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DAILY CANDLE SIZE TRACKERDAILY CANDLE SIZE TRACKER The daily candle size Indicator is a versatile tool designed to measure and analyze the length of candlesticks on your TradingView chart. This indicator helps traders gain insights into market volatility and price movement by displaying the relative size of particular size of candle in terms of its range (open to close) of particular day of week. Key Features: Visual Representation: Displays the length of every qualified candle directly on the chart, allowing for immediate visual assessment. Historical Analysis: View the lengths of past candles to identify patterns or changes in market volatility over time of certain size of candle. Usage: • Probability analysis : It help to analyze candles based on candle size on particular days of the week. • Volatility Assessment: Large candles may indicate higher market volatility, while smaller candles can suggest periods of consolidation or lower volatility. • Trade Confirmation: Use candle length information in conjunction with other technical indicators to confirm trade signals and refine entry and exit points. USER INPUTS • DAY LABEL: Select Particular day of week or all days of week. • START DATE : Select the prefer date from where you want to calculate. • CANDLE LENGTH : Define length of candle on the basis of open to close. ******************* THIS INDICATOR ONLY WORKS ON DAILY TIMEFRAME**************
Pine Script™ indicator
by Horizon_99
1
Screener | FractalystWhat’s the purpose of this indicator? This indicator is part of the Optirange suite , which analyzes all timeframes using a mechanical top-down approach to determine the overall market bias. It helps you identify the specific timeframes and exact levels for positioning in longs, shorts, or guiding you on whether to stay away from trading a particular market condition. The purpose of the Screener indicator is to track the contextual bias of multiple markets simultaneously on the charts without the need to switch between pairs. This allows traders to monitor various assets in real-time, enhancing decision-making efficiency and identifying potential trading opportunities more effectively. ----- How does this indicator identify the overall market bias? This indicator employs a systematic top-down approach, analyzing market structure, fractal blocks, and their mitigations from the 12M timeframe down to the 1D timeframe to uncover the story behind the market. This method helps identify the overall market bias, whether it’s bullish, bearish, or in consolidating conditions. Below is a flowchart that illustrates the calculation behind the market context identification, demonstrating the systematic approach: ----- According to the above trade plan, why do we only look for mitigations within Fractal Blocks of X1/X2? In this context, "X" stands for a break in the market's structure, and the numbers (1 and 2) indicate the sequence of these breaks within the same trend direction, either up or down. We focus on mitigations within Fractal Blocks during the X1/X2 stages because these points mark the early phase (X1) and the continuation (X2) of a trend. By doing so, we align our trades with the market's main direction and avoid getting stopped out in the middle of trends. ----- How does this indicator identify ranges in a mechanical way? Since the indicator is part of the Optirange suite , it follows the exact rules that Optirange utilizes to identify breaks of market structures in a mechanical manner. Let’s take a closer look at how the ranges are calculated: 1- First, we need to understand the importance of following a set of mechanical rules in identifying market structure: The image above illustrates the difference between a subjective and a mechanical approach to analyzing market structure. The subjective method often leads to uncertainty, where traders might struggle to pinpoint exact breaks in structure, resulting in inconsistent decision-making. Questions like “Is this a break?” or “Maybe this one...?” reflect the ambiguity of manual interpretation, which can cause confusion and errors in trading. On the other hand, the mechanical approach depicted on the right side of the image follows a clear, rule-based method to define breaks in market structure. This systematic approach eliminates guesswork by providing precise criteria for identifying structural changes, such as marking structural invalidation levels where market bias shifts from bullish to bearish or vice versa. The mechanical method not only offers consistency but also integrates statistical probabilities , enhancing the trader's ability to make data-driven decisions. By adhering to these mechanical rules, the Screener indicator ensures that ranges are identified consistently, allowing traders to rely on objective analysis rather than subjective interpretation . This approach is crucial for accurately defining market structures and making informed trading decisions. 2- Now let's take a look at a practical example of how the indicator utilizes Pivot points with a period of 2 to identify ranges: In this image, we see a Bearish Scenario on the left and a Bullish Scenario on the right. The indicator starts by identifying the first significant swing on the chart. It then validates this swing by checking if there is a preceding swing high (for a bearish scenario) or swing low (for a bullish scenario). Once validated, the indicator confirms a break of structure when price closes below or above these points, respectively. For instance, in the Bearish Scenario: The first significant swing is identified. The script checks for a preceding swing high before confirming any structural break. A candle closure below the swing low confirms the first bearish break of structure. This results in a confirmed market bias towards bearishness, with structural liquidity levels indicated for potential price targets. In the Bullish Scenario: The process is mirrored, identifying the first swing low and validating it with a preceding swing low. A closure above this swing confirms the bullish break of structure. This leads to a market bias towards bullishness, with invalidation levels to watch if the trend shifts. This practical example demonstrates how the indicator systematically identifies market ranges, ensuring that traders can make informed decisions based on clear, rule-based criteria. ----- How does this indicator identify ranges in a mechanical way, What are the underlying calculations? Fractal blocks refer to the most extreme swing candle within the latest break. They can serve as significant levels for price rejection and may guide movements toward the next break, often in confluence with topdown analysis for added confirmation. ----- What are mitigations, What are the underlying calculations? Mitigations refer to specific price action occurrences identified by the script: 1- When the price reaches the most recent fractal block and confirms a swing candle, the script automatically draws a line from the swing to the fractal block bar and labels it with a checkmark. 2- If the price wicks through the invalidation level and then retraces back to the fractal block while forming a swing candle, the script labels this as a double mitigation on the chart. This level will serve as the next potential invalidation level if a break occurs in the same direction. ----- What does the right table display? The table located at the right of your chart displays five colored symbols that represent the contextual market bias: Green: The market is in a bullish condition. Red: The market is in a bearish condition. White: The market condition is uncertain, and it is advisable to stay away from trading. ----- What does the bottom table display? The bottom table can be turned on in the Optirange indicator and serves multiple purposes: Range Counts and Mitigations: It shows the range counts and their mitigations across multiple timeframes, providing a comprehensive view of market dynamics. Hourly Timeframe Probabilities: The bottom row of the bias table displays the probabilities for various hourly timeframes, helping to identify potential entry levels based on the multi-timeframe bias determined by the Screener. In a bullish market context, you should look for long positions by focusing on hourly timeframes where buy-side probability exceeds 50%. In a bearish market context, you should look for short positions by focusing on hourly timeframes where the sell-side probability exceeds 50%. When the symbol is white within the Screener table, it signals that the market bias is unclear, and it's recommended to stay away from trading in such conditions. ----- How the range probabilities are calculated? Each break of market structure, denoted as X, is assigned a unique ID, starting from X1 for the first break, X2 for the second, and so on. The probabilities are calculated based on breaks holding, meaning price closing through the liquidity level, rather than invalidation. This probability is then divided by the total count of similar numeric breaks. For example, if 75 out of 100 bullish X1s become X2, then the probability of X1 becoming X2 on your charts will be displayed as 75% in the following format: ⬆ 75% ----- What does the top table display? The top table on the charts displays the current market context, offering insights into the underlying bias. It highlights the high-timeframe (HTF) bias and guides you on which timeframes you should use to enter long or short positions, based on the probability of success. Additionally, when the market bias is unclear, the table clearly signals that it's best to avoid trading that specific market until the context or market story becomes clearer. This helps traders make informed decisions and avoid uncertain market conditions. ----- How does the Screener indicator identify the market bias/context/story ? - Market Structure: The Optirange indicator analyzes market structure across multiple timeframes, from a top-down perspective, including 12M, 6M, 3M, 1M, 2W, 1W, 3D, and 1D. - Fractal Blocks: Once the market structure or current range is identified, the indicator automatically identifies the last push before the break and draws it as a box. These zones acts as a key area where the price often rejects from. - Mitigations: After identifying the Fractal Block, the indicator checks for price mitigation or rejection within this zone. If mitigation occurs, meaning the price has reacted or rejected from the Fractal Block, the indicator draws a checkmark from the deepest candle within the Fractal Block to the initial candle that has created the zone. - Bias Table: After identifying the three key elements—market structure, Fractal Blocks, and price mitigations—the indicator compiles this information into a multi-timeframe table. This table provides a comprehensive top-down perspective, showing what is happening from a structural standpoint across all timeframes. The Bias Table presents raw data, including identified Fractal Blocks and mitigations, to help traders understand the overall market trend. This data is crucial for the screener, which uses it to determine the current market bias based on a top-down analysis. - Screener: Once all higher timeframes (HTF) and lower timeframes (LTF) are calculated using the indicator, it follows the exact rules outlined in the flowchart to determine the market bias. This systematic approach not only helps identify the current market trend but also suggests the exact timeframes to use for finding entry, particularly on hourly timeframes. Example: 12M Timeframe: OANDA:EURUSD 6M Timeframe : OANDA:EURUSD 3M Timeframe : OANDA:EURUSD 1M Timeframe : OANDA:EURUSD 2W Timeframe : OANDA:EURUSD 1W Timeframe : OANDA:EURUSD ----- User-input settings and customizations Terms and Conditions | Disclaimer Our charting tools are provided for informational and educational purposes only and should not be construed as financial, investment, or trading advice. They are not intended to forecast market movements or offer specific recommendations. Users should understand that past performance does not guarantee future results and should not base financial decisions solely on historical data. By utilizing our charting tools, the buyer acknowledges that neither the seller nor the creator assumes responsibility for decisions made using the information provided. The buyer assumes full responsibility and liability for any actions taken and their consequences, including potential financial losses. Therefore, by purchasing these charting tools, the customer acknowledges that neither the seller nor the creator is liable for any unfavorable outcomes resulting from the development, sale, or use of the products. The buyer is responsible for canceling their subscription if they no longer wish to continue at the full retail price. Our policy does not include reimbursement, refunds, or chargebacks once the Terms and Conditions are accepted before purchase. By continuing to use our charting tools, the user acknowledges and accepts the Terms and Conditions outlined in this legal disclaimer.
Pine Script™ indicator
by Fractalyst
G.O.A.T. Scalper Diagnostics v1OVERVIEW: The G.O.A.T. Scalper Diagnostics indicator system enables users to discover unorthodox indicator patterns, reading price charts in unusual ways, thus gaining an edge over the majority of market participants they trade against. CONCEPTS: Th G.O.A.T. Scalper Diagnostics is a system that aims to satisfy the fundamental condition for successful online trading - providing an edge. It's a battle between advantages. To take other people's money, successful traders must have an advantage over everybody else. To hope for consistent success in trading, you need to do things differently and see what almost nobody else sees. Of course then you must act on it, and that's where the G.O.A.T. Scalper Diagnostic's mandate ends. I believe the vast majority of indicators out there show you what everybody else sees. I've always been an indicator guy, I respect and cherish most indicators and I know a good indicator when I see it. However, although most indicators are great works of art, their practicality is in most cases doubtful. Presenting great information is one thing, but providing an edge over the people you trade against is something different. What Everybody Else Sees The G.O.A.T. Scalper Diagnostics is based on indicators most of you have probably heard of and used: Moving Averages (particularly the Kaufman Moving Average, among others) ADX and DI Bollinger Bands Stochastic (particularly the Stochastic RSI) Most traders should be well familiar with these classic indicators, they've provided the basis for online indicator trading for decades. But it's also true that due to how popular online trading has become all over the world, one is more and more unable to use these indicators successfully on lower timeframes. Usually, more noteworthy success is achieved by going up in scale and discovering the timeframe where a particular indicator produces no false signals. Often times these timeframes range from bi-weekly to multi-month scale. In other words, consistently successful low timeframe trading and scalp trading in particular are now almost impossible using indicators. Traders that dominate the scalping arena are big professional/institutional groups of traders, who have systematic access to the order books of most exchanges. This can be achieved one way or another, but not by individuals, small groups without significant capital or simply traders who lack political/social power and influence in the trading field. In other words - giant order book traders have an edge over everybody else, who use indicators to trade on lower timeframes. Through a series of interventions into these classical indicators, the G.O.A.T. System brings them back into the lower timeframe competitive game. Most original formulas are preserved, but these immortal classics are applied in ways popular TA would consider unorthodox. Ingenious Indicators Built by Creators The G.O.A.T. Scalper Diagnostics relies on the fundamental work of others. The System is developed on the basis of: Quadratic Kernel Regression - it uses the publicly published library of Justin Dehorty: www.tradingview.com PMARP - Price Moving Average Ratio & Percentile, publicly published by "The_Caretaker": www.tradingview.com These Creators deserve full credit for their fundamental work and are endorsed by the G.O.A.T. Scalper Diagnostics project. And yet... ingenious and inspired as these tools are, in my humble opinion the general public is presented with a rather unproductive way to apply them. In my own view, these wonderful tools built by JDehorty and The_Caretaker have a massive potential should they be applied and wielded in a different direction. So I tried to bring my vision about them into flesh with the G.O.A.T. Diagnostics. What the G.O.A.T. Scalper Diagnostics Is and How to Use It It's a System for new pattern discovery, bringing the disciplines of pattern and indicator trading together. By using it as a stand-alone, or mixing it with other great indicators, one is able to discover new indicator patterns. Patterns can be compared, matched together and categorized. By applying statistics to differentiated historical pattern groups, we're able to derive their meaning. Thus, the trader is able to research their own "alphabet" to read the price charts. After categorizing and differentiating pattern groups with statistically predominant meaning, the trader is then able to read into longer scenarios - price set-ups that are harder to detect due to them being stretched in time or misshapen according to the particular situation. The G.O.A.T. Scalper leverages and encourages group trading, as different traders will probably discover different price "alphabets" for themselves, potentially giving rise to a social economy of sharing and combining "trading languages" based on indicator patterns people have discovered via the G.O.A.T. Diagnostics. Support/Resistance Trading The G.O.A.T. Scalper has its own way of deriving Support/Resistance. Unlike most existing S/R indicators, The Scalper derives Support/Resistance not by measuring price highs, lows and closes, but solely by using momentum and trend strength. This seems like a much more versatile way to plot S/R during scalping on low timeframes where time is of essence and the trader's view is too narrow to have macro S/R levels in constant consideration. The Scalper's way to derive S/R in real time and on the go, while staying very relative to important higher timeframe S/R zones, makes it much more desirable than any other S/R indicator I've thus far encountered. All S/R functionality is derived from the classical ADX and DI indicator. To do this, I use the ADX and DI in an unpopular way. To generate the actual plot of S/R levels I also modify the indicator's code, not by removing functional parts from it, but adding more to it in order to filter the signals it produces. I can metaphorically describe its action in the following way: Imagine you're Price action itself; You're walking through a labyrinth or corridors. You're walking through one straight corridor, and it has a crossing with another corridor ahead; Very strong wind is blowing along that other corridor. You can't see the wind, but when you reach it and try to move past it, the force of the wind resists your moving ahead and instead pushes you sideways. At this point, the G.O.A.T. Diagnostics already knows this can only be one thing - resistance. Orthodox TA and trading demand retests. In my opinion, this deeply rooted tradition wastes time proving the obvious, then wastes time again double-proving the validity of recent past, while scalping opportunities go to waste. Modern successful traders are way ahead of the popular strategy of testing and retesting S/R that almost every trader uses. So-called "Stops hunting" is just one expression of this situation, where wide adoption of the S/R retesting strategy actually lures unsuccessful traders into the schemes of the successful few. In my own way of trading, I use the G.O.A.T. Diagnostics to take action on Support/Resistance as it's plotted in real time. But probably my biggest heresy into the DI is my opinion, that the crossings of the +DI and -DI are useless and should actually be discarded. My research shows that the DIs often show indications of being "oversold", but don't seem to exhibit an "overbought" state. Statistically, I've had much more success basing my TA on that, rather than cross-ups and cross-downs of the DI plot lines. Therefore I discarded these crossings by presenting the DI part of the ADX and DI as a Heatmap channel rather than crossing lines. To further enhance the ability of the System to provide S/R analysis, I plot this Heatmap onto an adjustable price offset plots (a percentage above and below current price). In modern times, the vast majority of trading is done by automatic machines and algorithms. To give a specific example, one can easily notice, that a 5% offset of the BTC 1h price plot leads to remarkably accurate S/R charting. Following the rule to chart a S/R line connecting highs and lows on the 5% price offset often successfully "foresees" valid S/R zones before price ever visits them. Or, the levels were visited so far back in the timeframe's history that orthodox understanding considers them "invalidated" or washed away in the noise of the relevant volume profile. My explanation for this is simple - I think Grid bots now dominate automatic trading across the majority of exchanges. In my understanding, by adjusting the percentage offset of current price action I can often discover relevant conglomerations of dominating Grid bot cell parameters and anticipate price reaction. By plotting the DI heatmap on these price action offsets I can use the indicator for my trading decisions. Heatmaps Every heatmap produces different series of data. They're not the same. Bollinger Band heatmap depicts the percentile distance between the Band's extremes. The price candles heatmap, and the KAMA moving average heatmap, depict the percentile distance between price and the KAMA. So, it's the same thing. However, the percentile of that distance is calculated in two different ways, hence the difference in color in every particular moment. This color discrepancy aims to visualize the "strain" between price action and KAMA, like a soft and hard "springs" that go in unison with each other in sustainable moves, and in dissonance with each other during unsustainable moves. Price offset heatmap depicts the percentile average of the +DI (above price) and the -DI (below price). A Hot temperature above price and a Cold temperature below price would mean a strong bullish sentiment, and vise versa, while Green would mean neutrality in sentiment. There are important interplays between different heatmaps. For example, although representing totally different things, a Teal price bar would almost always (according to historical statistics) foreshadow a change in DI's heatmap sentiment. That's just one avenue of correlation between S/R analysis and sentiment analysis using the G.O.A.T. Diagnostics. Oscillator Chart In terms of applying Quadratic Kernel Regression, I endorse the natural principle that no center can exist without a periphery, and no periphery can exist without a center. Therefore I try to pay attention not only to the average of the regression's values, but also to the cloud of data points itself. Following this understanding, I attempt to depict the natural cycles of price converging/diverging towards/from its regression average. To do this, I apply the classic Stochastic formula. Thus, the Oscillator part of the System depicts the following: Thin heatmap line displays the cycles of price converging with its quadratic kernel regression average (moving down), and diverging with its regression average (moving up). Its heatmap depicts the percentile of this oscillation. The wider heatmap line displays the KAMA's cycles of convergence/divergence with its own quadratic kernel regression average. The reason for this is again creating discrepancy - while KAMA is based on price action, its regression data values differ from those of price action's regression. This discrepancy produces useful historic patterns that can be studied statistically. The thin and wide purple oscillator lines depict the change of slope of price action regression average and KAMA regression average, respectively. Very often change of slope is not detectable with the naked eye, but clearly indicated by the oscillators. By combining all these elements into a single analysis, a trader can detect hidden trends that are yet to become visible for the rest of market participants. For example, convergence of price with its quadratic kernel regression average while the slope of the average deteriorates down in most cases (according to statistics) means a sideways consolidation in a downtrend before downtrend continuation. Conversely, deviation of price action from its regression average while the regression average slope deteriorates down usually marks the very beginning of a downtrend. Bollinger Bands Bollinger Bands are not modified, but are based on quadratic kernel regression values. Thus, if Bollinger Bands themselves are indicative of volatility, then based on kernel regression values, they should indicate the volatility of change of values in the regression's window. Again, applying it to both the price and KAMA regression data series, a discrepancy is highlighted that leads to useful historical patterns subject to analysis and categorization. SOME EXAMPLES Support / Resistance Support/Resistance levels are market by White Triangles with dotted lines plotted from them, in real time. The indicator plots Ghost Triangles in anticipation of Support/Resistance, preparing the trader for the eventual confirmation of a zone of interest and signaling price is feeling Support or Resistance pressure. Dialing the length of the S/R lines to 25 makes the indicator more useful. Dialing the setting to 500 clearly shows macro S/R zones by conglomerating and bundling individual lines. The thicker the bundling and the confluence of lines, the more significant the zone. Thus lower timeframe scalping and trading is made more easy, without the need to do nearly as much manual S/R charting. Support/Resistance analysis and plotting is entirely based on a modified ADX. Heatmap Sustainable moves are generally marked by Green price color and calm KAMA colors. Unsustainable moves are usually marked by more extreme colors of price bars and KAMA. Red usually means price is unsustainably distanced from the KAMA, while deep Blue usually means price is undesirably close to the KAMA, foreshadowing a directional distancing. Usually Teal color of price bars and KAMA foreshadow a change of sentiment of the outside Heatmap sentiment channel. Red color of the outside channel always signals the direction of the desired sentimental movement, while Blue signals the extent at which the counter-element suffers. Thus, one side being Green, while the other is Blue, often means the Blue will soon evolve into a warmer color, attracting price in that direction. Outside Heatmap channel is entirely based on a modified DI. Oscillator Chart An example of Chart Diagnosis using the Oscillator and other elements of the G.O.A.T. Scalper: First (far left), a Resistance is plotted. This coincides with price bars being Red (distressed state). The thin colorful Oscillator line takes an Up-turn, signifying a period of price moving away from its Quadratic Kernel Regression (pink moving average). After Price cools down to Green sustainable colors, a Support is plotted. During this time, the thin colorful line is falling down, signifying a period when the distance between price action and its quadratic kernel regression average is decreasing. During this phase, the thin purple Oscillator line goes up. This signifies the slope of the price regression is restoring to the upside. Next, the thin colorful line starts going up again, signifying another period of price getting further away from its regression average. This time to the upside. Resistance is being broken and new support is established. At this point, the thin colorful line starts falling again, signifying distance between price and its regression MA is shortening. This is clearly visible as a sideways consolidation (with a slight tilt up of slope). A moment comes when all lines - the price and KAMA lines, and price and KAMA regression slopes, all point down. A new down period is clearly starting. This is further indicated by Teal price bars and new Resistance forming. Notice how the external heatmap channel goes into more balanced Green colors with trend enthusiasm calming down. This analysis may appear to be overwhelming and confusing at first, as these metrics are unorthodox and unpopular. But different aspects of the indicator can be toggled ON/OFF to single them out, which makes observations much simpler for new users. After some time spent discovering personal patterns, or reviewing other users' catalogues with already published pattern libraries, it soon becomes easy to read charts in this new way. Bollinger Bands Bollinger Bands provide another way to produce patterns that give users specific chart information. One noteworthy indication is when the price and KAMA Bollinger Bands separate their value zones. Since the zones of these Bands are based on the kernel regression values of the respective sources, their separation is significant and too often means violent reversals or violent continuations (which usually can be judged using the other metrics the System provides, or additional indicators of choice). Another noteworthy Bollinger Band pattern is when price action leaves a prolonged trending move. First phase of the end of a prolonged trending move is the BB zones expanding and doing a significant overlap. Second stage is price getting reaccepted in the Price BB. This however doesn't mean reacceptance in the KAMA BB and if the moment isn't right, usually leads to bounces and continuations. The KAMA needs to "make space" for price to get reaccepted into the KAMA BB. While the KAMA is outside its BB or very near to its wall, price reacceptance into it is not very probable. When KAMA withdraws from its BB wall, opening an "entrance on its membrane", that's when price is eligible to get reaccepted into the KAMA BB. That's usually the moment the long awaited consolidation starts and a long trending move is over. Users of the G.O.A.T. Scalper Diagnostics can discover many more patterns and correlations between patterns within the System. But the System itself can multiply all possible patterns when inspected in the context of additional indicators, leading to vast possibilities of signal and pattern discovery with huge potential. A very good idea would probably be to use the G.O.A.T. Diagnostics together with the Ichimoku. Ichimoku has always been famous for its genius simplicity and elegant profoundness, but notorious for its total lack of accuracy, as well as general uselessness on lower timeframes. The G.O.A.T. System has the potential to enhance all of Ichimoku's strengths and cure its weaknesses. Yet another good idea may be to pair it with kindred indicators, like the Gaussian Channel, which has a stunning performance, but suffers from too high level of generalization. The Diagnostics can provide the intricate texture of price manoeuvres the Gaussian Channel fails to register, while the GC can give the Scalper even more solid context for its patterns. The worthwhile possibilities seem endless... Entry Table I've added a little Entry Table at the bottom right corner. It's designed to potentially help scalpers trade faster, and to visualize a potential trade they're thinking about before they execute it. A Stop Loss is visually plotted in real time to better visualize it's placement in the chart context. It encourages responsible risk management in its settings: The user enters the amount of their trading portfolio; Then specify the percentage of their portfolio they're willing to risk at every trade; After that the user can chose to specify a flat percentage Stop Loss. The table will calculate the size of the entry of a market order, so the user only risks the specified percentage of their portfolio should the specified Stop Loss level is hit. There's also the option to use automatically suggested Stop Loss, based on recent volatility. The actual Stop Loss is calculated 20% away from the actual volatility level, to better protect from unforeseen wicks. In the current example, the user with a $1000 trading portfolio has to do a $1000 entry to lose 1% of their portfolio ($10) at a 1% Stop Loss. But the user has to do a $2,525 entry in order to lose 1% of their portfolio (%10) at a much closer Stop Loss which is less than 1%, based on recent volatility. The Entry Table should be considered as a cosmetic convenience and not a dedicated risk management tool. CONCLUSION: The G.O.A.T. Scalper Diagnostics is an indicator System, based on popular, but modified and tweaked versions of indicators like the ADX and DI, Stochastic, Bollinger Bands and MAs. It also leverages the remarkable work of inspired creators: JDehorty's Quadratic Kernel Regression library, and The_Caretaker's PMARP . The G.O.A.T. Scalper Diagnostics indicator system enables users to discover so-called new "indicator-pattern alphabets", reading price charts in new and unorthodox ways, thus gaining an edge over the majority of market participants they trade against. The high degree of freedom when discovering new patterns, either within the System itself or correlating its output to external auxiliary indicators, highlights the System's potential for original discoveries leading to highly personalized trading strategies. Exchanging information about personal pattern libraries can potentially also give birth to new private trading communities.
Pine Script™ indicator
by Xaumana
1
VWAP SlopePublishing one of the simplest yet one of my favorite concepts. Had to publish since I didn't really find any script for this on TV. VWAP slope. This is nothing fancy because it's just calculating "slope" with a very basic level formula vwap_slope = (vwap - vwap ) / length Above zero line, it's positive zone. Below zero line, it's a negative zone. The idea is to avoid choppy conditions and stay true to larger readings, sometimes when we have vwap directly on chart and when price interacts with it, we tend to take the lot of bad trades. The intention here is to avoid just that. This is also good at tracking failure of change in sentiments, this failure is very important, because one's failure occurs there is significant movement in the opposite direction of the failure. Since there isn't much alteration to this idea, there is not much to talk about tbh. Just remember, this is an educational idea and not assurance of future performance. Regards.
Pine Script™ indicator
by Pratik_4Clover
Landry Light with Moving AverageLandry Light with Moving Average Overview: This Pine Script, titled "Landry Light with Moving Average", visualizes the relationship between price action and a chosen moving average (MA) over time. It helps users easily identify periods where the price stays consistently above or below the moving average, which can be a useful indicator of bullish or bearish trends. Key Features: Moving Average Type Selection: The script allows users to choose between two types of moving averages: Exponential Moving Average (EMA) Simple Moving Average (SMA) This is done via a user input option, enabling traders to tailor the indicator to their preferred analysis method. Moving Average Length: Users can set the length of the moving average (default is 21 periods). This allows customization based on the trader's time frame, whether short-term or long-term analysis. Dynamic Moving Average Color: The moving average line changes color based on the relationship between the price and the MA: Green: Price is consistently above the MA (bullish condition). Red: Price is consistently below the MA (bearish condition). Blue: Price is crossing or close to the MA (neutral or indecisive condition). Cumulative Days Above/Below MA: The script tracks and displays the number of consecutive days the price remains above or below the moving average: Cumulative Days Above: Shown as a green histogram above the zero line. Cumulative Days Below: Shown as a red histogram below the zero line. This feature helps users identify sustained trends or potential reversals. Real-time Labels: The script generates dynamic labels that display the count of cumulative days the price has stayed above or below the moving average. These labels are positioned near the moving average on the chart, providing an easy reference for traders. How Users Can Benefit: Trend Identification: By visually representing how long the price stays above or below a key moving average, traders can identify strong bullish or bearish trends. This can inform entry and exit points. Visualizing Market Sentiment: The colored moving average line and histogram help traders quickly assess market sentiment. A prolonged green MA line suggests a strong uptrend, while a prolonged red line indicates a downtrend. Adaptability: With customizable moving average types and lengths, the indicator can be tailored to fit various trading strategies, whether for day trading, swing trading, or long-term investing. Reversal Signals: A shift from cumulative days above to cumulative days below (or vice versa) can serve as an early signal of a potential market reversal, allowing traders to adjust their positions accordingly. Simplified Decision-Making: The combination of visual cues (colors, histograms, and labels) simplifies decision-making, allowing traders to focus on trend strength rather than complex calculations. Usage: To use this script: Add the Indicator to Your Chart: Select the desired moving average type and length. The script will plot the moving average, colored by the trend, and display cumulative days above or below it. Interpret the Signals: Use the histogram and labels to gauge the strength of the trend. Monitor color changes in the moving average for potential trend reversals. Incorporate into Your Strategy: Combine this indicator with other tools (e.g., volume analysis, RSI) to confirm signals and refine your trading strategy. This indicator is particularly useful for traders who follow the "Landry Light" concept, emphasizing the importance of price staying above or below a moving average to determine trend strength.
Pine Script™ indicator
by starshiptrade
Intraday Stop Loss Calculator[fitfatq]Indicator Overview Intraday Stop Loss Calculator is a practical tool designed for day traders. This indicator helps traders instantly calculate the loss percentage based on the high or low of the current K-bar relative to the entry price. It also displays the stop-loss risk based on the day's high or low. You can select either long or short mode, allowing the indicator to calculate the appropriate data according to your trading strategy. Features Current K-bar Stop Loss: Calculates and displays the loss percentage based on the high or low of the current K-bar, making it ideal for short-term trading decisions. Day Stop Loss: Calculates and displays the loss percentage based on the day's high (for short positions) or low (for long positions), helping you better manage risk by understanding the distance between the current price and key levels. Adjustable Options Minute Period: Users can select the minute period for the indicator, with a default of 5 minutes. Position Type: Choose between "Long" or "Short," and the indicator will automatically calculate the relevant stop-loss data based on your selection. Show Day Stop Loss: Users can choose whether to display the stop-loss percentage based on the day's high or low. The default is enabled. Usage Instructions Load the indicator, set the minute period, and choose the long or short mode. Depending on your trading strategy, decide whether to display the day's stop-loss percentage. When switching symbols, if the current K-bar has no movement, the indicator may temporarily not display information. This is normal behavior. Please wait for the next K-bar or manually refresh. Basic Logic The indicator calculates and displays the loss percentage based on the high or low of the current K-bar and the day's high or low, helping traders understand potential stop-loss risks in real-time. Users can adjust parameters such as color and transparency to ensure the indicator displays clearly and meets their expectations. Notes When switching symbols, if the K-bar has no movement, the indicator may not immediately update. This is due to Pine Script requiring data changes to trigger calculations. This indicator is ideal for users who frequently engage in day trading, helping you better manage risk and make timely decisions. Additionally, please note that in the Chinese version of TradingView, the long/short options might be translated as "Short-term" and "Long-term," but this does not affect the functionality of the indicator.
Pine Script™ indicator
by fitfatq
lib_no_delayLibrary "lib_no_delay" This library contains modifications to standard functions that return na before reaching the bar of their 'length' parameter. That is because they do not compromise speed at current time for correct results in the past. This is good for live trading in short timeframes but killing applications on Monthly / Weekly timeframes if instruments, like in crypto, do not have extensive history (why would you even trade the monthly on a meme coin ... not my decision). Also, some functions rely on source (value at previous bar), which is not available on bar 1 and therefore cascading to a na value up to the last bar ... which in turn leads to a non displaying indicator and waste of time debugging this) Anyway ... there you go, let me know if I should add more functions. sma(source, length)   Parameters:      source (float) : Series of values to process.      length (simple int) : Number of bars (length).   Returns: Simple moving average of source for length bars back. ema(source, length)   Parameters:      source (float) : Series of values to process.      length (simple int) : Number of bars (length).   Returns: (float) The exponentially weighted moving average of the source. rma(source, length)   Parameters:      source (float) : Series of values to process.      length (simple int) : Number of bars (length).   Returns: Exponential moving average of source with alpha = 1 / length. atr(length)   Function atr (average true range) returns the RMA of true range. True range is max(high - low, abs(high - close ), abs(low - close )). This adapted version extends ta.atr to start without delay at first bar and deliver usable data instead of na by averaging ta.tr(true) via manual SMA.   Parameters:      length (simple int) : Number of bars back (length).   Returns: Average true range. rsi(source, length)   Relative strength index. It is calculated using the ta.rma() of upward and downward changes of source over the last length bars. This adapted version extends ta.rsi to start without delay at first bar and deliver usable data instead of na.   Parameters:      source (float) : Series of values to process.      length (simple int) : Number of bars back (length).   Returns: Relative Strength Index.
Pine Script™ library
by robbatt
DataDoodles ATR RangeThe "DataDoodles ATR Range" indicator provides a comprehensive visual representation of the Average True Range (ATR) levels based on the previous bar's close price . It includes both the raw ATR and an Exponential Moving Average (EMA) of the ATR to offer a smoother view of the range volatility. This indicator is ideal for traders who want to quickly assess potential price movements relative to recent volatility. Key Features: ATR Levels Above and Below Close: The indicator calculates and displays three levels of ATR-based ranges above and below the previous close price. These levels are visualized on the chart using distinct colors: - 1ATR Above/Below - 2ATR Above/Below - 3ATR Above/Below EMA of ATR Includes the EMA of ATR to provide a smoother trend of the ATR values, helping traders identify long-term volatility trends. Color-Coded Ranges: The plotted ranges are color-coded for easy identification, with warm gradient tones applied to the corresponding data table for quick reference. Customizable Table: A data table is displayed at the bottom right corner of the chart, providing real-time values for ATR, EMA ATR, and the various ATR ranges. Usage This indicator is useful for traders who rely on volatility analysis to set stop losses, take profit levels, or simply understand the current market conditions. By visualizing ATR ranges directly on the chart, traders can better anticipate potential price movements and adjust their strategies accordingly. Customization ATR Length: The default ATR length is set to 14 but can be customized to fit your trading strategy. Table Positioning: The data table is placed in the bottom right corner by default but can be moved as needed. How to Use Add the "DataDoodles ATR Range" indicator to your chart. Observe the plotted lines for potential support and resistance levels based on recent volatility. Use the data table for quick reference to ATR values and range levels. Disclaimer: This indicator is a tool for analysis and should be used in conjunction with other indicators and analysis methods. Always practice proper risk management and consider market conditions before making trading decisions.
Pine Script™ indicator
by armthanathat
Z-Score AggregatorOverview: This indicator is designed to take multiple other indicators as inputs, calculate their respective Z-scores, and then aggregate these Z-scores to provide a comprehensive measure. By transforming the inputs into Z-scores, this indicator standardizes the data, enabling a more accurate comparison across different indicators, each of which may have different scales and distributions. This indicator is beneficial for Mean-Reversion style trading and investing as it standardizes indicators and lets them work together in one system. The Z-score, which represents how many standard deviations an element is from the mean, is a crucial statistical tool in this process. It allows the indicator to normalize the varying data points, ensuring that each indicator's contribution to the aggregate score is proportional to its deviation from the average performance. Inputs: Z-score length: How far Back it will take into account the inputs Number Of Sources: This is to set the number of inputs the indicator uses so it calculates them properly and uses only the number of indicators you want. Source Inputs: 1-10 inputs (no need to use them all as long as you set the number of used indicators beforehand). Note: There are three indicators used in this example which are CCI, RSI and Sharpe Ratio. The indicator calculates their individual Z-scores and takes an average. Because Number Of Sources is set to 3 it only uses the first 3 indicators in use.
Pine Script™ indicator
by arieleliahu453
Cash Cycle BandCash cycle band shows the number of days and the profit margin compared to the previous period (it does not indicate how profitable the company is, but how well it is managed). Cash cycle band consists of 6 sections: 1. DPO is the days payables outstanding in the "red" followed by O/D which is overdraft or short-term debt (if any) . 2. DIO is the days inventory outstanding in the "green" followed by classified inventory (if any) consists of finished goods. work in process and raw materials. 3. DSO is days sales outstanding in "blue". 4. DWC is days converting working capital to revenue in "orange". 5. CCC is days converting inventory and resources to cash flow in "yellow". 6. GPM is gross profit margin and OPM is operating profit margin. The "😱" emoji indicates a value if it increases by more than or decreases by less than 20%, e.g. - DPO, finished goods, work in process, raw materials, GPM, OPM is decreasing. - O/D, DIO, DSO, DWC, CCC is increasing. The "🔥" emoji indicates a value if it increases by more than or decreases, e.g. - DPO, finished goods, work in process, raw materials, GPM, OPM is increasing. - O/D, DIO, DSO, DWC, CCC is decreasing. The order of the list depends on the day of each item, the more days more high.
Pine Script™ indicator
by rochano
Yield Curve InversionThe Yield Curve Inversion indicator is a tool designed to help traders and analysts visualize and interpret the dynamics between the US 10-year and 2-year Treasury yields. This indicator is particularly useful for identifying yield curve inversions, often seen as a precursor to economic recessions. Features and Interpretations Display Modes: Choose between "Spread Mode" to visualize the yield spread indicating normal (green) or inverted (red) curves, or "Both Yields Mode" to view both yields. Yield Spread: A plotted difference between 10-year and 2-year yields, with a zero line marking inversion. A negative spread suggests potential economic downturns. Color Coding: Green for a normal yield curve (10Y > 2Y) and red for an inverted curve (2Y > 10Y). Legend: Provides quick reference to yield curve states for easier interpretation. This indicator is for educational and informational purposes only. It should not be considered financial advice or a recommendation to buy or sell any financial instruments. Users should conduct their own research and consult with a financial advisor before making investment decisions. The creator of this indicator is not responsible for any financial losses incurred through its use.
Pine Script™ indicator
by Julien_Eche
SP500 RatiosThe "SP500 Ratios" indicator is a powerful tool developed for the TradingView platform, allowing users to access a variety of financial ratios and inflation-adjusted data related to the S&P 500 index. This indicator integrates with Nasdaq Data Link (formerly known as Quandl) to retrieve historical data, providing a comprehensive overview of key financial metrics associated with the S&P 500. Key Features Price to Sales Ratio: Quarterly ratio of price to sales (revenue) for the S&P 500. Dividend Yield: Monthly dividend yield based on 12-month dividend per share. Price Earnings Ratio (PE Ratio): Monthly price-to-earnings ratio based on trailing twelve-month reported earnings. CAPE Ratio (Shiller PE Ratio): Monthly cyclically adjusted PE ratio, based on average inflation-adjusted earnings over the past ten years. Earnings Yield: Monthly earnings yield, the inverse of the PE ratio. Price to Book Ratio: Quarterly ratio of price to book value. Inflation Adjusted S&P 500: Monthly S&P 500 level adjusted for inflation. Revenue Per Share: Quarterly trailing twelve-month sales per share, not adjusted for inflation. Earnings Per Share: Monthly real earnings per share, adjusted for inflation. User Configuration The indicator offers flexibility through user-configurable options. You can choose to display or hide each metric according to your analysis needs. Users can also adjust the line width for better visibility on the chart. Visualization The selected data is plotted on the chart with distinct colors for each metric, facilitating visual analysis. A dynamic legend table is also generated in the top-right corner of the chart, listing the currently displayed metrics with their associated colors. This indicator is ideal for traders and analysts seeking detailed insights into the financial performance and valuations of the S&P 500, while benefiting from the customization flexibility offered by TradingView.
Pine Script™ indicator
by Julien_Eche
1
Mxwll OptAlgoIntroducing the Mxwll OptAlgo Mxwll OptAlgo is a sophisticated algorithmic trading tool designed to identify potential long and short signals. It leverages an optimized combination of the M-Swift average, M-Smooth average, and M-RSI to fine-tune custom lengths and improve signal accuracy. The Mxwll OptAlgo provides long and short signals across various trading assets and timeframes. Additionally, it features optimized Take Profit (TP) and Stop Loss (SL) settings to help traders manage risk. Key Features Step-by-Step Complete Optimization: A systematic approach to optimize trading parameters. Buy/Sell Signals: Clear indicators for long and short positions. Easy to Use: User-friendly interface for seamless trading. Predictive counter trend channels Integrated trend following system and counter trend trading system 3-optimized strategies working cooperatively Alerts and auto trading capabilities How It Works The Mxwll OptAlgo is comprised of three strategies: Trend following using the OptAlgo AI Reversal counter trend trading Market crash shorting Mxwll OptAlgo can be used for market analysis and trading similarly to any moving average. The Mxwll OptAlgo MA is composed of two distinct moving averages to be used for trend following strategies. M-Swift Average: The M-Swift Average accounts for volume and weights current price movement heavier than older price movement - allowing for improved responsiveness to current price movement. Volume is additionally weighted to the average to determine the significance of the price move and the resulting response of the M-Swift average. The M-Swift average consists of an HVWMA with OBV weighting. The HVWMA is used to create a moving average that adapts to volume, attempting to respond to significant price moves with high volume quicker and significant price moves with low volume slower - which might not be indicative of the start of a strong trend. To further reduce the M-Swift average’s responsiveness to weak volume price moves, the average is weighted with a normalized OBV. With this, the M-Swift moving average uses these two indicators to create a responsive moving average to significant price moves with high volume. M-Smooth Average: The M-Smooth average consists of a McGinley average. The McGinley Average is designed to address some of the limitations of traditional moving averages, such as the Simple Moving Average (SMA) or Exponential Moving Average (EMA), by reducing their lag and more accurately reflecting the market's true movements, especially during periods of volatility. The McGinley Dynamic automatically adjusts its smoothing factor based on market speed. This means it responds more quickly to fast-moving markets and slows down during periods of consolidation, reducing the likelihood of false signals. Unlike traditional moving averages that have a fixed period and can lag significantly behind fast-moving prices, the McGinley Dynamic adjusts dynamically, which helps to reduce lag and keeps the moving average closer to the price action. The M-Smooth average uses bar low prices as a series during an uptrend - bar high prices as a series during a downtrend. A cross above the M-Smooth average indicates an uptrend, while a cross below the M-Smooth average indicates a downtrend. When this cross event occurs the M-Smooth average will “flip” from calculating on lows to highs, or highs to lows, contingent on the direction of the trend. The expectation is that a cross event of the M-Smooth average requires a substantial price move and, subsequent to this cross, price will continue to trend in the direction of the cross. OptAlgo: The OptAlgo is simply the average of the M-Swift average and the M-smooth average. By combining the M-Swift average and the M-Smooth average, the final output results in an average that slows during ranging markets and quickly adjusts to high volume breakouts and high volume reversals that initiate a trend. Due to the combination, the average will keep up quickly with a trend but remain at an appropriate distance from the current price - requiring a significant counter trend price move to change the direction of the OptAlgo average. How does the OptAlgo follow trends? The OptAlgo, comprising the two moving averages above, considers a cross event of the OptAlgo as a change in trend indication. The OptAlgo can be thought of as a moving average that significantly deviates from price. For price to cross the OptAlgo, a substantial price move must occur, and this event is treated as a "strong trend" or "new trend" indication. M-RSI: The M-RSI is a fundamental component of the trend following strategy. Prior to a trend following “long” or “short” signal, the M-RSI must generate a signal in confluence with an OptAlgo cross event. When price crosses over the opt algo its color will change to green, indicating an uptrend. A buy signal will generate should the M-RSI provide a similar indication. The M-RSI portion of the trend following strategy is explained below. When price crosses under the opt algo its color will change to green, indicating a downtrend, and a sell signal becomes eligible. The foundational logic for using the Opt Algo as a trend following strategy is to treat crossovers/crossunders of the Opt Algo as strong trend indications, and trade them. Steps to generate a trend following long signal: 1: M-RSI extends into oversold territory 2: Price crosses over the OptAlgo Steps to generate a trend following short signal: 1: M-RSI extends into overbought territory 2: Price crosses under the OptAlgo Our trend following strategy considers crossovers/crossunders at key market turning points as buy/sell opportunities. This strategy integrates the Mxwll RSI and Mxwll OptAlgo MA to determine entry points in anticipation of trend continuation. The Mxwll RSI must move below/above the optimized OB/OS level prior to a cross event for a long/short signal to be considered. Entry points for this strategy are marked as "Long" or "Short". At its core, the OptAlgo trend following strategy tries to enter a trend as close to the origin point as possible. As with any trend following strategy, price may not continue to move in the expected direction following entry, resulting in a losing trade. AI Reversal Predictions Our AI reversals strategy uses AI suggested turning points to capitalize on price reversions back towards the OptAlgo. These levels are considered by the AI on the selected days, and entry points at these levels are marked as "LLO" or "SLO". How AI reversals work Our AI reversals strategy attempts to trade price reversions back toward the Opt Algo. These levels are calculated on specific days of the week, but can be traded any day. The internal algorithm determines which HTF highs/lows are most likely to function as tradable support/resistance levels. For instance, if Friday consists of heavy trading activity and high/low prices are tracked/recorded as causing significant support / resistance when tested in the future, the algorithm will consider support and resistance levels created on Friday as future tradable levels. Additionally, if support/resistance levels created on Wednesday are recorded as weak or unpredictable when traded at in the future, the algorithm will not consider support/resistance levels generated on Thursday as tradable, and will not generate long or shit signals for these levels. In the background, the AI reversals strategy is tracking success rates at multiple support and resistance levels. The best performers, if there are any, will be considered tradable. A “best performer” is calculated as the raw price move up to a threshold (i.e. 0.5%) that occurs subsequent to a test of the level. Crash Short The "Crash Short" strategy prioritizes short positions during retracements of a sell off. A simple yet effective strategy. How Crash Short Works The Crash Short strategy uses a customized momentum indicator (similar to ROC, MOM, etc.) to identify strong downside price moves. When our customized momentum indicator gives strong sell indications, the RSI is then referenced to identify an upside retracement. When the RSI exceeds a user-inputted level, a “Crash Short” signal is generated. What is the customized momentum indicator? The customized momentum indicator is the RoCR (Rate of Change Ratio). Instead of classic ROC, which is close - close , the RoCR divides the current close by a previous close. This formula creates a ratio that is more normalized than a simple price difference. This ratio is used to determine upside/downside momentum, with values greater than 1 indicating bullish momentum and values less than 1 indicating bearish momentum. The RoCR looks for deviating values to the downside (less than 1) to identify strong selling. From there, once the RSI crosses over an optimized level (such as 35), the indicator will print a sell signal titled "Crash Short". Predictive Countertrend Channels Our Predictive Countertrend Channel applies a two-stage recursive filter to smooth data using exponential decay and periodic adjustments for trend extraction. Our counter trend channels aren't directly used for signal processing; however, these channels provide useful visual cues for extended market moves. Instructions for Optimization Step 1: Optimize Mxwll OptAlgo Begin by optimizing the M-Swift and M-Smooth averages for better signal accuracy. This step simply finds better performing M-Swift and M-Smooth lookbacks. Again, if the strategy is unprofitable you will be notified and from there decide not to use the strategy. Step 2: Optimize Mxwll RSI Refine the Mxwll RSI settings to explore potential adjustments in smoothness and signal output. This step aims to evaluate whether these adjustments could improve the accuracy of the signals generated by Mxwll OptAlgo, while being mindful of any potential impacts. Step 3: Optimize TP/SL Consider adjusting the Take Profit and Stop Loss settings to potentially manage risk. Step 4: Optimize Bars Between Trades Set the number of bars between trades to regulate the frequency of trade executions. This adjustment may help in reducing the risk of overtrading and support a more disciplined trading strategy. Step 5: Optimize Trade Flip Adjust the trade flip parameters to potentially improve the management of transitions between long and short positions. This adjustment is intended to help achieve smoother trade executions, though outcomes may vary. Step 6: Optimize RSI OB/OB Levels Consider adjusting the overbought (OB) and oversold (OS) RSI levels to explore potential improvements in signal sensitivity. Careful calibration of these levels may help refine the accuracy of trend reversal signals, although results may depend on market conditions. Finished! From this point, consider setting alerts to make the most of the Mxwll Opt Algo's potential accuracy. The effectiveness of the Opt Algo signal output can be evaluated using the "PF" table, which indicates the profit factor score for the strategy. A profit factor (PF) of less than or equal to 1 suggests that the strategy may not be profitable. Disclaimer No strategy works on any timeframe on any asset, so, if the Opt Algo underperforms for the asset/timeframe you're analyzing, the Opt Algo PF table lets you know it hasn't been generating accurate signals, in which case you can decide not to use it! Optimization Disclaimer Optimization can be tricky. It's helpful to test numerous strategies in aggregate to see if a strategy has potential. Despite this, optimization can cause overfitting. Overfitting occurs when a strategy is too closely fit to the data it's trading. Overfit backtests are deceptively phenomenal. While the historical performance looks great, the future expectancy of the strategy remains unpredictable - an overfit strategy will profit from periods of random price movement which, being random, are irreproducible and cannot be profited from other than their initial occurrence. When a strategy trades random price movement profitably, any and all profit earned can be reduced to chance. Keep this in mind when using the in-built optimization system. Optimization should be kept to a minimum, a tool to point you in the right direction, whether confirming potential or signifying a useless system.
Pine Script™ indicator
by MXWLL-Capital-Trading
2
Advanced Keltner Channel/Oscillator [MyTradingCoder]This indicator combines a traditional Keltner Channel overlay with an oscillator, providing a comprehensive view of price action, trend, and momentum. The core of this indicator is its advanced ATR calculation, which uses statistical methods to provide a more robust measure of volatility. Starting with the overlay component, the center line is created using a biquad low-pass filter applied to the chosen price source. This provides a smoother representation of price than a simple moving average. The upper and lower channel lines are then calculated using the statistically derived ATR, with an additional set of mid-lines between the center and outer lines. This creates a more nuanced view of price action within the channel. The color coding of the center line provides an immediate visual cue of the current price momentum. As the price moves up relative to the ATR, the line shifts towards the bullish color, and vice versa for downward moves. This color gradient allows for quick assessment of the current market sentiment. The oscillator component transforms the channel into a different perspective. It takes the price's position within the channel and maps it to either a normalized -100 to +100 scale or displays it in price units, depending on your settings. This oscillator essentially shows where the current price is in relation to the channel boundaries. The oscillator includes two key lines: the main oscillator line and a signal line. The main line represents the current position within the channel, smoothed by an exponential moving average (EMA). The signal line is a further smoothed version of the oscillator line. The interaction between these two lines can provide trading signals, similar to how MACD is often used. When the oscillator line crosses above the signal line, it might indicate bullish momentum, especially if this occurs in the lower half of the oscillator range. Conversely, the oscillator line crossing below the signal line could signal bearish momentum, particularly if it happens in the upper half of the range. The oscillator's position relative to its own range is also informative. Values near the top of the range (close to 100 if normalized) suggest that price is near the upper Keltner Channel band, indicating potential overbought conditions. Values near the bottom of the range (close to -100 if normalized) suggest proximity to the lower band, potentially indicating oversold conditions. One of the strengths of this indicator is how the overlay and oscillator work together. For example, if the price is touching the upper band on the overlay, you'd see the oscillator at or near its maximum value. This confluence of signals can provide stronger evidence of overbought conditions. Similarly, the oscillator hitting extremes can draw your attention to price action at the channel boundaries on the overlay. The mid-lines on both the overlay and oscillator provide additional nuance. On the overlay, price action between the mid-line and outer line might suggest strong but not extreme momentum. On the oscillator, this would correspond to readings in the outer quartiles of the range. The customizable visual settings allow you to adjust the indicator to your preferences. The glow effects and color coding can make it easier to quickly interpret the current market conditions at a glance. Overlay Component: The overlay displays Keltner Channel bands dynamically adapting to market conditions, providing clear visual cues for potential trend reversals, breakouts, and overbought/oversold zones. The center line is a biquad low-pass filter applied to the chosen price source. Upper and lower channel lines are calculated using a statistically derived ATR. Includes mid-lines between the center and outer channel lines. Color-coded based on price movement relative to the ATR. Oscillator Component: The oscillator component complements the overlay, highlighting momentum and potential turning points. Normalized values make it easy to compare across different assets and timeframes. Signal line crossovers generate potential buy/sell signals. Advanced ATR Calculation: Uses a unique method to compute ATR, incorporating concepts like root mean square (RMS) and z-score clamping. Provides both an average and mode-based ATR value. Customizable Visual Settings: Adjustable colors for bullish and bearish moves, oscillator lines, and channel components. Options for line width, transparency, and glow effects. Ability to display overlay, oscillator, or both simultaneously. Flexible Parameters: Customizable inputs for channel width multiplier, ATR period, smoothing factors, and oscillator settings. Adjustable Q factor for the biquad filter. Key Advantages: Advanced ATR Calculation: Utilizes a statistical method to generate ATR, ensuring greater responsiveness and accuracy in volatile markets. Overlay and Oscillator: Provides a comprehensive view of price action, combining trend and momentum analysis. Customizable: Adjust settings to fine-tune the indicator to your specific needs and trading style. Visually Appealing: Clear and concise design for easy interpretation. The ATR (Average True Range) in this indicator is derived using a sophisticated statistical method that differs from the traditional ATR calculation. It begins by calculating the True Range (TR) as the difference between the high and low of each bar. Instead of a simple moving average, it computes the Root Mean Square (RMS) of the TR over the specified period, giving more weight to larger price movements. The indicator then calculates a Z-score by dividing the TR by the RMS, which standardizes the TR relative to recent volatility. This Z-score is clamped to a maximum value (10 in this case) to prevent extreme outliers from skewing the results, and then rounded to a specified number of decimal places (2 in this script). These rounded Z-scores are collected in an array, keeping track of how many times each value occurs. From this array, two key values are derived: the mode, which is the most frequently occurring Z-score, and the average, which is the weighted average of all Z-scores. These values are then scaled back to price units by multiplying by the RMS. Now, let's examine how these values are used in the indicator. For the Keltner Channel lines, the mid lines (top and bottom) use the mode of the ATR, representing the most common volatility state. The max lines (top and bottom) use the average of the ATR, incorporating all volatility states, including less common but larger moves. By using the mode for the mid lines and the average for the max lines, the indicator provides a nuanced view of volatility. The mid lines represent the "typical" market state, while the max lines account for less frequent but significant price movements. For the color coding of the center line, the mode of the ATR is used to normalize the price movement. The script calculates the difference between the current price and the price 'degree' bars ago (default is 2), and then divides this difference by the mode of the ATR. The resulting value is passed through an arctangent function and scaled to a 0-1 range. This scaled value is used to create a color gradient between the bearish and bullish colors. Using the mode of the ATR for this color coding ensures that the color changes are based on the most typical volatility state of the market. This means that the color will change more quickly in low volatility environments and more slowly in high volatility environments, providing a consistent visual representation of price momentum relative to current market conditions. Using a good IIR (Infinite Impulse Response) low-pass filter, such as the biquad filter implemented in this indicator, offers significant advantages over simpler moving averages like the EMA (Exponential Moving Average) or other basic moving averages. At its core, an EMA is indeed a simple, single-pole IIR filter, but it has limitations in terms of its frequency response and phase delay characteristics. The biquad filter, on the other hand, is a two-pole, two-zero filter that provides superior control over the frequency response curve. This allows for a much sharper cutoff between the passband and stopband, meaning it can more effectively separate the signal (in this case, the underlying price trend) from the noise (short-term price fluctuations). The improved frequency response of a well-designed biquad filter means it can achieve a better balance between smoothness and responsiveness. While an EMA might need a longer period to sufficiently smooth out price noise, potentially leading to more lag, a biquad filter can achieve similar or better smoothing with less lag. This is crucial in financial markets where timely information is vital for making trading decisions. Moreover, the biquad filter allows for independent control of the cutoff frequency and the Q factor. The Q factor, in particular, is a powerful parameter that affects the filter's resonance at the cutoff frequency. By adjusting the Q factor, users can fine-tune the filter's behavior to suit different market conditions or trading styles. This level of control is simply not available with basic moving averages. Another advantage of the biquad filter is its superior phase response. In the context of financial data, this translates to more consistent lag across different frequency components of the price action. This can lead to more reliable signals, especially when it comes to identifying trend changes or price reversals. The computational efficiency of biquad filters is also worth noting. Despite their more complex mathematical foundation, biquad filters can be implemented very efficiently, often requiring only a few operations per sample. This makes them suitable for real-time applications and high-frequency trading scenarios. Furthermore, the use of a more sophisticated filter like the biquad can help in reducing false signals. The improved noise rejection capabilities mean that minor price fluctuations are less likely to cause unnecessary crossovers or indicator movements, potentially leading to fewer false breakouts or reversal signals. In the specific context of a Keltner Channel, using a biquad filter for the center line can provide a more stable and reliable basis for the entire indicator. It can help in better defining the overall trend, which is crucial since the Keltner Channel is often used for trend-following strategies. The smoother, yet more responsive center line can lead to more accurate channel boundaries, potentially improving the reliability of overbought/oversold signals and breakout indications. In conclusion, this advanced Keltner Channel indicator represents a significant evolution in technical analysis tools, combining the power of traditional Keltner Channels with modern statistical methods and signal processing techniques. By integrating a sophisticated ATR calculation, a biquad low-pass filter, and a complementary oscillator component, this indicator offers traders a comprehensive and nuanced view of market dynamics. The indicator's strength lies in its ability to adapt to varying market conditions, providing clear visual cues for trend identification, momentum assessment, and potential reversal points. The use of statistically derived ATR values for channel construction and the implementation of a biquad filter for the center line result in a more responsive and accurate representation of price action compared to traditional methods. Furthermore, the dual nature of this indicator – functioning as both an overlay and an oscillator – allows traders to simultaneously analyze price trends and momentum from different perspectives. This multifaceted approach can lead to more informed decision-making and potentially more reliable trading signals. The high degree of customization available in the indicator's settings enables traders to fine-tune its performance to suit their specific trading styles and market preferences. From adjustable visual elements to flexible parameter inputs, users can optimize the indicator for various trading scenarios and time frames. Ultimately, while no indicator can predict market movements with certainty, this advanced Keltner Channel provides traders with a powerful tool for market analysis. By offering a more sophisticated approach to measuring volatility, trend, and momentum, it equips traders with valuable insights to navigate the complex world of financial markets. As with any trading tool, it should be used in conjunction with other forms of analysis and within a well-defined risk management framework to maximize its potential benefits.
Pine Script™ indicator
by MyTradingCoder
Arjo FVG Filtering With Alerts [neo.|]Fair Value Gaps (Also known as FVGs or Imbalances) can be simply described as a three candle pattern, where the second candle's body isn't completely covered by the wicks or body of the second and third candle. These areas represent movements in the market where either buyers or sellers were not able to get involved due to price in the form of wicks not revisiting those levels, and instead moving away from them. As a result, they can be seen as potential areas of continuation given that price may want to continue in it's direction after it revisits them and offers Fair Value, since previously it made sharp moves away from those areas. However what is important to note, and what FVG Filtering aims to address, is that there are three notable types of FVGs as described by Arjo, which are Perfect FVGs denoted as FVGp on the indicator and chart below, Expansion (FVGe), and Reversal (FVGr). As the names imply, they each serve different purposes with the FVGp being the likeliest to hold on mitigation, expansion meaning price is likely to not retrace into the FVG and reversal being the least likely for the FVG to hold. The indicator is the first that automatically determines which one of the three underlying FVG types any particular FVG is, that way you can quickly make informed decisions based on the type of FVG you see appear on the chart. As you may notice, the type depends primarily on the third candle, which demonstrates the true strength of any particular FVG, and is how the filtering occurs on this indicator, which compares the sizes of the second and third candle's bodies, in order to classify the FVG candle sequence as one of the three aforementioned types. Color Options: FVG Colors: Change the color of any bullish or bearish FVG type to easily distinguish between them. Mitigated FVG Color: Apply colors to mitigated FVGs in order to avoid using ones that are no longer valid. Text Color: Change the color of the text within the FVG to your liking. Further styling options: How many FVGs you want to be displayed: Changes the amount of FVGs displayed on your chart by limiting each type of FVG to the number you select. How far you want the FVGs to extend: Modify the amount of bars forward that the FVG stretches out after it's inception. Table options: Show table: Display a table that will give you insights on how many FVGs were created of each type and what % they represent of the total. Table text color: Modify the color of the text within the table. Table border color: Modify the color of the border of the table. Alerts: Freely set alerts for any type of FVG you would like to see.
Pine Script™ indicator
by neommxm
6
Indian Markets Dashboard The Mobile Dashboard indicator provides a compact and customizable table on your TradingView chart, summarizing key data for up to six selected financial instruments. It displays the close price, previous day high (PDH), previous day low (PDL), and SuperTrend direction (Bull/Bear). The table's position, size, and transparency can be adjusted to suit your preferences, making it a convenient tool for quickly monitoring multiple assets on the go. Ideal for traders who need a clear and concise overview of market conditions directly on their chart. - TraderVK
Pine Script™ indicator
by TheBoTrader
Vmoon Trend TableVmoon Trend Table Indicator The **Vmoon Trend Table Indicator** is a powerful tool designed for traders who want to track trends across multiple timeframes and identify key pivot points that signal trend changes. This indicator provides a visual representation of trends in different timeframes through a convenient table, which can be positioned either at the top or bottom of the chart. It is particularly useful for those who prefer trading with the trend and need to monitor higher timeframes for stronger signals. #### Key Features: 1. **Multi-Timeframe Trend Detection**: - The indicator analyzes up to four different timeframes simultaneously, allowing traders to observe trends from shorter to longer timeframes. - The user can select which timeframes to monitor, making it adaptable to various trading strategies. 2. **Pivot Point Analysis**: - The Vmoon Trend Table identifies trends based on pivot points, which are defined by higher highs and higher lows for uptrends, and lower highs and lower lows for downtrends. - Users can customize the lookback period to define these pivot points, offering control over the sensitivity of trend detection. - A choice between using the high/low or close price for pivot calculations is available, allowing further customization. 3. **Visual Representation**: - The indicator provides a table showing the current trend direction (uptrend or downtrend) for each selected timeframe. - Trends are visually indicated by up or down arrows, colored appropriately to represent bullish or bearish trends. - The table can be positioned at the top or bottom of the chart, based on user preference. 4. **Support and Resistance Levels**: - The indicator can display support and resistance lines based on the most recent swing high/low points for each timeframe. - These lines help traders visualize critical levels where trends might change, enabling better decision-making. 5. **Historical Pivot Points**: - Users can toggle the visibility of historical pivot points on the chart, aiding in the evaluation of trend consistency and the placement of these points. 6. **Optimized Performance**: - The script is optimized to reduce the number of security calls, ensuring it runs efficiently even when tracking multiple timeframes. - Revisions have focused on improving speed and allowing users to reposition the information table according to their needs. #### How to Use: 1. **Set Timeframes**: Choose the timeframes that you want to monitor for trends. The indicator supports up to four different timeframes. 2. **Define Pivot Points**: Adjust the lookback period to define how pivot points (highs/lows) are calculated. Select whether to use high/low or close prices for this calculation. 3. **Monitor the Trend Table**: Observe the trend direction indicated in the table. Use this information to confirm the overall trend before making trading decisions. 4. **Watch Support/Resistance Levels**: If enabled, use the support and resistance levels drawn from higher timeframe pivots to anticipate potential trend reversals. 5. **Fine-Tune Settings**: Customize the indicator's display, such as repositioning the trend table, adjusting line widths, or changing colors, to fit your trading style.
Pine Script™ indicator
by CEOvasma
Qty CalculatorThis Pine Script indicator, titled "Qty Calculator," is a customizable tool designed to assist traders in managing their trades by calculating key metrics related to risk management. It takes into account your total capital, entry price, stop-loss level, and desired risk percentage to provide a comprehensive overview of potential trade outcomes. Key Features: User Inputs: Total Capital: The total amount of money available for trading. Entry Price: The price at which the trader enters the trade. Stop Loss: The price level at which the trade will automatically close to prevent further losses. Risk Percentage: The percentage of the total capital that the trader is willing to risk on a single trade. Customizable Table: Position: The indicator allows you to choose the position of the table on the chart, with options including top-left, top-center, top-right, bottom-left, bottom-center, and bottom-right. Size: You can adjust the number of rows and columns in the table to fit your needs. Risk Management Calculations: Difference Calculation: The difference between the entry price and the stop-loss level. Risk Per Trade: Calculated as a percentage of your total capital. Risk Levels: The indicator evaluates multiple risk levels (0.10%, 0.25%, 0.50%, 1.00%) and calculates the quantity, capital per trade, percentage of total capital, and the risk amount associated with each level. R-Multiples Calculation: The indicator calculates potential profit levels at 2x, 3x, 4x, and 5x the risk (R-Multiples), showing the potential gains if the trade moves in your favor by these multiples. Table Display: The table includes the following columns: CapRisk%: Displays the risk percentage. Qty: The quantity of the asset you should trade. Cap/Trade: The capital allocated per trade. %OfCapital: The percentage of total capital used in the trade. Risk Amount: The monetary risk taken on each trade. R Gains: Displays potential gains at different R-Multiples. This indicator is particularly useful for traders who prioritize risk management and want to ensure that their trades are aligned with their capital and risk tolerance. By providing a clear and customizable table of critical metrics, it helps traders make informed decisions and better manage their trading strategies.
Pine Script™ indicator
by gagandas
Thrax - QuickStrike 5-Mins Scalping** Indicator Description ** 1. Price Change Threshold (%) – The minimum price change required for a candle to be recognized as significant. Candles exceeding this threshold are considered potential candidates for zone creation. Default value for 5 min is 0.5%. As you move on higher timeframe the threshold should increase 2. Percentage Change for Zones (%) – The amount of price movement needed to form a dynamic support or resistance zone. Tweak this to control how sensitive the indicator is to price fluctuations. 5 min default value is 1%. For 15 min suggested is 2-3%. 3. Break Threshold for Zones (%) – Defines how much price must break above or below a zone for it to be removed from the chart/mitigated. Keeps the chart clean by removing invalidated zones. Default value is 0.1% in 5 min, for 15 min it is 0.5%. 4. Buy Zone Retracement Level (%) – The percentage retracement level for defining the inner buy zone within a broader bullish zone. Ideal for timing precision entries. Ideal value is 75% 5. Sell Zone Retracement Level (%) – The percentage retracement level used to determine the inner sell zone within a larger bearish zone. Helps in identifying potential reversal areas or exits. Ideal value is 25% By tailoring these inputs, traders can fully customize the indicator to suit their scalping strategies, enhancing their ability to navigate fast-moving markets with confidence. --------------------------------------------------------------------------- There are two primary approaches for scalping using this indicator: 1. Candle-Based Scalping: a. Bullish Signal: When you observe a bullish candle highlighted in blue (by default), you can consider entering a long position at the close of this candle. It’s advisable to wait for the candle to close before taking action. For a more aggressive scalp, you might take profits based on your scalp target after a few subsequent candles. If the price remains stagnant or moves unfavorably in the next few candles, you can exit with a small loss. Alternatively, if you have a higher risk tolerance, you may hold the position even if the price initially declines within a set percentage. b. Bearish Signal: For a bearish candle highlighted in yellow, you can enter a short trade at the close of the candle. Similar to the bullish setup, you have the option to exit after a few candles if the price doesn’t move as expected or hold the position with a higher risk tolerance if the price goes up initially. 2. Zone-Based Scalping: Entering Zones: Monitor the price as it enters a defined support or resistance zone. If you are open to higher risk, you can enter a trade immediately upon the price entering the zone. For a more cautious approach with a smaller stop loss, wait for the price to reach a retracement level within the zone before initiating your trade. This approach allows for a more precise entry but may result in missing out on trades if the price reverses before hitting the retracement level. Conversely, entering at the zone’s boundary offers the potential for early trade capture but comes with a higher stop loss risk. Adjust these strategies based on your risk tolerance and trading preferences to optimize your scalping opportunities.
Pine Script™ indicator
by thraxalgo
AutocorrelationWhat is Autocorrelation? Autocorrelation is a mathematical concept used to measure the degree of similarity between a given time series and a lagged version of itself over successive time intervals. Mathematically, it is the correlation of a signal with a delayed copy of itself as a function of delay. In simpler terms, autocorrelation helps us understand whether and how past values in a time series are related to future values. Autocorrelation in Finance: In finance, the autocorrelation is a tool used to analyze the behavior of time series data, such as asset prices or returns. It can reveal "patterns", trends, or cycles within the data. Price Autocorrelation: When applied to prices, autocorrelations can indicate whether an asset price tends to follow a trend. On price you will typically observe positive autocorrelation because price often exhibits a momentum effect where today's price is positively correlated with past prices. As a result, when prices are trending, they tend to continue in the same direction, creating a positive autocorrelation. Returns Autocorrelation: Returns on the other hand, generally show less autocorrelation than prices. This is because returns represent the change in prices over time, and in efficient markets, returns are often modeled as a random walk, leading to low or no significant autocorrelation. However, under certain market conditions, you may observe positive or negative autocorrelation in returns. Positive Autocorrelation of returns indicates a trend effect, where past returns can predict future returns. Negative Returns Autocorrelation suggest mean reversion, where large positive returns are often followed by negative returns and vice versa. Critical Value Analysis: This indicator comes with critical values based on user-selected confidence levels (90%,95%,99%). It assesses whether the autocorrelation at a particular lag is statistically significant, which is crucial for distinguishing between random noise and meaningful events. Trading Based on Autocorrelation: While this indicator was not really developed to be directly used for trading, this indicator is was instead to raise awareness on why you should avoid strategies involving mean reversion on price.
Pine Script™ indicator
by Traders_Endeavors
Relationship Exchange Rate and Inflation in UruguayThis Pine Script indicator, titled "Relationship Between Exchange Rate and Monthly Inflation in Uruguay," is designed to analyze the interaction between the exchange rate of the Uruguayan Peso (UYU) against the US Dollar (USD) and the monthly inflation rate in Uruguay. Data Retrieval: The script fetches the monthly exchange rate data for UYU/USD. It also retrieves the Consumer Price Index (CPI) data for Uruguay. Monthly Inflation Calculation: The script calculates the monthly inflation rate using the CPI data by determining the percentage change from the previous month. Formula Calculation: A specific formula is calculated by dividing the inverse of the exchange rate by the monthly inflation rate. Conditional Coloring: The resulting value is plotted on the chart with a conditional color: green if the exchange rate is greater than the inflation rate, otherwise red. This indicator provides a visual representation of how the exchange rate compares to the inflation rate, helping traders and analysts understand the economic dynamics between currency value and inflation in Uruguay.
Pine Script™ indicator
by free4fun