving average as the average of ALMA and ZLMA.
4. Compute raw RSI and smooth it with ALMA. Apply an EMA filter to raw RSI to reduce noise.
5. For both price and smoothed RSI, calculate the mean and standard deviation over the Z‑Score lookback period.
6. Compute Z‑Scores:
• z_price = (current price − composite MA mean) / standard deviation of price deviations
• z_rsi = (smoothed RSI − mean RSI) / standard deviation of RSI
7. Determine reversal conditions: both Z‑Scores exceed their thresholds in the same direction, RSI EMA is in oversold/overbought zones (below 40 or above 60), and price movement confirms directionality.
8. Compute signal strength as the sum of the absolute Z‑Scores, then classify into weak, medium, or strong.
9. Calculate ATR over the chosen period and multiply by layer multipliers to form shadow widths.
10.Derive slope over the chosen slope length and color the MA line and bars based on direction, optionally smoothing color transitions via EMA on RGB channels.
How this indicator actually works
1. The script begins by smoothing price data with ALMA and approximating a zero‑lag EMA, then averaging them for the main MA.
2. RSI is calculated, then smoothed and filtered.
3. Using a rolling window, the script computes statistical measures for both price deviations and RSI.
4. Z‑Scores tell how far current values lie from their recent norms.
5. When both Z‑Scores cross configured thresholds and momentum conditions align, reversal signals are flagged.
6. Signals are drawn with size and color reflecting strength.
7. The MA is plotted with dynamic coloring; ATR shadows are layered beneath to show volatility envelopes.
8. Bars can be colored to match MA slope, reinforcing trend context.
9. Alert conditions allow automated notifications when signals occur.
Inputs
Main Length: Main MA Length. Sets the period for ALMA and ZLMA.
RSI Length: RSI Length. Determines the lookback for momentum calculations.
Z-Score Lookback: Z‑Score Lookback. Window for mean and standard deviation computations.
Price Z-Score Threshold: Price Z‑Score Threshold. Minimum deviation required for price.
RSI Z-Score threshold: RSI Z‑Score Threshold. Minimum deviation required for momentum.
RSI EMA Filter Length: RSI EMA Filter Length. Smooths raw RSI readings.
ALMA Offset: Controls ALMA’s focal point in the window.
ALMA Sigma: Adjusts ALMA’s smoothing strength.
Show Reversal Signals : Toggle to display reversal signal markers.
Slope Sensitivity: Length for slope calculation. Higher values smooth slope changes.
Use Bar Coloring: Enables coloring of price bars based on MA slope.
Show MA Shadow: Toggle for ATR‑based shadow bands.
Shadow Layer Count: Number of shadow layers (1–4).
Base Shadow ATR Multiplier: Multiplier for ATR when sizing the first band.
Smooth Color Transitions (boolean): Smooths RGB transitions for line and shadows, if enabled.
ATR Length for Shadow: ATR Period for computing volatility bands.
Use Dynamic Signal Size: Toggles dynamic scaling of reversal symbols.
Features
Moving average smoothing: a hybrid of ALMA and Zero‑Lag EMA that balances responsiveness and noise reduction.
Slope coloring: MA line and optionally price bars change color based on trend direction; color transitions can be smoothed for visual continuity.
ATR shadow layers: translucent bands around the MA show volatility envelopes; up to four concentric layers help gauge distance from normal price swings.
Dual Z‑Score filters: price and momentum must both deviate beyond thresholds to trigger signals, reducing false positives.
Dynamic signal sizing: reversal markers scale in size based on the combined Z‑Score magnitude, making stronger signals more prominent.
Adaptive visuals: optional smoothing of color channels creates gradient effects on lines and fills for a polished look.
Alert conditions: built‑in buy and sell alerts notify traders when reversal setups emerge.
Conclusion
Uptrick: Dynamic Z‑Score Deviation delivers a structured way to identify short‑term reversal opportunities by fusing statistical rigor with adaptive smoothing and clear visual cues. It guides traders through multiple confirmation layers—hybrid moving average, dual Z‑Score analysis, momentum filtering, and volatility envelopes—while keeping the chart clean and informative.
Disclaimer
This indicator is provided for informational and educational purposes only and does not constitute financial advice. Trading carries risk and may not be suitable for all participants. Past performance is not indicative of future results. Always do your own analysis and risk management before making trading decisions.
Nasan Market Phase ClassifierThe Nasan Market Phase Classifier indicator designed to classify market phases using volume, volatility (or momentum), and statistical analysis. Here's a summary of how it works and what it does:
🔍 Core Concept
This indicator classifies the market into four phases based on volume and ATR (or optionally momentum):
High Volume / High ATR or Momentum (HV/HATR): Strong Trend
Low Volume / High ATR or Momentum (LV/HATR): False Breakout / Exhaustion
High Volume / Low ATR or Momentum (HV/LATR): Consolidation
Low Volume / Low ATR or Momentum (LV/LATR): Stagnation
⚙️ Key Settings
Short-Term Length: Used for the active market phase.
Long-Term Length: Used as the expected/benchmark distribution.
Use Momentum: Replaces volatility (ATR) with momentum (custom ROC-based formula).
Use Fixed Alpha: Toggles adaptive vs. fixed weighting in scoring (this is based on variation of the volatility - standard deviation of true range).
📊 How It Works
Volatility or Momentum Scoring:
Uses ATR-based or Momentum-based score depending on the setting.
Applies weighing (alpha) which is based on variability of the volatility itself.
Market Phase Count:
Measures how often each of the 4 volume/volatility combinations occur in:
Short-term window (observed phase)
Long-term window (expected distribution)
Category Proportions:
Calculates percentage share of each category (e.g., % time in HV/HATR).
Plots these on chart to visually see market phase dominance (can be used for screening of pine screener).
Statistical Testing:
IQV (Index of Qualitative Variation): Measures phase diversity (0 = focused, 1 = mixed).
Chi-Squared Test: Compares current vs. historical phase distribution.
Z-Test: Tests if current phase dominance is statistically significant.
📋 Outputs
On-Chart Plots and Tabels:
Strong Trend, False Breakout/Exhaustion, Consolidation, Stagnation
Strength Quality Plot: Trend strength normalized by IQV.
Dynamic Table (Top Right):
Shows each phase’s proportion (the current phase cell is highlighted in yellow), IQV, Chi² value, and current dominant phase. The current candle classification (text) is in purple.
Highlights the dominant phase classification and color-codes significance (the cell highlighted in green highly confident about the classification, orange intermediate confidence and red low confidence). This color coding is not just based on statistical significance it is based on IQV which takes into account how spread the proportions are.
🧠 Interpretation
A dominant HV/HATR phase with low IQV and high Z-Score indicates a strong and statistically significant trend.
High IQV suggests uncertainty or mixed market behavior.
Chi² spike indicates a shift from historical behavior can be used to see is the market behavior changing by changing the long term length say to 252 and short term length to 21 this will tell if the short term behavior is different from the past 252 day behavior.
Uptrick: Z-Score FlowOverview
Uptrick: Z-Score Flow is a technical indicator that integrates trend-sensitive momentum analysi s with mean-reversion logic derived from Z-Score calculations. Its primary objective is to identify market conditions where price has either stretched too far from its mean (overbought or oversold) or sits at a statistically “normal” range, and then cross-reference this observation with trend direction and RSI-based momentum signals. The result is a more contextual approach to trade entry and exit, emphasizing precision, clarity, and adaptability across varying market regimes.
Introduction
Financial instruments frequently transition between trending modes, where price extends strongly in one direction, and ranging modes, where price oscillates around a central value. A simple statistical measure like Z-Score can highlight price extremes by comparing the current price against its historical mean and standard deviation. However, such extremes alone can be misleading if the broader market structure is trending forcefully. Uptrick: Z-Score Flow aims to solve this gap by combining Z-Score with an exponential moving average (EMA) trend filter and a smoothed RSI momentum check, thus filtering out signals that contradict the prevailing market environment.
Purpose
The purpose of this script is to help traders pinpoint both mean-reversion opportunities and trend-based pullbacks in a way that is statistically grounded yet still mindful of overarching price action. By pairing Z-Score thresholds with supportive conditions, the script reduces the likelihood of acting on random price spikes or dips and instead focuses on movements that are significant within both historical and current contextual frameworks.
Originality and Uniquness
Layered Signal Verification: Signals require the fulfillment of multiple layers (Z-Score extreme, EMA trend bias, and RSI momentum posture) rather than merely breaching a statistical threshold.
RSI Zone Lockout: Once RSI enters an overbought/oversold zone and triggers a signal, the script locks out subsequent signals until RSI recovers above or below those zones, limiting back-to-back triggers.
Controlled Cooldown: A dedicated cooldown mechanic ensures that the script waits a specified number of bars before issuing a new signal in the opposite direction.
Gradient-Based Visualization: Distinct gradient fills between price and the Z-Mean line enhance readability, showing at a glance whether price is trading above or below its statistical average.
Comprehensive Metrics Panel: An optional on-chart table summarizes the Z-Score’s key metrics, streamlining the process of verifying current statistical extremes, mean levels, and momentum directions.
Why these indicators were merged
Z-Score measurements excel at identifying when price deviates from its mean, but they do not intrinsically reveal whether the market’s trajectory supports a reversion or if price might continue along its trend. The EMA, commonly used for spotting trend directions, offers valuable insight into whether price is predominantly ascending or descending. However, relying solely on a trend filter overlooks the intensity of price moves. RSI then adds a dedicated measure of momentum, helping confirm if the market’s energy aligns with a potential reversal (for example, price is statistically low but RSI suggests looming upward momentum). By uniting these three lenses—Z-Score for statistical context, EMA for trend direction, and RSI for momentum force—the script offers a more comprehensive and adaptable system, aiming to avoid false positives caused by focusing on just one aspect of price behavior.
Calculations
The core calculation begins with a simple moving average (SMA) of price over zLen bars, referred to as the basis. Next, the script computes the standard deviation of price over the same window. Dividing the difference between the current price and the basis by this standard deviation produces the Z-Score, indicating how many standard deviations the price is from its mean. A positive Z-Score reveals price is above its average; a negative reading indicates the opposite.
To detect overall market direction, the script calculates an exponential moving average (emaTrend) over emaTrendLen bars. If price is above this EMA, the script deems the market bullish; if below, it’s considered bearish. For momentum confirmation, the script computes a standard RSI over rsiLen bars, then applies a smoothing EMA over rsiEmaLen bars. This smoothed RSI (rsiEma) is monitored for both its absolute level (oversold or overbought) and its slope (the difference between the current and previous value). Finally, slopeIndex determines how many bars back the script compares the basis to check whether the Z-Mean line is generally rising, falling, or flat, which then informs the coloring scheme on the chart.
Calculations and Rational
Simple Moving Average for Baseline: An SMA is used for the core mean because it places equal weight on each bar in the lookback period. This helps maintain a straightforward interpretation of overbought or oversold conditions in the context of a uniform historical average.
Standard Deviation for Volatility: Standard deviation measures the variability of the data around the mean. By dividing price’s difference from the mean by this value, the Z-Score can highlight whether price is unusually stretched given typical volatility.
Exponential Moving Average for Trend: Unlike an SMA, an EMA places more emphasis on recent data, reacting quicker to new price developments. This quicker response helps the script promptly identify trend shifts, which can be crucial for filtering out signals that go against a strong directional move.
RSI for Momentum Confirmation: RSI is an oscillator that gauges price movement strength by comparing average gains to average losses over a set period. By further smoothing this RSI with another EMA, short-lived oscillations become less influential, making signals more robust.
SlopeIndex for Slope-Based Coloring: To clarify whether the market’s central tendency is rising or falling, the script compares the basis now to its level slopeIndex bars ago. A higher current reading indicates an upward slope; a lower reading, a downward slope; and similar readings, a flat slope. This is visually represented on the chart, providing an immediate sense of the directionality.
Inputs
zLen (Z-Score Period)
Specifies how many bars to include for computing the SMA and standard deviation that form the basis of the Z-Score calculation. Larger values produce smoother but slower signals; smaller values catch quick changes but may generate noise.
emaTrendLen (EMA Trend Filter)
Sets the length of the EMA used to detect the market’s primary direction. This is pivotal for distinguishing whether signals should be considered (price aligning with an uptrend or downtrend) or filtered out.
rsiLen (RSI Length)
Defines the window for the initial RSI calculation. This RSI, when combined with the subsequent smoothing EMA, forms the foundation for momentum-based signal confirmations.
rsiEmaLen (EMA of RSI Period)
Applies an exponential moving average over the RSI readings for additional smoothing. This step helps mitigate rapid RSI fluctuations that might otherwise produce whipsaw signals.
zBuyLevel (Z-Score Buy Threshold)
Determines how negative the Z-Score must be for the script to consider a potential oversold signal. If the Z-Score dives below this threshold (and other criteria are met), a buy signal is generated.
zSellLevel (Z-Score Sell Threshold)
Determines how positive the Z-Score must be for a potential overbought signal. If the Z-Score surpasses this threshold (and other checks are satisfied), a sell signal is generated.
cooldownBars (Cooldown (Bars))
Enforces a bar-based delay between opposite signals. Once a buy signal has fired, the script must wait the specified number of bars before registering a new sell signal, and vice versa.
slopeIndex (Slope Sensitivity (Bars))
Specifies how many bars back the script compares the current basis for slope coloration. A bigger slopeIndex highlights larger directional trends, while a smaller number emphasizes shorter-term shifts.
showMeanLine (Show Z-Score Mean Line)
Enables or disables the plotting of the Z-Mean and its slope-based coloring. Traders who prefer minimal chart clutter may turn this off while still retaining signals.
Features
Statistical Core (Z-Score Detection):
This feature computes the Z-Score by taking the difference between the current price and the basis (SMA) and dividing by the standard deviation. In effect, it translates price fluctuations into a standardized measure that reveals how significant a move is relative to the typical variation seen over the lookback. When the Z-Score crosses predefined thresholds (zBuyLevel for oversold and zSellLevel for overbought), it signals that price could be at an extreme.
How It Works: On each bar, the script updates the SMA and standard deviation. The Z-Score is then refreshed accordingly. Traders can interpret particularly large negative or positive Z-Score values as scenarios where price is abnormally low or high.
EMA Trend Filter:
An EMA over emaTrendLen bars is used to classify the market as bullish if the price is above it and bearish if the price is below it. This classification is applied to the Z-Score signals, accepting them only when they align with the broader price direction.
How It Works: If the script detects a Z-Score below zBuyLevel, it further checks if price is actually in a downtrend (below EMA) before issuing a buy signal. This might seem counterintuitive, but a “downtrend” environment plus an oversold reading often signals a potential bounce or a mean-reversion play. Conversely, for sell signals, the script checks if the market is in an uptrend first. If it is, an overbought reading aligns with potential profit-taking.
RSI Momentum Confirmation with Oversold/Overbought Lockout:
RSI is calculated over rsiLen, then smoothed by an EMA over rsiEmaLen. If this smoothed RSI dips below a certain threshold (for example, 30) and then begins to slope upward, the indicator treats it as a potential sign of recovering momentum. Similarly, if RSI climbs above a certain threshold (for instance, 70) and starts to slope downward, that suggests dwindling momentum. Additionally, once RSI is in these zones, the indicator locks out repetitive signals until RSI fully exits and re-enters those extreme territories.
How It Works: Each bar, the script measures whether RSI has dropped below the oversold threshold (like 30) and has a positive slope. If it does, the buy side is considered “unlocked.” For sell signals, RSI must exceed an overbought threshold (70) and slope downward. The combination of threshold and slope helps confirm that a reversal is genuinely in progress instead of issuing signals while momentum remains weak or stuck in extremes.
Cooldown Mechanism:
The script features a custom bar-based cooldown that prevents issuing new signals in the opposite direction immediately after one is triggered. This helps avoid whipsaw situations where the market quickly flips from oversold to overbought or vice versa.
How It Works: When a buy signal fires, the indicator notes the bar index. If the Z-Score and RSI conditions later suggest a sell, the script compares the current bar index to the last buy signal’s bar index. If the difference is within cooldownBars, the signal is disallowed. This ensures a predefined “quiet period” before switching signals.
Slope-Based Coloring (Z-Mean Line and Shadow):
The script compares the current basis value to its value slopeIndex bars ago. A higher reading now indicates a generally upward slope, while a lower reading indicates a downward slope. The script then shades the Z-Mean line in a corresponding bullish or bearish color, or remains neutral if little change is detected.
How It Works: This slope calculation is refreshingly straightforward: basis – basis . If the result is positive, the line is colored bullish; if negative, it is colored bearish; if approximately zero, it remains neutral. This provides a quick visual cue of the medium-term directional bias.
Gradient Overlays:
With gradient fills, the script highlights where price stands in relation to the Z-Mean. When price is above the basis, a purple-shaded region is painted, visually indicating a “bearish zone” for potential overbought conditions. When price is below, a teal-like overlay is used, suggesting a “bullish zone” for potential oversold conditions.
How It Works: Each bar, the script checks if price is above or below the basis. It then applies a fill between close and basis, using distinct colors to show whether the market is trading above or below its mean. This creates an immediate sense of how extended the market might be.
Buy and Sell Labels (with Alerts):
When a legitimate buy or sell condition passes every check (Z-Score threshold, EMA trend alignment, RSI gating, and cooldown clearance), the script plots a corresponding label directly on the chart. It also fires an alert (if alerts are set up), making it convenient for traders who want timely notifications.
How It Works: If rawBuy or rawSell conditions are met (refined by RSI, EMA trend, and cooldown constraints), the script calls the respective plot function to paint an arrow label on the chart. Alerts are triggered simultaneously, carrying easily recognizable messages.
Metrics Table:
The optional on-chart table (activated by showMetrics) presents real-time Z-Score data, including the current Z-Score, its rolling mean, the maximum and minimum Z-Score values observed over the last zLen bars, a percentile position, and a short-term directional note (rising, falling, or flat).
Current – The present Z-Score reading
Mean – Average Z-Score over the zLen period
Min/Max – Lowest and highest Z-Score values within zLen
Position – Where the current Z-Score sits between the min and max (as a percentile)
Trend – Whether the Z-Score is increasing, decreasing, or flat
Conclusion
Uptrick: Z-Score Flow offers a versatile solution for traders who need a statistically informed perspective on price extremes combined with practical checks for overall trend and momentum. By leveraging a well-defined combination of Z-Score, EMA trend classification, RSI-based momentum gating, slope-based visualization, and a cooldown mechanic, the script reduces the occurrence of false or premature signals. Its gradient fills and optional metrics table contribute further clarity, ensuring that users can quickly assess market posture and make more confident trading decisions in real time.
Disclaimer
This script is intended solely for informational and educational purposes. Trading in any financial market comes with substantial risk, and there is no guarantee of success or the avoidance of loss. Historical performance does not ensure future results. Always conduct thorough research and consider professional guidance prior to making any investment or trading decisions.
Dynamic RSI Bollinger Bands with Waldo Cloud
TradingView Indicator Description: Dynamic RSI Bollinger Bands with Waldo Cloud
Title: Dynamic RSI Bollinger Bands with Waldo Cloud
Short Title: Dynamic RSI BB Waldo
Overview:
Introducing an experimental indicator, the Dynamic RSI Bollinger Bands with Waldo Cloud, designed for adventurous traders looking to explore new dimensions in technical analysis. This indicator overlays on your chart, providing a unique perspective by integrating the Relative Strength Index (RSI) with Bollinger Bands, creating a dynamic trading tool that adapts to market conditions through the lens of momentum and volatility.
What is it?
This innovative indicator combines the traditional Bollinger Bands with the RSI in a way that hasn't been commonly explored. Here's a breakdown:
RSI Integration: The RSI is calculated with customizable length settings, and its values are used not just for momentum analysis but as the basis for the Bollinger Bands. This means the position and width of the bands are directly influenced by the RSI, offering a visual representation of momentum within the context of price volatility.
Dynamic Bollinger Bands: Instead of using price directly, the Bollinger Bands are calculated using a scaled version of the RSI. This scaling is done to fit the RSI values into the price range, ensuring the bands are relevant to the actual price movement. The standard deviation for these bands is also scaled accordingly, providing a unique volatility measure that's momentum-driven.
Waldo Cloud: Named after a visual representation concept, the 'Waldo Cloud' refers to the colored area between the Bollinger Bands, which changes based on various conditions:
Purple when RSI is overbought.
Blue when RSI is oversold.
Green for bullish conditions, defined by the fast-moving average crossing above the slow one, RSI is bullish, and the price is above the slow MA.
Red for bearish conditions, when the fast MA crosses below the slow MA, the RSI is bearish, and the price is below the slow MA.
Gray for neutral market conditions.
Moving Averages: Two simple moving averages (Fast MA and Slow MA) are included, which can be toggled on or off, offering additional trend analysis through crossovers.
How to Use It:
Given its experimental nature, this indicator should be used with caution and in conjunction with other analysis methods:
Identifying Market Conditions: Use the color of the Waldo Cloud to gauge market sentiment. A green cloud might suggest a good time to consider long positions, while a red cloud could indicate potential shorting opportunities. Purple and blue clouds highlight extreme conditions that might precede reversals.
Volatility and Momentum: The dynamic nature of the Bollinger Bands based on RSI provides insight into how momentum is affecting price volatility. When the bands are wide, it might indicate high momentum and potential trend continuation or reversal, depending on the RSI's position relative to its overbought/oversold levels.
Trend Confirmation: The moving average crossovers can act as confirmation signals. For instance, a bullish crossover (fast MA over slow MA) within a green cloud might strengthen a buy signal, whereas a bearish crossover in a red cloud might reinforce a sell decision.
Customization: Adjust the RSI length, overbought/oversold levels, and moving average lengths to suit different trading styles or market conditions. Experiment with these settings to find what works best for your strategy.
Combining with Other Indicators: Since this is an experimental tool, it's advisable to use it alongside established indicators like traditional Bollinger Bands, MACD, or trend lines to validate signals.
Conclusion:
The Dynamic RSI Bollinger Bands with Waldo Cloud is an experimental venture into combining momentum with volatility visually and interactively. It's designed for traders who are open to exploring new methods of market analysis.
Remember, due to its experimental status, this indicator should be part of a broader trading strategy, and backtesting or paper trading is recommended before applying it in live trading scenarios. Keep an eye on how the market reacts to the signals provided by this indicator and always consider risk management practices.
TDI 7 MA and HISTOGRAMTDI %K Histogram with 7 MA
Overview
This indicator enhances trend and momentum analysis using the %K line from the Traders Dynamic Index (TDI), combined with a 7-period moving average (MA) and a histogram.
How It Works
The script calculates %K (similar to Stochastic RSI), representing the relative price position within a given range.
A 7-period Simple Moving Average (SMA) is applied to smooth the %K line, reducing noise and improving trend clarity.
A histogram is plotted based on the difference between %K and the 7-period MA:
Green bars indicate that %K is above the 7-period MA, suggesting bullish momentum.
Red bars indicate that %K is below the 7-period MA, suggesting bearish momentum.
Key Features
-%K Line (Blue) – Reflects short-term momentum shifts.
-7-period MA (Purple) – Helps smooth out fluctuations in %K for better trend identification.
-Histogram (Green/Red Columns) – Highlights momentum shifts visually.
Overbought (68), Midpoint (50), and Oversold (32) Levels – Provides reference points for potential reversals or trend continuation.
How to Use
Bullish Confirmation: When the histogram turns green and %K is above the 7 MA, it suggests upward momentum.
Bearish Confirmation: When the histogram turns red and %K is below the 7 MA, it suggests downward momentum.
Overbought/Oversold Conditions: Use the 68 and 32 levels as potential reversal zones, but always confirm with price action.
Midpoint (50 Level): Acts as a dynamic support/resistance area for momentum shifts.
This indicator is suitable for trend-following and momentum-based trading strategies, whether on lower timeframes for scalping or higher timeframes for swing trading.
Try it out and integrate it with your trading system to refine your entries and exits!
Rosiz Support 1### Description of the Custom Indicator: MACD + CMF + MOM
This custom indicator combines three powerful technical analysis tools: **MACD (Moving Average Convergence Divergence)**, **CMF (Chaikin Money Flow)**, and **MOM (Momentum)**, to provide a comprehensive view of market trends, momentum, and money flow in a single pane. Here's what each component offers:
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#### 1. **MACD (Moving Average Convergence Divergence)**
The **MACD** is a trend-following momentum indicator that shows the relationship between two moving averages of an asset’s price.
- **Purpose**: Identifies trend direction and momentum strength.
- **Key Components**:
- **MACD Line**: Difference between the fast and slow exponential moving averages (EMA).
- **Signal Line**: A smoothed moving average of the MACD line, acting as a trigger for buy/sell signals.
- **Histogram**: The difference between the MACD line and the signal line. Positive values indicate bullish momentum, while negative values indicate bearish momentum.
- **Usage**: Look for crossovers (MACD crossing the signal line) to identify potential trend changes.
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#### 2. **CMF (Chaikin Money Flow)**
The **CMF** measures the volume-weighted average of accumulation and distribution over a specific period. It shows whether money is flowing into or out of an asset.
- **Purpose**: Detects buying or selling pressure based on price and volume.
- **Key Components**:
- **Positive CMF**: Indicates that the asset is being accumulated (buying pressure).
- **Negative CMF**: Indicates that the asset is being distributed (selling pressure).
- **Usage**: Values above 0 suggest bullish strength, while values below 0 suggest bearish strength.
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#### 3. **MOM (Momentum)**
The **Momentum Indicator** measures the rate of change of an asset's price over a specified period. It helps traders identify the speed of price movements.
- **Purpose**: Highlights the strength and direction of price momentum.
- **Key Components**:
- **Momentum Line**: Positive values indicate upward momentum, while negative values indicate downward momentum.
- **Usage**: A rising momentum line suggests strengthening price trends, while a falling line indicates weakening trends.
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### Benefits of Combining These Indicators:
1. **Trend Confirmation**: MACD provides a clear picture of trend direction and potential reversals.
2. **Volume-Based Insights**: CMF adds a layer of confirmation by analyzing money flow based on price and volume.
3. **Momentum Analysis**: MOM reveals the speed and strength of price movements, helping traders confirm breakouts or trend exhaustion.
4. **Enhanced Decision-Making**: The combination of these indicators allows traders to make more informed decisions by evaluating different aspects of market behavior in one pane.
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### How to Use:
- **Identify Trends**: Use MACD to identify overall trend direction and reversals.
- **Confirm Momentum**: Check MOM to validate the strength of the trend.
- **Gauge Buying/Selling Pressure**: Refer to CMF to confirm whether the price movement is backed by accumulation or distribution.
- **Entry/Exit Points**: Look for MACD crossovers, CMF shifts above/below zero, and momentum changes to refine entry and exit strategies.
This powerful tool integrates the strengths of three indicators, making it ideal for traders looking to analyze market conditions holistically and improve their timing and accuracy.
Big Candle Identifier with RSI Divergence and Advanced Stops1. Strategy Objective
The main goal of this strategy is to:
Identify significant price momentum (big candles).
Enter trades at opportune moments based on market signals (candlestick patterns and RSI divergence).
Limit initial risk through a fixed stop loss.
Maximize profits by using a trailing stop that activates only after the trade moves a specified distance in the profitable direction.
2. Components of the Strategy
A. Big Candle Identification
The strategy identifies big candles as indicators of strong momentum.
A big candle is defined as:
The body (absolute difference between close and open) of the current candle (body0) is larger than the bodies of the last five candles.
The candle is:
Bullish Big Candle: If close > open.
Bearish Big Candle: If open > close.
Purpose: Big candles signal potential continuation or reversal of trends, serving as the primary entry trigger.
B. RSI Divergence
Relative Strength Index (RSI): A momentum oscillator used to detect overbought/oversold conditions and divergence.
Fast RSI: A 5-period RSI, which is more sensitive to short-term price movements.
Slow RSI: A 14-period RSI, which smoothens fluctuations over a longer timeframe.
Divergence: The difference between the fast and slow RSIs.
Positive divergence (divergence > 0): Bullish momentum.
Negative divergence (divergence < 0): Bearish momentum.
Visualization: The divergence is plotted on the chart, helping traders confirm momentum shifts.
C. Stop Loss
Initial Stop Loss:
When entering a trade, an immediate stop loss of 200 points is applied.
This stop loss ensures the maximum risk is capped at a predefined level.
Implementation:
Long Trades: Stop loss is set below the entry price at low - 200 points.
Short Trades: Stop loss is set above the entry price at high + 200 points.
Purpose:
Prevents significant losses if the price moves against the trade immediately after entry.
D. Trailing Stop
The trailing stop is a dynamic risk management tool that adjusts with price movements to lock in profits. Here’s how it works:
Activation Condition:
The trailing stop only starts trailing when the trade moves 200 ticks (profit) in the right direction:
Long Position: close - entry_price >= 200 ticks.
Short Position: entry_price - close >= 200 ticks.
Trailing Logic:
Once activated, the trailing stop:
For Long Positions: Trails behind the price by 150 ticks (trail_stop = close - 150 ticks).
For Short Positions: Trails above the price by 150 ticks (trail_stop = close + 150 ticks).
Exit Condition:
The trade exits automatically if the price touches the trailing stop level.
Purpose:
Ensures profits are locked in as the trade progresses while still allowing room for price fluctuations.
E. Trade Entry Logic
Long Entry:
Triggered when a bullish big candle is identified.
Stop loss is set at low - 200 points.
Short Entry:
Triggered when a bearish big candle is identified.
Stop loss is set at high + 200 points.
F. Trade Exit Logic
Trailing Stop: Automatically exits the trade if the price touches the trailing stop level.
Fixed Stop Loss: Exits the trade if the price hits the predefined stop loss level.
G. 21 EMA
The strategy includes a 21-period Exponential Moving Average (EMA), which acts as a trend filter.
EMA helps visualize the overall market direction:
Price above EMA: Indicates an uptrend.
Price below EMA: Indicates a downtrend.
H. Visualization
Big Candle Identification:
The open and close prices of big candles are plotted for easy reference.
Trailing Stop:
Plotted on the chart to visualize its progression during the trade.
Green Line: Indicates the trailing stop for long positions.
Red Line: Indicates the trailing stop for short positions.
RSI Divergence:
Positive divergence is shown in green.
Negative divergence is shown in red.
3. Key Parameters
trail_start_ticks: The number of ticks required before the trailing stop activates (default: 200 ticks).
trail_distance_ticks: The distance between the trailing stop and price once the trailing stop starts (default: 150 ticks).
initial_stop_loss_points: The fixed stop loss in points applied at entry (default: 200 points).
tick_size: Automatically calculates the minimum tick size for the trading instrument.
4. Workflow of the Strategy
Step 1: Entry Signal
The strategy identifies a big candle (bullish or bearish).
If conditions are met, a trade is entered with a fixed stop loss.
Step 2: Initial Risk Management
The trade starts with an initial stop loss of 200 points.
Step 3: Trailing Stop Activation
If the trade moves 200 ticks in the profitable direction:
The trailing stop is activated and follows the price at a distance of 150 ticks.
Step 4: Exit the Trade
The trade is exited if:
The price hits the trailing stop.
The price hits the initial stop loss.
5. Advantages of the Strategy
Risk Management:
The fixed stop loss ensures that losses are capped.
The trailing stop locks in profits after the trade becomes profitable.
Momentum-Based Entries:
The strategy uses big candles as entry triggers, which often indicate strong price momentum.
Divergence Confirmation:
RSI divergence helps validate momentum and avoid false signals.
Dynamic Profit Protection:
The trailing stop adjusts dynamically, allowing the trade to capture larger moves while protecting gains.
6. Ideal Market Conditions
This strategy performs best in:
Trending Markets:
Big candles and momentum signals are more effective in capturing directional moves.
High Volatility:
Larger price swings improve the probability of reaching the trailing stop activation level (200 ticks).
