OA S/R PowerPurpose of the Script
This script identifies the strength of support and resistance levels based on key factors like volume, bounce frequency, and retests. Each level is assigned a score (0-100) and visualized with color-coded labels on the chart.
Key Features
Dynamic Strength Calculation:
Volume Strength: Measures the strength based on the volume of candles touching the level.
Bounce Strength: Evaluates how often the price bounces back from the level.
Retest Strength: Scores the consistency of retests over time.
Color-Coded Visualization:
Yellow: Strong levels (Strength ≥ 70).
Orange: Medium levels (Strength between 50-70).
Red: Resistance levels (Price is below the level).
Green: Support levels (Price is above the level).
Fully Customizable Settings:
Adjust the weight for volume, bounce, and retest contributions.
Configure timeframes, percentage range, and number of levels to analyze.
How It Works
Identify Peaks and Valleys: The script calculates local highs and lows using a configurable width setting to determine potential support and resistance levels.
Filter Key Levels: Nearby levels are merged based on a user-defined percentage range, ensuring clean and relevant levels.
Strength Scoring: Levels are scored dynamically based on:
The number of touches.
The volume of touches.
The frequency of bounces and retests.
Visual Feedback: Each level is plotted on the chart with a color-coded label, indicating its importance and price relationship.
Best Use Cases
Quickly identify strong support/resistance zones for breakout or reversal trades.
Use the dynamic scoring system to prioritize key levels for your strategy.
Customize weights to align with your trading style, such as emphasizing volume or retests.
Indicadores e estratégias
Cloud EMA Ajustable (9, 21, 50) con Filtro de SeñalesEl "Cloud EMA Ajustable (9, 21, 50) con Filtro de Señales" es una herramienta de análisis técnico diseñada para identificar zonas de soporte o resistencia dinámicas basadas en tres medias móviles exponenciales (EMAs) ajustables. Este indicador también incluye un filtro de señales que combina un cruce de EMAs con confirmación del RSI para ayudar a identificar posibles puntos de entrada en tendencias alcistas o bajistas.
Características principales:
Medias móviles exponenciales (EMAs):
EMA 9: Actúa como un indicador rápido de la tendencia a corto plazo.
EMA 21: Marca un soporte o resistencia intermedia.
EMA 50: Representa una tendencia más amplia.
Relleno de color entre EMA 21 y EMA 50:
Verde para tendencias alcistas (EMA 21 > EMA 50).
Rojo para tendencias bajistas (EMA 21 < EMA 50).
Señales basadas en mechas y RSI:
Una señal de entrada ocurre cuando la mecha de la vela toca la EMA 21, y se confirma una tendencia mediante las EMAs y el RSI.
Totalmente personalizable: Los usuarios pueden ajustar los períodos de las EMAs y el RSI según sus necesidades.
Ajustes disponibles para los usuarios:
Períodos de las EMAs:
Periodo EMA 9 : Personaliza el período para la EMA más rápida.
Periodo EMA 21 : Define el período de la EMA media, utilizada como referencia clave.
Periodo EMA 50: Ajusta el período para la EMA más lenta.
Período del RSI:
Periodo RSI : Cambia el período del RSI utilizado como filtro de tendencia.
Cómo interpretar el indicador:
Colores y relleno:
Verde: Indica una tendencia alcista (EMA 21 por encima de EMA 50).
Rojo: Indica una tendencia bajista (EMA 21 por debajo de EMA 50).
Señales de entrada:
Una señal de entrada (punto amarillo) aparece cuando:
-La mecha de la vela toca la EMA 21.
-Las EMAs confirman la tendencia (EMA 9 > EMA 21 para alcista o EMA 9 < EMA 21 para bajista).
-El RSI refuerza la tendencia (RSI > 50 para alcista o RSI < 50 para bajista).
Personalización:
Ajusta los períodos de las EMAs y el RSI para adaptarlos a diferentes marcos temporales o estilos de trading.
Este indicador es ideal para traders que buscan confirmar entradas basadas en tendencias y validaciones adicionales como el RSI, mejorando la precisión de sus decisiones operativas.
Credito
Gracias a la publicacion de @Dezziinutz por la aportacion de los parametros para la realizacion de este indicador, y por eso es gratis para la comunidad y el codigo es libre para que puedan manipularlo y modificarlo.
//@version=5
indicator("Cloud EMA Ajustable (9, 21, 50) con Filtro de Señales", overlay=true)
// Permitir al usuario editar los periodos de las EMAs desde la interfaz gráfica
periodoEMA9 = input.int(9, title="Periodo EMA 9", minval=1, tooltip="Edita el periodo de la EMA 9")
periodoEMA21 = input.int(21, title="Periodo EMA 21", minval=1, tooltip="Edita el periodo de la EMA 21")
periodoEMA50 = input.int(50, title="Periodo EMA 50", minval=1, tooltip="Edita el periodo de la EMA 50")
rsiPeriodo = input.int(14, title="Periodo RSI", minval=1, tooltip="Edita el periodo del RSI")
// Calcular las EMAs y el RSI con los periodos ajustables
ema9 = ta.ema(close, periodoEMA9)
ema21 = ta.ema(close, periodoEMA21)
ema50 = ta.ema(close, periodoEMA50)
rsi = ta.rsi(close, rsiPeriodo)
// Definir el color de la sombra entre la EMA 21 y EMA 50
fillColor = ema21 > ema50 ? color.new(color.green, 80) : color.new(color.red, 80)
// Dibujar las EMAs y asignarlas a variables de tipo plot
plotEMA9 = plot(ema9, title="EMA 9", color=color.blue, linewidth=2)
plotEMA21 = plot(ema21, title="EMA 21", color=ema21 > ema50 ? color.green : color.red, linewidth=2)
plotEMA50 = plot(ema50, title="EMA 50", color=ema21 > ema50 ? color.green : color.red, linewidth=2)
// Crear la sombra entre EMA 21 y EMA 50
fill(plotEMA21, plotEMA50, color=fillColor, title="Sombra entre EMA 21 y EMA 50")
// Condición: Cuando la mecha superior o inferior de la vela toque la EMA 21
toqueEMA21 = (high >= ema21 and low <= ema21) // La mecha toca la EMA 21
// Filtro: Asegurarse de que el precio está en una tendencia alcista/bajista según el cruce de EMAs
tendenciaAlcista = ema9 > ema21
tendenciaBajista = ema9 < ema21
// Filtro adicional: RSI debe estar por encima de 50 para tendencia alcista y por debajo de 50 para tendencia bajista
rsiAlcista = rsi > 50
rsiBajista = rsi < 50
// Condición para la señal: El precio toca la EMA 21, y hay una confirmación de tendencia
senal_entrada = toqueEMA21 and ((tendenciaAlcista and rsiAlcista) or (tendenciaBajista and rsiBajista))
// Dibujar un punto amarillo en la mecha de la vela si se da la condición
plotshape(senal_entrada, title="Señal de Entrada", location=location.abovebar, color=color.yellow, style=shape.circle, size=size.small)
Power Of 3 ICT 01 [TradingFinder] AMD ICT & SMC Accumulations🔵 Introduction
The ICT Power of 3 (PO3) strategy, developed by Michael J. Huddleston, known as the Inner Circle Trader, is a structured approach to analyzing daily market activity. This strategy divides the trading day into three distinct phases: Accumulation, Manipulation, and Distribution.
Each phase represents a unique market behavior influenced by institutional traders, offering a clear framework for retail traders to align their strategies with market movements.
Accumulation (19:00 - 01:00 EST) takes place during low-volatility hours, as institutional traders accumulate orders. Manipulation (01:00 - 07:00 EST) involves false breakouts and liquidity traps designed to mislead retail traders. Finally, Distribution (07:00 - 13:00 EST) represents the active phase where significant market movements occur as institutions distribute their positions in line with the broader trend.
This indicator is built upon the Power of 3 principles to provide traders with a practical and visual tool for identifying these key phases. By using clear color coding and precise time zones, the indicator highlights critical price levels, such as highs and lows, helping traders to better understand market dynamics and make more informed trading decisions.
Incorporating the ICT AMD setup into daily analysis enables traders to anticipate market behavior, spot high-probability trade setups, and gain deeper insights into institutional trading strategies. With its focus on time-based price action, this indicator simplifies complex market structures, offering an effective tool for traders of all levels.
🔵 How to Use
The ICT Power of 3 (PO3) indicator is designed to help traders analyze daily market movements by visually identifying the three key phases: Accumulation, Manipulation, and Distribution.
Here's how traders can effectively use the indicator :
🟣 Accumulation Phase (19:00 - 01:00 EST)
Purpose : Identify the range-bound activity where institutional players accumulate orders.
Trading Insight : Avoid placing trades during this phase, as price movements are typically limited. Instead, use this time to prepare for the potential direction of the market in the next phases.
🟣 Manipulation Phase (01:00 - 07:00 EST)
Purpose : Spot false breakouts and liquidity traps that mislead retail traders.
Trading Insight : Observe the market for price spikes beyond key support or resistance levels. These moves often reverse quickly, offering high-probability entry points in the opposite direction of the initial breakout.
🟣 Distribution Phase (07:00 - 13:00 EST)
Purpose : Detect the main price movement of the day, driven by institutional distribution.
Trading Insight : Enter trades in the direction of the trend established during this phase. Look for confirmations such as breakouts or strong directional moves that align with broader market sentiment
🔵 Settings
Show or Hide Phases :mDecide whether to display Accumulation, Manipulation, or Distribution.
Adjust the session times for each phase :
Accumulation: 1900-0100 EST
Manipulation: 0100-0700 EST
Distribution: 0700-1300 EST
Modify Visualization : Customize how the indicator looks by changing settings like colors and transparency.
🔵 Conclusion
The ICT Power of 3 (PO3) indicator is a powerful tool for traders seeking to understand and leverage market structure based on time and price dynamics. By visually highlighting the three key phases—Accumulation, Manipulation, and Distribution—this indicator simplifies the complex movements of institutional trading strategies.
With its customizable settings and clear representation of market behavior, the indicator is suitable for traders at all levels, helping them anticipate market trends and make more informed decisions.
Whether you're identifying entry points in the Accumulation phase, navigating false moves during Manipulation, or capitalizing on trends in the Distribution phase, this tool provides valuable insights to enhance your trading performance.
By integrating this indicator into your analysis, you can better align your strategies with institutional movements and improve your overall trading outcomes.
B-Xtrender By Neal inspired from @PuppytherapyThanks to @puppytherapy for creating the original B-Xtrender indicator, available at this link: B-Xtrender by @QuantTherapy
I played around the code to have entry and exit condition. The B-Xtrender @QuantTherapy
indicator is a momentum-based tool designed to help traders identify potential trade opportunities by tracking shifts in market momentum. Using a smoothed momentum oscillator, it detects changes in trend direction and provides clear signals for entry and exit points.
Features
Momentum Detection:
Tracks market momentum using the BX-Trender Oscillator.
Green bars indicate bullish momentum, while red bars indicate bearish momentum.
Lighter shades of green/red reflect weakening momentum.
Entry and Exit Signals:
Entry Condition: A long trade is triggered when the oscillator changes from red to green .
Exit Condition: A long trade exit is triggered when the oscillator changes from green to red .
Dynamic PnL Calculation:
Automatically calculates profit or loss in percentage (%) when a trade is exited.
Positive PnL values are prefixed with `+`, and negative values are shown as `-`.
Clear Visualization:
Bar chart-style oscillator in a separate pane for better trend visualization.
Trade labels on the main price chart for clear entry and exit points.
Inputs
Short-Term Momentum Parameters:
Short - L1: Length of the first EMA for short-term momentum calculations.
Short - L2: Length of the second EMA for short-term momentum calculations.
Short - L3: RSI smoothing period applied to the short-term momentum.
Long-Term Momentum Parameters:
Long - L1: Length of the EMA for long-term momentum calculations.
Long - L2: RSI smoothing period applied to the long-term momentum.
Entry and Exit Logic
Entry Condition:
A long trade is triggered when:
The BX-Trender Oscillator changes from red to green .
This shift indicates bullish momentum.
Exit Condition:
A long trade exit is triggered when:
The BX-Trender Oscillator changes from green to red .
This shift indicates a loss of bullish momentum or the start of bearish momentum.
PnL Calculation:
When exiting a trade, the indicator calculates the profit or loss as a percentage of the entry price.
Example:
A profit is displayed as +5.67% .
A loss is displayed as -3.21% .
Visualization
Oscillator Bars:
Green Bars: Represent increasing bullish momentum.
Light Green Bars: Represent weakening bullish momentum.
Red Bars: Represent increasing bearish momentum.
Light Red Bars: Represent weakening bearish momentum.
Just make sure that you checked off the B-Xtrend oscillator off from the style so chart can be active
Trade Labels:
Entry Labels: Displayed below the candle with the text Entry, long .
Exit Labels: Displayed above the candle with the text Exit .
Bar Chart Pane:
The oscillator is displayed in a separate pane for clear trend visualization.
Default Style
Oscillator Colors:
Green for bullish momentum.
Red for bearish momentum.
Light green and light red for weaker momentum.
Trade Labels:
Green labels for entries.
Red labels for exits, with percentage PnL displayed.
Use Cases
Momentum-Based Entries:
Detects shifts in momentum from bearish to bullish for precise trade entry points.
Trend Reversal Detection:
Identifies when bullish momentum weakens, signaling an exit opportunity.
Visual Simplicity:
Offers an intuitive way to track trends with its bar chart-style oscillator and clear trade labels.
This indicator doesn't indicate that it will work perfectly. More updates on the way.
Bitcoin Cycle [BigBeluga]Bitcoin Cycle Indicator is designed exclusively for analyzing Bitcoin’s long-term market cycles, working only on the 1D BTC chart . This indicator provides an in-depth view of potential cycle tops and bottoms, assisting traders in identifying key phases in Bitcoin’s market evolution.
🔵 Key Features:
Heatmap Cycle Phases: The indicator colors each cycle from blue to red , reflecting Bitcoin’s market cycle progression. Cooler colors (blue/green) signal potential accumulation or early growth phases, while warmer colors (yellow/red) indicate maturation and potential top regions.
All-Time High (ATH) and Future ATH Projection: Tracks the current ATH in real-time, while applying a linear regression model to project a possible new ATH in the future. This projection aims to provide insights into the next major cycle peak for long-term strategy.
Dashboard Overview: Displays the current ATH, potential new ATH, and the percentage distance between them. This helps users assess how far the current price is from the projected target.
Top & Bottom Cycle Signals: Red down arrows mark significant price peaks, potentially indicating cycle tops. Up arrows, numbered sequentially (inside each cycle), denote possible bottom signals for strategic DCA (Dollar Cost Averaging) entries.
1D BTC Chart Only: Built solely for the 1D BTC timeframe. Switching to any other timeframe or asset will trigger a warning message: " BTC 1D Only ." This ensures accuracy in analyzing Bitcoin’s unique cyclical behavior.
🔵 When to Use:
Ideal for long-term Bitcoin investors and cycle analysts, the Bitcoin Cycle Indicator empowers users to:
Identify key accumulation and distribution phases.
Track Bitcoin’s cyclical highs and lows with visual heatmap cues.
Estimate future potential highs based on historical patterns.
Strategize long-term positions by monitoring cycle tops and possible accumulation zones.
By visualizing Bitcoin’s cycles with color-coded clarity and top/bottom markers, this indicator is an essential tool for any BTC analyst aiming to navigate market cycles effectively.
T3 with ArrowsThe arrows indicate trend reversals - first time closing below and first time closing above.
Heikin Ashi Impulse SystemThis indicator uses Heikin Ashi and EMA to find buy and sell points, and uses EMA to filter out noise.
To color the K-line using Heikin Ashi, you may need to close the original K-line or place the indicator on the top layer.
On smaller timeframes you can reduce the buy/sell noise by increasing the EMA value, and enjoy it.
ICT SETUP BY SHUBHAM MEWARAICT concept setups for buying and selling above ema 200 for long and below ema 200 for short win rate is 70-80% manage proper riskmanagement of your capital
Sharpe Ratio Indicator (180)Meant to be used on the 1D chart and on BTC.
The Sharpe Ratio Indicator (180 days) is a tool for evaluating risk-adjusted returns, designed for investors who want to assess whether BTC is overvalued, undervalued, or in a neutral state. It plots the Sharpe Ratio over the past 180 days, color-coded to indicate valuation states:
- Red: Overvalued (Sharpe Ratio > 5).
- Green: Undervalued (Sharpe Ratio < -1).
-Blue: Critically Undervalued (Sharpe Ratio <-3).
- Yellow: Neutral (between -1 and 5).
Note that you can change those values yourself in the settings of the indicator.
Strengths:
- Real-time feedback on risk-adjusted returns helps in making timely investment decisions.
- Color-coded signals (red, green, blue and yellow) provide an intuitive, visual indication of the asset's valuation.
- Flexible: Easily adjustable to different subjective valuation levels and risk-free rates.
All hail to Professor Adam and The Real World Community!
Advanced Pivot Manipulation SuperTrend - Consolidation ZoneHere’s the description translated into English for your TradingView publication:
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Advanced Pivot Manipulation SuperTrend - Consolidation Zone
Description :
This advanced indicator combines multiple technical tools to provide a comprehensive analysis of trends, key levels, and consolidation zones. Ideal for traders seeking to spot opportunities while avoiding the traps of flat markets, it helps you better understand market dynamics and improve your trading decisions.
Key Features:
1.
Dynamic SuperTrend with Pivot Points:
- An enhanced SuperTrend algorithm based on pivot points for more precise trend tracking.
- Thresholds (Up/Dn) are dynamically adjusted using ATR (Average True Range) for improved volatility adaptation.
2. Consolidation Zones:
- Automatically identifies periods when the market moves within a narrow range (1% by default).
- Consolidation zones are visually highlighted to help avoid risky trades.
3. Dynamic Support and Resistance:
- Automatically calculates support and resistance levels based on a rolling period (configurable).
- These levels serve as key references for potential breakouts or trend reversals.
4. Advanced Detection Tools:
- Includes a volume multiplier and shadow-to-body ratio to signal unusual or potentially manipulated moves (e.g., spoofing).
5. Intuitive Visuals:
- SuperTrend lines are color-coded to indicate bullish (green) or bearish (red) trends.
- Semi-transparent lines mark support and resistance levels, and red backgrounds indicate consolidation zones.
Customizable Parameters:
- Pivot Point Period: Adjust the period for detecting pivot highs and lows.
- ATR Factor and Period: Control the sensitivity of the SuperTrend indicator.
- Lookback Period for S/R: Define the duration for calculating support and resistance levels.
- Volume Multiplier and Shadow/Body Ratio: Configure thresholds for detecting high volumes or anomalies in candlestick patterns.
How to Use:
- Easily identify dominant trends using the SuperTrend.
- Spot consolidation zones to avoid inefficient trades or prepare breakout strategies.
- Use support and resistance levels as reference points for placing orders or adjusting risk management.
Target Audience:
- Intraday and swing traders.
- Anyone looking for a comprehensive and customizable indicator to effectively analyze volatile markets.
---
Notes:
The indicator is fully customizable to suit your needs and strategies. Feel free to experiment with the parameters to maximize its effectiveness according to your trading style.
Keywords: SuperTrend, Support and Resistance, Consolidation, Pivot Points, Trends, ATR, Advanced Trading.
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This description highlights the indicator’s strengths and is designed to appeal to the TradingView community.
CICLOS DE INDUCCIÓN - GHOST TRADER"El indicador Ciclos de Inducción está diseñado para identificar patrones clave en el mercado, combinando conceptos avanzados como Fair Value Gaps (FVG), Change of Character (CHoCH) y zonas de liquidez. Este indicador te ayudará a visualizar los puntos de manipulación e inducción de precios que suelen preceder a movimientos significativos del mercado.
Funcionalidades principales:
FVG (Fair Value Gaps): Detecta desequilibrios en el mercado para identificar posibles zonas de retroceso y entrada óptima.
CHoCH (Change of Character): Marca los cambios estructurales en el precio, indicando potenciales giros de tendencia.
Zonas de Liquidez: Resalta niveles de alta probabilidad donde el precio puede buscar liquidez, como máximos/mínimos anteriores.
Cómo funciona:
Identifica ciclos de inducción utilizando confluencias entre las zonas de FVG, CHoCH y niveles de liquidez.
Proporciona alertas visuales cuando hay una alta probabilidad de manipulación o movimiento direccional.
Resalta entradas potenciales basadas en el comportamiento del precio en zonas críticas.
Ideal para traders que siguen estrategias de Smart Money Concepts (SMC) y buscan precisión en la identificación de patrones de manipulación del mercado."
Support & resistance - DHJ : BUY/SELL Signal//@version=5
indicator(" Support & resistance - DHJ : Support/Resistance, EMA Crossover, Previous Day High/Low", shorttitle = "Support & resistance - DHJ", overlay=true, max_boxes_count=50)
// User Inputs
int lookbackPeriod = input.int(20, "Lookback Period", minval=1, group="Settings")
int vol_len = input.int(2, "Delta Volume Filter Length", tooltip="Higher input, will filter low volume boxes", group="Settings")
float box_withd = input.float(1, "Adjust Box Width", maxval=1000, minval=0, step=0.1, group="Settings")
// Define the EMAs
ema9 = ta.ema(close, 9)
ema21 = ta.ema(close, 21)
// Plot the EMAs
plot(ema9, color=color.blue, linewidth=1)
plot(ema21, color=color.red, linewidth=1)
// Crossover conditions
longCondition = ta.crossover(ema9, ema21)
shortCondition = ta.crossunder(ema9, ema21)
// Plot buy/sell signals
plotshape(series=longCondition, location=location.belowbar, color=color.green, style=shape.labelup, text="BUY")
plotshape(series=shortCondition, location=location.abovebar, color=color.red, style=shape.labeldown, text="SELL")
// Previous day high and low
var float pdHigh = na
var float pdLow = na
if (ta.change(time("1D")))
pdHigh := high
pdLow := low
plot(pdHigh, color=color.green, linewidth=1, title="Previous Day High")
plot(pdLow, color=color.red, linewidth=1, title="Previous Day Low")
// Delta Volume Function
upAndDownVolume() =>
posVol = 0.0
negVol = 0.0
var isBuyVolume = true
switch
close > open => isBuyVolume := true
close < open => isBuyVolume := false
if isBuyVolume
posVol += volume
else
negVol -= volume
posVol + negVol
// Function to identify support and resistance boxes
calcSupportResistance(src, lookbackPeriod) =>
// Volume
Vol = upAndDownVolume()
vol_hi = ta.highest(Vol / 2.5, vol_len)
vol_lo = ta.lowest(Vol / 2.5, vol_len)
var float supportLevel = na
var float supportLevel_1 = na
var float resistanceLevel = na
var float resistanceLevel_1 = na
var box sup = na
var box res = na
var color res_color = na
var color sup_color = na
var float multi = na
var bool brekout_res = na
var bool brekout_sup = na
var bool res_holds = na
var bool sup_holds = na
// Find pivot points
pivotHigh = ta.pivothigh(src, lookbackPeriod, lookbackPeriod)
pivotLow = ta.pivotlow(src, lookbackPeriod, lookbackPeriod)
// Box width
atr = ta.atr(200)
withd = atr * box_withd
// Find support levels with Positive Volume
if (not na(pivotLow)) and Vol > vol_hi
supportLevel := pivotLow
supportLevel_1 := supportLevel - withd
topLeft = chart.point.from_index(bar_index - lookbackPeriod, supportLevel)
bottomRight = chart.point.from_index(bar_index, supportLevel_1)
sup_color := color.from_gradient(Vol, 0, ta.highest(Vol, 25), color(na), color.new(color.green, 30))
sup := box.new(
top_left = topLeft,
bottom_right = bottomRight,
border_color = color.green,
border_width = 1,
bgcolor = sup_color,
text = "Vol: " + str.tostring(math.round(Vol, 2)),
text_color = chart.fg_color,
text_size = size.small
)
// Find resistance levels with Negative Volume
if (not na(pivotHigh)) and Vol < vol_lo
resistanceLevel := pivotHigh
resistanceLevel_1 := resistanceLevel + withd
topLeft = chart.point.from_index(bar_index - lookbackPeriod, resistanceLevel)
bottomRight = chart.point.from_index(bar_index, resistanceLevel_1)
res_color := color.from_gradient(Vol, ta.lowest(Vol, 25), 0, color.new(color.red, 30), color(na))
res := box.new(
top_left = topLeft,
bottom_right = bottomRight,
border_color = color.red,
border_width = 1,
bgcolor = res_color,
text = "Vol: " + str.tostring(math.round(Vol, 2)),
text_color = chart.fg_color,
text_size = size.small
)
// Adaptive Box Len
sup.set_right(bar_index + 1)
res.set_right(bar_index + 1)
// Break of support or resistance conditions
brekout_res := ta.crossover(low, resistanceLevel_1)
res_holds := ta.crossunder(high, resistanceLevel)
sup_holds := ta.crossover(low, supportLevel)
brekout_sup := ta.crossunder(high, supportLevel_1)
// Change Color of Support to red if it was break, change color of resistance to green if it was break
if brekout_sup
sup.set_bgcolor(color.new(color.red, 80))
sup.set_border_color(color.red)
sup.set_border_style(line.style_dashed)
if sup_holds
sup.set_bgcolor(sup_color)
sup.set_border_color(color.green)
sup.set_border_style(line.style_solid)
if brekout_res
res.set_bgcolor(color.new(color.green, 80))
res.set_border_color(color.new(color.green, 0))
res.set_border_style(line.style_dashed)
if res_holds
res.set_bgcolor(res_color)
res.set_border_color(color.new(color.red, 0))
res.set_border_style(line.style_solid)
// Calculate support and resistance levels and their breakouts
= calcSupportResistance(close, lookbackPeriod)
// Check if Resistance becomes Support or Support Becomes Resistance
var bool res_is_sup = na
var bool sup_is_res = na
switch
brekout_res => res_is_sup := true
res_holds => res_is_sup := false
switch
brekout_sup => sup_is_res := true
sup_holds => sup_is_res := false
// Plot Res and Sup breakouts and holds
plotchar(res_holds, "Resistance Holds", "◆", color = #e92929, size = size.tiny, location = location.abovebar, offset = -1)
plotchar(sup_holds, "Support Holds", "◆", color = #20ca26, size = size.tiny, location = location.belowbar, offset = -1)
plotchar(brekout_res and res_is_sup , "Resistance as Support Holds", "◆", color = #20ca26, size = size.tiny, location = location.belowbar, offset = -1)
plotchar(brekout_sup and sup_is_res , "Support as Resistance Holds", "◆", color = #e92929, size = size.tiny, location = location.abovebar, offset = -1)
// Break Out Labels
if brekout_sup and not sup_is_res
label.new(
bar_index , supportLevel ,
text = "Break Sup",
style = label.style_label_down,
color = #7e1e1e,
textcolor = chart.fg_color,
size = size.small
)
if brekout_res and not res_is_sup
label.new(
bar_index , resistanceLevel ,
text = "Break Res",
style = label.style_label_up,
color = #2b6d2d,
textcolor = chart.fg_color,
size = size.small
)
Trend Intensity Index TeyoV5This indicator measures the strength and direction of a trend by analyzing the relationship between multiple smoothed price averages. It calculates an intensity index value, which ranges from 0 to 100, indicating the strength of the current trend.
Key Features:
Multiple Smoothing Methods: Users can select from various smoothing techniques (e.g., SMA, EMA, WMA) to customize the indicator's sensitivity.
Adjustable Smoothing Periods: Different smoothing periods can be applied to the price data to identify trends at various timeframes.
Intensity Index Calculation: The indicator computes the intensity index by comparing the values of the smoothed price averages. A higher positive value indicates a stronger uptrend, while a higher negative value suggests a stronger downtrend.
Visual Representation: The indicator is displayed as a line plot, with the intensity index values plotted against the price chart.
This indicator can be used to identify potential trend reversals, filter out false signals, and improve the timing of entry and exit points.
London USDEGP priceThis indicator calculates the hypothetical USDEGP price using CIB receipts price in London Stock Exchange and its price in EGX. Values are smoothed.
USDEGP Rate MultipleIndicator shows the ratio between USDEGP rate calculated using CIB GDR and the official rate. In no stress, value should be stable.
Bollinger Bands Strategy 8:30a to 1:00aBollinger Bands Strategy I modified to only take trades during the hours of 8:30a to 1:00a Eastern Time.
Adjustable ORB with ORB multipliers "Adjustable ORB with ORB Multipliers," calculates and visually represents the Opening Range Breakout (ORB) based on a user-defined timeframe (defaulting to 15 minutes). It identifies the high and low of the opening range and shades the area between these levels in blue for clear visualization. The indicator then computes additional levels at multiples of the opening range—specifically 1x and 2x the range distance above and below the ORB. These multiplier levels are plotted on the chart (with white lines for 1x levels and yellow lines for 2x levels) and are labeled accordingly ("1x" and "2x") on the left side of each line for easy reference. Users can choose to display or hide the 1x and 2x levels through input options, allowing for customization based on trading preferences. This tool aids traders in identifying potential breakout zones and setting target levels based on the initial market movement of the day.
Funded System CloudVisually Enhanced EMA Cross Trading Alerts
Customize your strategy with fast and slow EMA crossovers.
Intelligent cloud filtering to highlight trending opportunities.
Visually identify trend direction with color-coded clouds.
Set dynamic stop loss levels with a trailing stop or cloud boundaries.
Receive timely alerts for EMA crosses and stop-loss triggers.
Original script was borrowed from SyntaxGeek - I made an adjustment by erasing the arrows.
Adaptive Linear Regression ChannelOverview
The Adaptive Linear Regression Channel Script is an advanced, multi-functional trading tool crafted to help traders pinpoint market trends, identify potential reversals, assess volatility, and establish dynamic levels for profit-taking and position exits. By incorporating key concepts such as linear regression , standard deviation , and other volatility measures like the ATR , the script offers a comprehensive view of market behavior beyond traditional deviation metrics.
This dynamic model continuously adapts to changing market conditions, adjusting in real-time to provide clear visualizations of trends, channels, and volatility levels. This adaptability makes the script invaluable for both trend-following and counter-trend strategies, giving traders the flexibility to respond effectively to different market environments.
Background
What is Linear Regression?
Definition : Linear regression is a statistical technique used to model the relationship between a dependent variable (target) and one or more independent variables (predictors).
In its simplest form (simple linear regression), the relationship between two variables is represented by a straight line (the regression line).
y = mx + b
where :
- y is the target variable (price)
- m is the slope
- x is the independent variable (time)
- b is the intercept
Slope of the Regression Line
Definition: The slope (m) measures the rate at which the dependent variable (y) changes as the independent variable (x) changes.
Interpretation:
- A positive slope indicates an uptrend.
- A negative slope indicates a downtrend.
Uses in Trading:
- Identifying the strength and direction of market trends.
- Assessing the momentum of price movements.
R-squared (Coefficient of Determination)
Definition: A measure of how well the regression line fits the data, ranging from 0 to 1.
Calculation :
R2 = 1− (SS tot/SS res)
where:
- SSres is the sum of squared residuals.
- SStot is the total sum of squares.
Interpretation:
- Higher R2 indicates a better fit, meaning the model explains a larger proportion of the variance in the data.
Uses in Trading:
- Higher R-squared values give traders confidence in trend-based signals.
- Low R-squared values may suggest that the market is more random or volatile.
Standard Deviation
Definition: Standard Deviation quantifies the dispersion of data points in a dataset relative to the mean. A low standard deviation indicates that data points tend to be close to the mean, while a high standard deviation indicates that the data points are spread out over a larger range of values.
Calculation
σ=√∑(xi−μ)2/N
Where
- σ is the standard deviation.
- ∑ is the summation symbol, indicating that the expression that follows should be summed over all data points.
- xi, this represents the i-th data point in the dataset.
- μ\mu, this represents the mean(average) of all the data points in the dataset.
- (xi−μ)2, this is the squared difference between each data point and the mean.
- N is the total number of data points in the dataset.
- **Interpretation**
- A higher standard deviation indicates greater volatility.
- Useful for identifying overbought/oversold conditions in markets.
Key Features
Dynamic Linear Regression Channels:
The script automatically generates adaptive regression channels that expand or contract based on the current market volatility. This real-time adjustment ensures that traders are always working with the most relevant data, making it easier to spot key support and resistance levels.
The channel width itself serves as an indicator of market volatility, expanding during periods of heightened uncertainty and contracting during more stable phases. Additionally, the channel width is trained on previous channel widths , allowing the script to adapt and provide a more accurate view of volatility trends of the asset. Traders can also customize the script to train on less historical data , enabling a more recent view of volatility , which is particularly useful in fast-moving or changing markets.
Dynamic Profits and Stops:
What is it?
Dynamic profit levels allow traders to adjust take-profit targets based on real-time market conditions. Unlike static levels, which remain fixed regardless of market changes, these adaptive levels leverage past volatility data to create more flexible profit-taking strategies.
How does it work?
The script determines these levels using previously stored deviation values. These deviations are categorized into quantiles (like Q1, Q2, Q3, etc.) to classify current market conditions. As new deviation data is recorded, the profit levels are adjusted dynamically to reflect changes in market volatility. This approach helps to refine profit targets, especially when using regression channels with standard deviation rather than traditional ATR bands.
Why is it valuable?
By utilizing adaptive profit levels, traders can optimize their exits based on the current volatility landscape. For instance, when volatility increases, the dynamic levels expand, allowing trades to capture larger price movements. Conversely, during low volatility, profit targets tighten to lock in gains sooner, reducing exposure to market reversals. This flexibility is especially beneficial when combined with adaptive regression channels that respond to changes in standard deviation.
Slope-Based Trend Analysis:
One of the core elements of this script is the slope of the regression line , which helps define the direction and strength of the trend. Positive slopes indicate bullish momentum, while negative slopes suggest bearish conditions. The slope's steepness gives traders insight into the market's momentum, allowing them to adjust their strategies based on the strength of the trend.
Additionally, the script uses the slope to create a color gradient , which visually represents the intensity of the market's momentum. The gradient peaks at one color to show the maximum bullish momentum experienced in the past, while another color represents the maximum bearish momentum experienced in the past. This color-coded visualization makes it easier for traders to quickly assess the market's strength and direction at a glance.
Volatility Heatmap:
The integrated heatmap provides an intuitive, color-coded visualization of market volatility. The heatmap highlights areas where price action is expanding or contracting, giving traders a clear view of where volatility is rising or falling. By mapping out deviations from the regression line, the heatmap makes it easier to spot periods of high volatility that could lead to major market moves or potential reversals.
Deviation Concepts:
The script tracks price deviations from the regression line when a new range is formed, providing valuable insights when the price significantly deviates from the expected trend. These deviations are key in identifying potential breakout points or trend shifts .
This helps traders understand when the market is overextended or when a pullback may be imminent, allowing them to make more informed trading decisions.
Adaptive Model Properties:
Unlike static indicators, this script adapts over time . As the market changes, it stores historical data related to channel widths , slope dynamics , and volatility levels , adjusting its analysis accordingly to stay relevant to current market conditions.
Traders have the ability to train the model on all available data or specify a set number of bars to focus on more recent market activity. This flexibility allows for more tailored analysis , ensuring that traders can work with data that best fits their trading style and time horizon.
This continuous learning approach ensures that traders always have the most up-to-date insight into the market's structure.
Table
The table displays key metrics in real time to provide deeper insights into market behavior:
1. Deviation & Slope : Shows the current deviation if set to standard deviation or atr if set to atr(values used to calculated the channel widths) and the trend slope, helping to gauge market volatility and trend direction.
2. Rate of Change : For both deviation/atr and slope, the table also calculates the rate of change of their rates—essentially capturing the acceleration or deceleration of trends and volatility. This helps identify shifts in market momentum early.
3. R-squared : Indicates the strength and reliability of the trend fit. A higher value means the regression line better explains the price movements.
4. Quantiles : Uses historical deviation data to categorize current market conditions into quartiles (e.g., Q1, Q2, Q3). This helps classify the market's current volatility level, allowing traders to adjust strategies dynamically.
By combining these metrics, the table offers a comprehensive, real-time snapshot of market conditions, enabling more informed and adaptive trading decisions.
Settings
Here’s a breakdown of the script's settings for easy reference:
Linear Regression Settings
Show Dynamic Levels :Toggle to display dynamic profit levels on the chart.
Deviation Type :Select the method for calculating deviation—options include ATR (Average True Range) or Standard Deviation.
Timeframe :Sets the specific timeframe for the regression analysis (default is the chart’s timeframe).
Period :Defines the number of bars used for calculating the regression line (e.g., 50 bars).
Deviation Multiplier :Multiplier used to adjust the width of the deviation channel around the regression line.
Rate of Change :Sets the period for calculating the rate of change of the slope (used for momentum analysis).
Max Bars Back :Limits the number of historical bars to analyze (0 means all available data).
Slope Lookback :Number of bars used to calculate the slope gradient for trend detection.
Slope Gradient Display :Toggle to enable gradient coloring based on slope direction.
Slope Gradient Colors :Set colors for positive and negative slopes, respectively.
Slope Fill :Adjusts the transparency of the slope gradient fill.
Volatility Gradient Display :Toggle to enable gradient coloring based on volatility levels.
Volatility Gradient Colors :Set colors for low and high volatility, respectively.
Volatility Fill :Adjusts the transparency of the volatility gradient fill.
Table Settings
Show Table :Toggle to display the metrics table on the chart.
Table Position :Choose where to position the table (e.g., top-right, middle-center, etc.).
Font Size :Set the size of the text in the table. Options include Tiny, Small, Normal, Large, and Huge.
Simple Parallel Channel TrackerThis script will automatically draw price channels with two parallel trends lines, the upper trendline and lower trendline. These lines can be changed in terms of appearance at any time.
The Script takes in fractals from local and historic price action points and connects them over a certain period or amount of candles as inputted by the user. It tracks the most recent highs and lows formed and uses this data to determine where the channel begins.
The Script will decide whether to use the most recent high, or low, depending on what comes first.
Why is this useful?
Often, Traders either have no trend lines on their charts, or they draw them incorrectly. Whichever category a trader falls into, there can only be benefits from having Trend lines and Parallel Channels drawn automatically.
Trends naturally occur in all Markets, all the time. These oscillations when tracked allow for a more reliable following of Markets and management of Market cycles.
Magic Trend LineThe Magic Trend line in your script is derived using the Commodity Channel Index (CCI), along with adjustments based on the Average True Range (ATR) to create a dynamic trend-following indicator. The key idea behind this is to provide a smoothed trend line that responds to both market volatility (using ATR) and the underlying price action (via CCI).
Here’s a step-by-step breakdown of how the Magic Trend line is calculated:
1. CCI Calculation
The Commodity Channel Index (CCI) is a momentum-based indicator that measures the deviation of the current price from its average over a specified period. In this script:
The CCI period is set to 20 bars by default, controlled by the lengthCCI input.
The CCI formula is:
𝐶
𝐶
𝐼
=
Close
−
SMA(Close, lengthCCI)
0.015
×
Mean Deviation
CCI=
0.015×Mean Deviation
Close−SMA(Close, lengthCCI)
where the Mean Deviation is the average of the absolute differences between the close price and the SMA of the close.
2. ATR-Based Trend Bands
The Average True Range (ATR) is a measure of volatility, and it's used here to define dynamic upper and lower trend bands. These bands adjust based on the volatility of the market, providing a flexible trend filter.
The ATR period is set to 5 bars by default, controlled by the AP input.
The ATR multiplier (coeff) is set to 1.0 by default.
Using the ATR, two trend bands are calculated:
Upper Trend Band (upT): low - ATR * coeff
Lower Trend Band (downT): high + ATR * coeff
These bands help to determine whether the market is in an uptrend or a downtrend, and they dynamically adjust to market conditions.
3. Magic Trend Line Adjustment
Once the CCI is calculated and the ATR-based bands are defined, the Magic Trend line (MagicTrend) is determined as follows:
If the CCI is greater than or equal to 0 (indicating a bullish market condition), the Magic Trend is pushed upwards towards the upper trend band, ensuring the trend does not dip below the upward ATR-based boundary. The line is adjusted to be the maximum of the previous Magic Trend value and the upper trend boundary.
MagicTrend
=
max
(
upT
,
MagicTrend
)
MagicTrend=max(upT,MagicTrend )
If the CCI is less than 0 (indicating a bearish market condition), the Magic Trend is pushed downwards towards the lower trend band, ensuring the trend does not rise above the downward ATR-based boundary. The line is adjusted to be the minimum of the previous Magic Trend value and the lower trend boundary.
MagicTrend
=
min
(
downT
,
MagicTrend
)
MagicTrend=min(downT,MagicTrend )
This approach smooths the CCI values while constraining them within dynamically adjusted trend bands based on market volatility.
4. Trend Coloring
The Magic Trend line is colored blue when the trend is bullish (CCI ≥ 0).
It is colored red when the trend is bearish (CCI < 0).
In Summary:
The Magic Trend is essentially a dynamic trend line that adapts to both price momentum (via CCI) and market volatility (via ATR). It is designed to smooth out the market's fluctuations and provide a clear visual indication of the trend direction. The line itself is adjusted to never exceed certain volatility boundaries defined by the ATR, ensuring it remains in sync with the market's natural fluctuations. The trend direction is color-coded for easy interpretation: blue for bullish trends and red for bearish trends.
Buy When There's Blood in the Streets StrategyStatistical Analysis of Drawdowns in Stock Markets
Drawdowns, defined as the decline from a peak to a trough in asset prices, are an essential measure of risk and market dynamics. Their statistical properties provide insights into market behavior during extreme stress periods.
Distribution of Drawdowns: Research suggests that drawdowns follow a power-law distribution, implying that large drawdowns, while rare, are more frequent than expected under normal distributions (Sornette et al., 2003).
Impacts of Extreme Drawdowns: During significant drawdowns (e.g., financial crises), the average recovery time is significantly longer, highlighting market inefficiencies and behavioral biases. For example, the 2008 financial crisis led to a 57% drawdown in the S&P 500, requiring years to recover (Cont, 2001).
Using Standard Deviations: Drawdowns exceeding two or three standard deviations from their historical mean are often indicative of market overreaction or capitulation, creating contrarian investment opportunities (Taleb, 2007).
Behavioral Finance Perspective: Investors often exhibit panic-selling during drawdowns, leading to oversold conditions that can be exploited using statistical thresholds like standard deviations (Kahneman, 2011).
Practical Implications: Studies on mean reversion show that extreme drawdowns are frequently followed by periods of recovery, especially in equity markets. This underpins strategies that "buy the dip" under specific, statistically derived conditions (Jegadeesh & Titman, 1993).
References:
Sornette, D., & Johansen, A. (2003). Stock market crashes and endogenous dynamics.
Cont, R. (2001). Empirical properties of asset returns: stylized facts and statistical issues. Quantitative Finance.
Taleb, N. N. (2007). The Black Swan: The Impact of the Highly Improbable.
Kahneman, D. (2011). Thinking, Fast and Slow.
Jegadeesh, N., & Titman, S. (1993). Returns to Buying Winners and Selling Losers: Implications for Stock Market Efficiency.
