Arrow-SimplyTrade vol1.5-FinalTitle: Arrow-SimplyTrade vol1.5-Final
Description:
This advanced trading indicator is designed to assist traders in analyzing market trends and identifying optimal entry signals. It combines several popular technical analysis tools and strategies, including EMA (Exponential Moving Average), MA (Simple Moving Averages), Bollinger Bands, and candlestick patterns. This indicator provides both trend-following and counter-trend signals, making it suitable for various trading styles, such as scalping and swing trading.
Main Features:
EMA (Exponential Moving Average):
EMA200 is the main trend line that helps determine the overall market direction. When the price is above EMA200, the trend is considered bullish, and when the price is below EMA200, the trend is considered bearish.
It helps filter out signals that go against the prevailing market trend.
Simple Moving Averages (MA5 and MA15):
This indicator uses two Simple Moving Averages: MA5 (Fast) and MA15 (Slow). Their crossovers create buy or sell signals:
Buy Signal: When MA5 crosses above MA15, signaling a potential upward trend.
Sell Signal: When MA5 crosses below MA15, signaling a potential downward trend.
Bollinger Bands:
Bollinger Bands measure market volatility and can identify periods of overbought or oversold conditions. The Upper and Lower Bands help detect potential breakout points, while the Middle Line (Basis) serves as dynamic support or resistance.
This tool is particularly useful for identifying volatile conditions and potential reversals.
Arrows:
The indicator plots arrows on the chart to signal entry opportunities:
Green Arrows signal buy opportunities (when MA5 crosses above MA15 and price is above EMA200).
Red Arrows signal sell opportunities (when MA5 crosses below MA15 and price is below EMA200).
Opposite Arrows: Optionally, the indicator can also display arrows for counter-trend signals, triggered by MA5 and MA15 crossovers, regardless of the price's position relative to EMA200.
Candlestick Patterns:
The indicator detects popular candlestick patterns such as Bullish Engulfing, Bearish Engulfing, Hammer, and Doji.
These patterns are important for confirming entry points or anticipating trend reversals.
How to Use:
EMA200: The main trend line. If the price is above EMA200, consider long positions. If the price is below EMA200, consider short positions.
MA5 and MA15: Short-term trend indicators. The crossover of these averages generates buy or sell signals.
Bollinger Bands: Use these bands to spot overbought/oversold conditions. Breakouts from the bands may signal potential entry points.
Arrows: Green arrows represent buy signals, and red arrows represent sell signals. Opposite direction arrows can be used for counter-trend strategies.
Candlestick Patterns: Patterns like Bullish Engulfing or Doji can help confirm the signals.
Customizable Settings:
Fully customizable colors, line styles, and display settings for EMA, MAs, Bollinger Bands, and arrows.
The Candlestick Patterns feature can be toggled on or off based on user preference.
Important Notes:
This indicator is intended to be used in conjunction with other analysis tools.
Past performance does not guarantee future results.
Polish:
Tytuł: Arrow-SimplyTrade vol1.5-Final
Opis:
Ten zaawansowany wskaźnik handlowy jest zaprojektowany, aby pomóc traderom w analizie trendów rynkowych oraz identyfikowaniu optymalnych sygnałów wejścia. Łączy w sobie kilka popularnych narzędzi analizy technicznej i strategii, w tym EMA (Wykładnicza Średnia Ruchoma), MA (Prosta Średnia Ruchoma), Bollinger Bands oraz formacje świecowe. Wskaźnik generuje zarówno sygnały podążające za trendem, jak i przeciwnym trendowi, co sprawia, że jest odpowiedni do różnych stylów handlu, takich jak scalping oraz swing trading.
Główne Funkcje:
EMA (Wykładnicza Średnia Ruchoma):
EMA200 to główna linia trendu, która pomaga określić ogólny kierunek rynku. Gdy cena znajduje się powyżej EMA200, trend jest uznawany za wzrostowy, a gdy poniżej EMA200, za spadkowy.
Pomaga to filtrować sygnały, które są niezgodne z głównym trendem rynkowym.
Proste Średnie Ruchome (MA5 i MA15):
Wskaźnik używa dwóch Prostych Średnich Ruchomych: MA5 (szybka) oraz MA15 (wolna). Ich przecięcia generują sygnały kupna lub sprzedaży:
Sygnał Kupna: Kiedy MA5 przecina MA15 od dołu, sygnalizując potencjalny wzrost.
Sygnał Sprzedaży: Kiedy MA5 przecina MA15 od góry, sygnalizując potencjalny spadek.
Bollinger Bands:
Bollinger Bands mierzą zmienność rynku i mogą pomóc w identyfikowaniu okresów wykupienia lub wyprzedania rynku. Górna i dolna linia pomagają wykrywać punkty wybicia, a Środkowa Linia (Basis) działa jako dynamiczny poziom wsparcia lub oporu.
Narzędzie to jest szczególnie przydatne w wykrywaniu warunków zmienności i potencjalnych odwróceń trendu.
Strzałki:
Wskaźnik wyświetla strzałki na wykresie, które wskazują sygnały kupna i sprzedaży:
Zielona strzałka wskazuje sygnał kupna (gdy MA5 przecina MA15 i cena jest powyżej EMA200).
Czerwona strzałka wskazuje sygnał sprzedaży (gdy MA5 przecina MA15 i cena jest poniżej EMA200).
Strzałki w przeciwnym kierunku: Opcjonalna funkcja, która pokazuje strzałki w przeciwnym kierunku, uruchamiane przez przecięcia MA5 i MA15, niezależnie od pozycji ceny względem EMA200.
Formacje Świecowe:
Wskaźnik wykrywa popularne formacje świecowe, takie jak Bullish Engulfing, Bearish Engulfing, Hammer oraz Doji.
Formacje te pomagają traderom potwierdzić punkty wejścia i przewidzieć możliwe odwrócenia trendu.
Jak Używać:
EMA200: Główna linia trendu. Jeśli cena jest powyżej EMA200, rozważaj pozycje długie. Jeśli cena jest poniżej EMA200, rozważaj pozycje krótkie.
MA5 i MA15: Śledzą krótkoterminowe zmiany trendu. Przecięcia tych średnich generują sygnały kupna lub sprzedaży.
Bollinger Bands: Używaj tych pasm do wykrywania wykupionych lub wyprzedanych warunków. Wybicia z pasm mogą wskazywać potencjalne punkty wejścia.
Strzałki: Zielona strzałka wskazuje sygnał kupna, a czerwona strzałka sygnał sprzedaży. Strzałki w przeciwnym kierunku mogą być używane do strategii przeciwtrendowych.
Formacje Świecowe: Formacje takie jak Bullish Engulfing czy Doji mogą pomóc w potwierdzaniu sygnałów.
Ustawienia Personalizacji:
W pełni personalizowalne kolory, style linii i ustawienia wyświetlania dla EMA, MAs, Bollinger Bands oraz strzałek.
Funkcja Formacji Świecowych może być włączana lub wyłączana według preferencji użytkownika.
Ważne Uwagi:
Ten wskaźnik powinien być używany w połączeniu z innymi narzędziami analizy rynku.
Wyniki z przeszłości nie gwarantują wyników w przyszłości.
Cari dalam skrip untuk "Exponential Moving Average"
Golden & Death Cross with Re-Activation [By Oberlunar]🎄 Merry Christmas to All Traders! 🎄
Let me introduce you to a practical and customizable classic tool: the Golden & Death Cross with Re-Activation. This script is designed to help you navigate the markets with precision and adaptability.
Why Is This Script Important?
1. Customizable Moving Averages
You can choose from SMA, EMA, WMA, HMA, or RMA for both moving averages. This flexibility allows you to tailor the strategy to fit different markets and trading styles.
2. Smart Signal Handling
The script generates Golden Cross (LONG) and Death Cross (SHORT) signals while deactivating them automatically when the moving averages start to converge, avoiding unnecessary noise.
3. Reactivation Based on Distance Threshold
With the treshold parameter, signals are reactivated only when the moving averages move apart sufficiently, ensuring that the signals remain meaningful and not just random market noise.
What Are These Moving Averages?
SMA (Simple Moving Average),
EMA (Exponential Moving Average),
WMA (Weighted Moving Average),
HMA (Hull Moving Average),
RMA (Relative Moving Average)
Community Input
We invite you to test this script on various markets (forex, stocks, crypto) and share your insights:
Which moving average combination works best for EUR/USD?
How about BTC/USD?
Does the treshold make a noticeable difference?
Let us know in the comments!
Example Settings
MA 1 Type: HMA, Length: 21
MA 2 Type: HMA, Length: 200
Reactivation Threshold: 0.5
Experiment with it, and let us know your findings.
Wishing you a calm holiday season and a profitable new year ahead! 🎁
🎄 Merry Christmas and Happy Trading! 🎄
[blackcat] L1 BS Line of Defense █ OVERVIEW
The Pine Script provided is an advanced technical indicator designed to generate reliable buy and sell signals by integrating momentum, moving averages, and price level analyses. It employs a custom weighted moving average (WMA) and exponential moving averages (EMAs) to compute key signals known as the "Buy/Sell Signal" and the "Short Line." These signals aim to pinpoint optimal entry and exit points for trades by evaluating their relationship with current market dynamics.
█ FEATURES
Key Components:
• Custom Weighted Moving Average ( WMA ): Provides enhanced flexibility compared to traditional moving averages.
• Exponential Moving Averages ( EMA ): Smooths the defense line and its short-term counterpart to filter out market noise.
• Momentum Indicators: Includes both short-term and long-term momentum adjusted via custom WMA and EMAs.
• Conditional Signal Generation: Signals are triggered based on precise crossovers and price conditions.
Logical Framework:
1 — Input Parameters:
No explicit user-defined inputs; defaults are used for internal calculations.
2 — Custom Functions:
• custom_wma : Calculates a custom WMA.
• calculate_buy_sell_signals : Generates buy and sell signals.
3 — Calculations:
• Momentum and Range Analysis over 9, 34, and 60-bar periods.
• Application of custom WMA and EMAs to smooth and refine data.
• Derivation of the "defense line" and "short_ema_defense."
4 — Plotting:
• Main signal lines ("Buy/Sell Signal" and "Short Line") are visualized.
• A horizontal zero line serves as a reference point.
█ HOW TO USE
To utilize this script effectively:
1 — Add the script to your TradingView chart.
2 — Observe the "Buy/Sell Signal" and "Short Line" relative to the zero line and each other.
3 — Look for crossovers and divergence patterns to identify potential trade opportunities.
4 — Combine the signals with additional technical indicators or fundamental analysis for better accuracy.
█ LIMITATIONS
While the script provides valuable insights, users should consider the following limitations:
• Default settings may not suit all markets or instruments; customization might be necessary.
• False signals can occur during volatile or ranging markets.
• Backtesting and optimization are recommended before live trading.
█ NOTES
For further enhancement and personalization:
• Introduce adjustable input parameters for WMA and EMA lengths and weights.
• Extend the script into a full-fledged trading strategy with entry and exit rules.
• Apply the script across multiple timeframes for comprehensive analysis.
• Incorporate risk management practices such as stop-loss and take-profit levels.
• Explore related Pine Script functions like security() for multi-timeframe analysis and [pine>alertcondition() for automated alerts.
Understanding core concepts like momentum, moving averages, and crossovers will aid in developing similar indicators or refining existing ones.
MultiLayer Acceleration/Deceleration Strategy [Skyrexio]Overview
MultiLayer Acceleration/Deceleration Strategy leverages the combination of Acceleration/Deceleration Indicator(AC), Williams Alligator, Williams Fractals and Exponential Moving Average (EMA) to obtain the high probability long setups. Moreover, strategy uses multi trades system, adding funds to long position if it considered that current trend has likely became stronger. Acceleration/Deceleration Indicator is used for creating signals, while Alligator and Fractal are used in conjunction as an approximation of short-term trend to filter them. At the same time EMA (default EMA's period = 100) is used as high probability long-term trend filter to open long trades only if it considers current price action as an uptrend. More information in "Methodology" and "Justification of Methodology" paragraphs. The strategy opens only long trades.
Unique Features
No fixed stop-loss and take profit: Instead of fixed stop-loss level strategy utilizes technical condition obtained by Fractals and Alligator to identify when current uptrend is likely to be over (more information in "Methodology" and "Justification of Methodology" paragraphs)
Configurable Trading Periods: Users can tailor the strategy to specific market windows, adapting to different market conditions.
Multilayer trades opening system: strategy uses only 10% of capital in every trade and open up to 5 trades at the same time if script consider current trend as strong one.
Short and long term trend trade filters: strategy uses EMA as high probability long-term trend filter and Alligator and Fractal combination as a short-term one.
Methodology
The strategy opens long trade when the following price met the conditions:
1. Price closed above EMA (by default, period = 100). Crossover is not obligatory.
2. Combination of Alligator and Williams Fractals shall consider current trend as an upward (all details in "Justification of Methodology" paragraph)
3. Acceleration/Deceleration shall create one of two types of long signals (all details in "Justification of Methodology" paragraph). Buy stop order is placed one tick above the candle's high of last created long signal.
4. If price reaches the order price, long position is opened with 10% of capital.
5. If currently we have opened position and price creates and hit the order price of another one long signal, another one long position will be added to the previous with another one 10% of capital. Strategy allows to open up to 5 long trades simultaneously.
6. If combination of Alligator and Williams Fractals shall consider current trend has been changed from up to downtrend, all long trades will be closed, no matter how many trades has been opened.
Script also has additional visuals. If second long trade has been opened simultaneously the Alligator's teeth line is plotted with the green color. Also for every trade in a row from 2 to 5 the label "Buy More" is also plotted just below the teeth line. With every next simultaneously opened trade the green color of the space between teeth and price became less transparent.
Strategy settings
In the inputs window user can setup strategy setting: EMA Length (by default = 100, period of EMA, used for long-term trend filtering EMA calculation). User can choose the optimal parameters during backtesting on certain price chart.
Justification of Methodology
Let's explore the key concepts of this strategy and understand how they work together. We'll begin with the simplest: the EMA.
The Exponential Moving Average (EMA) is a type of moving average that assigns greater weight to recent price data, making it more responsive to current market changes compared to the Simple Moving Average (SMA). This tool is widely used in technical analysis to identify trends and generate buy or sell signals. The EMA is calculated as follows:
1.Calculate the Smoothing Multiplier:
Multiplier = 2 / (n + 1), Where n is the number of periods.
2. EMA Calculation
EMA = (Current Price) × Multiplier + (Previous EMA) × (1 − Multiplier)
In this strategy, the EMA acts as a long-term trend filter. For instance, long trades are considered only when the price closes above the EMA (default: 100-period). This increases the likelihood of entering trades aligned with the prevailing trend.
Next, let’s discuss the short-term trend filter, which combines the Williams Alligator and Williams Fractals. Williams Alligator
Developed by Bill Williams, the Alligator is a technical indicator that identifies trends and potential market reversals. It consists of three smoothed moving averages:
Jaw (Blue Line): The slowest of the three, based on a 13-period smoothed moving average shifted 8 bars ahead.
Teeth (Red Line): The medium-speed line, derived from an 8-period smoothed moving average shifted 5 bars forward.
Lips (Green Line): The fastest line, calculated using a 5-period smoothed moving average shifted 3 bars forward.
When the lines diverge and align in order, the "Alligator" is "awake," signaling a strong trend. When the lines overlap or intertwine, the "Alligator" is "asleep," indicating a range-bound or sideways market. This indicator helps traders determine when to enter or avoid trades.
Fractals, another tool by Bill Williams, help identify potential reversal points on a price chart. A fractal forms over at least five consecutive bars, with the middle bar showing either:
Up Fractal: Occurs when the middle bar has a higher high than the two preceding and two following bars, suggesting a potential downward reversal.
Down Fractal: Happens when the middle bar shows a lower low than the surrounding two bars, hinting at a possible upward reversal.
Traders often use fractals alongside other indicators to confirm trends or reversals, enhancing decision-making accuracy.
How do these tools work together in this strategy? Let’s consider an example of an uptrend.
When the price breaks above an up fractal, it signals a potential bullish trend. This occurs because the up fractal represents a shift in market behavior, where a temporary high was formed due to selling pressure. If the price revisits this level and breaks through, it suggests the market sentiment has turned bullish.
The breakout must occur above the Alligator’s teeth line to confirm the trend. A breakout below the teeth is considered invalid, and the downtrend might still persist. Conversely, in a downtrend, the same logic applies with down fractals.
In this strategy if the most recent up fractal breakout occurs above the Alligator's teeth and follows the last down fractal breakout below the teeth, the algorithm identifies an uptrend. Long trades can be opened during this phase if a signal aligns. If the price breaks a down fractal below the teeth line during an uptrend, the strategy assumes the uptrend has ended and closes all open long trades.
By combining the EMA as a long-term trend filter with the Alligator and fractals as short-term filters, this approach increases the likelihood of opening profitable trades while staying aligned with market dynamics.
Now let's talk about Acceleration/Deceleration signals. AC indicator is calculated using the Awesome Oscillator, so let's first of all briefly explain what is Awesome Oscillator and how it can be calculated. The Awesome Oscillator (AO), developed by Bill Williams, is a momentum indicator designed to measure market momentum by contrasting recent price movements with a longer-term historical perspective. It helps traders detect potential trend reversals and assess the strength of ongoing trends.
The formula for AO is as follows:
AO = SMA5(Median Price) − SMA34(Median Price)
where:
Median Price = (High + Low) / 2
SMA5 = 5-period Simple Moving Average of the Median Price
SMA 34 = 34-period Simple Moving Average of the Median Price
The Acceleration/Deceleration (AC) Indicator, introduced by Bill Williams, measures the rate of change in market momentum. It highlights shifts in the driving force of price movements and helps traders spot early signs of trend changes. The AC Indicator is particularly useful for identifying whether the current momentum is accelerating or decelerating, which can indicate potential reversals or continuations. For AC calculation we shall use the AO calculated above is the following formula:
AC = AO − SMA5(AO), where SMA5(AO)is the 5-period Simple Moving Average of the Awesome Oscillator
When the AC is above the zero line and rising, it suggests accelerating upward momentum.
When the AC is below the zero line and falling, it indicates accelerating downward momentum.
When the AC is below zero line and rising it suggests the decelerating the downtrend momentum. When AC is above the zero line and falling, it suggests the decelerating the uptrend momentum.
Now we can explain which AC signal types are used in this strategy. The first type of long signal is when AC value is below zero line. In this cases we need to see three rising bars on the histogram in a row after the falling one. The second type of signals occurs above the zero line. There we need only two rising AC bars in a row after the falling one to create the signal. The signal bar is the last green bar in this sequence. The strategy places the buy stop order one tick above the candle's high, which corresponds to the signal bar on AC indicator.
After that we can have the following scenarios:
Price hit the order on the next candle in this case strategy opened long with this price.
Price doesn't hit the order price, the next candle set lower high. If current AC bar is increasing buy stop order changes by the script to the high of this new bar plus one tick. This procedure repeats until price finally hit buy order or current AC bar become decreasing. In the second case buy order cancelled and strategy wait for the next AC signal.
If long trades are initiated, the strategy continues utilizing subsequent signals until the total number of trades reaches a maximum of 5. All open trades are closed when the trend shifts to a downtrend, as determined by the combination of the Alligator and Fractals described earlier.
Why we use AC signals? If currently strategy algorithm considers the high probability of the short-term uptrend with the Alligator and Fractals combination pointed out above and the long-term trend is also suggested by the EMA filter as bullish. Rising AC bars after period of falling AC bars indicates the high probability of local pull back end and there is a high chance to open long trade in the direction of the most likely main uptrend. The numbers of rising bars are different for the different AC values (below or above zero line). This is needed because if AC below zero line the local downtrend is likely to be stronger and needs more rising bars to confirm that it has been changed than if AC is above zero.
Why strategy use only 10% per signal? Sometimes we can see the false signals which appears on sideways. Not risking that much script use only 10% per signal. If the first long trade has been open and price continue going up and our trend approximation by Alligator and Fractals is uptrend, strategy add another one 10% of capital to every next AC signal while number of active trades no more than 5. This capital allocation allows to take part in long trades when current uptrend is likely to be strong and use only 10% of capital when there is a high probability of sideways.
Backtest Results
Operating window: Date range of backtests is 2023.01.01 - 2024.11.01. It is chosen to let the strategy to close all opened positions.
Commission and Slippage: Includes a standard Binance commission of 0.1% and accounts for possible slippage over 5 ticks.
Initial capital: 10000 USDT
Percent of capital used in every trade: 10%
Maximum Single Position Loss: -5.15%
Maximum Single Profit: +24.57%
Net Profit: +2108.85 USDT (+21.09%)
Total Trades: 111 (36.94% win rate)
Profit Factor: 2.391
Maximum Accumulated Loss: 367.61 USDT (-2.97%)
Average Profit per Trade: 19.00 USDT (+1.78%)
Average Trade Duration: 75 hours
How to Use
Add the script to favorites for easy access.
Apply to the desired timeframe and chart (optimal performance observed on 3h BTC/USDT).
Configure settings using the dropdown choice list in the built-in menu.
Set up alerts to automate strategy positions through web hook with the text: {{strategy.order.alert_message}}
Disclaimer:
Educational and informational tool reflecting Skyrex commitment to informed trading. Past performance does not guarantee future results. Test strategies in a simulated environment before live implementation
These results are obtained with realistic parameters representing trading conditions observed at major exchanges such as Binance and with realistic trading portfolio usage parameters.
EMA Volatility Channel [QuantAlgo]EMA Volatility Channel 🌊📈
The EMA Volatility Channel by QuantAlgo is an advanced technical indicator designed to capture price volatility and trend dynamics through adaptive channels based on exponential moving averages. This sophisticated system combines EMA-based trend analysis with dynamic volatility-adjusted bands to help traders and investors identify trend direction, potential reversals, and market volatility conditions. By evaluating both price momentum and volatility together, this tool enables users to make informed trading decisions while adapting to changing market conditions.
💫 Dynamic Channel Architecture
The EMA Volatility Channel provides a unique framework for assessing market trends through a blend of exponential moving averages and volatility-based channel calculations. Unlike traditional channel indicators that use fixed-width bands, this system incorporates dynamic volatility measurements to adjust channel width automatically, helping users determine whether price movements are significant relative to current market conditions. By combining smooth EMA trends with adaptive volatility bands, it evaluates both directional movement and market volatility, while the smoothing parameters ensure stable yet responsive channel adjustments. This adaptive approach allows users to identify trending conditions while remaining aware of volatility expansions and contractions, enhancing both trend-following and reversal strategies.
📊 Indicator Components & Mechanics
The EMA Volatility Channel is composed of several technical components that create a dynamic channel system:
EMA Midline: Calculates a smoothed exponential moving average that serves as the channel's centerline, providing a clear reference for trend direction.
Volatility Measurement: Computes average price movement to determine dynamic channel width, adapting to changing market conditions automatically.
Smooth Band Calculation: Applies additional smoothing to the channel bands, reducing noise while maintaining responsiveness to significant price movements.
📈 Key Indicators and Features
The EMA Volatility Channel combines various technical tools to deliver a comprehensive analysis of market conditions.
The indicator utilizes exponential moving averages with customizable length and smoothing parameters to adapt to different trading styles. Volatility calculations are applied to determine channel width, providing context-aware boundaries for price movement. The trend detection component evaluates price action relative to the channel bands, helping validate trends and identify potential reversals.
The indicator incorporates multi-layered visualization with color-coded channels and bars to signal both trend direction and market position. These adaptive visual cues, combined with programmable alerts for channel breakouts, help traders and investors track both trend changes and volatility conditions, supporting both trend-following and mean-reversion strategies.
⚡️ Practical Applications and Examples
✅ Add the Indicator: Add the indicator to your TradingView chart by clicking on the star icon to add it to your favorites ⭐️
👀 Monitor Channel Position: Watch the price position relative to the channel bands to identify trend direction and potential reversals. When price moves outside the channel, consider potential trend changes or extreme conditions.
🔔 Set Alerts: Configure alerts for channel breakouts and trend changes, ensuring you can act on significant technical developments promptly.
🌟 Summary and Tips
The EMA Volatility Channel by QuantAlgo is a versatile technical tool, designed to support both trend following and volatility analysis across different market environments. By combining smooth EMA trends with dynamic volatility-based channels, it helps traders and investors identify significant price movements while measuring market volatility, providing reliable technical signals. The tool's adaptability across timeframes makes it suitable for both trend-following and reversal strategies, allowing users to capture opportunities while maintaining awareness of changing market conditions.
Moving Average with Buy/Sell SignalsBINANCE:BTCUSD
Pine Script Brief: "44 Moving Average with Buy/Sell Signals"
This Pine Script is designed to generate buy and sell signals based on the interaction of the price with the 44-period Simple Moving Average (SMA). It also considers the closing behavior of the last five candles to further refine the conditions for generating signals. The script is intended for use in technical analysis for trading strategies on platforms like TradingView.
Features:
44-Period Simple Moving Average (SMA):
The script calculates and plots the 44-period SMA of the closing price on the chart, providing a trend-following indicator.
The SMA is used as a key level to determine when price action is "touching" or interacting with the moving average.
Buy and Sell Signal Logic:
Buy Signal:
The candle is green (close > open).
The candle's high and low are around the 44 SMA, indicating the candle is "touching" or near the moving average.
At least 2 of the last 5 candles must have closed above the 44 SMA.
The 44 SMA is positioned below the midpoint of the current candle.
Sell Signal:
The candle is red (close < open).
The candle's high and low are around the 44 SMA.
At least 2 of the last 5 candles must have closed below the 44 SMA.
The 44 SMA is positioned above the midpoint of the current candle.
Label Plotting:
The script uses the plotSignal function to plot buy and sell labels directly on the chart. The labels are plotted at the low of a green candle (for buy signals) and the high of a red candle (for sell signals).
Labels are color-coded for quick identification: green for buy and red for sell.
EMA for Smoothing (Optional):
An optional Exponential Moving Average (EMA) is plotted for additional trend smoothing, allowing users to visualize another moving average for possible trend-following strategies.
The length of the EMA is customizable, and it is plotted on the chart alongside the 44 SMA.
Alert Conditions:
Alerts can be set up for both buy and sell signals, notifying the user when these conditions are met. The alerts are triggered whenever the script detects a valid buy or sell signal.
Customizable Inputs:
The script allows customization of the following:
Smoothing Length: For the optional EMA line.
Tolerance: For adjusting the proximity check (candle touching the 44 SMA).
Styling: The color and text of the buy and sell labels can be customized.
Usage:
This script can be used by traders who want to identify possible entry and exit points based on price interaction with the 44-period moving average, combined with the behavior of previous candles. It is suitable for trend-following strategies and can be used in conjunction with other indicators to refine trading decisions.
Key Benefits:
Provides visual signals (buy/sell) directly on the chart.
Considers both immediate price action and historical trends (previous candles).
Offers customization for moving averages and labels.
Alerts can be set for automated notifications.
This Pine Script helps traders make informed decisions by combining the reliability of moving averages with price action and historical candle behavior, enhancing trading strategies based on trend-following principles.
simple swing indicator-KTRNSE:NIFTY
1. Pivot High/Low as Lines:
Purpose: Identifies local peaks (pivot highs) and troughs (pivot lows) in price and draws horizontal lines at these levels.
How it Works:
A pivot high occurs when the price is higher than the surrounding bars (based on the pivotLength parameter).
A pivot low occurs when the price is lower than the surrounding bars.
These pivots are drawn as horizontal lines at the price level of the pivot.
Visualization:
Pivot High: A red horizontal line is drawn at the price level of the pivot high.
Pivot Low: A green horizontal line is drawn at the price level of the pivot low.
Example:
Imagine the price is trending up, and at some point, it forms a peak. The script identifies this peak as a pivot high and draws a red line at the price of that peak. Similarly, if the price forms a trough, the script will draw a green line at the low point.
2. Moving Averages (20-day and 50-day):
Purpose: Plots the 20-day and 50-day simple moving averages (SMA) on the chart.
How it Works:
The 20-day SMA smooths the closing price over the last 20 days.
The 50-day SMA smooths the closing price over the last 50 days.
These lines provide an overview of short-term and long-term price trends.
Visualization:
20-day SMA: A blue line showing the 20-day moving average.
50-day SMA: An orange line showing the 50-day moving average.
Example:
When the price is above both moving averages, it indicates an uptrend. If the price crosses below these averages, it might signal a downtrend.
3. Supertrend:
Purpose: The Supertrend is an indicator based on the Average True Range (ATR) and is used to track the market trend.
How it Works:
When the market is in an uptrend, the Supertrend line will be green.
When the market is in a downtrend, the Supertrend line will be red.
Visualization:
Uptrend: The Supertrend line will be plotted in green.
Downtrend: The Supertrend line will be plotted in red.
Example:
If the price is above the Supertrend, the market is considered to be in an uptrend, and if the price is below the Supertrend, the market is in a downtrend.
4. Momentum (Rate of Change):
Purpose: Measures the rate at which the price changes over a set period, showing if the momentum is positive or negative.
How it Works:
The Rate of Change (ROC) measures how much the price has changed over a certain number of periods (e.g., 14).
Positive ROC indicates upward momentum, and negative ROC indicates downward momentum.
Visualization:
Positive ROC: A purple line is plotted above the zero line.
Negative ROC: A purple line is plotted below the zero line.
Example:
If the ROC line is above zero, it means the price is increasing, suggesting bullish momentum. If the ROC is below zero, it indicates bearish momentum.
5. Volume:
Purpose: Displays the volume of traded assets, giving insight into the strength of price movements.
How it Works:
The script will color the volume bars based on whether the price closed higher or lower than the previous bar.
Green bars indicate bullish volume (closing price higher than the previous bar), and red bars indicate bearish volume (closing price lower than the previous bar).
Visualization:
Bullish Volume: Green volume bars when the price closes higher.
Bearish Volume: Red volume bars when the price closes lower.
Example:
If you see a green volume bar, it suggests that the market is participating in an uptrend, and the price has closed higher than the previous period. Red bars indicate a downtrend or selling pressure.
6. MACD (Moving Average Convergence Divergence):
Purpose: The MACD is a trend-following momentum indicator that shows the relationship between two moving averages of the price.
How it Works:
The MACD Line is the difference between the 12-period EMA (Exponential Moving Average) and the 26-period EMA.
The Signal Line is the 9-period EMA of the MACD Line.
The MACD Histogram shows the difference between the MACD line and the Signal line.
Visualization:
MACD Line: A blue line representing the difference between the 12-period and 26-period EMAs.
Signal Line: An orange line representing the 9-period EMA of the MACD line.
MACD Histogram: A red or green histogram that shows the difference between the MACD line and the Signal line.
Example:
When the MACD line crosses above the Signal line, it’s considered a bullish signal. When the MACD line crosses below the Signal line, it’s considered a bearish signal.
Full Chart Example:
Imagine you're looking at a price chart with all the indicators:
Pivot High/Low Lines are drawn as red and green horizontal lines.
20-day and 50-day SMAs are plotted as blue and orange lines, respectively.
Supertrend shows a green or red line indicating the trend.
Momentum (ROC) is shown as a purple line oscillating around zero.
Volume bars are green or red based on whether the close is higher or lower.
MACD appears as a blue line and orange line, with a red or green histogram showing the MACD vs. Signal line difference.
How the Indicators Work Together:
Trend Confirmation: If the price is above the Supertrend line and both SMAs are trending up, it indicates a strong bullish trend.
Momentum: If the ROC is positive and the MACD line is above the Signal line, it further confirms bullish momentum.
Volume: Increasing volume, especially with green bars, suggests that the trend is being supported by active participation.
By using these combined indicators, you can get a comprehensive view of the market's trend, momentum, and potential reversal points (via pivot highs and lows).
Z-Score Weighted Trend System I [InvestorUnknown]The Z-Score Weighted Trend System I is an advanced and experimental trading indicator designed to utilize a combination of slow and fast indicators for a comprehensive analysis of market trends. The system is designed to identify stable trends using slower indicators while capturing rapid market shifts through dynamically weighted fast indicators. The core of this indicator is the dynamic weighting mechanism that utilizes the Z-score of price , allowing the system to respond effectively to significant market movements.
Dynamic Z-Score-Based Weighting System
The Z-Score Weighted Trend System I utilizes the Z-score of price to assign weights dynamically to fast indicators. This mechanism is designed to capture rapid market shifts at potential turning points, providing timely entry and exit signals.
Traders can choose from two primary weighting mechanisms:
Threshold-Based Weighting: The fast indicators are given weight only when the absolute Z-score exceeds a user-defined threshold. Below this threshold, fast indicators have no impact on the final signal.
Continuous Weighting: By setting the threshold to zero, fast indicators always contribute to the final signal, regardless of Z-score levels. However, this increases the likelihood of false signals during ranging or low-volatility markets
// Calculate weight for Fast Indicators based on Z-Score (Slow Indicator weight is kept to 1 for simplicity)
f_zscore_weights(series float z, simple float weight_thre) =>
float fast_weight = na
float slow_weight = na
if weight_thre > 0
if math.abs(z) <= weight_thre
fast_weight := 0
slow_weight := 1
else
fast_weight := 0 + math.sqrt(math.abs(z))
slow_weight := 1
else
fast_weight := 0 + math.sqrt(math.abs(z))
slow_weight := 1
Choice of Z-Score Normalization
Traders have the flexibility to select different Z-score processing methods to better suit their trading preferences:
Raw Z-Score or Moving Average: Traders can opt for either the raw Z-score or a moving average of the Z-score to smooth out fluctuations.
Normalized Z-Score (ranging from -1 to 1) or Z-Score Percentile: The normalized Z-score is simply the raw Z-score divided by 3, while the Z-score percentile utilizes a normal distribution for transformation.
f_zscore_perc(series float zscore_src, simple int zscore_len, simple string zscore_a, simple string zscore_b, simple string ma_type, simple int ma_len) =>
z = (zscore_src - ta.sma(zscore_src, zscore_len)) / ta.stdev(zscore_src, zscore_len)
zscore = switch zscore_a
"Z-Score" => z
"Z-Score MA" => ma_type == "EMA" ? (ta.ema(z, ma_len)) : (ta.sma(z, ma_len))
output = switch zscore_b
"Normalized Z-Score" => (zscore / 3) > 1 ? 1 : (zscore / 3) < -1 ? -1 : (zscore / 3)
"Z-Score Percentile" => (f_percentileFromZScore(zscore) - 0.5) * 2
output
Slow and Fast Indicators
The indicator uses a combination of slow and fast indicators:
Slow Indicators (constant weight) for stable trend identification: DMI (Directional Movement Index), CCI (Commodity Channel Index), Aroon
Fast Indicators (dynamic weight) to identify rapid trend shifts: ZLEMA (Zero-Lag Exponential Moving Average), IIRF (Infinite Impulse Response Filter)
Each indicator is calculated using for-loop methods to provide a smoothed and averaged view of price data over varying lengths, ensuring stability for slow indicators and responsiveness for fast indicators.
Signal Calculation
The final trading signal is determined by a weighted combination of both slow and fast indicators. The slow indicators provide a stable view of the trend, while the fast indicators offer agile responses to rapid market movements. The signal calculation takes into account the dynamic weighting of fast indicators based on the Z-score:
// Calculate Signal (as weighted average)
float sig = math.round(((DMI*slow_w) + (CCI*slow_w) + (Aroon*slow_w) + (ZLEMA*fast_w) + (IIRF*fast_w)) / (3*slow_w + 2*fast_w), 2)
Backtest Mode and Performance Metrics
The indicator features a detailed backtesting mode, allowing traders to compare the effectiveness of their selected settings against a traditional Buy & Hold strategy. The backtesting provides:
Equity calculation based on signals generated by the indicator.
Performance metrics comparing Buy & Hold metrics with the system’s signals, including: Mean, positive, and negative return percentages, Standard deviations, Sharpe, Sortino, and Omega Ratios
// Calculate Performance Metrics
f_PerformanceMetrics(series float base, int Lookback, simple float startDate, bool Annualize = true) =>
// Initialize variables for positive and negative returns
pos_sum = 0.0
neg_sum = 0.0
pos_count = 0
neg_count = 0
returns_sum = 0.0
returns_squared_sum = 0.0
pos_returns_squared_sum = 0.0
neg_returns_squared_sum = 0.0
// Loop through the past 'Lookback' bars to calculate sums and counts
if (time >= startDate)
for i = 0 to Lookback - 1
r = (base - base ) / base
returns_sum += r
returns_squared_sum += r * r
if r > 0
pos_sum += r
pos_count += 1
pos_returns_squared_sum += r * r
if r < 0
neg_sum += r
neg_count += 1
neg_returns_squared_sum += r * r
float export_array = array.new_float(12)
// Calculate means
mean_all = math.round((returns_sum / Lookback), 4)
mean_pos = math.round((pos_count != 0 ? pos_sum / pos_count : na), 4)
mean_neg = math.round((neg_count != 0 ? neg_sum / neg_count : na), 4)
// Calculate standard deviations
stddev_all = math.round((math.sqrt((returns_squared_sum - (returns_sum * returns_sum) / Lookback) / Lookback)) * 100, 2)
stddev_pos = math.round((pos_count != 0 ? math.sqrt((pos_returns_squared_sum - (pos_sum * pos_sum) / pos_count) / pos_count) : na) * 100, 2)
stddev_neg = math.round((neg_count != 0 ? math.sqrt((neg_returns_squared_sum - (neg_sum * neg_sum) / neg_count) / neg_count) : na) * 100, 2)
// Calculate probabilities
prob_pos = math.round((pos_count / Lookback) * 100, 2)
prob_neg = math.round((neg_count / Lookback) * 100, 2)
prob_neu = math.round(((Lookback - pos_count - neg_count) / Lookback) * 100, 2)
// Calculate ratios
sharpe_ratio = math.round((mean_all / stddev_all * (Annualize ? math.sqrt(Lookback) : 1))* 100, 2)
sortino_ratio = math.round((mean_all / stddev_neg * (Annualize ? math.sqrt(Lookback) : 1))* 100, 2)
omega_ratio = math.round(pos_sum / math.abs(neg_sum), 2)
// Set values in the array
array.set(export_array, 0, mean_all), array.set(export_array, 1, mean_pos), array.set(export_array, 2, mean_neg),
array.set(export_array, 3, stddev_all), array.set(export_array, 4, stddev_pos), array.set(export_array, 5, stddev_neg),
array.set(export_array, 6, prob_pos), array.set(export_array, 7, prob_neu), array.set(export_array, 8, prob_neg),
array.set(export_array, 9, sharpe_ratio), array.set(export_array, 10, sortino_ratio), array.set(export_array, 11, omega_ratio)
// Export the array
export_array
//}
Calibration Mode
A Calibration Mode is included for traders to focus on individual indicators, helping them fine-tune their settings without the influence of other components. In Calibration Mode, the user can visualize each indicator separately, making it easier to adjust parameters.
Alerts
The indicator includes alerts for long and short signals when the indicator changes direction, allowing traders to set automated notifications for key market events.
// Alert Conditions
alertcondition(long_alert, "LONG (Z-Score Weighted Trend System)", "Z-Score Weighted Trend System flipped ⬆LONG⬆")
alertcondition(short_alert, "SHORT (Z-Score Weighted Trend System)", "Z-Score Weighted Trend System flipped ⬇Short⬇")
Important Note:
The default settings of this indicator are not optimized for any particular market condition. They are generic starting points for experimentation. Traders are encouraged to use the calibration tools and backtesting features to adjust the system to their specific trading needs.
The results generated from the backtest are purely historical and are not indicative of future results. Market conditions can change, and the performance of this system may differ under different circumstances. Traders and investors should exercise caution and conduct their own research before using this indicator for any trading decisions.
Dema AFR | viResearchDema AFR | viResearch
Conceptual Foundation and Innovation
The "Dema AFR" indicator combines the Double Exponential Moving Average (DEMA) with an Average True Range (ATR)-based adaptive factor to create a responsive and adaptable trend-following system. The DEMA is known for its ability to smooth price data while reducing lag, making it highly effective for trend detection. By incorporating the ATR as a volatility factor, this indicator adapts dynamically to market conditions, allowing traders to capture trends while accounting for changes in volatility. The result is the Adaptive Factor Range (AFR), which provides clear signals for potential trend shifts and helps manage risk through its adaptive nature. This combination of DEMA smoothing and an ATR-based factor enables traders to follow trends more effectively while maintaining sensitivity to changing market conditions.
Technical Composition and Calculation
The "Dema AFR" script consists of two main components: the Double Exponential Moving Average (DEMA) and the Adaptive Factor Range (AFR). The DEMA is calculated over a user-defined length, smoothing out price fluctuations while reducing lag compared to traditional moving averages. The ATR is used to create a dynamic factor that adjusts the AFR based on market volatility. The factor is calculated by multiplying the ATR by a user-defined factor value, which scales the ATR to define upper and lower bounds for the AFR. The Adaptive Factor Range is derived from the DEMA, with upper and lower bounds set by adding or subtracting the ATR-based factor from the DEMA. When the price moves outside these bounds, the AFR is adjusted, and signals are generated. If the lower bound is exceeded, the AFR adjusts upward, while exceeding the upper bound causes the AFR to adjust downward. This dynamic adjustment helps the indicator stay responsive to market movements.
Features and User Inputs
The "Dema AFR" script provides several customizable inputs, allowing traders to tailor the indicator to their strategies. The DEMA Length controls the smoothing period for the DEMA, while the ATR Period defines the window for calculating the Average True Range. The ATR Factor determines the scale of the adaptive factor, controlling how much the AFR adjusts to volatility. Additionally, customizable bar colors and alert conditions allow traders to visualize the trend direction and receive notifications when key trend shifts occur.
Practical Applications
The "Dema AFR" indicator is designed for traders who want to capture trends while adapting to market volatility. The adaptive nature of the AFR makes it responsive to trend changes, providing early signals of potential trend reversals as the AFR adjusts to market movements. By incorporating ATR into the AFR calculation, the indicator adjusts to changing volatility, helping traders manage risk by staying aligned with market conditions. The AFR also helps confirm whether a price move is supported by momentum, improving the accuracy of trade entries and exits.
Advantages and Strategic Value
The "Dema AFR" script offers a significant advantage by combining the smoothness of the DEMA with the adaptability of the ATR-based factor. This dynamic combination allows the indicator to adjust to market conditions, providing more reliable trend signals in both trending and volatile markets. The adaptive nature of the AFR reduces the risk of false signals and helps traders stay on the right side of the trend while managing risk through volatility-adjusted ranges.
Alerts and Visual Cues
The script includes alert conditions that notify traders of key trend changes. The "Dema AFR Long" alert is triggered when the AFR indicates a potential upward trend, while the "Dema AFR Short" alert signals a potential downward trend. Visual cues such as color changes in the bar chart help traders quickly identify shifts in trend direction, allowing them to make informed decisions in real time.
Summary and Usage Tips
The "Dema AFR | viResearch" indicator provides traders with a powerful tool for trend analysis by combining DEMA smoothing with an ATR-based adaptive factor. This script helps traders stay aligned with trends while accounting for market volatility, improving their ability to detect trend reversals and manage risk. By incorporating this indicator into your trading strategy, you can make more informed decisions, whether in trending or volatile market environments. The "Dema AFR" offers a reliable and flexible solution for traders at all levels.
Note: Backtests are based on past results and are not indicative of future performance.
MVSF 6.0[ELPANO]The "MVSF 6.0 " indicator, which stands for Multi-Variable Strategy Framework, overlays on price charts to aid in trading decisions. It combines various moving averages and volume data to generate buy and sell signals based on predefined conditions.
Key features of the indicator include:
Moving Averages: It uses three exponential moving averages (EMAs) with lengths of 200, 100, and 50, and two simple moving averages (SMAs) with lengths of 14 and 9. These averages are combined into a single average line to detect trends.
Volume Analysis: The volume is assessed over a specified period (default is 2 bars) to determine its trend relative to its average, influencing the color and interpretation of signals.
Price Source and VWAP: Users can select the price (close, low, or high) used for calculations. The volume-weighted average price (VWAP) serves as a potential benchmark or condition in signal generation.
Signal Generation: Buy and sell signals are based on the relationship of the price to the average line and VWAP, the direction of the last candle, and the trend direction of the average line. These signals are visually represented on the chart.
Customization: Traders can toggle the visibility of signals, entry points, the average line, and even use these elements as conditions for filtering signals.
This script is designed to be flexible, allowing traders to modify settings according to their strategy needs. The description and implementation aim to provide clarity on how each component works together to assist in trading decisions, adhering to best practices for creating and publishing trading scripts.
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Der Indikator "MVSF 6.0 ", der für Multi-Variable Strategy Framework steht, wird über Preisdiagramme gelegt, um bei Handelsentscheidungen zu helfen. Er kombiniert verschiedene gleitende Durchschnitte und Volumendaten, um Kauf- und Verkaufssignale basierend auf vordefinierten Bedingungen zu generieren.
Wesentliche Merkmale des Indikators umfassen:
Gleitende Durchschnitte: Es werden drei exponentielle gleitende Durchschnitte (EMAs) mit Längen von 200, 100 und 50 sowie zwei einfache gleitende Durchschnitte (SMAs) mit Längen von 14 und 9 verwendet. Diese Durchschnitte werden zu einer einzelnen Durchschnittslinie kombiniert, um Trends zu erkennen.
Volumenanalyse: Das Volumen wird über einen festgelegten Zeitraum (standardmäßig 2 Balken) bewertet, um seinen Trend im Vergleich zum Durchschnitt zu bestimmen, was die Farbe und Interpretation der Signale beeinflusst.
Preisquelle und VWAP: Benutzer können den für Berechnungen verwendeten Preis (Schluss-, Tief- oder Hochkurs) auswählen. Der volumengewichtete Durchschnittspreis (VWAP) dient als mögliche Benchmark oder Bedingung bei der Generierung von Signalen.
Signalgenerierung: Kauf- und Verkaufssignale basieren auf dem Verhältnis des Preises zur Durchschnittslinie und zum VWAP, der Richtung der letzten Kerze und der Trendrichtung der Durchschnittslinie. Diese Signale werden visuell auf dem Diagramm dargestellt.
Anpassung: Händler können die Sichtbarkeit von Signalen, Einstiegspunkten, der Durchschnittslinie und sogar deren Verwendung als Bedingungen für die Filterung von Signalen ein- und ausschalten.
Dieses Skript ist so konzipiert, dass es flexibel ist und Händlern erlaubt, die Einstellungen gemäß ihren Strategiebedürfnissen zu modifizieren. Die Beschreibung und Implementierung zielen darauf ab, Klarheit darüber zu schaffen, wie jede Komponente zusammenarbeitet, um bei Handelsentscheidungen zu helfen, und halten sich an die besten Praktiken für die Erstellung und Veröffentlichung von Handelsskripten.
Enhanced Trend Arrows with Moving Average [ST]Enhanced Trend Arrows with Moving Average
Description in English:
This indicator is designed to identify market trends using a moving average and displays arrows after three consecutive closes above or below the moving average. It helps traders visualize confirmed trends and make informed decisions.
Detailed Explanation:
Configuration:
Length: Defines the period over which the moving average is calculated. The default value is 14.
MA Type: Allows choosing between a Simple Moving Average (SMA) and an Exponential Moving Average (EMA).
Uptrend Color: Sets the color of the arrows indicating an uptrend. The default color is green.
Downtrend Color: Sets the color of the arrows indicating a downtrend. The default color is red.
Moving Average Calculation:
The moving average (MA) is calculated based on the selected type (SMA or EMA) and period. The SMA is the simple arithmetic mean of the closing prices over the specified period, while the EMA gives more weight to recent prices.
Trend Identification:
The script detects when the price crosses above (crossover) or below (crossunder) the moving average.
When a crossover occurs (price moves above the MA), it indicates a potential uptrend, and the trend variable is set to 1.
When a crossunder occurs (price moves below the MA), it indicates a potential downtrend, and the trend variable is set to -1.
The script tracks the closing price at the crossover or crossunder point using the trendPrice variable.
It also counts consecutive bars above or below the moving average to confirm the trend, using above_count for uptrend and below_count for downtrend.
Arrow Display:
The script displays an up arrow ("▲") after three consecutive closes above the moving average, indicating a confirmed uptrend.
Similarly, it displays a down arrow ("▼") after three consecutive closes below the moving average, indicating a confirmed downtrend.
The arrows are displayed at the trendPrice level to clearly indicate the point at which the trend was confirmed.
Indicator Benefits:
Trend Identification: Helps traders identify market trends using moving averages, which are widely used in technical analysis.
Visual Cues: The arrows provide clear visual signals for confirmed trends, making it easier for traders to make informed decisions.
New Features and Enhancements:
This script has been enhanced to provide more accurate trend identification by ensuring arrows are only displayed after three consecutive closes above or below the moving average.
The color customization options for uptrend and downtrend arrows have been added for better visualization.
Improved description and explanations to make the functionality and usage of the indicator clearer.
Volatility Adjusted Weighted DEMA [BackQuant]Volatility Adjusted Weighted DEMA
The Volatility Adjusted Weighted Double Exponential Moving Average (VAWDEMA) by BackQuant is a sophisticated technical analysis tool designed for traders seeking to integrate volatility into their moving average calculations. This innovative indicator adjusts the weighting of the Double Exponential Moving Average (DEMA) according to recent volatility levels, offering a more dynamic and responsive measure of market trends.
Primarily, the single Moving average is very noisy, but can be used in the context of strategy development, where as the crossover, is best used in the context of defining a trading zone/ macro uptrend on higher timeframes.
Why Volatility Adjustment is Beneficial
Volatility is a fundamental aspect of financial markets, reflecting the intensity of price changes. A volatility adjustment in moving averages is beneficial because it allows the indicator to adapt more quickly during periods of high volatility, providing signals that are more aligned with the current market conditions. This makes the VAWDEMA a versatile tool for identifying trend strength and potential reversal points in more volatile markets.
Understanding DEMA and Its Advantages
DEMA is an indicator that aims to reduce the lag associated with traditional moving averages by applying a double smoothing process. The primary benefit of DEMA is its sensitivity and quicker response to price changes, making it an excellent tool for trend following and momentum trading. Incorporating DEMA into your analysis can help capture trends earlier than with simple moving averages.
The Power of Combining Volatility Adjustment with DEMA
By adjusting the weight of the DEMA based on volatility, the VAWDEMA becomes a powerful hybrid indicator. This combination leverages the quick responsiveness of DEMA while dynamically adjusting its sensitivity based on current market volatility. This results in a moving average that is both swift and adaptive, capable of providing more relevant signals for entering and exiting trades.
Core Logic Behind VAWDEMA
The core logic of the VAWDEMA involves calculating the DEMA for a specified period and then adjusting its weighting based on a volatility measure, such as the average true range (ATR) or standard deviation of price changes. This results in a weighted DEMA that reflects both the direction and the volatility of the market, offering insights into potential trend continuations or reversals.
Utilizing the Crossover in a Trading System
The VAWDEMA crossover occurs when two VAWDEMAs of different lengths cross, signaling potential bullish or bearish market conditions. In a trading system, a crossover can be used as a trigger for entry or exit points:
Bullish Signal: When a shorter-period VAWDEMA crosses above a longer-period VAWDEMA, it may indicate an uptrend, suggesting a potential entry point for a long position.
Bearish Signal: Conversely, when a shorter-period VAWDEMA crosses below a longer-period VAWDEMA, it might signal a downtrend, indicating a possible exit point or a short entry.
Incorporating VAWDEMA crossovers into a trading strategy can enhance decision-making by providing timely and adaptive signals that account for both trend direction and market volatility. Traders should combine these signals with other forms of analysis and risk management techniques to develop a well-rounded trading strategy.
Alert Conditions For Trading
alertcondition(vwdema>vwdema , title="VWDEMA Long", message="VWDEMA Long - {{ticker}} - {{interval}}")
alertcondition(vwdema<vwdema , title="VWDEMA Short", message="VWDEMA Short - {{ticker}} - {{interval}}")
alertcondition(ta.crossover(crossover, 0), title="VWDEMA Crossover Long", message="VWDEMA Crossover Long - {{ticker}} - {{interval}}")
alertcondition(ta.crossunder(crossover, 0), title="VWDEMA Crossover Short", message="VWDEMA Crossover Short - {{ticker}} - {{interval}}")
Thus following all of the key points here are some sample backtests on the 1D Chart
Disclaimer: Backtests are based off past results, and are not indicative of the future.
INDEX:BTCUSD
INDEX:ETHUSD
BINANCE:SOLUSD
MACDh with divergences & impulse system (overlayed on prices)-----------------------------------------------------------------
General Description:
This indicator ( the one on the top panel above ) consists on some lines, arrows and labels drawn over the price bars/candles indicating the detection of regular divergences between price and the classic MACD histogram (shown on the low panel). This script is special because it can be adjusted to fit several criteria when trading divergences filtering them according to the "height" and "width" of the patterns. The script also includes the "extra features" Impulse System and Keltner Channels, which you will hardly find anywhere else in similar classic MACD histogram divergence indicators.
The indicator helps to find trend reversals, and it works on any market, any instrument, any timeframe, and any market condition (except against really strong trends that do not show any other sign of reversion yet).
Please take on consideration that divergences should be taken with caution.
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Definition of classic Bullish and Bearish divergences:
* Bearish divergences occur in uptrends identifying market tops. A classical or regular bearish divergence occurs when prices reach a new high and then pull back, with an oscillator (MACD histogram in this case) dropping below its zero line. Prices stabilize and rally to a higher high, but the oscillator reaches a lower peak than it did on a previous rally.
In the chart above (weekly charts of NKE, Nike, Inc.), in area X (around August 2021), NKE rallied to a new bull market high and MACD-Histogram rallied with it, rising above its previous peak and showing that bulls were extremely strong. In area Y, MACD-H fell below its centerline and at the same time prices punched below the zone between the two moving averages. In area Z, NKE rallied to a new bull market high, but the rally of MACD-H was feeble, reflecting the bulls’ weakness. Its downtick from peak Z completed a bearish divergence, giving a strong sell signal and auguring a nasty bear market.
* Bullish divergences , in the other hand, occur towards the ends of downtrends identifying market bottoms. A classical (also called regular) bullish divergence occurs when prices and an oscillator (MACD histogram in this case) both fall to a new low, rally, with the oscillator rising above its zero line, then both fall again. This time, prices drop to a lower low, but the oscillator traces a higher bottom than during its previous decline.
In the example in the chart above (weekly charts of NKE, Nike, Inc.), you see a bearish divergence that signaled the October 2022 bear market bottom, giving a strong buy signal right near the lows. In area A, NKE (weekly charts) appeared in a free fall. The record low A of MACD-H indicated that bears were extremely strong. In area B, MACD-H rallied above its centerline. Notice the brief rally of prices at that moment. In area C, NKE slid to a new bear market low, but MACD-H traced a much more shallow low. Its uptick completed a bullish divergence, giving a strong buy signal.
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Some cool features included in this indicator:
1. This indicator also includes the “ Impulse System ”. The Impulse System is based on two indicators, a 13-day exponential moving average and the MACD-Histogram, and identifies inflection points where a trend speeds up or slows down. The moving average identifies the trend, while the MACD-Histogram measures momentum. This unique indicator combination is color coded into the price bars for easy reference.
Calculation:
Green Price Bar: (13-period EMA > previous 13-period EMA) and
(MACD-Histogram > previous period's MACD-Histogram)
Red Price Bar: (13-period EMA < previous 13-period EMA) and
(MACD-Histogram < previous period's MACD-Histogram)
Price bars are colored blue when conditions for a Red Price Bar or Green Price Bar are not met. The MACD-Histogram is based on MACD(12,26,9).
The Impulse System works more like a censorship system. Green price bars show that the bulls are in control of both trend and momentum as both the 13-day EMA and MACD-Histogram are rising (you don't have permission to sell). A red price bar indicates that the bears have taken control because the 13-day EMA and MACD Histogram are falling (you don't have permission to buy). A blue price bar indicates mixed technical signals, with neither buying nor selling pressure predominating (either both buying or selling are permitted).
2. Another "extra feature" included here is the " Keltner Channels ". Keltner Channels are volatility-based envelopes set above and below an exponential moving average.
3. It were also included a couple of EMAs.
Everything can be removed from the chart any time.
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Options/adjustments for this indicator:
*Horizontal Distance (width) between two tops/bottoms criteria.
Refers to the horizontal distance between the MACH histogram peaks involved in the divergence
*Height of tops/bottoms criteria (for Histogram).
Refers to the difference/relation/vertical distance between the MACH HISTOGRAM peaks involved in the divergence: 1st Histogram Peak is X times the 2nd.
*Height/Vertical deviation of tops/bottoms criteria (for Price).
Deviation refers to the difference/relation/vertical distance between the PRICE peaks involved in the divergence.
*Plot Regular Bullish Divergences?.
*Plot Regular Bearish Divergences?.
*Delete Previous Cancelled Divergences?.
*Shows a pair of EMAs.
*Shows Keltner Channels (using ATR)
Keltner Channels are volatility-based envelopes set above and below an exponential moving average.
*This indicator also has the option to show the Impulse System over the price bars/candles.
Machine Learning : Cosine Similarity & Euclidean DistanceIntroduction:
This script implements a comprehensive trading strategy that adheres to the established rules and guidelines of housing trading. It leverages advanced machine learning techniques and incorporates customised moving averages, including the Conceptive Price Moving Average (CPMA), to provide accurate signals for informed trading decisions in the housing market. Additionally, signal processing techniques such as Lorentzian, Euclidean distance, Cosine similarity, Know sure thing, Rational Quadratic, and sigmoid transformation are utilised to enhance the signal quality and improve trading accuracy.
Features:
Market Analysis: The script utilizes advanced machine learning methods such as Lorentzian, Euclidean distance, and Cosine similarity to analyse market conditions. These techniques measure the similarity and distance between data points, enabling more precise signal identification and enhancing trading decisions.
Cosine similarity:
Cosine similarity is a measure used to determine the similarity between two vectors, typically in a high-dimensional space. It calculates the cosine of the angle between the vectors, indicating the degree of similarity or dissimilarity.
In the context of trading or signal processing, cosine similarity can be employed to compare the similarity between different data points or signals. The vectors in this case represent the numerical representations of the data points or signals.
Cosine similarity ranges from -1 to 1, with 1 indicating perfect similarity, 0 indicating no similarity, and -1 indicating perfect dissimilarity. A higher cosine similarity value suggests a closer match between the vectors, implying that the signals or data points share similar characteristics.
Lorentzian Classification:
Lorentzian classification is a machine learning algorithm used for classification tasks. It is based on the Lorentzian distance metric, which measures the similarity or dissimilarity between two data points. The Lorentzian distance takes into account the shape of the data distribution and can handle outliers better than other distance metrics.
Euclidean Distance:
Euclidean distance is a distance metric widely used in mathematics and machine learning. It calculates the straight-line distance between two points in Euclidean space. In two-dimensional space, the Euclidean distance between two points (x1, y1) and (x2, y2) is calculated using the formula sqrt((x2 - x1)^2 + (y2 - y1)^2).
Dynamic Time Windows: The script incorporates a dynamic time window function that allows users to define specific time ranges for trading. It checks if the current time falls within the specified window to execute the relevant trading signals.
Custom Moving Averages: The script includes the CPMA, a powerful moving average calculation. Unlike traditional moving averages, the CPMA provides improved support and resistance levels by considering multiple price types and employing a combination of Exponential Moving Averages (EMAs) and Simple Moving Averages (SMAs). Its adaptive nature ensures responsiveness to changes in price trends.
Signal Processing Techniques: The script applies signal processing techniques such as Know sure thing, Rational Quadratic, and sigmoid transformation to enhance the quality of the generated signals. These techniques improve the accuracy and reliability of the trading signals, aiding in making well-informed trading decisions.
Trade Statistics and Metrics: The script provides comprehensive trade statistics and metrics, including total wins, losses, win rate, win-loss ratio, and early signal flips. These metrics offer valuable insights into the performance and effectiveness of the trading strategy.
Usage:
Configuring Time Windows: Users can customize the time windows by specifying the start and finish time ranges according to their trading preferences and local market conditions.
Signal Interpretation: The script generates long and short signals based on the analysis, custom moving averages, and signal processing techniques. Users should pay attention to these signals and take appropriate action, such as entering or exiting trades, depending on their trading strategies.
Trade Statistics: The script continuously tracks and updates trade statistics, providing users with a clear overview of their trading performance. These statistics help users assess the effectiveness of the strategy and make informed decisions.
Conclusion:
With its adherence to housing trading rules, advanced machine learning methods, customized moving averages like the CPMA, and signal processing techniques such as Lorentzian, Euclidean distance, Cosine similarity, Know sure thing, Rational Quadratic, and sigmoid transformation, this script offers users a powerful tool for housing market analysis and trading. By leveraging the provided signals, time windows, and trade statistics, users can enhance their trading strategies and improve their overall trading performance.
Disclaimer:
Please note that while this script incorporates established tradingview housing rules, advanced machine learning techniques, customized moving averages, and signal processing techniques, it should be used for informational purposes only. Users are advised to conduct their own analysis and exercise caution when making trading decisions. The script's performance may vary based on market conditions, user settings, and the accuracy of the machine learning methods and signal processing techniques. The trading platform and developers are not responsible for any financial losses incurred while using this script.
By publishing this script on the platform, traders can benefit from its professional presentation, clear instructions, and the utilisation of advanced machine learning techniques, customised moving averages, and signal processing techniques for enhanced trading signals and accuracy.
I extend my gratitude to TradingView, LUX ALGO, and JDEHORTY for their invaluable contributions to the trading community. Their innovative scripts, meticulous coding patterns, and insightful ideas have profoundly enriched traders' strategies, including my own.
Momentum Ratio Oscillator [Loxx]What is Momentum Ratio Oscillator?
The theory behind this indicator involves utilizing a sequence of exponential moving average (EMA) calculations to achieve a smoother value of momentum ratio, which compares the current value to the previous one. Although this results in an outcome similar to that of some pre-existing indicators (such as volume zone or price zone oscillators), the use of EMA for smoothing is what sets it apart. EMA produces a smooth step-like output when values undergo sudden changes, whereas the mathematics used for those other indicators are completely distinct. This is a concept by the beloved Mladen of FX forums.
To utilize this version of the indicator, you have the option of using either levels, middle, or signal crosses for signals. The indicator is range bound from 0 to 1.
What is an EMA?
EMA stands for Exponential Moving Average, which is a type of moving average that is commonly used in technical analysis to smooth out price data and identify trends.
In a simple moving average (SMA), each data point is given equal weight when calculating the average. For example, if you are calculating the 10-day SMA, you would add up the prices for the past 10 days and divide by 10 to get the average. In contrast, in an EMA, more weight is given to recent prices, while older prices are given less weight.
The formula for calculating an EMA involves using a smoothing factor that is multiplied by the difference between the current price and the previous EMA value, and then adding this to the previous EMA value. The smoothing factor is typically calculated based on the length of the EMA being used. For example, a 10-day EMA might use a smoothing factor of 2/(10+1) or 0.1818.
The result of using an EMA is that the line produced is more responsive to recent price changes than a simple moving average. This makes it useful for identifying short-term trends and potential trend reversals. However, it can also be more volatile and prone to whipsaws, so it is often used in combination with other indicators to confirm signals.
Overall, the EMA is a widely used and versatile tool in technical analysis, and its effectiveness depends on the specific context in which it is applied.
What is Momentum?
In technical analysis, momentum refers to the rate of change of an asset's price over a certain period of time. It is often used to identify trends and potential trend reversals in financial markets.
Momentum is calculated by subtracting the closing price of an asset X days ago from its current closing price, where X is the number of days being used for the calculation. The result is the momentum value for that particular day. A positive momentum value suggests that prices are increasing, while a negative value indicates that prices are decreasing.
Traders use momentum in a variety of ways. One common approach is to look for divergences between the momentum indicator and the price of the asset being traded. For example, if an asset's price is trending upwards but its momentum is trending downwards, this could be a sign of a potential trend reversal.
Another popular strategy is to use momentum to identify overbought and oversold conditions in the market. When an asset's price has been rising rapidly and its momentum is high, it may be considered overbought and due for a correction. Conversely, when an asset's price has been falling rapidly and its momentum is low, it may be considered oversold and due for a bounce back up.
Momentum is also often used in conjunction with other technical indicators, such as moving averages or Bollinger Bands, to confirm signals and improve the accuracy of trading decisions.
Overall, momentum is a useful tool for traders and investors to analyze price movements and identify potential trading opportunities. However, like all technical indicators, it should be used in conjunction with other forms of analysis and with consideration of the broader market context.
Extras
Alerts
Signals
Loxx's Expanded Source Types, see here for details
Stochastic MACD - Slow and FastStochastic MACD - Slow and Fast
The "Stochastic MACD - Slow and Fast" indicator combines two popular technical indicators, the Stochastic Oscillator and the Moving Average Convergence Divergence ( MACD ).
The Stochastic Oscillator is a momentum indicator that measures the current closing position of an asset relative to its recent price range. This indicator helps traders identify possible turning points in an asset's trend, it is used to identify if the market is overbought or oversold.
On the other hand, the MACD is an indicator used to identify the trend and strength of the market and shows the difference between two exponential moving averages ( EMA ) of different periods. The MACD is commonly used to determine the direction of an asset's price trend.
The combination of both indicators can help traders identify market entry and exit opportunities. This indicator has two parts: a slow part and a fast part. The slow part uses input values for the lengths of the moving averages and the length of the signal for the MACD indicator. The fast part uses different input values for the lengths of the moving averages. Also, each part has its own set of line colors and histogram colors for easy visualization.
In general, the "Stochastic MACD - Slow and Fast" indicator is used to identify possible turning points in the trend of an asset. Traders can use the indicator to determine when to enter or exit a position based on the signals generated by the indicator. The stochastic MACD is a variation of the regular MACD that incorporates a stochastic oscillator to provide additional signals.
In summary, this indicator can be useful for those looking for a combination of two popular indicators to help identify trading opportunities.
In addition, parameters were defined to activate or deactivate the graphic signal.
When the Stochastic MACD Slow Line Crosses the Stochastic MACD Slow Signal Line:
Long or Buy = ↑ // The Entry is more Effective if it is made when the signal is below the Zero Trend Line .
Short or Sell = ↓ // The Entry is more Effective if it is made when the signal is above the Zero Trend Line .
When the Fast Stochastic MACD Line Crosses the Slow Stochastic MACD Line:
Long or Buy = ▲ // The Entry is more Effective if it is made when the signal is below the Zero Trend Line .
Short or Sell = ▼ // The Entry is more Effective if it is made when the signal is above the Zero Trend Line .
Taking into account the above, alerts were also defined for possible Purchases or Sales or entries in Long or Short.
COPOSITION AND USE OF THE INDICATOR
This script is an implementation of the Stochastic MACD indicator with two variations - Slow and Fast. It uses a combination of the Stochastic Oscillator and the Moving Average Convergence Divergence (MACD) indicator to identify trend reversals and momentum shifts in the price of an asset.
The Slow version of the Stochastic MACD is built using three inputs - fastLength, slowLength, and signalLength. The fastLength and slowLength are used to calculate two exponential moving averages (EMAs), while the signalLength is used to calculate a signal line as an EMA of the difference between the two EMAs. The Stochastic Oscillator is then applied to the difference between the two EMAs, and the resulting values are plotted on the chart.
The Fast version of the Stochastic MACD is built using the same inputs as the Slow version, but with different values. It uses a shorter fastLength value and a longer slowLength value to generate the two EMAs, and the resulting values are plotted on the chart.
The script also includes inputs for choosing the type of moving average to use (SMA, EMA, etc.), the source of price data (open, close, etc.), the lookback period, and the colors for the lines and histogram bars.
This script can be used in different markets such as forex, indices, and cryptocurrencies for analysis and trading. However, it is important to note that no trading strategy is guaranteed to be profitable, and traders should always conduct their own research and risk management.
EMA and MACD with Trailing Stop Loss (by Coinrule)An exponential moving average ( EMA ) is a type of moving average (MA) that places a greater weight and significance on the most recent data points. The exponential moving average is also referred to as the exponentially weighted moving average. An exponentially weighted moving average reacts more significantly to recent price changes than a simple moving average simple moving average ( SMA ), which applies an equal weight to all observations in the period.
Moving average convergence divergence ( MACD ) is a trend-following momentum indicator that shows the relationship between two moving averages of a security’s price. The MACD is calculated by subtracting the 26-period exponential moving average ( EMA ) from the 12-period EMA.
The result of that calculation is the MACD line. A nine-day EMA of the MACD called the "signal line," is then plotted on top of the MACD line, which can function as a trigger for buy and sell signals. Traders may buy the security when the MACD crosses above its signal line and sell—or short—the security when the MACD crosses below the signal line. Moving average convergence divergence ( MACD ) indicators can be interpreted in several ways, but the more common methods are crossovers, divergences, and rapid rises/falls.
The Strategy enters and closes the trade when the following conditions are met:
LONG
The MACD histogram turns bearish
EMA7 is greater than EMA14
EXIT
Price increases 3% trailing
Price decreases 1% trailing
This strategy is back-tested from 1 January 2022 to simulate how the strategy would work in a bear market and provides good returns.
Pairs that produce very strong results include XRPUSDT on the 1-minute timeframe. This short timeframe means that this strategy opens and closes trades regularly
In order to further improve the strategy, the EMA can be changed from 7 and 14 to, say, EMA20 and EMA50. Furthermore, the trailing stop loss can also be changed to ideally suit the user to match their needs.
The strategy assumes each order is using 30% of the available coins to make the results more realistic and to simulate you only ran this strategy on 30% of your holdings. A trading fee of 0.1% is also taken into account and is aligned to the base fee applied on Binance.
Adaptive MA constructor [lastguru]Adaptive Moving Averages are nothing new, however most of them use EMA as their MA of choice once the preferred smoothing length is determined. I have decided to make an experiment and separate length generation from smoothing, offering multiple alternatives to be combined. Some of the combinations are widely known, some are not. This indicator is based on my previously published public libraries and also serve as a usage demonstration for them. I will try to expand the collection (suggestions are welcome), however it is not meant as an encyclopaedic resource, so you are encouraged to experiment yourself: by looking on the source code of this indicator, I am sure you will see how trivial it is to use the provided libraries and expand them with your own ideas and combinations. I give no recommendation on what settings to use, but if you find some useful setting, combination or application ideas (or bugs in my code), I would be happy to read about them in the comments section.
The indicator works in three stages: Prefiltering, Length Adaptation and Moving Averages.
Prefiltering is a fast smoothing to get rid of high-frequency (2, 3 or 4 bar) noise.
Adaptation algorithms are roughly subdivided in two categories: classic Length Adaptations and Cycle Estimators (they are also implemented in separate libraries), all are selected in Adaptation dropdown. Length Adaptation used in the Adaptive Moving Averages and the Adaptive Oscillators try to follow price movements and accelerate/decelerate accordingly (usually quite rapidly with a huge range). Cycle Estimators, on the other hand, try to measure the cycle period of the current market, which does not reflect price movement or the rate of change (the rate of change may also differ depending on the cycle phase, but the cycle period itself usually changes slowly).
Chande (Price) - based on Chande's Dynamic Momentum Index (CDMI or DYMOI), which is dynamic RSI with this length
Chande (Volume) - a variant of Chande's algorithm, where volume is used instead of price
VIDYA - based on VIDYA algorithm. The period oscillates from the Lower Bound up (slow)
VIDYA-RS - based on Vitali Apirine's modification of VIDYA algorithm (he calls it Relative Strength Moving Average). The period oscillates from the Upper Bound down (fast)
Kaufman Efficiency Scaling - based on Efficiency Ratio calculation originally used in KAMA
Deviation Scaling - based on DSSS by John F. Ehlers
Median Average - based on Median Average Adaptive Filter by John F. Ehlers
Fractal Adaptation - based on FRAMA by John F. Ehlers
MESA MAMA Alpha - based on MESA Adaptive Moving Average by John F. Ehlers
MESA MAMA Cycle - based on MESA Adaptive Moving Average by John F. Ehlers, but unlike Alpha calculation, this adaptation estimates cycle period
Pearson Autocorrelation* - based on Pearson Autocorrelation Periodogram by John F. Ehlers
DFT Cycle* - based on Discrete Fourier Transform Spectrum estimator by John F. Ehlers
Phase Accumulation* - based on Dominant Cycle from Phase Accumulation by John F. Ehlers
Length Adaptation usually take two parameters: Bound From (lower bound) and To (upper bound). These are the limits for Adaptation values. Note that the Cycle Estimators marked with asterisks(*) are very computationally intensive, so the bounds should not be set much higher than 50, otherwise you may receive a timeout error (also, it does not seem to be a useful thing to do, but you may correct me if I'm wrong).
The Cycle Estimators marked with asterisks(*) also have 3 checkboxes: HP (Highpass Filter), SS (Super Smoother) and HW (Hann Window). These enable or disable their internal prefilters, which are recommended by their author - John F. Ehlers. I do not know, which combination works best, so you can experiment.
Chande's Adaptations also have 3 additional parameters: SD Length (lookback length of Standard deviation), Smooth (smoothing length of Standard deviation) and Power (exponent of the length adaptation - lower is smaller variation). These are internal tweaks for the calculation.
Length Adaptaton section offer you a choice of Moving Average algorithms. Most of the Adaptations are originally used with EMA, so this is a good starting point for exploration.
SMA - Simple Moving Average
RMA - Running Moving Average
EMA - Exponential Moving Average
HMA - Hull Moving Average
VWMA - Volume Weighted Moving Average
2-pole Super Smoother - 2-pole Super Smoother by John F. Ehlers
3-pole Super Smoother - 3-pole Super Smoother by John F. Ehlers
Filt11 -a variant of 2-pole Super Smoother with error averaging for zero-lag response by John F. Ehlers
Triangle Window - Triangle Window Filter by John F. Ehlers
Hamming Window - Hamming Window Filter by John F. Ehlers
Hann Window - Hann Window Filter by John F. Ehlers
Lowpass - removes cyclic components shorter than length (Price - Highpass)
DSSS - Derivation Scaled Super Smoother by John F. Ehlers
There are two Moving Averages that are drown on the chart, so length for both needs to be selected. If no Adaptation is selected ( None option), you can set Fast Length and Slow Length directly. If an Adaptation is selected, then Cycle multiplier can be selected for Fast and Slow MA.
More information on the algorithms is given in the code for the libraries used. I am also very grateful to other TradingView community members (they are also mentioned in the library code) without whom this script would not have been possible.
HEYC-Bands-Strategy by HassonyaHey guys, HEYC-Bands-Strategy indicator is moving average envelopes trend tracker system are pivot-based envelopes set above and below a moving average. Envelope is then set the high and low above or below the moving average. This creates parallel bands that follow price action. With a moving average as the base, Moving Average Envelopes can be used as a trend following indicator. However, this indicator is not limited to just trend following. You can also use it as support and resistance. The indicator aims to ensure that you follow the trend with maximum consistency and stay in the trend.
The indicator has 15 different options that form the basis of the moving average. What options are these?
- EMA - Exponential Moving Average
- WMA - Weighted Moving Average
- VWMA - Volume-Weighted Moving Average
- DEMA - Double Exponential Moving Average
- TEMA - Triple Exponential Moving Average
- LAGMA - Laguerre Moving Average
- HULLMA - Hull Moving Average
- EHMA - Exponential Hull Moving Average
- ETMA - Exponential Triangular Moving Average
- SSMA - Super-Smoother Moving Average
- ALMA - Arnaud Legoux Moving Average
- VIDYA - Variable Index Dynamic Average
- STMA - Triangular Moving Average
- ZEMA - Zero-Lag Exponential Moving Average
- SMA - Simple Moving Average
With the simplest logic, you can use it as buy when the price closes on the band, and sell when the price closes below the band.
Vertical lines and background guide you in the buying/selling trend changes in the indicator settings.
Thanks for support
Crypto EMA+MA+MACS by hobbeLeThis is an indicator that includes several EMAs and MAs (Used in Cryptotrading).
In addition, the Golden and Death Cross are also displayed.
Used MAs
MA 7 - Orange Line
MA 21 - Yellow Line
MA 25 - Grey Line
MA 99 - Blue Line
MA 200 - Green Line
Used EMAs
EMA 200 - Grey Dotted Line
EMA 222 - Pink Dotted Line
Golden Cross
Crossover MA25 + MA200
Death Cross
Crossunder MA25 + MA200
What is a Moving Average (MA) ?
A moving average (MA) is a widely used indicator in technical analysis that helps smooth out price action by filtering out the “noise” from random short-term price fluctuations.
Moving average is a trend-following, or lagging, indicator because it is based on past prices. The most common applications of moving averages are:
to identify the trend direction
to determine support and resistance levels
The two basic and commonly used moving averages are the simple moving average ( SMA ), which is the arithmetic average of a security over a defined number of time periods, and the exponential moving average ( EMA ), which gives greater weight to more recent prices.
What is a Golden Cross?
The golden cross is a candlestick pattern that is a bullish signal in which a relatively short-term moving average crosses above a long-term moving average. The golden cross is a bullish breakout pattern formed from a crossover involving a security's short-term moving average (such as the 15-day moving average) breaking above its long-term moving average (such as the 50-day moving average) or resistance level. As long-term indicators carry more weight, the golden cross indicates a bull market on the horizon and is reinforced by high trading volumes.
What Is a Death Cross?
The death cross is a technical chart pattern indicating the potential for a major selloff. The death cross appears on a chart when a stock’s short-term moving average crosses below its long-term moving average.
Source; Investopedia
5/22 Cross by bistatistic"5/22 Cross by bistatistic" is an indicator prepared using exponential moving averages. It can be used in the graphics of stock and money markets, especially the bitcoin market.
The intersection times of 5-day and 22-day exponential moving averages allow us to decide the direction of the trend.
We can use the buy and sell signals of 5/22 Cross as follows:
If the 5-day exponential moving average crosses the 22-day exponential moving average upward, buy it,
If the 5-day exponential moving average crosses the 22-day exponential moving average downward, sell it.
I think it gives good results in periods of 1 hour or more. As the time period grows, the probability of giving correct results will increase.
***
"5/22 Cross by bistatistic" üssel hareketli ortalamalar kullanılarak hazırlanmış bir göstergedir. Bitcoin piyasası başta olmak üzere hisse senedi ve para piyasalarının grafiklerinde kullanılabilmektedir.
5 günlük ve 22 günlük üssel hareketli ortalamaların kesişim zamanları trendin yönüne karar vermemizi sağlar.
5/22 Cross'un alış ve satış sinyallerini şu şekilde kullanabiliriz :
Eğer 5 günlük üssel hareketli ortalama 22 günlük üssel hareketli ortalama ile yukarı yönlü kesişirse satın alın,
Eğer 5 günlük üssel hareketli ortalama, 22 günlük üssel hareketli ortalama ile aşağı yönlü kesişirse sat.
Daha çok 1 saatlik ve üzeri periyotlarda iyi sonuçlar verdiğini düşünüyorum. Zaman periyodu büyüdükçe doğru sonuç verme olasılığı da artacaktır.
Colored Moving Averages Can Help You Spot TrendsMoving averages are perhaps the most popular indicator in technical analysis. But sometimes they're not the easiest to interpret.
This indicator helps you see the trend by coloring the MA based on its direction. It's green when rising and red when falling. Of course, you can easily change that in the Style tab under Settings.
Color MA also lets you select from five different types of moving averages, including simple, exponential and Hull. We've included a list for easy reference below. Just change the "AvgType" on the Input tab under Settings.
This chart of Facebook shows the 20-day simple moving average. Notice how swings often marked turns in the stock price.
AvgType codes:
1 - Simple Moving Average
2 - Exponential Moving Average
3 - Hull Moving Average
4 - Weighted Moving Average
5 - Volume Weighted Moving Average
DECODE Moving Average ToolkitDECODE Moving Average Toolkit: Your All-in-One MA Analysis Powerhouse!
This versatile indicator is designed to be your go-to solution for analysing trends, identifying potential entry/exit points, and staying ahead of market movements using the power of Moving Averages (MAs).
Whether you're a seasoned trader or just starting out, the Decode MAT offers a comprehensive suite of features in a user-friendly package.
Key Features:
Multiple Moving Averages: Visualize up to 10 Moving Averages simultaneously on your chart.
Includes 5 Exponential Moving Averages (EMAs) and 5 Simple Moving Averages (SMAs).
Easily toggle the visibility of each MA and customize its length to suit your trading style and the asset you're analyzing.
Dynamic MA Ribbons: Gain a clearer perspective on trend direction and strength with 5 configurable MA Ribbons.
Each ribbon is formed between a corresponding EMA and SMA (e.g., EMA 20 / SMA 20).
The ribbon color changes to indicate bullish (e.g., green) or bearish (e.g., red) sentiment, providing an intuitive visual cue.
Toggle ribbon visibility with a single click.
Powerful Crossover Alerts: Never miss a potential trading opportunity with up to 5 customizable MA Crossover Alerts.
Define your own fast and slow MAs for each alert from any of the 10 available MAs.
Receive notifications directly through TradingView when your specified MAs cross over or cross under.
Optionally display visual symbols (e.g., triangles ▲▼) directly on your chart at the exact crossover points for quick identification.
Highly Customizable:
Adjust the source price (close, open, etc.) for all MA calculations.
Fine-tune the appearance (colors, line thickness) of every MA line, ribbon, and alert symbol to match your charting preferences.
User-Friendly Interface: All settings are neatly organized in the indicator's input menu, making configuration straightforward and intuitive.
How Can You Use the Decode MAT in Your Trading?
This toolkit is incredibly versatile and can be adapted to various trading strategies:
Trend Identification:
Use longer-term MAs (e.g., 50, 100, 200 period) to identify the prevailing market trend. When prices are consistently above these MAs, it suggests an uptrend, and vice-versa.
Observe the MA ribbons: A consistently green ribbon can indicate a strong uptrend, while a red ribbon can signal a downtrend. The widening or narrowing of the ribbon can also suggest changes in trend momentum.
Dynamic Support & Resistance:
Shorter-term MAs (e.g., 10, 20 period EMAs) can act as dynamic levels of support in an uptrend or resistance in a downtrend. Look for price pullbacks to these MAs as potential entry opportunities.
Crossover Signals (Entries & Exits):
Golden Cross / Death Cross: Configure alerts for classic crossover signals. For example, a 50-period MA crossing above a 200-period MA (Golden Cross) is often seen as a long-term bullish signal. Conversely, a 50-period MA crossing below a 200-period MA (Death Cross) can be a bearish signal.
Shorter-Term Signals: Use crossovers of shorter-term MAs (e.g., EMA 10 crossing EMA 20) for more frequent, shorter-term trading signals. A fast MA crossing above a slow MA can signal a buy, while a cross below can signal a sell.
Use the on-chart symbols for quick visual confirmation of these crossover events.
Confirmation Tool:
Combine the Decode MAT with other indicators (like RSI, MACD, or volume analysis) to confirm signals and increase the probability of successful trades. For instance, a bullish MA crossover combined with an oversold RSI reading could strengthen a buy signal.
Multi-Timeframe Analysis:
Apply the toolkit across different timeframes to get a broader market perspective. A long-term uptrend on the daily chart, confirmed by a short-term bullish crossover on the 1-hour chart, can provide a higher-confidence entry.
The DECODE Moving Average Toolkit empowers you to tailor your MA analysis precisely to your needs.
