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Linear Regression Oscillator [ChartPrime]Linear Regression Oscillator Indicator Overview: The Linear Regression Oscillator is a custom TradingView indicator designed to provide insights into potential mean reversion and trend conditions. By calculating a linear regression on the closing prices over a user-defined period, this oscillator helps identify overbought and oversold levels and highlights trend changes. The indicator also offers visual cues and color-coded price bars to aid in quick decision-making. Key Features: ◆ Customizable Look-Back Period: Input: Length Default: 20 Description: Determines the period over which the linear regression is calculated. A longer period smooths the oscillator but may lag, while a shorter period is more responsive but may be noisier. ◆ Overbought and Oversold Thresholds: Inputs: Upper Threshold and Lower Threshold Default: 1.5 and -1.5 respectively Description: Define the upper and lower bounds for identifying overbought and oversold conditions. Values outside these thresholds suggest potential reversals. ◆ Candlestick Color Plotting: Input: Plot Bar Color Default: false Description: Option to color the price bars based on the oscillator's value, providing a visual representation of market conditions. Bars turn cyan for positive oscillator values and blue for negative. ◆ Mean Reversion and Trend Signals: Visual markers and labels indicate when the oscillator suggests mean reversion or trend changes, aiding in identifying key market turning points. ◆ Invalidation Levels: Tracks the highest and lowest prices over a recent period to set levels where the current trend signal would be considered invalidated. ◆ Gradient Color Coding: Utilizes gradient color coding to enhance the visualization of oscillator values, making it easier to interpret overbought and oversold conditions. ◆ Usage Notes: Setting the Look-Back Period: Adjust the "Length" input based on the timeframe and the type of trading you are conducting. Shorter periods are more suited for intraday trading, while longer periods can be used for swing trading. Interpreting Thresholds: Use the upper and lower threshold inputs to fine-tune the sensitivity of the overbought and oversold signals. Higher absolute values reduce the number of signals but increase their reliability. Candlestick Coloring: Enabling the "Plot Bar Color" option can help quickly identify the current state of the oscillator in relation to the zero line. This visual aid can be particularly useful in fast-moving markets. Mean Reversion and Trend Signals: Pay attention to the symbols and labels on the chart indicating mean reversion and trend changes. These signals are designed to highlight potential entry and exit points. Invalidation Levels: Use the plotted invalidation levels as stop-loss or signal invalidation points. If the price moves beyond these levels, the current trend signal is likely invalid. This indicator helps traders identify overbought and oversold conditions, potential mean reversions, and trend changes based on the linear regression of the closing prices over a specified look-back period.
Penunjuk Pine Script®
oleh ChartPrime
76
Liquidity Hour by Ibramiho v2Liquidity Hour by Ibramiho (Version 2) - Identify High-Potential Reversal Zones Understanding the pre-New York session hour is crucial for institutional traders. This period is often characterized by increased liquidity and price volatility as major financial players prepare for the upcoming trading day. The Liquidity Hour indicator capitalizes on this phenomenon, automatically pinpointing the candle (by default, in orange) immediately before the New York session opens. Why Focus on This Candle? Liquidity Magnet: Institutional traders often use this hour to establish or adjust positions, creating pockets of liquidity. Breakout and Retracement Potential: The indicator helps you spot potential areas where price might retrace after a breakout, offering high-probability trading opportunities. Visual Clarity: The highlighted candle acts as a visual anchor, making it easy to identify these key levels on your chart. How It Works 1. Automatic Detection: The indicator intelligently detects the pre-New York session candle, regardless of your chart's timeframe. 2. Colour Coding: The candle is highlighted in orange (customizable), instantly drawing your attention. 3. Trade Insights: Watch for price breakouts above or below the highlighted candle. When price retraces back to this level, it signals a potential entry or exit point. Key Features Customizable Colour: Change the highlight colour to suit your chart preferences. Working Timeframes: Works on timeframes, from minutes up to 2 hours timeframe. Versatile Trading: Suitable for both intraday and swing trading strategies. Unlock the Power of Institutional Liquidity Don't miss out on the opportunities that arise in the hour before the New York session. With the Liquidity Hour indicator, you'll gain a valuable edge by identifying key levels where price action is most likely to reverse.
Penunjuk Pine Script®
oleh RaheemUSD
1
SMC Community [algoat] — Smart Money ConceptsEmpower your trading with the core principles of the Smart Money Concepts through interactive features and highly customizable settings. The indicator's strength lies in the unique SMC Core algorithm, a calculation based on real price action data, capturing every tick from small intraday fluctuations to significant high timeframe movements. algoat SMC Core is our continually evolving, specialized structure mapping algorithm, serving as the backbone of our price action related publications. ⭐ Key Features Swing Market Structure: Change of Character, Break of Structure Recognize and visualize real-time market structures with swing elements. Identify and mark key structural changes in the market to visually highlight shifts in market trends and patterns. This feature is designed to alert you to significant changes in the market's behavior, signaling a potential shift from accumulation to distribution phases, or vice versa. It helps traders adapt their strategies based on evolving market dynamics. Order Flow: Structure Fractal Connect the successive structural high and low levels, visualizing the intricate flow of market movements. This feature highlights fractal structures within the market, enabling traders to detect significant price action patterns. Structure Range: Determine Discount, Premium, and Equilibrium Zones This feature provides a unique way of visualizing price areas where a security could be overbought or oversold (premium or discount zones) and where the price is expected to be fair and balanced (equilibrium zone). Distance from the current price is displayed in percentage terms, which can assist traders with crucial data for risk management and strategic planning. The Range function helps you identify the most favorable price zones for entries and set your stop-loss and take-profit levels more accurately. Liquidity Grabs: Reveal Hidden Manipulation Attempts Identify uncovered market areas where high liquidity trading may take place. Liquidity Grabs help track "smart money" footprints by identifying levels where large institutional traders may have induced liquidity traps. Understanding these traps can aid in avoiding false market moves and optimizing trade entries. Institutional Interest Zones: Order Blocks and Fair Value Gaps Uncover areas where bigger orders may be lined up. Reveal zones of interest ordered by volume strength. Receive warnings about market price imbalances. ▸ Order Blocks pinpoint crucial zones where large institutional investors ("smart money") have shown strong buying or selling interest recently. These blocks can serve as a tool for identifying key areas for potential trade entries or exits. ▸ Fair Value Gaps detect discrepancies between the perceived market value and the actual market price, revealing potential areas for price correction. With its mitigation settings, you can fine-tune the FVG detection according to the magnitude of value misalignment you consider significant. Mitigation types dictate how price interacts with a zone, with order blocks requiring a close through (indicating stronger price movement) and fair value gaps requiring a wick through (hinting at weak rejection). ══════════════════ ⭐ Why SMC? In the ever-evolving trading landscape, mainstream methods and strategies can quickly become outdated as they are widely adopted. Liquidity is constantly sought after, and the best source for this is exploring and exploiting trading strategies that are widely accepted and applied. Currently, one of these strategies is the SMC (Supply, Demand, and Price Action). It's no coincidence that our educational materials incorporate concepts such as liquidity grabs (LG) and Smart Money Traps (SMT). As the application of SMC gains popularity among retail traders, trading with this approach becomes more challenging. Therefore, the recent focus has been on reforming the SMC methodology, as it is the only method that relies on real price movements and will always work when applied correctly. The indicator reflects our personal use and deep comprehension of Smart Money Concepts. It provides streamlined tools for tracking algorithmic trends with modern visualizations, without unnecessary clutter. ▸ What does the proper application of SMC entail? Many SMC traders associate their key areas of interest with the market structure, which is generally considered acceptable. However, depending solely on a single foundation can lead to significant deviations, which may cause notable impacts on trading results. Moreover, if the basis for the market structure calculation is inaccurate, the consequences can be even more severe. It's akin to risking money on a lottery ticket, believing it will be a winner. Our methodology is different, and it may ensure longevity in the financial markets. The structure remains crucial, but it is not the sole foundation of everything; instead, it serves as a validation tool. Each calculation, such as order blocks (OB), Fair Value Gaps (FVG), liquidity grabs (LG), range analysis, and more, is independent and unique, separate from the structure. However, validation must ultimately come from the structure itself. We employ individual and high-quality filters: before a function calculation is validated by the structure, it must undergo rigorous testing based on its own set of validation conditions. This approach aims to enhance robustness and accuracy, providing traders with a reliable framework for making informed trading decisions. ▸ An example of structure validation: Order Block with "Swing Sensitivity" These order blocks will only be displayed and utilized by the script if there is a swing structure validation with a valid break. In other words, the presence of a confirmed swing Change of Character (ChoCh) or Break of Structure (BoS) is essential for the Order Block to be considered valid and relevant. This approach ensures that the order blocks are aligned with the overall market structure and are not based on isolated or unreliable price movements. Whether it's Fair Value Gaps (FVG), Liquidity Grabs (LG), Range calculations, or other functionalities, the same underlying principle holds true. The background structure calculation serves as a validation mechanism for the data and insights generated by these functions, ensuring they adhere to the specific criteria and rules established within our methodology. By incorporating this robust validation process, traders can have confidence in the reliability and accuracy of the information provided by the indicator, allowing them to make informed trading decisions based on validated data and analysis. ══════════════════ 👉 Usage - the general approach Determine your trading style and build your basic strategy: The indicator helps you understand your trading style, whether it's swing trading, scalping or another approach. By analyzing the SMC indicator, you gain valuable information about potential market trends, entry and exit points, and overall market sentiment. Steps: Identify Trading Style: Determine whether you are a swing trader, scalper, or long-term investor. This will influence how you use the indicator. Analyze Market Trends: Use the SMC indicator to observe market trends and identify potential entry and exit points. Adapt Strategies: Adjust your strategies based on the market dynamics revealed by the SMC indicator, such as changes in order flow or market structure. 👉 Example of usage In the following chart, you'll notice how we've utilized the indicator to formulate a strategic trading approach. We've employed Order Blocks equipped with volume parameters to identify crucial market zones. Simultaneously, we've leveraged swing/internal market structures to gain insights into potential long- and short-term market turnarounds. Lastly, we've examined trend line liquidity zones to pinpoint probable impulses and breakouts within ongoing trends. Now we can see how the price descended to the order block with the highest volume, which we had previously marked as our point of interest for an entry. As the price closed below the median Order Block, we noted its mitigation. After an internal CHoCH, it's directing us towards the main Order Block as a target. ══════════════════ 🧠 General advice Trading effectively requires a range of techniques, experience, and expertise. From technical analysis to market fundamentals, traders must navigate multiple factors, including market sentiment and economic conditions. However, traders often find themselves overwhelmed by market noise, making it challenging to filter out distractions and make informed decisions. By integrating multiple analytical approaches, traders can tailor their strategies to fit their unique trading styles and objectives. Confirming signals with other indicators As with all technical indicators, it is important to confirm potential signals with other analytical tools, such as support and resistance levels, as well as indicators like RSI, MACD, and volume. This helps increase the probability of a successful trade. Use proper risk management When using this or any other indicator, it is crucial to have proper risk management in place. Consider implementing stop-loss levels and thoughtful position sizing. Combining with other technical indicators Integrate this indicator with other technical indicators to develop a comprehensive trading strategy and provide additional confirmation. Conduct Thorough Research and Backtesting Ensure a solid understanding of the indicator and its behavior through thorough research and backtesting before making trading decisions. Consider incorporating fundamental analysis and market sentiment into your trading approach. ══════════════════ ⭐ Conclusion We hold the view that the true path to success is the synergy between the trader and the tool, contrary to the common belief that the tool itself is the sole determinant of profitability. The actual scenario is more nuanced than such an oversimplification. A word to the wise is enough: developed by traders, for traders — pioneering innovations for the modern era. Risk Notice Everything provided by algoat — from scripts, tools, and articles to educational materials — is intended solely for educational and informational purposes. Past performance does not assure future returns.
Penunjuk Pine Script®
oleh algoat
12
TS & AO This is Best Intraday and Swing Trading Indicator Certainly! Let’s explore some intraday and swing trading indicators that can help traders make informed decisions SuperTrend: The Supertrend indicator is commonly used for intraday trading. It is plotted on the price chart and helps determine the current trend. Parameters: It uses the Average True Range (ATR) with default values of 10 for the period and 3 for the multiplier. Interpretation: Upward trend: When Supertrend is below the bars and changes color to green, it indicates a buy signal. Downward trend: When Supertrend is above the bars and turns red, it signals a sell opportunity1. VWAP (Volume Weighted Average Price): VWAP is a volume-based indicator. It compares the value of a stock traded at a specific time to the total volume traded for that stock. Interpretation: Bullish trend: When the stock price is above VWAP, it suggests an uptrend. Traders can consider buying on retracements toward VWAP in the direction of the trend1. Moving Averages (MAs): MAs are versatile indicators suitable for intraday, swing, and longer-term trading. Common MAs include: 9-day MA: Short-term trend indicator. 50-day MA: Intermediate trend indicator. 100-day MA: Longer-term trend indicator. Interpretation: Uptrend: When the stock price is above the MA, it signals a bullish trend. Downtrend: When the price is below the MA, it suggests a bearish trend2.
Penunjuk Pine Script®
oleh bigprofitstocks
1
[MAD] Entrytool / Bybit-LinearThis indicator, "Entry Tool," was coded at request for Sandmann . It is designed to provide traders with real-time feedback for strategizing entries, exits, and liquidation levels for trades initiated at that given moment. The tool visualizes average entry prices, stop-loss levels, multiple take-profit targets, and potential liquidation prices, offering a comprehensive overview of possible trade outcomes. It aids traders in pre-planning their trades by visually simulating the impact of different trading decisions directly on the live chart. Each setting and parameter can be customized to align with individual trading strategies and risk tolerances, making this tool versatile for various trading styles, including day trading, swing trading, and position trading. ------------------------------ Steps to Use the Indicator: 1. Basic Setup: Setup Type: Choose between "Long" or "Short" to set the direction of the trade. Leverage: Adjust the leverage to understand its impact on your potential returns and liquidation price. Tracking follows the close price, alternative you can enter a specific price. 2. Position Setup: Initial Entry Amount: Set the starting amount for the trade. Distance: First Increment Percentage from Entry price Amount: Define the increase for the first incremental addition to the position and specify the amount to be added. Distance: Second Increment Percentage from Entry Amount: Set the increase for the second incremental addition and the corresponding amount. 3. Risk Management: Stop-Loss (SL) Percentage: Set the percentage below or above the average entry price at which the position should be closed to minimize losses. Take-Profit (TP) Percentages: Define up to four different profit target levels by specifying the percentage above or below the average entry price. 4. Visual Settings: Box Colors: Customize the colors of the boxes that represent long and short positions to differentiate easily on the chart. Box Extension: Determine the length by which the box extends beyond the current bar, which helps in visualizing the potential price movement. Line Colors and Extensions: Select colors for various lines such as the Average Entry Line, Stop-Loss Line, Take-Profit Lines, and Liquidations Line. Adjust the length of these lines for better visibility. Label Settings: Configure the distance of labels from their corresponding lines and set the font size for better readability. 5. Additional Features: Liquidation Price Visualization: This new feature calculates and displays the liquidation price based on the current leverage and margin settings, giving traders a critical insight into their risk exposure. Interactive Drag Point: Adjust the start price manually by dragging the point on the chart, which dynamically updates entry and exit levels as well as risk metrics. Detailed Leverage Data Array: Input different scenarios with specific leverage, initial margin, and maintenance rates to see how these factors impact potential liquidation points. 6. Informations about leverage calculation The data used are fetched from Bybit for Linear pairs to calculate the liquidations like in their documentation. Keep in mind that other exchanges may calulate based on another formular.
Penunjuk Pine Script®
oleh djmad
3
Enhanced Forex IndicatorDescription of the "Enhanced Forex Indicator" The "Enhanced Forex Indicator" is designed for traders who want a comprehensive technical analysis tool on the TradingView platform. This script integrates Exponential Moving Averages (EMAs), support and resistance zones, and candlestick pattern recognition to provide actionable trading signals, particularly useful for Forex and other financial markets. The script is suitable for intraday trading and swing trading. Components of the Indicator Exponential Moving Averages (EMAs): Short EMA (Blue Line): Faster responding average, good for identifying recent trend changes. Long EMA (Red Line): Slower moving average, helps in confirming longer-term trends. Support and Resistance Zones: Resistance Zone (Red): Area where potential selling pressure could overcome buying pressure, halting price increases temporarily or reversing them. Support Zone (Green): Area where potential buying pressure could overcome selling pressure, supporting prices and preventing them from falling further. Candlestick Patterns: Bullish Engulfing Pattern (Green Triangle Up 'BE'): Suggests a potential upward reversal or start of a bullish trend. Bearish Engulfing Pattern (Red Triangle Down 'BE'): Indicates a potential downward reversal or start of a bearish trend. Buy/Sell Signals: Buy Signal (Green Label 'BUY'): Triggered when the price is above both EMAs and a bullish engulfing pattern is detected. Sell Signal (Red Label 'SELL'): Triggered when the price is below both EMAs and a bearish engulfing pattern is detected. Trading Setup: Entry: Consider entering a buy position when the 'BUY' signal appears, indicating bullish conditions. Enter a sell position when the 'SELL' signal appears, indicating bearish conditions. Exit: Look for closing signals opposite your entry or use predefined take profit and stop loss levels. For instance, exit a buy position on a 'SELL' signal or when the price drops below the support zone. Risk Management: Set stop losses just below the support zone for buy orders and above the resistance zone for sell orders to protect against significant losses. Adjust position sizes according to your risk tolerance and account balance. Considerations: Use this indicator in conjunction with other analysis tools and fundamental data to confirm signals and strengthen your trading strategy. Periodically backtest the strategy based on this indicator to ensure its effectiveness in current market conditions. Optimization: Adjust the lengths of the EMAs and the buffer size of the support and resistance zones to better fit the asset's volatility and your trading timeframe.
Penunjuk Pine Script®
oleh Trade_Monk_Sensei
Multi-Timeframe Trend TableThe "Multi-Timeframe Trend Table" indicator is a tool that consolidates a variety of critical trading metrics into a single, easy-to-read table format. This indicator is especially useful for traders who need to analyze multiple timeframes and indicators simultaneously to make informed trading decisions. By displaying a broad spectrum of data including trend information, rangebound status, volatility levels, VWAP (Volume Weighted Average Price), and specific candlestick patterns, the indicator provides a comprehensive overview of market conditions across different timeframes. Functionality and Components At its core, the indicator provides real-time insights into market trends by showing whether each timeframe is experiencing an upward, downward, or neutral trend based on simple moving averages. This is complemented by the "Rangebound" status, which indicates whether the price is trading within a defined range, giving insights into market consolidation periods. This can be critical for identifying breakouts or breakdowns from established ranges. Volatility Measurement Another key feature of the indicator is the "Volatility" column, which rates the market's volatility on a scale from 1 to 10. This feature uses the Average True Range (ATR) to assess how drastically prices are changing within a given timeframe, providing a numerical value that helps traders understand the intensity of price movements. High volatility levels (scores above 6) are highlighted, which can be crucial for strategies that prefer high volatility. VWAP and Candlestick Patterns The indicator also displays the VWAP, which is essential for traders who focus on volume as it shows the average price a security has traded at throughout the day, based on both volume and price. It is especially useful for traders looking to confirm trend directions or catch potential reversals. Additionally, the "Candle" column enhances the indicator's utility by identifying specific candlestick patterns like Doji, Hammer, Inverted Hammer, Bullish Engulfing, and Bearish Engulfing, which are pivotal for pinpointing momentum changes and potential entry or exit points. Usage Strategy Traders can utilize this indicator by setting up specific rules based on the information provided. For instance, a possible strategy could involve entering a trade when a Bullish Engulfing pattern appears in a low-volatility environment as indicated by a volatility score under 6, suggesting a potential uptrend start with limited downside risk. Similarly, a trader might consider exiting a position or taking a short position when a Bearish Engulfing pattern is identified during high volatility periods, signaling possible sharp price declines. Adaptability and Customization An added advantage is the indicator’s adaptability; traders can customize which columns to display based on their trading preferences and strategies. Whether focusing on trends, volatility, or candlestick patterns, users can configure the table to match their specific needs. This makes it a versatile tool suited for various trading styles and objectives, from day trading to swing trading. Overall Utility Overall, the "Multi-Timeframe Trend Table" indicator is an invaluable asset for traders who manage multiple instruments across different timeframes, offering a bird's-eye view of the markets in one concise table. It aids in quick decision-making by providing all necessary data points at a glance, reducing the need to switch between multiple charts and potentially missing critical market movements. By integrating trend analysis with volatility and candlestick patterns, it equips traders with a powerful synthesis of technical analysis tools to enhance their trading strategies and improve market timing.
Penunjuk Pine Script®
oleh brhodes88
5
Master Candle Breakout Trading Strategy - Omkar BanneDiscover the Power of Master Candle Trading with Our Indicator! 📈 What does it do? This indicator scans price action to identify 'Master Candle' formations, a powerful signal indicating potential trend continuations. A Master Candle occurs when the high and low of the next 4 candles are within the range of the previous candle, suggesting a period of consolidation followed by a breakout. How can it be used? Swing Trading Capture significant price movements by entering trades at the breakout of Master Candle formations. It can also be used for Intraday trading. Trend Reversals Identify potential trend reversals early by recognizing Master Candle patterns. Entry The indicator displays the entry price depending on the high of the master candle. Risk Management Set stop-loss levels and take-profit targets based on the size of the Master Candle, enhancing risk management. Customizable Threshold Adjust tolerance levels for high and low prices to suit your trading style. Background It highlights the master candle using a different background colour. Box It draws a box around the pattern formation. Theme Options Choose between light and dark themes for optimal visibility. Whether you're a beginner or an experienced trader, our Master Candle Trading Strategy Indicator can enhance your trading arsenal and improve your profitability.
Penunjuk Pine Script®
oleh OmkarBanne
4
DEMA RSI Overlay [BackQuant]DEMA RSI Overlay PLEASE Read the following, knowing what an indicator does at its core before adding it into a system is pivotal. The core concepts can allow you to include it in a logical and sound manner. Anyways, BackQuant's new trading indicator that blends the Double Exponential Moving Average (DEMA) with the Relative Strength Index (RSI) to create a unique overlay on the trading chart. This combination is not arbitrary; both the DEMA and RSI are revered for their distinct advantages in trading strategy development. Let's delve into the core components of this script, the rationale behind choosing DEMA and RSI, the logic of long and short signals, and its practical trading applications. Understanding DEMA DEMA is an enhanced version of the conventional exponential moving average that aims to reduce the lag inherent in traditional averages. It does this by applying more weight to recent prices. The reduction in lag makes DEMA an excellent tool for tracking price trends more closely. In the context of this script, DEMA serves as the foundation for the RSI calculation, offering a smoother and more responsive signal line that can provide clearer trend indications. Why DEMA? DEMA is chosen for its responsiveness to price changes. This characteristic is particularly beneficial in fast-moving markets where entering and exiting positions quickly is crucial. By using DEMA as the price source, the script ensures that the signals generated are timely and reflective of the current market conditions, reducing the risk of entering or exiting a trade based on outdated information. Integrating RSI The RSI, a momentum oscillator, measures the speed and change of price movements. It oscillates between zero and 100 and is typically used to identify overbought or oversold conditions. In this script, the RSI is calculated based on DEMA, which means it inherits the responsiveness of DEMA, allowing traders to spot potential reversals or continuation signals sooner. Why RSI? Incorporating RSI offers a measure of price momentum and market conditions relative to past performance. By setting thresholds for long (buy) and short (sell) signals, the script uses RSI to identify potential turning points in the market, providing traders with strategic entry and exit points. Calculating Long and Short Signals Long Signals : These are generated when the RSI of the DEMA crosses above the longThreshold (set at 70 by default) and the closing price is not above the upper volatility band. This suggests that the asset is gaining upward momentum while not being excessively overbought, presenting a potentially favorable buying opportunity. Short Signals : Generated when the RSI of the DEMA falls below the shortThreshold (set at 55 by default). This indicates that the asset may be losing momentum or entering a downtrend, signaling a possible selling or shorting opportunity. Logical Soundness The logic of combining DEMA with RSI for generating trade signals is sound for several reasons: Timeliness : The use of DEMA ensures that the price source for RSI calculation is up-to-date, making the momentum signals more relevant. Balance : By setting distinct thresholds for long and short signals, the script balances sensitivity and specificity, aiming to minimize false signals while capturing genuine market movements. Adaptability : The inclusion of user inputs for periods and thresholds allows traders to customize the indicator to fit various trading styles and timeframes. Trading Use-Cases This DEMA RSI Overlay indicator is versatile and can be applied across different markets and timeframes. Its primary use-cases include: Trend Following: Traders can use it to identify the start of a new trend or the continuation of an existing trend. Swing Trading: The indicator's sensitivity to price changes makes it ideal for swing traders looking to capitalize on short to medium-term price movements. Risk Management: By providing clear long and short signals, it helps traders manage their positions more effectively, potentially reducing the risk of significant losses. Final Note We have also decided to add in the option of standard deviation bands, calculated on the DEMA, this can be used as a point of confluence rendering trading ranges. Expanding when volatility is high and compressing when it is low. For example: This provides the user with a 1, 2, 3 standard deviation band of the DEMA. 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
Penunjuk Pine Script®
oleh BackQuant
2
GKD-B Multi-Ticker Stepped Baseline [Loxx]Giga Kaleidoscope GKD-B Multi-Ticker Stepped Baseline is a Baseline module included in Loxx's "Giga Kaleidoscope Modularized Trading System". This version of the GKD-B Baseline is designed specifically to support traders who wish to conduct GKD-BT Multi-Ticker Backtests with multiple tickers. This functionality is exclusive to the GKD-BT Multi-Ticker Backtests. Traders have the capability to apply a filter to the selected moving average, leveraging various volatility metrics to enhance trend identification. This feature is tailored for traders favoring a gradual and consistent approach, enabling them to discern more sustainable trends. The system permits filtering for both the input data and the moving average results, requiring price movements to exceed a specific threshold—defined as multiples of the volatility—before acknowledging a trend change. This mechanism effectively reduces false signals caused by market noise and lateral movements. A distinctive aspect of this tool is its ability to adjust both price and moving average data based on volatility indicators like VIX, EUVIX, BVIV, and EVIV, among others. Understanding the time frame over which a volatility index is measured is crucial; for instance, VIX is measured on an annual basis, whereas BVIV and EVIV are based on a 30-day period. To accurately convert these measurements to a daily scale, users must input the correct "days per year" value: 252 for VIX and 30 for BVIV and EVIV. Future updates will introduce additional functionality to extend analysis across various time frames, but currently, this feature is solely available for daily time frame analysis. █ GKD-B Multi-Ticker Stepped Baseline includes 65+ different moving averages: Adaptive Moving Average - AMA ADXvma - Average Directional Volatility Moving Average Ahrens Moving Average Alexander Moving Average - ALXMA Deviation Scaled Moving Average - DSMA Donchian Double Exponential Moving Average - DEMA Double Smoothed Exponential Moving Average - DSEMA Double Smoothed FEMA - DSFEMA Double Smoothed Range Weighted EMA - DSRWEMA Double Smoothed Wilders EMA - DSWEMA Double Weighted Moving Average - DWMA Ehlers Optimal Tracking Filter - EOTF Exponential Moving Average - EMA Fast Exponential Moving Average - FEMA Fractal Adaptive Moving Average - FRAMA Generalized DEMA - GDEMA Generalized Double DEMA - GDDEMA Hull Moving Average (Type 1) - HMA1 Hull Moving Average (Type 2) - HMA2 Hull Moving Average (Type 3) - HMA3 Hull Moving Average (Type 4) - HMA4 IE /2 - Early T3 by Tim Tilson Integral of Linear Regression Slope - ILRS Kaufman Adaptive Moving Average - KAMA Laguerre Filter Leader Exponential Moving Average Linear Regression Value - LSMA ( Least Squares Moving Average ) Linear Weighted Moving Average - LWMA McGinley Dynamic McNicholl EMA Non-Lag Moving Average Ocean NMA Moving Average - ONMAMA One More Moving Average - OMA Parabolic Weighted Moving Average Probability Density Function Moving Average - PDFMA Quadratic Regression Moving Average - QRMA Regularized EMA - REMA Range Weighted EMA - RWEMA Recursive Moving Trendline Simple Decycler - SDEC Simple Jurik Moving Average - SJMA Simple Moving Average - SMA Sine Weighted Moving Average Smoothed LWMA - SLWMA Smoothed Moving Average - SMMA Smoother Super Smoother T3 Three-pole Ehlers Butterworth Three-pole Ehlers Smoother Triangular Moving Average - TMA Triple Exponential Moving Average - TEMA Two-pole Ehlers Butterworth Two-pole Ehlers smoother Variable Index Dynamic Average - VIDYA Variable Moving Average - VMA Volume Weighted EMA - VEMA Volume Weighted Moving Average - VWMA Zero-Lag DEMA - Zero Lag Exponential Moving Average Zero-Lag Moving Average Zero Lag TEMA - Zero Lag Triple Exponential Moving Average Geometric Mean Moving Average Coral Tether Lines Range Filter Triangle Moving Average Generalized Ultinate Smoother Adaptive Moving Average - AMA The Adaptive Moving Average (AMA) is a moving average that changes its sensitivity to price moves depending on the calculated volatility. It becomes more sensitive during periods when the price is moving smoothly in a certain direction and becomes less sensitive when the price is volatile. ADXvma - Average Directional Volatility Moving Average Linnsoft's ADXvma formula is a volatility-based moving average, with the volatility being determined by the value of the ADX indicator. The ADXvma has the SMA in Chande's CMO replaced with an EMA , it then uses a few more layers of EMA smoothing before the "Volatility Index" is calculated. A side effect is, those additional layers slow down the ADXvma when you compare it to Chande's Variable Index Dynamic Average VIDYA . The ADXVMA provides support during uptrends and resistance during downtrends and will stay flat for longer, but will create some of the most accurate market signals when it decides to move. Ahrens Moving Average Richard D. Ahrens's Moving Average promises "Smoother Data" that isn't influenced by the occasional price spike. It works by using the Open and the Close in his formula so that the only time the Ahrens Moving Average will change is when the candlestick is either making new highs or new lows. Alexander Moving Average - ALXMA This Moving Average uses an elaborate smoothing formula and utilizes a 7 period Moving Average. It corresponds to fitting a second-order polynomial to seven consecutive observations. This moving average is rarely used in trading but is interesting as this Moving Average has been applied to diffusion indexes that tend to be very volatile. Deviation Scaled Moving Average - DSMA The Deviation-Scaled Moving Average is a data smoothing technique that acts like an exponential moving average with a dynamic smoothing coefficient. The smoothing coefficient is automatically updated based on the magnitude of price changes. In the Deviation-Scaled Moving Average, the standard deviation from the mean is chosen to be the measure of this magnitude. The resulting indicator provides substantial smoothing of the data even when price changes are small while quickly adapting to these changes. Donchian Donchian Channels are three lines generated by moving average calculations that comprise an indicator formed by upper and lower bands around a midrange or median band. The upper band marks the highest price of a security over N periods while the lower band marks the lowest price of a security over N periods. Double Exponential Moving Average - DEMA The Double Exponential Moving Average ( DEMA ) combines a smoothed EMA and a single EMA to provide a low-lag indicator. It's primary purpose is to reduce the amount of "lagging entry" opportunities, and like all Moving Averages, the DEMA confirms uptrends whenever price crosses on top of it and closes above it, and confirms downtrends when the price crosses under it and closes below it - but with significantly less lag. Double Smoothed Exponential Moving Average - DSEMA The Double Smoothed Exponential Moving Average is a lot less laggy compared to a traditional EMA . It's also considered a leading indicator compared to the EMA , and is best utilized whenever smoothness and speed of reaction to market changes are required. Double Smoothed FEMA - DSFEMA Same as the Double Exponential Moving Average (DEMA), but uses a faster version of EMA for its calculation. Double Smoothed Range Weighted EMA - DSRWEMA Range weighted exponential moving average (EMA) is, unlike the "regular" range weighted average calculated in a different way. Even though the basis - the range weighting - is the same, the way how it is calculated is completely different. By definition this type of EMA is calculated as a ratio of EMA of price*weight / EMA of weight. And the results are very different and the two should be considered as completely different types of averages. The higher than EMA to price changes responsiveness when the ranges increase remains in this EMA too and in those cases this EMA is clearly leading the "regular" EMA. This version includes double smoothing. Double Smoothed Wilders EMA - DSWEMA Welles Wilder was frequently using one "special" case of EMA (Exponential Moving Average) that is due to that fact (that he used it) sometimes called Wilder's EMA. This version is adding double smoothing to Wilder's EMA in order to make it "faster" (it is more responsive to market prices than the original) and is still keeping very smooth values. Double Weighted Moving Average - DWMA Double weighted moving average is an LWMA (Linear Weighted Moving Average). Instead of doing one cycle for calculating the LWMA, the indicator is made to cycle the loop 2 times. That produces a smoother values than the original LWMA Ehlers Optimal Tracking Filter - EOTF The Elher's Optimum Tracking Filter quickly adjusts rapid shifts in the price and yet is relatively smooth when the price has a sideways action. The operation of this filter is similar to Kaufman’s Adaptive Moving Average Exponential Moving Average - EMA The EMA places more significance on recent data points and moves closer to price than the SMA ( Simple Moving Average ). It reacts faster to volatility due to its emphasis on recent data and is known for its ability to give greater weight to recent and more relevant data. The EMA is therefore seen as an enhancement over the SMA . Fast Exponential Moving Average - FEMA An Exponential Moving Average with a short look-back period. Fractal Adaptive Moving Average - FRAMA The Fractal Adaptive Moving Average by John Ehlers is an intelligent adaptive Moving Average which takes the importance of price changes into account and follows price closely enough to display significant moves whilst remaining flat if price ranges. The FRAMA does this by dynamically adjusting the look-back period based on the market's fractal geometry. Generalized DEMA - GDEMA The double exponential moving average (DEMA), was developed by Patrick Mulloy in an attempt to reduce the amount of lag time found in traditional moving averages. It was first introduced in the February 1994 issue of the magazine Technical Analysis of Stocks & Commodities in Mulloy's article "Smoothing Data with Faster Moving Averages.". Instead of using fixed multiplication factor in the final DEMA formula, the generalized version allows you to change it. By varying the "volume factor" form 0 to 1 you apply different multiplications and thus producing DEMA with different "speed" - the higher the volume factor is the "faster" the DEMA will be (but also the slope of it will be less smooth). The volume factor is limited in the calculation to 1 since any volume factor that is larger than 1 is increasing the overshooting to the extent that some volume factors usage makes the indicator unusable. Generalized Double DEMA - GDDEMA The double exponential moving average (DEMA), was developed by Patrick Mulloy in an attempt to reduce the amount of lag time found in traditional moving averages. It was first introduced in the February 1994 issue of the magazine Technical Analysis of Stocks & Commodities in Mulloy's article "Smoothing Data with Faster Moving Averages''. This is an extension of the Generalized DEMA using Tim Tillsons (the inventor of T3) idea, and is using GDEMA of GDEMA for calculation (which is the "middle step" of T3 calculation). Since there are no versions showing that middle step, this version covers that too. The result is smoother than Generalized DEMA, but is less smooth than T3 - one has to do some experimenting in order to find the optimal way to use it, but in any case, since it is "faster" than the T3 (Tim Tillson T3) and still smooth, it looks like a good compromise between speed and smoothness. Hull Moving Average (Type 1) - HMA1 Alan Hull's HMA makes use of weighted moving averages to prioritize recent values and greatly reduce lag whilst maintaining the smoothness of a traditional Moving Average. For this reason, it's seen as a well-suited Moving Average for identifying entry points. This version uses SMA for smoothing. Hull Moving Average (Type 2) - HMA2 Alan Hull's HMA makes use of weighted moving averages to prioritize recent values and greatly reduce lag whilst maintaining the smoothness of a traditional Moving Average. For this reason, it's seen as a well-suited Moving Average for identifying entry points. This version uses EMA for smoothing. Hull Moving Average (Type 3) - HMA3 Alan Hull's HMA makes use of weighted moving averages to prioritize recent values and greatly reduce lag whilst maintaining the smoothness of a traditional Moving Average. For this reason, it's seen as a well-suited Moving Average for identifying entry points. This version uses LWMA for smoothing. Hull Moving Average (Type 4) - HMA4 Alan Hull's HMA makes use of weighted moving averages to prioritize recent values and greatly reduce lag whilst maintaining the smoothness of a traditional Moving Average. For this reason, it's seen as a well-suited Moving Average for identifying entry points. This version uses SMMA for smoothing. IE /2 - Early T3 by Tim Tilson and T3 new The T3 moving average is a type of technical indicator used in financial analysis to identify trends in price movements. It is similar to the Exponential Moving Average (EMA) and the Double Exponential Moving Average (DEMA), but uses a different smoothing algorithm. The T3 moving average is calculated using a series of exponential moving averages that are designed to filter out noise and smooth the data. The resulting smoothed data is then weighted with a non-linear function to produce a final output that is more responsive to changes in trend direction. The T3 moving average can be customized by adjusting the length of the moving average, as well as the weighting function used to smooth the data. It is commonly used in conjunction with other technical indicators as part of a larger trading strategy. Integral of Linear Regression Slope - ILRS A Moving Average where the slope of a linear regression line is simply integrated as it is fitted in a moving window of length N (natural numbers in maths) across the data. The derivative of ILRS is the linear regression slope. ILRS is not the same as a SMA ( Simple Moving Average ) of length N, which is actually the midpoint of the linear regression line as it moves across the data. Kaufman Adaptive Moving Average - KAMA Developed by Perry Kaufman, Kaufman's Adaptive Moving Average (KAMA) is a moving average designed to account for market noise or volatility. KAMA will closely follow prices when the price swings are relatively small and the noise is low. Laguerre Filter The Laguerre Filter is a smoothing filter which is based on Laguerre polynomials. The filter requires the current price, three prior prices, a user defined factor called Alpha to fill its calculation. Adjusting the Alpha coefficient is used to increase or decrease its lag and its smoothness. Leader Exponential Moving Average The Leader EMA was created by Giorgos E. Siligardos who created a Moving Average which was able to eliminate lag altogether whilst maintaining some smoothness. It was first described during his research paper "MACD Leader" where he applied this to the MACD to improve its signals and remove its lagging issue. This filter uses his leading MACD's "modified EMA" and can be used as a zero lag filter. Linear Regression Value - LSMA ( Least Squares Moving Average ) LSMA as a Moving Average is based on plotting the end point of the linear regression line. It compares the current value to the prior value and a determination is made of a possible trend, eg. the linear regression line is pointing up or down. Linear Weighted Moving Average - LWMA LWMA reacts to price quicker than the SMA and EMA . Although it's similar to the Simple Moving Average , the difference is that a weight coefficient is multiplied to the price which means the most recent price has the highest weighting, and each prior price has progressively less weight. The weights drop in a linear fashion. McGinley Dynamic John McGinley created this Moving Average to track prices better than traditional Moving Averages. It does this by incorporating an automatic adjustment factor into its formula, which speeds (or slows) the indicator in trending, or ranging, markets. McNicholl EMA Dennis McNicholl developed this Moving Average to use as his center line for his "Better Bollinger Bands" indicator and was successful because it responded better to volatility changes over the standard SMA and managed to avoid common whipsaws. Non-lag moving average The Non Lag Moving average follows price closely and gives very quick signals as well as early signals of price change. As a standalone Moving Average, it should not be used on its own, but as an additional confluence tool for early signals. Ocean NMA Moving Average - ONMAMA Created by Jim Sloman, the NMA is a moving average that automatically adjusts to volatility without being programmed to do so. For more info, read his guide "Ocean Theory, an Introduction" One More Moving Average (OMA) The One More Moving Average (OMA) is a technical indicator that calculates a series of Jurik-style moving averages in order to reduce noise and provide smoother price data. It uses six exponential moving averages to generate the final value, with the length of the moving averages determined by an adaptive algorithm that adjusts to the current market conditions. The algorithm calculates the average period by comparing the signal to noise ratio and using this value to determine the length of the moving averages. The resulting values are used to generate the final value of the OMA, which can be used to identify trends and potential changes in trend direction. Parabolic Weighted Moving Average The Parabolic Weighted Moving Average is a variation of the Linear Weighted Moving Average . The Linear Weighted Moving Average calculates the average by assigning different weights to each element in its calculation. The Parabolic Weighted Moving Average is a variation that allows weights to be changed to form a parabolic curve. It is done simply by using the Power parameter of this indicator. Probability Density Function Moving Average - PDFMA Probability density function based MA is a sort of weighted moving average that uses probability density function to calculate the weights. By its nature it is similar to a lot of digital filters. Quadratic Regression Moving Average - QRMA A quadratic regression is the process of finding the equation of the parabola that best fits a set of data. This moving average is an obscure concept that was posted to Forex forums in around 2008. Regularized EMA - REMA The regularized exponential moving average (REMA) by Chris Satchwell is a variation on the EMA (see Exponential Moving Average) designed to be smoother but not introduce too much extra lag. Range Weighted EMA - RWEMA This indicator is a variation of the range weighted EMA. The variation comes from a possible need to make that indicator a bit less "noisy" when it comes to slope changes. The method used for calculating this variation is the method described by Lee Leibfarth in his article "Trading With An Adaptive Price Zone". Recursive Moving Trendline Dennis Meyers's Recursive Moving Trendline uses a recursive (repeated application of a rule) polynomial fit, a technique that uses a small number of past values estimations of price and today's price to predict tomorrow's price. Simple Decycler - SDEC The Ehlers Simple Decycler study is a virtually zero-lag technical indicator proposed by John F. Ehlers. The original idea behind this study (and several others created by John F. Ehlers) is that market data can be considered a continuum of cycle periods with different cycle amplitudes. Thus, trending periods can be considered segments of longer cycles, or, in other words, low-frequency segments. Applying the right filter might help identify these segments. Simple Loxx Moving Average - SLMA A three stage moving average combining an adaptive EMA, a Kalman Filter, and a Kauffman adaptive filter. Simple Moving Average - SMA The SMA calculates the average of a range of prices by adding recent prices and then dividing that figure by the number of time periods in the calculation average. It is the most basic Moving Average which is seen as a reliable tool for starting off with Moving Average studies. As reliable as it may be, the basic moving average will work better when it's enhanced into an EMA . Sine Weighted Moving Average The Sine Weighted Moving Average assigns the most weight at the middle of the data set. It does this by weighting from the first half of a Sine Wave Cycle and the most weighting is given to the data in the middle of that data set. The Sine WMA closely resembles the TMA (Triangular Moving Average). Smoothed LWMA - SLWMA A smoothed version of the LWMA Smoothed Moving Average - SMMA The Smoothed Moving Average is similar to the Simple Moving Average ( SMA ), but aims to reduce noise rather than reduce lag. SMMA takes all prices into account and uses a long lookback period. Due to this, it's seen as an accurate yet laggy Moving Average. Smoother The Smoother filter is a faster-reacting smoothing technique which generates considerably less lag than the SMMA ( Smoothed Moving Average ). It gives earlier signals but can also create false signals due to its earlier reactions. This filter is sometimes wrongly mistaken for the superior Jurik Smoothing algorithm. Super Smoother The Super Smoother filter uses John Ehlers’s “Super Smoother” which consists of a Two pole Butterworth filter combined with a 2-bar SMA ( Simple Moving Average ) that suppresses the 22050 Hz Nyquist frequency: A characteristic of a sampler, which converts a continuous function or signal into a discrete sequence. Three-pole Ehlers Butterworth The 3 pole Ehlers Butterworth (as well as the Two pole Butterworth) are both superior alternatives to the EMA and SMA . They aim at producing less lag whilst maintaining accuracy. The 2 pole filter will give you a better approximation for price, whereas the 3 pole filter has superior smoothing. Three-pole Ehlers smoother The 3 pole Ehlers smoother works almost as close to price as the above mentioned 3 Pole Ehlers Butterworth. It acts as a strong baseline for signals but removes some noise. Side by side, it hardly differs from the Three Pole Ehlers Butterworth but when examined closely, it has better overshoot reduction compared to the 3 pole Ehlers Butterworth. Triangular Moving Average - TMA The TMA is similar to the EMA but uses a different weighting scheme. Exponential and weighted Moving Averages will assign weight to the most recent price data. Simple moving averages will assign the weight equally across all the price data. With a TMA (Triangular Moving Average), it is double smoother (averaged twice) so the majority of the weight is assigned to the middle portion of the data. Triple Exponential Moving Average - TEMA The TEMA uses multiple EMA calculations as well as subtracting lag to create a tool which can be used for scalping pullbacks. As it follows price closely, its signals are considered very noisy and should only be used in extremely fast-paced trading conditions. Two-pole Ehlers Butterworth The 2 pole Ehlers Butterworth (as well as the three pole Butterworth mentioned above) is another filter that cuts out the noise and follows the price closely. The 2 pole is seen as a faster, leading filter over the 3 pole and follows price a bit more closely. Analysts will utilize both a 2 pole and a 3 pole Butterworth on the same chart using the same period, but having both on chart allows its crosses to be traded. Two-pole Ehlers smoother A smoother version of the Two pole Ehlers Butterworth. This filter is the faster version out of the 3 pole Ehlers Butterworth. It does a decent job at cutting out market noise whilst emphasizing a closer following to price over the 3 pole Ehlers . Variable Index Dynamic Average - VIDYA Variable Index Dynamic Average Technical Indicator ( VIDYA ) was developed by Tushar Chande. It is an original method of calculating the Exponential Moving Average ( EMA ) with the dynamically changing period of averaging. Variable Moving Average - VMA The Variable Moving Average (VMA) is a study that uses an Exponential Moving Average being able to automatically adjust its smoothing factor according to the market volatility. Volume Weighted EMA - VEMA An EMA that uses a volume and price weighted calculation instead of the standard price input. Volume Weighted Moving Average - VWMA A Volume Weighted Moving Average is a moving average where more weight is given to bars with heavy volume than with light volume. Thus the value of the moving average will be closer to where most trading actually happened than it otherwise would be without being volume weighted. Zero-Lag DEMA - Zero Lag Double Exponential Moving Average John Ehlers's Zero Lag DEMA's aim is to eliminate the inherent lag associated with all trend following indicators which average a price over time. Because this is a Double Exponential Moving Average with Zero Lag, it has a tendency to overshoot and create a lot of false signals for swing trading. It can however be used for quick scalping or as a secondary indicator for confluence. Zero-Lag Moving Average The Zero Lag Moving Average is described by its creator, John Ehlers , as a Moving Average with absolutely no delay. And it's for this reason that this filter will cause a lot of abrupt signals which will not be ideal for medium to long-term traders. This filter is designed to follow price as close as possible whilst de-lagging data instead of basing it on regular data. The way this is done is by attempting to remove the cumulative effect of the Moving Average. Zero-Lag TEMA - Zero Lag Triple Exponential Moving Average Just like the Zero Lag DEMA , this filter will give you the fastest signals out of all the Zero Lag Moving Averages. This is useful for scalping but dangerous for medium to long-term traders, especially during market Volatility and news events. Having no lag, this filter also has no smoothing in its signals and can cause some very bizarre behavior when applied to certain indicators. █ Volatility Goldie Locks Zone This volatility filter is the standard first pass filter that is used for all NNFX systems despite the additional volatility/volume filter used in step 5. For this filter, price must fall into a range of maximum and minimum values calculated using multiples of volatility. Unlike the standard NNFX systems, this version of volatility filtering is separated from the core Baseline and uses it's own moving average with Loxx's Exotic Source Types. █ Volatility Types included The GKD system utilizes volatility-based take profits and stop losses. Each take profit and stop loss is calculated as a multiple of volatility. You can change the values of the multipliers in the settings as well. This module includes 17 types of volatility: Close-to-Close Parkinson Garman-Klass Rogers-Satchell Yang-Zhang Garman-Klass-Yang-Zhang Exponential Weighted Moving Average Standard Deviation of Log Returns Pseudo GARCH(2,2) Average True Range True Range Double Standard Deviation Adaptive Deviation Median Absolute Deviation Efficiency-Ratio Adaptive ATR Mean Absolute Deviation Static Percent Various volatility estimators and indicators that investors and traders can use to measure the dispersion or volatility of a financial instrument's price. Each estimator has its strengths and weaknesses, and the choice of estimator should depend on the specific needs and circumstances of the user. Volatility Ticker Selection Import volatility tickers like VIX, EUVIX, BVIV, and EVIV. Close-to-Close Close-to-Close volatility is a classic and widely used volatility measure, sometimes referred to as historical volatility. Volatility is an indicator of the speed of a stock price change. A stock with high volatility is one where the price changes rapidly and with a larger amplitude. The more volatile a stock is, the riskier it is. Close-to-close historical volatility is calculated using only a stock's closing prices. It is the simplest volatility estimator. However, in many cases, it is not precise enough. Stock prices could jump significantly during a trading session and return to the opening value at the end. That means that a considerable amount of price information is not taken into account by close-to-close volatility. Despite its drawbacks, Close-to-Close volatility is still useful in cases where the instrument doesn't have intraday prices. For example, mutual funds calculate their net asset values daily or weekly, and thus their prices are not suitable for more sophisticated volatility estimators. Parkinson Parkinson volatility is a volatility measure that uses the stock’s high and low price of the day. The main difference between regular volatility and Parkinson volatility is that the latter uses high and low prices for a day, rather than only the closing price. This is useful as close-to-close prices could show little difference while large price movements could have occurred during the day. Thus, Parkinson's volatility is considered more precise and requires less data for calculation than close-to-close volatility. One drawback of this estimator is that it doesn't take into account price movements after the market closes. Hence, it systematically undervalues volatility. This drawback is addressed in the Garman-Klass volatility estimator. Garman-Klass Garman-Klass is a volatility estimator that incorporates open, low, high, and close prices of a security. Garman-Klass volatility extends Parkinson's volatility by taking into account the opening and closing prices. As markets are most active during the opening and closing of a trading session, it makes volatility estimation more accurate. Garman and Klass also assumed that the process of price change follows a continuous diffusion process (Geometric Brownian motion). However, this assumption has several drawbacks. The method is not robust for opening jumps in price and trend movements. Despite its drawbacks, the Garman-Klass estimator is still more effective than the basic formula since it takes into account not only the price at the beginning and end of the time interval but also intraday price extremes. Researchers Rogers and Satchell have proposed a more efficient method for assessing historical volatility that takes into account price trends. See Rogers-Satchell Volatility for more detail. Rogers-Satchell Rogers-Satchell is an estimator for measuring the volatility of securities with an average return not equal to zero. Unlike Parkinson and Garman-Klass estimators, Rogers-Satchell incorporates a drift term (mean return not equal to zero). As a result, it provides better volatility estimation when the underlying is trending. The main disadvantage of this method is that it does not take into account price movements between trading sessions. This leads to an underestimation of volatility since price jumps periodically occur in the market precisely at the moments between sessions. A more comprehensive estimator that also considers the gaps between sessions was developed based on the Rogers-Satchel formula in the 2000s by Yang-Zhang. See Yang Zhang Volatility for more detail. Yang-Zhang Yang Zhang is a historical volatility estimator that handles both opening jumps and the drift and has a minimum estimation error. Yang-Zhang volatility can be thought of as a combination of the overnight (close-to-open volatility) and a weighted average of the Rogers-Satchell volatility and the day’s open-to-close volatility. It is considered to be 14 times more efficient than the close-to-close estimator. Garman-Klass-Yang-Zhang Garman-Klass-Yang-Zhang (GKYZ) volatility estimator incorporates the returns of open, high, low, and closing prices in its calculation. GKYZ volatility estimator takes into account overnight jumps but not the trend, i.e., it assumes that the underlying asset follows a Geometric Brownian Motion (GBM) process with zero drift. Therefore, the GKYZ volatility estimator tends to overestimate the volatility when the drift is different from zero. However, for a GBM process, this estimator is eight times more efficient than the close-to-close volatility estimator. Exponential Weighted Moving Average The Exponentially Weighted Moving Average (EWMA) is a quantitative or statistical measure used to model or describe a time series. The EWMA is widely used in finance, with the main applications being technical analysis and volatility modeling. The moving average is designed such that older observations are given lower weights. The weights decrease exponentially as the data point gets older – hence the name exponentially weighted. The only decision a user of the EWMA must make is the parameter lambda. The parameter decides how important the current observation is in the calculation of the EWMA. The higher the value of lambda, the more closely the EWMA tracks the original time series. Standard Deviation of Log Returns This is the simplest calculation of volatility. It's the standard deviation of ln(close/close(1)). Pseudo GARCH(2,2) This is calculated using a short- and long-run mean of variance multiplied by ?. avg(var;M) + (1 ? ?) avg(var;N) = 2?var/(M+1-(M-1)L) + 2(1-?)var/(M+1-(M-1)L) Solving for ? can be done by minimizing the mean squared error of estimation; that is, regressing L^-1var - avg(var; N) against avg(var; M) - avg(var; N) and using the resulting beta estimate as ?. Average True Range The average true range (ATR) is a technical analysis indicator, introduced by market technician J. Welles Wilder Jr. in his book New Concepts in Technical Trading Systems, that measures market volatility by decomposing the entire range of an asset price for that period. The true range indicator is taken as the greatest of the following: current high less the current low; the absolute value of the current high less the previous close; and the absolute value of the current low less the previous close. The ATR is then a moving average, generally using 14 days, of the true ranges. True Range Double A special case of ATR that attempts to correct for volatility skew. Standard Deviation Standard deviation is a statistic that measures the dispersion of a dataset relative to its mean and is calculated as the square root of the variance. The standard deviation is calculated as the square root of variance by determining each data point's deviation relative to the mean. If the data points are further from the mean, there is a higher deviation within the data set; thus, the more spread out the data, the higher the standard deviation. Adaptive Deviation By definition, the Standard Deviation (STD, also represented by the Greek letter sigma ? or the Latin letter s) is a measure that is used to quantify the amount of variation or dispersion of a set of data values. In technical analysis, we usually use it to measure the level of current volatility. Standard Deviation is based on Simple Moving Average calculation for mean value. This version of standard deviation uses the properties of EMA to calculate what can be called a new type of deviation, and since it is based on EMA, we can call it EMA deviation. Additionally, Perry Kaufman's efficiency ratio is used to make it adaptive (since all EMA type calculations are nearly perfect for adapting). The difference when compared to the standard is significant--not just because of EMA usage, but the efficiency ratio makes it a "bit more logical" in very volatile market conditions. Median Absolute Deviation The median absolute deviation is a measure of statistical dispersion. Moreover, the MAD is a robust statistic, being more resilient to outliers in a data set than the standard deviation. In the standard deviation, the distances from the mean are squared, so large deviations are weighted more heavily, and thus outliers can heavily influence it. In the MAD, the deviations of a small number of outliers are irrelevant. Because the MAD is a more robust estimator of scale than the sample variance or standard deviation, it works better with distributions without a mean or variance, such as the Cauchy distribution. For this indicator, a manual recreation of the quantile function in Pine Script is used. This is so users have a full inside view into how this is calculated. Efficiency-Ratio Adaptive ATR Average True Range (ATR) is a widely used indicator for many occasions in technical analysis. It is calculated as the RMA of the true range. This version adds a "twist": it uses Perry Kaufman's Efficiency Ratio to calculate adaptive true range. Mean Absolute Deviation The mean absolute deviation (MAD) is a measure of variability that indicates the average distance between observations and their mean. MAD uses the original units of the data, which simplifies interpretation. Larger values signify that the data points spread out further from the average. Conversely, lower values correspond to data points bunching closer to it. The mean absolute deviation is also known as the mean deviation and average absolute deviation. This definition of the mean absolute deviation sounds similar to the standard deviation (SD). While both measure variability, they have different calculations. In recent years, some proponents of MAD have suggested that it replace the SD as the primary measure because it is a simpler concept that better fits real life. █ Giga Kaleidoscope Modularized Trading System Core components of an NNFX algorithmic trading strategy The NNFX algorithm is built on the principles of trend, momentum, and volatility. There are six core components in the NNFX trading algorithm: 1. Volatility - price volatility; e.g., Average True Range, True Range Double, Close-to-Close, etc. 2. Baseline - a moving average to identify price trend 3. Confirmation 1 - a technical indicator used to identify trends 4. Confirmation 2 - a technical indicator used to identify trends 5. Continuation - a technical indicator used to identify trends 6. Volatility/Volume - a technical indicator used to identify volatility/volume breakouts/breakdown 7. Exit - a technical indicator used to determine when a trend is exhausted 8. Metamorphosis - a technical indicator that produces a compound signal from the combination of other GKD indicators* *(not part of the NNFX algorithm) What is Volatility in the NNFX trading system? In the NNFX (No Nonsense Forex) trading system, ATR (Average True Range) is typically used to measure the volatility of an asset. It is used as a part of the system to help determine the appropriate stop loss and take profit levels for a trade. ATR is calculated by taking the average of the true range values over a specified period. True range is calculated as the maximum of the following values: -Current high minus the current low -Absolute value of the current high minus the previous close -Absolute value of the current low minus the previous close ATR is a dynamic indicator that changes with changes in volatility. As volatility increases, the value of ATR increases, and as volatility decreases, the value of ATR decreases. By using ATR in NNFX system, traders can adjust their stop loss and take profit levels according to the volatility of the asset being traded. This helps to ensure that the trade is given enough room to move, while also minimizing potential losses. Other types of volatility include True Range Double (TRD), Close-to-Close, and Garman-Klass What is a Baseline indicator? The baseline is essentially a moving average, and is used to determine the overall direction of the market. The baseline in the NNFX system is used to filter out trades that are not in line with the long-term trend of the market. The baseline is plotted on the chart along with other indicators, such as the Moving Average (MA), the Relative Strength Index (RSI), and the Average True Range (ATR). Trades are only taken when the price is in the same direction as the baseline. For example, if the baseline is sloping upwards, only long trades are taken, and if the baseline is sloping downwards, only short trades are taken. This approach helps to ensure that trades are in line with the overall trend of the market, and reduces the risk of entering trades that are likely to fail. By using a baseline in the NNFX system, traders can have a clear reference point for determining the overall trend of the market, and can make more informed trading decisions. The baseline helps to filter out noise and false signals, and ensures that trades are taken in the direction of the long-term trend. What is a Confirmation indicator? Confirmation indicators are technical indicators that are used to confirm the signals generated by primary indicators. Primary indicators are the core indicators used in the NNFX system, such as the Average True Range (ATR), the Moving Average (MA), and the Relative Strength Index (RSI). The purpose of the confirmation indicators is to reduce false signals and improve the accuracy of the trading system. They are designed to confirm the signals generated by the primary indicators by providing additional information about the strength and direction of the trend. Some examples of confirmation indicators that may be used in the NNFX system include the Bollinger Bands, the MACD (Moving Average Convergence Divergence), and the MACD Oscillator. These indicators can provide information about the volatility, momentum, and trend strength of the market, and can be used to confirm the signals generated by the primary indicators. In the NNFX system, confirmation indicators are used in combination with primary indicators and other filters to create a trading system that is robust and reliable. By using multiple indicators to confirm trading signals, the system aims to reduce the risk of false signals and improve the overall profitability of the trades. What is a Continuation indicator? In the NNFX (No Nonsense Forex) trading system, a continuation indicator is a technical indicator that is used to confirm a current trend and predict that the trend is likely to continue in the same direction. A continuation indicator is typically used in conjunction with other indicators in the system, such as a baseline indicator, to provide a comprehensive trading strategy. What is a Volatility/Volume indicator? Volume indicators, such as the On Balance Volume (OBV), the Chaikin Money Flow (CMF), or the Volume Price Trend (VPT), are used to measure the amount of buying and selling activity in a market. They are based on the trading volume of the market, and can provide information about the strength of the trend. In the NNFX system, volume indicators are used to confirm trading signals generated by the Moving Average and the Relative Strength Index. Volatility indicators include Average Direction Index, Waddah Attar, and Volatility Ratio. In the NNFX trading system, volatility is a proxy for volume and vice versa. By using volume indicators as confirmation tools, the NNFX trading system aims to reduce the risk of false signals and improve the overall profitability of trades. These indicators can provide additional information about the market that is not captured by the primary indicators, and can help traders to make more informed trading decisions. In addition, volume indicators can be used to identify potential changes in market trends and to confirm the strength of price movements. What is an Exit indicator? The exit indicator is used in conjunction with other indicators in the system, such as the Moving Average (MA), the Relative Strength Index (RSI), and the Average True Range (ATR), to provide a comprehensive trading strategy. The exit indicator in the NNFX system can be any technical indicator that is deemed effective at identifying optimal exit points. Examples of exit indicators that are commonly used include the Parabolic SAR, and the Average Directional Index (ADX). The purpose of the exit indicator is to identify when a trend is likely to reverse or when the market conditions have changed, signaling the need to exit a trade. By using an exit indicator, traders can manage their risk and prevent significant losses. In the NNFX system, the exit indicator is used in conjunction with a stop loss and a take profit order to maximize profits and minimize losses. The stop loss order is used to limit the amount of loss that can be incurred if the trade goes against the trader, while the take profit order is used to lock in profits when the trade is moving in the trader's favor. Overall, the use of an exit indicator in the NNFX trading system is an important component of a comprehensive trading strategy. It allows traders to manage their risk effectively and improve the profitability of their trades by exiting at the right time. What is an Metamorphosis indicator? The concept of a metamorphosis indicator involves the integration of two or more GKD indicators to generate a compound signal. This is achieved by evaluating the accuracy of each indicator and selecting the signal from the indicator with the highest accuracy. As an illustration, let's consider a scenario where we calculate the accuracy of 10 indicators and choose the signal from the indicator that demonstrates the highest accuracy. The resulting output from the metamorphosis indicator can then be utilized in a GKD-BT backtest by occupying a slot that aligns with the purpose of the metamorphosis indicator. The slot can be a GKD-B, GKD-C, or GKD-E slot, depending on the specific requirements and objectives of the indicator. This allows for seamless integration and utilization of the compound signal within the GKD-BT framework. How does Loxx's GKD (Giga Kaleidoscope Modularized Trading System) implement the NNFX algorithm outlined above? Loxx's GKD v2.0 system has five types of modules (indicators/strategies). These modules are: 1. GKD-BT - Backtesting module (Volatility, Number 1 in the NNFX algorithm) 2. GKD-B - Baseline module (Baseline and Volatility/Volume, Numbers 1 and 2 in the NNFX algorithm) 3. GKD-C - Confirmation 1/2 and Continuation module (Confirmation 1/2 and Continuation, Numbers 3, 4, and 5 in the NNFX algorithm) 4. GKD-V - Volatility/Volume module (Confirmation 1/2, Number 6 in the NNFX algorithm) 5. GKD-E - Exit module (Exit, Number 7 in the NNFX algorithm) 6. GKD-M - Metamorphosis module (Metamorphosis, Number 8 in the NNFX algorithm, but not part of the NNFX algorithm) (additional module types will added in future releases) Each module interacts with every module by passing data to A backtest module wherein the various components of the GKD system are combined to create a trading signal. That is, the Baseline indicator passes its data to Volatility/Volume. The Volatility/Volume indicator passes its values to the Confirmation 1 indicator. The Confirmation 1 indicator passes its values to the Confirmation 2 indicator. The Confirmation 2 indicator passes its values to the Continuation indicator. The Continuation indicator passes its values to the Exit indicator, and finally, the Exit indicator passes its values to the Backtest strategy. This chaining of indicators requires that each module conform to Loxx's GKD protocol, therefore allowing for the testing of every possible combination of technical indicators that make up the six components of the NNFX algorithm. What does the application of the GKD trading system look like? Example trading system: Backtest: Multi-Ticker CC Backtest Baseline: Hull Moving Average Volatility/Volume: Hurst Exponent Confirmation 1: Advance Trend Pressure as shown on the chart above Confirmation 2: uf2018 Continuation: Coppock Curve Exit: Rex Oscillator Metamorphosis: Baseline Optimizer Each GKD indicator is denoted with a module identifier of either: GKD-BT, GKD-B, GKD-C, GKD-V, GKD-M, or GKD-E. This allows traders to understand to which module each indicator belongs and where each indicator fits into the GKD system. █ Giga Kaleidoscope Modularized Trading System Signals Standard Entry 1. GKD-C Confirmation gives signal 2. Baseline agrees 3. Price inside Goldie Locks Zone Minimum 4. Price inside Goldie Locks Zone Maximum 5. Confirmation 2 agrees 6. Volatility/Volume agrees 1-Candle Standard Entry 1a. GKD-C Confirmation gives signal 2a. Baseline agrees 3a. Price inside Goldie Locks Zone Minimum 4a. Price inside Goldie Locks Zone Maximum Next Candle 1b. Price retraced 2b. Baseline agrees 3b. Confirmation 1 agrees 4b. Confirmation 2 agrees 5b. Volatility/Volume agrees Baseline Entry 1. GKD-B Baseline gives signal 2. Confirmation 1 agrees 3. Price inside Goldie Locks Zone Minimum 4. Price inside Goldie Locks Zone Maximum 5. Confirmation 2 agrees 6. Volatility/Volume agrees 7. Confirmation 1 signal was less than 'Maximum Allowable PSBC Bars Back' prior 1-Candle Baseline Entry 1a. GKD-B Baseline gives signal 2a. Confirmation 1 agrees 3a. Price inside Goldie Locks Zone Minimum 4a. Price inside Goldie Locks Zone Maximum 5a. Confirmation 1 signal was less than 'Maximum Allowable PSBC Bars Back' prior Next Candle 1b. Price retraced 2b. Baseline agrees 3b. Confirmation 1 agrees 4b. Confirmation 2 agrees 5b. Volatility/Volume agrees Volatility/Volume Entry 1. GKD-V Volatility/Volume gives signal 2. Confirmation 1 agrees 3. Price inside Goldie Locks Zone Minimum 4. Price inside Goldie Locks Zone Maximum 5. Confirmation 2 agrees 6. Baseline agrees 7. Confirmation 1 signal was less than 7 candles prior 1-Candle Volatility/Volume Entry 1a. GKD-V Volatility/Volume gives signal 2a. Confirmation 1 agrees 3a. Price inside Goldie Locks Zone Minimum 4a. Price inside Goldie Locks Zone Maximum 5a. Confirmation 1 signal was less than 'Maximum Allowable PSVVC Bars Back' prior Next Candle 1b. Price retraced 2b. Volatility/Volume agrees 3b. Confirmation 1 agrees 4b. Confirmation 2 agrees 5b. Baseline agrees Confirmation 2 Entry 1. GKD-C Confirmation 2 gives signal 2. Confirmation 1 agrees 3. Price inside Goldie Locks Zone Minimum 4. Price inside Goldie Locks Zone Maximum 5. Volatility/Volume agrees 6. Baseline agrees 7. Confirmation 1 signal was less than 7 candles prior 1-Candle Confirmation 2 Entry 1a. GKD-C Confirmation 2 gives signal 2a. Confirmation 1 agrees 3a. Price inside Goldie Locks Zone Minimum 4a. Price inside Goldie Locks Zone Maximum 5a. Confirmation 1 signal was less than 'Maximum Allowable PSC2C Bars Back' prior Next Candle 1b. Price retraced 2b. Confirmation 2 agrees 3b. Confirmation 1 agrees 4b. Volatility/Volume agrees 5b. Baseline agrees PullBack Entry 1a. GKD-B Baseline gives signal 2a. Confirmation 1 agrees 3a. Price is beyond 1.0x Volatility of Baseline Next Candle 1b. Price inside Goldie Locks Zone Minimum 2b. Price inside Goldie Locks Zone Maximum 3b. Confirmation 1 agrees 4b. Confirmation 2 agrees 5b. Volatility/Volume agrees Continuation Entry 1. Standard Entry, 1-Candle Standard Entry, Baseline Entry, 1-Candle Baseline Entry, Volatility/Volume Entry, 1-Candle Volatility/Volume Entry, Confirmation 2 Entry, 1-Candle Confirmation 2 Entry, or Pullback entry triggered previously 2. Baseline hasn't crossed since entry signal trigger 4. Confirmation 1 agrees 5. Baseline agrees 6. Confirmation 2 agrees
Penunjuk Pine Script®
oleh loxx
ATR Bands (Keltner Channel), Wick and SRSI Signals [MW]Introduction This indicator uses a novel combination of ATR Bands, candle wicks crossing the ATR upper and lower bands, and baseline, and combines them with the Stochastic SRSI oscillator to provide early BUY and SELL signals in uptrends, downtrends, and in ranging price conditions. How it’s unique People generally understand Bollinger Bands and Keltner Channels. Buy at the bottom band, sell at the top band. However, because the bands themselves are not static, impulsive moves can render them useless. People also generally understand wicks. Candles with large wicks can represent a change in pattern, or volatile price movement. Combining those two to determine if price is reaching a pivot point is relatively novel. When Stochastic RSI (SRSI) filtering is also added, it becomes a genuinely unique combination that can be used to determine trade entries and exits. What’s the benefit The benefit of the indicator is that it can help potentially identify pivots WHEN THEY HAPPEN, and with potentially minimal retracement, depending on the trader’s time window. Many indicators wait for a trend to be established, or wait for a breakout to occur, or have to wait for some form of confirmation. In the interpretation used by this indicator, bands, wicks, and SRSI cycles provide both the signal and confirmation. It takes into account 3 elements: Price approaching the upper or lower band or the baseline - MEANING: Price is becoming extended based on calculations that use the candle trading range. A candle wick of a defined proportion (e.g. wick is 1/2 the size of a full candle OR candle body) crosses a band or baseline, but the body does not cross the band or baseline - MEANING: Buyers and sellers are both very active. The Stochastic RSI reading is above 80 for SELL signals and below 20 for BUY signals - MEANING: Additional confirmation that price is becoming extended based on the current cyclic price pattern. How to Use SIGNALS Buy Signals - Green(ish): B Signal - Potential pivot up from the lower band when using the preferred multiplier B1 Signal - Potential pivot up from the lower band when using phi * multiplier B2 Signal - Potential pivot up from the lower band when using 1/2 * multiplier B3 Signal - Potential pivot up from baseline Sell Signals - Red(ish): S Signal - Potential pivot down from the upper band when using the preferred multiplier S1 Signal - Potential pivot down from the upper band when using S2 Signal - Potential pivot down from the upper band when using 1/2 * multiplier S3 Signal - Potential pivot down from the baseline DISCUSSION During an uptrend or downtrend, signals from the baseline can help traders identify areas where they may enter the trending move with the least amount of drawdown. In both cases, entry points can occur with baseline signals in the direction of the trend. For example, in an uptrend (when the price is forming higher highs and higher lows, or when the baseline is rising), price tends to oscillate between the upper band and baseline. In this case, the baseline BUY signal (B3) can show an entry point. In a downtrend (when the price is forming lower highs and lower lows, or when the baseline is falling), price tends to oscillate between the baseline and the lower band. In this case, the baseline SELL signal (S3) can show an entry point. During consolidation, when price is ranging, price tends to oscillate between the upper and lower bands, while crossing through the baseline unperturbed. Here, entry points can occur at the upper and lower bands. When all conditions are met at the lower band during consolidation, a BUY signal (B), can occur. This signal may also occur prior to a break out of consolidation to the upside. When all conditions are met at the upper band during consolidation, a SELL signal (S), can occur. This signal may also occur prior to a break out of consolidation to the downside. Additional B1, B2, and S1, and S2 signals can be displayed that use the bands based on a multiplier that is half that of the primary one, and phi (0.618) times the primary multiplier as a way to quickly check for signals occurring along different, but related, bands. Calculations ATR Bands, or Keltner Channels, are a technical analysis tool that are used to measure market volatility and identify overbought or oversold conditions in the trading of financial instruments, such as stocks, bonds, commodities, and currencies. ATR Bands consist of three lines plotted on a price chart: Middle Band, Basis, or Baseline: This is typically a simple moving average (SMA) of the closing prices over a certain period. It represents the intermediate-term trend of the asset's price. Upper Band: This is calculated by adding a certain number of ATRs to the middle band (SMA). The upper band adjusts itself with the increase in volatility. Lower Band: This is calculated by subtracting the same number of ATRs from the middle band (SMA). Like the upper band, the lower band adjusts to changes in volatility. The candle wick signals occur if the wick is at the specified ratio compared to either the entire candle or the candle body. The upper band, lower band, and baseline signals happen if the wick is the specified ratio of the total candle size. For the major signals for upper and lower bands, these occur when the wick extends outside of the bands while closing a candle inside of the bands. For the baseline signals, they occur if a wick crosses a baseline but closes on the other side. Settings CHANNEL SETTINGS Baseline EMA Period (Default: 21): Period length of the moving average basis line. ATR Period (Default: 21): The number of periods over which the Average True Range (ATR) is calculated. Basis MA Type (Default: SMA): The moving average type for the basis line. Multiplier (Default: 2.5: The deviation multiplier used to calculate the band distance from the basis line. ADDITIONAL CHANNELS Half of Multiplier Offset (Default: True): Toggles the display of the ATR bands that are set a distance of half of the ATR multiplier. Quarter of Multiplier Offset (Default: false): Toggles the display of the ATR bands that are set a distance of one quarter of the ATR multiplier. Phi (Φ) Offset (Default: false): Toggles the display of the ATR bands that are set a distance of phi (Φ) times the ATR multiplier. WICK SETTINGS FOR CANDLE FILTERS Wick Ratio for Bands (Default: 0.4): The ratio of wick size to total candle size for use at upper and lower bands. Wick Ratio for Baseline (Default: 0.4): The ratio of wick size to total candle size for use at baseline. Use Candle Body (rather than full candle size) (Default: false): Determines whether wick calculations use the candle body or the entire candle size. VISUAL PREFERENCES - SIGNALS Show Signals (Default: true): Allows signal labels to be shown. Show Signals from 1/2 Band Offset (Default: false): Toggle signals originating from 1/2 offset upper and lower bands. Show Signals from Phi (Φ) Band Offset (Default: false): Toggle signals originating from phi (Φ) offset upper and lower bands. Show Baseline Signals (Default: false): Toggle Baseline signals. VISUAL PREFERENCES - BANDS Show ATR (Keltner) Bands (Default: true): Use a background color inside the Bollinger Bands. Fill Bands (Default: true): Use a background color inside the Bollinger Bands. STOCHASTIC SETTINGS Use Stochastic RSI Filtering (Default: False): This will only trigger some SELL signals when the stochastic RSI is above 80, and BUY signals when below 20. K (Default: 3): The smoothing level for the Stochastic RSI. RSI Length (Default: 14): The period length for the RSI calculation. Stochastic Length (Default: 8): The period length over which the stochastic calculation is performed. Other Usage Notes and Limitations To understand future price movement, this indicator assumes that 3 things must be known: Evidence of a change of market structure. This can be demonstrated by increased volatility, consolidation, volume spikes (which can be tracked with the MW Volume Impulse Indicator) or, in the case of this indicator, candle wicks. The potential cause of the change. It could be a VWAP line (which can be tracked with the Multi VWAP , and Multi VWAP from Gaps indicators), an event, an important support or resistance level, a key moving average, or many other things. This indicator assumes the ATR bands can be a cause. The current position in the price cycle. Oscillators like the RSI, and MACD, are typical measures of price oscillation (other oscillators like the Price and Volume Stochastic Divergence indicator can also be useful). This indicator uses the Stochastic RSI oscillator to determine overbought and oversold conditions. When evidence of the change appears, and the potential cause of the change is identified, and the price oscillation is at a favorable position for the desired trading direction, this indicator will generate a signal. ATR Bands (or Keltner Channels) are used to determine when price might “revert to the mean”. Crossing, or being near the upper or lower band, can indicate an overbought or oversold condition, which could lead to a price reversal. By tracking the behavior of candle wicks during these events, we can see how active the battle is between buyers and sellers. If the top of a wick is large, it may indicate that sellers are aggressively attempting to bring the price down. Conversely, if the bottom wick is large, it can indicate that buyers are actively trying to counter the price action caused by selling pressure. When this wicking action occurs at times when price is not near the upper band, lower band, or baseline, it could indicate the presence of an important level. That could mean a nearby VWAP line, a supply or demand zone, a round price number, or a number of other factors. In any case, this wick may be the first indication of a price reversal. Shorter baseline periods may be better for short period trading like scalping or day trading, while longer period baselines can show signals that are better suited to swing trading, or longer term investing. It's important for traders to be aware of the limitations of any indicator and to use them as part of a broader, well-rounded trading strategy that includes risk management, fundamental analysis, and other tools that can help with reducing false signals, determining trend direction, and providing additional confirmation for a trade decision. Diversifying strategies and not relying solely on one type of indicator or analysis can help mitigate some of these risks. The TradingView platform allows a maximum of 500 labels per chart. This means that if your settings allow for a lot of signals, labels for earlier ones may not appear if the total number of labels exceeds 500 for the chart.
Penunjuk Pine Script®
oleh mwrightinc
6
Bollinger Band Wick and SRSI Signals [MW]Introduction This indicator uses a novel combination of Bollinger Bands, candle wicks crossing the upper and lower Bollinger Bands and baseline, and combines them with the Stochastic SRSI oscillator to provide early BUY and SELL signals in uptrends, downtrends, and in ranging price conditions. How it’s unique People generally understand Bollinger Bands and Keltner Channels. Buy at the bottom band, sell at the top band. However, because the bands themselves are not static, impulsive moves can render them useless. People also generally understand wicks. Candles with large wicks can represent a change in pattern, or volatile price movement. Combining those two to determine if price is reaching a pivot point is relatively novel. When Stochastic RSI (SRSI) filtering is also added, it becomes a genuinely unique combination that can be used to determine trade entries and exits. What’s the benefit The benefit of the indicator is that it can help potentially identify pivots WHEN THEY HAPPEN, and with potentially minimal retracement, depending on the trader’s time window. Many indicators wait for a trend to be established, or wait for a breakout to occur, or have to wait for some form of confirmation. In the interpretation used by this indicator, bands, wicks, and SRSI cycles provide both the signal and confirmation. It takes into account 3 elements: Price approaching the upper or lower band or the baseline - MEANING: Price is becoming extended based on calculations that use the candle trading range. A candle wick of a defined proportion (e.g. wick is 1/2 the size of a full candle OR candle body) crosses a band or baseline, but the body does not cross the band or baseline - MEANING: Buyers and sellers are both very active. The Stochastic RSI reading is above 80 for SELL signals and below 20 for BUY signals - MEANING: Additional confirmation that price is becoming extended based on the current cyclic price pattern. How to Use SIGNALS Buy Signals - Green(ish): B Signal - Potential pivot up from the lower band when using the preferred multiplier B1 Signal - Potential pivot up from baseline Sell Signals - Red(ish): S Signal - Potential pivot down from the upper band when using the preferred multiplier S1 Signal - Potential pivot down from the baseline DISCUSSION During an uptrend or downtrend, signals from the baseline can help traders identify areas where they may enter the trending move with the least amount of drawdown. In both cases, entry points can occur with baseline signals in the direction of the trend. For example, in an uptrend (when the price is forming higher highs and higher lows, or when the baseline is rising), price tends to oscillate between the upper band and baseline. In this case, the baseline BUY signal (B3) can show an entry point. In a downtrend (when the price is forming lower highs and lower lows, or when the baseline is falling), price tends to oscillate between the baseline and the lower band. In this case, the baseline SELL signal (S3) can show an entry point. During consolidation, when price is ranging, price tends to oscillate between the upper and lower bands, while crossing through the baseline unperturbed. Here, entry points can occur at the upper and lower bands. When all conditions are met at the lower band during consolidation, a BUY signal (B), can occur. This signal may also occur prior to a break out of consolidation to the upside. When all conditions are met at the upper band during consolidation, a SELL signal (S), can occur. This signal may also occur prior to a break out of consolidation to the downside. Additional, B1 and S1 signals can be displayed that use the baseline as the pivot level. Settings SIGNALS Show Bollinger Band Signals (Default: True): Allows signal labels to be shown. Hide Baseline Signals (Default: False): Baseline signals are on by default. This will turn them off. Show Wick Signals (Defau lt: True): Displays signals when wicking occurs. BOLLINGER BAND SETTINGS Period length for Bollinger Band Basis (Default: 21): Length of the Bollinger Band (BB) moving average basis line. Basis MA Type (Default: SMA): The moving average type for the BB Basis line. Source (Default: “close”): The source of time series data. Standard Deviation Multiplier (Default: 2.5: The deviation multiplier used to calculate the band distance from the basis line. WICK SETTINGS FOR BOLLINGER BANDS Wick Ratio for Bands (Default: 0.3): The ratio of wick size to total candle size for use at upper and lower bands. Wick Ratio for Baseline (Default: 0.3): The ratio of wick size to total candle size for use at baseline. WICK SETTINGS FOR CANDLE SIGNALS Upper Wick Threshold (Default: 50): The percent of upper wick compared to the full candle size or candle body size. Lower Wick Threshold (Default: 50): The percent of lower wick compared to the full candle size or candle body size. Use Candle Body (Default: false): Toggles the use of the full candle size versus the candle body size when calculating the wick signal. VISUAL PREFERENCES Fill Bands (Default: true): Use a background color inside the Bollinger Bands. Show Signals (Default: true): Toggle the Bollinger Band upper band, lower band, and baseline signals. Show Bollinger Bands (Default: true): Show the Bollinger Bands. STOCHASTIC SETTINGS Use Stochastic RSI Filtering (Default: False): This will only trigger some SELL signals when the stochastic RSI is above 80, and BUY signals when below 20. K (Default: 3): The smoothing level for the Stochastic RSI. RSI Length (Default: 14): The period length for the RSI calculation. Stochastic Length (Default: 8): The period length over which the stochastic calculation is performed. Calculations Bollinger Bands are a technical analysis tool that are used to measure market volatility and identify overbought or oversold conditions in the trading of financial instruments, such as stocks, bonds, commodities, and currencies. Bollinger Bands consist of three lines plotted on a price chart: Middle Band, Basis, or Baseline: This is typically a simple moving average (SMA) of the closing prices over a certain period. It represents the intermediate-term trend of the asset's price. Upper Band: This is calculated by adding a certain number of standard deviations to the middle band (SMA). The upper band adjusts itself with the increase in volatility. Lower Band: This is calculated by subtracting the same number of standard deviations from the middle band (SMA). Like the upper band, the lower band adjusts to changes in volatility. The candle wick signals occur if the wick is at the specified ratio compared to either the entire candle or the candle body. The upper band, lower band, and baseline signals happen if the wick is the specified ratio of the total candle size. For the major signals for upper and lower bands, these occur when the wick extends outside of the bands while closing a candle inside of the bands. For the baseline signals, they occur if a wick crosses a baseline but closes on the other side. Other Usage Notes and Limitations To understand future price movement, this indicator assumes that 3 things must be known: Evidence of a change of market structure. This can be demonstrated by increased volatility, consolidation, volume spikes (which can be tracked with the MW Volume Impulse Indicator) or, in the case of this indicator, candle wicks. The potential cause of the change. It could be a VWAP line (which can be tracked with the Multi VWAP , and Multi VWAP from Gaps indicators), an event, an important support or resistance level, a key moving average, or many other things. This indicator assumes the ATR bands can be a cause. The current position in the price cycle. Oscillators like the RSI, and MACD, are typical measures of price oscillation (other oscillators like the Price and Volume Stochastic Divergence indicator can also be useful). This indicator uses the Stochastic RSI oscillator to determine overbought and oversold conditions. When evidence of the change appears, and the potential cause of the change is identified, and the price oscillation is at a favorable position for the desired trading direction, this indicator will generate a signal. ATR Bands (or Keltner Channels) are used to determine when price might “revert to the mean”. Crossing, or being near the upper or lower band, can indicate an overbought or oversold condition, which could lead to a price reversal. By tracking the behavior of candle wicks during these events, we can see how active the battle is between buyers and sellers. If the top of a wick is large, it may indicate that sellers are aggressively attempting to bring the price down. Conversely, if the bottom wick is large, it can indicate that buyers are actively trying to counter the price action caused by selling pressure. When this wicking action occurs at times when price is not near the upper band, lower band, or baseline, it could indicate the presence of an important level. That could mean a nearby VWAP line, a supply or demand zone, a round price number, or a number of other factors. In any case, this wick may be the first indication of a price reversal. Shorter baseline periods may be better for short period trading like scalping or day trading, while longer period baselines can show signals that are better suited to swing trading, or longer term investing. It's important for traders to be aware of the limitations of any indicator and to use them as part of a broader, well-rounded trading strategy that includes risk management, fundamental analysis, and other tools that can help with reducing false signals, determining trend direction, and providing additional confirmation for a trade decision. Diversifying strategies and not relying solely on one type of indicator or analysis can help mitigate some of these risks. The TradingView platform allows a maximum of 500 labels per chart. This means that if your settings allow for a lot of signals, labels for earlier ones may not appear if the total number of labels exceeds 500 for the chart.
Penunjuk Pine Script®
oleh mwrightinc
Wave Pendulum Trend [QuantraSystems]Wave Pendulum Trend Introduction The Wave Pendulum Trend (𝓟𝓮𝓷𝓭𝓾𝓵𝓾𝓶 𝓣𝓻𝓮𝓷𝓭) extrapolates market trends using physical principles derived from waves and pendulums. This indicator is a bespoke build, and its performance and behavior cannot be compared to existing indicators. It is designed for trend following but is also effective for identifying mean reversions, momentum strength, and shows range-bound market periods within the dynamic bands. In order to ascertain a smooth yet rapid trend direction of the market, the 𝓟𝓮𝓷𝓭𝓾𝓵𝓾𝓶 𝓣𝓻𝓮𝓷𝓭 combines several factors. A bespoke set of functions captures the momentum of price movements and dynamically weighs it over time. The indicator then extrapolates acceleration from the change in delta of price movements. Legend With bar coloring enabled, the price section mirrors current trend conditions. Please keep this feature disabled if you intend to use multiple indicators to avoid confusion. The 𝓟𝓮𝓷𝓭𝓾𝓵𝓾𝓶 𝓣𝓻𝓮𝓷𝓭 presents extensive market insights. The purple and green bands around the oscillator signal the selected standard deviation (default σ = 2), for the trader to calculate how common the trending movements are in relation to the selected asset’s history. The inner, dynamic thresholds, indicated by the blue “Range-bound market” label in the graphic above, border the area that signals a ranging market if both 𝓐𝓬𝓬𝓮𝓵𝓮𝓻𝓪𝓽𝓲𝓸𝓷 and 𝓜𝓸𝓶𝓮𝓷𝓽𝓾𝓶 signals remain inside. If either line exceeds these thresholds, care is advised as a shift in market behavior is underway. “Trend strength” in the graphic provides a good estimate for the trending movements strength. If the signal lines exceed the set standard deviation in non-classic mode, a reversal is very likely. Case Study As shown in the above case study we see two profitable swing trades on the 4H chart of Ethereum. Please note the display variant here is set to “Heikin-Ashi”. We always recommend using a multitude of indicators to attain multiple signals on the likelihood of opening the correct position. However, this standalone scenario serves as an example on how the 𝓟𝓮𝓷𝓭𝓾𝓵𝓾𝓶 𝓣𝓻𝓮𝓷𝓭 added two profitable swing trades. The first short trade was opened after the 𝓐𝓬𝓬𝓮𝓵𝓮𝓻𝓪𝓽𝓲𝓸𝓷 and 𝓜𝓸𝓶𝓮𝓷𝓽𝓾𝓶 reversed after crossing the threshold of standard deviation. This trade offered a late entry only, these two factors were followed late by the third signal in this case – the trend reversal. Such a trade would require additional indicators to signal at the same time, so the trader can get more confirmations. The trade was closed after 6D with an 8% gain on a 1x short position. The second trade is a long position that enters in the same manner. The trader takes the reversal beyond the select standard deviation as a likely entry. After 7D a triple confirmation was received, as indicated by the triangle, that a reversal or at least a plateau is extremely likely. The trade was closed after 7D with a 17.23% gain on a 1x long position. Recommended Settings Trend Following / Investing (1D chart) Please use the default settings! Swing Trading (4H chart) Wave MA - Type: TEMA Wave MA – Length: 30 Display Variant: Heikin-Ashi Bar Coloring: Off Choose Mode for Coloring: Signal Notes Quantra Standard Value Contents: The Heikin-Ashi (HA) candle visualization smoothes out the signal line to provide more informative insights into momentum and trends. This allows earlier entries and exits by observing the indicator values transformed by the HA. Various visualization options are available to adjust the indicator to the user’s preference: Aside from HA, a classic line, or a hybrid of both. A special feature of Quantra’s indicators is that they are probabilistically built - therefore they work well as confluence and can easily be stacked to increase signal accuracy. To add to Quantra's indicators’ utility we have added the option to change the price bars colors based on different signals: Settings: TEMA and DEMA length settings should be longer compared to other Moving Averages (MAs). Due to its complex calculations, the indicator requires a larger amount of historical data for accurate computation. Sensitivity to Divergences: The Wave Pendulum Trend is particularly sensitive to divergences, making it a useful tool in spotting potential trend reversals or continuations. Trend Following and Reversions: While it is primarily used for trend following, it also excels in identifying market reversions. Momentum and Acceleration: The interaction between momentum and acceleration is a key feature of this indicator. Visualization: The indicator offers various visualization options, including bar coloring based on HA Candles and extremes and trends. It also introduces a novel approach to visualizing the oscillator in the "Classic" mode and provides an adjustable Standard Deviation (SD) measure for reversal signals in non-classic modes. Choose Mode for Coloring Trend Following (Indicator above mid line counts as uptrend, below is downtrend) Extremes (Everything beyond the SD bands is highlighted to signal mean reversion) Candles (Color of HA candles as barcolor) Reversions (Only for HA) (Reversion Signals via the triangles if HA candles change trend while beyond the SD bands, high probability entries/exits) Methodology The methodology behind the Wave Pendulum Trend is inspired by wave and pendulum theories to extrapolate market moves. By calculating the momentum and its acceleration from price data, it provides a nuanced view of the market trend. Traders should observe the color coding, which reflects the interplay between momentum, acceleration, and set thresholds for acceleration. The Signal Mode is particularly useful for quickly identifying trend, momentum, and acceleration exhaustions. Additionally, the indicator can help filter out ranges with insufficient momentum acceleration. Traders are encouraged to experiment with this mode and adjust the threshold settings to suit their strategies.
Penunjuk Pine Script®
oleh QuantraSystems
3
Price Range Volume Profile++ [Pt]█ Introduction The Price Range Volume Profile++ (PRVP++) is an advanced, feature-rich indicator specifically designed for volume profile users for in-depth volume analysis. Unlike most other volume profile tools that are limited to a 5000-bar lookback, PRVP++ can utilize all available candles on the chart, offering an unparalleled scope of historical data analysis. █ Main Features Full Chart Historical Lookback : PRVP++ sets a new standard with its ability to analyze the entire history of candles available on a chart, far exceeding the typical 5000-bar limit of other tools. This feature allows traders to conduct a comprehensive and detailed study of volume data over extensive time periods. Volume Profile Analysis : The tool provides an in-depth volume profile analysis, showcasing the distribution of trading activity across different price levels. This is crucial for identifying key areas of interest in the market. Bull/Bear Strength Profile : A standout feature that displays the relative strength of buyers (bulls) and sellers (bears) at different price levels. This visual representation helps traders gauge market sentiment and power dynamics. Automatic HVN and LVN Identification : PRVP++ automatically highlights High Volume Nodes (HVNs) and Low Volume Nodes (LVNs), making it easier for traders to identify significant zones of trading activity and potential breakout areas. Customization and Visual Enhancements : Offers customization for the profile's width, horizontal offset, and a sophisticated gradient color scheme for HVNs and LVNs, enhancing the tool's visual appeal and analytical utility. █ Input Parameters Price Range : Sets the percentage distance for the volume profile relative to the current closing price, determining the extent of volume data analysis. Profile Step Size (Tick Size) : Users can choose automatic sizing or set a specific tick step size, offering flexibility in the granularity of the volume profile. Volume Profile Options : Includes settings for gradient power and color selections for high and low volume areas, along with a fun mode for random color variations. Profile Placement and Appearance : Adjustments for profile width, horizontal offset, and the option for background fill to enhance visibility. Background Fill : Allows users to fill the background of the volume profile range, enhancing the visual impact and readability. Time Weighted Profile : An option that weights the volume profile to give more emphasis to recent trading activities, highlighting the impact of recent market movements. Smooth Filter : A feature that smoothens the volume profile to reduce noise and fluctuations, offering a clearer view of dominant volume levels. High and Low Volume Node Settings : Customizable detection settings for HVNs and LVNs, line styles, label text sizes, and the option to extend lines for clearer market analysis. Extra Settings : Includes displaying the current price on the profile, a customizable settings table with adjustable location and font size, and table opacity. Random Color Generation : A feature for dynamically changing the colors used in the volume profile. █ Possible Use Cases Long-Term Market Analysis : Due to its ability to analyze all available candles on the chart, PRVP++ is exceptionally suited for long-term market analysis. Traders can study the historical volume profile over extended periods, identifying significant volume trends and shifts that could impact long-term investment strategies. Identifying Key Support and Resistance Levels : The automatic HVN and LVN identification feature of PRVP++ makes it easier for traders to spot potential support and resistance levels. HVNs often correspond to strong support or resistance zones where significant trading activity has occurred, while LVNs may indicate levels where the price could break through more easily. Gauging Market Sentiment with Bull/Bear Strength Profile : The Bull/Bear Strength Profile helps traders understand the prevailing market sentiment at different price levels. By analyzing the dominance of buying or selling pressure, traders can align their trades with the market's direction or prepare for potential reversals. Intraday Trading and Scalping : For intraday traders and scalpers, the time-weighted feature and the ability to adjust profile step size offer valuable insights. By emphasizing recent trading activity and adjusting the granularity of the profile, traders can make more informed decisions based on short-term price movements and volume changes. Breakout Trading : By utilizing the LVN identification, traders can pinpoint areas with low trading activity that might serve as potential breakout points. This information can be instrumental in formulating strategies to capitalize on sudden price movements. Volume Gap Analysis : PRVP++ can be used to identify volume gaps, which are areas with significantly low volume. These gaps can act as important indicators for price movements, as prices may move quickly through these levels due to the lack of historical trading activity. Risk Management and Position Sizing : Understanding the volume profile can aid in better risk management and position sizing. By recognizing areas of high and low volume, traders can set stop-loss orders more effectively and adjust their position sizes according to the perceived strength of support or resistance levels. Swing Trading : For swing traders, the comprehensive historical lookback and HVN/LVN analysis provide critical information about where to enter and exit trades. Swing traders can utilize these features to identify trend reversals and momentum shifts. █ Best Practices and Tips Start with a Clear Understanding : Before utilizing PRVP++, ensure you have a solid grasp of volume profile concepts. Understanding High Volume Nodes (HVNs), Low Volume Nodes (LVNs), and their implications on market behavior is crucial. Combine with Other Analysis Tools : While PRVP++ is powerful, it's most effective when used in conjunction with other technical analysis tools and indicators. Combining volume profile data with price action analysis, trend lines, and technical indicators can provide a more comprehensive market view. Customize According to Your Trading Style : Tailor the tool's settings to fit your trading strategy. Day traders might prefer a more detailed profile, while long-term investors may benefit from broader data analysis. Pay Attention to HVNs and LVNs : HVNs can indicate potential support or resistance areas, while LVNs might suggest breakout points. Monitor these areas closely for trading opportunities. Utilize the Full Historical Lookback Feature : For a broader perspective, use the full historical lookback feature to understand long-term volume patterns and their impact on current price movements. Keep an Eye on Bull/Bear Strength : Use the Bull/Bear Strength Profile to gauge market sentiment at different price levels. This can help in predicting potential price movements. Regularly Update Your Strategy : As market conditions change, regularly review and adjust your use of PRVP++ to ensure it aligns with current market dynamics. Stay Informed About Market News : Be aware of how economic news and global events might affect the volume and price, as these factors can significantly impact the effectiveness of volume-based strategies. █ Disclaimers and Risk Advice No Guarantee of Profits : Trading involves risk, and the use of the PRVP++ tool does not guarantee profits. Always be aware of the potential for loss. Educational Purposes Only : The information provided by PRVP++ is for educational purposes only and should not be considered financial advice. Not a Standalone Tool : PRVP++ should not be used as a standalone decision-making tool. Combine it with comprehensive market analysis and personal judgment. Past Performance Not Indicative of Future Results [/b: Historical data and trends analyzed by PRVP++ do not guarantee future market behavior. Use Risk Management : Always employ sound risk management strategies, including setting stop-loss orders and managing position sizes to protect your capital. Personal Responsibility : Trading decisions remain the responsibility of the individual trader. Use PRVP++ as one of several tools in your decision-making process.
Penunjuk Pine Script®
oleh PtGambler
3
Trend Sentinel BarrierEveryone in the market wants to take profits from the trend. It is easy to think but hard to execute. In fact, some callbacks or rebounds may cause you to close the position out of fear and let you miss bigger profits. Indicator: Trend Sentinel Barri er solves this problem for you! It use AI algorithm to help you seize profits. It is a trend indicator, using AI algorithm to calculate the cumulative trading volume of bulls and bears, identify trend direction and opportunities, and calculate short-term average cost in combination with changes of turnover ratio in multi-period trends, so as to grasp the profit from the trend more effectively without being cheated. 💠Usage： Signal: "BUY" means bullish trend, "SELL" means bearish trend. Support and resistance range: "red area" represents strong support or resistance for long-term fluctuation costs, and "blue area" represents moderate support of resistance for short-term fluctuation costs. 🎈Tip I： When the BUY and SELL signal appear, it means that the direction of the trend will change, and the color of the candles will also change. Don't care about the color of the candles, let's just focus on the price, support and resistance. 🎈Tip II： Take the BUY signal as an example. When the signal appears and you hold long position, you need to pay attention to the blue and red support range. If the price returns to this range but there is no SELL signal, you can consider holding the long position for a while. If the price pump with long candles, and then pulls back to the range, you need to be vigilant. You can consider taking the profit when the price breakthrough the support range, or wait for the SELL signal. 🎈Advanced tip I： In most cases, the trend market is not smooth, there will be a lot of callbacks or rebounds, but because of this, we have many opportunities to do swing trading. Continuing to take the BUY signal as an example, when this signal appears, every time the price falls back to the blue or red support area, you can consider adding positions. There are two ways to deal with these newly added positions. One is to do swing trading. You can consider taking profits near the previous high when the price rises. The advantage of this operation is that you can get more profits in the same trend market. The second is to continue to hold it as the bottom position until the general trend is completely over, and then close the position after obtaining huge profits. 🎈Advanced tip II： When using advanced tips I, you can consider adding some momentum indicators to assist you in judging whether pullbacks or rebounds have failed, so as to increase your position. Similarly, the momentum indicator can also help you find a take-profit point for newly added positions For details, please refer to the momentum indicator: KD Momentum Matrix *The signals in the indicators are for reference only and not intended as investment advice. Past performance of a strategy is not indicative of future earnings results. Update- Optimize the alarm function. If you need to monitor the "Buy" or "Sell" signal, when creating an alarm, set the condition bar to: Trend Sentinel Barrier --> "Buy" or "Sell" --> Crossing Up --> value --> 1
Penunjuk Pine Script®
oleh sypool-AI-TradeGenius
1
Dual Weighted RSIDescription: The Dual Weighted RSI (DWRSI) is a custom technical analysis tool that extends the concept of the traditional Relative Strength Index (RSI) by incorporating two different RSI calculations, each with its own timeframe and weighting factor. This unique approach allows traders to analyze market momentum through a combination of RSIs from different timeframes, providing a more nuanced and customizable view of market conditions. The DWRSI calculates two separate RSIs based on user-defined timeframes (e.g., daily, weekly) and applies a scale factor to each RSI, ranging from 0 to 1. This scale factor determines the contribution of each RSI to the final combined value: a factor of 1 means the full value of the RSI is used, 0 means none of the value is used, and 0.5 means half of the value is used. The final DWRSI value is the sum of these scaled RSIs, offering a unique perspective on market trends. How to Use: Add the Indicator: Search for "Dual Weighted RSI" or "DWRSI" in the TradingView indicators list and add it to your chart. Set the Parameters: First RSI Length: Set the period length for the first RSI calculation. First RSI Timeframe: Choose the timeframe for the first RSI (e.g., "D" for daily). First RSI Scale Factor: Adjust the scale factor for the first RSI (0 to 1). Second RSI Length: Set the period length for the second RSI calculation. Second RSI Timeframe: Choose the timeframe for the second RSI (e.g., "W" for weekly). Second RSI Scale Factor: Adjust the scale factor for the second RSI (0 to 1). Interpret the DWRSI: A rising DWRSI indicates increasing bullish momentum, while a falling DWRSI suggests growing bearish momentum. Compare the DWRSI with the individual RSI plots to assess the influence of different timeframes. Trading Signals: Potential buy signals are indicated when the DWRSI crosses above key levels (e.g., 30 or 50). Potential sell signals are suggested when the DWRSI crosses below key levels (e.g., 70 or 50). Use Cases: DWRSI is ideal for traders who want to combine short-term and long-term momentum analysis. It suits various trading styles, including swing trading, day trading, and positional trading.
Penunjuk Pine Script®
oleh Ungovernable
Hedge Coin M - Statistical Support and ResistanceHedge Coin M - Statistical Support and Resistance Introduction "Hedge Coin M - Statistical Support and Resistance" is a sophisticated, statistically-driven indicator designed specifically for traders in the COIN-M market on Binance. It offers a nuanced approach to identifying key market levels, focusing on the dynamics of support and resistance through advanced volatility analysis. Foundation and Credits: This script is an advanced adaptation of TradingView's standard code for the Bollinger Bands indicator. It extends the foundational concept of Bollinger Bands by integrating additional volatility metrics. Calculation Method This indicator employs Volume Weighted Moving Averages (VWMA) to create two distinct sets of Bollinger Bands, named BB-a and BB-b. BB-a is derived from the VWMA of high prices, targeting potential resistance levels. BB-b is based on the VWMA of low prices, aimed at identifying critical support levels. Users can independently adjust the standard deviation (SD) multipliers for the upper and lower bands of both BB-a and BB-b, accommodating different market conditions. Enhanced Volatility Analysis The indicator calculates additional standard deviation lines for the upper band of BB-a and the lower band of BB-b. These lines provide deeper insights into market volatility. Plotted Graphs The primary plots include the upper and lower bands of BB-a and BB-b, marked in distinct colors for clarity. Additional SD lines are plotted to indicate potential extended levels of support and resistance, offering traders a broader view of possible market movements. Purpose and Usage "Hedge Coin M - Statistical Support and Resistance" is designed to provide traders with a consistent, statistical method for identifying significant price levels. It aids in scaling entry into positions, helping traders to navigate the COIN-M market with more informed decision-making. This tool is especially useful for traders who combine long-term holding with swing trading strategies, offering a balanced approach to market engagement. Integration and Adaptation Easily integrate this indicator into your TradingView chart for the COIN-M market. Use the insights provided to complement your overall trading strategy, particularly in identifying and reacting to significant market movements. Disclaimer Important Note: This indicator is provided for informational purposes only. It does not constitute financial advice, investment advice, trading advice, or any other sort of advice. Trading decisions should be made based on your own analysis, prudence, and judgment. Please be aware of the risks involved in trading and consult a financial advisor if necessary.
Penunjuk Pine Script®
oleh drmch2020
Minervini Stage 2 AnalysisHandbook for Minervini Stage 2 Analysis Indicator Introduction This handbook provides detailed instructions and guidelines for using the Minervini Stage 2 Analysis Indicator based on Mark Minervini's swing trading methodology. This indicator is designed for traders focusing on US stocks, aiming to capture gains in medium to short-term uptrends (swing trading). Understanding Stage 2 Stage 2 represents a bullish uptrend in a stock's price. Mark Minervini emphasizes entering long positions during this phase. The stage is identified using four key criteria related to moving averages (MAs). Indicator Criteria Stock Price Above MA 150 and 200: Indicates an overall uptrend. MA 150 Above MA 200: Signals a stronger medium-term trend compared to the long-term trend. MA 200 Trending Up for At Least 1 Month (22 Days): Confirms a stable uptrend. MA 50 Above Both MA 150 and 200: Shows short-term strength and momentum. Using the Indicator Entering Trades: Consider long positions when all four criteria are met. This signifies that the stock is in a Stage 2 uptrend. Monitoring Trades: Regularly check if the stock continues to meet these criteria. The indicator provides a clear visual and textual representation for ease of monitoring. Alarm Signals and Exit Strategy One Criterion Not Met: This serves as an alarm signal. Increased vigilance is required, and traders should prepare for a potential exit. Two Criteria Not Met: Strong indication to close the trade. This suggests the stock may be transitioning out of Stage 2, increasing the risk of holding the position. Risk Management Stop-Loss Orders: Consider setting a trailing stop-loss to protect profits and minimize losses. Position Sizing: Adjust position sizes according to your risk tolerance and portfolio strategy. Volume and Relative Strength Analysis Volume Analysis: Look for increased trading volume as confirmation when the stock price moves above key MAs. Relative Strength (RS) Rating: Compare the stock's performance to the broader market to gauge its strength. Limitations and Considerations Market Conditions: The indicator's effectiveness may vary with market conditions. It is more reliable in a bullish market environment. Supplementary Analysis: Combine this indicator with other analysis methods (fundamental, technical) for a holistic approach. Continuous Learning: Stay updated with market trends and adjust your strategy accordingly. Conclusion The Minervini Stage 2 Analysis Indicator is a powerful tool for identifying potential long positions in uptrending stocks. Its reliance on specific criteria aligns with Mark Minervini's proven swing trading strategy. However, always exercise due diligence and risk management in your trading decisions.
Penunjuk Pine Script®
oleh JS_TechTrading
1
ATR Range Accumulation by Standard Deviation and Volume [SS]So, this is an indicator/premise I have been experimenting with, which mixes ATR with Z-Score and Volume metrics. What does the indicator do? The indicator, on the lower timeframes, uses an ATR approach to determine short-term ranges. It takes the average ATR range over a designated lookback period and plots out the levels like so: It then calculates the Z-Score for these ATR targets (shown in the chart above) and calculates, over the designated lookback period, how often price accumulates at that standard deviation level. The indicator is essentially a hybrid of my Z-Score Support and Resistance indicator and my frequency distribution indicator. It combines both concepts into one. You also have the option of sorting by volume accumulation. This will display the accumulation of the ranges by volume accumulation, like so: Larger Timeframes: If you want to see the accumulation by volume or standard deviation on the larger timeframes, you can. Simply toggle on your preferred setting: Show Total Accumulation Breakdown: This will break down the levels, over the lookback period, by standard deviation. This is similar to the Z-Score support and resistance indicator. It will then show you how often price accumulates at these various standard deviation levels. Here is an example on the daily timeframe using the 1D chart settings: Inversely, you can repeat this, with the Z-Score levels, but show accumulation by volume. This will print 5 boxes, which are between +3 Standard Deviations and -3 Standard Deviations, like so: Here we can see that 61% of volume accumulation is between -1 and 1 standard deviation. Using it to Trade: For swing trading, I suggest using the larger timeframe information. However, for both swing and day traders, it is also helpful to use the ATR display. You can modify the ATR display to show the levels on any timeframe by selecting which timeframe you would like to see ATR ranges for. If you are trading on the 1 or 5-minute chart, I suggest leaving the levels at no shorter than a 60-minute timeframe. You can also use these levels on the daily for the weekly levels, etc. The accumulation being shown will be based on the current chart timeframe. This is a function of Pinescript, but in this case, it's actually advantageous because if you are trading on the shorter timeframe, and a level has 0% recent accumulation, it's unlikely we will see that level soon or overly quickly. Intraday retracements will generally happen to areas of high accumulation. How this indicator is different: The difference in this indicator comes from its focus on accumulation in relation to Standard Deviation. There is one thing that is consistent among retail traders, algorithms, market makers, and funds, and that is looking at the market in terms of standard deviation. Each person, market maker, and algorithm may be slightly nuanced in how it conceptualizes standard deviation (whether it be since the inception of the ticker (or IPO), or the previous 500 days, or the previous 100 days, etc.), but the premise remains consistent. Standard Deviation is a really important, if not the most important, metric to pay attention to. Another important metric is volume. Thus, the premise is that combining volume accumulation with standard deviation should, theoretically, be telling. We can see the extent of buying at various standard deviations and whether a stock is really a buy or not. And that's the indicator! Hope you enjoy it. Leave your comments and questions below. Safe trades!
Penunjuk Pine Script®
oleh Steversteves
6
Momentum Candle bar’s open price (open) from its close price (close). That gives the size of the bar’s body. The difference between the open and closed is the candle’s body range. The colour of a candle’s body shows the direction of prices. if Close > Open then it's Bullish Body Candle & if close < open then it's Bearish Body Candle. Stronger the interest of buyers or sellers is reflected in the formation of the Body of Candle. When the body is indeed more than 50% bigger than the average size of a candle then it will show Momentum on the chart. we can see the Colour of the candle Changes When it is Stronger than the Average candle & Body size is Bigger than the Average Candle size. Depending upon Bullish or Bearish the candle Colour Changes to Indicate the Strong Presence of the Buyer or Seller The Candle which strong but not solid and above Average then it will show Normal Colour Of Candle and the Candle which is Below Average will have no colour on Volume Like Bars on the Chart & chart no effect on the candle colour. Buyer or Seller's Activity is always reflected in Candle. This helps us to make Trade Decisions. If Solid Candle at Support or Resistance give or add more Conviction. If Found At Support or resistance will act as Reversal. If found at Swing Low or Retracement, it will help to take trade accordingly with the main trend. Solid Candle Helps in Good Risk to Reward. Mark the High and Low Of the Strong Candle and observe the Price Action. as long as the candle is trading below average helps us to take action for Range Breakout & saves us from Taking Entry in Range. The Distribution at the Top and consolidation at the Bottom can be Observed by the Behaviour of Candles on the Chart. The candle is always a little first step of price action, Whatever Happens in the market is always first printed in a candle, The Leader Candle or Momentum Candle with Follow always Decides the Trend. It's Simple But useful in Day Trading as well as in Swing Trading or Positional Trading too
Penunjuk Pine Script®
oleh Gautam_Dixit
4
MTF Market Structure - SMC IndicatorsThe Multi Timeframe Market Structure helps understand and identify bullish or bearish Market Structure by highlighting “KEY” Highs and Lows. It also identifies changes in market direction by identifying a “Shift in Market Structure” (See Point 2 below) or “Break in Market Structure” (See Point 3 Below). What are Key Highs and Lows? Not every high or low is a “Key” high or low. “Key” highs and lows are specific highs and lows that form the structure of the market and have significance in understanding the current trend in the market (see point 1 below). The indicator identifies these “Key” highs and lows on multiple time frames, allowing the trader to keep a perspective of the Market Structure with multiple timeframes simultaneously (see point 5 below). The key highs and lows identified by the indicator are as follows: Key Lows : Identify significant Swing Lows, Short-term lows “STL”, Intermediate-Term Lows “ITL”, and Long-Term Lows “LTL”. Key Highs : Identify significant Swing Highs, Short-term highs “STH”, Intermediate-Term Highs “ITH”, and Long-Term Highs “LTH”. Significant Swing High : This is a price swing with one lower candle to the right and one lower candle to the left of it. Significant Swing Low : This is a price swing with one higher candle to the right and one higher candle to the left of it. Short-Term High “STH” is a price swing with one lower Significant Swing High to the right and one lower Significant Swing High to the left of it. Short-Term Low “STL” is a price swing with one higher Significant Swing Low to the right and one higher Significant Swing Low to the left of it. Intermediate-Term High “ITH” is a price swing with one lower STH to the right and one lower STH to the left of it. Intermediate-Term Low “ITL” is a price swing with one higher STL to the right and one higher STL to the left of it. Long-Term High “LTH” is a price swing with one lower ITH to the right and one lower ITH to the left of it. Long-Term Low “ITL” is a price swing with one higher ITL to the right and one higher ITL to the left of it. By identifying key highs and lows using the Market Structure Indicator, it can be used in multiple ways by using those reference points as follows: 1. Identifying Market Trends by Connecting Key Highs and Lows. Bullish trend identification is when the indicator is making higher ITLs and ITHs. Bearish Trend identification when the indicator is making lower ITLs and ITHs. PS: it’s essential to understand the underlying market trend on multiple timeframes to use the next features correctly. Always use the Shifts and Breaks in Market Structures in line with the 1H or higher timeframes Market Trend for higher probability trade opportunities. This is because, generally, higher timeframes have more importance than lower timeframes. 2. Shift In Market Structure - SMS for Entries A Shift in Market Structure “SMS” identifies potential reversal in short-term market trend relative to the timeframe where the SMS is identified. This occurs after a run of any Significant Swing High or Low and then reversing, creating a Fair Value Gap “FVG”. There can be Bullish and Bearish Market Structure Shifts. When a Bullish Shift in Market Structure occurs, the indicator identifies an opportunity for the price to change from Bearish to Bullish, as seen in the image below. When a Bearish Shift in Market Structure occurs, the indicator identifies an opportunity for the price to change from Bullish to Bearish. 3. Break In Market Structure - BMS for Entries A Break in Market Structure “BMS” has a similar function to the Shift in Market Structure “SMS”; however, when it occurs, it identifies a potential longer-term trend reversal (compared to the SMS) relative to the timeframe where the BMS is identified. Unlike “SMS”, the BMS occurs after a run only after a run on Key Highs or Lows. Similar to the SMS, there can be Bullish and Bearish Breaks in Market Structure. When a Bullish Break in Market Structure occurs, the indicator identifies an opportunity for a longer-term trend change from Bearish to Bullish, as seen in the image below. The FVG must occur in the lower 50% of the impulse price leg (at Discount). When a Bearish Break in Market Structure occurs, the indicator identifies an opportunity for a longer-term trend change from Bullish to Bearish. The FVG must occur in the upper 50% of the impulse price leg (at Premium). 4. Inversion Break and Shift in Market Structure for Early Entries Inversion “BMS” and “SMS” are similar to the normal SMS and BMS, but they occur: Bullish: When the FVG of the Bearish BMS/SMS forms in the lower 50% of the impulse price leg (at Discount). We use the FVG that forms from the Bearish SMS/BMS as an inversion FVG for potential entry after market trend change from Bearish to Bullish. Bearish: When the FVG of the Bullish BMS/SMS forms in the upper 50% of the impulse price leg (at Premium). We use the FVG that forms from the Bullish SMS/BMS as an inversion FVG for potential entry after market trend change from Bullish to Bearish. 5. Multi Time Frame analysis The indicator allows multiple timeframe perspectives to be considered when using it. The key Highs and Lows have significance not only on the current timeframe they are identified but also on lower or higher timeframes simultaneously. This is because a ITL/ITH on the 1H means It’s a LTL/LTH on one or more timeframes lower (15Min, 5M, and 1Min). And at the same time, it’s a STL/STH on one timeframe higher (4H) Also, it’s a Significant Low/High (marked with a dot) on two timeframes higher (Daily). The same logic applies to all other Key Highs and Lows. Another example is a Significant Low/High (swing marked with a dot below or above it) on the current timeframe (1D) means it’s a STL/STH on one timeframe lower (4H) and an ITL/ITH on two timeframes lower (1H) and a LTH/LTH on three timeframes lower or more (15M, 5M, 1Min, 30 Seconds, etc…). This Multi-time frame analysis is a great way to help traders understand Market Structure and Market trend on multiple timeframes simultaneously, and it also assists in Top-down analysis. PS: Note that this multi-timeframe analysis approach and logic can be applied to any timeframe and for any type of trading (swing trading, day trading, scalping, or short-term trading) because the price is fractal. For example, if a trader is a swing trader, then it’s best to identify trader opportunities on the 1H or higher; however, lower timeframes Market Structure can still be used to help the traders refine their entries and target key highs and lows in the opposite direction. If a trader is a day trader or a scalper, the trader could use Market Structure on 15M or lower to identify trader opportunities and target key highs and lows in the opposite direction. 6. Setting Targets The indicator can also be used to identify potential targets after the SMS or BMS occurs. Targets can be chosen above Key Highs or Lows depending on the trade objective and timeframe where the trade idea is identified. Bonus Features Highlight Market Structure Trend This feature is an excellent backtesting visual tool to look at changes in market trends highlighted in colours. These changes are based on the Shift or Break in of Market Structure depending on the selection option. When "Shift/Break" in Market Structure" is selected, a Bullish trend is highlighted in blue when a Bullish Shift/Break in Market Structure Occurs and in Red when a Bearish Shift/Break in Market Structure Occurs. Notifications Sends notifications when there is a Shift or Break in Market Structure on the current timeframe of choice.
Penunjuk Pine Script®
oleh SMCIndicators
3
Peak & Valley Levels [AlgoAlpha]The Peak & Valley Levels indicator is a sophisticated script designed to pinpoint key support and resistance levels in the market. By utilizing candle length and direction, it accurately identifies potential reversal points, offering traders valuable insights for their strategies. Core Components: Peak and Valley Detection: The script recognizes peaks and valleys in price action. Peaks (potential resistance levels) are identified when a candle is longer than the previous one, changes direction, and closes lower, especially on lower volume. Valleys (potential support levels) are detected under similar conditions but with the candle closing higher. Color-Coded Visualization: Red lines mark resistance levels, signifying peaks in the price action. Green lines indicate support levels, representing valleys. Dynamic Level Adjustment: The script adapts these levels based on ongoing market movements, enhancing their relevance and accuracy. Rejection Functions: Bullish Rejection: Determines if a candlestick pattern rejects a level as potential support. Bearish Rejection: Identifies if a pattern rejects a level as possible resistance. Usage and Strategy Integration: Visual Aid for Support and Resistance: The indicator is invaluable for visualizing key market levels where price reversals may occur. Entry and Exit Points: Traders can use the identified support and resistance levels to fine-tune entry and exit points in their trading strategies. Trend Reversal Signals: The detection of peaks and valleys serves as an early indicator of potential trend reversals. Application in Trading: Versatile for Various Trading Styles: This indicator can be applied across different trading styles, including swing trading, scalping, or trend-following approaches. Complementary Tool: For best results, it should be used alongside other technical analysis tools to confirm trading signals and strategies. Customization and Adaptability: Traders are encouraged to experiment with different settings and timeframes to tailor the indicator to their specific trading needs and market conditions. In summary, the Peak & Valley Levels by AlgoAlpha is a dynamic and adaptable tool that enhances a trader’s ability to identify crucial market levels. Its integration of candlestick analysis with dynamic level adjustment offers a robust method for spotting potential reversal points, making it a valuable addition to any trader's toolkit.
Penunjuk Pine Script®
oleh AlgoAlpha
15
Dynamic Trend Fusion (DTF)The "Dynamic Trend Fusion" (DTF) indicator is a powerful technical analysis tool for traders. It stands out from other indicators due to its adaptability and ability to provide insights into different trading styles. Users can choose from various trading options such as "Short-term Trading," "Long-term Trading," "Aggressive Short-term," "Conservative Long-term," "Balanced Approach," "High Sensitivity," "Low Sensitivity," "Day Trading," and "Swing Trading." These options allow traders to customize the indicator to suit their specific trading strategies. DTF combines the Moving Average Convergence Divergence (MACD) and Relative Strength Index (RSI) indicators, normalizing them to a similar scale for a comprehensive view of market conditions. It then calculates a combined value and smoothes it using a moving average. One of its standout features is the ability to identify bullish and bearish states, which is represented visually on the chart. When the indicator detects a transition from a bullish to a bearish state or vice versa, the color of the line changes. Additionally, DTF offers alert conditions, notifying users when the market shifts into a bullish or bearish state, allowing for timely decision-making. In summary, the DTF indicator sets itself apart by providing traders with a versatile tool that can be tailored to various trading styles and offers clear visual signals for trend changes, enhancing trading precision and efficiency.
Penunjuk Pine Script®
oleh TheRealDrip2Rip
2