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3D Engine OverlayThe Overlay 3D Engine is an advanced and innovative indicator designed to render 3D objects on a trading chart using Pine Script language. This tool enables users to visualize complex geometric shapes and structures on their charts, providing a unique perspective on market trends and data. It is recommended to use this indicator with a time frame of 1 week or greater. The code defines various data structures, such as vectors, faces, meshes, locations, objects, and cameras, to represent the 3D objects and their position in the 3D space. It also provides a set of functions to manipulate these structures, such as scaling, rotating, and translating the objects, as well as calculating their perspective transformation based on a given camera. The main function, "render," takes a list of 3D objects (the scene) and a camera as input, processes the scene, and then generates the corresponding 2D lines to be drawn on the chart. The true range of the asset's price is calculated using an Exponential Moving Average (EMA), which helps adjust the rendering based on the asset's volatility. The perspective transformation function "perspective_transform" takes a mesh, a camera, an object's vertical offset, and the true range as input and computes the 2D coordinates for each vertex in the mesh. These coordinates are then used to create a list of polygons that represent the visible faces of the objects in the scene. The "process_scene" function takes a list of 3D objects and a camera as input and applies the perspective transformation to each object in the scene, generating a list of 2D polygons that represent the visible faces of the objects. Finally, the "render" function iterates through the list of 2D polygons and draws the corresponding lines on the chart, effectively rendering the 3D objects in a 2D projection on the trading chart. The rendering is done using Pine Script's built-in "line" function, which allows for scalable and efficient visualization of the objects. One of the challenges faced while developing the Overlay 3D Engine indicator was ensuring that the 3D objects rendered on the chart would automatically scale correctly for different time frames and trading pairs. Various assets and time frames exhibit different price ranges and volatilities, which can make it difficult to create a one-size-fits-all solution for rendering the 3D objects in a visually appealing and easily interpretable manner. To overcome this challenge, I implemented a dynamic scaling mechanism that leverages the true range of the asset's price and a calculated ratio. The true range is calculated using an Exponential Moving Average (EMA) of the difference between the high and low prices of the asset. This measure provides a smooth estimate of the asset's volatility, which is then used to adjust the scaling of the 3D objects rendered on the chart. The ratio is calculated by dividing the asset's opening price by the true range, which is then divided by a constant factor (32 in this case). This ratio effectively normalizes the scaling of the 3D objects based on the asset's price and volatility, ensuring that the rendered objects appear correctly sized and positioned on the chart, regardless of the time frame or trading pair being analyzed. By incorporating the true range and the calculated ratio into the rendering process, the Overlay 3D Engine indicator is able to automatically adjust the scaling of the 3D objects on the chart, providing a consistent and visually appealing representation of the objects across various time frames and trading pairs. This dynamic scaling mechanism enhances the overall utility and versatility of the indicator, making it a valuable tool for traders and analysts seeking a unique perspective on market trends. In addition to the dynamic scaling mechanism mentioned earlier, the Overlay 3D Engine indicator also employs a sophisticated perspective transformation to render the 3D objects on the chart. Perspective transformation is an essential aspect of 3D graphics, as it provides the necessary conversion from 3D coordinates to 2D coordinates, allowing the 3D objects to be displayed on a 2D chart. The perspective transformation process in the Overlay 3D Engine indicator begins by taking the 3D mesh data of the objects and transforming their vertices based on the position, orientation, and field of view of a virtual camera. The camera's field of view (FOV) is adjusted using a tangent function, which ensures that the rendered objects appear with the correct perspective, regardless of the chart's aspect ratio. Once the vertices of the 3D objects have been transformed, the perspective-transformed 2D coordinates are then used to create polygons that can be rendered on the chart. These polygons represent the visible faces of the 3D objects and are drawn using lines that connect the transformed vertices. The incorporation of perspective transformation in the Overlay 3D Engine indicator ensures that the 3D objects are rendered with a realistic appearance, providing a visually engaging and informative representation of the market trends. This technique, combined with the dynamic scaling mechanism, makes the Overlay 3D Engine indicator a powerful and innovative tool for traders and analysts seeking to visualize and interpret market data in a unique and insightful manner. In summary, the Overlay 3D Engine indicator offers a novel way to interpret and visualize market data, enhancing the overall trading experience by providing a unique perspective on market trends.
Penunjuk Pine Script®
oleh The_Peaceful_Lizard
18
AUTOMATIC GRID BOT STRATEGY [ilovealgotrading] OVERVIEW: This Grid trading strategy can help you maximize your profit in a ranging sideways market with no clear direction. INDICATOR: We can get some money by taking advantage of the movement of the price between the range we have determined. Short positions are opened while the price is rising, long positions are opened while the price is falling. Therefore, there is no need to predict the trend direction. What is different in this indicator: I want to say thank you to © thequantscience. His GRID SPOT TRADING ALGORITHM - GRID BOT TRADING strategy helped me when I was writing my indicator. I want to explain what I have improved: 1- Grid strategy is a type of strategy that can be traded in very short time frames and users can trade this strategy algorithmically by connecting this strategy to their own accounts with the help of API systems. For this reason, I have developed a software that can give us signals by dynamically changing the long and short messages when users are trading. 2- We can change the start and end dates of our grid bot as we want. It is necessary to use this setting when setting up automatic bots, so that previously opened transactions are not taken into account. 3 - Lot or quantity size should not be excessively small when users are taking automatic trades because exchanges have limitations, to avoid this problem, I have prevented this error by automatically rounding up to the nearest quantity size inside the software. 4 - Users can avoid excessive losses by using stop loss on this grid bot if they wish. 5 - When our price is over the range high or below the range low, our open positions are closed, if the stop button is active. We can also change which close price time frame we take as a basis from the settings. 6 -Users can set how many dollars they can enter per transaction while performing their transactions automatically. IMPLEMENTATION DETAILS – SETTINGS: This script allows the user to choose the highs and lows leves of our range. Our bot trades in the specified range. 1. This strategy allows us to set start and end backtest dates. 2. We can change range high and range low leves of our bot 3. IF people want to trade algorithmically with the help of this bot, there are 6 different input systems that will receive the Json codes as an alarm 4. IF the price closes above the upper line or below the lower line, all transactions will be closed. We can determine in which time frame our transactions will be stopped if the price closes outside these levels.We can adjust how our bot works by activating or turning off the Stop Loss button. 5. In this strategy, you can determine your dollar cost for per position. 6. The user can also divide the interval we have determined into 10 parts or 20 equal parts. 7. The grid is divided and colored at the interval we set. At the same time, if we don't want we can turn off colored channels. Notes: If you're going to connect this bot to an automatic Long and Short direction, Don’t forget! you need to Webhook URL, Don’t miss paste this code to your message window {{strategy.order.alert_message}} ALSO: Set your range below the support zones and above the resistance zones. Don't be afraid to take a wide range, it doesn't matter if you make a little money, the important thing is that you don't lose money. If you have any ideas what to add to my work to add more sources or make calculations cooler, suggest in DM .
Strategi Pine Script®
oleh projeadam
106
Zero-lag TEMA Crosses [Loxx]Zero-lag TEMA Crosses is a spinoff of a the Zero-lag MA as described by David Stendahl in the April 2000 issue of the journal "Technical Analysis of Stocks and Commodities". This indicator uses TEMA calculation mode in order to make the lag lesser compared to the original Zero-lag MA, and that makes this version even faster than the Zero-lag DEMA too. This indicator is the difference between a Fast and Slow Zero-lag TEMA. This indicator is very useful for lower timeframe scalping. What is the Zero-lag MA? The Zero-lag MA (Zero-Lag Moving Average) is a technical indicator that was introduced in the April 2000 issue of the journal "Technical Analysis of Stocks and Commodities" by David Stendahl. The Zero-lag MA is a type of moving average (MA) that is designed to reduce or eliminate the lag that is typically associated with traditional moving averages. Moving averages are a widely used technical analysis tool that helps traders to identify trends and potential trading opportunities. They work by calculating the average price of a security over a given period of time, and then plotting that average on a chart. The most commonly used moving averages are simple moving averages (SMAs) and exponential moving averages (EMAs). The problem with traditional moving averages is that they can be slow to respond to changes in market conditions. This lag can cause traders to miss out on potential trading opportunities, or to enter or exit trades at the wrong time. The Zero-lag MA was developed as a solution to this problem. The Zero-lag MA is calculated using a combination of two EMAs and a subtraction formula. The first step in calculating the Zero-lag MA is to calculate two exponential moving averages: a fast EMA and a slow EMA. The fast EMA is calculated over a shorter period of time than the slow EMA. The exact period lengths will depend on the trader's preferences and the security being analyzed. Once the two EMAs have been calculated, the next step is to take the difference between them. This difference represents the current market trend, with a positive value indicating an uptrend and a negative value indicating a downtrend. However, this difference alone is not enough to create a useful indicator, as it can still suffer from lag. To further reduce lag, the difference between the two EMAs is multiplied by a factor derived from a third, slower EMA. This slower EMA acts as a smoothing factor, helping to reduce noise and make the indicator more accurate. The exact period length of the slower EMA will depend on the trader's preferences and the security being analyzed. The final step in calculating the Zero-lag MA is to add the result of the multiplication to the fast EMA. This produces a final value that represents the current market trend with reduced lag. The Zero-lag MA can be plotted on a chart like any other moving average, and can be used to identify trends, potential trading opportunities, and support and resistance levels. Overall, the Zero-lag MA is designed to provide traders with a more accurate representation of current market conditions by reducing the lag time between price changes and the moving average. By doing so, it can help traders to make more informed trading decisions and improve their overall profitability. What is the TEMA? The triple exponential moving average (TEMA) is a technical analysis indicator that was developed to reduce the lag of traditional moving averages, such as the simple moving average (SMA) or the exponential moving average (EMA). The TEMA was first introduced by Patrick Mulloy in the January 1994 issue of the "Technical Analysis of Stocks and Commodities" magazine. The TEMA is a type of moving average that is calculated by applying multiple exponential smoothing techniques to price data. Unlike traditional moving averages, which apply a single smoothing factor to price data, the TEMA applies three smoothing factors to produce a more responsive and accurate indicator. To calculate the TEMA, the following steps are taken: Calculate the single exponential moving average (SMA) of the price data over a given period. Calculate the double exponential moving average (DEMA) of the SMA over the same period. Calculate the triple exponential moving average (TEMA) of the DEMA over the same period. The formula for calculating the TEMA is: TEMA = 3 * EMA(SMA) - 3 * EMA(EMA(SMA)) + EMA(EMA(EMA(SMA))) where EMA is the exponential moving average and SMA is the simple moving average. The TEMA is designed to reduce the lag associated with traditional moving averages by applying multiple smoothing factors to the price data. This helps to filter out short-term price fluctuations and provide a smoother indicator of the underlying trend. The TEMA is also less susceptible to whipsaws, which occur when a security's price moves in one direction and then quickly reverses, causing false trading signals. The TEMA can be used in a variety of ways in technical analysis. It can be used to identify trends, determine support and resistance levels, and generate trading signals. When the TEMA is rising, it is generally interpreted as a bullish signal, indicating that the price is trending higher. When the TEMA is falling, it is generally interpreted as a bearish signal, indicating that the price is trending lower. In summary, the TEMA is a more responsive and accurate indicator than traditional moving averages, designed to reduce lag and provide a smoother representation of the underlying trend. It is a useful tool for technical analysts and traders looking to identify trends, support and resistance levels, and potential trading opportunities. Extras Alerts Bar coloring Signals Loxx's Expanded Source Types, see here:
Penunjuk Pine Script®
oleh loxx
8
Wavemeter [theEccentricTrader]█   OVERVIEW This indicator is a representation of my take on price action based wave cycle theory. The indicator counts the number of confirmed wave cycles, keeps a rolling tally of the average wave length, wave height and frequency, and displays the statistics in a table. The indicator also displays the current wave measurements as an optional feature. █   CONCEPTS Green and Red Candles • A green candle is one that closes with a high price equal to or above the price it opened. • A red candle is one that closes with a low price that is lower than the price it opened. Swing Highs and Swing Lows • A swing high is a green candle or series of consecutive green candles followed by a single red candle to complete the swing and form the peak. • A swing low is a red candle or series of consecutive red candles followed by a single green candle to complete the swing and form the trough. Peak and Trough Prices (Basic) • The peak price of a complete swing high is the high price of either the red candle that completes the swing high or the high price of the preceding green candle, depending on which is higher. • The trough price of a complete swing low is the low price of either the green candle that completes the swing low or the low price of the preceding red candle, depending on which is lower. Historic Peaks and Troughs The current, or most recent, peak and trough occurrences are referred to as occurrence zero. Previous peak and trough occurrences are referred to as historic and ordered numerically from right to left, with the most recent historic peak and trough occurrences being occurrence one. Wave Cycles A wave cycle is here defined as a complete two-part move between a swing high and a swing low, or a swing low and a swing high. As can be seen in the example above, the first swing high or swing low will set the course for the sequence of wave cycles that follow; a chart that begins with a swing low will form its first complete wave cycle upon the formation of the first complete swing high and vice versa. Wave Length Wave length is here measured in terms of bar distance between the start and end of a wave cycle. For example, if the current wave cycle ends on a swing low the wave length will be the difference in bars between the current swing low and current swing high. In such a case, if the current swing low completes on candle 100 and the current swing high completed on candle 95, we would simply subtract 95 from 100 to give us a wave length of 5 bars. Average wave length is here measured in terms of total bars as a proportion as total waves. The average wavelength is calculated by dividing the total candles by the total wave cycles. Wave Height Wave height is here measured in terms of current range. For example, if the current peak price is 100 and the current trough price is 80, the wave height will be 20. Amplitude Amplitude is here measured in terms of current range divided by two. For example if the current peak price is 100 and the current trough price is 80, the amplitude would be calculated by subtracting 80 from 100 and dividing the answer by 2 to give us an amplitude of 10. Frequency Frequency is here measured in terms of wave cycles per second (Hertz). For example, if the total wave cycle count is 10 and the amount of time it has taken to complete these 10 cycles is 1-year (31,536,000 seconds), the frequency would be calculated by dividing 10 by 31,536,000 to give us a frequency of 0.00000032 Hz. Range The range is simply the difference between the current peak and current trough prices, generally expressed in terms of points or pips. █   FEATURES Inputs Show Sample Period Start Date End Date Position Text Size Show Current Show Lines Table The table is colour coded, consists of two columns and, as many as, nine rows. Blue cells display the total wave cycle count and average wave measurements. Green cells display the current wave measurements. And the final row in column one, coloured black, displays the sample period. Both current wave measurements and sample period cells can be hidden at the user’s discretion. Lines For a visual aid to the wave cycles, I have added a blue line that traces out the waves on the chart. These lines can be hidden at the user’s discretion. █   HOW TO USE The indicator is intended for research purposes, strategy development and strategy optimisation. I hope it will be useful in helping to gain a better understanding of the underlying dynamics at play on any given market and timeframe. For example, the indicator can be used to compare the current range and frequency with the average range and frequency, which can be useful for gauging current market conditions versus historic and getting a feel for how different markets and timeframes behave. █   LIMITATIONS Some higher timeframe candles on tickers with larger lookbacks such as the DXY , do not actually contain all the open, high, low and close (OHLC) data at the beginning of the chart. Instead, they use the close price for open, high and low prices. So, while we can determine whether the close price is higher or lower than the preceding close price, there is no way of knowing what actually happened intra-bar for these candles. And by default candles that close at the same price as the open price, will be counted as green. You can avoid this problem by utilising the sample period filter. The green and red candle calculations are based solely on differences between open and close prices, as such I have made no attempt to account for green candles that gap lower and close below the close price of the preceding candle, or red candles that gap higher and close above the close price of the preceding candle. I can only recommend using 24-hour markets, if and where possible, as there are far fewer gaps and, generally, more data to work with. Alternatively, you can replace the scenarios with your own logic to account for the gap anomalies, if you are feeling up to the challenge. It is also worth noting that the sample size will be limited to your Trading View subscription plan. Premium users get 20,000 candles worth of data, pro+ and pro users get 10,000, and basic users get 5,000. If upgrading is currently not an option, you can always keep a rolling tally of the statistics in an excel spreadsheet or something of the like.
Penunjuk Pine Script®
oleh theEccentricTrader
MomentumIndicatorsLibrary "MomentumIndicators" This is a library of 'Momentum Indicators', also denominated as oscillators. The purpose of this library is to organize momentum indicators in just one place, making it easy to access. In addition, it aims to allow customized versions, not being restricted to just the price value. An example of this use case is the popular Stochastic RSI. # Indicators: 1. Relative Strength Index (RSI): Measures the relative strength of recent price gains to recent price losses of an asset. 2. Rate of Change (ROC): Measures the percentage change in price of an asset over a specified time period. 3. Stochastic Oscillator (Stoch): Compares the current price of an asset to its price range over a specified time period. 4. True Strength Index (TSI): Measures the price change, calculating the ratio of the price change (positive or negative) in relation to the absolute price change. The values of both are smoothed twice to reduce noise, and the final result is normalized in a range between 100 and -100. 5. Stochastic Momentum Index (SMI): Combination of the True Strength Index with a signal line to help identify turning points in the market. 6. Williams Percent Range (Williams %R): Compares the current price of an asset to its highest high and lowest low over a specified time period. 7. Commodity Channel Index (CCI): Measures the relationship between an asset's current price and its moving average. 8. Ultimate Oscillator (UO): Combines three different time periods to help identify possible reversal points. 9. Moving Average Convergence/Divergence (MACD): Shows the difference between short-term and long-term exponential moving averages. 10. Fisher Transform (FT): Normalize prices into a Gaussian normal distribution. 11. Inverse Fisher Transform (IFT): Transform the values of the Fisher Transform into a smaller and more easily interpretable scale is through the application of an inverse transformation to the hyperbolic tangent function. This transformation takes the values of the FT, which range from -infinity to +infinity, to a scale limited between -1 and +1, allowing them to be more easily visualized and compared. 12. Premier Stochastic Oscillator (PSO): Normalizes the standard stochastic oscillator by applying a five-period double exponential smoothing average of the %K value, resulting in a symmetric scale of 1 to -1 # Indicators of indicators: ## Stochastic: 1. Stochastic of RSI (Relative Strengh Index) 2. Stochastic of ROC (Rate of Change) 3. Stochastic of UO (Ultimate Oscillator) 4. Stochastic of TSI (True Strengh Index) 5. Stochastic of Williams R% 6. Stochastic of CCI (Commodity Channel Index). 7. Stochastic of MACD (Moving Average Convergence/Divergence) 8. Stochastic of FT (Fisher Transform) 9. Stochastic of Volume 10. Stochastic of MFI (Money Flow Index) 11. Stochastic of On OBV (Balance Volume) 12. Stochastic of PVI (Positive Volume Index) 13. Stochastic of NVI (Negative Volume Index) 14. Stochastic of PVT (Price-Volume Trend) 15. Stochastic of VO (Volume Oscillator) 16. Stochastic of VROC (Volume Rate of Change) ## Inverse Fisher Transform: 1.Inverse Fisher Transform on RSI (Relative Strengh Index) 2.Inverse Fisher Transform on ROC (Rate of Change) 3.Inverse Fisher Transform on UO (Ultimate Oscillator) 4.Inverse Fisher Transform on Stochastic 5.Inverse Fisher Transform on TSI (True Strength Index) 6.Inverse Fisher Transform on CCI (Commodity Channel Index) 7.Inverse Fisher Transform on Fisher Transform (FT) 8.Inverse Fisher Transform on MACD (Moving Average Convergence/Divergence) 9.Inverse Fisher Transfor on Williams R% (Williams Percent Range) 10.Inverse Fisher Transfor on CMF (Chaikin Money Flow) 11.Inverse Fisher Transform on VO (Volume Oscillator) 12.Inverse Fisher Transform on VROC (Volume Rate of Change) ## Stochastic Momentum Index: 1.Stochastic Momentum Index of RSI (Relative Strength Index) 2.Stochastic Momentum Index of ROC (Rate of Change) 3.Stochastic Momentum Index of VROC (Volume Rate of Change) 4.Stochastic Momentum Index of Williams R% (Williams Percent Range) 5.Stochastic Momentum Index of FT (Fisher Transform) 6.Stochastic Momentum Index of CCI (Commodity Channel Index) 7.Stochastic Momentum Index of UO (Ultimate Oscillator) 8.Stochastic Momentum Index of MACD (Moving Average Convergence/Divergence) 9.Stochastic Momentum Index of Volume 10.Stochastic Momentum Index of MFI (Money Flow Index) 11.Stochastic Momentum Index of CMF (Chaikin Money Flow) 12.Stochastic Momentum Index of On Balance Volume (OBV) 13.Stochastic Momentum Index of Price-Volume Trend (PVT) 14.Stochastic Momentum Index of Volume Oscillator (VO) 15.Stochastic Momentum Index of Positive Volume Index (PVI) 16.Stochastic Momentum Index of Negative Volume Index (NVI) ## Relative Strength Index: 1. RSI for Volume 2. RSI for Moving Average rsi(source, length)   RSI (Relative Strengh Index). Measures the relative strength of recent price gains to recent price losses of an asset.   Parameters:      source : (float) Source of series (close, high, low, etc.)      length : (int) Period of loopback   Returns: (float) Series of RSI roc(source, length)   ROC (Rate of Change). Measures the percentage change in price of an asset over a specified time period.   Parameters:      source : (float) Source of series (close, high, low, etc.)      length : (int) Period of loopback   Returns: (float) Series of ROC stoch(kLength, kSmoothing, dSmoothing, maTypeK, maTypeD, almaOffsetKD, almaSigmaKD, lsmaOffSetKD)   Stochastic Oscillator. Compares the current price of an asset to its price range over a specified time period.   Parameters:      kLength      kSmoothing : (int) Period for smoothig stochastic      dSmoothing : (int) Period for signal (moving average of stochastic)      maTypeK : (int) Type of Moving Average for Stochastic Oscillator      maTypeD : (int) Type of Moving Average for Stochastic Oscillator Signal      almaOffsetKD : (float) Offset for Arnaud Legoux Moving Average for Oscillator and Signal      almaSigmaKD : (float) Sigma for Arnaud Legoux Moving Average for Oscillator and Signal      lsmaOffSetKD : (int) Offset for Least Squares Moving Average for Oscillator and Signal   Returns: A tuple of Stochastic Oscillator and Moving Average of Stochastic Oscillator stoch(source, kLength, kSmoothing, dSmoothing, maTypeK, maTypeD, almaOffsetKD, almaSigmaKD, lsmaOffSetKD)   Stochastic Oscillator. Customized source. Compares the current price of an asset to its price range over a specified time period.   Parameters:      source : (float) Source of series (close, high, low, etc.)      kLength : (int) Period of loopback to calculate the stochastic      kSmoothing : (int) Period for smoothig stochastic      dSmoothing : (int) Period for signal (moving average of stochastic)      maTypeK : (int) Type of Moving Average for Stochastic Oscillator      maTypeD : (int) Type of Moving Average for Stochastic Oscillator Signal      almaOffsetKD : (float) Offset for Arnaud Legoux Moving Average for Stoch and Signal      almaSigmaKD : (float) Sigma for Arnaud Legoux Moving Average for Stoch and Signal      lsmaOffSetKD : (int) Offset for Least Squares Moving Average for Stoch and Signal   Returns: A tuple of Stochastic Oscillator and Moving Average of Stochastic Oscillator tsi(source, shortLength, longLength, maType, almaOffset, almaSigma, lsmaOffSet)   TSI (True Strengh Index). Measures the price change, calculating the ratio of the price change (positive or negative) in relation to the absolute price change. The values of both are smoothed twice to reduce noise, and the final result is normalized in a range between 100 and -100.   Parameters:      source : (float) Source of series (close, high, low, etc.)      shortLength : (int) Short length      longLength : (int) Long length      maType : (int) Type of Moving Average for TSI      almaOffset : (float) Offset for Arnaud Legoux Moving Average      almaSigma : (float) Sigma for Arnaud Legoux Moving Average      lsmaOffSet : (int) Offset for Least Squares Moving Average   Returns: (float) TSI smi(sourceTSI, shortLengthTSI, longLengthTSI, maTypeTSI, almaOffsetTSI, almaSigmaTSI, lsmaOffSetTSI, maTypeSignal, smoothingLengthSignal, almaOffsetSignal, almaSigmaSignal, lsmaOffSetSignal)   SMI (Stochastic Momentum Index). A TSI (True Strengh Index) plus a signal line.   Parameters:      sourceTSI : (float) Source of series for TSI (close, high, low, etc.)      shortLengthTSI : (int) Short length for TSI      longLengthTSI : (int) Long length for TSI      maTypeTSI : (int) Type of Moving Average for Signal of TSI      almaOffsetTSI : (float) Offset for Arnaud Legoux Moving Average      almaSigmaTSI : (float) Sigma for Arnaud Legoux Moving Average      lsmaOffSetTSI : (int) Offset for Least Squares Moving Average      maTypeSignal      smoothingLengthSignal      almaOffsetSignal      almaSigmaSignal      lsmaOffSetSignal   Returns: A tuple with TSI, signal of TSI and histogram of difference wpr(source, length)   Williams R% (Williams Percent Range). Compares the current price of an asset to its highest high and lowest low over a specified time period.   Parameters:      source : (float) Source of series (close, high, low, etc.)      length : (int) Period of loopback   Returns: (float) Series of Williams R% cci(source, length, maType, almaOffset, almaSigma, lsmaOffSet)   CCI (Commodity Channel Index). Measures the relationship between an asset's current price and its moving average.   Parameters:      source : (float) Source of series (close, high, low, etc.)      length : (int) Period of loopback      maType : (int) Type of Moving Average      almaOffset : (float) Offset for Arnaud Legoux Moving Average      almaSigma : (float) Sigma for Arnaud Legoux Moving Average      lsmaOffSet : (int) Offset for Least Squares Moving Average   Returns: (float) Series of CCI ultimateOscillator(fastLength, middleLength, slowLength)   UO (Ultimate Oscilator). Combines three different time periods to help identify possible reversal points.   Parameters:      fastLength : (int) Fast period of loopback      middleLength : (int) Middle period of loopback      slowLength : (int) Slow period of loopback   Returns: (float) Series of Ultimate Oscilator ultimateOscillator(source, fastLength, middleLength, slowLength)   UO (Ultimate Oscilator). Customized source. Combines three different time periods to help identify possible reversal points.   Parameters:      source : (float) Source of series (close, high, low, etc.)      fastLength : (int) Fast period of loopback      middleLength : (int) Middle period of loopback      slowLength : (int) Slow period of loopback   Returns: (float) Series of Ultimate Oscilator macd(source, fastLength, slowLength, signalLength, maTypeFast, maTypeSlow, maTypeMACD, almaOffset, almaSigma, lsmaOffSet)   MACD (Moving Average Convergence/Divergence). Shows the difference between short-term and long-term exponential moving averages.   Parameters:      source : (float) Source of series (close, high, low, etc.)      fastLength : (int) Period for fast moving average      slowLength : (int) Period for slow moving average      signalLength : (int) Signal length      maTypeFast : (int) Type of fast moving average      maTypeSlow : (int) Type of slow moving average      maTypeMACD : (int) Type of MACD moving average      almaOffset : (float) Offset for Arnaud Legoux Moving Average      almaSigma : (float) Sigma for Arnaud Legoux Moving Average      lsmaOffSet : (int) Offset for Least Squares Moving Average   Returns: A tuple with MACD, Signal, and Histgram fisher(length)   Fisher Transform. Normalize prices into a Gaussian normal distribution.   Parameters:      length   Returns: A tuple with Fisher Transform and signal fisher(source, length)   Fisher Transform. Customized source. Normalize prices into a Gaussian normal distribution.   Parameters:      source : (float) Source of series (close, high, low, etc.)      length   Returns: A tuple with Fisher Transform and signal inverseFisher(source, length, subtrahend, denominator)   Inverse Fisher Transform. Transform the values of the Fisher Transform into a smaller and more easily interpretable scale is through the application of an inverse transformation to the hyperbolic tangent function. This transformation takes the values of the FT, which range from -infinity to +infinity, to a scale limited between -1 and +1, allowing them to be more easily visualized and compared.   Parameters:      source : (float) Source of series (close, high, low, etc.)      length : (int) Period for loopback      subtrahend : (int) Denominator. Useful in unbounded indicators. For example, in CCI.      denominator   Returns: (float) Series of Inverse Fisher Transform premierStoch(length, smoothlen)   Premier Stochastic Oscillator (PSO). Normalizes the standard stochastic oscillator by applying a five-period double exponential smoothing average of the %K value, resulting in a symmetric scale of 1 to -1.   Parameters:      length : (int) Period for loopback      smoothlen : (int) Period for smoothing   Returns: (float) Series of PSO premierStoch(source, smoothlen, subtrahend, denominator)   Premier Stochastic Oscillator (PSO) of custom source. Normalizes the source by applying a five-period double exponential smoothing average.   Parameters:      source : (float) Source of series (close, high, low, etc.)      smoothlen : (int) Period for smoothing      subtrahend : (int) Denominator. Useful in unbounded indicators. For example, in CCI.      denominator   Returns: (float) Series of PSO stochRsi(sourceRSI, lengthRSI, kLength, kSmoothing, dSmoothing, maTypeK, maTypeD, almaOffsetKD, almaSigmaKD, lsmaOffSetKD)   Parameters:      sourceRSI      lengthRSI      kLength      kSmoothing      dSmoothing      maTypeK      maTypeD      almaOffsetKD      almaSigmaKD      lsmaOffSetKD stochRoc(sourceROC, lengthROC, kLength, kSmoothing, dSmoothing, maTypeK, maTypeD, almaOffsetKD, almaSigmaKD, lsmaOffSetKD)   Parameters:      sourceROC      lengthROC      kLength      kSmoothing      dSmoothing      maTypeK      maTypeD      almaOffsetKD      almaSigmaKD      lsmaOffSetKD stochUO(fastLength, middleLength, slowLength, kLength, kSmoothing, dSmoothing, maTypeK, maTypeD, almaOffsetKD, almaSigmaKD, lsmaOffSetKD)   Parameters:      fastLength      middleLength      slowLength      kLength      kSmoothing      dSmoothing      maTypeK      maTypeD      almaOffsetKD      almaSigmaKD      lsmaOffSetKD stochTSI(source, shortLength, longLength, maType, almaOffset, almaSigma, lsmaOffSet, kLength, kSmoothing, dSmoothing, maTypeK, maTypeD, almaOffsetKD, almaSigmaKD, lsmaOffSetKD)   Parameters:      source      shortLength      longLength      maType      almaOffset      almaSigma      lsmaOffSet      kLength      kSmoothing      dSmoothing      maTypeK      maTypeD      almaOffsetKD      almaSigmaKD      lsmaOffSetKD stochWPR(source, length, kLength, kSmoothing, dSmoothing, maTypeK, maTypeD, almaOffsetKD, almaSigmaKD, lsmaOffSetKD)   Parameters:      source      length      kLength      kSmoothing      dSmoothing      maTypeK      maTypeD      almaOffsetKD      almaSigmaKD      lsmaOffSetKD stochCCI(source, length, maType, almaOffset, almaSigma, lsmaOffSet, kLength, kSmoothing, dSmoothing, maTypeK, maTypeD, almaOffsetKD, almaSigmaKD, lsmaOffSetKD)   Parameters:      source      length      maType      almaOffset      almaSigma      lsmaOffSet      kLength      kSmoothing      dSmoothing      maTypeK      maTypeD      almaOffsetKD      almaSigmaKD      lsmaOffSetKD stochMACD(source, fastLength, slowLength, signalLength, maTypeFast, maTypeSlow, maTypeMACD, almaOffset, almaSigma, lsmaOffSet, kLength, kSmoothing, dSmoothing, maTypeK, maTypeD, almaOffsetKD, almaSigmaKD, lsmaOffSetKD)   Parameters:      source      fastLength      slowLength      signalLength      maTypeFast      maTypeSlow      maTypeMACD      almaOffset      almaSigma      lsmaOffSet      kLength      kSmoothing      dSmoothing      maTypeK      maTypeD      almaOffsetKD      almaSigmaKD      lsmaOffSetKD stochFT(length, kLength, kSmoothing, dSmoothing, maTypeK, maTypeD, almaOffsetKD, almaSigmaKD, lsmaOffSetKD)   Parameters:      length      kLength      kSmoothing      dSmoothing      maTypeK      maTypeD      almaOffsetKD      almaSigmaKD      lsmaOffSetKD stochVolume(kLength, kSmoothing, dSmoothing, maTypeK, maTypeD, almaOffsetKD, almaSigmaKD, lsmaOffSetKD)   Parameters:      kLength      kSmoothing      dSmoothing      maTypeK      maTypeD      almaOffsetKD      almaSigmaKD      lsmaOffSetKD stochMFI(source, length, kLength, kSmoothing, dSmoothing, maTypeK, maTypeD, almaOffsetKD, almaSigmaKD, lsmaOffSetKD)   Parameters:      source      length      kLength      kSmoothing      dSmoothing      maTypeK      maTypeD      almaOffsetKD      almaSigmaKD      lsmaOffSetKD stochOBV(source, kLength, kSmoothing, dSmoothing, maTypeK, maTypeD, almaOffsetKD, almaSigmaKD, lsmaOffSetKD)   Parameters:      source      kLength      kSmoothing      dSmoothing      maTypeK      maTypeD      almaOffsetKD      almaSigmaKD      lsmaOffSetKD stochPVI(source, kLength, kSmoothing, dSmoothing, maTypeK, maTypeD, almaOffsetKD, almaSigmaKD, lsmaOffSetKD)   Parameters:      source      kLength      kSmoothing      dSmoothing      maTypeK      maTypeD      almaOffsetKD      almaSigmaKD      lsmaOffSetKD stochNVI(source, kLength, kSmoothing, dSmoothing, maTypeK, maTypeD, almaOffsetKD, almaSigmaKD, lsmaOffSetKD)   Parameters:      source      kLength      kSmoothing      dSmoothing      maTypeK      maTypeD      almaOffsetKD      almaSigmaKD      lsmaOffSetKD stochPVT(source, kLength, kSmoothing, dSmoothing, maTypeK, maTypeD, almaOffsetKD, almaSigmaKD, lsmaOffSetKD)   Parameters:      source      kLength      kSmoothing      dSmoothing      maTypeK      maTypeD      almaOffsetKD      almaSigmaKD      lsmaOffSetKD stochVO(shortLen, longLen, maType, almaOffset, almaSigma, lsmaOffSet, kLength, kSmoothing, dSmoothing, maTypeK, maTypeD, almaOffsetKD, almaSigmaKD, lsmaOffSetKD)   Parameters:      shortLen      longLen      maType      almaOffset      almaSigma      lsmaOffSet      kLength      kSmoothing      dSmoothing      maTypeK      maTypeD      almaOffsetKD      almaSigmaKD      lsmaOffSetKD stochVROC(length, kLength, kSmoothing, dSmoothing, maTypeK, maTypeD, almaOffsetKD, almaSigmaKD, lsmaOffSetKD)   Parameters:      length      kLength      kSmoothing      dSmoothing      maTypeK      maTypeD      almaOffsetKD      almaSigmaKD      lsmaOffSetKD iftRSI(sourceRSI, lengthRSI, lengthIFT)   Parameters:      sourceRSI      lengthRSI      lengthIFT iftROC(sourceROC, lengthROC, lengthIFT)   Parameters:      sourceROC      lengthROC      lengthIFT iftUO(fastLength, middleLength, slowLength, lengthIFT)   Parameters:      fastLength      middleLength      slowLength      lengthIFT iftStoch(kLength, kSmoothing, dSmoothing, maTypeK, maTypeD, almaOffsetKD, almaSigmaKD, lsmaOffSetKD, lengthIFT)   Parameters:      kLength      kSmoothing      dSmoothing      maTypeK      maTypeD      almaOffsetKD      almaSigmaKD      lsmaOffSetKD      lengthIFT iftTSI(source, shortLength, longLength, maType, almaOffset, almaSigma, lsmaOffSet, lengthIFT)   Parameters:      source      shortLength      longLength      maType      almaOffset      almaSigma      lsmaOffSet      lengthIFT iftCCI(source, length, maType, almaOffset, almaSigma, lsmaOffSet, lengthIFT)   Parameters:      source      length      maType      almaOffset      almaSigma      lsmaOffSet      lengthIFT iftFisher(length, lengthIFT)   Parameters:      length      lengthIFT iftMACD(source, fastLength, slowLength, signalLength, maTypeFast, maTypeSlow, maTypeMACD, almaOffset, almaSigma, lsmaOffSet, lengthIFT)   Parameters:      source      fastLength      slowLength      signalLength      maTypeFast      maTypeSlow      maTypeMACD      almaOffset      almaSigma      lsmaOffSet      lengthIFT iftWPR(source, length, lengthIFT)   Parameters:      source      length      lengthIFT iftMFI(source, length, lengthIFT)   Parameters:      source      length      lengthIFT iftCMF(length, lengthIFT)   Parameters:      length      lengthIFT iftVO(shortLen, longLen, maType, almaOffset, almaSigma, lsmaOffSet, lengthIFT)   Parameters:      shortLen      longLen      maType      almaOffset      almaSigma      lsmaOffSet      lengthIFT iftVROC(length, lengthIFT)   Parameters:      length      lengthIFT smiRSI(source, length, shortLengthTSI, longLengthTSI, maTypeTSI, almaOffsetTSI, almaSigmaTSI, lsmaOffSetTSI, maTypeSignal, smoothingLengthSignal, almaOffsetSignal, almaSigmaSignal, lsmaOffSetSignal)   Parameters:      source      length      shortLengthTSI      longLengthTSI      maTypeTSI      almaOffsetTSI      almaSigmaTSI      lsmaOffSetTSI      maTypeSignal      smoothingLengthSignal      almaOffsetSignal      almaSigmaSignal      lsmaOffSetSignal smiROC(source, length, shortLengthTSI, longLengthTSI, maTypeTSI, almaOffsetTSI, almaSigmaTSI, lsmaOffSetTSI, maTypeSignal, smoothingLengthSignal, almaOffsetSignal, almaSigmaSignal, lsmaOffSetSignal)   Parameters:      source      length      shortLengthTSI      longLengthTSI      maTypeTSI      almaOffsetTSI      almaSigmaTSI      lsmaOffSetTSI      maTypeSignal      smoothingLengthSignal      almaOffsetSignal      almaSigmaSignal      lsmaOffSetSignal smiVROC(length, shortLengthTSI, longLengthTSI, maTypeTSI, almaOffsetTSI, almaSigmaTSI, lsmaOffSetTSI, maTypeSignal, smoothingLengthSignal, almaOffsetSignal, almaSigmaSignal, lsmaOffSetSignal)   Parameters:      length      shortLengthTSI      longLengthTSI      maTypeTSI      almaOffsetTSI      almaSigmaTSI      lsmaOffSetTSI      maTypeSignal      smoothingLengthSignal      almaOffsetSignal      almaSigmaSignal      lsmaOffSetSignal smiWPR(source, length, shortLengthTSI, longLengthTSI, maTypeTSI, almaOffsetTSI, almaSigmaTSI, lsmaOffSetTSI, maTypeSignal, smoothingLengthSignal, almaOffsetSignal, almaSigmaSignal, lsmaOffSetSignal)   Parameters:      source      length      shortLengthTSI      longLengthTSI      maTypeTSI      almaOffsetTSI      almaSigmaTSI      lsmaOffSetTSI      maTypeSignal      smoothingLengthSignal      almaOffsetSignal      almaSigmaSignal      lsmaOffSetSignal smiFT(length, shortLengthTSI, longLengthTSI, maTypeTSI, almaOffsetTSI, almaSigmaTSI, lsmaOffSetTSI, maTypeSignal, smoothingLengthSignal, almaOffsetSignal, almaSigmaSignal, lsmaOffSetSignal)   Parameters:      length      shortLengthTSI      longLengthTSI      maTypeTSI      almaOffsetTSI      almaSigmaTSI      lsmaOffSetTSI      maTypeSignal      smoothingLengthSignal      almaOffsetSignal      almaSigmaSignal      lsmaOffSetSignal smiFT(source, length, shortLengthTSI, longLengthTSI, maTypeTSI, almaOffsetTSI, almaSigmaTSI, lsmaOffSetTSI, maTypeSignal, smoothingLengthSignal, almaOffsetSignal, almaSigmaSignal, lsmaOffSetSignal)   Parameters:      source      length      shortLengthTSI      longLengthTSI      maTypeTSI      almaOffsetTSI      almaSigmaTSI      lsmaOffSetTSI      maTypeSignal      smoothingLengthSignal      almaOffsetSignal      almaSigmaSignal      lsmaOffSetSignal smiCCI(source, length, maTypeCCI, almaOffsetCCI, almaSigmaCCI, lsmaOffSetCCI, shortLengthTSI, longLengthTSI, maTypeTSI, almaOffsetTSI, almaSigmaTSI, lsmaOffSetTSI, maTypeSignal, smoothingLengthSignal, almaOffsetSignal, almaSigmaSignal, lsmaOffSetSignal)   Parameters:      source      length      maTypeCCI      almaOffsetCCI      almaSigmaCCI      lsmaOffSetCCI      shortLengthTSI      longLengthTSI      maTypeTSI      almaOffsetTSI      almaSigmaTSI      lsmaOffSetTSI      maTypeSignal      smoothingLengthSignal      almaOffsetSignal      almaSigmaSignal      lsmaOffSetSignal smiUO(fastLength, middleLength, slowLength, shortLengthTSI, longLengthTSI, maTypeTSI, almaOffsetTSI, almaSigmaTSI, lsmaOffSetTSI, maTypeSignal, smoothingLengthSignal, almaOffsetSignal, almaSigmaSignal, lsmaOffSetSignal)   Parameters:      fastLength      middleLength      slowLength      shortLengthTSI      longLengthTSI      maTypeTSI      almaOffsetTSI      almaSigmaTSI      lsmaOffSetTSI      maTypeSignal      smoothingLengthSignal      almaOffsetSignal      almaSigmaSignal      lsmaOffSetSignal smiMACD(source, fastLength, slowLength, signalLength, maTypeFast, maTypeSlow, maTypeMACD, almaOffset, almaSigma, lsmaOffSet, shortLengthTSI, longLengthTSI, maTypeTSI, almaOffsetTSI, almaSigmaTSI, lsmaOffSetTSI, maTypeSignal, smoothingLengthSignal, almaOffsetSignal, almaSigmaSignal, lsmaOffSetSignal)   Parameters:      source      fastLength      slowLength      signalLength      maTypeFast      maTypeSlow      maTypeMACD      almaOffset      almaSigma      lsmaOffSet      shortLengthTSI      longLengthTSI      maTypeTSI      almaOffsetTSI      almaSigmaTSI      lsmaOffSetTSI      maTypeSignal      smoothingLengthSignal      almaOffsetSignal      almaSigmaSignal      lsmaOffSetSignal smiVol(shortLengthTSI, longLengthTSI, maTypeTSI, almaOffsetTSI, almaSigmaTSI, lsmaOffSetTSI, maTypeSignal, smoothingLengthSignal, almaOffsetSignal, almaSigmaSignal, lsmaOffSetSignal)   Parameters:      shortLengthTSI      longLengthTSI      maTypeTSI      almaOffsetTSI      almaSigmaTSI      lsmaOffSetTSI      maTypeSignal      smoothingLengthSignal      almaOffsetSignal      almaSigmaSignal      lsmaOffSetSignal smiMFI(source, length, shortLengthTSI, longLengthTSI, maTypeTSI, almaOffsetTSI, almaSigmaTSI, lsmaOffSetTSI, maTypeSignal, smoothingLengthSignal, almaOffsetSignal, almaSigmaSignal, lsmaOffSetSignal)   Parameters:      source      length      shortLengthTSI      longLengthTSI      maTypeTSI      almaOffsetTSI      almaSigmaTSI      lsmaOffSetTSI      maTypeSignal      smoothingLengthSignal      almaOffsetSignal      almaSigmaSignal      lsmaOffSetSignal smiCMF(length, shortLengthTSI, longLengthTSI, maTypeTSI, almaOffsetTSI, almaSigmaTSI, lsmaOffSetTSI, maTypeSignal, smoothingLengthSignal, almaOffsetSignal, almaSigmaSignal, lsmaOffSetSignal)   Parameters:      length      shortLengthTSI      longLengthTSI      maTypeTSI      almaOffsetTSI      almaSigmaTSI      lsmaOffSetTSI      maTypeSignal      smoothingLengthSignal      almaOffsetSignal      almaSigmaSignal      lsmaOffSetSignal smiOBV(source, shortLengthTSI, longLengthTSI, maTypeTSI, almaOffsetTSI, almaSigmaTSI, lsmaOffSetTSI, maTypeSignal, smoothingLengthSignal, almaOffsetSignal, almaSigmaSignal, lsmaOffSetSignal)   Parameters:      source      shortLengthTSI      longLengthTSI      maTypeTSI      almaOffsetTSI      almaSigmaTSI      lsmaOffSetTSI      maTypeSignal      smoothingLengthSignal      almaOffsetSignal      almaSigmaSignal      lsmaOffSetSignal smiPVT(source, shortLengthTSI, longLengthTSI, maTypeTSI, almaOffsetTSI, almaSigmaTSI, lsmaOffSetTSI, maTypeSignal, smoothingLengthSignal, almaOffsetSignal, almaSigmaSignal, lsmaOffSetSignal)   Parameters:      source      shortLengthTSI      longLengthTSI      maTypeTSI      almaOffsetTSI      almaSigmaTSI      lsmaOffSetTSI      maTypeSignal      smoothingLengthSignal      almaOffsetSignal      almaSigmaSignal      lsmaOffSetSignal smiVO(shortLen, longLen, maType, almaOffset, almaSigma, lsmaOffSet, shortLengthTSI, longLengthTSI, maTypeTSI, almaOffsetTSI, almaSigmaTSI, lsmaOffSetTSI, maTypeSignal, smoothingLengthSignal, almaOffsetSignal, almaSigmaSignal, lsmaOffSetSignal)   Parameters:      shortLen      longLen      maType      almaOffset      almaSigma      lsmaOffSet      shortLengthTSI      longLengthTSI      maTypeTSI      almaOffsetTSI      almaSigmaTSI      lsmaOffSetTSI      maTypeSignal      smoothingLengthSignal      almaOffsetSignal      almaSigmaSignal      lsmaOffSetSignal smiPVI(source, shortLengthTSI, longLengthTSI, maTypeTSI, almaOffsetTSI, almaSigmaTSI, lsmaOffSetTSI, maTypeSignal, smoothingLengthSignal, almaOffsetSignal, almaSigmaSignal, lsmaOffSetSignal)   Parameters:      source      shortLengthTSI      longLengthTSI      maTypeTSI      almaOffsetTSI      almaSigmaTSI      lsmaOffSetTSI      maTypeSignal      smoothingLengthSignal      almaOffsetSignal      almaSigmaSignal      lsmaOffSetSignal smiNVI(source, shortLengthTSI, longLengthTSI, maTypeTSI, almaOffsetTSI, almaSigmaTSI, lsmaOffSetTSI, maTypeSignal, smoothingLengthSignal, almaOffsetSignal, almaSigmaSignal, lsmaOffSetSignal)   Parameters:      source      shortLengthTSI      longLengthTSI      maTypeTSI      almaOffsetTSI      almaSigmaTSI      lsmaOffSetTSI      maTypeSignal      smoothingLengthSignal      almaOffsetSignal      almaSigmaSignal      lsmaOffSetSignal rsiVolume(length)   Parameters:      length rsiMA(sourceMA, lengthMA, maType, almaOffset, almaSigma, lsmaOffSet, lengthRSI)   Parameters:      sourceMA      lengthMA      maType      almaOffset      almaSigma      lsmaOffSet      lengthRSI
Perpustakaan Pine Script®
oleh andre_007
6
ATR-Stepped, Another New Adaptive Moving Average [Loxx]ATR-Filtered, Another New Adaptive Moving Average is a modification of @cheatcountry's "Another New Adaptive Moving Average " shown below I've added AT- stepped filtering. This is a standard ATR filter that works by requiring movement by XX multiple of ATR before registering a trend flip. I've also included Loxx's Expanded Source Types. You can read about those here: From @cheatcountry on A New Adaptive Moving Average The New Adaptive Moving Average was created by Scott Cong (Stocks and Commodities Mar 2023) and this is a companion indicator to my previous script This indicator still works off of the same concept as before with effort vs results but this indicator takes a slightly different approach and instead defines results as the absolute difference between the closing price and a closing price x bars ago. As you can see in my chart example, this indicator works great to stay with the current trend and provides either a stop loss or take profit target depending on which direction you are going in. As always, I use darker colors to show stronger signals and lighter colors to show normal signals. Buy when the line turns green and sell when it turns red. Included Alerts Signals Loxx's Expanded Source Types
Penunjuk Pine Script®
oleh loxx
4
Hikkake Hunter 2.0This script serves as a successor to a previous script I wrote for identifying Hikkakes nearly two years ago. The old version has been preserved here: █  OVERVIEW This script is a rework of an old script that identified the Hikkake candlestick pattern. While this pattern is not usually considered a part of the standard candlestick patterns set, I found a lot of value when finding a solution to identifying it. A Hikkake pattern is a 3-candle pattern where a middle candle is nested in between the range of the prior candle, and a candle that follows has a higher high and a higher low (bearish setup) or a lower high and a lower low (bullish setup). What makes this pattern unique is the "confirmation" status of the pattern; within 3 candles of this pattern's appearance, there must be a candle that closes above the high (bullish setup) or below the low (bearish setup) of the second candle. Additional flexibility has been added which allows the user to specify the number of candles (up to 5) that the pattern may have to confirm after its appearance. █  CONCEPTS This script will cover concepts mainly focusing on candlestick analysis, price analysis (with higher timeframes), and statistical analysis. I believe there is also educational value presented with the use of user-defined-types (UDTs) in accomplishing these concepts that I hope others will find useful. Candlestick Analysis - Identification and confirmation of the patterns in the deprecated script were clunky and inefficient. While the previous script required the use of 6 candles to perform the confirmations of patterns (restricted solely to identifying patterns that confirmed in 3 candles or less), this script only requires 3 candles to identify and process patterns by utilizing a UDT representing a 'pattern object'. An object representing a pattern will be created when it has been identified, and fields within that object will be set for processing by the functions it is passed to. Pattern objects are held by a var array (values within the array persist between bars) and will be removed from this array once they have been confirmed or non-confirmed. This is a significant deviation from the previous script's methods, as it prevents unnecessary re-evaluations of the confirmation status of patterns (i.e. Hikkakes confirmed on the first candle will no longer need to be checked for confirmations on the second or third; a pitfall of the deprecated version which required multiple booleans tracking prior confirmation statuses). This deviation is also what provides the flexibility in changing the number of candles that can pass before a pattern is deemed non-confirmed. As multiple patterns can be confirmed simultaneously, this script uses another UDT representing a linked-list reduction of the pattern object used to process it. This liked-list object will then be used for Price Analysis. Price Analysis - This script employs the use of a UDT which contains all the returns of confirmed patterns. The user specifies how many candles ahead of the confirmed pattern to calculate its return, as well as where this calculation begins. There are two settings: FROM APPEARANCE and FROM CONFIRMATION (default). Price differences are calculated from the open of the candle immediately following the candle which had confirmed the pattern to the close of the candle X candles ahead (default 10). ( SEE FEATURES ) Because of how Pine functions, this calculation necessitates a lookback on prior candles to identify when a pattern had been confirmed. This is accomplished with the following pseudo-code: if not na(confirmed linked-list ) for all confirmed in list GET MATRIX PLACEMENT offset = FROM CONFIRMATION ? 0 : # of candles to confirm openAtFind = open percent return = ((close - openAtFind) / openAtFind) * 100 ADD percent return TO UDT IN MATRIX All return UDTs are held in a matrix which breaks up these patterns into specific groups covered in the next section. Higher Timeframes - This script makes a request.security call to a higher timeframe in order to identify a price range which breaks up these patterns into groups based on the 'partition' they had appeared in. The default values for this partitioning will break up the chart into three sections: upper, middle, and lower. The upper section represents the highest 20% of the yearly trading range that an asset has experienced. The lower section represents the trading range within a third (33%) of the yearly low. And the middle section represents the yearly high-low range between these two partitions. The matrix containing all return UDTs will have these returns split up based on the number of candles required to confirm the pattern as well as the partition the pattern had appeared in. The underlying rationale is that patterns may perform better or worse at different parts of an asset's trading range. Statistical Analysis - Once a pattern has been confirmed, the matrix containing all return UDTs will be queried to check if a 'returnArray' object has been created for that specific pattern. If not, one will be initialized and a confirmed linked-list object will be created that contains information pertinent to the matrix position of this object. This matrix contains the returns of both the Bullish and Bearish Hikkake patterns, separated by the number of candles needed to confirm them, and by the partitions they had appeared in. For the standard 3 candles to confirm, this means the matrix will contain 18 elements (dependent on the number of candles allowed for confirmations; its size will range from 12 to 30). When the required number of candles for Price Analysis passes, a percent return is calculated and added to the returnArray contained in the matrix at the location derived from the confirmed linked-list object's values. The return is added, and all values in the returnArray are updated using Pine's built in array.___ functions. This returnArray object contains the array of all returns, its size, its average, the median, the standard deviation of returns, and a separate 3-integer array which holds values that correspond to the types of returns experienced by this pattern (negative, neutral, and positive)*. After a pattern has been confirmed, this script will place the partition and all of the aforementioned stats values (plus a 95% confidence interval of expected returns) related to that pattern onto the tooltip of the label that identifies it. This allows users to scroll over the label of a confirmed pattern to gauge its prior performance under specific conditions. The percent return of the specific pattern identified will later be placed onto the label tooltip as well. ( SEE LIMITATIONS ) The stats portion of this script also plays a significant role in how patterns are presented when using the Adaptive Coloring mode described in FEATURES . *These values are incremented based on user-input related to what constitutes a 'negative' or 'positive' return. Default values would place any return by a pattern between -3% and 3% in the 'neutral' category, and values exceeding either end will be placed in the 'negative' or 'positive' categories. █  FEATURES This script contains numerous inputs for modifying its behavior and how patterns are presented/processed, separated into 5 groups. Confirmation Setting - The most important input for this script's functioning. This input is a 'confirm=true' input and must be set by the user before the script is applied to the chart. It sets the number of candles that a pattern has to confirm once it has been identified. Alert Settings - This group of booleans sets which types of alerts will fire during the scripts execution on the chart. If enabled, the four alerts will trigger when: a pattern has been identified, a pattern has been confirmed, a pattern has been non-confirmed, and show the return for that confirmed pattern in an alert. Because this script uses the 'alert' function and not 'alertcondition', these must be enabled before 'any alert() function call' is set in TradingView's 'alerts' settings. Partition Settings - This group of inputs are responsible for creating (and viewing) the partitions that breaks the returns of the patterns identified up into their respective groups. The user may set the resolution to grab the range from, the length back of this resolution the partitions get their values from, the thresholds which breaks the partitions up into their groups, and modify the visibility (if they're shown, the colors, opacity) of these partitions. Stats Settings - These inputs will drastically alter how patterns are presented and the resulting information derived from them after their appearance. Because of this section's importance, some of these inputs will be described in more detail. P/L Sample Length - Defines the number of candles after the starting point to grab values from in the % return calculation for that pattern. P/L Starting Point - Defines the starting point where the P/L calculation will take place. 'FROM APPEARANCE' will set the starting point at the candle immediately following the pattern's appearance. 'FROM CONFIRMATION' will place the starting point immediately following the candle which had confirmed the pattern. ( SEE LIMITATIONS ) Min Returns Needed - Sets how many times a specific pattern must appear (both by number of candles needed to confirm and by partition) before the statistics for that pattern are displayed onto the tooltip (and for gradient coloration in Adaptive Coloring mode). Enable Adaptive Coloring - Changes the coloration of the patterns based on the bullish/bearishness of the specified Gradient Reference value of that pattern compared to the Return Tolerance values OR the minimum and maximum values of that specified Gradient Reference value contained in the matrix of all returns. This creates a color from a gradient using the user-specified colors and alters how many of the patterns may appear if prior performance is taken into account. Gradient Reference - Defines which stats measure of returns will be used in the gradient color generation. The two settings are 'AVG' and 'MEDIAN'. Hard Limit - This boolean sets whether the Return Tolerance values will not be replaced by values that exceed them from the matrix of returns in color gradient generation. This changes the scale of the gradient where any Gradient Reference values of patterns that exceed these tolerances will be colored the full bullish or bearish gradient colors, and anything in between them will be given a color from the gradient. Visibility Settings - This last section includes all settings associated with the overall visibility of patterns found with this script. This includes the position of the labels and their colors (+ pattern colors without Adaptive Coloring being enabled), and showing patterns that were non-confirmed. Most of these inputs in the script have these kinds of descriptions to what they do provided by their tooltips. █  HOW TO USE I attempted to make this script much easier to use in terms of analyzing the patterns and displaying the information to the user. The previous script would have the user go to the 'data window' side bar on TradingView to view the returns of a pattern after they had specified which pattern to analyze through the settings, needlessly convoluted. This aim at simplicity was achieved through the use of UDTs and specific code-design. To use, simply apply the indicator to a chart, set the number of candles (between 2 and 5) for confirming this specific pattern and adjust the many settings described above at your leisure. █  LIMITATIONS Disclaimer - This is a tool created with the hopes of helping identify a specific pattern and provide an informative view about the performance of that pattern. Previous performance is not indicative of future results. None of this constitutes any form of financial advice, *use at your own risk*. Statistical Analysis - This script assumes that all patterns will yield a NORMAL DISTRIBUTION regarding their returns which may not be reflective of reality. I personally have limited experience within the field of statistics apart from a few high school/college courses and make no guarantees that the calculation of the 95% confidence interval is correct. Please review the source code to verify for yourself that this interval calculation is correct (Function Name: f_DisplayStatsOnLabel). P/L Starting Point - Because of when the object related to the confirmation status of a pattern is created (specifically the linked-list object) setting the 'P/L Starting Point' to 'FROM APPEARANCE' will yield the results of that P/L calculation at the same time as 'FROM CONFIRMATION'. █ EXAMPLES Default Settings: Partition Background (default): Partition Background (Resolution D : Length 30): Adaptive Coloration: Show Non-Confirmed:
Penunjuk Pine Script®
oleh SolCollector
2
Extended Price Volume Trend Strategy : EducationalThe Extended Price Volume Trend (EPVT) is a technical indicator that is used to identify potential trend changes and measure the strength of a trend. In this strategy, we combine the EPVT with other indicators to create a trading system that aims to capture trend reversals and momentum shifts. The EPVT indicator is calculated by taking the cumulative volume and multiplying it by the percentage change in price. We then find the highest and lowest values of this indicator over a certain period of time to determine the baseline. The difference between the EPVT and the baseline is then plotted on a chart to create the EPVT line. To use this indicator for trading, we look for crossovers of the EPVT line with zero. When the EPVT crosses above zero, it indicates that buying pressure is increasing, and we may consider taking a long position. Conversely, when the EPVT crosses below zero, it indicates that selling pressure is increasing, and we may consider taking a short position. To further refine our trading signals, we use three take-profit levels, which we set as a percentage of the current EPVT value. We also use a simple moving average to provide additional confirmation of trend changes. In summary, the EPVT trading strategy is a technical analysis-based approach to trading that aims to identify potential trend reversals and momentum shifts. By combining the EPVT indicator with other technical tools, we can create a comprehensive trading system that provides clear entry and exit signals for both long and short positions. Please note that this strategy is for educational purposes only and should not be taken as financial advice.
Strategi Pine Script®
oleh Oracle_Systems
1
Trend Line Trendlines are easily recognizable lines that traders draw on charts to connect a series of prices together or show some data's best fit. The resulting line is then used to give the trader a good idea of the direction in which an investment's value might move. A trendline is a line drawn over pivot highs or under pivot lows to show the prevailing direction of price. Trendlines are a visual representation of support and resistance in any time frame. They show direction and speed of price, and also describe patterns during periods of price contraction. Key Takeaways Trendlines indicate the best fit of some data using a single line. A single trendline can be applied to a chart to give a clearer picture of the trend. The time period being analyzed and the exact points used to create a trendline vary from trader to trader. The trendline is among the most important tools used by technical analysts. Instead of looking at past business performance or other fundamentals, technical analysts look for trends in price action. A trendline helps technical analysts determine the current direction in market prices. Technical analysts believe the trend is your friend, and identifying this trend is the first step in the process of making a good trade. To create a trendline, an analyst must have at least two points on a price chart. Some analysts like to use different time frames such as one minute or five minutes. Others look at daily charts or weekly charts. Some analysts put aside time altogether, choosing to view trends based on tick intervals rather than intervals of time. What makes trendlines so universal in usage and appeal is they can be used to help identify trends regardless of the time period, time frame or interval used.
Penunjuk Pine Script®
oleh HPotter
7
Previous Levels With Custom TimeZoneThe Previous Levels With Custom TimeZone indicator shows to users specifics price area which can be liquidity to take. Users can determine the desired time zone to retrieve the correct daily, weekly and monthly values. Several price area are shown with with indicator which are : Daily Open Price Daily Low Price Daily High Price Previous Daily Low Price Previous Daily High Price Previous Weekly Low Price Previous Weekly High Price Previous Monthly Low Price Previous Monthly High Price All price area are configurable to let user have specific color or line style for each area. Here's some example : Daily Open / High / Low Previous Daily High / Low Previous Weekly High / Low Previous Monthly High / Low
Penunjuk Pine Script®
oleh LudoGH68
19
[JL] Fractals ATR BlockI decided to combine Fractal ROC , ATR Break, and Order Blocks to an Indicator The Fractal ROC , ATR Break, and Order Blocks indicator combines three concepts to help traders identify potential trade opportunities and manage risk. By using a combination of Fractal ROC , ATR Break, and Order Blocks, traders can gain a deeper understanding of market dynamics and make more informed trading decisions. Fractal ROC is a momentum-based indicator that calculates the rate of change of the price between fractals, which are turning points in the market. It is calculated by taking the difference between the closing price and the lowest price in the previous n+1 periods, and dividing it by the difference between the open price 2n periods ago and the lowest price in the previous n+1 periods. This calculation is done for both up and down fractals. When the Fractal ROC value is greater than the ROC Break Level (as determined by the input variable roclevel), it indicates a potential momentum shift in the market. This can be used to identify potential trade entries or exits, depending on your trading strategy. ATR Break is an indicator that helps traders identify significant price movements in the market. It measures the distance between the price and the Average True Range (ATR), which is a measure of the volatility of the market. ATR Break is calculated by taking the difference between the close and high/low, and dividing it by the previous ATR value. This calculation is done for both up and down movements. When the ATR Break value is greater than the ATR Break Level (as determined by the input variable atrlevel), it indicates a significant move in the market. This can be used to identify potential breakouts or breakdowns, and can be used to set stop-loss and take-profit levels. An Order Block is a price level where significant buying or selling activity has taken place. The order blocks made by ATR Break and Fractal ROC are drawn using boxes on the chart. When the ATR or Fractal ROC level is breached, a box is drawn with the high and low of the candle that breached the level as the top and bottom of the box, respectively. The box is then extended to the right until the end of the chart or until another ATR or Fractal ROC level is breached, at which point a new box is drawn. This allows traders to easily identify significant price movements and potential support and resistance levels on the chart. When an Order Block is identified, it can be used as a potential support or resistance level . If price approaches an Order Block from below, it is likely to bounce off this level and continue in an upward direction. Similarly, if price approaches an Order Block from above, it is likely to bounce off this level and continue in a downward direction. Traders can use these levels to identify potential trade entries or exits, as well as to set stop-loss and take-profit levels. Overall, the Fractal ROC , ATR Break, and Order Blocks indicator is a powerful tool for traders who want to identify potential trade opportunities and manage risk. By combining these three concepts, traders can gain a deeper understanding of market dynamics and make more informed trading decisions. As with any indicator, it is important to use it in conjunction with other analysis tools and to have a clear trading plan in place.
Penunjuk Pine Script®
oleh Jesse.Lau
Futures All List Candle Analysis - FALCAIn this command; There is an alphabetical list of USDS-M coins with the USDT PERP extension on the Binance Futures side. There are 13 lists in total. Each list contains 39 data. Due to data limitation, 13 lists are formed. There are 13 coins in the first 11 of the lists. The 12th list contains 3 coins. The last list (FAVORITE LIST) is CRYPTOCAP:TOTAL, BINANCE:BTCUSDTPERP, BINANCE:BTCDOMUSDTPERP as standard. You must add 10 coins to the final list. The lists show data for the time period you selected. Explanation of the (C/H) header: Close /High takes a maximum value of 1. As long as this value is 1, a price increase is observed. Explanation of the (C/O) header: Close /Open can be greater than ,1. In this case, a price increase is observed. Close /Open can be less than 1. In this case, a price decrease is observed. The value Close /Open can be equal to 1. In this case, price stability is observed. Explanation of the (C/L) header: Close /Low takes a minimum value of 1. As long as this value is 1, a price decrease is observed. Coins with a price decrease are shown in red. Coins with a price increase will turn green. ***NOTE: For this command to work, you must first add 10 favorite coins to the "FAVORITE LIST".
Penunjuk Pine Script®
oleh gokhanpirnal
2
Another New Adaptive Moving Average [CC]The New Adaptive Moving Average was created by Scott Cong (Stocks and Commodities Mar 2023) and this is a companion indicator to my previous script . This indicator still works off of the same concept as before with effort vs results but this indicator takes a slightly different approach and instead defines results as the absolute difference between the closing price and a closing price x bars ago. As you can see in my chart example, this indicator works great to stay with the current trend and provides either a stop loss or take profit target depending on which direction you are going in. As always, I use darker colors to show stronger signals and lighter colors to show normal signals. Buy when the line turns green and sell when it turns red. Let me know if there are any other indicator scripts you would like to see me publish!
Penunjuk Pine Script®
oleh cheatcountry
2
Quantitative Price Forecasting - The Quant ScienceThis script is a quantitative price forecasting indicator that forecasts price changes for a given asset. The model aims to forecast future prices by analyzing past data within a selected time period. Mathematical probability is used to calculate whether starting from time X can lead to reaching prices Y1 and Y2. In this context, X represents the current selected time period, Y1 represents the selected percentage decrease, and Y2 represents the selected percentage increase. The probabilities are estimated using the simple average. The simple average is displayed on the chart, showing in red the periods where the price is below the average and in green the periods where the price is above the average. This powerful tool not only provides forecasts of future prices but also calculates the distribution of variations around the average. It then takes this information and creates an estimate of the average price variation around the simple average. Using a mean-reverting logic, buying and selling opportunities are highlighted. We recommend turning off the display of bars on your chart for a better experience when using this indicator. Unlock the full potential of your trading strategy with our powerful indicator. By analyzing past price data, it provides accurate forecasts and calculates the probability of reaching specific price targets. Its mean-reverting logic highlights buying and selling opportunities, while the simple moving average displayed on the chart shows periods where the price is above or below the average. Additionally, it estimates the average variation of price around the simple average, giving you valuable insights into price movements. Don't miss out on this valuable tool that can take your trading to the next level
Penunjuk Pine Script®
oleh thequantscience
13
Bitcoin Correlation MapHello everyone, This indicator shows the correlation coefficients of altcoins with bitcoin in a table. What is the correlation coefficient? The correlation coefficient is a value that takes a value between 0 and 1 when a parity makes similar movements with the reference parity, and takes a value between 0 and -1 when it makes opposite movements. In order to obtain more meaningful and real-time results in this indicator, the weighted average of the correlation values of the last 200bar was used. You can change the bar length as you wish. With the correlation value, you can see the parities that have similar movements with bitcoin and integrate them into your strategy. You can change the coin list as you wish, and you can also calculate their correlation with etherium instead of bitcoin . The indicator shows the correlation value of 36 altcoins at the moment. The indicator indicates the color of the correlated parities as green and the color of the inversely correlated parities as red. Cheers
Penunjuk Pine Script®
oleh Milvetti
7
Expected Move Plotter [CHE]Expected Move Plotter "There is magic in everything new." Introduction: This script is an indicator for financial trading that plots the expected movement of a security based on the average range over the last five periods. The script is written in Pine Script, a high-level programming language used for creating technical indicators, strategies, and other trading tools for the TradingView platform. Inputs: Percentage of Open and Close: This input specifies the percentage of the open and close price to use for the expected movement. Time Periods: The script takes the different time periods into account and translates them to either 60 seconds, 240 seconds, 1 day, 3 days, 7 days, 1 month, 3 months or 12 months. Calculation: The script uses the "Open" and "High"/"Low" values of the last 5 periods to calculate the average range and plots the expected movement above and below the current open price. The plot is either green or red depending on whether the expected move is above or below the current close. Code Breakdown: The script starts by defining three integer constants: MS_IN_MIN, MS_IN_HOUR, and MS_IN_DAY, which represent the number of milliseconds in a minute, hour, and day, respectively. The function timeStep_translate() returns a string that represents the timeframe for a chart based on the current timeframe. The function first converts the chart's timeframe to milliseconds and then uses a switch statement to determine the string value to be returned based on the number of milliseconds in the timeframe. The script then retrieves the data for the open, high, and low values for the last five periods. The high and low values are used to calculate the average range, which is then used to plot the expected movement above and below the current open price. Conclusion: This script provides traders with a visual representation of the expected movement of a security based on the average range over the last five periods. It takes different time periods into account and provides a clear indication of whether the expected move is above or below the current close. The script is easy to use and provides a useful tool for traders looking to make informed trading decisions. Best regards Chervolino
Penunjuk Pine Script®
oleh chervolino
1
InsideBar2.0Inside Bar: Inside Bar is defined as, " when candle body range falls within previous day candle body". Some of us take the whole prices range . Here i have taken only the price range of the body of tehecandle. I have created an indicator to identify Inside bras and draw target levels on both the sides. Traders can easily convert it into a strategy and checkout the success rate. This script is written to identify InsideBar and then plot target 1 and target 2 irrespective the direction of following candles. Inside Bar is here defined clearly when the whole body( Not high/Low, but Open and Close Only of the candle falls within the whole body of previous candle Few static Variables are declared for one time use to store the following values MotherCandle Index High and Low of MotherCandle Target 1 equal to size of the body of mother candle Target 2 equal twice the size of Mother Candle Depending upon the direction of the trend and breakout of the MotherCandle boundaries, target lines and labels are drawn. Line.delete function is used to delete all the previous lines to keep the chart clean and not draw line on all every inside-bar detected in the past. Label.delete function is used to delete all the previous labels for Target levels to clearly show current target levels. barcolor() function is used to change the inside bar candle changed to "Yellow" .
Penunjuk Pine Script®
oleh Dr_AtulGoswami
23
Stock Relative Strength Power IndexAs always, this is not financial advice and use at your own risk. Trading is risky and can cost you significant sums of money if you are not careful. Make sure you always have a proper entry and exit plan that includes defining your risk before you enter a trade. This idea recently came out of some discussions I stumbled across in a trading group I am a part of regarding Relative Strength and Relative Weakness (shortened to RS and RW from here on out). The whole mechanism behind this trading system is to filter out underperforming securities relative to the current market direction to be in only the strongest or weakest stocks when the market is currently experiencing a bullish or bearish cycle. The idea behind this is there is no point in parking your money into a stock that is treading water or even going down if the market is making strong moves upwards. At that point, you are at worst losing money, and at best trading equal to the index/ETF, in which case the argument is why are you not just trading the index/ETF instead? RS or RW will filter out these sector laggards and allow you to position yourself into strong (or the strongest) stocks at any given time to help improve portfolio performance. Further, not only does it protect your position should the market shift against you briefly, it also often sees exceptional performance in the same cycle. For example, if $SPY makes a 5% move over the course of a month, a stock with RS/RW may make a 10% move, or more, allowing you to see increased profit potential. RS/RW is based on the idea of performance, that is the raw percent change of a security over a given time period relative to a benchmark. This benchmark is often the S&P500 (ES/SPX/SPY and their derivatives). I have to stress that this is not beta, which measures the volatility of a stock over a given period (i.e. if $SPY moves $1, $NVDA will often move $1.74). This is a measurement of the market (i.e. $SPY) has moved 1% over the course of a day, $NVDA has moved 8% over the course of the day. This is very often used as a signal of institutional interest as apart from some very unique moments, retail traders cannot and will not provide enough market pressure to move a market outside of a stock's normal trading range, nor will they outperform the sector or market as a whole consistently over time without some big money to make them move. The problem with running strict performance analysis (i.e. % change from period T ago to period T + n at present) is that while it gives us a baseline of how much the stock has moved, it doesn't overall mean much. For instance, if a $100 stock has moved 5% today, but has been experiencing a period of increased volatility and it's Average True Range (ATR) (the amount a stock will move over X number of periods, on average) is $7, performance seems impressive but is actually generally fairly weak to what the stock has been doing recently. Conversely, if we take a second stock, this time worth $20, and it too has moved 5% in one day but has an ATR of only $0.25, that stock has made an exceptional move and we want to be part of that. Here, I have created an indicator called the Stock Relative Strength Power Index. This takes the stock's rate of change (ROC) (the % move it has made over X number of periods), the stock's normalized ATR (the ATR represented as a percentage instead of a raw value), and compares these to one another to get the "Power Rating": a representation of the true strength of a stock over X number of periods. The indicator does two things. First, the raw ROC is divided by the stock's normalized ATR to assess whether the stock is moving outside of its normal range of variation or not. Second, since we are interested in trading only stocks with exceptional RS/RW to the market, I have also applied this same calculation to the S&P500 ($SPY) and the various SPDR sector indexes. These comparisons allow for a rapid and accurate assessment of the true strength of a stock at any given time on any given time frame. To cycle back above to our examples, the $100 stock has a Power Rating of only 0.71 (i.e. it is trading less than its current average), while our $20 stock has a Power Rating of 5. If we then compare these to both the market as a whole and the sector that the stock is a part of, we get a much clearer indication of the true buying or selling pressure imposed on the stock at any given time. Use: The indicator has 3 lines. The blue line is the security of interest, the red line is the market baseline (i.e. the sector ETF $SPY), and the white line is the sector index. I have given an example above on the semiconductor/tech stock $NVDA on a 30min timeframe. You can see that since the start of 2023, $NVDA has generally been strong to the market and its own sector since the blue line is greater than both the red and white lines over many days. This would have provided some nice day trading opportunities, or even some nice short term swing trades. The values themselves are generally meaningless outside of either the 1 or -1 value lines. All that matters is that the current ticker is surpassing both the market and the sector while being > 1.0 for a long trade or less than -1.0 for a short trade. However, I must stress this indicator gives no trade signals on its own, it is purely a confirmation indicator. An example of a trade would be if you had a trade signal given by either an indicator or by price action suggesting to buy some $NVDA for a trade to the upside, the Power Rating indicator would confirm this by showing if $NVDA was actually showing true strength by being both greater than 1 (the cutoff for it surpassing its ATR) and being above both the red and white lines. Further, you can see $NVDA has been stronger than the market when using the comparison function as well, but the has fluxed in and out of strength intraday when using the actual indicator vs. the static performance ratio chart (plotted as line graphs on the chart). I have made it possible to change the colour of the plots and the line levels. The adjustment of the line levels gives the trader the flexibility to change their target breakout level (i.e. only trading stocks that have a Power Rating > 2, for example, meaning they are trading at least 2X their normal trading range). The third security comparison is flexible and can be used to compare to the sector ETF (initial intention) or it can be used to compare to other tickers within the same sector, for example. The trader should select the appropriate ETF for the given security of interest to avoid false confirmation if they want to use an ETF as their third input. The proper sector should be readily available on most online websites and accessible in a matter of seconds meaning that the delay is minimal, at worst. If a trader wishes to add additional functionality, such as a crypto trader using BTCUSD as the benchmark instead of $SPY, I encourage them to copy and paste this script and modify as needed since I have made this open source. This indicator works on all timeframes. The lookback period can be changed, so a day trader who may use a 5min chart (and use a period of 12 to get the hourly Power Rating) will find this equally useful as someone who may be a core trader who wants to look at the performance over the course of years and may use a 60 period on a monthly chart. Happy trading and I hope this helps!
Penunjuk Pine Script®
oleh christoefert
15
Price Distance RatioThis study plots the ratio between current price and the price N days ago. With N input that is configurable, users can find optimal long/short entries when price is in an established trend and price has diverge far from a given local peak or all time high. With many years of stock trading the analysis indicates a connection between the distance of price and subsequent returns. Portfolios of stocks with lower price to local highes ratios generally underperformed portfolios of stocks with higher prices to peaks reached similar N days ago. The highest returns to previous peak are recorded when buying at the biggest dip. For example, the purchase at 20% drawdown could generate 25% when price returns to the peak. The purchase at 50% drawdown could generate bigger, i.e. 100% return, when price returns to the peak. And the purchase at 90% drawdown could generate much bigger, i.e. 900% return, in a case the price returns to the peak. However, buying very far below local peaks on almost all holding periods produces lower CAGR returns because of "timing adjustment". In simple words, typically the drawdown takes less time vs. further recovery. For example: 👉 The largest BTC drawdown in 2013-2015 took 410 days (Peak-to-Valley) . And the recovery of BTC to new highs took 771 days (Valley-to-Peak) after that. 👉 The 3rd longest drawdown in BTC took 363 days (observed from December 17, 2017 to December 15, 2018). And further recovery in BTC to its new high took almost two years - 716 days . 👉The 4th longest drawdown in BTC took 162 days (observed from June 08, 2011 to November 17, 2011). And further recovery in BTC to its new high took more than a year - 469 days . The concept of this study could recognizes at least 4 different modes of action. 👉 In a clearly established upward trend traders should be buying (following the trend) when Ratio is above 100% and reducing the size when Ratio turns below 100%. 👉 Conversely, in a clearly established downward trend traders should be shorted when Ratio is below 100% and covering when the Ratio turns back to 100%. 👉 In a sideways movement traders are advised to wait carefully if the Ratio near 100% for a long time, and take a position the trend is clear. 👉 Chartists can analyze the dynamic of the indicator - both in terms of trends and overall level. For example as it shown at the chart. The understading of the study and rules of "timing adjustments" could genarate the awesome opportunities for stock options traders also, with strategies of selling uncovered call options and vertical call spreads. // Many thanks to @HPotter and @Wheeelman wizards for their continious support and assistance.
Penunjuk Pine Script®
oleh PandorraResearch
CryptoverseThis Indicator dynamically generates and charts Pivot Points, Support and Resistance Lines, Trend Channels and even Rsi Divergences in every market and every time period. While it helps you identify your entry points, stop loss and take positions, it certainly does not include trading signals and trading strategy. Bonus: the indicator contains ema21, ema50, ema100 and ema200 to support the lines created. If you wish, you can change the EMA values in the settings. Recommendation: RSI is included in the indicator codes in order to detect divergences dataally, but it is not displayed on the chart. I recommend adding an additional RSI indicator to keep track of past and current potential divergences. USER MANUAL: ---------------------------------------------- General Settings: Pivot Period: This field determines how many candles before and after a candle should be controlled in order to be able to determine the top and bottom points on the chart. Support and Resistance Lines and Trend Channels formed on the chart are created by calculating the Pivot points formed according to the period determined here. (Default value: 6) Pivot Source: Determines the pivot points to be created according to the value of the relevant candle. (Default and Recommended: closing) ---------------------------------------------- Support And Resistance Settings: Custom Bars Back: This area allows you to specify how many pivot points from the current candle to the previous candle to create support resistance lines on the Chart. The default value is the last 500 candles. *Note: The more old candles are checked, the more support and resistance lines will appear. This may prevent you from making sound determinations on the chart.* Current Bar Decrease: This field works integrated with Custom Bars Back. By subtracting the current candle by the specified number, it provides the formation of lines without including those candles. Default value: It is set to 0 to include current data. Example: If Custom Bars Back: 500 and Current Bar Decrease: 10, Support and Resistance lines are created by considering 500 candles before the last 10 candles without including the last 10 candles on the chart. Show S/R Lines: This field allows you to show or hide the Support and Resistance lines at any time. Auto Simplification: This field is marked by default. It allows the Simplification Steps value to be determined automatically within the code according to the time period and current volatility of the relevant parity. (It is recommended to use the default version.) Simplification Steps: This field allows you to get more understandable lines by simplifying the Support and Resistance lines based on Pivot points. If a simplification is not done, the lines to be formed with only the pivot points will be too many and this creates a dirty and useless appearance on the chart. Each 1 digit you enter as a step combines the lines that are close to each other at a value of 0.01% and creates a common line. Example: If you enter the number 10 as Steps, it will form a single common line from lines close together, starting at 0.01% respectively. It will continue to increase by 0.02%, 0.03%, 0.04% in its next steps. For the number 10, it will complete its loop by combining lines within the last remaining lines that are as close as 0.1% to each other and creating new lines from their midpoints. The deafult value is 14. (Max. simplifies lines with closeness up to 1.4%.) Important Note: If Auto Simplification is on, the entered value has no meaning. The Indicator performs simplification operations automatically. If you want to manage these steps manually, you can turn off Auto Simplification and enter your own value. S/R Lines Color: Allows you to specify the color of the lines. Label Location: Allows you to determine how many candles ahead the information label formed for each line will be positioned. Line Label Descriptions: Line: It is the price value that the line coincides with.* Distance: Shows the percentage distance of the line from the current price. ▲ : Shows the percentage distance from the line above it. ▼ : Shows the percentage distance from the line below it. Strength: Indicates the total number of steps the process has taken during the simplification process. The height of the number indicates the strength of resistance and support in the close price range. C. Width: stands for Channel Width. It shows the percentage value between the highest price and the lowest price on the past candle as many candles specified by Custom Bars Back. S. Steps: stands for Simplification Steps. Indicates the number of simplification steps applied. A value of 150 in the image indicates that a 1.5% simplification range has been applied. ---------------------------------------------- Trend Channels Settings: Show All Trend Lines: Allows you to show and hide trend channels. Hide Old Trend Lines: If you enable it, it will hide channels created in the past except for Current Trend channels. Helper Line Format: Allows the auxiliary line that converts a trendline to a channel to be drawn based on percentage or price. Note: There may be cases where the auxiliary lines do not provide full parallelism when using large time intervals by preferring a percentage. Up Trend Color: Indicates the color of the Up Trend channel. Down Trend Color: Specifies the color of the Downtrend channel. Show Up Trend Overflow, Show Down Trend Overflow: When the price closes above or below the trend channels, it provides awareness with the help of a text on the chart. Colors can be adjusted according to preference. ---------------------------------------------- RSI Divergences Settings: This indicator gives you information about 4 different divergences. You can customize the divergence views with the show and hide options. Bullish Regular, Bullish Hidden, Bearish Regular and Bearish Hidden. Green divergences from the bottom of the graph represent bullish, and red divergences above the graph represent bearish. Important note: Seeing a mismatch label definitely indicates that there is a mismatch between prices and rsi, but a mismatch does not always indicate a change in price. Potential Divergence: The indicator not only shows you past divergences, but also informs you of potential divergences based on the current status of the chart. A potential divergence may not turn into a true one if the price flow continues to increase or decrease in the same direction. But all divergences seen in the past must have been shown as potential divergences beforehand. Rsi Length, Rsi Source: Allows you to change settings for RSI values typically embedded within the indicator. Note: Pivot Source and RSI Source using the same type of candle data ensures that divergences are displayed correctly. ---------------------------------------------- EMA Settings: The indicator allows you to use 4 different EMA data in addition to Support and Resistance lines, Trend Channels and RSI divergences. By default, 21, 50, 100 and 200 are used. You can change the EMA values and colors in the Settings section, or you can use the show hide options in the Style section.
Penunjuk Pine Script®
oleh HasanGocmen
2
PSAR BBPT ZLSMA BTC 1minLong entry: PSAR gives buy signal BBPT prints green histogram ZLSMA is below the price ZLSMA has uptrend SL is smaller than the max SL Optional Sessions and EMA filters Short entry PSAR gives sell signal BBPT prints red histogram ZLSMA is above the price ZLSMA has downtrend SL is smaller than the max SL Optional Sessions and EMA filters SL: Placed below ZLSMA + offset on long Placed above ZLSMA + offset on short TP1: 1x the SL by default Takes no profit by default, 50% is also a good setting TP2: 2x the SL by default Take out all remaining position size. If price reaches TP1, the SL is set to the entry price.
Strategi Pine Script®
oleh Rolan_Kruger
TOTAL:(RSI+TSI)TOTAL:(RSI+TSI) This indicator collects instant data of RSI and TSI oscillators. RSI moves between (0) and (100) values as a moving line, while TSI moves between (-100) and (+100) values as two moving lines. The top value of the sum of these values is graphically; It takes the total value (+300) from RSI (+100), TSI (+100) and (+100). The lowest value of the sum of these values is graphically; It takes the value (-200) from the RSI (0), (-100) and (-100) from the TSI. In case this indicator approaches (+300) graphically; It can be seen that price candlesticks mostly move upwards. This may not always give accurate results. Past incompatibilities can affect this situation. In case this indicator approaches (-200) graphically; It can be seen that price candlesticks mostly move downwards. This may not always give accurate results. Past incompatibilities can affect this situation. The graphical movements and numerical values created by this indicator do not give precise results for price candles.
Penunjuk Pine Script®
oleh gokhanpirnal
DR/IDR of Omega by TRSTNThis is an EXPERIMENTAL Script by @TRSTNGLRD derived from the coding of @IAmMas7er's "DR/IDR" Indicator that adds a total of 11 additional DR / IDR Ranges on both lower and higher timeframes. This script is no-longer being worked on, so I have made it public. Background: This Script utilizes the Fibonacci-Doubling Sequence between the range of 18:30pm and 16:55pm NY-Time. Each Cycle is grouped into the following: Omega/2, Omega/4, Omega/8, and Omega/16 The Mas7er's three original sessions are: Omega/4v1, Omega/4v2, and Omega/8v1 These three Sessions above take rule over all others. If you are looking to back-test this version of the script, please use the Experimental ranges as confirmation for the three above. Important Notes: - Please only select Sessions with their respected groups (All of Omega/4, All of Omega/16, etc...) rather than selecting all of them at once. If you select all of them at once, the ranges will not be correct and cut each other off. The only exceptions to this rule are the Mas7er's original ranges above. - If you wish to have multiple groups of Ranges together, please add a second indicator to your chart. - Omega/16v1 and Omega/16v6 are known to have a high-probability of a Judas Swing (takes out both sides of the range) - Be Cautious! - Omega/2v1 is a very large DR / IDR range. I am working on shrinking it in size, but have more experimenting to do with different ranges. - I do not use the experimental ranges with the IDR , only the DR . I have not been able to define probabilities fully yet, but the levels are respected nonetheless. This script is not supposed to work EXACTLY like the Mas7er's, rather, generally instead. Please comment and leave your opinion below about which ranges work the best and how you may utilize them. Thank you!
Penunjuk Pine Script®
oleh TRSTNGLRD
6