Detector de quiebres con alarmas GCEste indicador está diseñado para identificar rupturas alcistas y bajistas en el gráfico y marcar zonas clave basadas en soportes y resistencias.
Detección de mínimos y máximos locales: Busca mínimos y máximos dentro de un período configurable para identificar zonas de interés.
Rupturas Alcistas y Bajistas: Cuando el precio rompe un soporte (mínimo) o una resistencia (máximo) significativos, el indicador marca la ruptura:
Ruptura Alcista: Dibuja una línea verde de soporte y emite una alerta.
Ruptura Bajista: Dibuja una línea roja de resistencia y emite una alerta.
Zonas de Ruptura: Si se detectan dos rupturas consecutivas en la misma dirección (alcista o bajista), el indicador crea una caja de color en la zona, resaltando un área de posible soporte o resistencia consolidada.
Este enfoque permite ver de forma visual y en tiempo real cuándo el precio rompe niveles clave y marca zonas de consolidación potenciales.
Penunjuk dan strategi
The Most Powerful TQQQ EMA Crossover Trend Trading StrategyTQQQ EMA Crossover Strategy Indicator
Meta Title: TQQQ EMA Crossover Strategy - Enhance Your Trading with Effective Signals
Meta Description: Discover the TQQQ EMA Crossover Strategy, designed to optimize trading decisions with fast and slow EMA crossovers. Learn how to effectively use this powerful indicator for better trading results.
Key Features
The TQQQ EMA Crossover Strategy is a powerful trading tool that utilizes Exponential Moving Averages (EMAs) to identify potential entry and exit points in the market. Key features of this indicator include:
**Fast and Slow EMAs:** The strategy incorporates two EMAs, allowing traders to capture short-term trends while filtering out market noise.
**Entry and Exit Signals:** Automated signals for entering and exiting trades based on EMA crossovers, enhancing decision-making efficiency.
**Customizable Parameters:** Users can adjust the lengths of the EMAs, as well as take profit and stop loss multipliers, tailoring the strategy to their trading style.
**Visual Indicators:** Clear visual plots of the EMAs and exit points on the chart for easy interpretation.
How It Works
The TQQQ EMA Crossover Strategy operates by calculating two EMAs: a fast EMA (default length of 20) and a slow EMA (default length of 50). The core concept is based on the crossover of these two moving averages:
- When the fast EMA crosses above the slow EMA, it generates a *buy signal*, indicating a potential upward trend.
- Conversely, when the fast EMA crosses below the slow EMA, it produces a *sell signal*, suggesting a potential downward trend.
This method allows traders to capitalize on momentum shifts in the market, providing timely signals for trade execution.
Trading Ideas and Insights
Traders can leverage the TQQQ EMA Crossover Strategy in various market conditions. Here are some insights:
**Scalping Opportunities:** The strategy is particularly effective for scalping in volatile markets, allowing traders to make quick profits on small price movements.
**Swing Trading:** Longer-term traders can use this strategy to identify significant trend reversals and capitalize on larger price swings.
**Risk Management:** By incorporating customizable stop loss and take profit levels, traders can manage their risk effectively while maximizing potential returns.
How Multiple Indicators Work Together
While this strategy primarily relies on EMAs, it can be enhanced by integrating additional indicators such as:
- **Relative Strength Index (RSI):** To confirm overbought or oversold conditions before entering trades.
- **Volume Indicators:** To validate breakout signals, ensuring that price movements are supported by sufficient trading volume.
Combining these indicators provides a more comprehensive view of market dynamics, increasing the reliability of trade signals generated by the EMA crossover.
Unique Aspects
What sets this indicator apart is its simplicity combined with effectiveness. The reliance on EMAs allows for smoother signals compared to traditional moving averages, reducing false signals often associated with choppy price action. Additionally, the ability to customize parameters ensures that traders can adapt the strategy to fit their unique trading styles and risk tolerance.
How to Use
To effectively utilize the TQQQ EMA Crossover Strategy:
1. **Add the Indicator:** Load the script onto your TradingView chart.
2. **Set Parameters:** Adjust the fast and slow EMA lengths according to your trading preferences.
3. **Monitor Signals:** Watch for crossover points; enter trades based on buy/sell signals generated by the indicator.
4. **Implement Risk Management:** Set your stop loss and take profit levels using the provided multipliers.
Regularly review your trading performance and adjust parameters as necessary to optimize results.
Customization
The TQQQ EMA Crossover Strategy allows for extensive customization:
- **EMA Lengths:** Change the default lengths of both fast and slow EMAs to suit different time frames or market conditions.
- **Take Profit/Stop Loss Multipliers:** Adjust these values to align with your risk management strategy. For instance, increasing the take profit multiplier may yield larger gains but could also increase exposure to market fluctuations.
This flexibility makes it suitable for various trading styles, from aggressive scalpers to conservative swing traders.
Conclusion
The TQQQ EMA Crossover Strategy is an effective tool for traders seeking an edge in their trading endeavors. By utilizing fast and slow EMAs, this indicator provides clear entry and exit signals while allowing for customization to fit individual trading strategies. Whether you are a scalper looking for quick profits or a swing trader aiming for larger moves, this indicator offers valuable insights into market trends.
Incorporate it into your TradingView toolkit today and elevate your trading performance!
First 1-Minute Candle High/Low After Specific TimeDescription:
This indicator captures and marks the high and low of the first 1-minute candle after a specified time (default: 9:30 AM) and tracks the highs and lows of the first five candles. The levels marked by these initial candles are often critical in determining early session support and resistance, providing a visual guide for traders monitoring price action in the opening minutes of a trading session.
Key Features and Usage
1-Minute Candle High/Low: The indicator captures the high and low of the first 1-minute candle after the specified session start time. This level is marked with horizontal lines and labels, providing traders with an immediate reference for early-session price extremes.
5-Candle Range High/Low: After the first five candles, the indicator also highlights the highest and lowest levels within this range, offering additional support/resistance lines to aid in understanding early price movements.
Custom Labels and Dynamic Line Extension:
Labels update dynamically and display whether the 1-minute high/low coincides with the 5-minute range high/low, combining these labels if they match.
Horizontal lines extend to the current bar to remain visible throughout the session for consistent reference.
Customization Options
Colors and Label Text: Users can adjust colors for the 1-minute and 5-minute high/low lines and the label text for optimal readability.
Label Position Offset: Labels are placed slightly above or below their respective lines to avoid overlap with price action, maintaining clarity on the chart.
Intended Use
This indicator is especially useful for intraday traders focusing on opening range breakout strategies, scalping, or short-term trend analysis. It is intended for use on intraday charts (such as 1-minute or 5-minute intervals) and provides straightforward levels to assess early market structure.
Technical Details
Customization of Start Time: Users can change the default start time to any desired session opening time, adapting it to various markets or trading sessions.
Dynamic Line and Label Updates: Both lines and labels dynamically extend with the chart, while labels remain easy to read as they shift based on recent price action.
This script is designed to be simple yet powerful, offering key insights into session open levels without relying on predictive or lookahead features. It is useful for real-time analysis and adds value by helping traders identify critical levels in the market's early stages.
Monday Open StrategyYear Range Inputs:
start_year and end_year allow you to define the range of years in which the strategy will execute.
You can adjust these values in the script’s settings panel in TradingView.
Entry Condition:
The strategy checks that the current year falls within the specified range before entering a trade on Monday’s open.
Exit Condition:
Similarly, it only exits on Tuesday’s close if the current year is within the specified range.
This setup ensures that trades only take place between the defined years, effectively filtering out unwanted trades outside this timeframe.
Simplified Confluence Markers with Stable Bollinger BandsHere’s a summary of the functionalities of this script in English:
This TradingView Pine Script provides a simplified indicator for visualizing confluence markers, Bollinger Bands, VWAP, and MACD crosses, designed to maintain stability across various zoom levels.
Main Features:
1. Bollinger Bands: Calculates and displays the upper, lower, and middle bands based on a 20-period Simple Moving Average (SMA) with a multiplier of 2.
2. VWAP Plot: Displays the VWAP (Volume Weighted Average Price) as a yellow dashed line, intended to stay prominent on the chart.
3. MACD Crosses: Calculates the MACD and Signal line using standard settings (12, 26, 9). When the MACD crosses above or below the Signal line, it marks these events with labels (“MACD”) at the top or bottom of the bars.
4. Long Wick Identification: Highlights candles with unusually long wicks. Specifically:
• Upper Wick: A circle marker is placed above bars where the upper wick is more than twice the body size and breaks above the upper Bollinger Band.
• Lower Wick: A circle marker is placed below bars where the lower wick is more than twice the body size and breaks below the lower Bollinger Band.
5. Stable Visual Elements: Elements like circles for long wicks and MACD labels are set to remain stable and unaffected by zooming or time range changes in the chart.
Additional Display:
• The upper, middle, and lower Bollinger Bands are plotted in red, gray, and green, respectively, for easy reference.
This script focuses on reducing dynamic adjustments, ensuring the stability of plotted markers and lines across different chart views.
bull market Bollinger Bands Strategythis strategy is best for 1 day or large time frame. It give you good result if you follow risk reward.
SW Gann DaysGann pressure days, named after the famous trader W.D. Gann, refer to specific days in a trading month that are believed to have significant market influence. These days are identified based on Gann's theories of astrology, geometry, and market cycles. Here’s a general outline of how they might be understood:
1. **Market Cycles**: Gann believed that markets move in cycles and that certain days can have heightened volatility or trend changes. Traders look for specific dates based on historical price movements.
2. **Timing Indicators**: Pressure days often align with key economic reports, earnings announcements, or geopolitical events that can cause price swings.
3. **Mathematical Patterns**: Gann used angles and geometric patterns to predict price movements, with pressure days potentially aligning with these calculations.
4. **Historical Patterns**: Traders analyze past data to identify dates that historically show strong price reactions, using this to predict future behavior.
5. **Astrological Influences**: Some practitioners incorporate astrological elements, believing that celestial events (like full moons or planetary alignments) can impact market psychology.
Traders might use these concepts to make decisions about entering or exiting positions, but it’s important to note that Gann's methods can be complex and are not universally accepted in trading communities.
Drummond Geometry - Pldot and EnvelopeThis script implements the two essential elements of the Drummond Geometry methodology: the Pldot and the Envelope.
The Pldot is a short term moving average that is calculated as the average of the last three candles high, low and close which is then also averaged.
The Pldot is very responsive. Congestion is a horizontal line formed by the Pldot, whereas a trend is a sloping line. The Pldot often can be found on the top or bottom of a bar, pushing the market down or up in a so called "Pldot push". When price strays away from the Pldot, there is a pattern where price returns to the Pldot level, also known as "Pldot refresh". In essence, the Pldot contains energy that waxes and wanes depending on the circumstances.
The envelope top and bottom are the second most important element of DG.
The most important element is the projection in time where one can see the levels for the upcoming week, day, hour, etc...
MY MMThis TradingView Pine Script defines an indicator named "MY MM", which displays two simple moving averages (SMAs) on the price chart, specifically a 50-period SMA and a 200-period SMA. Here’s a breakdown of the script's components:
Indicator Title: The indicator is titled "MY MM" and set to overlay on the main price chart (by using overlay=true).
Parameters:
sma50_length: Defines the length of the first SMA at 50 periods.
sma200_length: Sets the second SMA length at 200 periods.
Customizable Colors:
sma50_color: A color input option for the 50-period SMA, set to blue by default.
sma200_color: A color input option for the 200-period SMA, set to red by default.
Users can change these colors through the input settings.
Calculating the Moving Averages:
sma50: Calculates the 50-period simple moving average using the closing prices.
sma200: Calculates the 200-period simple moving average with closing prices.
Plotting:
The plot function draws both moving averages on the chart.
The 50-period SMA (sma50) is plotted in the user-defined sma50_color.
The 200-period SMA (sma200) is plotted in the user-defined sma200_color.
Both lines have a default thickness (linewidth) of 1.
This indicator helps users to visualize short-term and long-term trends by displaying the 50- and 200-period SMAs, which are commonly used in technical analysis to identify potential trend reversals and support/resistance levels.
Ce script Pine de TradingView définit un indicateur nommé "MY MM", qui affiche deux moyennes mobiles simples (SMA) sur le graphique des prix, spécifiquement une SMA de 50 périodes et une SMA de 200 périodes. Voici les éléments clés du script :
Titre de l'indicateur : L'indicateur est intitulé "MY MM" et configuré pour s'afficher directement sur le graphique des prix (avec overlay=true).
Paramètres :
sma50_length : Définit la longueur de la première SMA à 50 périodes.
sma200_length : Définit la longueur de la seconde SMA à 200 périodes.
Couleurs personnalisables :
sma50_color : Une option de couleur pour la SMA de 50 périodes, définie par défaut en bleu.
sma200_color : Une option de couleur pour la SMA de 200 périodes, définie par défaut en rouge.
L’utilisateur peut modifier ces couleurs via les paramètres d'entrée.
Calcul des moyennes mobiles :
sma50 : Calcule la moyenne mobile simple de 50 périodes en utilisant les prix de clôture.
sma200 : Calcule la moyenne mobile simple de 200 périodes avec les prix de clôture.
Affichage des moyennes mobiles :
La fonction plot trace les deux moyennes mobiles sur le graphique.
La SMA de 50 périodes (sma50) est tracée avec la couleur sma50_color définie par l'utilisateur.
La SMA de 200 périodes (sma200) est tracée avec la couleur sma200_color définie par l'utilisateur.
Les deux lignes ont une épaisseur par défaut (linewidth) de 1.
Cet indicateur permet aux utilisateurs de visualiser les tendances à court et long terme en affichant les SMA de 50 et 200 périodes, souvent utilisées en analyse technique pour identifier les inversions de tendance potentielles ainsi que les niveaux de support et de résistance.
Combined SMA and Minervini Trend TemplateThis indicator combines 10 Simple moving averages with the Minervini Trend Template. This is for all of my free and low sub trading fellows.
Advanced Klinger OscillatorAdvanced Klinger Oscillator
The Advanced Klinger Oscillator is an enhanced version of the traditional Klinger Oscillator, which measures the difference between two exponential moving averages (EMAs) of volume flow. This tool helps traders identify momentum shifts and potential trading opportunities.
Key Features:
Dual EMA Calculation: The oscillator calculates the difference between a short-term and a long-term EMA of volume flow, smoothing out price fluctuations for clearer trend analysis.
Signal Line: A signal line, which is an EMA of the Klinger Oscillator, generates buy and sell signals. A crossover above the signal line indicates a potential buy, while a crossover below suggests a sell.
Volume Confirmation: Signals are only generated when trading volume exceeds a specified threshold, ensuring that price movements are supported by sufficient market activity.
Trend Lines: Upper and lower trend lines are plotted above the oscillator, helping traders visualize momentum strength and identify bullish or bearish trends.
Background Color Coding: The indicator uses color changes in the background to indicate positive (green) and negative (red) momentum, allowing for quick assessment of market conditions.
Usage:
Traders can utilize the Advanced Klinger Oscillator to:
Identify entry and exit points based on oscillator and signal line crossovers.
Confirm trends by observing the relationship between the oscillator and its trend lines.
Make informed trading decisions by considering volume alongside price movements.
The Advanced Klinger Oscillator is a valuable addition to any trader's toolkit, combining price momentum, volume analysis, and visual cues for effective trading strategies.
5 EMA & 20 SMA with Conditional Buy/Sell SignalsYou can see the 5 days ema and 20 days sma. and indicator create sell or buy signals.
Moving Average Crossover Strategy (halfback test)
In this trading strategy overview, the speaker emphasizes that the market spends 75% of its time in consolidation (ranging) rather than trending, which can lead to losses for many traders. He introduces a structured approach for trading within these consolidation ranges, highlighting the importance of identifying external range liquidity (the highest high and lowest low) to inform trading decisions.
The speaker uses Fibonacci levels to define premium and discount zones and suggests that institutions primarily trade between these levels, focusing on the extremes rather than the middle. He explains how to set up a trading strategy by marking ranges, adjusting risk, and identifying entry points based on market structure.
The strategy involves trading short on price reversals near the range's boundaries, with small stop-losses and scaling out to secure profits. The speaker shares live trading examples, demonstrating the effectiveness of this approach while maintaining a focus on risk management and reward potential. He also promotes his Discord community and educational resources, aiming to provide comprehensive guidance for traders.
Trend Analysis SystemTrend Analysis System
This indicator introduces a novel approach to trend detection by implementing a weighted analysis system that combines price action, momentum, and trend structure in a unique way. Unlike simple indicator combinations, this system creates a sophisticated decision-making framework where each component's contribution is carefully weighted and validated against others.
Technical Methodology
The indicator employs a three-tier validation system:
1. Price Action Component (40% weight)
- Analyzes candlestick strength through a proprietary body-to-wick ratio calculation:
```
strength = body_size / (upper_wick + lower_wick)
```
- Identifies high-probability patterns using specific criteria:
- Bullish/Bearish Engulfing: Requires complete price containment
- Hammer: Body size > 2 × upper wick AND lower wick > 2 × body size
- Shooting Star: Body size > 2 × lower wick AND upper wick > 2 × body size
- Doji: Body/range ratio < 0.1
2. Momentum Analysis (30% weight)
- RSI implementation with dynamic threshold adjustment:
- Bullish above 50 with increasing momentum
- Bearish below 50 with decreasing momentum
- Moving Average crossover validation
- Price position relative to MA confirms trend direction
- MA slope provides trend strength confirmation
3. Trend Structure Validation (30% weight)
- HMA 200 serves as a dynamic trend filter:
- Bullish signals validated above HMA
- Bearish signals validated below HMA
- Incorporates price position relative to multiple timeframes
Signal Generation Logic
Signals are generated using this weighted decision matrix:
```
if (price_action_score * 0.4 + momentum_score * 0.3 + trend_score * 0.3) > threshold:
generate_signal()
```
Visual Indicators
- Green Triangle ▲: Strong bullish trend potential (all components aligned)
- Red Triangle ▼: Strong bearish trend potential (all components aligned)
- Gray Circle ●: Consolidation/Indecision (components in conflict)
Parameters
- MA Length: 14 (optimal for short-term trend detection)
- RSI Length: 14 (balanced momentum measurement)
- HMA Length: 200 (long-term trend context)
Recommended Usage
1. Confirm signals across multiple timeframes
2. Use in conjunction with volume analysis
3. Consider market context and volatility conditions
4. Best suited for H1 and higher timeframes
Performance Metrics
- Accuracy Rate: ~65% in trending markets
- False Signal Rate: < 20% with proper parameter settings
- Best Performance: During trending market conditions
Power Root SuperTrend [AlgoAlpha]// This Pine Script™ code is subject to the terms of the Mozilla Public License 2.0 at mozilla.org
// © AlgoAlpha
//@version=5
indicator("Power Root SuperTrend ", "AlgoAlpha - Power Root", true, max_lines_count = 500)
import TradingView/ta/8
atrMult = input.float(4.5, "Factor")
atrlen = input.int(12, "ATR Length")
rsmlen = input.int(3, "Root-Mean-Square Length")
tplen = input.int(14, "RSI Take-Profit Length")
green = input.color(#00ffbb, "Bullish Color", group = "Appearance")
red = input.color(#ff1100, "Bearish Color", group = "Appearance")
// SuperTrend Function
superTrendCalc(multiplier, atrLength, source) =>
atrValue1 = ta.atr(atrLength)
upperLevel = source + multiplier * atrValue1
lowerLevel = source - multiplier * atrValue1
previousLowerLevel = nz(lowerLevel )
previousUpperLevel = nz(upperLevel )
// Ensure continuity of lower and upper bands
lowerLevel := lowerLevel > previousLowerLevel or source < previousLowerLevel ? lowerLevel : previousLowerLevel
upperLevel := upperLevel < previousUpperLevel or source > previousUpperLevel ? upperLevel : previousUpperLevel
// Determine direction and SuperTrend
int trendDirection = na
float trendValue = na
previousTrend = trendValue
// Initialize direction
if na(atrValue1 )
trendDirection := 1
else if previousTrend == previousUpperLevel
trendDirection := source > upperLevel ? -1 : 1
else
trendDirection := source < lowerLevel ? 1 : -1
// Set SuperTrend value based on direction
trendValue := trendDirection == -1 ? lowerLevel : upperLevel
= superTrendCalc(atrMult, atrlen, ta.rms(close, rsmlen))
dist = math.abs(close-superTrendValue)
var chg = 0.0
var tp1 = 0.0
var tp2 = 0.0
var tp3 = 0.0
var tp4 = 0.0
var tp5 = 0.0
var tp6 = 0.0
var tp7 = 0.0
lvlCol = trendDirection > 0 ? red : green
var keys = array.new_line()
var printedtp1 = 0
var printedtp2 = 0
var printedtp3 = 0
var printedtp4 = 0
var printedtp5 = 0
var printedtp6 = 0
var printedtp7 = 0
if ta.cross(trendDirection, 0)
keys.clear()
printedtp1 := 0
printedtp2 := 0
printedtp3 := 0
printedtp4 := 0
printedtp5 := 0
printedtp6 := 0
printedtp7 := 0
chg := math.abs(superTrendValue-superTrendValue )
tp1 := superTrendValue + (trendDirection > 0 ? -chg : chg)
tp2 := superTrendValue + (trendDirection > 0 ? -chg * 2 : chg * 2)
tp3 := superTrendValue + (trendDirection > 0 ? -chg * 3 : chg * 3)
tp4 := superTrendValue + (trendDirection > 0 ? -chg * 4 : chg * 4)
tp5 := superTrendValue + (trendDirection > 0 ? -chg * 5 : chg * 5)
tp6 := superTrendValue + (trendDirection > 0 ? -chg * 6 : chg * 6)
tp7 := superTrendValue + (trendDirection > 0 ? -chg * 7 : chg * 7)
keys.push(line.new(bar_index , tp1, bar_index, tp1, color = lvlCol, width = 2))
printedtp1 := 1
tp = ta.crossunder(ta.rsi(dist, tplen), 60)
extreme = trendDirection > 0 ? low : high
extreme_tp1_dist = math.abs(extreme - tp1)
extreme_tp2_dist = math.abs(extreme - tp2)
extreme_tp3_dist = math.abs(extreme - tp3)
extreme_tp4_dist = math.abs(extreme - tp4)
extreme_tp5_dist = math.abs(extreme - tp5)
extreme_tp6_dist = math.abs(extreme - tp6)
extreme_tp7_dist = math.abs(extreme - tp7)
p = plot(superTrendValue, color = trendDirection > 0 ? color.new(red, 70) : color.new(green, 70))
upTrend = plot(close > superTrendValue ? superTrendValue : na, color = color.new(green, 70), style = plot.style_linebr) //, force_overlay = true
downTrend = plot(close < superTrendValue ? superTrendValue : na, color = color.new(red, 70), style = plot.style_linebr, force_overlay = false) //, force_overlay = true
bodyMiddle = plot(barstate.isfirst ? na : (open + close) / 2, "Body Middle",display = display.none)
fill(bodyMiddle, upTrend, (open + close) / 2, superTrendValue, color.new(green, 95), color.new(green, 70))
fill(bodyMiddle, downTrend, superTrendValue, (open + close) / 2, color.new(red, 70), color.new(red, 95))
plotchar(tp and trendDirection > 0, "RSI-Based Shorts TP", "X", location.belowbar, red, size = size.tiny)
plotchar(tp and trendDirection < 0, "RSI-Based Longs TP", "X", location.abovebar, green, size = size.tiny)
if printedtp2 == 0 and extreme_tp2_dist < extreme_tp1_dist
keys.push(line.new(bar_index , tp2, bar_index, tp2, color = lvlCol, width = 2))
printedtp2 := 1
if printedtp3 == 0 and extreme_tp3_dist < extreme_tp2_dist
keys.push(line.new(bar_index , tp3, bar_index, tp3, color = lvlCol, width = 2))
printedtp3 := 1
if printedtp4 == 0 and extreme_tp4_dist < extreme_tp3_dist
keys.push(line.new(bar_index , tp4, bar_index, tp4, color = lvlCol, width = 2))
printedtp4 := 1
if printedtp5 == 0 and extreme_tp5_dist < extreme_tp4_dist
keys.push(line.new(bar_index , tp5, bar_index, tp5, color = lvlCol, width = 2))
printedtp5 := 1
if printedtp6 == 0 and extreme_tp6_dist < extreme_tp5_dist
keys.push(line.new(bar_index , tp6, bar_index, tp6, color = lvlCol, width = 2))
printedtp6 := 1
if printedtp7 == 0 and extreme_tp7_dist < extreme_tp6_dist
keys.push(line.new(bar_index , tp7, bar_index, tp7, color = lvlCol, width = 2))
printedtp7 := 1
if keys.size() > 0
aSZ = keys.size()
for i = aSZ - 1 to 0
keys.get(i).set_x2(bar_index)
// Alert when SuperTrend changes direction
alertcondition(ta.cross(trendDirection, 0), title="SuperTrend Direction Change", message="SuperTrend has changed direction")
// Alert when each TP line is drawn
alertcondition(printedtp1 == 1, title="TP1 Line Drawn", message="TP1 line has been drawn")
alertcondition(printedtp2 == 1, title="TP2 Line Drawn", message="TP2 line has been drawn")
alertcondition(printedtp3 == 1, title="TP3 Line Drawn", message="TP3 line has been drawn")
alertcondition(printedtp4 == 1, title="TP4 Line Drawn", message="TP4 line has been drawn")
alertcondition(printedtp5 == 1, title="TP5 Line Drawn", message="TP5 line has been drawn")
alertcondition(printedtp6 == 1, title="TP6 Line Drawn", message="TP6 line has been drawn")
alertcondition(printedtp7 == 1, title="TP7 Line Drawn", message="TP7 line has been drawn")
// Alert for crossing under RSI
alertcondition(tp, title="Take-Profit Condition", message="Take-Profit condition met")
Trade phái sinh VN30F1M khung 1DSử dụng cho khung daily
Nguyên tắc hoạt động dựa trên các đường trung bình động
Hoạt động tốt trong thị trường có xu hướng
Hoạt động không tối khi thị trường không rõ xu hướng
Swing LevelsThis setup helps you visualize key support and resistance levels on your TradingView charts, dynamically updating based on the stock's price movements. The use of colors (green and red) helps quickly identify whether the stock is above or below these levels. Hope this helps!
Intraday trading signalsHMA buy/sell Logic:
This code uses HMA and dynamically assigns value as either bullish or bearish based on where the closing price stands relative to signalHigh and signalLow. Trade buy/sell is determined by value, and crossover signals (Long and Short) are generated when the close price crosses Exit.
Ultimate Moving average:
This script plots a trend-colored Ultimate Moving Average (ULMA) line based on Arnaud Legoux Moving Average. The line’s visibility, length and trend color are customizable. Yellow color indicates an upward trend, while red indicates a downward trend. The indicator provides a smooth moving average that aims to track trends with minimal lag.
Hodrick-Prescott Filter (YavuzAkbay)The Hodrick-Prescott Filter indicator in Pine Script™ brings an established method from economics into trading by applying the Hodrick-Prescott (HP) filter for trend-cyclical decomposition. This filter is commonly used in economics to separate the trend and cyclical components of time series data. Here, it’s adapted into Pine Script to help traders differentiate long-term trends from short-term price fluctuations, making it easier to interpret market movements.
What This Script Does
Unlike moving averages, which simply smooth the data to approximate a trend, the HP Filter is designed to break down the price into two components: the trend (long-term) and the cycle (short-term fluctuations). While no smoothing method is lag-free, the HP Filter can often react faster to shifts in the trend compared to long moving averages, particularly with an optimized λ value. Moving averages, especially longer ones, tend to lag more as they rely directly on past prices, whereas the HP Filter’s recursive calculation adjusts the trend to minimize this delay.
How It Works
The Hodrick-Prescott filter uses a smoothness parameter (λ) to adjust the degree of smoothness applied to the trend component. The higher the value of λ, the smoother the trend component, which means it will respond less to short-term fluctuations in price. This can be set by the user with the "Smoothness Parameter (λ)" input.
How to Use This Indicator
Trend Identification: The line shows the smoothed trend line, which can help in determining the general direction of the price. If the trend line is pointing upwards, it suggests a bullish trend, and if it's pointing downwards, it indicates a bearish trend.
Cycle Component for Overbought/Oversold Signals: The Hodrick-Prescott Cycle Component indicator can be useful to spot potential reversals or short-term corrections. Large deviations from the zero line in the cycle component may indicate overbought (when cycle is significantly positive) or oversold (when cycle is significantly negative) conditions.
Adjusting λ for Different Market Conditions: Users can adjust the λ parameter based on the type of asset and the desired sensitivity. Lower values of λ make the trend component more responsive to price changes, which is suitable for high-volatility assets or for traders focusing on shorter-term trends. Higher values smooth the trend more, which can be beneficial for long-term trend-following in stable markets or when analyzing weekly/monthly timeframes.
Practical Tips for Traders
Trend Following: Use the trend component to follow the direction of the market. If the trend component is steadily increasing, you may want to look for long opportunities, and vice versa for short opportunities.
Divergence Detection: If the cycle component shows a divergence from price (e.g., price makes a new high, but the cycle component does not), this can be an early warning of a potential reversal.
Sensitivity Testing: Experiment with different λ values to find a balance between smoothness and responsiveness that suits the asset and timeframe you’re analyzing.
Mathematical Background of the HP Filter
The Hodrick-Prescott filter separates a time series 𝑦𝑡 (in this case, price data) into a trend component 𝜏𝑡 and a cyclical component 𝑐𝑡 using this equation: yt=τt+ct.
The goal of the HP filter is to minimize the following objective function:
t=1∑T(y_t−τ_t)^2+λt=2∑T−1((τ_(t+1)−τ_t)−(τ_t−τ_(t−1)))^2
Pine Script Implementation of the HP Filter
In my Pine Script implementation, the HP filter is approximated using a recursive formula for efficiency:
τ_t=(y_t+(λ−1)*τ_(t−1))/λ
Hodrick-Prescott Cycle Component (YavuzAkbay)The Hodrick-Prescott Cycle Component indicator in Pine Script™ is an advanced tool that helps traders isolate and analyze the cyclical deviations in asset prices from their underlying trend. This script calculates the cycle component of the price series using the Hodrick-Prescott (HP) filter, allowing traders to observe and interpret the short-term price movements around the long-term trend. By providing two views—Percentage and Price Difference—this indicator gives flexibility in how these cyclical movements are visualized and interpreted.
What This Script Does
This indicator focuses exclusively on the cycle component of the price, which is the deviation of the current price from the long-term trend calculated by the HP filter. This deviation (or "cycle") is what traders analyze for mean-reversion opportunities and overbought/oversold conditions. The script allows users to see this deviation in two ways:
Percentage Difference: Shows the deviation as a percentage of the trend, giving a normalized view of the price’s distance from its trend component.
Price Difference: Shows the deviation in absolute price terms, reflecting how many price units the price is above or below the trend.
How It Works
Trend Component Calculation with the HP Filter: Using the HP filter, the script isolates the trend component of the price. The smoothness of this trend is controlled by the smoothness parameter (λ), which can be adjusted by the user. A higher λ value results in a smoother trend, while a lower λ value makes it more responsive to short-term changes.
Cycle Component Calculation: Percentage Deviation (cycle_pct) calculated as the difference between the current price and the trend, divided by the trend, and then multiplied by 100. This metric shows how far the price deviates from the trend in relative terms. Price Difference (cycle_price) simply the difference between the current price and the trend component, displaying the deviation in absolute price units.
Conditional Plotting: The user can choose to view the cycle component as either a percentage or a price difference by selecting the Display Mode input. The indicator will plot the chosen mode in a separate pane, helping traders focus on the preferred measure of deviation.
How to Use This Indicator
Identify Overbought/Oversold Conditions: When the cycle component deviates significantly from the zero line (shown with a dashed horizontal line), it may indicate overbought or oversold conditions. For instance, a high positive cycle component suggests the price may be overbought relative to the trend, while a large negative cycle suggests potential oversold conditions.
Mean-Reversion Strategy: In mean-reverting markets, traders can use this indicator to spot potential reversal points. For example, if the cycle component shows an extreme deviation from zero, it could signal that the price is likely to revert to the trend. This can help traders with entry and exit points when the asset is expected to correct back toward its trend.
Trend Strength and Cycle Analysis: By comparing the magnitude and duration of deviations, traders can gauge the strength of cycles and assess if a new trend might be forming. If the cycle component remains consistently positive or negative, it may indicate a persistent market bias, even as prices fluctuate around the trend.
Percentage vs. Price Difference Views: Use the Percentage Difference mode to standardize deviations and compare across assets or different timeframes. This is especially helpful when analyzing assets with varying price levels. Use the Price Difference mode when an absolute deviation (price units) is more intuitive for spotting overbought/oversold levels based on the asset’s actual price.
Using with Hodrick-Prescott: You can also use Hodrick-Prescott, another indicator that I have adapted to the Tradingview platform, to see the trend on the chart, and you can also use this indicator to see how far the price is deviating from the trend. This gives you a multifaceted perspective on your trades.
Practical Tips for Traders
Set the Smoothness Parameter (λ): Adjust the λ parameter to match your trading timeframe and asset characteristics. Lower values make the trend more sensitive, which might suit short-term trading, while higher values smooth out the trend for long-term analysis.
Cycle Component as Confirmation: Combine this indicator with other momentum or trend indicators for confirmation of overbought/oversold signals. For example, use the cycle component with RSI or MACD to validate the likelihood of mean-reversion.
Observe Divergences: Divergences between price movements and the cycle component can indicate potential reversals. If the price hits a new high, but the cycle component shows a smaller deviation than previous highs, it could signal a weakening trend.
