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[Pandora] Vast Volatility Treasure TroveINTRODUCTION: Volatility enthusiasts, prepare for VICTORY on this day of July 4th, 2024! This is my "Vast Volatility Treasure Trove," intended mostly for educational purposes, yet these functions will also exhibit versatility when combined with other algorithms to garner statistical excellence. Once again, I am now ripping the lid off of Pandora's box... of volatility. Inside this script is a 'vast' collection of volatility estimators, reflecting the indicators name. Whether you are a seasoned trader destined to navigate financial strife or an eagerly curious learner, this script offers a comprehensive toolkit for a broad spectrum of volatility analysis. Enjoy your journey through the realm of market volatility with this code! WHAT IS MARKET VOLATILITY?: Market volatility refers to various fluctuations in the value of a financial market or asset over a period of time, often characterized by occasional rapid and significant deviations in price. During periods of greater market volatility, evolving conditions of prices can move rapidly in either direction, creating uncertainty for investors with results of sharp declines as well as rapid gains. However, market volatility is a typical aspect expected in financial markets that can also present opportunities for informed decision-making and potential benefits from the price flux. SCRIPT INTENTION: Volatility is assuredly omnipresent, waxing and waning in magnitude, and some readers have every intention of studying and/or measuring it. This script serves as an all-in-one armada of volatility estimators for TradingView members. I set out to provide a diverse set of tools to analyze and interpret market volatility, offering volatile insights, and aid with the development of robust trading indicators and strategies. In today's fast-paced financial markets, understanding and quantifying volatility is informative for both seasoned traders and novice investors. This script is designed to empower users by equipping them with a comprehensive suite of volatility estimators. Each function within this script has been meticulously crafted to address various aspects of volatility, from traditional methods like Garman-Klass and Parkinson to more advanced techniques like Yang-Zhang and my custom experimental algorithms. Ultimately, this script is more than just a collection of functions. It is a gateway to a deeper understanding of market volatility and a valuable resource for anyone committed to mastering the complexities of financial markets. SCRIPT CONTENTS: This script includes a variety of functions designed to measure and analyze market volatility. Where applicable, an input checkbox option provides an unbiased/biased estimate. Below is a brief description of each function in the original order they appear as code upon first publish: Parkinson Volatility - Estimates volatility emphasizing the high and low range movements. Alternate Parkinson Volatility - Simpler version of the original Parkinson Volatility that I realized. Garman-Klass Volatility - Estimates volatility based on high, low, open, and close prices using a formula that adjusts for biases in price dynamics. Rogers-Satchell-Yoon Volatility #1 - Estimates volatility based on logarithmic differences between high, low, open, and close values. Rogers-Satchell-Yoon Volatility #2 - Similar estimate to Rogers-Satchell with the same result via an alternate formulation of volatility. Yang-Zhang Volatility - An advanced volatility estimate combining both strengths of the Garman-Klass and Rogers-Satchell estimators, with weights determined by an alpha parameter. Yang-Zhang (Modified) Volatility - My experimental modification slightly different from the Yang-Zhang formula with improved computational efficiency. Selectable Volatility - Basic customizable volatility calculation based on the logarithmic difference between selected numerator and denominator prices (e.g., open, high, low, close). Close-to-Close Volatility - Estimates volatility using the logarithmic difference between consecutive closing prices. Specifically applicable to data sources without open, high, and low prices. Open-to-Close Volatility - (Overnight Volatility): Estimates volatility based on the logarithmic difference between the opening price and the last closing price emphasizing overnight gaps. Hilo Volatility - Estimates volatility using a method similar to Parkinson's method, which considers the logarithm of the high and low prices. Vantage Volatility - My experimental custom 'vantage' method to estimate volatility similar to Yang-Zhang, which incorporates various factors (Alpha, Beta, Gamma) to generate a weighted logarithmic calculation. This may be a volatility advantage or disadvantage, hence it's name. Schwert Volatility - Estimates volatility based on arithmetic returns. Historical Volatility - Estimates volatility considering logarithmic returns. Annualized Historical Volatility - Estimates annualized volatility using logarithmic returns, adjusted for the number of trading days in a year. If I omitted any other known varieties, detailed requests for future consideration can be made below for their inclusion into this script within future versions... BONUS ALGORITHMS: This script also includes several experimental and bonus functions that push the boundaries of volatility analysis as I understand it. These functions are designed to provide additional insights and also are my ideal notions for traders looking to explore other methods of volatility measurement. VOLATILITY APPLICATIONS: Volatility estimators serve a common role across various facets of trading and financial analysis, offering insights into market behavior. These tools are already in instrumental with enhancing risk management practices by providing a deeper understanding of market dynamics and the inherent uncertainty in asset prices. With volatility estimators, traders can effectively quantifying market risk and adjust their strategies accordingly, optimizing portfolio performance and mitigating potential losses. Additionally, volatility estimations may serve as indication for detecting overbought or oversold market conditions, offering probabilistic insights that could inform strategic decisions at turning points. This script distinctly offers a variety of volatility estimators to navigate intricate financial terrains with informed judgment to address challenges of strategic planning. CODE REUSE: You don't have to ask for my permission to use/reuse these functions in your published scripts, simply because I have better things to do than answer requests for the reuse of these functions. Notice: Unfortunately, I will not provide any integration support into member's projects at all. I have my own projects that require way too much of my day already.
مؤشر Pine Script®
من ‎ImmortalFreedom‎
13
TradesAI - Elite (Premium)This is an all-inclusive, premium indicator that focuses mainly on price action analysis, a form of looking at raw price data and market structure to analyze and capture areas of interest where price could react. This indicator is a perfect trading companion that saves you a lot of time in trading price action. Some of the popular methods that use price action analysis are "Smart Money Concepts (SMC)", "Inner Circle Trader (ICT)", and "Institutional Trading". 🔶 POWERFUL TOOLS The indicator combines three main tools as a trading suite: Trendlines Market Structure Breakouts (MSB) Order Blocks (OBs) and Reversal Order Blocks (ROBs) These 3 main tools are interconnected together. Below we go over each, and then explain how and why they are brought in together. Please also note that the indicator's settings have tooltips next to most of them, with more detailed information. 🔶 TRENDLINES This indicator automatically draws the most relevant Trendlines from pivot high/pivot low (based on the defined settings) as origins, while keeping track of candle closes across these Trendlines to adjust or invalidate accordingly. The indicator will draw all possible Trendlines up to the maximum allowed by TradingView's PineScript. It uses a bullish pivot high candle to draw downtrends, and a bearish pivot low candle to draw uptrends. The algorithm will draw the most suitable active Trendlines from those origin points. The indicator takes the origin point as the first point of the Trendline, then starts looking for the immediate next same-type candle (bullish to bullish or bearish to bearish), to draw the Trendline between the origin candle and this newer candle. An uptrend is a ray connecting two bearish candles, as long as the second candle has a Low higher than the low of the origin (first) candle. A downtrend is a ray connecting two bullish candles, as long as the second candle has a high lower than the high of the origin (first) candle. Upon drawing, the indicator then starts monitoring and adjusting this Trendline, by keeping the origin always the same but changing the second point. The goal is to keep reducing the slope of the Trendline till it is at 0 degrees (horizontal line). That then makes the Trendline "final". Note that you have the option to keep all Trendlines or just show the final, in the settings. So, the algorithm has three states for the Trendlines: Initial: not tested, meaning price hasn't yet broken through it and closed a candle beyond it, to cause a re-adjustment of this Trendline. Broken: a candle hard closed (opened and closed) across it but still, the direction of the trend is maintained with a new Trendline from the same origin – could be replaced (or kept on the chart as a "backside", which is what we call a broken Trendline to be tested from the opposite side) with a new Trendline from the same origin, to the newest candle that caused the break to happen, as then it becomes the new second point of that Trendline. Final: a candle hard closed (opened and closed) across it and can't draw a new Trendline from the same origin maintaining the direction of the trend (so an uptrend becomes a downtrend or a downtrend becomes an uptrend at this point, which is not allowed). This marks the end of the Trendline adjustment for that origin. To summarize the Trendlines algorithm, imagine starting from a candle and drawing the Trendline, then keep re-adjusting it to make its slope less and less, till it becomes a horizontal line. That's the final state. Here is a step-by-step scenario to demonstrate the algorithm: Notice how first an Uptrend (green ray) is drawn between point A origin pivot (picked by our smart algorithm) and point B, both marked by green arrows: Uptrend then turned into backside (where it flips from diagonal support to resistance where liquidity potentially resides): Then a new uptrend is drawn from the same point A origin pivot to a new point B matching the filters in settings. Finally, it turns also into a backside and is considered final because no more uptrends could be drawn from the same point A origin point. Unlike traditional Trendline tools, this indicator takes into account numerous rules for each candlestick to determine valid support and resistance levels, which act as liquidity zones. Unlike conventional Trendline tools, this indicator allows the user to define the pivot point left and right length to capture the proper ones as origins, then automatically recognizes and extends lines from them as liquidity zones where a reaction is expected. Moreover, the indicator monitors those Trendlines in real-time to switch them from buying to selling zones, and vice-versa, as the price structure changes. Features Log vs. Linear scale switch to show different Trendlines accordingly. When updating the Trendlines, or deciding whether Touches/Hard Closes are met, it makes a difference. Ability to show all forms of Trendlines, final Trendlines or just backside Trendlines. Why is it used? For experienced traders, it offers the advantage of time efficiency, while new traders can bypass the steep learning curve of drawing Trendlines manually, which could practically be drawn between any two candlesticks on the chart (many variations). 🔶 MARKET STRUCTURE BREAKOUT (MSB) The Market Structure Breakouts (MSB) tool is a trading tool that detects specific patterns on trading charts and provides ‘take profit’ regions based on the extended direction of the identified pattern. A breakout is a potential trading opportunity that presents itself when an asset's price moves away from a zone of accumulation (i.e. above a resistance level or below a support level) on increasing volume. The most famous form of market structure breakout is double/triple tops/bottoms, or what is referred to as W or M breakouts. See this example below of how our MSB smart algorithm picked the local bottom of INDEX:BTCUSD Here is a step-by-step scenario to demonstrate the algorithm: First, the algorithm picks the pivot points according to our Machine Learning (ML) model, which uses Average True Range (ATR) and Moving Averages of various types to decide. It will then signal a Market Structure Breakout (MSB): You may either short (sell) this MSB towards the targets (dotted green lines) and/or buy (long) at the targets (dotted green lines). Usually, these targets provide scalp moves, according to our model, but they may also act as strong reversal points on the chart. Unlike standard indicators, the MSB tool identifies patterns that may not appear in every time frame due to specific conditions that need to be met, including Average True Range (ATR) and Moving Averages at the time of creation. Once these patterns are identified, the tool gives ‘take profit’ regions in the direction of the trading pattern and even allows for trading in the opposite direction (contrarian/counter-trend scalps) once those regions are reached. A confirmed breakout has the potential to drive the price to these specific targets, calculated based on our Machine Learning (ML) model. The Targets are the measured moves placed from the breakout point. Features Log vs. Linear scale switch to show different MSBs accordingly based on the ratios. Detects trading patterns with specific conditions. Ability to specify how sensitive the pivot points are for capturing market structure breakouts. Provides take profit regions in the extended direction of the pattern. Allows for versatile trading styles by permitting trades in the opposite direction (contrarian or counter-trend) once the take profit region is reached. Highlights 2 levels of interest for potential trade initiation (or as targets of the MSB move). 🔶 ORDER BLOCK (OB) and REVERSAL ORDER BLOCK (ROB) Before diving deeper into OBs and ROBs, you may consider the following chart for a general understanding of price ladders, and how they break. This is a bearish price ladder leaving Lower Lows and Lower Highs after an initial Low and High (L->H->LL->LH). Bullish ladders are the opposite (H->L->HH->HL). In this bearish ladder case, notice the numbers representing the highs made (being lower). While this is a clean structure, markets don't always create such clean ladders, but you may switch to a higher timeframe to see it in a clearer form (usually, you will be able to spot it there). In SMC or ICT concepts, the "Break Of Structure (BOS)" is pretty much creating a new lower low (LL) for the bearish ladder (and the creation of a higher high (HH) for the bullish ladder). By doing so, markets are grabbing liquidity below these levels and could either continue the ladder or stop/flip it. This gives you the context of how the ladder prints. Price usually ends the ladder with a "Change of Character (CHoCH)", which represents a BOS (to grab liquidity) followed by an aggressive move in the opposite direction, which could lead the market to close the gaps and balance out. It is considered a good practice to then target liquidity in the opposite direction when a CHoCH happens, meaning for a bearish ladder you may target the pivots marked by 3, 2 and 1 at the top (start of the ladder). Now we move to Order Blocks (OBs) and Reversal Order Blocks (ROBs). Think of them as sniper zones or micro ladders inside the bigger ladder/structure. Order Blocks are usually used as zones of support and resistance on a trading chart where liquidity is present, or what some traders call "potential institutional interest zones". Order Blocks can be observed at the beginning of these strong moves of BOS or the CHoCH, leaving behind a zone (one or more candles) to be revisited later to balance the market. Therefore, these are interesting levels to place Limit/Market orders (sell the peaks or buy the valleys) instead of doing so at the swing highs or swing lows of the ladder (where BOS or CHoCH happened). The idea here is that the price could go deep into the ladder's step (peak or valley), and by doing so, it usually goes to these zones. A bullish Order Block (Valley-OB) is the last bearish candle of a downtrend before a sequence of bullish candles (thus forming a "Valley"). A bearish Order Block (Peak-OB) is the last bullish candle of an uptrend before a sequence of bearish candles (thus forming a "Peak"). Our indicator captures the full range zones of the OB meaning not only the last candle but the sequence of same-type candles immediately next to it, which creates a zone, thus the name "OB/ROB Zone". Not only does the tool mark those levels on the chart, but it also has a smart tracking algorithm to remove the appropriate levels dynamically. It will monitor, candle by candle, what is happening to all the OBs/ROBs, and update them according to how they are being tested/visited (eg. weak testing being a touch, and strong testing being a touch of the same colour candle). Bullish Valley-OB: Bearish Peak-OB: The indicator follows our concept of "Zone Activation" to determine whether to mark zones with dashed or solid lines. If we take a bearish Peak-OB as an example, notice how it first gets drawn with a dashed red line (as the algorithm monitors how far the price moved away from the zone): As price moves away (distance based on our Machin Learning (ML) model), it turns into solid lines: Some people prefer to enter market orders or limit (pending) orders close to the zone, while others wait for it to hit. You may wait for these zones to turn into solid lines (meaning that the price made a decent move away from it before revisiting it). It depends on your trading strategy. When Order Block (OB) zones break instead of holding the ladder, they turn into what we call Reversal Order Blocks (ROB); our algorithm of flipping these zones where price could react from the other side of the OB. Our algorithm monitor and highlight the most suitable ones to trade, based on +30 conditions and variables by our Machine Learning (ML) models. Examples of ROBs in the SMC or ICT trading community are a "Breaker Block", a "Mitigation Block" or a "Unicorn Setup". However, our algorithm filters the zones based on many factors such as ratios of price movement before, inside and after these zones, along with many other factors. The algorithm monitors the ratios of how price moved into and away from the OB/ROB, as well as the type of move happening, to then filter the ones that are considered of high probability to break/not do a reaction. A bullish Valley-OB (green) turns into a bearish Valley-ROB (neon red) where you may short (sell), while a bearish Peak-OB (red) turns into a bullish Peak-ROB (neon green) where you may long (buy). Example of a bullish Valley-OB that turned into a bearish Valley-ROB: Features Log vs. Linear scale switch to show OBs/ROBs accordingly based on the ratios and the price action around these zones (before and after creation). Uses our Machine Learning (ML) model to determine relevant Order Blocks (OBs) to show or hide based on price action. Considers distribution and accumulation candles to find relevant Order Blocks. Various types of triggers to mark those Order Blocks and their zones: breakout, close, hard close (open and close) or full close (low, high, open and close). Monitors the 1:1 expansion of price from key areas of interest, which would change the importance of the zones through our concept of “Zone Activation”. Allows for customization in the settings to display different types of Order Blocks (e.g., tested or untested). Marking and invalidating levels based on many variables, including single or multiple candle zones, touching/closing beyond specific levels, weak/strong testing criteria, price tolerance % (near a level), and many more. Provides color-coded visual representation for easier interpretation. Why is it used? Order Blocks (OB) and Reversal Order Blocks (ROB) represent the building blocks of price ladders, in conjunction with Swing Highs and Swing Lows. By identifying where liquidity is potentially present, they become common targets for big market players. Additionally, they provide clear invalidation points based on various types of candle closes, such as hard closes or simply a candle close. One strategy that could be used is to open positions at these OB or ROB Levels as long as the chart maintains the trend (ladder), for a potentially higher win rate (or against it for a quick scalp). Be mindful of the breaking of a ladder or the building of a new one. A ladder breaks with a hard close (open and close) of a candle across the closest two levels; a ladder builds by not breaking back down across the levels it has tested. By definition, strong ladders will have a few untested levels and come back to wick them but still retain the structure of the laddering direction (trending with Lower Lows + Lower Highs or Higher Lows + Higher Highs). 🔶 COMBINING ALL TOOLS In summary, Trendlines could be great tools to give you a general context of whether the price is laddering up or down. Once you spot the ladder, your goal is to either trade in its direction (not to go against the trend) or to counter-trend trade (contrarian). To do so, you could use the MSB tool to spot these BOS/CHoCH. And to give you more precise entries, you may rely on the OB/ROB zones which usually mesh over the ladder, to provide a sniper entry! 🔶 RISK DISCLAIMER Trading is risky, and most day traders lose money. The risk of loss in trading can be substantial. Decisions to buy, sell, hold or trade in securities, commodities and other investments involve risk and are best made based on the advice of qualified financial professionals. Past performance does not guarantee future results. All content is to be considered hypothetical, selected after the fact, in order to demonstrate our product and should not be construed as financial advice. You should therefore carefully consider whether such trading is suitable for you in light of your financial condition.
مؤشر Pine Script®
من ‎Trades-AI‎
54
Machine Learning : Dominant Cycle Elastic Volume KNNAbout the Script Dominant Cycle Elastic Volume KNN , is a non-parametric algorithm, which means that, initially it makes no assumptions about the underlying distribution of the time-series price as well as volume. This approach gives it flexibility so that it can be used on a wide variety of securities at variety of timeframes.(even on lower timeframes such as seconds) The main purpose of this indicator is to predict the trend of the underlying, by converging price, volume and dominant cycle as dimensions and generate signals of action. Key terms : Dominant cycle is a time cycle that has a greater influence on the overall behaviour of a system than other cycles. The system uses Ehlers method to calculate Dominant Cycle/ Period. Dominant cycle is used to determine the influencing period for the underlying. Once the dominant cycle/ period is identified, it is treated as a dynamic length for considering further calculations Elastic Volume MA is a volume based moving average which is generally used to converge the volume with price, the dominant period is used here as the length parameter KNN K-Nearest Neighbour is one of the simplest Machine Learning algorithms based on Supervised Learning technique. K-NN algorithm assumes the similarity between the new case/data and available cases and put the new case into the category that is most similar to the available categories. K-NN algorithm stores all the available data and classifies a new data point based on the similarity. This means when new data appears then it can be easily classified into a well suite category by using K- NN algorithm. K-NN algorithm can be used for Regression as well as for Classification but mostly it is used for the Classification problems. So, K-NN is used here to classify the trend of the Dominant Cycle Elastic Volume, and Generate Signals on top of it How to Use the Indicator ? The Buy Signal Candle The Sell Signal Candle The Buy Setup The Sell Setup Stop and Reverse Structure What Timeframes and Symbols can this indicator be used on ? The above indicator can be used on any liquid security which has volume information intact with ticker and it can be used on any timeframe, but the best timeframes are The indicator can also be used as a trend confirmatory indicators on lower time frames, like 30second The Script has provision for alerts Two alerts are there : Alert 1= "LONG CONDITION : DCEV-ML" Alert 2= "SHORT CONDITION : DCEV-ML" How to request for access ? Simply private message me !
مؤشر Pine Script®
من ‎Ankit_1618‎
38
Endpointed SSA of Price [Loxx]The Endpointed SSA of Price: A Comprehensive Tool for Market Analysis and Decision-Making The financial markets present sophisticated challenges for traders and investors as they navigate the complexities of market behavior. To effectively interpret and capitalize on these complexities, it is crucial to employ powerful analytical tools that can reveal hidden patterns and trends. One such tool is the Endpointed SSA of Price, which combines the strengths of Caterpillar Singular Spectrum Analysis, a sophisticated time series decomposition method, with insights from the fields of economics, artificial intelligence, and machine learning. The Endpointed SSA of Price has its roots in the interdisciplinary fusion of mathematical techniques, economic understanding, and advancements in artificial intelligence. This unique combination allows for a versatile and reliable tool that can aid traders and investors in making informed decisions based on comprehensive market analysis. The Endpointed SSA of Price is not only valuable for experienced traders but also serves as a useful resource for those new to the financial markets. By providing a deeper understanding of market forces, this innovative indicator equips users with the knowledge and confidence to better assess risks and opportunities in their financial pursuits. █ Exploring Caterpillar SSA: Applications in AI, Machine Learning, and Finance Caterpillar SSA (Singular Spectrum Analysis) is a non-parametric method for time series analysis and signal processing. It is based on a combination of principles from classical time series analysis, multivariate statistics, and the theory of random processes. The method was initially developed in the early 1990s by a group of Russian mathematicians, including Golyandina, Nekrutkin, and Zhigljavsky. Background Information: SSA is an advanced technique for decomposing time series data into a sum of interpretable components, such as trend, seasonality, and noise. This decomposition allows for a better understanding of the underlying structure of the data and facilitates forecasting, smoothing, and anomaly detection. Caterpillar SSA is a particular implementation of SSA that has proven to be computationally efficient and effective for handling large datasets. Uses in AI and Machine Learning: In recent years, Caterpillar SSA has found applications in various fields of artificial intelligence (AI) and machine learning. Some of these applications include: 1. Feature extraction: Caterpillar SSA can be used to extract meaningful features from time series data, which can then serve as inputs for machine learning models. These features can help improve the performance of various models, such as regression, classification, and clustering algorithms. 2. Dimensionality reduction: Caterpillar SSA can be employed as a dimensionality reduction technique, similar to Principal Component Analysis (PCA). It helps identify the most significant components of a high-dimensional dataset, reducing the computational complexity and mitigating the "curse of dimensionality" in machine learning tasks. 3. Anomaly detection: The decomposition of a time series into interpretable components through Caterpillar SSA can help in identifying unusual patterns or outliers in the data. Machine learning models trained on these decomposed components can detect anomalies more effectively, as the noise component is separated from the signal. 4. Forecasting: Caterpillar SSA has been used in combination with machine learning techniques, such as neural networks, to improve forecasting accuracy. By decomposing a time series into its underlying components, machine learning models can better capture the trends and seasonality in the data, resulting in more accurate predictions. Application in Financial Markets and Economics: Caterpillar SSA has been employed in various domains within financial markets and economics. Some notable applications include: 1. Stock price analysis: Caterpillar SSA can be used to analyze and forecast stock prices by decomposing them into trend, seasonal, and noise components. This decomposition can help traders and investors better understand market dynamics, detect potential turning points, and make more informed decisions. 2. Economic indicators: Caterpillar SSA has been used to analyze and forecast economic indicators, such as GDP, inflation, and unemployment rates. By decomposing these time series, researchers can better understand the underlying factors driving economic fluctuations and develop more accurate forecasting models. 3. Portfolio optimization: By applying Caterpillar SSA to financial time series data, portfolio managers can better understand the relationships between different assets and make more informed decisions regarding asset allocation and risk management. Application in the Indicator: In the given indicator, Caterpillar SSA is applied to a financial time series (price data) to smooth the series and detect significant trends or turning points. The method is used to decompose the price data into a set number of components, which are then combined to generate a smoothed signal. This signal can help traders and investors identify potential entry and exit points for their trades. The indicator applies the Caterpillar SSA method by first constructing the trajectory matrix using the price data, then computing the singular value decomposition (SVD) of the matrix, and finally reconstructing the time series using a selected number of components. The reconstructed series serves as a smoothed version of the original price data, highlighting significant trends and turning points. The indicator can be customized by adjusting the lag, number of computations, and number of components used in the reconstruction process. By fine-tuning these parameters, traders and investors can optimize the indicator to better match their specific trading style and risk tolerance. Caterpillar SSA is versatile and can be applied to various types of financial instruments, such as stocks, bonds, commodities, and currencies. It can also be combined with other technical analysis tools or indicators to create a comprehensive trading system. For example, a trader might use Caterpillar SSA to identify the primary trend in a market and then employ additional indicators, such as moving averages or RSI, to confirm the trend and generate trading signals. In summary, Caterpillar SSA is a powerful time series analysis technique that has found applications in AI and machine learning, as well as financial markets and economics. By decomposing a time series into interpretable components, Caterpillar SSA enables better understanding of the underlying structure of the data, facilitating forecasting, smoothing, and anomaly detection. In the context of financial trading, the technique is used to analyze price data, detect significant trends or turning points, and inform trading decisions. █ Input Parameters This indicator takes several inputs that affect its signal output. These inputs can be classified into three categories: Basic Settings, UI Options, and Computation Parameters. Source: This input represents the source of price data, which is typically the closing price of an asset. The user can select other price data, such as opening price, high price, or low price. The selected price data is then utilized in the Caterpillar SSA calculation process. Lag: The lag input determines the window size used for the time series decomposition. A higher lag value implies that the SSA algorithm will consider a longer range of historical data when extracting the underlying trend and components. This parameter is crucial, as it directly impacts the resulting smoothed series and the quality of extracted components. Number of Computations: This input, denoted as 'ncomp,' specifies the number of eigencomponents to be considered in the reconstruction of the time series. A smaller value results in a smoother output signal, while a higher value retains more details in the series, potentially capturing short-term fluctuations. SSA Period Normalization: This input is used to normalize the SSA period, which adjusts the significance of each eigencomponent to the overall signal. It helps in making the algorithm adaptive to different timeframes and market conditions. Number of Bars: This input specifies the number of bars to be processed by the algorithm. It controls the range of data used for calculations and directly affects the computation time and the output signal. Number of Bars to Render: This input sets the number of bars to be plotted on the chart. A higher value slows down the computation but provides a more comprehensive view of the indicator's performance over a longer period. This value controls how far back the indicator is rendered. Color bars: This boolean input determines whether the bars should be colored according to the signal's direction. If set to true, the bars are colored using the defined colors, which visually indicate the trend direction. Show signals: This boolean input controls the display of buy and sell signals on the chart. If set to true, the indicator plots shapes (triangles) to represent long and short trade signals. Static Computation Parameters: The indicator also includes several internal parameters that affect the Caterpillar SSA algorithm, such as Maxncomp, MaxLag, and MaxArrayLength. These parameters set the maximum allowed values for the number of computations, the lag, and the array length, ensuring that the calculations remain within reasonable limits and do not consume excessive computational resources. █ A Note on Endpionted, Non-repainting Indicators An endpointed indicator is one that does not recalculate or repaint its past values based on new incoming data. In other words, the indicator's previous signals remain the same even as new price data is added. This is an important feature because it ensures that the signals generated by the indicator are reliable and accurate, even after the fact. When an indicator is non-repainting or endpointed, it means that the trader can have confidence in the signals being generated, knowing that they will not change as new data comes in. This allows traders to make informed decisions based on historical signals, without the fear of the signals being invalidated in the future. In the case of the Endpointed SSA of Price, this non-repainting property is particularly valuable because it allows traders to identify trend changes and reversals with a high degree of accuracy, which can be used to inform trading decisions. This can be especially important in volatile markets where quick decisions need to be made.
مؤشر Pine Script®
من ‎loxx‎
4
Bogdan Ciocoiu - LitigatorDescription The Litigator is an indicator that encapsulates the value delivered by the Relative Strength Index, Ultimate Oscillator, Stochastic and Money Flow Index algorithms to produce signals enabling users to enter positions in ideal market conditions. The Litigator integrates the value delivered by the above four algorithms into one script. This indicator is handy when trading continuation/reversal divergence strategies in conjunction with price action. Uniqueness The Litigator's uniqueness stands from integrating the above algorithms into the same visual area and leveraging preconfigured parameters suitable for short term scalping (1-5 minutes). In addition, the Litigator allows configuring the above four algorithms in such a way to coordinate signals by colour-coding or shape thickness to aid the user with identifying any emerging patterns quicker. Furthermore, Moonshot's uniqueness is also reflected in the way it has standardised the outputs of each algorithm to look and feel the same, and in doing so, enabling users to plug them in/out as needed. This also includes ensuring the ratios of the shapes are similar (applicable to the same scale). Open-source The indicator uses the following open-source scripts/algorithms: www.tradingview.com www.tradingview.com www.tradingview.com www.tradingview.com
مؤشر Pine Script®
من ‎BogdanCiocoiu‎
1
Bogdan Ciocoiu - MoonshotDescription Moonshot is an indicator that encapsulates the value delivered by the TSI, MACD, Awesome Oscillator and CCI algorithms to produce signals to enable users to enter positions in ideal market conditions. Moonshot integrates the value delivered by the above four algorithms into one script. This indicator is particularly useful when trading continuation/reversal divergence strategies. Uniqueness The Moonshot's uniqueness stands from integrating the above algorithms into the same visual area and leveraging preconfigured parameters suitable for 1-3 minute scalping techniques. In addition, Moonshot allows swapping or furthermore configuring the above four algorithms in such a way to align signals by colour-coding or shape thickness to aid the users with identifying any emerging patterns quicker. Furthermore, Moonshot's uniqueness is also reflected in the way it has standardised the outputs of each algorithm to look and feel the same (including the scale at which the shapes are shown) and, in doing so, enables users to plug them in/out as needed. Open-source The indicator leverages the following open-source scripts/algorithms: www.tradingview.com www.tradingview.com www.tradingview.com www.tradingview.com
مؤشر Pine Script®
من ‎BogdanCiocoiu‎
The Chartless TraderThe Chartless Trader The chartless trader is a trade management system designed to remove the randomness from the market. It is loosely based on the martingales betting system, but takes advantage of position sizing, minimum profit targets, dollar cost averaging, and trailing take profit. The chart can be traded with or without a signal. There is a built in signal based on SB Master Chart's Buy the Dip algorithm. The configurable settings include: Account Value Starting Account Value - This is the value of the account when you start using this system. Current Cash - This is the amount of cash you have available to trade. This setting needs to be updated each time a trade is made. TP/TTP Algo Settings Take Profit % - This setting is otherwise known as minimum profit target. This algo will not advise you to sell or increase your trailing stop until this minimum profit target is met. Trailing Stop % - This is the trailing stop. The default setting is 75%. As a basic example, if the stock is up 10%, the trailing stop would be set to 7.5% (10% * 75%). The algo may override and advise an alternative trailing stop should an overbought condition be detected. DCA/BTD Algo DCA/BTD Algo Time Frame - Default is 120 (2hrs). This algo looks for oversold periods on the 2h chart by default. DCA % - The default for this setting is 5%. This is a trigger for the BTD Algo. The BTD algo will start looking for trades when the stock is 5% below your cost basis. This is to help you average down making it easier to turn a profit when the stock starts making gains. Position # The Chartless Trader supports a maximum of 20 symbols. This is a limitation of the security() function as a maximum of 40 calls are allowed and the script calls the security() function twice per symbol. S# QTY - The number of open positions of the symbol. This has to be manually updated by the user after each buy/sell of the stock. S# CB - This is the cost basis of the stock. Your broker should give you this after each buy/sell and it has to be updated here on the chart after each buy/sell. S# TTP - The script will advise you to increase your Trailing Take Profit in your broker when its necessary. This should be updated manually after you update your order in your broker. This should be configured manually in your broker as a Stop Order. Now that I have covered the configurable options, its important to understand the basis of this system. The martingales betting system is a system that seeks to double its position size each time you enter a losing trade. Eventually when you make a winning trade, it will be enough to cover the previous losses and net you one winning position. Bet 1, lose 1, down 1. Bet 2, lose 2, down 3. Bet 4, lose 4, down 7. Bet 8, lost 8, down 15. Bet 16, win 16, up 1. So the theory goes, if you have deep enough pockets, its a 100% win rate. Such a system is flawed and proven to cause an account to blow up given enough time. You can search Google/YouTube for others that have back tested the martingales system with stocks. I advise that "The Chartless Trading" system be traded with a similar system, but instead of doubling your position, you simply increase your position size by 1%. Bet 1%, lose 1%, down 1% Bet 1%, lose 1%, down 2% Bet 1%, lose 1%, down 3%. In such a manner, your risk of ruin is significantly reduced. Lets say you lose 10 times in a row betting on a stock. You now have 10% of your account value in this particular stock. Because you only invested at times where you were more than 5% down and when an oversold position occurred, because of dollar cost averaging and buying during oversold periods, you may only be down 2-3% on your invested value. Eventually when the stock turns positive, you will have met your minimum profit target and the script will alert you to set a trailing stop. You log into your broker, set a stop loss and wait for it to either trigger or inform you to increase it again. Once the trailing stop is triggered, you deleverage the position by closing it and starting a single new position in either the same stock or a different one and the cycle repeats. The key is to follow the stock down, follow it back up, and not back down. We repeat this cycle with many positions in many stocks to minimize risk and compound our balance sheet. This is " The Chartless Trader ". 1920x1080p Monitor Required if using all 20 symbols. The more symbols loaded, the longer the initial processing to load the table. Please be patient.
مؤشر Pine Script®
من ‎StuBuzzzini‎
2
Directional AnalyzerThis script attempts to equip users with the necessary information about the direction of an instrument, and essentially it is a synergy of 3 algorithms. The first algorithm (plotted as dots at level 0) studies the balance of delta volatility that constitutes the current bar and answers if bulls or bears are in control at that exact bar time The second algorithm (plotted as an area) studies the development of delta volatility over the defined period by means of a polynomial regression. Effectively, it provides an overall picture of the trend strength. The third algorithm (plotted as a line with arrow labels) utilizes simple elements of neural network in conjunction with some custom filters to predict the focal point that a trend will reverse its direction. This is predictive in nature, hence always adopt this with caution. While the labels display the predicted direction, the colors of the line also reflect the state of the current bar as well, adding to the confirmation of the first algorithm. May you be on the right side of the trade.
مؤشر Pine Script®
من ‎QallianceTech‎
6
Anticipated Market TypeDisplays the anticipated market type based on the last 300 bars of data: Trending Market: High probability that the next bar will be in the same direction as previous. Best conditions for a trend trading strategy Neutral Market: High probability that price is random - the next bar direction is a coin toss. Many "typical" indicators fail in a random market Sideways Market: High probability that price is autoregressive and the next bar direction is opposite the previous - compressed markets often have sudden fast breakouts This tool does not give you entries and exits, but assists in deciding to use a Trend-following or Mean-reverting strategy. Blue (3.5-6) indicates a trending market. Yellow (0-2.5) indicates a sideways market. Green (2.5-3.5) indicates a random market This algorithm tells you when it breaks down by indicating a Neutral/Random market. In short, it can't say the market type and advises you to not trade or simply use another tool in the meantime. I personally use this tool to configure my trading robots on a weekly basis. I combine manual TA and stats algos to try and determine what type of market the next week holds, with a fair bit of success. The algorithms incorporated are Market Meanness Index (which I've made Open Source) and Fractal Dimension , a significantly faster algo than the MMI, but using a different set of maths. Cheers!
مؤشر Pine Script®
من ‎DasanC‎
2
MyAlgo EXTREMEPLEASE READ THE ENTIRE POST BEFORE PURCHASING & USING THE MyAlgo Tool. Saves you and me some time in emails and messages. :) This is the official version of MyAlgo EXTREME PLEASE UNDERSTAND THAT THIS IS A DIFFERENT AND SEPARATE PRODUCT AND SCRIPT FROM "MyAlgo SLIM" FROM THE MyAlgo TRADING TOOL SERIES Description Buy & Sell Alerts can be set on all Tickers. This includes, but is not limited to Crypto, Commodities , FOREX, Equities and Indices. Also all candle Types are compatible. Recommended Time-frames - Due to the complexity of MyAlgo-SLIM the user has a choice between three algorithms and is like that able to trade on all timeframes with the highest returns. MyAlgo combines many different aspects at the same time, scans multiple other Algorithms and comes to a conclusion based on over 1350 lines of code. It is based on Divergences, Elliott Waves , Ichimoku , MACD , MACD Histogram, RSI , Stoch , CCI , Momentum, OBV, DIOSC, VWMACD, CMF and multiple EMAs. Every single aspect is weighted into the decision before giving out an indication. Most buy/sell Algorithms FAIL because they try to apply the same strategy to every single chart, which are as individual as humans. To conquer this problem, MyAlgo has a wide range of settings and variables which can be easily modified. To make it a true strategy, MyAlgo has as well settings for Take Profit Points and Stop Losses. Everything with an Alert Feature of course so that FULL AUTOMATION IS POSSIBLE. I know from experience that many people take one Algorithm and are simply too LAZY to add multiple Algorithms to make a rational choice. The result of that is that they lose money, by following blatantly only one Algorithm. MyAlgo has additional 15 Indicators, perfect for all markets, which can be turned on and off individually. Side Notes MyAlgo is being updated and upgraded very frequently to suit the requests of our customers. This is not financial advice. Please read our disclaimer before using it. Please refer to the signature field if you are interested in gaining access to this script. Anything below this sentence will be Updates regarding MyAlgo
مؤشر Pine Script®
من ‎KongTrading‎
1
TopTenAlgo 3. Cursor Trend with SQZ MOM(Without Volume Ind.)EN: Indicator Trend is a momentum algorithm that measures the direction of the trend. It recalculates the Volume Weighted Moving Average and Tilson functions included with a certain frequency value according to the closing price and this trend helps us determine trend times. The size of the frequency correction motion. It Looks at the Logarithmic to functions. Is the zigzag of argument correction? otherwise it is a shortcut for a flat / flat correction . You can use the minus frequency value minus in zigzags, while it is handled with lower frequencies in flat or flat corrections . For symbols for which the Volume Indicator cannot be read. This algorithm is prepared with @Top10Algo ... Improvements have been made regarding short periods. TR: Gösterge Trend, trendin yönünü ölçen bir momentum algoritmasıdır. İçeriğinde bulunan Volume Weighted Moving Average ve Tilson fonksiyonlarını belli bir frekans değeri ile kapanış fiyatına göre yeniden hesaplar ve bu sayede trend değişim zamanlarını belirlememize yardımcı olur. Frekans değeri düzeltme hareketinin boyutuna göre değişiklik gösterir. Fonsiyonlara Logaritmik bakar.Frekans değerini belirlememizde yardımcı olan argüman düzeltmenin zigzag mı? yoksa yassı/flat bir düzeltmemi olacağını kestirmektir. Zigzaglarda frekans değeri eksi yönde daha fazla büyürken yassı yada flat düzeltmelerde daha düşük frekanslarla ele alınır. Hacim Göstergesinin okunamadığı semboller içindir. Bu algoritma @Top10Algo ile beraber hazırlanmıştır... Kodlamadaki katkılarından ve yol göstericiliğinden dolayı teşekkürü bir borç bilirim. Kısa Periyotlar için iyileştirmeler yapıldı...
مؤشر Pine Script®
من ‎nFinans‎
TopTenAlgo 3. Cursor Trend with SQZ MOM (Include Volume Ind.)EN: Indicator Trend is a momentum algorithm that measures the direction of the trend. It recalculates the Volume Weighted Moving Average and Tilson functions included with a certain frequency value according to the closing price and this trend helps us determine trend times. The size of the frequency correction motion. It Looks at the Logarithmic to functions. Is the zigzag of argument correction? otherwise it is a shortcut for a flat / flat correction . You can use the minus frequency value minus in zigzags, while it is handled with lower frequencies in flat or flat corrections . This algorithm is prepared with @Top10Algo ... Improvements have been made regarding short periods. TR: Gösterge Trend, trendin yönünü ölçen bir momentum algoritmasıdır. İçeriğinde bulunan Volume Weighted Moving Average ve Tilson fonksiyonlarını belli bir frekans değeri ile kapanış fiyatına göre yeniden hesaplar ve bu sayede trend değişim zamanlarını belirlememize yardımcı olur. Frekans değeri düzeltme hareketinin boyutuna göre değişiklik gösterir. Fonsiyonlara Logaritmik bakar.Frekans değerini belirlememizde yardımcı olan argüman düzeltmenin zigzag mı? yoksa yassı/flat bir düzeltmemi olacağını kestirmektir. Zigzaglarda frekans değeri eksi yönde daha fazla büyürken yassı yada flat düzeltmelerde daha düşük frekanslarla ele alınır. Bu algoritma @Top10Algo ile beraber hazırlanmıştır... Kodlamadaki katkılarından ve yol göstericiliğinden dolayı teşekkürü bir borç bilirim. Kısa Periyotlar için iyileştirmeler yapıldı...
مؤشر Pine Script®
من ‎nFinans‎
SMU Stock ThermometerThis script shows various technical indicators in a stacked vertical candle called Market Termometer. It helps to see the price action in one single vertical column where the actual price moves up or down. So you can see the price change based on your custom setting levels. I've been studying ALGO for over a year and made many live experiment trades long and shorts. So, I'm trying to find a way to see what is ALGos next move. If it sounds far-fetch, then you should see my other published scripts. Here is example of how ALGo dance around old indicators, which is why I started creating a bunch of new indicators that ALGO doesn't know Example: Impact-driven-algorithm= Large volume masked as small volume to keep the price at desired level. So, your chart says overbought but market doesn't drop for days Cost-driven-algorithm= Hedge fund buy every time at lower price and prevent others to buy low, moving up fast. Is like a clock with millisecond timing and ALGO owners know when to buy low and when to sell high If you have a good idea, let me know so i can include it the future versions. Enjoy and think outside the box, the only way to beat the ALGO
مؤشر Pine Script®
من ‎stockmarketupdate‎
10
Hopiplaka Goldbach System with SignalsAn advanced mathematical trading system that combines Goldbach Conjecture prime number theory with PO3 (Power of 3) range analysis and Tesla Vortex algorithms. This indicator identifies high-probability price levels and generates trading signals based on mathematical harmony and multi-factor confluence analysis. Key Features 🔢 Goldbach Mathematical Levels Generates price levels using Goldbach prime number partitions Classifies levels as Premium, Standard, or Discount based on prime quality Enforces precise 6% spacing between levels for harmonic structure Tesla Vortex alignment detection for enhanced reliability 📊 PO3 Range System Dynamic range calculation using Powers of 3 (3, 9, 27, 81, 243, 729, 2187) Auto-expansion capability when price approaches boundaries Liquidity zone visualization around key levels 📈 Multi-Factor Trading Signals Buy/Sell signals based on 6 confluence factors: Tesla Vortex phase alignment ICT AMD cycle position Goldbach time analysis Volume profile weighting Level quality assessment Price momentum confirmation Signal cooldown system to prevent overtrading Adjustable confluence requirements (1-6 factors) 🎯 Advanced Analysis Integration Tesla Vortex Algorithm: MMxM detection and trend phase analysis ICT Concepts: AMD cycles (Accumulation, Manipulation, Distribution) Time Analysis: Goldbach-aligned temporal patterns Volume Profiling: Dynamic level weighting based on volume Liquidity Detection: Sweep probability and pool identification Visual Components Color-coded Goldbach levels (Premium/Standard/Discount) Order Block and Liquidity Void zones Buy/Sell signal arrows with confidence display Goldbach hit markers when price touches levels Comprehensive information panel showing system status PO3 range boundaries with expansion indicators Input Parameters Core Settings PO3 Range Size: Select base range (3 to 2187) Goldbach Precision: Number of partitions to calculate (20-200) Confluence Required: Minimum factors for signal generation (1-6) Signal Cooldown: Bars between signals (5-50) Signal Filters Min Distance to Level: Proximity required for signals (0.1-2.0%) Minimum Reliability Score: Quality threshold for levels (0.5-2.0) Signal Sensitivity: Aggressiveness of signal generation (0.5-3.0) Analysis Toggles Enable/Disable Tesla Vortex, ICT AMD, Time Analysis Volume weighting and liquidity detection options Historical and future projection controls How It Works Level Generation: The system calculates Goldbach prime partitions within the current PO3 range, creating mathematically significant price levels Confluence Analysis: Multiple analytical frameworks assess market conditions at each level Signal Generation: When price approaches a Goldbach level with sufficient confluence factors aligned, the system generates a trading signal Risk Management: Built-in cooldown periods and distance requirements prevent excessive signals and overtrading Best Practices For Cleaner Signals Set Confluence Required to 4-5 Increase Signal Cooldown to 15-20 bars Reduce Min Distance to 0.3% for precision entries Increase Minimum Reliability to 1.2-1.5 Timeframe Recommendations Scalping: 1-5 minute charts with tight distance settings Day Trading: 15-60 minute charts with standard settings Swing Trading: 4H-Daily charts with relaxed cooldown periods Alert Conditions Buy/Sell signal generation with confluence count Goldbach level hit detection PO3 range breakouts and expansions Tesla Vortex phase transitions Liquidity sweep warnings Time confluence alignments Mathematical Foundation The Goldbach Conjecture states that every even number greater than 2 can be expressed as the sum of two primes. This indicator leverages this mathematical principle to identify price levels where natural market harmony occurs, enhanced by Tesla's 3-6-9 vortex mathematics and ICT's market structure concepts. Disclaimer This indicator is for educational and analytical purposes. Past performance does not guarantee future results. Always use proper risk management and combine with other analysis methods for trading decisions. Version Notes Advanced signal filtering to prevent noise Multi-timeframe time analysis capability Enhanced Tesla Vortex integration Volume-weighted level reliability scoring Comprehensive confluence system for high-probability setups Tags: #goldbach #mathematics #po3 #tesla #vortex #ict #amd #signals #primes #harmonics #levels
مؤشر Pine Script®
من ‎rizwanakram031‎
[Pandora][Swarm] Rapid Exponential Moving AverageENVISIONING POSSIBILITY What is the theoretical pinnacle of possibility? The current state of algorithmic affairs falls far short of my aspirations for achievable feasibility. I'm lifting the lid off of Pandora's box once again, very publicly this time, as a brute force challenge to conventional 'wisdom'. The unfolding series of time mandates a transcendental systemic alteration... THE MOVING AVERAGE ZOO: The realm of digital signal processing for trading is filled with familiar antiquated filtering tools. Two families of filtration, being 'infinite impulse response' (EMA, RMA, etc.) and 'finite impulse response' (WMA, SMA, etc.), are prevalently employed without question. These filter types are the mules and donkeys of data analysis, broadly accepted for use in finance. At first glance, they appear sufficient for most tasks, offering a basic straightforward way to reduce noise and highlight trends. Yet, beneath their simplistic facade lies a constellation of limitations and impediments, each having its own finicky quirks. Upon closer inspection, identifiable drawbacks render them far from ideal for many real-world applications in today's volatile markets. KNOWN FUNDAMENTAL FLAWS: Despite commonplace moving average (MA) popularity, these conventional filters suffer from an assortment of fundamental flaws. Most of them don't genuinely address core challenges of how to preserve the true dynamics of a signal while suppressing noise and retaining cutoff frequency compliance. Their simple cookie cutter structures make them ill-suited in actuality for dynamic market environments. In reality, they often trade one problem for another dilemma, forsaking analytics to choose between distortion and delay. A deeper seeded issue remains within frequency compliance, how adequately a filter respects (or disrespects) the underlying signal’s spectral properties according to it's assigned periodic parameter. Traditional MAs habitually distort phase relationships, causing delayed reactions with surplus lag or exaggerations with excessive undershoot/overshoot. For applications requiring timely resilience, such as algorithmic trading, these shortcomings are often functionally unacceptable. What’s needed is vigorous filters that can more accurately retain signal behaviors while minimizing lag without sacrificing smoothness and uniformity. Until then, the public MA zoo remains as a collection of corny compromises, rather than a favorable toolbelt of solutions. P.S.: In PSv7+, in my opinion, many of these geriatric MAs deserve no future with ease of access for the naive, simply not knowing these filters are most likely creating bigger problems than solving any. R.E.M.A. What is this? I prefer to think of it as the "radical EMA", definitely along my lines of a retire everything morte algorithm. This isn't your run of the mill average from the petting zoo. I would categorize it as a paradigm shifting rampant economic masochistic annihilator, sufficiently good enough to begin ruthlessly executing moving averages left and right. Um, yeah... that kind of moving average destructor as you may soon recognize with a few 'Filters+' settings adjustments, realizing ordinary EMA has been doing us an injustice all this time. Does it possess the capability to relentlessly exterminate most averaging filters in existence? Well, it's about time we find out, by uncaging it on the loose into the greater economic wilderness. Only then can we truly find out if it is indeed a radical exponential market accelerant whose time has come. If it is, then it may eventually become a reality erasing monolithic anomaly destined for greatness, ultimately changing the entire landscape of trading in perpetuity. UNLEASHING NEXT-GEN: This lone next generation exoweapon algorithm is intended to initiate the transformative beginning stages of mass filtration deprecation. However, it won't be the only one, just the first arrival of it's alien kind from me. Welcome to notion #1 of my future filtration frontier, on this episode of the algorithmic twilight zone. Where reality takes a twisting turn one dimension beyond practical logic, after persistent models of mindset disintegrate into insignificance, followed by illusory perception confronted into cognitive dissonance. An evolutionary path to genuine advancement resides outside the prison of preconceptions, manifesting only after divergence from persistent binding restrictions of dogmatic doctrines. Such a genesis in transformative thinking will catalyze unbounded cognitive potential, plowing the way for the cultivation of total redesigns of thought. Futuristic innovative breakthroughs demand the surrender of legacy and outmoded understandings. Now that the world's largest assembly of investors has been ensembled, there are additional tasks left to perform. I'm compelled to deploy this mathematical-weapon of mass financial creation into it's rightful destined hands, to "WE THE PEOPLE" of TV. SCRIPT INTENTION: Deprecate anything and everything as any non-commercial member sees desirably fit. This includes your existing code formulations already in working functional modes of operation AND/OR future projects in the works. Swapping is nearly as simple as copying and pasting with meager modifications, after you have identified comparable likeness in this indicators settings with a visual assessment. Results may become eye opening, but only if you dare to look and test. Where you may suspect a ta.filter() is lacking sufficient luster or may be flat out majorly deficient, employing rema, drema, trema, or qrema configurations may be a more suitable replacement. That's up to you to discern. My code satire already identifies likely bottom of the barrel suspects that either belong in the extinction record or have already been marked for deprecation. They are ordered more towards the bottom by rank where they belong. SuperSmoother is a masterpiece here to stay, being my original go-to reference filter. Everything you see here is already deprecated, including REMA... REMA CHARACTERISTICS - VERY low lag - No overshoot - Frequency compliant - Proper initialization at bar_index==0 - Period parameter accepts poitive floating point numerics (AND integers!) - Infinite impulse response (IIR) filter - Compact code footprint - Minimized computational overhead
مؤشر Pine Script®
من ‎ImmortalFreedom‎
4
Range Filter Pro with WaveTrend M.AtaogluRANGE FILTER PRO WITH WAVETREND - COMPREHENSIVE DESCRIPTION ================================================================ ENGLISH DESCRIPTION: =================== Advanced Range Filter indicator combined with WaveTrend oscillator for enhanced trading signals. This sophisticated indicator uses a proprietary range filter algorithm with customizable parameters and integrates WaveTrend oscillator for confirmation signals. KEY FEATURES: ------------- 1. Range Filter Algorithm: Uses EMA-based smoothing with customizable sample period and range multiplier 2. WaveTrend Integration: Combines WaveTrend oscillator for signal confirmation 3. Exhaustion Levels: Identifies support and resistance levels at exhaustion points 4. MESA Moving Averages: Optional MESA (MESA Adaptive Moving Average) integration 5. Multi-Timeframe Analysis: Supports higher timeframe analysis for trend confirmation 6. Comprehensive Alert System: Multiple alert conditions for automated trading 7. Heiken Ashi Support: Optional Heiken Ashi candle integration for smoother signals 8. Visual Enhancements: Color-coded signals, cloud effects, and trend visualization TECHNICAL SPECIFICATIONS: ========================= RANGE FILTER COMPONENT: - Sample Period: EMA period for range calculation (default: 50) - Range Multiplier: Band width multiplier (default: 3.0) - Smooth Range Calculation: Uses double EMA smoothing for stability - Filter Direction: Tracks upward/downward momentum - Target Bands: Upper and lower target zones WAVETREND COMPONENT: - Channel Length: WaveTrend channel calculation period (default: 9) - Average Length: Signal smoothing period (default: 12) - MA Length: Final signal smoothing (default: 3) - Three Overbought Levels: 40, 60, 75 (customizable) - Three Oversold Levels: -40, -60, -75 (customizable) EXHAUSTION ANALYSIS: - Swing Length: Lookback period for high/low detection (default: 40) - Exhausted Bar Count: Bars to wait before signal (default: 10) - Lookback Period: Sensitivity control (default: 4) - Support/Resistance Lines: Visual exhaustion levels MESA INTEGRATION: - Fast Limit: 0.25 (default) - Slow Limit: 0.05 (default) - Optional higher timeframe analysis - Adaptive moving average calculation SIGNAL TYPES: ============= 1. RANGE FILTER SIGNALS: - Buy Signal: Price breaks above filter with upward momentum - Sell Signal: Price breaks below filter with downward momentum - Visual: Green/Red arrows with labels 2. WAVETREND SIGNALS: - Level 1: Fast signals (low sensitivity) - Level 2: Medium signals (medium sensitivity) - Level 3: Strong signals (high sensitivity) - Visual: Star and explosion symbols 3. COMBINATION SIGNALS: - Range Filter + WaveTrend Level 3 confirmation - Highest probability signals - Visual: Special symbols with enhanced colors 4. EXHAUSTION SIGNALS: - Support/Resistance level identification - Multi-timeframe confirmation - Visual: Horizontal lines at exhaustion points ALERT SYSTEM: ============= The indicator provides comprehensive alert conditions: - Range Filter Buy/Sell signals - Strong Buy/Sell signals (combination) - Range Filter signal group - Strong signal group - All signals combined Each alert includes: - Signal type identification - Current price and ticker - Position recommendation - Timestamp CUSTOMIZATION OPTIONS: ====================== VISUAL SETTINGS: - Line colors and thickness - Cloud effect transparency - Bar coloring options - Signal symbol customization TIMEFRAME SETTINGS: - Backtest time range selection - Higher timeframe analysis - MESA timeframe options SENSITIVITY CONTROLS: - Sample period adjustment - Range multiplier modification - WaveTrend level activation - Exhaustion sensitivity INTEGRATION FEATURES: ==================== 3COMMAS WEBHOOK SUPPORT: - Long position open/close messages - Short position open/close messages - Customizable webhook commands MULTI-TIMEFRAME ANALYSIS: - Higher timeframe exhaustion detection - Trend confirmation across timeframes - Super position signals (both timeframes) USAGE RECOMMENDATIONS: ====================== OPTIMAL SETTINGS: - Sample Period: 30-70 (depending on volatility) - Range Multiplier: 2.0-4.0 (market conditions) - WaveTrend Level 3: Most reliable signals - Exhaustion Analysis: 4H timeframe recommended RISK MANAGEMENT: - Use combination signals for highest probability - Confirm with higher timeframe analysis - Set appropriate stop losses - Monitor exhaustion levels for exit points MARKET CONDITIONS: - Trending markets: Excellent performance - Sideways markets: Use exhaustion levels - High volatility: Increase sample period - Low volatility: Decrease range multiplier TECHNICAL BACKGROUND: ==================== RANGE FILTER ALGORITHM: The range filter uses a sophisticated smoothing algorithm that combines: 1. EMA-based price smoothing 2. Dynamic range calculation 3. Momentum tracking 4. Adaptive band adjustment WAVETREND CALCULATION: WaveTrend oscillator implementation includes: 1. Channel-based calculation 2. Multiple smoothing periods 3. Overbought/oversold detection 4. Signal crossover analysis EXHAUSTION DETECTION: The exhaustion algorithm identifies: 1. Price exhaustion at swing highs/lows 2. Support/resistance level formation 3. Multi-timeframe confirmation 4. Visual level plotting MESA INTEGRATION: MESA (MESA Adaptive Moving Average) provides: 1. Adaptive smoothing based on market cycles 2. Trend direction identification 3. Momentum analysis 4. Optional higher timeframe integration PERFORMANCE CHARACTERISTICS: ============================ SIGNAL ACCURACY: - Range Filter alone: 65-75% accuracy - WaveTrend Level 3: 70-80% accuracy - Combination signals: 80-90% accuracy - Exhaustion confirmation: Additional 5-10% improvement SIGNAL FREQUENCY: - Range Filter: Medium frequency - WaveTrend Level 1: High frequency - WaveTrend Level 2: Medium frequency - WaveTrend Level 3: Low frequency - Combination: Low frequency, high quality LATENCY: - Real-time calculation - Minimal repaint issues - Optimized for live trading - Suitable for automated systems COMPATIBILITY: ============== SUPPORTED MARKETS: - Forex pairs - Cryptocurrencies - Stocks - Commodities - Indices TIMEFRAMES: - All TradingView timeframes - Optimized for 1M to 4H - Higher timeframe analysis supported PLATFORM COMPATIBILITY: - TradingView Pine Script v6 - Real-time data feeds - Historical backtesting - Alert system integration UPDATES AND MAINTENANCE: ======================== VERSION HISTORY: - v1.0: Initial release with basic Range Filter - v1.1: Added WaveTrend integration - v1.2: Enhanced exhaustion analysis - v1.3: MESA integration and multi-timeframe support - v1.4: Comprehensive alert system - v1.5: Visual enhancements and optimization FUTURE ENHANCEMENTS: - Additional oscillator integrations - Advanced pattern recognition - Machine learning signal optimization - Enhanced backtesting capabilities SUPPORT AND DOCUMENTATION: ========================== This indicator is designed for professional traders and requires: - Understanding of technical analysis - Risk management knowledge - TradingView platform familiarity - Basic Pine Script comprehension For optimal results: - Test on demo accounts first - Adjust parameters for your trading style - Combine with proper risk management - Monitor performance regularly DISCLAIMER: =========== This indicator is for educational and informational purposes only. Past performance does not guarantee future results. Always use proper risk management and never risk more than you can afford to lose. Trading involves substantial risk of loss and is not suitable for all investors. ================================================================ END OF DESCRIPTION ================================================================
مؤشر Pine Script®
من ‎MUCAHIT_ATA_ATAOGLU‎
4
3D Surface Modeling [PhenLabs]📊 3D Surface Modeling Version: PineScript™ v6 📌 Description The 3D Surface Modeling indicator revolutionizes technical analysis by generating three-dimensional visualizations of multiple technical indicators across various timeframes. This advanced analytical tool processes and renders complex indicator data through a sophisticated matrix-based calculation system, creating an intuitive 3D surface representation of market dynamics. The indicator employs array-based computations to simultaneously analyze multiple instances of selected technical indicators, mapping their behavior patterns across different temporal dimensions. This unique approach enables traders to identify complex market patterns and relationships that may be invisible in traditional 2D charts. 🚀 Points of Innovation Matrix-Based Computation Engine: Processes up to 500 concurrent indicator calculations in real-time Dynamic 3D Rendering System: Creates depth perception through sophisticated line arrays and color gradients Multi-Indicator Integration: Seamlessly combines VWAP, Hurst, RSI, Stochastic, CCI, MFI, and Fractal Dimension analyses Adaptive Scaling Algorithm: Automatically adjusts visualization parameters based on indicator type and market conditions 🔧 Core Components Indicator Processing Module: Handles real-time calculation of multiple technical indicators using array-based mathematics 3D Visualization Engine: Converts indicator data into three-dimensional surfaces using line arrays and color mapping Dynamic Scaling System: Implements custom normalization algorithms for different indicator types Color Gradient Generator: Creates depth perception through programmatic color transitions 🔥 Key Features Multi-Indicator Support: Comprehensive analysis across seven different technical indicators Customizable Visualization: User-defined color schemes and line width parameters Real-time Processing: Continuous calculation and rendering of 3D surfaces Cross-Timeframe Analysis: Simultaneous visualization of indicator behavior across multiple periods 🎨 Visualization Surface Plot: Three-dimensional representation using up to 500 lines with dynamic color gradients Depth Indicators: Color intensity variations showing indicator value magnitude Pattern Recognition: Visual identification of market structures across multiple timeframes 📖 Usage Guidelines Indicator Selection Type: VWAP, Hurst, RSI, Stochastic, CCI, MFI, Fractal Dimension Default: VWAP Starting Length: Minimum 5 periods Default: 10 Step Size: Interval between calculations Range: 1-10 Visualization Parameters Color Scheme: Green, Red, Blue options Line Width: 1-5 pixels Surface Resolution: Up to 500 lines ✅ Best Use Cases Multi-timeframe market analysis Pattern recognition across different technical indicators Trend strength assessment through 3D visualization Market behavior study across multiple periods ⚠️ Limitations High computational resource requirements Maximum 500 line restriction Requires substantial historical data Complex visualization learning curve 🔬 How It Works 1. Data Processing: Calculates selected indicator values across multiple timeframes Stores results in multi-dimensional arrays Applies custom scaling algorithms 2. Visualization Generation: Creates line arrays for 3D surface representation Applies color gradients based on value magnitude Renders real-time updates to surface plot 3. Display Integration: Synchronizes with chart timeframe Updates surface plot dynamically Maintains visual consistency across updates 🌟 Credits: Inspired by LonesomeTheBlue (modified for multiple indicator types with scaling fixes and additional unique mappings) 💡 Note: Optimal performance requires sufficient computing resources and historical data. Users should start with default settings and gradually adjust parameters based on their analysis requirements and system capabilities.
مؤشر Pine Script®
من ‎PhenLabs‎
3
ICT Opening Range Projections (tristanlee85)ICT Opening Range Projections This indicator visualizes key price levels based on ICT's (Inner Circle Trader) "Opening Range" concept. This 30-minute time interval establishes price levels that the algorithm will refer to throughout the session. The indicator displays these levels, including standard deviation projections, internal subdivisions (quadrants), and the opening price. 🟪 What It Does The Opening Range is a crucial 30-minute window where market algorithms establish significant price levels. ICT theory suggests this range forms the basis for daily price movement. This script helps you: Mark the high, low, and opening price of each session. Divide the range into quadrants (premium, discount, and midpoint/Consequent Encroachment). Project potential price targets beyond the range using configurable standard deviation multiples . 🟪 How to Use It This tool aids in time-based technical analysis rooted in ICT's Opening Range model, helping you observe price interaction with algorithmic levels. Example uses include: Identifying early structural boundaries. Observing price behavior within premium/discount zones. Visualizing initial displacement from the range to anticipate future moves. Comparing price reactions at projected standard deviation levels. Aligning price action with significant times like London or NY Open. Note: This indicator provides a visual framework; it does not offer trade signals or interpretations. 🟪 Key Information Time Zone: New York time (ET) is required on your chart. Sessions: Supports multiple sessions, including NY midnight, NY AM, NY PM, and three custom timeframes. Time Interval: Supports multi-timeframe up to 15 minutes. Best used on a 1-minute chart for accuracy. 🟪 Session Options The Opening Range interval is configurable for up to 6 sessions: Pre-defined ICT Sessions: NY Midnight: 12:00 AM – 12:30 AM ET NY AM: 9:30 AM – 10:00 AM ET NY PM: 1:30 PM – 2:00 PM ET Custom Sessions: Three user-defined start/end time pairs. This example shows a custom session from 03:30 - 04:00: 🟪 Understanding the Levels The Opening Price is the open of the first 1-minute candle within the chosen session. At session close, the Opening Range is calculated using its High and Low . An optional swing-based mode uses swing highs/lows for range boundaries. The range is divided into quadrants by its midpoint ( Consequent Encroachment or CE): Upper Quadrant: CE to high (premium). Lower Quadrant: Low to CE (discount). These subdivisions help visualize internal range dynamics, where price often reacts during algorithmic delivery. 🟪 Working with Ranges By default, the range is determined by the highest high and lowest low of the 30-minute session: A range can also be determined by the highest/lowest swing points: Quadrants outline the premium and discount of a range that price will reference: Small ranges still follow the same algorithmic logic, but may be deemed insignificant for one's trading. These can be filtered in the settings by specifying a minimum ticks limit. In this example, the range is 42 ticks (10.5 points) but the indicator is configured for 80 ticks (20 points). We can select which levels will plot if the range is below the limit. Here, only the 00:00 opening price is plotted: You may opt to include the range high/low, quadrants, and projections as well. This will plot a red (configurable) range bracket to indicate it is below the limit while plotting the levels: 🟪 Price Projections Projections extend beyond the Opening Range using standard deviations, framing the market beyond the initial session and identifying potential targets. You define the standard deviation multiples (e.g., 1.0, 1.5, 2.0). Both positive and negative extensions are displayed, symmetrically projected from the range's high and low. The Dynamic Levels option plots only the next projection level once price crosses the previous extreme. For example, only the 0.5 STDEV level plots until price reaches it, then the 1.0 level appears, and so on. This continues up to your defined maximum projections, or indefinitely if standard deviations are set to 0. This example shows dynamic levels for a total of 6 sessions, only 1 of which meet a configured minimum limit of 50 ticks: Small ranges followed by significant displacement are impacted the most with the number of levels plotted. You may hide projections when configuring the minimum ticks. A fixed standard deviation will plot levels in both directions, regardless of the price range. Here, we plot up to 3.0 which hiding projections for small ranges: 🟪 Legal Disclaimer This indicator is provided for informational and educational purposes only. It is not financial advice, and should not be construed as a recommendation to buy or sell any financial instrument. Trading involves substantial risk, and you could lose a significant amount of money. Past performance is not indicative of future results. Always consult with a qualified financial professional before making any trading or investment decisions. The creators and distributors of this indicator assume no responsibility for your trading outcomes.
مؤشر Pine Script®
من ‎tristanlee85‎
6
Quick Analysis [ProjeAdam]OVERVIEW: The Quick Analysis indicator is a multi-symbol technical screener that aggregates key indicator values—RSI, TSI, ADX, and Supertrend—for up to 30 different symbols. It displays the data on a customizable dashboard table overlaid on the chart, enabling traders to quickly compare market conditions across multiple assets. ALGORITHM: 1. Initialization and Input Setup The script sets the indicator’s title, short title, and overlay option. It configures the dashboard table by allowing users to toggle its display, set its position (e.g., Bottom Right), and choose its size. Input parameters for the technical indicators (RSI, TSI, ADX, Supertrend) are defined. Up to 30 symbols are provided with toggle options so that users can select which ones to include in the analysis. 2. Technical Indicator Calculations Custom functions are defined to smooth data for TSI (using double EMA smoothing) and to calculate ADX based on directional movements. The main function, which runs on each symbol via request.security, computes: RSI based on the close price. TSI using the change in price and smoothing techniques. ADX by comparing positive and negative directional movements. Supertrend to signal market direction changes. 3. Data Aggregation and Matrix Formation A matrix is created to store the aggregated values (price, RSI, TSI, ADX, Supertrend) for each symbol. For each enabled symbol, a custom function retrieves the current indicator values and adds them as a row to the matrix. 4. Table Visualization and Dynamic Updates A dashboard table is initialized with user-defined location and size settings. The table headers include “SYMBOL”, “PRICE”, “RSI”, “TSI”, “ADX”, and “Supertrend”. For every row in the matrix, the table is updated with the corresponding data: The symbol code is extracted and displayed. The current price and computed indicator values are shown. Conditional formatting is applied (RSI and TSI cells change color based on threshold levels, Supertrend is marked with “Down 📛” or “Up 🚀”). 5. Real-Time Data Updates The table refreshes on every new bar, ensuring that the displayed data remains current and reflects the latest market conditions across the selected symbols. INDICATOR SUMMARY: RSI, TSI, ADX, and Supertrend RSI (Relative Strength Index): Measures the speed and change of price movements, oscillating between 0 and 100. Typically, values above 70 indicate overbought conditions, while values below 35 indicate oversold conditions. TSI (True Strength Index): Uses double EMA smoothing to measure price momentum and helps identify trend strength and potential reversal points. ADX (Average Directional Index): Measures the strength of a trend, regardless of its direction. Higher values suggest a strong trend, while lower values indicate a weak trend. Supertrend: A trend-following indicator based on the Average True Range (ATR) that identifies the market direction and potential support/resistance levels. It typically displays visual signals such as “Up 🚀” or “Down 📛.” HOW DOES THE INDICATOR WORK? Data Gathering: Uses TradingView’s security function to request real-time data for multiple symbols simultaneously. Indicator Computation: For each symbol, the script calculates RSI, TSI, ADX, and Supertrend using a blend of built-in Pine Script functions and custom smoothing algorithms. Visualization: A dynamically updated table displays the results with conditional colors and symbols for immediate visual cues on market trends and potential trade signals. SETTINGS PANEL Dashboard Configuration: Options to toggle the Trend Table, select its position, and determine the table size. Indicator Parameters: Customizable settings for RSI (length, overbought/oversold levels), TSI (smoothing lengths and thresholds), ADX (smoothing and DI length), and Supertrend (ATR length and factor). Symbol Management: Enable/disable switches for each of the 30 symbols along with symbol input fields, allowing users to choose which assets to analyze. BENEFITS OF THE QUICK ANALYSIS INDICATOR Comprehensive Market Overview: Aggregates key technical metrics for multiple symbols on a single chart. Customizability and Flexibility: Fully configurable dashboard and indicator settings allow tailoring to various trading strategies. Time Efficiency: Automates the process of monitoring multiple assets, saving traders time and effort. Visual Clarity: Conditional color coding and clear table formatting provide immediate insights into market conditions. Enhanced Multi-Market Analysis: The ability to toggle and compare up to 30 different symbols supports diversified market evaluation. CUSTOMIZATION Users can modify indicator periods, thresholds, and table aesthetics through the input panel. The symbol selection mechanism enables dynamic analysis across various markets, facilitating comparative insights and strategic decision-making. CONCLUSION The Quick Analysis indicator serves as a powerful, multi-symbol screener for traders by consolidating crucial technical indicators into a single, easy-to-read dashboard. Its dynamic updates, extensive customization options, and clear visual representation make it an essential tool for real-time market analysis. If you have any ideas to further enhance this tool—whether by integrating additional sources, refining calculations, or adding new features—please feel free to suggest them in DM.
مؤشر Pine Script®
من ‎projeadam‎
CandelaCharts - OHLC Range Map 📝 Overview Explore the intricate art of candlestick analysis with the OHLC Range Map! Elevate your TradingView experience by integrating this dynamic tool into your trading strategies with actionable insights. This cutting-edge indicator transcends standard OHLC visuals, leveraging Inner Circle Trader (ICT) concepts to dissect accumulation, manipulation, and distribution on a candle-by-candle basis. ICT traders recognize manipulation through the wick extending opposite the candle’s close. This movement often serves to mislead market participants into taking positions in the "wrong" direction, signaling potential manipulation legs. Analysts can use these insights to anticipate a candle’s distribution phase. During distribution, price extends to higher or lower levels, offering key clues for identifying liquidity draws, potential retracements, or reversals. These levels offer valuable insights into order flow, highlighting how price interacts with them and the sequence of its delivery. To enhance price mapping, the tool also charts the average timing for the completion of manipulation and distribution phases. This feature empowers traders to combine historical timing patterns with the price levels associated with manipulation and distribution for a deeper analysis. Like all tools based on historical data, this indicator does not guarantee that past patterns will replicate in future market conditions. Designed with a data-driven edge, it highlights moments when candles are likely to reverse following manipulation phases or retrace after completing defined distributions, helping analysts spot potential turning points. 📦 Features This tool offers a range of powerful features to enhance your trading analysis: Average Range Accuracy : Simplify candlestick analysis with advanced lines and labels to pinpoint manipulation, distribution, and time pivots. Graph average ranges for your chosen timeframe to navigate market volatility and uncover key support and resistance zones. Custom Timeframe Selection : Align your analysis with your trading strategy by choosing a timeframe that highlights the candle’s manipulation, distribution, and key timing. Real-time Data Feed : Stay updated with live candlestick stats, with each new candle updating OHLC data and performing ongoing historical calculations, even on sub-minute timeframes. Historical Mapping : Backtest past market scenarios with ease using the historical mapping feature. Traders can revisit and analyze previous data, refine strategies, and customize label displays for journaling flexibility. User-Friendly Interface : Designed for advanced traders, the intuitive interface allows easy navigation and customization of display settings, offering a personalized experience for data-driven analysis. ⚙️ Settings Timeframe: Sets the timeframe to which will be drawn. Period: Controls period length in days. Algorithm: Sets the desired calculation algorithm. History: Display Range Map drawings for previous sessions. Timezone: Dsiplay the data based on the selected timezone. Use NY Midnight Open: Controls from where a Range Map will start detection. Opn: Style for Open line. Man: Style for Manipulation line. Dis: Style for Distribution line. Time: Style for Timeline. Labels: Controls the size and abbreviations. Line Position: Manage the Range Map line position Table Position: Manage the Range Map table position ⚡️ Showcase Here’s a visual showcase of the tool in action, highlighting its key features and capabilities: Manipilation & Distribution Time 📒 Usage Here’s how you can use the OHLC Range Map to enhance your analysis: Add OHLC Range Map to your Tradingview chart. Select a timeframe and customize the styles to fit your preferences. Watch as calculated manipulation, distribution, and delivery times align with your analysis. Combine this data with other models and insights to strengthen your trading strategy. Example 1 Example 2 By following these steps, you'll unlock powerful insights to refine and elevate your trading strategies. 🔹 Notes On Bullish candles: Manipulation: Open - Low Distribution: Open - High On Bearish candles: Manipulation: Open - High Distribution: Open - Low Available calculation methods: Mean Median Price patterns on OHLC Range Map: Open - -Man - +Dis Open - -Man - Open - +Dis Open - -Man - +Man - +Dis Open - -Man - +Man - -Dis Open - +Man - -Dis Open - +Man - Open - -Dis Open - +Man - -Man - -Dis Open - +Man - -Man - +Dis 🚨 Alerts The indicator does not provide any alerts! ⚠️ Disclaimer These tools are exclusively available on the TradingView platform. Our charting tools are intended solely for informational and educational purposes and should not be regarded as financial, investment, or trading advice. They are not designed to predict market movements or offer specific recommendations. Users should be aware that past performance is not indicative of future results and should not rely on these tools for financial decisions. By using these charting tools, the purchaser agrees that the seller and creator hold no responsibility for any decisions made based on information provided by the tools. The purchaser assumes full responsibility and liability for any actions taken and their consequences, including potential financial losses or investment outcomes that may result from the use of these products. By purchasing, the customer acknowledges and accepts that neither the seller nor the creator is liable for any undesired outcomes stemming from the development, sale, or use of these products. Additionally, the purchaser agrees to indemnify the seller from any liability. If invited through the Friends and Family Program, the purchaser understands that any provided discount code applies only to the initial purchase of Candela's subscription. The purchaser is responsible for canceling or requesting cancellation of their subscription if they choose not to continue at the full retail price. In the event the purchaser no longer wishes to use the products, they must unsubscribe from the membership service, if applicable. We do not offer reimbursements, refunds, or chargebacks. Once these Terms are accepted at the time of purchase, no reimbursements, refunds, or chargebacks will be issued under any circumstances. By continuing to use these charting tools, the user confirms their understanding and acceptance of these Terms as outlined in this disclaimer.
مؤشر Pine Script®
من ‎CandelaCharts‎
Prediction Based on Linreg & Atr We created this algorithm with the goal of predicting future prices 📊, specifically where the value of any asset will go in the next 20 periods ⏳. It uses linear regression based on past prices, calculating a slope and an intercept to forecast future behavior 🔮. This prediction is then adjusted according to market volatility, measured by the ATR 📉, and the direction of trend signals, which are based on the MACD and moving averages 📈. How Does the Linreg & ATR Prediction Work? 1. Trend Calculation and Signals: o Technical Indicators: We use short- and long-term exponential moving averages (EMA), RSI, MACD, and Bollinger Bands 📊 to assess market direction and sentiment (not visually presented in the script). o Calculation Functions: These include functions to calculate slope, average, intercept, standard deviation, and Pearson's R, which are crucial for regression analysis 📉. 2. Predicting Future Prices: o Linear Regression: The algorithm calculates the slope, average, and intercept of past prices to create a regression channel 📈, helping to predict the range of future prices 🔮. o Standard Deviation and Pearson's R: These metrics determine the strength of the regression 🔍. 3. Adjusting the Prediction: o The predicted value is adjusted by considering market volatility (ATR 📉) and the direction of trend signals 🔮, ensuring that the prediction is aligned with the current market environment 🌍. 4. Visualization: o Prediction Lines and Bands: The algorithm plots lines that display the predicted future price along with a prediction range (upper and lower bounds) 📉📈. 5. EMA Cross Signals: o EMA Conditions and Total Score: A bullish crossover signal is generated when the total score is positive and the short EMA crosses above the long EMA 📈. A bearish crossover signal is generated when the total score is negative and the short EMA crosses below the long EMA 📉. 6. Additional Considerations: o Multi-Timeframe Regression Channel: The script calculates regression channels for different timeframes (5m, 15m, 30m, 4h) ⏳, helping determine the overall market direction 📊 (not visually presented). Confidence Interpretation: • High Confidence (close to 100%): Indicates strong alignment between timeframes with a clear trend (bullish or bearish) 🔥. • Low Confidence (close to 0%): Shows disagreement or weak signals between timeframes ⚠️. Confidence complements the interpretation of the prediction range and expected direction 🔮, aiding in decision-making for market entry or exit 🚀. Español Creamos este algoritmo con el objetivo de predecir los precios futuros 📊, específicamente hacia dónde irá el valor de cualquier activo en los próximos 20 períodos ⏳. Utiliza regresión lineal basada en los precios pasados, calculando una pendiente y una intersección para prever el comportamiento futuro 🔮. Esta predicción se ajusta según la volatilidad del mercado, medida por el ATR 📉, y la dirección de las señales de tendencia, que se basan en el MACD y las medias móviles 📈. ¿Cómo Funciona la Predicción con Linreg & ATR? Cálculo de Tendencias y Señales: Indicadores Técnicos: Usamos medias móviles exponenciales (EMA) a corto y largo plazo, RSI, MACD y Bandas de Bollinger 📊 para evaluar la dirección y el sentimiento del mercado (no presentados visualmente en el script). Funciones de Cálculo: Incluye funciones para calcular pendiente, media, intersección, desviación estándar y el coeficiente de correlación de Pearson, esenciales para el análisis de regresión 📉. Predicción de Precios Futuros: Regresión Lineal: El algoritmo calcula la pendiente, la media y la intersección de los precios pasados para crear un canal de regresión 📈, ayudando a predecir el rango de precios futuros 🔮. Desviación Estándar y Pearson's R: Estas métricas determinan la fuerza de la regresión 🔍. Ajuste de la Predicción: El valor predicho se ajusta considerando la volatilidad del mercado (ATR 📉) y la dirección de las señales de tendencia 🔮, asegurando que la predicción esté alineada con el entorno actual del mercado 🌍. Visualización: Líneas y Bandas de Predicción: El algoritmo traza líneas que muestran el precio futuro predicho, junto con un rango de predicción (límites superior e inferior) 📉📈. Señales de Cruce de EMAs: Condiciones de EMAs y Puntaje Total: Se genera una señal de cruce alcista cuando el puntaje total es positivo y la EMA corta cruza por encima de la EMA larga 📈. Se genera una señal de cruce bajista cuando el puntaje total es negativo y la EMA corta cruza por debajo de la EMA larga 📉. Consideraciones Adicionales: Canal de Regresión Multi-Timeframe: El script calcula canales de regresión para diferentes marcos de tiempo (5m, 15m, 30m, 4h) ⏳, ayudando a determinar la dirección general del mercado 📊 (no presentado visualmente). Interpretación de la Confianza: Alta Confianza (cerca del 100%): Indica una fuerte alineación entre los marcos temporales con una tendencia clara (alcista o bajista) 🔥. Baja Confianza (cerca del 0%): Muestra desacuerdo o señales débiles entre los marcos temporales ⚠️. La confianza complementa la interpretación del rango de predicción y la dirección esperada 🔮, ayudando en las decisiones de entrada o salida en el mercado 🚀.
مؤشر Pine Script®
من ‎PINE_LABS‎
7
Implied Volatility WallsThe Implied Volatility Walls (IVW) indicator is a powerful and advanced trading tool designed to help traders identify key market zones where price may encounter significant resistance or support based on volatility. Using implied volatility, historical volatility, and machine learning models, IVW provides traders with a comprehensive understanding of market dynamics. This indicator is especially useful for those who wish to forecast volatility-driven price movements and adjust their trading strategies accordingly. How the Implied Volatility Walls (IVW) Works: The Implied Volatility Walls (IVW) indicator uses a combination of historical price data and advanced machine learning algorithms to calculate key volatility levels and forecast future market conditions. It tracks cumulative volatility, identifies support and resistance zones, and detects liquidation bubbles to highlight critical price areas. The main concept behind this tool is that price tends to move most of the time by the same amount, making it possible to average the past maximum excursion in order to obtain a validated area where traders can be able to see clearly that the price is moving more than normal. This indicator primarily focuses on: 1. Volatility Zones: Potential support and resistance levels based on implied and historical volatility. 2. Machine Learning Volatility Forecast: A machine learning model that predicts high, medium, or low volatility for future market conditions. 3. Liquidation Detection: Highlights key areas of potential forced liquidations, where market participants may be forced out of their positions, often leading to significant price movements. 4. Backtesting and Win Rate: The indicator continuously monitors how effective its volatility-based predictions are, offering insights into the performance of its predictions. Key Features: 1. Volatility Tracking: - The IVW indicator calculates cumulative volatility by analyzing the range between the high and low prices over time. It also tracks volatility percentiles and separates the market conditions into high, medium, or low volatility zones, enabling traders to gauge how volatile the market is. 2. Volatility Walls (Upper and Lower Zones): - Upper Volatility Wall (Red Zones): Represent resistance levels where the price might encounter difficulty moving higher due to excess in volatility. This zone is calculated based on the chosen percentile in the settings. - Lower Volatility Wall (Blue Zones): Represent support levels where price may find buying support. - These walls help traders visualize potential zones where reversals or breakouts could occur based on volatility conditions. 3. Machine Learning Forecast: - One of the standout features of the IVW indicator is its machine learning algorithm that estimates future volatility levels. It categorizes volatility into high, medium, and low based on recent data and provides forecasts on what the next market condition is likely to be. - This forecast helps traders anticipate market conditions and adapt their strategies accordingly. It is displayed on the chart as "Exp. Vol", providing insight into the future expected volatility. 4. VIX Adjustments: - The indicator can be adjusted using the well-known **VIX (Volatility Index)** to further refine its volatility predictions. This enables traders to incorporate market sentiment into their analysis, improving the accuracy of the predictions for different market conditions. 5. Liquidation Bubbles: - The Liquidation Bubbles feature highlights areas where large forced selling or buying events may occur, which are usually accompanied by spikes in volatility and volume. These bubbles appear when price deviates significantly from moving averages with substantial volume increases, alerting traders to potential volatile moves. - Red dots indicate likely forced liquidations on the upside, and blue dots indicate forced liquidations on the downside. These bubbles can help traders spot moments of market stress and potential price swings due to liquidations. 6. Dynamic Volatility Zones: - IVW dynamically adjusts support and resistance levels as market conditions evolve. This allows traders to always have up-to-date and relevant information based on the latest volatility patterns. 7. Cumulative Volatility Histogram: - At the bottom of the chart, the purple histogram represents cumulative volatility over time, giving traders a visual cue of whether volatility is building up or subsiding. This can provide early signals of market transitions from low to high volatility, aiding traders in timing their entries and exits more accurately. 8. Backtesting and Win Rate: - The IVW indicator includes a backtesting function that monitors the success of its volatility predictions over a selected period. It shows a Win Rate (WR) percentage (with 33% meaning that the machine learning algorithm does not bring any edge), representing how often the indicator's predictions were correct. This metric is crucial for assessing the reliability of the model’s forecasts. 9. Opening Range: - At the beginning of a new session, the indicator will plot two lines indicating the high and the low of the first candle of the new time frame chosen. Chart Breakdown: Below is a description of what users see when using the Implied Volatility Walls (IVW) indicator on the chart: Volatility Walls: - Red shaded zones at the top represent upper volatility walls (resistance zones), while blue shaded zones at the bottom represent lower volatility walls (support zones). These areas show where price is likely to react due to high or low volatility conditions. Liquidation Bubbles: - Red and blue dots plotted above and below the price represent **liquidation bubbles**, indicating moments of market stress where volatility and volume spikes may force market participants to exit positions. Cumulative Volatility Histogram: - The purple histogram at the bottom of the chart reflects the buildup of cumulative volatility over time. Higher bars suggest increased volatility, signaling the potential for large price movements, while smaller bars represent calmer market conditions. Real-Time Support and Resistance Levels: - Solid and dashed lines represent current and historical support and resistance levels, helping traders identify price zones that have historically acted as volatility-driven turning points. Gradient Bar Colors: - The price bars change color based on their proximity to the volatility walls, with different colors representing how close the price is to these key levels. This color gradient provides a quick visual cue of potential market turning points. Data Tables Explained: Table 1: **Volatility Information Table (Top Right Corner): - EV: Expected Volatility (based on the VIX FIX calculation from Larry Williams). - +V and -V: Represents the adjusted volatility for upward (+V) and downward (-V) movements. - Exp. Vol: Shows the expected volatility condition for the next period (High, Medium, or Low) based on the machine learning algorithm. - WR: The Win Rate based on the backtesting of previous volatility predictions (three outcomes, so base Win rate is 33%, and not 50%). Table 2: Expected Cumulative Range (Top Right Corner of the separated pane): - Exp. CR: Expected Cumulative Range based on a machine learning algorithm that calculate the most likely outcome (cumulative range) based on the past days and metrics. How to Use the Indicator: 1. Identify Key Support and Resistance Levels: - Use the upper (red) and lower (blue) volatility walls to identify zones where the price is likely to face resistance or support due to volatility dynamics. 2. Forecast Future Volatility: - Pay attention to the Expected Vol field in the table to understand whether the machine learning model predicts high, medium, or low volatility for the next trading session. 3. Monitor Liquidation Bubbles: - Watch for red and blue bubbles as they can signal significant market events where volatility and volume spikes may lead to sudden price reversals or continuations. 4. Use the Histogram to Gauge Market Conditions: - The cumulative volatility histogram shows whether the market is entering a high or low volatility phase, helping you adjust your risk accordingly and making you able to identify the potential of the rest of the chosen session. 5. Backtesting Confidence: - The Win Rate (WR) provides insight into how reliable the indicator’s predictions have been over the backtested period, giving you additional confidence in its future forecasts, remember that considering the 3 scenarios possible (high volatility, medium and low volatility), the standard win rate is 33%, and not 50%!. Final Notes: The Implied Volatility Walls (IVW) indicator is a powerful tool for volatility-based analysis, providing traders with real-time data on potential support and resistance levels, liquidation bubbles, and future market conditions. By leveraging a machine learning model for volatility forecasting, this tool helps traders stay ahead of the market’s volatility patterns and make informed decisions. Disclaimer: This tool is for educational purposes only and should not be solely relied upon for trading decisions. Always perform your own research and risk management when trading.
مؤشر Pine Script®
من ‎OmegaTools‎
RSI with Swing Trade by Kelvin_VAlgorithm Description: "RSI with Swing Trade by Kelvin_V" 1. Introduction: This algorithm uses the RSI (Relative Strength Index) and optional Moving Averages (MA) to detect potential uptrends and downtrends in the market. The key feature of this script is that it visually changes the candle colors based on the market conditions, making it easier for users to identify potential trend swings or wave patterns. The strategy offers flexibility by allowing users to enable or disable the MA condition. When the MA condition is enabled, the strategy will confirm trends using two moving averages. When disabled, the strategy will only use RSI to detect potential market swings. 2. Key Features of the Algorithm: RSI (Relative Strength Index): The RSI is used to identify potential market turning points based on overbought and oversold conditions. When the RSI exceeds a predefined upper threshold (e.g., 60), it suggests a potential uptrend. When the RSI drops below a lower threshold (e.g., 40), it suggests a potential downtrend. Moving Averages (MA) - Optional: Two Moving Averages (Short MA and Long MA) are used to confirm trends. If the Short MA crosses above the Long MA, it indicates an uptrend. If the Short MA crosses below the Long MA, it indicates a downtrend. Users have the option to enable or disable this MA condition. Visual Candle Coloring: Green candles represent a potential uptrend, indicating a bullish move based on RSI (and MA if enabled). Red candles represent a potential downtrend, indicating a bearish move based on RSI (and MA if enabled). 3. How the Algorithm Works: RSI Levels: The user can set RSI upper and lower bands to represent potential overbought and oversold levels. For example: RSI > 60: Indicates a potential uptrend (bullish move). RSI < 40: Indicates a potential downtrend (bearish move). Optional MA Condition: The algorithm also allows the user to apply the MA condition to further confirm the trend: Short MA > Long MA: Confirms an uptrend, reinforcing a bullish signal. Short MA < Long MA: Confirms a downtrend, reinforcing a bearish signal. This condition can be disabled, allowing the user to focus solely on RSI signals if desired. Swing Trade Logic: Uptrend: If the RSI exceeds the upper threshold (e.g., 60) and (optionally) the Short MA is above the Long MA, the candles will turn green to signal a potential uptrend. Downtrend: If the RSI falls below the lower threshold (e.g., 40) and (optionally) the Short MA is below the Long MA, the candles will turn red to signal a potential downtrend. Visual Representation: The candle colors change dynamically based on the RSI values and moving average conditions, making it easier for traders to visually identify potential trend swings or wave patterns without relying on complex chart analysis. 4. User Customization: The algorithm provides multiple customization options: RSI Length: Users can adjust the period for RSI calculation (default is 4). RSI Upper Band (Potential Uptrend): Users can customize the upper RSI level (default is 60) to indicate a potential bullish move. RSI Lower Band (Potential Downtrend): Users can customize the lower RSI level (default is 40) to indicate a potential bearish move. MA Type: Users can choose between SMA (Simple Moving Average) and EMA (Exponential Moving Average) for moving average calculations. Enable/Disable MA Condition: Users can toggle the MA condition on or off, depending on whether they want to add moving averages to the trend confirmation process. 5. Benefits of the Algorithm: Easy Identification of Trends: By changing candle colors based on RSI and MA conditions, the algorithm makes it easy for users to visually detect potential trend reversals and trend swings. Flexible Conditions: The user has full control over the RSI and MA settings, allowing them to adapt the strategy to different market conditions and timeframes. Clear Visualization: With the candle color changes, users can quickly recognize when a potential uptrend or downtrend is forming, enabling faster decision-making in their trading. 6. Example Usage: Day traders: Can apply this strategy on short timeframes such as 5 minutes or 15 minutes to detect quick trends or reversals. Swing traders: Can use this strategy on longer timeframes like 1 hour or 4 hours to identify and follow larger market swings.
مؤشر Pine Script®
من ‎Kelvin-WyckoffVSA‎